Gluck, M.A., Mercado, E., & Myers, C.E. (2016). Learning and Memory: From Brain to Behavior. 3rd edition. New York: Worth
Gluck, M.A., Mercado, E., & Myers, C.E. (2014). Learning and Memory: From Brain to Behavior. 2nd edition. New York: Worth
Gluck, M.A., Mercado, E., & Myers, C.E. (2008). Learning and Memory: From Brain to Behavior. 1st edition. New York: Worth
Spanish translation: Aprendizaje y memoria (2009). Mexico: McGraw Hill Interamericana Editores, S.A. DE C.V.
Korean translation: 학습과 기억: 뇌에서 행동까지. (2011). Sigma Press, Inc.
German translation: Lernen und Gedächtnis (2010). Heidelberg: Spektrum Akademischer Verlag.
Gluck, M.A. & Myers, C.E. (2001). Gateway to Memory: An Introduction to Neural Network Models of the Hippocampus and Learning. Cambridge, MA: MIT Press.
BOOKS & JOURNAL ISSUES: EDITED
Gluck, M. A., Kosslyn, S. M., & Anderson, J. (2008) Memory
and Mind: A Festschrift for Gordon H. Bower. New York: Taylor
Gluck, M. A., Poldrack, R. A., & Keri, S. (2008). The Cognitive
Neuroscience of Category Learning (Special issue of Neuroscience
and Biobehavioral Reviews, Guest Editors). 32. 2
Gluck, M. A. & Myers, C. E. (2001). Gateway to Memory: An
Introduction to Neural Network Models of the Hippocampus and Learning.
Cambridge, MA: MIT Press.
Steinmetz, J., Gluck, M., & Solomon, P. (2001). Model Systems
and the Neurobiology of Associative Learning: A Festshrift for Richard
F. Thompson, Mahwah, NJ: Lawrence Erlbaum Associates.
Gluck, M. A., (1996), Hippocampal Computation and Memory
(Special issue of Hippocampus, Guest Editor). 6(6). J. Wiley &
Gluck, M. A. & Rumelhart, D. E., (1990). Neuroscience and
Connectionist Theory, Hillsdale, N.J. Lawrence Erlbaum Associates.
Gluck, M.A., (1990). Neural Networks for Defense Applications.
San Francisco: Miller-Freeman Publications.
REFEREED JOURNAL PUBLICATIONS
Schuck, N.W., Petok, J.R., Meeter, M., Schjeide, B.M., Schröder, J., Bertram, L., Gluck, M. A., Li, S. (2018). Aging and a genetic KIBRA polymorphism interactively affect feedback-and observation-based probabilistic classification learning. Neurobiology of Aging. 61. 36-43.
We tested whether age-related behavioral differences in probabilistic category learning from feedback or observation depend on a genetic factor known to influence individual differences in hippocampal function, the KIBRA gene (single nucleotide polymorphism rs17070145). Results showed comparable age-related performance impairments in observational as well as feedback-based learning. Moreover, genetic analyses indicated an age-related interactive effect of KIBRA on learning: among older adults, the beneficial T-allele was positively associated with learning from feedback, but negatively with learning from observation. In younger adults, no effects of KIBRA were found. Our results add behavioral genetic evidence to emerging data showing age-related differences in how neural resources relate to memory functions, namely that hippocampal and striatal contributions to probabilistic category learning may vary with age.
Lerner, I., Lupkin, S., Sinha, N., Tsai, A., & Gluck, M.A. (2017). Baseline Levels of Rapid-eye-Movement Sleep May Protect Against Excessive Activity in Fear-Related Neural Circuits. Journal of Neuroscience
In the current study, we used long-term mobile sleep monitoring and functional neuroimaging (fMRI) to explore whether trait-like variations in sleep patterns, measured in advance in both male and female participants, predict subsequent patterns of neural activity during fear learning. Our results indicate that higher baseline levels of REM sleep predict reduced fear-related activity in, and connectivity between, the hippocampus, amygdala and ventromedial PFC during conditioning. Additionally, skin conductance responses (SCRs) were weakly correlated to the activity in the amygdala. Conversely, there was no direct correlation between REM sleep and SCRs, indicating that REM may only modulate fear acquisition indirectly. In a follow-up experiment, we show that these results are replicable, though to a lesser extent, when measuring sleep over a single night just before conditioning. As such, baseline sleep parameters may be able to serve as biomarkers for resilience, or lack thereof, to trauma.
Motor-symptom Laterality Affects Acquisition in Parkinson’s disease: a Cognitive and fMRI study Pei Huang, M.D.1*, Yu-Yan Tan, M.D., Ph.D.1*, Dong-Qiang Liu, Ph.D.25 , Mohammad
M. Herzallah, M.D., Ph.D.3, 4, Elizabeth Lapidow, B.A.3, Ying Wang M.D.16 , Yu-Feng Zang, M.D.5, Mark Gluck, Ph.D.3§, Sheng-Di Chen, M.D., Ph.D.7 1§
Herzallah, M.M., Khdour, H.Y., Taha, A.B., Elmashala, A.M., Mousa, H.N., Taha,M.B., Ghanim, Z., Sehwail, M.M., Misk, A.J., Balsdon, T., Moustafa, A.A., Myers, C.E., Gluck, M.A. (2017) Depression Reduces Accuracy While Parkinsonism Slows Response Time for Processing Positive Feedback in Patients with Parkinson’s Disease with Comorbid Major Depressive Disorder Tested on a Probabilistic Category-Learning Task. Frontiers in Psychiatry. 8(84). https://doi.org/10.3389/fpsyt.2017.00084
Using a computerbased cognitive task that dissociates learning from positive and negative feedback, we tested four groups of subjects: (1) patients with PD who have MDD, (2) patients with PD without MDD, (3) matched patients with MDD alone (without PD), and (4) matched healthy control subjects. Furthermore, we used a mathematical model of decision making to fit both choice and response time data, allowing us to detect and characterize differences between the groups that are not revealed by cognitive results. Our results suggest that PD patients with MDD exhibit cognitive profiles with mixed traits characteristic of both MDD and PD, furthering our understanding of both PD and MDD and their often-complex comorbidity. To the best of our knowledge, this is the first study to examine feedback-based learning in PD with MDD while controlling for the effects of PD and MDD.
Montgomery K.S., Edwards G. 3rd, Levites Y., Kumar A., Myers C.E., Gluck M.A., Setlow B., Bizon J.L. (2015). Deficits in hippocampal-dependent transfer generalization learning accompany synaptic dysfunction in a mouse model of amyloidosis. Frontiers Hippocampus. 2015 Sep 29. Doi: 10.1002/hippo.22535.
Elevated ß-amyloid and impaired synaptic function in hippocampus are among the earliest manifestations of Alzheimer's disease (AD). The current studies employed a mouse analog of an associative "transfer learning" task that has previously been used to identify risk for prodromal AD in humans. The rodent version of the task assesses the transfer of learning about stimulus features relevant to a food reward across a series of compound discrimination problems. The relevant feature that predicts the food reward is unchanged across problems, but an irrelevant feature (i.e., the context) is altered. Across three experiments, our data show that the ability to generalize learned associations to new contexts is disrupted even in the presence of subtle hippocampal dysfunction and suggest that, across species, this aspect of hippocampal-dependent learning may be useful for early identification of AD-like pathology.
Lerner, I., Lupkin, S., Peters, S., Corter, J., Peters, S., Cannella, L., & Gluck, M.A. (2016). The influence of sleep on emotional and cognitive processing is primarily trait- (but not state-) dependent. Neurobiology of Learning and Memory. 134, 275-286.
Human studies of sleep and cognition have established that different sleep stages contribute to distinct
aspects of cognitive and emotional processing. However, since the majority of these findings are based
on single-night studies, it is difficult to determine whether such effects arise due to individual,
between-subject differences in sleep patterns, or from within-subject variations in sleep over time. In
the current study, we investigated the longitudinal relationship between sleep patterns and cognitive
performance by monitoring both in parallel, daily, for a week. Using two cognitive tasks – one assessing
emotional reactivity to facial expressions and the other evaluating learning abilities in a probabilistic categorization
task – we found that between-subject differences in the average time spent in particular
sleep stages predicted performance in these tasks far more than within-subject daily variations.
Specifically, the typical time individuals spent in Rapid-Eye Movement (REM) sleep and Slow-Wave
Sleep (SWS) was correlated to their characteristic measures of emotional reactivity, whereas the typical
time spent in SWS and non-REM stages 1 and 2 was correlated to their success in category learning. These
effects were maintained even when sleep properties were based on baseline measures taken prior to the
experimental week. In contrast, within-subject daily variations in sleep patterns only contributed to
overnight difference in one particular measure of emotional reactivity. Thus, we conclude that the effects
of natural sleep on emotional cognition and category learning are more trait-dependent than statedependent,
and suggest ways to reconcile these results with previous findings in the literature.
2016 Elsevier Inc. All rights reserved.
O'Connell, G., Myers, C.E., Hopkins, R.O., McLaren, R.P., Gluck, M.A., &
Wills, A.J. (2016, July 21). Amnesic patients show superior generalization
in category learning. Neuropsychology. .
Questions remain about the precise role of the hippocampus in this facet of learning, but a connectionist model by Gluck and Myers (1993) predicts that generalization should be enhanced following hippocampal damage. In a two-category learning task, a group of amnesic patients (n=9) learned the training items to a similar level of accuracy as matched controls (n=9). Both groups then classified new items at various levels of distortion. The amnesic group showed significantly more accurate generalization to high distortion novel items, a difference also present when compared to a larger group of unmatched controls (n=33). The model prediction of a broadening of generalization gradients in amnesia, at least for items near category boundaries, was supported by the results. Our study shows for the first time that amnesia can sometimes improve generalization.
Khdour, H.Y., Imam, A.F., Mughrabi, I.T., Myers, C.E., Gluck, M.A., Herzallah, M.M., &
Moustafa, A.A. (2016/in press). Generalized anxiety disorder and social anxiety disorder, but not panic anxiety disorder, are associated with higher sensitivity to learning from negative feedback: behavioral and computational investigation. Frontiers in Behavioral Neuroscience.
Anxiety spectrum disorders, including generalized anxiety disorder (GAD), social anxiety disorder (SAD) and panic anxiety disorder (PAD), are a group of common psychiatric conditions. In this study, we tested the cognitive correlates of medication-free patients with GAD, SAD, and PAD, along with matched healthy participants, using a probabilistic category-learning task that allows the dissociation between positive and negative feedback learning. We also fitted all participants’ data to an actor-critic model that examines learning rate parameters from positive and negative feedback to investigate effects of valence vs. action on performance. SAD and GAD patients were more sensitive to negative feedback than either PAD patients or healthy participants. PAD, SAD and GAD patients did not differ in positive-feedback learning compared to healthy participants. Computational analysis revealed that participants’ behavioral results are better explained by the critic’s learning from negative feedback variable. These findings argue that (a) not all anxiety spectrum disorders share the same cognitive correlates, but are rather different in ways that do not link them to the hallmark of anxiety (higher sensitivity to negative feedback); and (b) perception of negative consequences is the core feature of GAD and SAD, but not PAD.
Singh N., Sharpley A. L., Emir U. E., Masaki C., Herzallah M. M., Gluck M. A., Sharp T., Harmer C. J., Vasudevan S. R., Cowen P., Churchill G. C. (2016). Effect of the putative lithium mimetic ebselen on brain myo-inositol, sleep and emotional processing in humans. Neuropsychopharmacology. June; 41(7). 1768-78.
Lithium remains the gold standard in treating bipolar disorder but has unwanted toxicity and side effects. We previously reported that ebselen inhibits inositol monophosphatase (IMPase) and exhibits lithium-like effects in animal models through lowering of inositol. Ebselen has been tested in clinical trials for other disorders, enabling us to determine for the first time the effect of a blood-brain barrier penetrant IMPase inhibitor on human central nervous system (CNS) function. We now report that in a double-blind, placebo-controlled trial with healthy participants, acute oral ebselen reduced brain myo-inositol in the anterior cingulate cortex, consistent with CNS target engagement. Ebselen decreased slow-wave sleep and affected emotional processing by increasing recognition of some emotions, decreasing latency time in the acoustic startle paradigm and decreasing the reinforcement of rewarding stimuli. In summary, ebselen affects the phosphoinositide cycle and has CNS effects on surrogate markers that may be relevant to the treatment of bipolar disorder, which can be tested in future clinical trials.
Moustafa, A. A., Gluck, M. A., Herzallah, M. M. & Myers, C. E. (2015). The influence of trial order on learning from reward vs. punishment in a probabilistic categorization task: experimental and computational analyses. Frontiers in Behavioral Neuroscience, 9:153.
Previous research has shown that trial ordering affects cognitive performance, but this has not been tested using category-learning tasks that differentiate learning from reward and punishment. Here, we tested two groups of healthy young adults using a probabilistic category learning task of reward and punishment in which there are two types of trials (reward, punishment) and three possible outcomes: (1) positive feedback for correct responses in reward trials; (2) negative feedback for incorrect responses in punishment trials; and (3) no feedback for incorrect answers in reward trials and correct answers in punishment trials. We found that early training on reward-based trials led to omission of reward being treated as similar to punishment, but prior training on punishment-based trials led to omission of reward being treated more neutrally. This suggests that early training on one type of trials, specifically reward-based trials, can create a bias in how neutral feedback is processed, relative to those receiving early punishment-based training or training that mixes positive and negative outcomes.
Tomer, R., Slagter, H. A., Christian, B. T., Fox, A. S., King, C. R., Murali, D., Gluck, M. A., & Davidson, R. J., (2014). Love to win or hate to lose? Asymmetry of dopamine D2 receptor binding predicts sensitivity to reward vs. punishment. Journal of Cognitive Neuroscience. In press.
Humans show consistent differences in the extent to which their behavior reflects a bias towards
appetitive approach-related behavior or avoidance of aversive stimuli (Elliot, 2008). We examined
the hypothesis that in healthy subjects this motivational bias (assessed by self-report and by a
probabilistic learning task that allows direct comparison of the relative sensitivity to reward and
punishment) reflects lateralization of dopamine signaling. Using [F-18]fallypride to measure D2/D3
binding , we found that self-reported motivational bias was predicted by the asymmetry of frontal D2
binding. Similarly, striatal and frontal asymmetries in D2 dopamine receptor binding, rather than
absolute binding levels, predicted individual differences in learning from reward vs. punishment.
These results suggest that normal variation in asymmetry of dopamine signaling may, in part,
underlie human personality and cognition.
Vadhan, N. P., Myers, C. E., Benedict, E., Rubin, E., Foltin, R. W., & Gluck, M. A. (2013,
November 4). A Decrement in Probabilistic Category Learning in Cocaine Users After
Controlling for Marijuana and Alcohol Use. Experimental and Clinical Psychopharmacology.
Advance online publication. doi: 10.1037/a0034506.
Aspects of stimulus-response (S-R) learning, mediated by striatal dopamine signaling, have been found to be
altered in cocaine users relative to healthy controls. However, the influence of cocaine users’ marijuana and
alcohol use has not been accounted for. This study evaluated S-R learning and other neurocognitive functions
in cocaine users while controlling for the relative influences of marijuana and alcohol use. Twenty-five
long-term cocaine users and 2 control groups (25 moderate marijuana and alcohol users and 23 healthy
controls) completed a computerized assessment of probabilistic category learning (the Weather Prediction
task), as well as measures of equivalence learning, declarative learning, and executive, attentional, and motor
function. Cocaine users exhibited decreased performance on the Weather Prediction task, as well as measures
of declarative learning, attention, and motor function (p0.05), relative to both control groups. Cocaine users
exhibited decrements in probabilistic category learning, declarative recall, and attentional and motor function,
compared with both marijuana and alcohol users and nondrug users. Therefore, these decrements appear to be
specifically related to the cocaine use, but not the moderate marijuana and alcohol use, of long-term cocaine
Herzallah, M. M., Moustafa, A. A., Natsheh, J. Y., Abdellatif, S. M, Taha, M. B., Tayem, Y. I., Sehwail, M. A., Amleh, I., Petrides, G., Myers, C. E, & Gluck, M. A. (2013/in press).
Learning from negative feedback in patients with major depressive disorder is attenuated by SSRI antidepressants. Frontiers in Integrative Neuroscience.
One barrier to interpreting past studies of cognition and Major Depressive Disorder (MDD) has been the
failure in many studies to adequately dissociate the effects of MDD from the potential cognitive side effects of
Selective Serotonin Reuptake Inhibitors (SSRI) use. To better understand how remediation of depressive symptoms affects
cognitive function in MDD, we evaluated three groups of subjects: medication - naďve patients with MDD, medicated patients
with MDD receiving the SSRI paroxetine and healthy control subjects. All were administered a category - learning task that
allows for dissociation between learning from positive feedback (reward) versus learning from negative feedback (punishment).
Healthy subjects learned significantly better from positive feedback than medication - naďve and medicated MDD groups,
whose learning accuracy did not differ significantly. In contrast, medicated patients with MDD learned significantly
less from negative feedback than medication - naďve patients with MDD and healthy subjects, whose learning accuracy
was comparable. A comparison of subject's relative sensitivity to positive versus negative feedback showed that both the
medicated MDD and healthy control groups conform to Kahneman and Tversky's (1979) Prospect Theory, which expects losses
(negative feedback) to loom psychologically slightly larger than gains (positive feedback). However,medicated MDD and
HC profiles are not similar, which indicates that the state of medicated MDD is not 'normal' when comparedto HC,
but rather balanced with less learning from both positive and negative feedback. On the other hand, medication - naďve
patients with MDD violate Prospect Theory by having significantly exaggerated learning from negative feedback.
This suggests that SSRI antidepressants impair learning from negative feedback, while having negligible effect
on learning from positive feedback. Overall, these findings shed light on the importance of dissociating the
cognitive consequences of MDD from those of SSRI treatment , and from cognitive evaluation of MDD subjects in a medication -
naďve state before the administration of antidepressants. Future research is needed to correlate the mood -
elevating effects and the cognitive balance between reward - and punishment - based learning related to SSRIs.
Herzallah, M. M., Moustafa, A. A., Natsheh, J. Y.,Danoun, O. A., Simon, J.R., Tayem, Y. I., Sehwail, M. A., Amleh, I., Bannoura, I., Petrides, G., Myers, E. E, & Gluck, M. A. (2013/in press).
Depression impairs learning, whereas the selective serotonin reuptake inhibitor, paroxetine, impairs generalization in patients with major depressive disorder. Journal of Affective Disorders.
To better understand how medication status and task demands affect cognition in major depressive
disorder (MDD), we evaluated medication-naďve patients with MDD, medicated patients with MDD
receiving the selective serotonin reuptake inhibitors (SSRI) paroxetine, and healthy controls. All three
groups were administered a computer-based cognitive task with two phases, an initial phase in which
a sequence is learned through reward-based feedback (which our prior studies suggest is striatal-
dependent), followed by a generalization phase that involves a change in the context where learned rules
are to be applied (which our prior studies suggest is hippocampal-region dependent). Medication-naďve
MDD patients were slow to learn the initial sequence but were normal on subsequent generalization of
that learning. In contrast, medicated patients learned the initial sequence normally, but were impaired at
the generalization phase. We argue that these data suggest (i) an MDD-related impairment in striatal-
dependent sequence learning which can be remediated by SSRIs and (ii) an SSRI-induced impairment in
hippocampal-dependent generalization of past learning to novel contexts, not otherwise seen in the
medication-naďve MDD group. Thus, SSRIs might have a beneficial effect on striatal function required for
sequence learning, but a detrimental effect on the hippocampus and other medial temporal lobe
structures is critical for generalization
Simon, J.R. & Gluck, M.A. (2013/ in press). Adult age differences in learning and generalization of reward-based associations. Psychology and Aging.
Feedback-based associative learning (e.g., acquiring new associations from positive or negative outcomes) and generalization
(e.g., applying past learning to new settings) are important cognitive skills that enable people to make economic decisions
or social judgments. This ability to acquire new skills based on feedback and transfer those experiences to predict positive
outcomes in novel situations is essential at all ages, but especially among older adults who must continually adapt to new people,
environments and technologies. Ample evidence from animal work, clinical research and computational modeling has demonstrated that
feedback-based associative learning is sensitive to basal ganglia dysfunction and generalization to medial temporal lobe dysfunction.
This dissociation is relevant because of recent evidence suggesting that healthy aging compromises the basal ganglia system earlier
than the medial temporal lobes. However, few studies have investigated how healthy aging influences these cognitive processes.
Here, we examined both feedback-based associative learning and generalization in younger, middle-aged and older adults using a computer-
ized acquired equivalence task. Results revealed a significant effect of age group on feedback-based associative learning, consistent
with evidence of persistent age-related declines in the basal ganglia. In contrast, generalization was spared in all but the oldest
adult group, likely reflecting preserved medial temporal lobe function until advanced old age. Our findings add behavioral evidence to
the emerging view that healthy aging affects the striatal system before the medial temporal lobes. Although further evidence is needed,
this finding may shed light on the possible time course of neural system dysfunction in healthy aging.
Moustafa, A. A., Wufong, E., Servatius, R. J., Pang, K. C., Gluck, M. A., & Myers, C. E. (2013).
Why trace and delay conditioning are sometimes (but not always) hippocampal dependent: A computational model. Brain Research. 1493: 48-67.
A recurrent-network model provides a unified account of the hippocampal region in mediating the representation of temporal information in classical
eyeblink conditioning. Much empirical research is consistent with a general conclusion that delay conditioning (in which the conditioned stimulus CS
and unconditioned stimulus US overlap and co-terminate) is independent of the hippocampal system, while trace conditioning (in which the CS terminates
before US onset) depends on the hippocampus. However, recent studies show that, under some circumstances, delay conditioning can be hippocampal-dependent
and trace conditioning can be spared following hippocampal lesion. Here, we present an extension of our prior trial-level models of hippocampal
function and stimulus representation (Gluck & Myers, 1993, 2001) that can explain these findings within a unified framework. Specifically,
the current model includes adaptive recurrent collateral connections that aid in the representation of intra-trial temporal information.
With this model, as in our prior models, we argue that the hippocampus is not specialized for conditioned response timing, but rather is a
general-purpose system that learns to predict the next state of all stimuli given the current state of variables encoded by activity in recurrent
collaterals. As such, the model correctly predicts that hippocampal involvement in classical conditioning should be critical not only when there
is an intervening trace interval, but also when there is a long delay between CS onset and US onset. Our model simulates empirical data from many
variants of classical conditioning, including delay and trace paradigms in which the length of the CS, the inter-stimulus interval, or the trace
interval is varied. Finally, we discuss model limitations, future directions, and several novel empirical predictions of this temporal processing
model of hippocampal function and learning.
Moustafa, A. A., Herzallah, M. M., & Gluck, M. A. (2013). Dissociating the cognitive effects of levodopa versus dopamine agonists in a neurocomputational model of learning in Parkinson's disease.
Neurodegenerative Disorders. 11:102-111 DOI: 10.1159/000341999
Background/Aims: Levodopa and dopamine agonists have different effects on the motor, cognitive, and
psychiatric aspects of Parkinson's disease (PD). Methods: Using a compu- tational model of basal ganglia (BG) and prefrontal cortex (PFC) dopamine,
we provide a theoretical synthesis of the dissociable effects of these dopaminergic medications on brain and cognition. Our model incorporates the
findings that levodopa is converted by dopamine cells into dopamine, and thus activates prefrontal and striatal D1 and D2 do- pamine receptors,
whereas antiparkinsonian dopamine ag- onists directly stimulate D2 receptors in the BG and PFC (although some have weak affinity to D1 receptors).
Results: In agreement with prior neuropsychological studies, our model explains how levodopa enhances, but dopamine agonists impair or have no effect on,
stimulus-response learning and working memory. Conclusion: Our model explains how le- vodopa and dopamine agonists have differential effects on motor and
cognitive processes in PD.
Sheynin, J. Shikari, S., Gluck, M. A., Moustafa, A. A., Servatius, R. J. & Myers, C. E. (2013). Enhanced avoidance learning in behaviorally inhibited young men
and women. Stress, 16(3), 289-299.
Behavioral inhibition (BI) is a temperamental tendency to avoid or withdraw from novel social and nonsocial situations, and
has been shown to predispose individuals to anxiety disorders. However, adequate means to assess individual differences in
avoidance learning in humans are presently limited. Here, we tested whether individuals with high self-reported BI show faster
associative learning on a purely cognitive task and whether such inhibited individuals are more prone to avoid aversive
outcomes. In Experiment 1, we tested 74 healthy undergraduate students on a computer-based probabilistic classification task, where participants were asked to classify four distinct visual stimuli into two
categories. Two stimuli were associated with reward (point gain) and two were associated with punishment (point loss). In
Experiment 2, 79 participants from the same population were tested on a novel
modification of the same task, where they also had the option to opt out of responding on each trial, thus avoiding any chance
of being punished (or rewarded) on that trial. Results show that inhibited participants demonstrated better associative learning
in Experiment 1, while exhibiting a greater tendency to opt out in Experiment 2. These results indicate that the facilitated classically conditioned learning previously observed in inhibited individuals can be extended to a cognitive task, and also highlight a specific preference in inhibited individuals for
withdrawal ("opting out") as a response strategy, when multiple strategies are available to avoid punishment.
Levi-Gigi, E., Kéri, S., Myers, C.E., Lencovsky, Z., Sharvit-Benbaji, H.,
Orr, S.P., Gilbertson, M.W., Servatius, R.J., Tsao, J.W. & Gluck, M.A. (2012). Individuals with post-traumatic stress disorder show
a selective deficit in generalization of associative learning. Neuropsychology, 26(6), 758-767
Drawing on two different populations, Israeli
police and Hungarian civilians, the present study assessed the
ability of individuals with Post-Traumatic Stress Disorder (PTSD)
to generalize previous learning to novel situations. Past neuroimaging
studies have demonstrated diminished medial temporal lobe (MTL)
activation and/or reduced hippocampal volume in individuals
with PTSD. Our earlier computational models of cortico-hippocampal
function and subsequent experimental tests of these models in
MTL-impaired clinical populations argue that even mild hippocampal
dysfunction may result in subtle impairments in generalization.
Therefore, we predicted that individuals with PTSD would show
impaired generalization. Participants were tested on a two-phase
learning paradigm, the Acquired Equivalence Task, which measures
the ability to generalize past learning to novel situations.
We found that both PTSD and non-PTSD participants were capable
of learning the initial stimulus-outcome associations. However,
as predicted, only individuals with PTSD showed a selective
deficit in generalization of this learning to novel situations.
This is consistent with an emerging view of PTSD as being not
only an anxiety disorder but also a learning disorder.
A., Kéri, S., Myers, C. E., Levy-Gigi, E. , Gluck, M. A. & Kelemen,
O. (2012). Impaired generalization of associative learning in latients
with alcohol dependence after intermediate-term abstinence. Alcohol
and Alcoholism, 47(5), 533-537. In Press: doi: 10.1093/alcalc/ags050
We used an associative learning task to investigate
cognitive dysfunctions in alcohol dependence. This test is suitable
for the assessment of stimulus–response learning and memory
generalization (acquired equivalence), which is related to medial
temporal lobe functioning. Methods: Twenty patients with alcohol
dependence (abstinence: >6 months) and 20 matched healthy controls
participated. In the task, antecedent stimuli were cartoon faces
and consequent stimuli were color cartoon fishes. The task was
to learn face–fish associations using feedback. In the transfer
phase, the fish–face pairs were generalized to new associations.
Results: There was no significant difference between patients
and controls during the acquisition phase of fish–face associations.
In the transfer phase, however, patients were impaired relative
to controls. We found no association between task performance
and intelligence. Conclusion: These results suggest that abstinent
patients with alcohol dependence show marked dysfunctions in
in the generalization of associations, which may indicate the
dysfunction of the medial temporal lobe.
T., Gluck, M. A. and Stark C. L., (2011). Functional specialization
within the striatum along both the dorsal/ventral and anterior/posterior
axes during associative learning via reward and punishment. Learning
and Memory. 8:703-711.
The goal of the present study was to elucidate
the role of the human striatum in learning via reward and punishment
during an associative learning task. Previous studies have identified
the striatum as a critical component in the neural circuitry
of reward-related learning. It remains unclear, however, under
what task conditions, and to what extent, the striatum is modulated
by punishment during an instrumental learning task. Using high-resolution
fMRI during a reward- and punishment-based probabilistic associative
learning task, we observed activity in the ventral putamen for
stimuli learned via reward regardless of whether participants
were correct or incorrect (i.e., outcome). In contrast, activity
in the dorsal caudate was modulated by trials that received
feedback – either correct reward or incorrect punishment trials.
We also identified an anterior/posterior dissociation reflecting
reward and punishment prediction error estimates. Additionally,
differences in patterns of activity that correlated with the
amount of training were identified along the anterior/posterior
axis of the striatum. We suggest that unique subregions of the
striatum – separated along both a dorsal/ventral and anterior/posterior
axis – differentially participate in the learning of associations
through reward and punishment.
K. S., Simmons, R. K., Edwards, G., Nicolle, M. M., Gluck, M. A.,
Myers, C. E., & Bizon, J. L. (2011). Novel age-dependent learning
deficits in a mouse model of Alzheimer's disease: implications for
translational research. Neurobiology of Aging. 32(7), 1273-85.
Computational modeling predicts that the
hippocampus plays an important role in the ability to apply
previously learned information to novel problems and situations
(referred to as the ability to generalize information or simply
as ‘transfer learning’). These predictions have been tested
in humans using a computer-based task on which individuals with
hippocampal damage are able to learn a series of complex discriminations
with two stimulus features (shape and color), but are impaired
in their ability to transfer this information to newly configured
problems in which one of the features is altered. This deficit
occurs despite the fact that the feature predictive of the reward
(the relevant information) is not changed. The goal of the current
study was to develop a mouse analog of transfer learning and
to determine if this new task was sensitive to pathological
changes in a mouse model of AD. We describe a task in which
mice were able to learn a series of concurrent discriminations
that contained two stimulus features (odor and digging media)
and could transfer this learned information to new problems
in which the irrelevant feature in each discrimination pair
was altered. Moreover, we report age-dependent deficits specific
to transfer learning in APP + PS1 mice relative to non-transgenic
littermates. The robust impairment in transfer learning may
be more sensitive to AD-like pathology than traditional cognitive
assessments in that no deficits were observed in the APP + PS1
mice on the widely used Morris water maze task. These data describe
a novel and sensitive paradigm to evaluate mnemonic decline
in ADmouse models that has unique translational advantages over
standard species-specific cognitive assessments (e.g., water
maze for rodent and delayed paragraph recall for humans).
E., Kelemen, O., Gluck, M. A., & Kéri, S. (2011). Impaired context
reversal learning, but not cue reversal learning, in patients with
amnestic mild cognitive impairment. Neuropsychologia, 49,
We assessed 30 newly diagnosed patients with
amnestic mild cognitive impairment (aMCI) and 30 matched healthy
controls. Reversal learning was assessed using a novel reinforcement
learning task developed in our lab at Rutgers University. Participants
first acquired and then reversed stimulus–outcome associations
based on negative and positive feedback (losing and gaining
points). Stimuli consisted of a cue (geometric shapes) and a
spatial context (background color or pattern). Relative to controls,
patients with aMCI exhibited a marked reversal learning deficit,
which was highly selective for the reversal of context. The
acquisition of stimulus–outcome associations and cue reversal
learning were spared. Performance on the context reversal learning
task significantly correlated with the right hippocampal volume.
A. A. & Gluck, M. A. (2011). Computational cognitive models of prefrontal-striatal-hippocampal
interactions in Parkinson's disease and schizophrenia. Neural Networks, 24(6),575-591.
In press (doi:10.1016/j.neunet.2011.02.006)
Disruption to different components of the
prefrontal cortex, basal ganglia, and hippocampal circuits leads
to various psychiatric and neurological disorders including
Parkinson's disease (PD) and schizophrenia. Medications used
to treat these disorders (such as levodopa, dopamine agonists,
antipsychotics, among others) affect the prefrontal-striatal-hippocampal
circuits in a complex fashion. We have built models of prefrontal-striatal
and striatal-hippocampal interactions which simulate cognitive
dysfunction in PD and schizophrenia. In these models, we argue
that the basal ganglia is key for stimulus-response learning,
the hippocampus for stimulus-stimulus representational learning,
and the prefrontal cortex for stimulus selection during learning
about multidimensional stimuli. In our models, PD is associated
with reduced dopamine levels in the basal ganglia and prefrontal
cortex. In contrast, the cognitive deficits in schizophrenia
are associated primarily with hippocampal dysfunction, while
the occurrence of negative symptoms is associated with frontostriatal
deficits in a subset of patients. In this paper, we review our
past models and provide new simulation results for both PD and
schizophrenia. We also describe an extended model that includes
simulation of the different functional role of D1 and D2 dopamine
receptors in the basal ganglia and prefrontal cortex, a dissociation
we argue is essential for understanding the nonuniform effects
of levodopa, dopamine agonists, and antipsychotics on cognition.
Motivated by clinical and physiological data, we discuss model
limitations and challenges to be addressed in future models
of these brain disorders.
Z., Moustafa, A. A., Kéri, S., Myers, C. E., & Gluck, M. A. (2011).
General functioning predicts reward and punishment learning in schizophrenia.
Schizophrenia Research. Aug 25 Epub.
Previous studies investigating feedback-driven
reinforcement learning in patients with schizophrenia have provided
mixed results. In this study, we explored the clinical predictors
of reward and punishment learning using a probabilistic classification
learning task. Patients with schizophrenia (n=40) performed
similarly to healthy controls (n=30) on the classification learning
task. However, more severe negative and general symptoms were
associated with lower reward-learning performance, whereas poorer
general psychosocial functioning was correlated with both lower
reward- and punishment-learning performances. Multiple linear
regression analyses indicated that general psychosocial functioning
was the only significant predictor of reinforcement learning
performance when education, antipsychotic dose, and positive,
negative and general symptoms were included in the analysis.
These results suggest a close relationship between reinforcement
learning and general psychosocial functioning in schizophrenia.
Moustafa, A.A., & Gluck, M.A. (2011). A neurocomputational model
of dopamine and prefrontal-striatal interactions during multi-cue
category learning by Parkinson's patients. Journal of Cognitive
Neuroscience, 23(1), 151-167.
Most existing models of dopamine and learning
in Parkinson disease (PD) focus on simulating the role of basal
ganglia dopamine in reinforcement learning. Much data argue,
however, for a critical role for prefrontal cortex (PFC) dopamine
in stimulus selection in attentional learning. Here, we present
a new computational model that simulates performance in multicue
category learning, such as the “weather prediction” task. The
model addresses how PD and dopamine medications affect stimulus
selection processes, which mediate reinforcement learning. In
this model, PFC dopamine is key for attentional learning, whereas
basal ganglia dopamine, consistent with other models, is key
for reinforcement and motor learning. The model assumes that
competitive dynamics among PFC neurons is the neural mechanism
underlying stimulus selection with limited attentional resources,
whereas competitive dynamics among striatal neurons is the neural
mechanism underlying action selection. According to our model,
PD is associated with decreased phasic and tonic dopamine levels
in both PFC and basal ganglia. We assume that dopamine medications
increase dopamine levels in both the basal ganglia and PFC,
which, in turn, increase tonic dopamine levels but decrease
the magnitude of phasic dopamine signaling in these brain structures.
Increase of tonic dopamine levels in the simulated PFC enhances
attentional shifting performance. The model provides a mechanistic
account for several phenomena, including (a) medicated PD patients
are more impaired at multicue probabilistic category learning
than unmedicated patients and (b) medicated PD patients opt
out of reversal when there are alternative and redundant cue
A. A., Kéri, S., Herzallah, M. M., Myers, C. E., & Gluck, M. A.
(2010). A neural model of hippocampal–striatal interactions in associative
learning and transfer generalization in various neurological and
psychiatric patients. Brain and Cognition, 74, 132–144.
Building on our previous neurocomputational
models of basal ganglia and hippocampal region function (and
their modulation by dopamine and acetylcholine, respectively),
we show here how an integration of these models can inform our
understanding of the interaction between the basal ganglia and
hippocampal region in associative learning and transfer generalization
across various patient populations. As a common test bed for
exploring interactions between these brain regions and neuromodulators,
we focus on the acquired equivalence task, an associative learning
paradigm in which stimuli that have been associated with the
same outcome acquire a functional similarity such that subsequent
generalization between these stimuli increases. This task has
been used to test cognitive dysfunction in various patient populations
with damages to the hippocampal region and basal ganglia, including
studies of patients with Parkinson’s disease (PD), schizophrenia,
basal forebrain amnesia, and hippocampal atrophy. Simulation
results show that damage to the hippocampal region—as in patients
with hippocampal atrophy (HA), hypoxia, mild Alzheimer’s (AD),
or schizophrenia—leads to intact associative learning but impaired
transfer generalization performance. Moreover, the model demonstrates
how PD and anterior communicating artery (ACoA) aneurysm—two
very different brain disorders that affect different neural
mechanisms— can have similar effects on acquired equivalence
performance. In particular, the model shows that simulating
a loss of dopamine function in the basal ganglia module (as
in PD) leads to slow acquisition learning but intact transfer
generalization. Similarly, the model shows that simulating the
loss of acetylcholine in the hippocampal region (as in ACoA
aneurysm) also results in slower acquisition learning. We argue
from this that changes in associative learning of stimulus–action
pathways (in the basal ganglia) or changes in the learning of
stimulus representations (in the hippocampal region) can have
similar functional effects.
, S., Moustafa, A. A., Myers, C. E., Benedek, G., & Gluck, M. A.
(2010). Alpha-synuclein gene duplication impairs reward learning.
Proceedings of the National Academy of Sciences. 107 (36). 15992-94.
M. M., Moustafa, A. A., Misk, A. J., Al-Dweib, L. H., Abdelrazeq,
S. A., Myers, C. E., & Gluck, M. A. (2010). Depression impairs learning
whereas anticholinergics impair transfer generalization in Parkinson
patients tested on dopaminergic medications. Cognitive & Behavioral
Neurology. 23(2). 98-105.
In a study of acquired equivalence in Parkinson
disease (PD), in which patients were tested on normal dopaminergic
medication, we found that comorbid clinical depression impairs
initial acquisition, whereas the use of anticholinergic therapy
impairs subsequent transfer generalization. In addition, this
study provides a replication of the basic finding of Myers et
al (2003) that patients with PD on dopaminergic therapy are
impaired at initial acquisition, but normal at subsequent transfer
generalization, generalizing these results to an Arabic-speaking
population including many participants with no formal education.
These results are consistent with our past computational modeling,
which argues that acquisition of incrementally acquired, feedback-based
learning tasks is dependent on cortico-striatal circuits, whereas
transfer generalization is dependent on medial temporal (MT)
structures. They are also consistent with prior computational
modeling, and with empiric work in humans and animals, suggesting
that anticholinergic drugs may particularly impair cognitive
abilities that depend on the MT lobe.
A. A., Myers, C. E., & Gluck, M. A. (2009). A neurocomputational
model of classical conditioning phenomena: a putative role for the
hippocampal region in associative learning. Brain Research, 1276, 180-195.
Some existing models of hippocampal function
simulate performance in classical conditioning tasks using the
error backpropagation algorithm to guide learning (Gluck, M.A.,
and Myers, C.E., (1993). Hippocampal mediation of stimulus representation:
a computational theory. Hippocampus, 3(4), 491–516.). This algorithm
is not biologically plausible because it requires information
to be passed backward through layers of nodes and assumes that
the environment provides information to the brain about what
correct outputs should be. Here, we show that the same information-processing
function proposed for the hippocampal region in the Gluck and
Myers (1993) model can also be implemented in a network without
using the backpropagation algorithm. Instead, our newer instantiation
of the theory uses only (a) Hebbian learning methods which match
more closely with synaptic and associative learning mechanisms
ascribed to the hippocampal region and (b) a more plausible
representation of input stimuli. We demonstrate here that this
new more biologically plausible model is able to simulate various
behavioral effects, including latent inhibition, acquired equivalence,
sensory preconditioning, negative patterning, and context shift
effects. In addition, the newer model is able to address some
new phenomena including the effect of the number of training
trials on blocking and overshadowing.
Bódi, N., Csibri,
E., Myers, C. E., Gluck, M. A., & Kéri, S. (2009). Associative learning,
acquired equivalence, and flexible generalization of knowledge in
mild Alzheimer disease. Cognitive Behavioral Neurology,
Acquired equivalence is a phenomenon in which
prior training to treat two stimuli as equivalent increases
generalization between them. Previous studies demonstrated that
the hippocampal region might play an important role in acquired
equivalence associative learning. In this study, we tested the
possibility that acquired equivalence learning is a sensitive
marker of mild Alzheimer disease. Alzheimer's patients exhibited
mild impairments in the training phase, whereas they were profoundly
impaired on the acquired equivalence test. Associative knowledge
could not be transferred to a more flexible retrieval condition.
These results suggest that acquired equivalence learning is
specifically impaired in early AD, which may indicate the pathology
of the hippocampal region.
Rutledge, R. B.,
Lazzaro, S. C., Lau, B., Myers, C. E., Gluck, M. A., & Glimcher,
P. W. (2009). Dopaminergic drugs modulate learning rates and perseveration
in Parkinson's patients in a dynamic foraging task. Journal
of Neuroscience. 29(48). 15104-15114.
Although previous studies have shown that
Parkinson’s patients are impaired in tasks involving learning
from feedback, they have not directly tested the widely held
hypothesis that dopamine neuron activity specifically encodes
the reward prediction error signal used in reinforcement learning
models. To test a key prediction of this hypothesis, we fit
choice behavior from a dynamic foraging task with reinforcement
learning models and show that treatment with dopaminergic drugs
alters choice behavior in a manner consistent with the theory.
More specifically,we found that dopaminergic drugs selectively
modulate learning from positive outcomes.We observed no effect
of dopaminergic drugs on learning from negative outcomes. We
also found a novel dopamine-dependent effect on decision making
that is not accounted for by reinforcement learning models:
perseveration in choice, independent of reward history, increases
with Parkinson’s disease and decreases with dopamine therapy.
I., Rosenfeld, A., Shohamy, D., Myers, C., Gluck, M., & Stickgold,
R. (2009). Sleep enhances category learning. Learning and Memory.
The ability to categorize objects and events
in the world around us is a fundamental and critical aspect
of human learning. We trained healthy adults on a probabilistic
category-learning task ("Weather Prediction") in two
different training modes: Feedback or Observational. The aim
of this study was to see whether either form of probabilistic
category learning undergoes subsequent enhancement during sleep.
The findings reported here represent the first clear evidence
that active, off-line memory enhancement of a procedural category
rule-learning task takes place throughout a night of sleep,
leading to an absolute improvement in performance the next morning.
The positive correlation between the extent of learning and
the amount of REM sleep obtained the following night suggests
that successful learning of the classification of objects and
events in the world around us can lead to an increase in subsequent
REM sleep, and provides further evidence of an active, sleep-dependent
process. Evidence from our previous imaging studies and studies
using patients with amnesia and Parkinson’s disease suggests
that memory systems supported by the MTL and prefrontal cortex
are activated during observational learning and early stages
of feedback learning, while the striatum is activated as feedback
training continues (Poldrack et al. 2001; Aron et al., 2004;
Hopkins et al. 2004; Shohamy et al. 2004a,b). Thus, one possible
mechanism that could explain our findings is that a localized
sleep-dependent process strengthens memories stored in hippocampal-neocortical
networks, but not those stored in the striatum.
Myers, C. E., Hopkins, R. O., Sage, J., & Gluck, M. A. (2009.).
Distinct hippocampal and basal ganglia contributions to probabilistic
learning and reversal. Journal of Cognitive Neuroscience. 21 (9).
The hippocampus and the basal ganglia have
each, separately, been implicated as necessary for reversal
learning-the ability to adaptively change a response when previously
learned stimulus-outcome contingencies are reversed. Here, we
compared the contribution of the hippocampus and the basal ganglia
to distinct aspects of learning and reversal. Amnesic subjects
with selective hippocampal damage, Parkinson subjects with disrupted
basal ganglia function, and healthy controls were tested on
a novel probabilistic learning and reversal paradigm. In this
task, reversal can be achieved in two ways: Subjects can reverse
a previously learned response, or they can select a new cue
during the reversal phase, effectively ''opting out'' of the
reversal. We found that both patient groups were intact at initial
learning, but differed in their ability to reverse. Amnesic
subjects failed to reverse, and continued to use the same cue
and response learned before the reversal. Parkinson subjects,
by contrast, opted out of the reversal by learning a new cue-outcome
association. These results suggest that both the hippocampus
and the basal ganglia support reversal learning, but in different
ways. The basal ganglia are necessary for learning a new response
when a previously learned response is no longer rewarding. The
failure of the amnesic subjects to reverse their response or
to learn a new cue is consistent with a more general role for
the hippocampus in configural learning, and suggests it may
also support the ability to respond to changes in cue-outcome
Bódi, S. Kéri, H. Nagy, A. Moustafa, C. E. Myers, N. Daw, G. Dibo,
A. Takats, D. Bereczki, and M. A. Gluck Reward-learning and the
novelty-seeking personality: a between- and within-subjects study
of the effects of dopamine agonists on young Parkinson's patients.
Brain, September 1, 2009; 132(9): 2385 - 2395.
In this study, we investigated reward and
punishment processing in three groups: young, never-medicated
Parkinson's disease patients, recently medicated patients receiving
the dopamine receptor agonists pramipexole and ropinirole and
healthy controls. The never-medicated patients were also re-evaluated
after 12 weeks of treatment with dopamine agonists. Reward and
punishment processing was assessed by a feedback-based probabilistic
classification task. Results revealed that never-medicated patients
with Parkinson's disease showed selective deficits on reward
processing and novelty seeking, which were remediated by dopamine
agonists. These medications disrupted punishment processing.
In addition, dopamine agonists increased the correlation between
reward processing and novelty-seeking personality traits, whereas
these drugs decreased the correlation between punishment processing
and harm-avoidance personality traits. Our finding that dopamine
agonist administration in young patients with Parkinson's disease
resulted in increased novelty seeking, enhanced reward processing,
and decreased punishment processing may shed light on the cognitive
and personality bases of the impulse control disorders which
arise as side-effects of dopamine agonist therapy in some Parkinson's
Guthrie, M., Myers,
C. E., & Gluck, M. A. (2009). A neurocomputational model
of tonic and phasic dopamine in action selection: A comparison with
cognitive deficits in Parkinson’s disease. Behavioral Brain Research.
The striatal dopamine signal has multiple
facets; tonic level, phasic rise and fall, and variation of
the phasic rise/fall depending on the expectation of reward/punishment.We
have developed a network model of the striatal direct pathway
using an ionic current level model of the medium spiny neuron
that incorporates currents sensitive to changes in the tonic
level of dopamine. The model neurons in the network learn action
selection based on a novel set of mathematical rules that incorporate
the phasic change in the dopamine signal. This network model
is capable of learning to perform a sequence learning task that
in humans is thought to be dependent on the basal ganglia. When
both tonic and phasic levels of dopamine are decreased, as would
be expected in unmedicated Parkinson's disease (PD), the model
reproduces the deficits seen in a human PD group off medication.
When the tonic level is increased to normal, but with reduced
phasic increases and decreases in response to reward and punishment,
respectively, as would be expected in PD medicated with L-Dopa,
the model again reproduces the human data. These findings support
the view that the cognitive dysfunctions seen in Parkinson's
disease are not solely either due to the decreased tonic level
of dopamine or to the decreased responsiveness of the phasic
dopamine signal to reward and punishment, but to a combination
of the two factors that varies dependent on disease stage and
T., Goldberg, T., Callicott, Q. C., Apud, J., Das, S., Zoltick,
B., Egan, M., Meeter, M., Myers, C., Gluck, M., Weinberger, D.,
& Mattay, V. (2009). Neural correlates of probabilistic category
learning in patients with schizophrenia. Journal of Neuroscience.
Forty patients with schizophrenia receiving
antipsychotic medication and 25 healthy participants were assessed
on interleaved blocks of probabilistic category learning and
control tasks while undergoing functional magnetic resonance
imaging. Based on analyses of the patients and healthy adults
matched on learning and performance, a minority of patients
with schizophrenia achieve successful probabilistic category
learning and performance levels through differential activation
of a circumscribed neural network which suggests a compensatory
mechanism in patients showing successful learning. In particular,
we found greater caudate and dorsolateral prefrontal cortex
activity in the healthy adults and greater activation in a more
rostral region of the dorsolateral prefrontal, cingulate, parahippocampal
and parietal cortex in patients. These results suggest that
successful probabilistic category learning can occur in the
absence of normal frontal-striatal function.
M., Polgar, P., Kelemen, O., Rethelyi, J., Bitter, I., Myers, C.
E., Gluck, M. A., & Kéri, S. (2008). Associative learning in
deficit and non-deficit schizophrenia. Neuroreport. 19(1),
C. E., Hopkins, R. O, DeLuca, J., Moore, N. B., Wolansky, L. J.,
& Gluck, M. A. (2008). Learning and generalization deficits
in patients with memory impairments due to anterior communicating
artery aneurysm rupture or hypoxic brain injury. Neuropsychology.
We studied feedback-guided associative
learning and acquired equivalence in schizophrenia patients
who were subtyped as being deficit (showing negative symptoms)
or non-deficit (not showing negative symptoms). Acquired equivalence
learning, which depends on the medial temporal lobe, was impaired
in both subtypes. In contrast, feedback-guided associative
learning, which depends on basal ganglia function, was impaired
only in the deficit patients. This suggests that the enduring
negative symptoms in deficit schizophrenia may be related
to decreased response to cognitive feedback and deficient
basal ganglia function.
Schmitz T.W., Asthana S., Gluck M.A., Myers C.E. (2008). Associative Learning
Over Trials Activates the Hippocampus in Healthy Elderly but not
Mild Cognitive Impairment. Aging, Neuropsychology, and Cognition,
Human a anterograde amnesia can result
from a variety of etiologies, including hypoxic brain injury
and anterior communicating artery (ACoA) aneurysm rupture.
Although both etiologies cause a similar severe disruption
in declarative memory, we demonstrate here that there are
subtle differences in how these patients learn and generalize
from incrementally acquired feedback-based learning. In two
different tasks, we found that the ACoA patients were slow
at initial learning, but completed the transfer generalization
phase as well as controls. In contrast, the hypoxic patients
tended to show the opposite pattern: normal at initial learning,
but impaired at transfer generalization.
Gluck, M. A., Poldrack,
R. A., & Kéri, S. (2008). The cognitive neuroscience of category
learning. Neuroscience and Biobehavioral Reviews, 32(2), 193-196.
The ability to form associations between
choice alternatives and their contingent outcomes is an important
aspect of learning that may be sensitive to hippocampal dysfunction
in memory disorders of aging such as amnestic Mild Cognitive
Impairment (aMCI), or early Alzheimer Disease. In this preliminary
study we examined brain activation using functional magnetic
resonance imaging (fMRI) in twelve healthy elderly participants
and nine patients with aMCI during an associative learning
task. Using a high-field 3.0 Tesla MRI scanner, we examined
the dynamic neural response during associative learning over
trials. The slope of signal attenuation associated with learning
was analyzed for differences between groups within an a-priori
defined hippocampal region. Results indicated dynamic signal
attenuation associated with learning in the healthy elderly
sample, but not in aMCI. The absence of an associative learning
effect in the aMCI sample reaffirms an important link between
the learning difficulties that are commonly encountered in
aMCI and the medial temporal region.
Chase, H. W., Clark,
L., Myers, C. E., Gluck, M. A., Sahakian, B. J., Bullmore, E. T.,
& Robbins, T. W. (2008). The role of the orbitorfrontal cortex in
human discrimination learning. Neuropsychologia, 46(5), 1326-1337.
- The study of category learning has been a central paradigm
within cognitive psychology for over 25 years. Cognitive neuroscientists
have been drawn to this para- digm for several reasons: first,
there is a large body of pre-existing empirical and theoretical
analyses of category learning. Neuropsychological studies of
clinical populations and neuroimaging of healthy subjects provide
insights into the cognitive neuroscience of category learning.
Second, category learning has aspects of both elementary associative
learning as well as higher-order cognition. On one hand, category
learning can be viewed as a ''cognitive skill'' that shares
behavioral properties, and possibly some neural substrates,
with motor-skill learning and conditioning. It is this dual
nature-part elementary skill, part higher cognition-which helps
make category learning a valuable paradigm for studying the
fundamental aspects of human learning at both the behavioral
and neural levels of analysis. In the spring of 2002, the J.S.
McDonnell Foundation funded a multidisciplinary collaborative
consortium of researchers working in the cognitive neuroscience
of category learning. With the conclusion of this three-year
consortium, this special issue of Neuroscience and Biobehavioral
Reviews presents the broader scientific community with a
collection of its highlights, emphasizing new multidisci- plinary
collaborations and research which emerged from the consortium.
M. A. (2008). Behavioral and neural correlates of error correction
in classical conditioning and human category learning. In M. A.
Gluck, J. R. Anderson, & S. M. Kosslyn (Eds). Memory and Mind:
A Festschrift for Gordon H. Bower (pp. 281-305). New York: Lawrence
- • Several lines of evidence implicate the prefrontal cortex
in learning but there is little evidence from studies of human
lesion patients to demonstrate the critical role of this structure.
To this end, we tested patients with lesions of the frontal
lobe (n = 36) and healthy controls (n = 35) on two learning
tasks: the weather prediction task (WPT), and an eight-pair
concurrent visual discrimination task (‘Choose’). Performance
of both tasks was previously shown to be disrupted in patients
with Parkinson’s disease; the Choose deficit was only present
when patients were medicated. Patients with damage to the orbitofrontal
cortex (OFC) were significantly impaired on Choose, compared
to both healthy controls and non-OFC lesion patients. The OFC
lesion patients showed a mild deficit on the first 50 trials
of the WPT, compared to the control subjects but not non-OFC
lesion patients. The selective deficit in the OFC patients on
Choose performance could not be attributed to the larger lesion
size in this group, and the deficit was not correlated with
the volume of damage to adjacent prefrontal subregions (e.g.
anterior cingulate cortex). These data support the notion that
the OFC play a role in normal discrimination learning, and suggest
qualitative similarities in learning performance of patients
with OFC damage and medicated PD patients.
- To what extent are the processes of human learning analogous
to the more ele- mentary learning processes studied in animal-conditioning
experiments? This question, and the broader goal of integrating
mathematical models of animal and human learning, was the focus
of my collaborative research at Stanford with Gordon Bower in
the mid-1980s as well as my doctoral dissertation, which he
supervised (Gluck & Bower, 1988a, 1988b, 1990). This chapter
is divided into four sections. In the first, I review the concept
of error correction, and discuss how this learning principle
has been a building block for models of both animal and human
learning. Then, I turn to the neural substrates of error correction
learning in classical conditioning, discussing the functional
roles of three brain regions: the cerebellum, the basal ganglia,
and the hippocampus. In the third section, I show how past bridges
between animal and human learning provide a behavioral tool
for using models and data on the neural substrates of classical
conditioning to inform our understanding of the cognitive neuroscience
of human learning, especially probabilistic category learning.
In the fourth and final section, I briefly review the status
of our understanding of the cognitive neuroscience of category
learning, and some exciting new research directions that lie
Meeter, M., Radics, G., Myers, C. E., Gluck, M. A., Hopkins, R.
O. (2008). Probabilistic categorization: How do normal participants
and amnesic patients do it? Neuroscience and Biobehavioral Reviews.
We review evidence in favor of two alternative
conceptualizations of learning in probabilistic categorization:
as rule-based learning, or as incremental learning. Each conceptualization
forms the basis of a way of analyzing performance: strategy
analysis assumes rule-based learning, while rolling regression
analysis assumes incremental learning. Here, we contrasted the
ability of each to predict performance of normal categorizers.
Both turned out to predict responses about equally well. We
then reviewed performance of patients with damage to regions
deemed important for either rule-based or incremental learning.
Evidence was again about equally compatible with either alternative
conceptualization of learning, although neither predicted an
involvement of the medial temporal lobe. We suggest that a new
way of conceptualizing probabilistic categorization might be
fruitful, in which the medial temporal lobe helps setup representations
that are then used by other regions to assign patterns to categories.
Shohamy, D., Myers, C. E., Kalanithi, J., & Gluck, M. A. (2008).
Basal ganglia and dopamine contributions to probabilistic category
learning. Neuroscience and Biobehavioral Reviews. 32, 219-236.
Vadhan, N. P,
Myers, C. E., Rubin, E., Shohamy, D., Foltin, R. W., & Gluck,
M. A. (2008) Stimulus-response learning in long-term cocaine users:
acquired equivalence and probabilistic category learning. Drug and
Alcohol Dependence. 93. 155-162.
We review behavioral, neuropsychological,
functional neuroimaging, and computational studies of basal
ganglia and dopamine contributions to category learning in humans.
Collectively, these studies implicate the basal ganglia in incremental,
feedback-based learning that involves integrating information
across multiple experiences. The medial temporal lobes, by contrast,
contribute to rapid encoding of relations between stimuli and
support flexible generalization of learning to novel contexts
and stimuli. By breaking down our understanding of the cognitive
and neural mechanisms contributing to different aspects of learning,
recent studies are providing insight into how, and when, these
different processes support learning, how they may interact
with each other, and the consequence of different forms of learning
for the representation of knowledge.
Cocaine-dependent and non-drug using controls
were administered two computerized learning tasks. On an acquired
equivalence task in which an initial phase of learning with
conflicting response demands was followed by a subseqent generalization
phase in which the stimuli were presented in novel recombinations,
the cocaine users were slower than controls on the initial learning
but generalized normally in the second phase. In contrast, when
administered a probabilistic "weather prediction"
category learning task, there were no group differences. These
data are consistent with the hypothesis that long-term cocaine
users have particular difficulty when established learning interferes
with new learning, possibly reflecting altered domaine transmission
in the basal ganglia.
Myers, C, E.,
Kluger, A., Golomb, J., Gluck, M. A, & Ferris, S. (2008) Learning
and generalization tasks predict short-term cognitive outcome in
non-demented elderly. Journal of Geriatric Psychiatry and Neurology.
This study examines whether behavioral measures
obtained in non-demented elderly can predict cognitive status
at two-year follow-up. Prior studies have established that delayed
paragraph recall can help predict short-term risk for decline
to mild cognitive impairment (MCI) and Alzheimer's disease (AD).
We examined whether prediction accuracy can be improved by adding
a discrimination-and-generalization task that has previously
been shown to be disrupted in non-demented elderly with hippocampal
atrophy, a risk factor for AD. Fifty non-demented medically
medically healthy elderly patients received baseline clinical
diagnosis and cognitive testing; two years later, patients received
a follow-up clinical diagnosis of normal, MCI, or probable AD.
Two baseline variables, delayed paragraph recall and generalization
performance, were predictive of follow-up outcome with sensitivity
of 81% and specificity of 91% - better than the classification
accuracy based on either of these measures alone. These preliminary
results suggest that these behavioral tasks may be useful tools
in predicting short-term cognitive outcome in non-demented elderly.
P. Farkas, M, Nagy, O., Kelemen, O. Rethelyi, J. Bitter, I., Myers,
C. E., Gluck, M. A., & Kéri, S. (2009). How to find the way out
from four rooms? The learning of "chaining" associations may shed
light on the neuropsychology of the deficit syndrome in schizophrenia.
Schizophrenia Research. 99(1-3), 200-207.
To better understand the cognitive component
of the deficit syndrome in schizophrenia in which patients display
negative symptoms including apathy, social withdrawal and lack
of affect, we studied patients learning a sequence chaining
task previously used with Parkinson's and aMCI patients (Shohamy
et al, 2005; Nagy et al, 2007). Participants navigated a cartoon
character through a sequence of four rooms by learning to choose
the open door from three colored doors in each room. In the
training phase, each stimulus leading to reward (open door in
each room) was trained via feedback until the complete sequence
was learned. In the probe phase, the decision-making context
was manipulated so that, in a given room, there appeared a door
which was correct in another room as well as the door that was
correct in that room. In our previous papers, we argued that
the training phase is predominantly related to basal ganglia
circuits while the context-dependent probe phase requires intact
medial-temporal lobe functioning. In the current study, both
deficit and non-deficit patients (that is, those who display
only positive but not negative symptoms) were similarly impaired
on the probe phase compared with controls. However, the training
phase was only compromised in deficit patients. In particular,
more severe negative symptoms were associated with more errors
on the training phase. Executive functions were unrelated to
performance on this sequence learning task. These results suggest
that the deficit syndrome in schizophrenia is associated with
prominently impaired stimulus-response reinforcement learning,
which may indicate abnormal functioning of basal ganglia circuits.
Nagy, H., Myers, C. E., Benedek, G., Shohamy, D., & Gluck, M. A.
(2008). Risk and protective haplotypes of the alpha-synuclein gene
associated with Parkinson's disease differentially affect cognitive
sequence learning. Genes, Brain, and Behavior. 7 (1). 31-36.
Alpha-synuclein (SNCA) is a key factor in
the regulation of dopaminergic transmission and related to Parkinson's
disease. In this study, we investigated the effects of risk
and protective SNCA haplotypes associated with Parkinson's disease
on cognitive sequence learning in 204 healthy volunteers. We
found that the risk haplotypes are associated with less effective
stimulus-reward learning of sequences and with superior context
representation of sequences. In contrast, participants with
protective haplotypes exhibit better stimulus-reward learning
and worse context representation, which suggests that these
functions are inversely affected by risk and protective haplotypes.
Since stimulus-reward learning may be mediated by the basal
ganglia, and context learning may be related to the medial temporal
lobe, our data raise the possibility that dopaminergic signals
regulated by SNCA inversely affect these memory systems.
H., Myers, C. E., Benedek, M. D., Shohamy, D., Gluck, M., Kéri,
S. Cognitive sequence learning in Parkinson's disease and amnestic
mild cognitive impairment: dissociation between sequential and non-sequential
learning of associations. Neuropsychologia. 45, 1386-1392.
We assessed never-medicated patients with
Parkinson's disease (PD) and amnestic mild cognitive impairment
(aMCI) using a chaining task. In the training phase, each link
in a sequence of stimuli leading to reward is trained step-by-step
using feedback after each decision, until the complete sequence
is learned. In the probe phase of the chaining task, the context
of stimulus-response associations must be used (the place of
the associations in the sequence). Results revealed that patients
with PD showed impaired learning during the training phase of
the chaining task, but their performance was spared in the probe
phase. In contrast, patients with aMCI with prominent medial
temporal lobe (MTL) dysfunctions showed intact learning during
the training phase of the chaining task, but their performance
was impaired in the probe phase of the chaining task. These
results indicate that when dopaminergic mechanisms in the BG
are dysfunctional, series of stimulus-response associations
are less efficiently acquired, but their sequential manner is
maintained. In contrast, MTL dysfunctions may result in a non-sequential
learning of associations, which may indicate a loss of contextual
Nagy, O., Kelemen,
O., Benedek, G., Myers, C. E., Shohamy, D., Gluck, M. A. & Kéri, S.
(2007). Dopaminergic contribution to cognitive sequence learning.
Journal of Neural Transmission. 114. 607-612.
To test the hypthesis that dopaminergic
mechanisms in the basal ganglia are important in feedback-guided
habit learning, we assessed cognitive sequence learning in 120
healthy volunteers and measured plasma levels of homovanillic
acid [HVA] (a metabolite of dopamine), 5-hydroxyindoleacetic
acid [5-HIAA] (a metabolite of serotonin), and 3-methoxy-4-hydroxypheylglycol
[MHPG] (a metabolite of norepinephrine). Results revealed a
significant negative relationship between errors in the feedback-guided
training phase of the sequence learning task and the plasma
HVA level. Participant who had lower HVA level than the median
value of the whole sample committed more errors during the training
phase compared with participants who has higher HVA plasma level
than the median value. A similar phenomenon was not observed
for the context-dependent phase of the task and for 5-HIAA and
MHPG. These results suggest that dopamine plays a special role
in feedback-guided cognitive sequence learning.
P, Farkas M, Nagy O, Kelemen O, Réthelyi J, Bitter I, Myers CE,
Gluck MA, Kéri S. (2007). Learning cognitive skills in depression: the effect
of context-change. Semmelweis Egyetem, Pszichiátriai és Pszichoterápiás
Klinika, Budapest, Hungary. Psychiatry Hungarian, 22(4), 271-275.
AIMS: Patients with depression show cognitive
impairment, including executive function deficit, impairments
in attention, declarative memory and psychomotor performance.
In addition to classic, widely studied cognitive functions,
in depression implicit learning and the interpretation of feedback
and its impact on performance can also be impaired compared
to healthy individuals. While cognitive functions have been
widely studied, much less is known about implicit learning in
depression. METHODS: The two-phased Kilroy sequence association
test examines the basal ganglia-mediated and the temporal lobe
and hippocampus-mediated learning processes within one test.
We compared the performance of 22 depressed patients (according
to DSM-IV) and 20 healthy control subjects using the Kilroy
test. In the depressed group, we also compared the performance
on each step of the test with the symptom severity measured
by the Hamilton D symptom scale. RESULTS: Depressed patients
showed impaired performance compared to healthy subjects on
the first, learning phase of the test. The degree of deficit
on the learning phase correlated with symptom severity. We found
no difference between the two groups on the second, context-dependent
phase of the test. CONCLUSION: Our results confirm the presence
of a striatal deficit in depressed patients. Results indicate
that parallel memory systems are not equally affected in depression,
and the character of deficit in depression may be specific to
C. E., DeLuca, J., Hopkins, R. O, & Gluck, M. A. (2006). Conditional
discrimination and reversal in amnesia subsequent to hypoxic brain
injury or anterior communicating artery aneurysm rupture. Neuropsychologia.
Human anterograde amnesia can develop following
either bilateral damage to the hippocampus and medial temporal
lobes (as in hypoxic injury) or following damage to the basal
forebrain, as seen following anterior communicating artery (ACoA)
aneurysm rupture. Both yield similar mnestic deficits as assessed
by standard neuropsychological measures. However, our previous
animal and computational models suggest there should be specific
qualitative differences in the pattern of impaired and spared
memory abilities following damage to the hippocampus versus
basal forebrain. Here, we show such a predicted dissociation
in both forms of amnesia using a single two-stage task, involving
conditional discrimination and reversal. These results highlight
the importance of considering etiology in evaluating mnemonic
deficits in amnesic populations.
M. A., Myers, C. E., Nicolle, M. M. & Johnson, S. (2006). Computational
models of the hippocampal region: Implications for prediction of
risk for Alzheimer's disease in non-demented elderly. Current Alzheimer's
Research. 3. 247-257.
We have pursued an interdisciplinary research
program to develop novel behavioral assessment tools for evaluating
specific memory impairments following damage to the medial temporal
lobe, including the hippocampus and associated structures that
show pathology early in the course of Alzheimer's disease (AD).
Our approach uses computational models to identify the functional
consequences of hippocampal-region damage, leading to testable
predictions in both rodents and humans. Our modeling argues
that hippocampal-region dysfunction may selectively impair the
ability to generalize when familiar information is presented
in novel recombinations. Converging support for the relevance
of these tasks to aging and Alzheimer's disease comes from our
recent fMRI studies of individuals with mild cognitive impairment
(MCI). A new mouse version of one of our tasks shows promise
for translating these paradigms into rodents, allowing for future
studies of therapeutic interventions in transgenic mouse models
Meeter, M., Myers, C.E., Shohamy, D., Hopkins, R.O. & Gluck, M.A.
(2006). Strategies in probabilistic categorization: Results from
a new way of analyzing performance. Learning & Memory, 13,
The "Weather Prediction" task is a widely
used task for investigating probabilistic category learning,
in which various cues are probabilistically (but not perfectly)
predictive of class membership. Here, we present a new method
for the analysis of probabilistic categorization, which attempts
to identify the strategy followed by a participant. Monte Carlo
simulations show that the analysis can, indeed, reliably identify
such a strategy if it is used, and can identify switches from
one strategy to another. Analysis of data from normal young
adults shows that the fitted strategy can predict subsequent
responses. Analysis of performance of patients with dense memory
impairments due to hippocampal damage shows that although these
patients can change strategies, they are as likely to fall back
to an inferior strategy as to move to more optimal ones.
D., Myers, C. E., Geghman, K. D., Sage, J. & Gluck, M.A. (2006).
L-Dopa impairs learning, but not generalization, in Parkinson's
disease. Neuropsychologia. 44(5), 774-84.
L-dopa is commonly used to treat the motor
symptoms of Parkinson's disease. This study demonstrates that
L-dopa may be associated with the opposite effect on some forms
of cognitive behavior, since Parkinson's patients tested off
L-dopa medication were able to perform a learning task better
than those patients tested while on L-dopa medication, and no
worse than healthy control subjects. Further, we found a dissociation
of the effect of L-dopa within a single two-phase task: patients
tested on medication were not impaired at the ability to generalize
based on learned information, only on initial acquisition. This
suggests that dopaminergic modulation of learning is implicated
in the rate of learning, but not in how that information is
A. R, Gluck, M. A, & Poldrack, R. A. (2006). Long-term test-retest
reliability of functional MRI in a classification learning task.
Neuroimage. 23(3), 1000-1006.
Healthy adult subjects were scanned on two
sessions, one year apart, while performing a probabilistic classification
learning task known to activate fronto-striatal circuitry. We
show that behavioral performance and frontostriatal activation
were highly concordant at a group level at both timepoints.
We conclude that fMRI can have high long-term test-retest reliability,
making it suitable as a biomarker for brain development and
F., Weickert, T. W., Goldberg, T. E., Tessitore, A., Hariri, A.,
Das, S., Lee, B., Zoltick, B., Meeter, M., Myers, C. E., Gluck,
M. A., Weinberger, D. R., Mattay, V. S., (2005). Neural mechanisms
underlying probabilistic category learning in normal aging. Journal
of Neuroscience, 24(49), 11340-11348.
Probabilistic category learning engages neural
circuitry that includes both the prefrontal cortex and the caudate
nucleus of the basal ganglia, two regions that show prominent
changes with normal aging. Using the "weather prediction" task,
young and older adults displayed equivalent learning curves,
used similar strategies, and activated analogous brain regions
with BOLD fMRI. However, the extent of caudate and prefrontal
activation was less, and parietal activation was greater, in
older participants. The percentage correct and reaction times
were mainly positively correlated with caudate and prefrontal
activation in young individuals, but positively correlated with
prefrontal and parietal cortices in older individuals. Differential
activation within a circumscribed neural network in the context
of equivalent learning suggests that some brain regions, such
as the parietal cortices, may provide compensatory mechanisms
for healthy older adults in the context of deficient prefrontal
cortex and caudate nuclei responses.
S., Nagy, O., Kelemen, O., Myers, C. E, & Gluck, M. A. (2005). Dissociation
between medial temporal and basal ganglia memory systems in schizophrenia.
Schizophrenia Research, 77, 321-328.
Basal ganglia and medial temporal lobe dependent
learning was studied in patients with schizophrenia using a
two-phase acquired equivalence task in which prior training
to treat two stimuli as equivalent increases generalization
between them (Myers et al, 2003). Patients with schizophrenia
showed a selective deficit on stimulus generalization, whereas
initial stimulus-response learning was spared. However, errors
during the initial stimulus-response learning was correlated
with daily dose of chlorpromazine-equivalent antipsychotics.
This is the first study to show that patients with schizophrenia
exhibit deficits in medial-temporal-dependent learning, but
not during basal-ganglia-dependent learning, within a single
task. High-dose first generation antipsychotics may disrupt
basal-ganglia-dependent learning by blocking dopaminergic neurotransmission
in the nigro-striatal system.
M. A., Myers, C. E., Meeter, M. (2005). Cortico-hippocampal interaction
and adaptive stimulus representation: A neurocomputational theory
of associative learning and memory. Neural Networks, 18, 1265-1279.
Computational models of the hippocampal region
link psychological theories of associative learning with their
underlying physiological and anatomical substrates. Our approach
to theory development began with a broad description of the
computations that depend on the hippocampal region in classical
conditioning (Gluck & Myers, 1993, 2001). In more recent computational
modeling, we have shown how some aspects of this proposed information-processing
function could emerge from known anatomical and physiological
characteristics of the hippocampal region, including the entorhinal
cortex and the septohippocampal cholinergic system. The modeling
to date lays the groundwork for future directions that increase
the depth of detail of the biological modeling, as well as the
breadth of behavioral phenomena addressed. In particular, we
seek to reconcile these incremental associative learning models
with other models of the hippocampal region that account for
the rapid formation of declarative memories.
D., Myers, C. E., Grossman, S., Sage, J. & Gluck, M. A. (2005).
The Role of dopamine in cognitive sequence learning: Evidence from
Parkinson's disease. Behavioral Brain Research, 156,191-199.
M., Myers, C. E., & Gluck, M. A. (2005). Integrating incremental
learning and episodic memory models of the hippocampal region. Psychological
Review, 112(3), 560-585.
By integrating previous computational models
of corticohippocampal function, we develop and test a unified
theory of the neural substrates of familiarity, recollection,
and classical conditioning. This approach integrates models
from two traditions of hippocampal modeling, those of episodic
memory and incremental learning, by drawing on an earlier mathematical
model of conditioning, SOP (A. Wagner, 1981). The model describes
how a familiarity signal may arise from parahippocampal cortices,
giving a novel explanation for the finding that the neural response
to a stimulus in these regions decreases with increasing stimulus
A.R., Shohamy, D., Clark, J., Myers, C., Gluck, M.A. & Poldrack,
R.A. (2004). Human midbrain sensitivity to cognitive feedback and
uncertainty during classification learning. Journal of Neurophysiology,
We investigated the mechanisms of probabilistic
category learning in humans using functional magnetic resonance
imaging, in order to examine the effects of feedback and uncertainty.
Stimulus presentation and feedback activated brain regions consistent
with the mesencephalic dopaminergic system, while the delay
period did not. Midbrain activity was significantly different
for negative vs. positive feedback (consistent with coding of
the 'prediction error'), and was reliably correlated with the
degree of uncertainty, as well as with activity in the mesencephalic
dopaminergic system .
D., Myers, C., Grossman, S., Sage, J., Gluck, M., Poldrack, R. (2004).
Cortico-striatal contributions to feedback-based learning: Converging
data from neuroimaging and neuropsychology. Brain, 127(4), 851-859.
Feedback structure was found to be a critical
variable in determining when Parkinson's patients are impaired,
or not, on a probabilistic classification task. Training patients
to learn this task in a non-feedback manner (i.e. using observational
learning) remediated a previously documented learning deficit.
In a prior functional imaging study, healthy controls showed
striatal activity during feedback-based learning, which was
decreased when the task was learned without feedback. The present
findings link prior neuroimaging and neurophysiological
data with an understanding of the pattern of spared or impaired
learning abilities in Parkinson's patients, and provide converging
evidence for the role of midbrain dopaminergic systems
in feedback processing.
D., Myers, C. E., Onlaor, S., & Gluck, M. A. (2004). The role
of the basal ganglia in category learning: How do patients with
Parkinson's disease learn? Behavioral Neuroscience, 118
Parkinson's patients were impaired at learning
a classification task, and this impairment was associated with
Parkinson's patients' failure to adopt the kind of complex learning
strategies necessary for optimal performance on this task. This
suggests that Parkinson's patients may not only be slow to learn
under certain conditions, but may also approach learning tasks
in a qualitatively different manner.
R. O, Myers, C. E, Shohamy, D., Grossman, S., & Gluck, M. A.
(2004). Impaired probabilistic category learning in hypoxic subjects
with hippocampal damage. Neuropsychologia, 42, 524-535.
Amnesic patients were found to be impaired
at two forms of probabilistic category learning, both early
and late in training, in contrast to previous reports of Knowlton,
Squire, & Gluck (1994) which reported essentially normal
learning early in training.
C. E., Shohamy, D., Gluck, M. A., Grossman, S., Onlaor, S., &
Kapur, N. (2003). Dissociating medial temporal and basal ganglia
memory systems with a latent learning task. Neuropsychologia, 41,
A dissociation between medial temporal and
basal ganglia damage is evident in a latent learning task in
which prior exposure to cues, uncorrelated with each other,
slows subsequent learning of an association in healthy normal
controls. This effect was abolished in media temporal
amnesia. In contrast, Parkinson’s patients showed a reversal
of the effect: exposed subjects learned faster than non-exposed
M. A., Meeter, M., & Myers, C. E. (2003). Computational models
of the hippocampal region: Linking incremental learning and episodic
memory. Trends in Cognitive Science, 7(6), 269-276.
Two approaches to hippocampal models are
reviewed: (1) models of the hippocampal region inincremental
learning focusing on the development of new stimulus representations,
and (2) models that emphasize the role of the hippocampal region
in rapid storage and retrieval of episodic memories. It is suggested
that both approaches are partially correct and might reflect
the different functions of substructures of the hippocampal
C., Shohamy, D., Gluck, M., Grossman, S., Kluger, A., Ferris, S.,
Golomb, J., Schnirman, G., & Schwartz, R. (2003). Dissociating
hippocampal versus basal ganglia contributions to learning and transfer.
Journal of Cognitive Neuroscience, 15(2), 185-193.
As predicted by our prior computational models,
we found a double dissociation between the associative learning
deficits observed in patients with medial temporal damage
(elderly with mild hipocampal atrophy) versus patients with
basal ganglia dysfunction (mild Parkinson’s disease). On an
“acquired equivalence” task based on animal conditioning paradigms,
MT subjects were normal at initial learning, but impaired on
a subsequent transfer generalization. In contrast, Parkinson’s
patients were slow to learn the initial task, but then transferred
normally. These results suggest distinct contributions of the
medial temporal lobe and basal ganglia in learning and memory.
M.T., Padilla, Y., & Gluck, M.A. (2003). Selective hippocampal
lesions disrupt a novel cue effect but fail to eliminate blocking
in rabbit eyeblink conditioning. Cognitive, Affective, and Behavioral
Neuroscience, 2(4), 318-328.
Selective ibotenic acid lesions of the hippocampus
do not eliminate blocking in the rabbit eyeblink paradigm
but do disrupt the CR decrement found in control animals
on the first compound training trial, as predicted by Gluck
& Myers (1993). This suggests that blocking is a multiply
determined phenomenon, whereby the cerebellum may mediate blocking
through error-correction (Rescorla & Wagner, 1972), while
the hippocampus contributes to blocking through novelty detection
(Mackintosh & Turner, 1971).
M.T., Chelius, L., & Gluck, M.A. (2002) Selective entorhinal
lesions and non-selective cortical-hippocampal region lesions, but
not selective hippocampal lesions, disrupt learned irrelevance in
rabbit eyeblink conditioning. Cognitive Affective and Behavioral
Neuroscience, 2, 214-226.
Rabbits with neurotoxic lesions of the entorhinal
cortex as well as broad hippocampal-region lesions failed to
show slowed learning following uncorrelated preexposures to
the CS and US (i.e., learned irrelevance) and, thus, learned
faster than control rabbits. In contrast, hippocampal-lesioned
animals showed normal (slowed) learning. This confirms a novel
prediction of Myers, Gluck, & Granger’s (1995) computational
model of entorhinal function in associative learning, which
expects that the entorhinal cortex is necessary for unsupervised
compression of stimulus-stimulus redundancies.
M., Chelius, L., Masand, V., Gluck, M., Myers, C., & Schnirman,
G., (2002). A comparison of latent inhibition and learned irrelevance
pre-exposure effects in rabbit and human eyeblink conditioning.
Integrative Physiological and Behavioral Science, 37(3). 188-214.
M. A., Shohamy, D., & Myers, C. E. (2002). How do people solve
the “weather prediction” task?: Individual variability in strategies
for probabilistic category learning. Learning and Memory,
- New experimental and theoretical analyses of our “weather prediction”
task indicate that there are at least three different strategies
that describe how subjects learn this task: (1) an optimal multi-cue
strategy, (2) a one-cue strategy, and (3) a singleton strategy.
This variability in how subjects approach this task may have important
implications for interpreting how various brain regions are involved
in probabilistic category learning.
A. G. & Gluck, M. A. (2002). Processing integral and separable
dimensions in category learning: A connectionist perspective. Connection
Science. 14(1). 1-48.
- A mechanistic connectionist explanation for variations in dimensional
interactions provides a new perspective for the exploration of
how similarities between stimuli are transformed from physical
to psychological space when learning to identify, discriminate,
and categorize them. Although currently limited to monochromatic
stimuli, the model may serve as a starting point for characterizing
the general properties of the human perceptual system that cause
some pairs of dimensions to be treated integrally, and others
separably, a classic problem in cognitive psychology.
T., Padilla, Y., Gluck, M. (2002). Blocking in Rabbit Eyeblink Conditioning
Is Not Due to Learned Inattention: Indirect Support for an Error
Correction Mechanism of Blocking. Integrative Physiological &
Behavioral Science. 254 - 264.
Allen, M.T., Padilla, Y., & Gluck, M.A. (2002). Blocking in
rabbit eyeblink conditioning is not due to learned inattention.
Integrative Physiological and Behavioral Science, 37(4),
M.T., Padilla, Y., & Gluck, M.A. (2002). Ibotenic acid lesions
of the medial septum retard delay eyeblink conditioning in rabbits
(Oryctolagus cuniculus). Behavioral Neuroscience,
Rabbits with selective medial septal lesions
and rabbits receiving systemic scopolamine were significantly
slower to condition than were intact and sham-lesioned rabbits.
This demonstrates that the selective removal of the medial septum
retards delay eyeblink conditioning in a manner similar to the
disruption seen after systemic administration of scopolamine.
Extending the earlier findings of Berry and Thompson (1979)
these results support our previous computational models of septo-hippocampal
function in learning (Myers et al., 1996).
C., Bryant, D., DeLuca, J., & Gluck, M. (2002). Dissociating
basal forebrain and medial temporal amnesic syndromes: Insights
from classical conditioning. Integrative Physiological and Behavioral
Science, April-June 2002, 37(2), 85-102.
A two-phase learning and transfer task provides
a double dissociation between MT amnesics (spared initial learning
but impaired transfer) and AcoA amnesics (slow initial learning
but spared transfer), as implied by our previous computational
models of septo-hippocampal interaction (Myers et al., 1996).
These subtle but dissociable differences in the amnesic syndrome
following damage to the MTL lobes vs. basal forebrain appear
to be most salient in non - declarative tasks such as eyeblink
classical conditioning and simple associative learning.
Kluger, A., Golomb, J., Ferris, S., de Leon, M., Schnirman, G.,
& Gluck, M. (2002). Hippocampal atrophy disrupts transfer
generalization in non-demented elderly. Journal of Geriatric
Psychology and Neurology, 15, 82-90.
Nondemented elderly were trained on a series
of concurrent visual discriminations, then tested for transfer
when stimulus feature were recombined in new ways. As predicted
by Gluck and Myers’s (1993) corticohippocampal model, individuals
with mild hippocampal atrophy were normal on the initial concurrent
discrimination but showed significant impairments in transfer
compared to non-atrophied subjects.
B., Mercado, E., Allen, M. T., Myers, C. E. & Gluck, M. A. (2002).
A connectionist model of septohippocampal dynamics during conditioning:
Closing the loop. Behavioral Neuroscience.
Our previous neurocomputational model of
septo-hippocampal function in conditioning was extended to incorporate
hippocampal-septal feedback loops, modeled as dynamic variations
in hippocampal learning rates. The model successfully accounts
for changes in behavior and septo-hippocampal activity during
various conditioning paradigms. The model provides a computational,
neurally-based synthesis of prior learning theories that explain
change s in medial septal activity based on the novelty of stimulus
M. T., Myers, C., & Gluck, M. (2001). Parallel neural
systems for classical conditioning: Support from computational
modeling. Integrative Physiological and Behavioral Science,
Orduńa, I., Mercado, E., III, Gluck, M.A., & Merzenich, M.M.
(2001). Spectrotemporal sensitivities in rat auditory cortical neurons.
Hearing Research, 160, 47-57.
Mercado, E., III, Bao,
S., Orduńa, I., Gluck, M.A., & Merzenich, M.M. (2001). Basal
forebrain stimulation changes cortical sensitivities to complex
sound. Neuroreport, 12, 2283-2288.
R. A., Clark, J., Pare-Blagoev, E. J., Shohamy, D., Creso-Moyano,
J., Myers, C. E. & Gluck, M. A. (2001). Interactive memory systems
in the brain. Nature. 414 (Nov 29). 546-550.
FMRI studies of probabilistic category learning
showed that the medial temporal lobe and basal ganglia were
differentially engaged across subjects depending on whether
the training involved error-correcting feedback to categorization
responses or the passive observation of stimulus-category pairs.
Event-related FMRI showed rapid modulation of activity in the
MTL early in learning which was negatively correlated across
individuals with basal ganglia activity. As predicted by our
previous computational model of cortico-hippocampal activity
(Gluck & Myers, 1993), hippocampal activity rapidly declined
M.A., Allen, M.T., Myers, C.E., & Thompson, R.F. (2001) Cerebellar
substrates for error-correction in motor-reflex conditioning. Neurobiology
of Learning and Memory, 76, 314-341.
We evaluate a mapping of Rescorla and Wagner's
(1972) behavioral model of classical conditioning onto the cerebellar
substrates for motor-reflex learning. Several novel implications
of this cerebellar error-correcting model are described, including
a recent empirical study by Kim et al. (1998). They verified
our prediction that suppressing the putative error-correction
pathway should interfere with Kamin's (1969) blocking effect,
a behavioral manifestation of error-correction learning. Overall,
the model leads to a comprehensive view of the neural substrates
of conditioning in which this real-time circuit-level model
of the cerebellum can be viewed as a generalization of the long-term
memory module of Gluck and Myers (1993) trial-level theory of
cerebellar-hippocampal interaction in classical motor-reflex
E., III, Myers, C., Gluck, M. (2001). A computational model
of mechanisms controlling experience-dependent reorganization of
representational maps in auditory cortex. Cognitive, Affective
and Behavioral Neuroscience, 1(1), 37-55.
Simulations performed with a biologically-based
neural network model of auditory cortical processing are used
to investigate the possible effects of basal forebrain modulation
on map reorganization in auditory cortex. The model successfully
accounts for experimentally observed effects of pairing basal
forebrain stimulation with the presentation of a single
tone, but not of two tones, suggesting that auditory cortical
plasticity is constrained in ways not accounted for by
Myers, C. E., DeLuca, J., Schultheis, M. T., Schnirman, G. M., Ermita,
B. R., Diamond, B., Warren, S. G., & Gluck, M. A. (2001). Impaired
delay eyeblink classical conditioning in individuals with anterograde
amnesia resulting from anterior communicating artery aneurysm rupture.
Behavioral Neuroscience, 115(3), 560-570.
Anterior communicating artery (ACoA) aneurysm rupture can lead to an anterograde
amnesia syndrome similar to that observed after damage to the hippocampus and medial temporal lobes (MT).
It is currently believed that ACoA amnesia results from basal forebrain damage that disrupts hippocampal
processing without direct hippocampal damage. Converging evidence from animal studies and computational
modeling suggests that qualitative differences may exist in the pattern of memory impairment after basal
forebrain or MT damage. For example, animals with basal forebrain but not hippocampal damage are impaired
at delay eyeblink classical conditioning (EBCC). In this study, individuals with ACoA amnesia were shown to
be impaired at delay EBCC compared with matched controls; this contrasts with the spared delay EBCC previously
observed in MT amnesia. This finding suggests the beginning of a possible dissociation between the memory
impairments in MT versus ACoA amnesia.
C. E., Hopkins, R. O., Kesner, R. P, Monti, L., & Gluck, M.
A. (2000). Conditional spatial discrimination in humans with hypoxic
brain injury. Psychobiology, 28(3), 275-282.
C., Oliver, L., Ermita, B., Warren, S., & Gluck, M. (2000).
Stimulus exposure effects in human associative learning. Quarterly
Journal of Experimental Psychology B: Comparative and Physiological
Psychology, 53B, 173-187.
Learning that one cue (CS) predicts a second, salient cue (US) can often be slowed
by prior exposure to one or both stimuli. In animals, CS±US learning is more strongly retarded following
uncorrelated exposure to both CS and US than following exposure to the US alone. In this paper we present
several studies showing a similar effect in humans, using a computer-based task. Experiments 1 and 2 used
a between-groups design and demonstrated a strong CS/US exposure effect, whether or not the US was signaled
by a neutral cue during exposure. Experiment 3 demonstrated similar effects using a within-subjects design.
Overall, these results are consistent with several theoretical interpretations and suggest that uncorrelated
CS/US exposure leads to a robust retardation of subsequent CS±US learning in humans.
D., Allen, M. T., & Gluck, M. A. (2000). Dissociating entorhinal
and hippocampal involvement in latent inhibition. Behavioral
Neuroscience, 114(5), 867-874.
Rabbits with neurotoxic lesions of the entorhinal
cortex failed to show slowed learning following preexposure
to a cue (i.e., latent inhibition) and, thus, learned faster
than control rabbits. In contrast, hippocampal-lesioned animals
showed normal (slowed) learning. This confirms a novel prediction
of Myers, Gluck, & Granger’s (1995) computational model
of entorhinal function in associative learning.
Mercado, E., III, Myers, C. E.
& Gluck, M.A. (2000). Modeling auditory cortical processing
as an adaptive chirplet transform. Neurocomputing, 32-33(1-4),
Rokers, B., Myers, C.E, &
Gluck, M.A. (2000). A dynamic model of learning in the septo-hippocampal
Gluck and Myers (Hippocampus (1993) 491-516) modeled the hippocampus
as an auto-encoder; Myers et al. (Neurobiol. Learning Memory 66 (1996) 51-66) argued that
the cholinergic input from medial septum modulates learning rate in this auto-encoder.
Neurophysiological evidence suggests the hippocampus self-regulates septal acetylcholine
release in response to novel stimuli (Hasselmo and Schnell, J. Neurosci. 14 (1994) 3898-3914).
We have extended our earlier model of septohippocampal modulation to include such a feedback loop.
The resulting dynamic model learns faster and better than the earlier version on phenomena such as
blocking and shift reversal. It can also be applied to data regarding the effects of the
anticholinergic drug scopolamine.
N., Hanson, S.J., & Gluck, M.A., (2000). Nonlinear autoassociation
is not equivalent to PCA. Neural Computation, 12(3), 531-545.
A common misperception within the neural network community is that even with
nonlinearities in their hidden layer, autoassociators trained with backpropagation are equivalent
to linear methods such as principal component analysis (PCA). Our purpose is to demonstrate that
nonlinear autoassociators actually behave differently from linear methods and that they can outperform
these methods when used for latent extraction, projection, and classification. While linear
autoassociators emulate PCA, and thus exhibit a flat or unimodal reconstruction error surface,
autoassociators with nonlinearities in their hidden layer learn domains by building error reconstruction
surfaces that, depending on the task, contain multiple local valleys. This interpolation bias allows
nonlinear autoassociators to represent appropriate classifications of nonlinear multimodal domains,
in contrast to linear autoassociators, which are inappropriate for such tasks. In fact, autoassociators
with hidden unit nonlinearities can be shown to perform nonlinear classification and nonlinear recognition.
C., McGlinchey-Berroth, R., Warren, S., Monti, L., Brawn, C. M.,
& Gluck, M. A. (2000). Latent learning in medial temporal amnesia:
Evidence for disrupted representational but preserved attentional
processes. Neuropsychology, 14(1), 3-15.
Individuals with medial temporal lobe amnesia
were impaired at representational processing in a latent learning
paradigm, as predicted by the Gluck & Myers (1993)
model of hippocampal function. In contrast, these subjects were
not impaired at an attentional task.
C., Ermita, B., Hasselmo, M. & Gluck, M. (1998). Further
implications of a computational model of septohippocampal cholinergic
modulation in eyeblink conditioning. Psychobiology,
Builds upon our previous work (Myers et
al., 1996) in which we showed that Gluck and Myers’s (1993)
corticohippocampal model could be extended to incorporate Hasselmo
and Schnell’s (1994) hypothesis that septohippocampal cholinergic
processes regulate the amount of information storage in the
hippocampus. Here we show that the model accounts for numerous
additional results from the eyeblink conditioning literature,
and is consistent with data concerning localized scopalamine
injections to the medial septum, the lateral septum, and the
M. A., Ermita, B. R., Oliver, L. M., & Myers, C. E. (1997).
Extending models of hippocampal function in animal conditioning
to human amnesia. Memory, 5 (1/2), 179-212.
Although most analyses of human amnesia
have focused on the loss of explicit declarative and episodic
memories following hippocampal-region damage, considerable insights
into amnesia can also be realized by studying hippocampal function
in simple procedural, or habit-based, associative learning tasks.
Reviews several recent papers which argue that the hippocampal
region plays a critical role in the formation of new stimulus
representations during learning, (Gluck & Myers, 1993,
1995; Myers & Gluck, 1995; Myers, Gluck, & Granger,
1995). Summarizes our recent experimental work with amnesic
patients using two behavioral paradigms: eyeblink conditioning
and probabilistic category learning.
M. A., & Myers, C. E. (1997). Psychobiological models of hippocampal
function in learning and memory. Annual Review of Psychology.
M. A., & Myers, C. E. (1996). Integrating behavioral and physiological
models of hippocampal function. Hippocampus (Special Issue on Computational
Models of Hippocampal Function in Memory, M. Gluck, Guest Editor).
In recent modeling of hippocampal function, we have attempted to integrate
formal behavioral analyses of classical conditioning with psychobiological data on brain lesions
(Gluck and Myers  Hippocampus 3:491-516; Myers and Gluck  Behav Neurosci 108(5):835-847).
Based on comparative behavioral analyses, we have argued that animals with hippocampal region damage
are unable to alter stimulus similarity based on experience. While hippocampal-damaged animals can
still learn whether to respond to an individual stimulus, they are notably impaired at many tasks
involving learning relationships between stimuli-especially in the absence of explicit reinforcement.
These analyses lead to a computational theory which identifies two representational recoding processes-
predictive differentiation and redundancy compression-which alter stimulus similarity relationships in
intact animals but are dependent on intact hippocampal region processing. More recent, and ongoing,
modeling aims to broaden this model of hippocampal region function in classical conditioning, with an
emphasis on physiological and anatomical constraints, including the role of the fornix and subcortical
modulation, preprocessing in sensory cortices, and localization of the proposed representational functions
within more precisely identified hippocampal region substrates (Myers et al.  Psychology 23(2):116-138;
Myers and Gluck  Behav Neurosci; Myers et al.  Neurobiol Learning Memory). Working to bridge
between behavioral and physiological levels of analysis, we ultimately hope to develop a more complete
understanding of hippocampal region function in memory across a wider range of behavioral paradigms,
elucidating how this functionality emerges from underlying physiological and anatomical substrates.
M. A. (1996). Computational models of hippocampal function in memory:
Introduction to special issue. Hippocampus (Special Issue on Computational
Models of Hippocampal Function in Memory, M. Gluck, Guest Editor).
Gluck, M. A., Oliver, L. M., &
Myers, C. E. (1996). Late-training amnesic deficits in probabilistic
category learning: A neurocomputational analysis.Learning
and Memory, 3, 326-340.
Building upon earlier behavioral models
of animal and human learning, we explore how a psychobiological
model of animal conditioning can be applied to amnesic category
learning. We show that the late-training deficit found in Knowlton,
Squire, and Gluck’s (1994) study of amnesic category learning
can be understood as a natural consequence of Gluck and Myers
(1993) theory of hippocampal-region function, a theory which
has heretofore been applied only to studies of animal learning.
C. E., & Gluck, M. A. (1996). Cortico-hippocampal representations
in simultaneous odor discrimination: A computational interpretation
of Eichenbaum, Mathews, and Cohen (1989). Behavioral Neuroscience,
A model of hippocampal-region function in
Pavlovian conditioning (Gluck & Myers, 1993; Myers &
Gluck, 1994) is generalized to provide a computational interpretation
of Eichenbaum and colleagues' simultaneous odor discrimination
studies (Eichenbaum, Fagan, Mathews & Cohen, 1988; Eichenbaum,
Mathews & Cohen, 1989). This modeling makes two central
points. First, Eichenbaum et al.’s data on forced-choice odor
discrimination can be understood as a reflecting the same underlying
representational recodings previously invoked to describe behaviors
seen in studies of classical eyeblink conditioning. Second,
the computational mechanisms which underlie performance in the
intact and lesioned model are consistent with the more qualitative
interpretations suggested by Eichenbaum et al. (1988). 1989)
to explain the intact and lesioned rat data.
C. E., Ermita, B., Harris, K., Hasselmo, M., Solomon, P., &
Gluck, M. A. (1996). A computational model of the effects
of septohippocampal disruption on classical eyeblink conditioning.
Neurobiology of Learning and Memory, 66, 51-66.
A previous neurocomputational model of cortico-hippocampal
interaction (Gluck & Myers, 1993) provides a framework for
examing the behavioral effects of septohippocampal modulation
during classical conditioning. According to Hasselmo’s (1995)
model of septohippocampal function, anticholinergic drugs such
as scopolomine should disrupt learning by selectively reducing
the hippocampus’s ability to store new information. Hasselmo’s
model can be approximated within the Gluck-Myers model by a
manipulation of hippocampal learning rates, and with this manipulation,
we can account for the effects of scopolamine on classical conditioning
in humans and rabbits. The model further predicts that while
cholinergic agonists (such as Tacrine) may improve learning
in subjects with artificially depressed brain acetycholine levels,
there may be little memory improvement in normal subjects from
such cholinergic therapy.
Gabrieli, J.D.E., McGlinchey-Berroth,
R., Carrillo, M.C., Gluck, M.A., Cermak, L.S., & Disterhoft,
J.F. (1995). Intact delay-eyeblink classical conditioning in amnesia.
Behavioral Neuroscience, 109(5), 819-827.
The status of classical conditioning in
human amnesia was exampined by comparing conditioning of the
eyeblink response to a tone conditioned stimulus in the delay
paradigm between 7 amnesic and 7 age- and education-matched
normal control subjects. Amnesic patients exhibited normal baseline
performance in pseudoconditioning, and normal acquisition and
extinction of conditioned responses in terms of the number,
latency, and magnitude of eyeblinks. These results indicate
that in humans, as in rabbits, brain structures critical for
declarative memory are not essential for the acquisition of
elementary CS-US associations.
C. E., Gluck, M. A., & Granger R. (1995). Dissociation of hippocampal
and entorhinal function in associative Learning: A computational
approach. Psychobiology. 23(2). 116-138.
Proposes that Gluck & Myers (1993) computational
theory of hippocampal-region function may be subdivided and
localized via analysis of the biological substrate and its emergent
operation. In particular, the parahippocampal region is conjectured
to constructs new stimulus representations which compress redundant
information. To the extent that parahippocampal-region
function can survive damage strictly limited to the hippocampus
proper, this hypothesis has implications for interpreting the
behavioral consequences of selective lesions which spare the
M. A. & Myers, C. E., (1995). Representation and association
in memory: A neurocomputational view of hippocampal function.
Current Directions in Psychological Science, 4(1). 23-29.
B. J., Squire, L. R. , & Gluck, M. A. (1994). Probabilistic
category learning in amnesia. Learning and Memory.
Amnesic patients and control subjects were
trained on two category learning tasks in which each of four
cues was probabilistically associated with one of two outcomes.
Both groups exhibited significant and similar learning curves
during early training trials, but the control subjects outperformed
the amnesics on later trials. These findings are relevant to
recent connectionist theories of category learning (Gluck &
Bower, 1988), and raise the possibility that the learning of
cue-outcome associations is fundamentally similar to conditioning
as studied in experimental animals.
C. E. & Gluck, M. A. (1994). Context, conditioning and hippocampal
re-representation. Behavioral Neuroscience, 108(5), 835-847.
A previous computational account of hippocampal-region
function in associative learning (Gluck & Myers, 1993) has
emergent implications which accurately describe the role of
the hippocampal region in contextual processing. This
account unifies two seemingly conflicting views of contextual
processing; it accords contextual cues no special representational
status yet it still allows context to stand in a superordinate
relationship to the cues it contains. The model makes several
novel predictions and provides a framework for understanding
the conditions under which a learned response either is, or
is not, decremented in a novel context as well as explaining
data suggesting that hippocampal lesion reduces contextual sensitivity.
Gluck, M., Myers, C.E., & Goebel, J. (1994).
A computational perspective on dissociating hippocampal and entorhinal function
(Response to Eichenbaum, et al.).Behavioral and Brain Sciences, 17, 478-479.
Shanks, D. R. & Gluck, M.
A. (1994). Tests of an adaptive network model for the identification,
categorization, and recognition of continuous-dimension stimuli.
Connection Science, 6(1), 59-89.
- Describes a new adaptive network model, the Consequential Region
Model, for the identification and categorization of stimuli varying
on multiple, continuous dimensions. The models provides
excellent fits to identification and categorization data. These
results illustrate how an associative network can show appropriate
sensitivity to inter-item similarities among training exemplars
as an emergent property of its scheme for representing stimuli.
R. M., Gluck, M. A., Palmeri, T. J., McKinley, S. C., & Glauthier,
P. (1994). Comparing models of rule-based classification learning:
A replication and extension of Shepard, Hovland, and Jenkins. Memory
Cognition, 22, 352-369.
- An experimental study of task difficulty for learning six fundamental
types of rule-based categorization problems is used to compare
four current computational models of classification learning.
The results of these new category learning experiments suggest
the need to incorporate some form of selective attention to dimensions
in category-learning models based on stimulus generalization and
M. A. & Myers, C. (1993). Hippocampal mediation of stimulus
representation: A computational theory. Hippocampus, 3(4):
- Proposes a computational theory of the hippocampal-region's
function in mediating stimulus representations. The theory assumes
that the hippocampal region develops new stimulus representations
which enhance the discriminability of differentially predictive
cues while compressing the representation of redundant cues. The
theory makes several novel predictions regarding the effects of
hippocampal lesionsand suggests that a profitable direction for
future empirical and theoretical research will be the study of
learning tasks in which both intact and lesioned animals exhibit
similar initial learning behaviors, but differ on subsequent transfer
and generalization tasks.
Gluck, M. A., & Granger, R.
(1993). Computational models of the neural bases of learning and
memory. Annual Review of Neuroscience, 16, 667-706.
Reviews current efforts to develop computational
models of the neural bases of learning and memory, with a focus
on the behavioral implications of network-level characterizations
of synaptic change in three anatomical regions: olfactory (piriform)
cortex, cerebellum, and the hippocampal formation.
Corter, J. E., & Gluck, M.
A. (1992) Explaining basic categories: Feature predictability and
information. Psychological Bulletin, 111(2), 291-303.
M. A. (1991). Stimulus generalization and representation in adaptive
network models of category learning. Psychological Science,
It is shown here how an approximate exponential
generalization gradient emerges from stimulus representation
assumptions isomorphic to a special case of Shepard’s theory
of stimulus generalization within Gluck and Bower’s (1988) configural-cue
network model of human learning. Thus, the network model can
be viewed as a combination of Shepard’s theory and an associative
learning rule derived from the Rescorla-Wagner theory of classical
Gluck, M. A. & Bower, G. H.
(1990). Component and pattern information in adaptive networks
Journal of Experimental Psychology: General, 119(1), 105-109.
Donegan, N. H., Gluck, M. A.,
& Thompson, R. F. (1989). Integrating behavioral and biological
models of classical conditioning. Psychology of Learning
and Motivation (Volume 22). New York: Academic Press, 109-156.
M. A. & Bower, G. H. (1988). From conditioning to category
learning: An adaptive network model. Journal of Experimental
Psychology: General, 117(3), 227-247.
Gluck, M. A., & Bower, G.
H. (1988). Evaluating an adaptive network model of human learning.
Journal of Memory and Language, 27, 166-195.
Gluck, M. A., Parker, D. B., &
Reifsnider, E. (1988). Some biological implications of a differential-Hebbian
learning rule. Psychobiology, 16(3), 298-302.
Gluck, M. A. & Thompson, R.
F. (1987). Modeling the neural substrates of associative learning
and memory: A computational approach, Psychological Review,
Jolicoeur, P., Gluck, M. A., &
Kosslyn, S. M. (1984). Pictures and names: Making the connection.
Cognitive Psychology, 16, 243-275.
I. & Gluck, M.A. (2001) The Neural Basis of Blocking. International
Encyclopedia of the Social and Behavioral Sciences. 1260-1262.
Blocking is a conditioning paradigm, first described
by Leon Kamin (1969), in which previous conditioning to a stimulus which a
second stimulus can be conditioned during compound conditioning. This effect
reflects the fact that temporal contiguity does not suffice for associations
to occur between events, and reveals the animal's active role in the selection
and processing of stimuli during associative learning. No single neural mechanism
has yet been identified as a neural basis for blocking, but compelling evidence
for an underlying negative feedback mechanism has been provided. The hippocampus,
as a structure claimed to be relevant for the selection of stimuli, has also been
shown to play a role in blocking, although those results are somewhat obscured by
lack of specificity in the lesions. Future research in the neural basis of blocking
should include further exploration of negative feedback mechanisms as well as more
detailed studies regarding the role of the hippocampus and related structures in
Rokers, B., Myers, C., & Gluck, M. (2001). "A dynamic model of learning in the septohippocampal system." In J. Bower (Ed.), Computational Neuroscience: Trends in Research 1999, New York: Plenum Press.
Gluck, M.A., Allen, M.T., & Myers, C.E. (2001). Medial Septal Modulation of Conditioning: From Two-Stage Learning Theories to Connectionist Models. In J. E. Steinmetz, M. A. Gluck, & P. F. Solomon (Eds.), Model Systems of Associative Learning: A Festschrift for Richard F. Thompson (pp. 295-316). Mahwah, NJ: Lawrence Erlbaum Associates.
Allen, M.T., Myers, C.E., & Gluck, M.A. (2000). Neural network approaches to eyeblink classical conditioning. In D. S. Woodruff-Pak & J. E. Steinmetz (Eds.), Eyeblink Classical Conditioning: Animal (pp. 229-255). Kluwer Academic Publishers.
Cahill, L., Gluck, M., Hasselmo, M., Keil, F., Martin, A., McGaugh, J., Murre, J., Myers, C., Petrides, M., Roozendaal, B., Schacter, D., Simons, D., Smith, W. & Williams, C. (1998). Learning and memory: Systems analysis. In M. Zigmond, F. Bloom, S. Landis, J. Roberts, L. Squire (Eds.), Fundamental Neuroscience, New York: Academic Press.
Gluck, M., & Myers, C. (1998). Psychobiological models of hippocampal function in learning and memory. In J. Martinez & R. Kesner (Eds.), Neurobiology of Learning and Memory (pp. 417-448). San Diego, CA: Academic Press.
Zackheim, J., Myers, C., & Gluck, M. (1998). A temporally sensitive recurrent network model of occasion setting. In N. Schmajuk & P. Holland (Eds.), Occasion Setting: Associative Learning and Cognition in Animals (pp. 319-342). Washington, DC: American Psychological Association.
Ermita, B.R., Myers, C.E., Hasselmo, M., & Gluck, M.A. (1997). Septohippocampal cholinergic modulation in classical conditioning. In J. M. Bower (Ed.), Computational Neuroscience (pp. 631-639). New York: Plenum Press.
Gluck, M.A., & Myers, C.E. (1997). Adaptive stimulus representations in a computational model of cortico-hippocampal function. In M. Baudry & J. Davis (Eds.), Long Term Potentiation: Volume III (pp. 325-350). Cambridge, MA: MIT Press.
Gluck, M.A., & Myers, C.E. (1997). A neural-network approach to adaptive similarity and stimulus representations in cortico-hippocampal function. In J. Donahoe & V. Dorsel (Eds.), Neural-network models of cognition: Biobehavioral foundations. Amsterdam, Netherlands: Elsevier Science Press.
Gluck, M.A. & Myers, C.E. (1994). A neurocomputational theory of hippocampal function in stimulus representation and learning. In S. Zournetzer, J. Davis, T. McKenna, & C. Lau (Eds.), An Introduction to Neural and Electronic Networks (Second Edition) (pp. 77-90).
Gluck, M.A., Myers, C.E., & Thompson, R.F. (1994). A computational model of the cerebellum and motor-reflex learning. In S. Zournetzer, J. Davis, T. McKenna, & C. Lau (Eds.). An Introduction to Neural and Electronic Networks (Second Edition) (pp. 91-80).
Gluck, M. A. (1992). Stimulus sampling and distributed representations in adaptive network theories of learning. In A. Healy, S. Kosslyn, & R. Shiffrin (Eds.), From Learning Theory to Connectionist Theory: Essays in Honor of William K. Estes (pp. 169-199). New Jersey: Lawrence Erlbaum Associates.
Bartha, G. T., Thompson, R. F., & Gluck M. A. (1991). Sensorimotor learning and the cerebellum. In M.A. Arbib & J.-P. Ewert (Eds.), Visual Structures and Integrated Functions, Springer Research Notes in Neural Computing (pp. 381-196). Berlin: Springer-Verlag.
Thompson, R.F. & Gluck, M.A. (1991). Brain substrates of basic associative learning and memory. In H. J. Weingartner & R. F. Lister (Eds.), Cognitive Neuroscience (pp. 24-45). New York: Oxford University Press.
Gluck, M.A., Reifsnider, E.S., & Thompson, R.F. (1990). Adaptive Signal Processing and the Cerebellum: Models of Classical Conditioning and VOR Adaptation. In Gluck, M.A. & Rumelhart, D. E. (Eds.). Neuroscience and Connectionist Theory (pp. 131-185). Hillsdale, NJ: Lawrence Erlbaum Associates.
Thompson, R.F., & Gluck, M.A. (1989). A biological neural-network analysis of learning and memory. In S. Zournetzer, J. Davis, & C. Lau (Eds.) An Introduction to Neural and Electronic Networks (pp. 91-107). New York: Academic Press.
AND GUEST-EDITED JOURNAL ISSUES
and Mind: A Festschrift for Gordon H. Bower,
(M. A. Gluck, J. R. Anderson, & S. M. Kosslyn, Eds.) , 2007
Gluck, M. A., Mercado, E., & Myers, C. E. (2007, Expected). Learning
and Memory: From Brain to Behavior. New York: Worth.
Gluck, M. A. & Myers, C. E. (2001).
Gateway to Memory: An Introduction to Neural Network Models
of the Hippocampus and Learning. Cambridge, MA: MIT Press.
Steinmetz, J., Gluck, M., &
Solomon, P. (2001). Model Systems and the Neurobiology
of Associative Learning: A Festshrift for Richard F. Thompson, Mahwah,
NJ: Lawrence Erlbaum Associates.
Gluck, M. A., Guest Editor,
(1996), Hippocampal Computation and Memory (Special issue
of Hippocampus). 6(6). J. Wiley & Sons.
Gluck, M. A. & Rumelhart,
D. E., Editors (1990). Neuroscience and Connectionist
Theory, Hillsdale, N.J. Lawrence Erlbaum Associates.
M.A., Editor (1990). Neural Networks for Defense
Applications, San Francisco: Miller-Freeman Publications.
REVIEWS AND COMMENTARIES
Warren, S. & Gluck, M., (1998). Making memories. Lincoln Center Theater Review (pp. 18-20). Spring Issue Number 18. New York, NY: Lincoln Center.
Gluck, M. A., Bartha, G. T., Reifsnider, E. S., & Shiffrar, M. M. (1990). Review of Eckmiller & von der Malsburg, 'Neural Computers.' Psychological Science, 1(5), 287-292.
N., Myers, C.E. & Gluck, M.A (1995). A novelty detection approach
to classification. Proceedings of the Fourteenth International
Joint Conference on Artificial Intelligence. Montreal, August
20-25 1995). Montreal, Canada: Morgan Kaufmann. 518-523.
Gluck, M. A. (1994). What does
the hippocampus compute?: Precis of the NIPS workshop. In J. D.
Cowan, G. Tesauro, G., & J. Alspector, (Editors), Advances
in Neural Information Processing Systems #6. San Francisco,
CA: Morgan Kaufman Publishers. 1173-1175.
Gluck, M. A., & Myers, C.
E. (1993). Adaptive stimulus representations: A computational theory
of hippocampal-region function. In S. Hanson, J. Cowan, & C.
Giles (Editors). Advances in Neural Information Processing Systems
#5. San Mateo, CA: Morgan Kaufman. 937-944.
M. A., Glauthier, P. T., & Sutton, R. S. (1992). Adaptation
of cue-specific learning rates in network models of human category
learning. In Proceedings of the 14th Annual Conference of the
Cognitive Science Society (Bloomington, IN), Hillsdale, NJ:
Lawrence Earlbaum Associates. 540-545.
Gluck, M. A. & Myers, C. E.
(1992). Hippocampal-system function in stimulus representation and
generalization: A computational theory. In Proceedings of the
14th Annual Conference of the Cognitive Science Society (Bloomington,
IN), Hillsdale, NJ: Lawrence Earlbaum Associates. 390-395.
Hanson, S. J., & Gluck, M.
A. (1991). Spherical units as dynamic consequential regions:
Implications for attention and cue-competition in categorization.
Advances in Neural Information Processing Systems #3. San
Mateo, CA: Morgan Kaufman, 656-665.
D., Fisher, D., Gluck, M., Langley, P., & Pazzani, M. (1990).
Computational models of category learning. In Proceedings of
the 12th Annual Conference of the Cognitive Science Society (Cambridge,
MA), Hillsdale, NJ: Lawrence Erlbaum Associates 989-996.
Gluck, M., Parker, D. B., &
Reifsnider, E. B., (1989). Learning with temporal derivatives
in pulse-coded neuronal systems. In D. Touretzky (Ed.). Advances
in Neural Information Processing Systems. San Mateo, CA:
Morgan Kaufman, 195-205.
Pavel, M., Gluck, M. A., &
Henkle, V. (1989). Constraints on adaptive networks for modeling
human generalization. In D. Touretzky (Ed.). Advances in Neural
Infromation Processing Systems. San Mateo, CA: Morgan
M. A. & Bower, G. H., & Hee, M. (1989). A configural-cue
network model of animal and human associative learning. Proceedings
of the 11th Annual Conference of the Cognitive Science Society,
Ann Arbor, MI. 323-332.
Never published 1992 book-length draft version
Corter, J., Gluck, M. A., Bower,
G. H. (1988). Basic levels in hierarchically structured categories,
Proceedings of the 10th Annual Conference of the Cognitive Science
Society, Montreal, Canada. 118-124.
Pavel, M., Gluck, M. A., Henkle,
V. (1988). Generalization by humans and multi-layer adaptive
networks, Proceedings of the 10th Annual Conference of the Cognitive
Science Society, Montreal, Canada. 680-687.
Gluck, M. A. & Bower,
G. H. (1988). From conditioning to category learning: An adaptive
network model. Journal of Experimental Psychology: General, 117(3), 227-247.
Gluck, M. A. & Bower, G. H.
(1986). Conditioning and categorization: Some common effects of
informational variables in animal and human learning. Proceedings
of the 8th Annual Conference of the Cognitive Science Society, Amherst,
Gluck, M. A., & Thompson,
R. F. (1985). A computer model of the neural substrates of
classical conditioning in the Aplysia. Proceedings of the 7th
Annual Conference of the Cognitive Science Society, Irvine,
Gluck, M. A. & Corter, J.
E. (1985). Information, uncertainty, and the utility of categories.
Proceedings of the 7th Annual Conference of the Cognitive Science
Society, Irvine, Calif. .283-287
Corter, J. E., & Gluck, M.
A. (1985). Machine generalization and human categorization:
An information-theoretic view. Proceedings of AAAI/IEEE Workshop
on Uncertainty and Probability in Artificial Intelligence, Los
Angeles, Calif. 201-207.