BOOKS AND EDITED VOLUMES

Gluck, M. A., Mercado, E., & Myers, C. E. (2008). Learning and Memory: From Brain to Behavior. New York: Worth.

Gluck, M. A., Kosslyn, S. M., & Anderson, J. (2008) Memory and Mind: A Festschrift for Gordon H. Bower. New York: Taylor & Francis.

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 & Sons.

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

2008

• 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 .

• 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. 21 (2). 93-103.

• 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.

Polgar, P. Farkas, M, Nagy, O., Kelemen, O. Rethelyi, J. Bitter, I., Myers, C. E., Gluck, M. A., & Keri, S. (2008). 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. In press.

• 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, 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 (2007) 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 information.

Kéri, S., Nagy, H., Myers, C. E., Benedek, G., Shohamy, D., & Gluck, M. A. (2007). Risk and protective haplotypes of the alpha-synuclein gene associated with Parkinson's disease differentially affect cognitive sequence learning. Genes, Brain, and Behavior. 7. 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.

• 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.

2006

Myers, 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. 44(1):130-139.

• 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.

Gluck, 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 of AD.

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, 230-239..

• 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.

Shohamy, 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 later processed.

Aron, 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). 1000-6.

• 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 neurodegeneration.

2005

Fera, 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. The 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.

Kéri, 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.

Gluck, 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.

Shohamy, 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. 156:191-9.

• Individuals with Parkinson's disease were impaired on a cognitive sequence learning task which requires learning a chain of associations leading to reward; this impairment was remediated with dopaminegic medication. These findings link the cognitive deficits in Parkinson's disease with a rich literature of animal studies exploring the role of dopamine in reward-related learning.

Meeter, 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 familiarity.

2004

Aron, 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. J. Neurophysiology. 92, 1144-1152.

• 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 .

Shohamy, 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.

Shohamy, 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 (4). 676-686.

• 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.

Hopkins, 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.

2003 

Myers, 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. 1919-1928.

• 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 subjects.

Gluck, 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 region.

Myers, 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.

Allen, 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).

2002

Allen, 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.

Allen, 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.

Gluck, 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. 9. 408-418.

• 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.

Tijsseling, 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.

Allen, 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). 254-264.


Allen, 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, 116(4). 733-738.

• 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).

Myers, 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.

Myers, C., 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.

Rokers, 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. 116(1), 48-62.

• 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 events.

2001

Allen, M. T., Myers, C., & Gluck, M. (2001).  Parallel neural systems for classical conditioning:  Support from computational modeling.  Integrative Physiological and Behavioral Science, 36(1), 36-61.

Orduña, 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., Orduña, I., Gluck, M.A., & Merzenich, M.M. (2001). Basal forebrain stimulation changes cortical sensitivities to complex sound. Neuroreport, 12, 2283-2288.

• The selectivity and sensitivity of auditory cortical neuronal responses were altered in adult rats by repeated presentation of complex sounds that were paired with basal forebrain stimulation. The auditory cortical region that was responsive to complex sounds was two to five times greater in paired-stimulation rats than in naïve rats. These findings demonstrate that feature selectivity within the auditory cortex can be flexibly altered in adult mammals through appropriate intensive training.

Poldrack, 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 with training.

Gluck, 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 conditioning.

Mercado, 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 current theories.

2000

Myers, 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.

• Hypoxic subjects with significant hippocampal atrophy were able to acquire and reverse a discrimination, although they were slower relative to matched controls. They also showed a tendency to perseverate after reward contingencies were reversed.

Myers, 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.

Shohamy, 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), 913-919.

Rokers, B., Myers, C.E, & Gluck, M.A. (2000). A dynamic model of learning in the septo-hippocampal system. Neurocomputing. 32-33(1-4). 501-507.

Japkowicz, N., Hanson, S.J., & Gluck, M.A., (2000). Nonlinear autoassociation is not equivalent to PCA. Neural Computation. 12(3). 531-545.

Myers, 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.

1995-1999

Myers, C., Ermita, B., Hasselmo, M. & Gluck, M. (1998).  Further implications of a computational model of septohippocampal cholinergic modulation in eyeblink conditioning.  Psychobiology, 26(1), 1-20.

• 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 hippocampus.

Gluck, 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.

Gluck, M. A., & Myers, C. E. (1997). Psychobiological models of hippocampal function in learning and memory. Annual Review of Psychology. 48. 481-514.

• We review current computational models of hippocampal function in learning and memory, concentrating on those that make strongest contact with psychological issues and behavioral data.

Gluck, 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). 6(6). 643-653.

Gluck, 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). 6(6). 565-566.

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.

Myers, C. E., & Gluck, M. A.  (1996). Cortico-hippocampal representations in simultaneous odor discrimination: A computational interpretation of Eichenbaum, Mathews, and Cohen (1989). Behavioral Neuroscience. 110(4), 1-22.

• 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.

Myers, 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.

Myers, 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 parahippocampal region.

Gluck, 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.

• An overview of our current computational theories of hippocampal function in memory, with special reference to similarities and differences to related qualitative theories of H. Eichenbaum. To appear side-by-side with a similar article by Eichenbaum.

1991-1994

Knowlton, B. J.,  Squire, L. R. , & Gluck, M. A. (1994). Probabilistic category learning in amnesia.  Learning and Memory. 1, 106-120.

• 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.

Myers, 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.

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.

Nosofsky, 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 cue conditioning.

Gluck, M. A. & Myers, C. (1993). Hippocampal mediation of stimulus representation: A computational theory. Hippocampus. 3(4): 491-516

• 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.

• A quantitative measure is derived for the utility of a category that successfully predicts the basic level in experiments on both artifificial and  natural category hierarchies.

Gluck, M. A. (1991). Stimulus generalization and representation in adaptive network models of category learning. Psychological Science, 2(1), 50-55.

• 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 conditioning.

1984-1990

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.

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. (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, 94(2), 176-191.

Jolicoeur, P., Gluck, M. A., & Kosslyn, S. M. (1984).  Pictures and names: Making the connection. Cognitive Psychology, 16, 243-275.

BOOK CHAPTERS

Orduna, I. & Gluck, M.A. (in press) The Neural Basis of Blocking. International Encyclopedia of the Social and Behavioral Sciences.

Rokers, B., Myers, C., & Gluck, M. (2001).  "A dynamic model of learning in the septo-hippocampal system."  In (J. Bower, ed.) Computational Neuroscience:  Trends in Research 1999, Plenum Press, New York.

Gluck, M.A., Allen, M.T., & Myers, C.E.  (2001). Medial Septal Modulation of        Conditioning: From Two-Stage Learning Theories to Connectionist Models. Model Systems of Associative Learning: A Festschrift for Richard F. Thompson  (Eds.  J.E Steinmetz, M.A. Gluck, & P.F. Solomon). Lawrence Erlbaum Associates, Mahwah, NJ, pp. 295-316.

Allen, M.T., Myers, C.E., & Gluck, M.A. (2000)  Neural network approaches to eyeblink classical conditioning.  Eyeblink Classical Conditioning :  Animal. (Eds.  D.S. Woodruff-Pak & J.E. Steinmetz). Kluwer Academic Publishers. pp. 229-255.

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 (Editors). Long Term Potentiation: Volume III. MIT Press: Cambridge, MA. p. 325-350

Gluck, M. A., & Myers, C. E. (1997). A neural-network approach to adaptive similarity and stimulus representations in cortico-hippocampal function.  In <>J. Donahoe and V. Dorsel (Editor), 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 (Editors). An Introduction to Neural and Electronic Networks (Second Edition). 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 (Editors). An Introduction to Neural and Electronic Networks (Second Edition). 91-80.

Gluck, M. A., (1992). Stimulus sampling and distributed representations in adaptive network theories of learning. In A. Healy, S. Kosslyn, & R. Shiffrin (Editors), From Learning Theory to Connectionist Theory: Essays in Honor of William K. Estes. New Jersey: Lawrence Erlbaum Associates. 169-199.