this article may be addressed to either Michael Kahana or Robert Sekuler, Volen National Center for Complex Systems, MS 013, Brandeis University, Waltham, MA 02254-9110. E-mail may be sent to kahana @brandeis.edu or sekuler@brandeis.edu plex multidimensional stimulus spaces (Nosofsky, 1992; Maddox & Ashby, 1996; Ashby & Perrin, 1988), with decision rules that can predict performance in a variety of classification paradigms (Nosofsky & Palmeri, 1998; Nosofsky & Alfonso-Reese, 1999; Maddox & Ashby, 1996). Although models of classification and models of visual discrimination share many assumptions about stimulus representation and subjects' decision rules, models of classification have been primarily developed to explain subjects' classification of combinations of simple geometric forms, whereas models of discrimination have been developed to explain subjects ' discrimination of elemental visual stimuli, including sinusoidal luminance gratings. Because such stimuli can be combined to synthesize more complex images such as textures and natural scenes, they represent a natural test-bed for assessing theories' power and generalizability

The medial temporal lobe (MTL) has been studied extensively at all levels of analysis, yet its function remains unclear. Theory regarding the cognitive function of the MTL has centered along 3 themes. Different authors have emphasized the role of the MTL in episodic recall, spatial navigation, or relational memory. Starting with the temporal context model (M.W. Howard and M. J. Kahana, 2002), a distributed memory model that has been applied to benchmark data from episodic recall tasks, the authors propose that the entorhinal cortex supports a gradually changing representation of temporal context and the hippocampus proper enables retrieval of these contextual states. Simulation studies show this hypothesis explains the firing of place cells in the entorhinal cortex and the behavioral effects of hippocampal lesion in relational memory tasks. These results constitute a first step towards a unified computational theory of MTL function that integrates neurophysiological, neuropsychological and cognitive findings.

In the single-store model of memory, the enhanced recall for the last items in a free-recall task (i.e., the recency effect) is understood to reflect a general property of memory rather than a separate short-term store. This interpretation is supported by the finding of a long-term recency effect under conditions that eliminate the contribution from the short-term store. In this article, evidence is reviewed showing that recency effects in the short and long terms have different properties, and it is suggested that 2 memory components are needed to account for the recency effects: an episodic contextual system with changing context and an activation-based short-term memory buffer that drives the encoding of item–context associations. A neurocomputational model based on these 2 components is shown to account for previously observed dissociations and to make novel predictions, which are confirmed in a set of experiments.

Cleeremans: The search for the computational correlates of consciousness

Mental localization efforts tend to stress the where more than the what. We argue that the proper targets for localization are well-specified cognitive models. We make this case by relating an existing cognitive model of category learning to a learning circuit involving the hippocampus, perirhinal, and prefrontal cortices. Results from groups varying in function along this circuit (e.g., infants, amnesics, and older adults) are successfully simulated by reducing the model’s ability to form new clusters in response to surprising events, such as an error in supervised learning or an unfamiliar stimulus in unsupervised learning. Clusters in the model are akin to conjunctive codes that are rooted in an episodic experience (the surprising event) yet can develop to resemble abstract codes as they are updated by subsequent experiences. Thus, the model holds that the line separating episodic and semantic information can become blurred. Dissociations (categorization vs. recognition) are explained in terms of cluster recruitment demands. Franz remarked in his 1912 essay “New Phrenology” that “the individual parts of the brain do not work independently; they work interdependently, and it is because of the possible functional and anatomical connections that certain types or kinds of mental states are more in evidence

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This paper considers the relation between item recognition and cued recall -- two standard measures of episodic memory. Going beyond measures of performance on each task, we examine the degree to which correlations between successful recognition and successful recall of a single studied episode reflect the commonality of memory processes underlying the two tasks. Specifically, we consider whether four computational memory models (local and global match versions of both matrix and convolution-correlation models) can account for the relatively invariant correlation (# 0.5) between successive recognition and recall tests. Whereas basic versions of each model cannot account for the correlation, versions that take into account variability in goodness-of-encoding and in response criteria, as well as output encoding, are able to account for the level of dependency between tasks. These elaborated models also succeeded in fitting data from two new experiments that manipulated the level of variability in goodness-of-encoding across conditions. This model-

The Complementary Learning Systems model of recognition (Norman & O'Reilly, 2001) predicts that increasing list strength (i.e., strengthening the memory traces associated with some studied items) should impair recognition of non-strengthened studied items when discrimination is based on recollection, but not when discrimination is based on familiarity. This finding implies that the magnitude of the list strength effect (LSE) for recognition sensitivity will depend on the extent to which participants are relying on recollection vs. familiarity. In the experiments reported here, we isolated the contribution of recollection to recognition performance in three different ways: by collecting self-report measures of recollection and familiarity (Experiments 1 and 2); by focusing on high-confidence responses (Experiments 2 and 3); and by using related lures at test (Experiment 3). In all three experiments, we found a significant LSE for measures of recognition sensitivity that isolate the cont...

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I would like to thank my advisor, Dr. Kazuhiko Kawamura, for his sage guidance and support. I would not have been able to compile this thesis without him, and he has provided me with insight and direction since the day I first started graduate school. I would also like to thank Dr. David Noelle and Dr. Mitch Wilkes for helping me learn that knowing how to ask the correct question in a tough situation is sometimes more important than finding its answer. Flo Fottrell deserves my thanks for helping me throughout my graduate career. She has assisted me in finding my way around the school, and always gives the right advice. Similarly, I would like to acknowledge my fellow students in the CIS for all their help, especially when it came to developing my Linux administrator skills. My parents receive my deepest gratitude for their rock-solid support and for instilling in me a love of knowledge, and my brother for teaching me humility of that knowledge. Finally, I would like to thank Shazi Jiang for standing beside me throughout my MS career. I couldn't have done it without her.