for learn- for a wide range of visual behaviors. Familiar objects ing a wide variety of behaviors (Chen and Wise, 1995; activated fewer neurons than did novel objects, but Knight et al., 1995; Asaad et al., 1998; Parker et al., these neurons were more narrowly tuned, and the ob- 1998). Thus, it is a good candidate for studying the effects of experience. ject representation was more resistant to the effects We used a modified version of a delayed matching- of degradation, after experience. These results dem- to-sample (DMS) task that required monkeys to discrimi- onstrate a neural correlate of visual learning in the PF nate and remember each of a set of five objects (see cortex of adult monkeys. Experimental Procedures). Monkeys were briefly shown a sample object, then after a short delay, a test object. If the test object matched the sample, monkeys were Introductio

this article should be addressed to Marvin M. Chun, Department of Psychology, Vanderbilt University, Nashville, Tennessee 37203. E-mail: marvin.chun@vanderbilt.edu Journal of Experimental Psychology: Copyright 2003 by the American Psychological Association, Inc. Learning, Memory, and Cognition 2003, Vol. 29, No. 2, 224--234 0278-7393/03/$12.00 DOI: 10.1037/0278-7393.29.2.224 224 display was defined by a unique configuration of multiple item locations, and participants had to associate different configurations with different embedded target locations (Cohen & Eichenbaum, 1993; Eichenbaum, 1992; Rudy & Sutherland, 1994). The memory traces for spatial context were specific enough to discriminate one context from another (Logan, 1988)

This article analyzes the relationship between skill learning and repetition priming, 2 implicit memory phenomena. A number of reports have suggested that skill learning and repetition priming can be dissociated from each other and are therefore based on different mechanisms. The authors present a theoretical analysis showing that previous results cannot be regarded as evidence of a processing dissociation between skill learning and repetition priming. The authors also present a single-mechanism computational model that simulates a specific experimental task and exhibits both skill learning and repetition priming, as well as a number of apparent dissociations between these measures. These theoretical and computational analyses provide complementary evidence that skill learning and repetition priming are aspects of a single underlying mechanism that has the characteristics of procedural memory. One of the most significant developments in the study of human memory over the last two decades has been the discovery of a dissociation between two different kinds of memory systems. An early indication of this dissociation came from studies of amnesia in patients with excision or lesions of the hippocampus (Scoville & Milner, 1957). These patients were dramatically impaired in their

visual structure: human data and a model

The way in which meaning is represented and processed in the brain is a key issue in cognitive neuroscience, which can be usefully addressed by functional imaging techniques. In contrast to previous imaging studies of semantic knowledge, which have primarily used blocked designs, in this study we use an eventrelated fMRI (erfMRI) design, which has the advantage of enabling events to be presented pseudorandomly, thus reducing strategic processes and enabling more direct comparison with psychological behavioral studies. We used a semantic categorization task in which events were words representing either artifact or natural kinds concepts. Significant areas of activation for semantic processing included inferior frontal lobe bilaterally (BA 47) and left temporal regions, both inferior (BA 36 and 20) and middle (BA 21). These are areas that have been identified in previous neuroimaging studies of semantic knowledge. However, there were no significant differences between artifact and natural kinds concepts. These results are consistent with our previous imaging studies using blocked designs and suggest that conceptual knowledge is represented in a unitary, distributed neural system undifferentiated by domain of knowledge. These findings demonstrate that event-related designs can generate activations that are similar to those seen in blocked designs investigating semantics and, moreover, offer a greater capacity for interpretation free from the confounds of block effects. © 2002 Elsevier Science (USA)

Theories of object representation can be classified as structural, holistic or hybrid, depending on their approach to the mereology and compositionality of shapes. We tested the predictions of some of the current theories in three experiments, by quantifying the effects of various priming cues on response times to 3D objects. In experiment 1, there were two possible locations for the stimulus components: left-right and top-bottom. The prime could be identical to the stimulus, identical in location but with different parts, identical in the complement of differently located parts, or altogether different. Both location and part identity effects were significant. In experiment 2 we added a part-neutral (empty frame) prime condition; the effect of location, but not of part, remained significant. In experiment 3, which included an additional location-neutral prime condition, only the location effect, again, was significant. These findings are not entirely compatible either with the structu...

Abstract. A model of sensory information processing is presented. The model assumes that learning of internal (hidden) generative models, which can predict the future and evaluate the precision of that prediction, is of central importance for information extraction. Furthermore, the model makes a bridge to goal-oriented systems and builds upon the structural similarity between the architecture of a robust controller and that of the hippocampal entorhinal loop. This generative control architecture is mapped to the neocortex and to the hippocampal entorhinal loop. Implicit memory phenomena; priming and prototype learning are emerging features of the model. Mathematical theorems ensure stability and attractive learning properties of the architecture. Connections to reinforcement learning are also established: both the control network, and the network with a hidden model converge to (near) optimal policy under suitable conditions. Falsifying predictions, including the role of the feedback connections between neocortical areas are made.

iteria. Declarative Memory Observations of preserved and impaired memory in patients with amnesia indicate that the recall and recognition of facts and episodes, or declarative memory, is dependent on a particular subset of brain regions and can be disrupted selectively. How can we develop a better understanding of this selectivity? Indeed, one might pose the question: Why is declarative memory different from all other forms of memory? Here are four answers to this question: 1. Because declarative memory has distinct behavioral characteristics. 2. Because declarative memory has distinct subjective characteristics. 3. Because declarative memory has a distinct cognitive structure. 4. Because declarative memory has distinct neural substrates. Memory theorists tend to give one or another of these answers greater emphasis, as discussed further below. In any event, determi

An important source of evidence concerning rapid adaptation and learning in the brain is the phenomenon of repetition suppression---the longlasting and item-specific decrease in neural responsivity with repeated exposure to an item, yielding a sparser representation. Existing accounts are informal and do little more than describe the phenomenon. In this paper, explore the hypothesis that repetition suppression can be characterized as the result of adaptation of the neural code with the rational goal of maximizing information transmission. Our work is based on two assumptions. First, in naturalistic environments, when an organism encounters some object, the object is more likely to be encountered again in the near future; consequently a probabilistic model of the environment must be updated following each experience. Second, neural codes are continually optimized to transmit information efficiently. Through simulation studies, we show that our model can explain the key phenomena of repetition suppression, and therefore serves as a framework for interpreting changes in cortical information processing with experience.

An important source of evidence concerning rapid adaptation and learning in the brain is the robust phenomenon of repetition suppression---the long lasting and item-specific decrease in neural activity with repeated exposure to an item, yielding sparser, sharper representations. Existing accounts of repetition suppression are informal and do little more than describe the phenomenon. We explore the hypothesis that repetition suppression arises from an unsupervised learning mechanism that reduces sensitivity to noise by increasing the item-specific gain of neural responses, in conjunction with the assumption that neurons are biased toward infrequent activity. This hypothesis explains key experimental observations concerning changes in neural representation with mere repetition of stimuli, regardless of task relevance. Additionally, this hypothesis explains related data concerning improved discriminability and noise robustness of individual neurons due to practice on a specific task.