Damage to the hippocampal system disrupts recent memory but leaves remote memory intact. The account presented here suggests that memories are first stored via synaptic changes in the hippocampal system, that these changes support reinstatement of recent memories in the neocortex, that neocortical synapses change a little on each reinstatement, and that remote memory is based on accumulated neocortical changes. Models that learn via changes to connections help explain this organization. These models discover the structure in ensembles of items if learning of each item is gradual and interleaved with learning about other items. This suggests that the neocortex learns slowly to discover the structure in ensembles of experiences. The hippocampal system permits rapid learning of new items without disrupting this structure, and reinstatement of new memories interleaves them with others to integrate them into structured neocortical memory systems.

Why there are complementary learning systems in the hippocampus and neocortex: insights from the successes and failures of connectionist models of learning and memory.

A theory of memory retrieval is developed and is shown to apply over a range of experimental paradigms. Access to memory traces is viewed in terms of a resonance metaphor. The probe item evokes the search set on the basis of probe-memory item relatedness, just as a ringing tuning fork evokes sympathetic vibrations in other tuning forks. Evidence is accumulated in parallel from each probe-memory item comparison, and each comparison is modeled by a continuous random walk process. In item recognition, the decision process is self-terminating on matching comparisons and exhaustive on nonmatching comparisons. The mathematical model produces predictions about accuracy, mean reaction time, error latency, and reaction time distributions that are in good accord with experimental data. The theory is applied to four item recognition paradigms (Sternberg, prememorized list, study-test, and continuous) and to speed-accuracy paradigms; results are found to provide a basis for comparison of these paradigms. It is noted that neural network models can be interfaced to the retrieval theory with little difficulty and that semantic memory models may benefit from such a retrieval scheme.

A Theory of Memory Retrieval.

The diffusion decision model allows detailed explanations of behavior in two-choice discrimination tasks. In this article, the model is reviewed to show how it translates behavioral data—accuracy, mean response times, and response time distributions—into components of cognitive processing. Three experiments are used to illustrate experimental manipulations of three components: stimulus difficulty affects the quality of information on which a decision is based; instructions emphasizing either speed or accuracy affect the criterial amounts of information that a subject requires before initiating a response; and the relative proportions of the two stimuli affect biases in drift rate and starting point. The experiments also illustrate the strong constraints that ensure the model is empirically testable and potentially falsifiable. The broad range of applications of the model is also reviewed, including research in the domains of aging and neurophysiology.

The Diffusion Decision Model: Theory and Data for Two-Choice Decision Tasks

Priming is a nonconscious form of human memory, which is concerned with perceptual identification of words and objects and which has only recently been recognized as separate from other forms of memory or memory systems. It is currently under intense experimental scrutiny. Evidence is converging for the proposition that priming is an expression of a perceptual representation system that operates at a pre-semantic level; it emerges early in development, and access to it lacks the kind of flexibility characteristic of other cognitive memory systems. Conceptual priming, however, seems to be based on the operations of semantic memory.

http://miwalab.cog.human.nagoya-u.ac.jp/database/resume/2008-07-07.pdf

Priming and human memory systems

A simulation model of episodic memory, MINERVA 2, is applied to the learning of concepts, as represented by the schema-abstraction task. The model assumes that each experience produces a separate memory trace and that knowledge of abstract concepts is derived from the pool of episodic traces at the time of retrieval. A retrieval cue contacts all traces simultaneously, activating each according to its similarity to the cue, and the information retrieved from memory reflects the summed content of all activated traces responding in parallel. The MINERVA 2 model is able to retrieve an abstracted prototype of the category when cued with the category name and to retrieve and disambiguate a category name when cued with a category exemplar. The model successfully predicts basic findings from the schema-abstraction literature (e.g., differential forgetting of prototypes and old instances, typicality, and category size effects), including some that have been cited as evidence against exemplar theories of concepts. The model is compared to other classification models, and its implications regarding the abstraction problem are discussed. How is abstract knowledge related to specific experience? In present-day terms, this question concerns the relationship between episodic and generic memories. This article explores the possibility that there is only one memory system, which stores episodic traces, and that abstract knowledge as such does not have to be stored but can be derived from the pool of traces of specific experiences at the time of retrieval. I demonstrate how this might work by applying a simulation model of a multipletrace memory theory to the sehema-abstraction experimental paradigm, which is widely believed to capture in the laboratory the processes by which generic or abstract ideas are formed. Multiple-trace theories assume that each event to which one attends gives rise to its own memory trace. Thus, repetition of an item such as a word in a list does not strengthen a prior representation (i.e., one predating the experiment or one laid down by the item's first experimental occurrence); rather, it produces a new trace that coexists in memory with traces of other occurrences of the same item. Experiments supporting the multiple-trace assumption have been primarily concerned with the ability of subjects to remember an item's presentation frequency, list membership, presentation modality, exposure duration, serial position, and so forth (e.g., Hintzman, 1976; Hintzman & Block, 1971; Hintzman, Block, & Summers, 1973;

/pdf/schema-abstraction-in-a-multiple-trace-memory-model-2i26m74p1g.pdf

"Schema Abstraction" in a Multiple-Trace Memory Model

Different Ways to Cue a Coherent Memory System: A Theory for Episodic, Semantic, and Procedural Tasks.

Describes 2 contrasting models for response latency in the yes-no signal detection situation and outlines their main characteristics. The 1st model is a generalization of the notion that latency in detection is some inverse function of distance from the criterion; the 2nd proposes that instead of a single observation on any 1 trial the S makes multiple observations and a count of these observations determines the response and its latency. Although the predictions of the models are similar in many respects, there are some points concerning the ordering of mean latencies, reaction time receiver operating characteristic curves, latency-probability relations, and the constancy of d' which differentiate them. Particularly important, the multiple observations model predicts that response bias and sensitivity are interdependent. The possibility of multiple observations in detection is briefly considered. (2 p. ref.) (PsycINFO Database Record (c) 2006 APA, all rights reserved).

Response latency models for signal detection.

Comparison of convolution and matrix distributed memory systems for associative recall and recognition.

Global matching: A comparison of the SAM, Minerva II, Matrix, and TODAM models.

The results of three studies testing whether associative interference occurs in recognition as it does in recall are reported.

Ray Pike

Papers

Different Ways to Cue a Coherent Memory System: A Theory for Episodic, Semantic, and Procedural Tasks.

Response latency models for signal detection.

Comparison of convolution and matrix distributed memory systems for associative recall and recognition.

Global matching: A comparison of the SAM, Minerva II, Matrix, and TODAM models.

Associative Interference Effects in Recognition and Recall