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Chen, Qi; Mirman, Daniel – Psychological Review, 2012
One of the core principles of how the mind works is the graded, parallel activation of multiple related or similar representations. Parallel activation of multiple representations has been particularly important in the development of theories and models of language processing, where coactivated representations ("neighbors") have been shown to…
Descriptors: Competition, Word Recognition, Language Processing, Inhibition
Solway, Alec; Botvinick, Matthew M. – Psychological Review, 2012
Recent work has given rise to the view that reward-based decision making is governed by two key controllers: a habit system, which stores stimulus-response associations shaped by past reward, and a goal-oriented system that selects actions based on their anticipated outcomes. The current literature provides a rich body of computational theory…
Descriptors: Habit Formation, Brain, Decision Making, Rewards
Berry, Christopher J.; Shanks, David R.; Speekenbrink, Maarten; Henson, Richard N. A. – Psychological Review, 2012
We present a new modeling framework for recognition memory and repetition priming based on signal detection theory. We use this framework to specify and test the predictions of 4 models: (a) a single-system (SS) model, in which one continuous memory signal drives recognition and priming; (b) a multiple-systems-1 (MS1) model, in which completely…
Descriptors: Priming, Recognition (Psychology), Models, Prediction
Gonzalez, Cleotilde; Dutt, Varun – Psychological Review, 2011
In decisions from experience, there are 2 experimental paradigms: sampling and repeated-choice. In the sampling paradigm, participants sample between 2 options as many times as they want (i.e., the stopping point is variable), observe the outcome with no real consequences each time, and finally select 1 of the 2 options that cause them to earn or…
Descriptors: Feedback (Response), Learning Theories, Models, Sampling
Griffiths, Thomas L.; Tenenbaum, Joshua B. – Psychological Review, 2009
Inducing causal relationships from observations is a classic problem in scientific inference, statistics, and machine learning. It is also a central part of human learning, and a task that people perform remarkably well given its notorious difficulties. People can learn causal structure in various settings, from diverse forms of data: observations…
Descriptors: Causal Models, Prior Learning, Logical Thinking, Statistical Inference
Juslin, Peter; Nilsson, Hakan; Winman, Anders – Psychological Review, 2009
Probability theory has long been taken as the self-evident norm against which to evaluate inductive reasoning, and classical demonstrations of violations of this norm include the conjunction error and base-rate neglect. Many of these phenomena require multiplicative probability integration, whereas people seem more inclined to linear additive…
Descriptors: Probability, Theories, Norms, Computer Simulation
Ashby, F. Gregory; Ennis, John M.; Spiering, Brian J. – Psychological Review, 2007
A biologically detailed computational model is described of how categorization judgments become automatic in tasks that depend on procedural learning. The model assumes 2 neural pathways from sensory association cortex to the premotor area that mediates response selection. A longer and slower path projects to the premotor area via the striatum,…
Descriptors: Biology, Computation, Models, Classification