AIMC Topic: Models, Psychological

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Multiscale Modeling of Gene-Behavior Associations in an Artificial Neural Network Model of Cognitive Development.

Cognitive science
In the multidisciplinary field of developmental cognitive neuroscience, statistical associations between levels of description play an increasingly important role. One example of such associations is the observation of correlations between relatively...

A rational model of function learning.

Psychonomic bulletin & review
Theories of how people learn relationships between continuous variables have tended to focus on two possibilities: one, that people are estimating explicit functions, or two that they are performing associative learning supported by similarity. We pr...

Letter identification and the neural image classifier.

Journal of vision
Letter identification is an important visual task for both practical and theoretical reasons. To extend and test existing models, we have reviewed published data for contrast sensitivity for letter identification as a function of size and have also c...

Modeling the dynamics of evaluation: a multilevel neural network implementation of the iterative reprocessing model.

Personality and social psychology review : an official journal of the Society for Personality and Social Psychology, Inc
We present a neural network implementation of central components of the iterative reprocessing (IR) model. The IR model argues that the evaluation of social stimuli (attitudes, stereotypes) is the result of the IR of stimuli in a hierarchy of neural ...

g-Distance: On the comparison of model and human heterogeneity.

Psychological review
Models are often evaluated when their behavior is at its closest to a single, sometimes averaged, set of empirical results, but this evaluation neglects the fact that both model and human behavior can be heterogeneous. Here, we develop a measure, -di...

Using large-scale experiments and machine learning to discover theories of human decision-making.

Science (New York, N.Y.)
Predicting and understanding how people make decisions has been a long-standing goal in many fields, with quantitative models of human decision-making informing research in both the social sciences and engineering. We show how progress toward this go...

AI, visual imagery, and a case study on the challenges posed by human intelligence tests.

Proceedings of the National Academy of Sciences of the United States of America
Observations abound about the power of visual imagery in human intelligence, from how Nobel prize-winning physicists make their discoveries to how children understand bedtime stories. These observations raise an important question for cognitive scien...

Computational evidence for hierarchically structured reinforcement learning in humans.

Proceedings of the National Academy of Sciences of the United States of America
Humans have the fascinating ability to achieve goals in a complex and constantly changing world, still surpassing modern machine-learning algorithms in terms of flexibility and learning speed. It is generally accepted that a crucial factor for this a...

Making Sense of Computational Psychiatry.

The international journal of neuropsychopharmacology
In psychiatry we often speak of constructing "models." Here we try to make sense of what such a claim might mean, starting with the most fundamental question: "What is (and isn't) a model?" We then discuss, in a concrete measurable sense, what it mea...

Structured Event Memory: A neuro-symbolic model of event cognition.

Psychological review
Humans spontaneously organize a continuous experience into discrete events and use the learned structure of these events to generalize and organize memory. We introduce the (SEM) model of event cognition, which accounts for human abilities in event ...