Special Issue on Model-Based Cognitive Neuroscience

Posted on Dec 5, 2014

Thomas Palmeri from Vanderbilt, Brad Love from University College London, and Brandon Turner from The Ohio State University are co-editing a special issue of the Journal of Mathematical Psychology on Model-Based Cognitive Neuroscience. This special issue aims to explore the growing intersection between cognitive modeling and cognitive neuroscience. Cognitive modeling has a rich history of formalizing and testing hypotheses about cognitive mechanisms within a mathematical and computational language, making exquisite predictions of how people perceive, learn, remember, and decide. Cognitive neuroscience aims to identify neural mechanisms associated with key aspects of cognition, using techniques like neurophysiology, electrophysiology, and structural and functional brain imaging. These two come together in a powerful new approach called model-based cognitive neuroscience, which can both inform model selection and help interpret neural measures. Cognitive models decompose complex behavior into representations and processes and these latent model states are used to explain the modulation of brain states under different experimental conditions. Reciprocally, neural measures provide data that help constrain cognitive models and adjudicate between competing cognitive models that make similar predictions of behavior. For example, brain measures are related to cognitive model parameters fitted to individual participant data, measures of brain dynamics are related to measures of model dynamics, model parameters are constrained by neural measures, model parameters are used in statistical analyses of neural data, or neural and behavioral data are analyzed jointly within hierarchical modeling framework.

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