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Joint Models of Neural and Behavioral Data

  • Presents a one-of-its-kind flexible Bayesian framework for combining neural and cognitive models
  • Provides an approach that reveals interactions between behavioral and neural parameters
  • Offers tools and resources for the application of the joint modeling approach

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Table of contents (7 chapters)

  1. Front Matter

    Pages i-xiii
  2. Motivation

    • Brandon M. Turner, Birte U. Forstmann, Mark Steyvers
    Pages 1-12
  3. A Tutorial on Joint Modeling

    • Brandon M. Turner, Birte U. Forstmann, Mark Steyvers
    Pages 13-37
  4. Assessing Model Performance with Generalization Tests

    • Brandon M. Turner, Birte U. Forstmann, Mark Steyvers
    Pages 39-51
  5. Applications

    • Brandon M. Turner, Birte U. Forstmann, Mark Steyvers
    Pages 53-73
  6. Future Directions

    • Brandon M. Turner, Birte U. Forstmann, Mark Steyvers
    Pages 75-84
  7. Other Approaches

    • Brandon M. Turner, Birte U. Forstmann, Mark Steyvers
    Pages 85-96
  8. Conclusions

    • Brandon M. Turner, Birte U. Forstmann, Mark Steyvers
    Pages 97-99
  9. Back Matter

    Pages 101-109

About this book

This book presents a flexible Bayesian framework for combining neural and cognitive models. Traditionally, studies in cognition and cognitive sciences have been done by either observing behavior (e.g., response times, percentage correct, etc.) or by observing neural activity (e.g., the BOLD response). These two types of observations have traditionally supported two separate lines of study, which are led by two different cognitive modelers. Joining neuroimaging and computational modeling in a single hierarchical framework allows the neural data to influence the parameters of the cognitive model and allows behavioral data to constrain the neural model. This Bayesian approach can be used to reveal interactions between behavioral and neural parameters, and ultimately, between neural activity and cognitive mechanisms. Chapters demonstrate the utility of this Bayesian model with a variety of applications, and feature a tutorial chapter where the methods can be applied to an example problem. The book also discusses other joint modeling approaches and future directions.

Joint Models of Neural and Behavioral Data will be of interest to advanced graduate students and postdoctoral candidates in an academic setting as well as researchers in the fields of cognitive psychology and neuroscience. 


Authors and Affiliations

  • Department of Psychology, The Ohio State University, Columbus, USA

    Brandon M. Turner

  • Cognitive Science Center, University of Amsterdam, Amsterdam, The Netherlands

    Birte U. Forstmann

  • Department of Cognitive Sciences, University of California, Irvine, Irvine, USA

    Mark Steyvers

About the authors

Brandon Turner is an Assistant Professor in the Psychology Department at The Ohio State University. His research interests include dynamic models of cognition and perceptual decision making, efficient methods for performing likelihood-free and likelihood-informed Bayesian inference, and unifying behavioral and neural explanations of cognition. His current focus is on understanding how external factors such as the environment, and internal factors such as working memory interact to shape an observer's perception of the world, and ultimately how this perception drives their decisions. Dr. Turner is an editorial board member for the journal Decision.

Birte U. Forstmann is a Professor for Cognitive Neurosciences at the University of Amsterdam. She earned her PhD in 2006 at the Max Planck Institute for Human Cognitive and Brain Sciences in Leipzig, Germany. After completing her postdoc in 2008 at the University of Amsterdam, she became tenured Research Fellow at the Cognitive Science Center Amsterdam with the focus of model-based cognitive neurosciences. Since then she has contributed to a range of topics in cognitive neuroscience, experimental psychology, mathematical psychology, and lately also in quantiative neuroanatomy. Despite its diversity, her work is motivated by a single strong conviction, namely that behavioral data and brain measurements need to make contact with psychological theory via concrete mathematical models of latent cognitive processes.

Mark Steyvers is a professor in the Department of Cognitive Sciences at the University of California, Irvine. He also holds joint faculty appointments with the Department of Computer Science and the Department of Psychology and Social Behavior at the University of California, Irvine. Dr. Steyvers is Associate Editor for Computational Brain & Behavior and consulting editor for Psychological Review and an editorial board member for Behavior Research Methods


Bibliographic Information

Buy it now

Buying options

eBook USD 64.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book USD 84.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Other ways to access