Journal
JOURNAL OF MATHEMATICAL PSYCHOLOGY
Volume 76, Issue -, Pages 65-79Publisher
ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.jmp.2016.01.001
Keywords
Model-based cognitive neuroscience; Linking; Analysis methods
Categories
Funding
- NIH [R01-EY021833, P30-EY08126]
- NSF Temporal Dynamics of Learning Center [SMA-1041755]
- Alan Turing Institute [TU/B/000086] Funding Source: researchfish
- Wellcome Trust [106931/Z/15/Z] Funding Source: researchfish
- Wellcome Trust [106931/Z/15/Z] Funding Source: Wellcome Trust
Ask authors/readers for more resources
Our understanding of cognition has been advanced by two traditionally non-overlapping and non interacting groups. Mathematical psychologists rely on behavioral data to evaluate formal models of cognition, whereas cognitive neuroscientists rely on statistical models to understand patterns of neural activity, often without any attempt to make a connection to the mechanism supporting the computation. Both approaches suffer from critical limitations as a direct result of their focus on data at one level of analysis (cf. Marr, 1982), and these limitations have inspired researchers to attempt to combine both neural and behavioral measures in a cross-level integrative fashion. The importance of solving this problem has spawned several entirely new theoretical and statistical frameworks developed by both mathematical psychologists and cognitive neuroscientists. However, with each new approach comes a particular set of limitations and benefits. In this article, we survey and characterize several approaches for linking brain and behavioral data. We organize these approaches on the basis of particular cognitive modeling goals: (1) using the neural data to constrain a behavioral model, (2) using the behavioral model to predict neural data, and (3) fitting both neural and behavioral data simultaneously. Within each goal, we highlight a few particularly successful approaches for accomplishing that goal, and discuss some applications. Finally, we provide a conceptual guide to choosing among various analytic approaches in performing model-based cognitive neuroscience. (C) 2016 Elsevier Inc. All rights reserved.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available