Turner, BM;
Forstmann, BU;
Love, BC;
Palmeri, TJ;
Van Maanen, L;
(2017)
Approaches to analysis in model-based cognitive neuroscience.
Journal of Mathematical Psychology
, 76
(B)
pp. 65-79.
10.1016/j.jmp.2016.01.001.
Preview |
Text
Approaches to analysis in model-based cognitive neuroscience.pdf Download (1MB) | Preview |
Abstract
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.
| Type: | Article |
|---|---|
| Title: | Approaches to analysis in model-based cognitive neuroscience |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1016/j.jmp.2016.01.001 |
| Publisher version: | http://doi.org/10.1016/j.jmp.2016.01.001 |
| Language: | English |
| Additional information: | Copyright © 2016 Elsevier Inc. All rights reserved. This manuscript version is made available under a Creative Commons Attribution Non-commercial Non-derivative 4.0 International license (CC BY-NC-ND 4.0). This license allows you to share, copy, distribute and transmit the work for personal and non-commercial use providing author and publisher attribution is clearly stated. Further details about CC BY licenses are available at http://creativecommons.org/ licenses/by/4.0. Access may be initially restricted by the publisher. The published article is available from the journal website at http://dx.doi.org/10.1016/j.jmp.2016.01.001 |
| Keywords: | Model-based cognitive neuroscience; linking; analysis methods |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > Div of Psychology and Lang Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > Div of Psychology and Lang Sciences > Experimental Psychology |
| URI: | https://discovery.ucl.ac.uk/id/eprint/1492919 |
Archive Staff Only
 |
View Item |
