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Modeling the BOLD correlates of competitive neural dynamics

Bonaiuto, James and Arbib, Michael A. (2014) Modeling the BOLD correlates of competitive neural dynamics. Neural Networks, 49 . pp. 1-10. ISSN 0893-6080. http://resolver.caltech.edu/CaltechAUTHORS:20140306-100906446

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Abstract

Winner-take-all models are commonly used to model decision-making tasks where one outcome must be selected from several competing options. Related random walk and diffusion models have been used to explain such processes and apply them to psychometric and neurophysiological data. Recent model-based fMRI studies have sought to find the neural correlates of decision-making processes. However, due to the fact that hemodynamic responses likely reflect synaptic rather than spiking activity, the expected BOLD signature of winner-take-all circuits is not clear. A powerful way to integrate data from neurophysiology and brain imaging is by developing biologically plausible neural network models constrained and testable by neural and behavioral data, and then using Synthetic Brain Imaging — transforming the output of simulations with the model to make predictions testable against neuroimaging data. We developed a biologically realistic spiking winner-take-all model comprised of coupled excitatory and inhibitory neural populations. We varied the difficulty of a decision-making task by adjusting the contrast, or relative strength of inputs representing two response options. Synthetic brain imaging was used to estimate the BOLD response of the model and analyze its peak as a function of input contrast. We performed a parameter space analysis to determine values for which the model performs the task accurately, and given accurate performance, the distribution of the input contrast–BOLD response relationship. This underscores the need for models grounded in neurophysiological data for brain imaging analyses which attempt to localize the neural correlates of cognitive processes based on predicted BOLD responses.


Item Type:Article
Related URLs:
URLURL TypeDescription
http://dx.doi.org/10.1016/j.neunet.2013.09.001DOIArticle
http://www.sciencedirect.com/science/article/pii/S0893608013002347PublisherArticle
Additional Information:© 2013 Elsevier Ltd. Received 13 June 2013; received in revised form 2 September 2013; accepted 4 September 2013.
Subject Keywords:Neural network model; FMRI, decision-making; Winner-take-all; Synthetic brain imaging
Record Number:CaltechAUTHORS:20140306-100906446
Persistent URL:http://resolver.caltech.edu/CaltechAUTHORS:20140306-100906446
Official Citation:Bonaiuto, J., & Arbib, M. A. (2014). Modeling the BOLD correlates of competitive neural dynamics. Neural Networks, 49(0), 1-10. doi: http://dx.doi.org/10.1016/j.neunet.2013.09.001
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:44173
Collection:CaltechAUTHORS
Deposited By: Jason Perez
Deposited On:07 Mar 2014 19:18
Last Modified:07 Mar 2014 19:18

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