Article
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Preserved in Portico This version is not peer-reviewed
Visualization of the Dynamic Brain Activation Pattern During a Decision Making Task
Version 1
: Received: 12 September 2022 / Approved: 15 September 2022 / Online: 15 September 2022 (03:46:46 CEST)
A peer-reviewed article of this Preprint also exists.
Parmar, H.; Walden, E. Visualization of the Dynamic Brain Activation Pattern during a Decision-Making Task. Brain Sci. 2022, 12, 1468. Parmar, H.; Walden, E. Visualization of the Dynamic Brain Activation Pattern during a Decision-Making Task. Brain Sci. 2022, 12, 1468.
Abstract
Decision making is a complex process involving various parts of the brain which are active during different times. It is challenging to measure externally the exact instance when any given region becomes active during the decision-making process. Here we try to extract and visualize the dynamic functional brain activation information from the observed fMRI data. We propose the use of a regularized deconvolution model to simultaneously map various activation regions within the brain and track how different activation regions changes with time. Thus, providing both spatial and temporal brain activation information. The activation information can then be further analyzed as per need and requirements. The proposed technique was validated using simulated data and then applied to a simple decision-making task for identification of various brain regions involved in different stages of decision making. The visualization aspect of the algorithm allows us to actually see the flow of activation (and deactivation) in form of a motion picture. The dynamic estimate may aid in understanding the causality of activation between various brain regions in a better way.
Keywords
decision making; dynamic activation; fMRI; visualization; deconvolution
Subject
Social Sciences, Behavior Sciences
Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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