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Neural correlates of decision making on whole body yaw rotation: an fNIRS study

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de Winkel,  KN
Department Human Perception, Cognition and Action, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Project group: Motion Perception & Simulation, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Max Planck Institute for Biological Cybernetics, Max Planck Society;

/persons/resource/persons84102

Nesti,  A
Department Human Perception, Cognition and Action, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Max Planck Institute for Biological Cybernetics, Max Planck Society;

/persons/resource/persons83839

Bülthoff,  HH
Project group: Cybernetics Approach to Perception & Action, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Department Human Perception, Cognition and Action, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Max Planck Institute for Biological Cybernetics, Max Planck Society;

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Citation

de Winkel, K., Nesti, A., Ayaz, H., & Bülthoff, H. (2017). Neural correlates of decision making on whole body yaw rotation: an fNIRS study. Neuroscience Letters, 654, 56-62. doi:10.1016/j.neulet.2017.04.053.


Cite as: https://hdl.handle.net/21.11116/0000-0000-C2E7-0
Abstract
Prominent accounts of decision making state that decisions are made on the basis of an accumulation of sensory evidence, orchestrated by networks of prefrontal and parietal neural populations. Here we assess whether these findings generalize to decisions on self-motion.
Participants were presented with whole body yaw rotations of different durations in a 2-Interval-Forced-Choice paradigm, and tasked to discriminate motions on the basis of their amplitude. The cortical hemodynamic response was recorded using functional near-infrared spectroscopy (fNIRS) while participants were performing the task.
The imaging data was used to predict the specific response on individual experimental trials, and to predict whether the comparison stimulus would be judged larger than the reference. Classifier performance on the former variable was negligible. However, considerable performance was achieved for the latter variable, specifically using parietal imaging data. The findings provide support for the notion that activity in the parietal cortex reflects modality independent decision variables that represent the strength of the neural evidence in favor of a decision. The results are encouraging for the use of fNIRS as a method to perform neuroimaging in moving individuals.