Assessing neural activity related to decision-making through flexible odds ratio curves and their derivatives.

Abstract:

:It is well established that neural activity is stochastically modulated over time. Therefore, direct comparisons across experimental conditions and determination of change points or maximum firing rates are not straightforward. This study sought to compare temporal firing probability curves that may vary across groups defined by different experimental conditions. Odds-ratio (OR) curves were used as a measure of comparison, and the main goal was to provide a global test to detect significant differences of such curves through the study of their derivatives. An algorithm is proposed that enables ORs based on generalized additive models, including factor-by-curve-type interactions to be flexibly estimated. Bootstrap methods were used to draw inferences from the derivatives curves, and binning techniques were applied to speed up computation in the estimation and testing processes. A simulation study was conducted to assess the validity of these bootstrap-based tests. This methodology was applied to study premotor ventral cortex neural activity associated with decision-making. The proposed statistical procedures proved very useful in revealing the neural activity correlates of decision-making in a visual discrimination task.

journal_name

Stat Med

journal_title

Statistics in medicine

authors

Roca-Pardiñas J,Cadarso-Suárez C,Pardo-Vazquez JL,Leboran V,Molenberghs G,Faes C,Acuña C

doi

10.1002/sim.4220

subject

Has Abstract

pub_date

2011-06-30 00:00:00

pages

1695-711

issue

14

eissn

0277-6715

issn

1097-0258

journal_volume

30

pub_type

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