4.7 Article

Within-subject reaction time variability: Role of cortical networks and underlying neurophysiological mechanisms

期刊

NEUROIMAGE
卷 237, 期 -, 页码 -

出版社

ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.neuroimage.2021.118127

关键词

Electrocorticography; ECoG; Reaction time; Cortical network; Cortical excitability

资金

  1. NIH [R01EB026439, P41EB018783, U01NS108916, P50MH109429, U24NS109103, KL2TR002379]
  2. US Army Research Office [W911NF1410440]
  3. Fondazione Neurone

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Variations in reaction time have long been studied in human behavior, but the neural basis for within-subject and within-task variability has been minimally explored. This study used direct cortical recordings to investigate the variance in behavioral reaction time, showing that population-level neural activity differences in the task-related cortical network can explain a significant portion of the variability in reaction time. Specific brain region latencies and cumulative latency differences across the cortical network were found to contribute to reaction time variability.
Variations in reaction time are a ubiquitous characteristic of human behavior. Extensively documented, they have been successfully modeled using parameters of the subject or the task, but the neural basis of behavioral reaction time that varies within the same subject and the same task has been minimally studied. In this paper, we investigate behavioral reaction time variance using 28 datasets of direct cortical recordings in humans who engaged in four different types of simple sensory-motor reaction time tasks. Using a previously described technique that can identify the onset of population-level cortical activity and a novel functional connectivity algorithm described herein, we show that the cumulative latency difference of population-level neural activity across the task-related cortical network can explain up to 41% of the trial-by-trial variance in reaction time. Furthermore, we show that reaction time variance may primarily be due to the latencies in specific brain regions and demonstrate that behavioral latency variance is accumulated across the whole task-related cortical network. Our results suggest that population-level neural activity monotonically increases prior to movement execution, and that trial-by-trial changes in that increase are, in part, accounted for by inhibitory activity indexed by low-frequency oscillations. This pre-movement neural activity explains 19% of the measured variance in neural latencies in our data. Thus, our study provides a mechanistic explanation for a sizable fraction of behavioral reaction time when the subject's task is the same from trial to trial.

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