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

• Published in: NeuroImage (Orlando, Fla.) Vol. 237; p. 118127
• Main Authors: Paraskevopoulou, Sivylla E., Coon, William G., Brunner, Peter, Miller, Kai J., Schalk, Gerwin
• Format: Journal Article
• Language: English
• Published: United States Elsevier Inc 15.08.2021; Elsevier Limited; Elsevier
• Subjects: Adult; Algorithms; Alpha Rhythm - physiology; Behavior; Cerebral Cortex - physiology; Connectome; Cortical excitability; Cortical network; ECoG; Electrocorticography; Electrodes; Experiments; Female; Gamma Rhythm - physiology; Human subjects; Humans; Latency; Male; Middle Aged; Nerve Net - physiology; Neural networks; Oscillations; Physiology; Population; Psychomotor Performance - physiology; Reaction time; Reaction Time - physiology; Reaction time task; Response time; Young Adult; Reaction time; Cortical excitability; Cortical network; ECoG; Electrocorticography
• ISSN: 1053-8119; 1095-9572; 1095-9572
• DOI: 10.1016/j.neuroimage.2021.118127

•Behavioral reaction-time task elicits electrocorticographic broadband gamma response.•Functional connectivity analysis reveals cortical response trajectories.•Subthreshold broadband gamma activity predicts cortical onset time.•Onset times accumulated across trajectories explain behavioral reaction-time variance. [Display omitted] 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.