Brain signatures of predictive and reactive strategies in a simple delayed reaction time task: an EEG study
Year: 2025
Type: article
Abstract: In a simple pre-cued sensorimotor task, two behavioral patterns emerge spontaneously on a trial-by-trial basis, characterized by a bimodal distribution. The early and the late patterns are likely the product of two distinct mutually exclusive strategies: predictive and reactive. Predictive behavior is driven by an internally generated, top-down mechanism, allowing participants to estimate the timing of the target stimulus. In contrast, reactive behavior relies on an externally-driven, bottom-up mechanism, where participants wait for the target stimulus before responding. In this exploratory study, we aimed to further validate the existence of these two strategies by showing they are distinguishable based on EEG patterns, analyzed in both temporal and frequency domains using different metrics, including event-related potentials (ERP), time-frequency representations, modulation index, inter-trial phase coherence, and connectivity. Early behavioral responses showed an augmented ERP, named contingent negative variation, in comparison to late behavioral responses. This validate the hypothesis of a top-down, predictive mechanism, based on temporal estimations. In addition, we showed that EEG dynamics differentiated the two conditions in the SET period. This result further corroborates the hypothesis that the commitment to one strategy does not occur before trial onset but rather builds up during the SET period. When analyzing the electrical activity after the GO-signal, we observed that early and late responses are associated with distinct EEG features, with early behavior displaying feature typical of top-down processes. In our experiment, the two behaviors occurred naturally, without external manipulations that could introduce confounding cognitive demands and obscure genuine differences in EEG patterns between strategy-dependent conditions.
Source: NeuroImage
Institution: University of Trento
Language: English
Subfield: Cognitive Neuroscience
Field: Neuroscience
Domain: Life Sciences
Open Access status: gold
Estimated APC paid: $3,540
Funder: Università degli Studi di Trento
OpenAlex ID: W4411373131