Background: Previous research has shown that temporal prediction processes are associated with phase resets of low-frequency delta oscillations in a network of parietal, sensory and frontal areas during non-rhythmic sensory stimulation. Transcranial alternating current stimulation (tACS) modulates perceptually relevant brain oscillations in a frequency and phase-specific manner, allowing the assessment of their functional qualities in certain cognitive functions like temporal prediction.
Objective: We addressed the relation between oscillatory activity and temporal prediction by using tACS to manipulate brain activity in a sinusoidal manner. This enables the investigation of the relevance of low-frequency oscillations' phase for temporal prediction.
Methods: Delta tACS was applied over the left and right parietal cortex in two separate unimodal and crossmodal temporal prediction experiments. Participants judged either the visual or the tactile reappearance of a uniformly moving visual stimulus, which shortly disappeared behind an occluder. tACS was applied with six different phase shifts relative to sensory stimulation in both experiments. Additionally, a computational model was developed and analysed to elucidate oscillation-based functional principles for the generation of temporal predictions.
Results: Only in the unimodal experiment, the application of delta tACS resulted in a phase-dependent modulation of temporal prediction performance. By considering the effect of sustained tACS in the computational model, we demonstrate that the entrained dynamics can phase-specifically modulate temporal prediction accuracy.
Conclusion: Our results suggest that delta oscillatory phase contributes to unimodal temporal prediction. Crossmodal prediction may involve a broader brain network or cross-frequency interactions, extending beyond parietal delta phase and the scope of our current stimulation design.
Keywords: Non-invasive brain stimulation; Phase-specificity; Temporal prediction; Transcranial alternating current stimulation.
Copyright © 2024. Published by Elsevier Inc.