EEG anticipatory activity depends on sensory modality

Perceptual anticipation is known to impact the reaction time of decisions. While anticipatory patterns have been identified in human brain activity, the single-trial neural signature of anticipation remains unexplored. Similarly, past studies have underlined an effect of pre-stimulus alpha-band activity on reaction times. Still, it remains unknown whether this activity is stimulus-specific or rather acts as a general indicator of readiness. This study aimed to determine whether human participants expected a visual or an auditory stimulus at the single-trial level in both cued and uncued trials. We show that pre-stimulus brain activity entails information about the expected upcoming stimulus, and that the information content can be extracted from single-trial brain activity. Behavioral analyses helped uncover the link between correct anticipation and shifts in decision strategy, and additionally validated the classification of uncued trials. This understanding of single-trial stimulus-specific neural signatures of anticipation can significantly impact cognitive neuroscience, human-computer interaction, and neuroergonomics research, enabling the development of real-time systems capable of predicting and adapting to an individuals anticipated stimuli, thereby enhancing task performance and user experience in diverse applications ranging from adaptive interfaces to clinical interventions. Novelty and SignificanceWith a focus on uncovering single-trial neural signatures of anticipation, this study aims to explore the specificity of pre-stimulus brain activity to expected visual or auditory stimuli in both cued and uncued trials, i.e. whether participants are informed about the upcoming stimulus or not. Our research seeks to contribute to the fundamental understanding of human cognition by elucidating the informational content embedded in anticipatory brain patterns. The insights gained hold promise in advancing fields like cognitive neuroscience and human-computer interaction, paving the way for innovative applications in adaptive interface design, real-time systems, and personalized interventions.