Biology subjects

Deodato, M.

Publications and source records attributed to Deodato, M..

4 recordsLinked to original sources

bioRxiv2026

Oscillatory and aperiodic neural dynamics shape temporal perception and weighting of perceptual priors in ADHD profiles

Attention-deficit/hyperactivity disorder (ADHD) is characterized by an atypically compressed sense of time, yet the neural mechanisms underlying this atypical temporal perception remain poorly understood. Temporal perception depends on the brains ability to organize sensory input into coherent experiences, ensuring perceptual stability despite uncertainty. Oscillations in the alpha band (8-13 Hz) and aperiodic 1/f dynamics have been proposed as key neural mechanisms through which the visual system orchestrates sensory information over time. Individuals with ADHD show atypicalities in these neural dynamics, but how these features relate to ADHD differences in temporal processing remains unexplored. Here, we combined a sustained visual temporal integration task with resting-state EEG to test whether oscillatory and aperiodic neural dynamics jointly account for temporal processing performance across neurotypical participants with self-reported ADHD traits (n = 83). Higher ADHD features in both inattentive and hyperactive-impulsive domains were associated with narrower temporal binding windows and reduced serial dependence on prior perception, indicating sharper temporal resolution but diminished perceptual stability. Resting-state EEG revealed systematically faster individual alpha frequency (IAF) and flatter aperiodic spectra in individuals with higher ADHD traits. Mediation analyses showed that faster IAF explained ADHD-related reductions in temporal integration thresholds and serial dependence, whereas increased neural noise selectively amplified perceptual history-dependent biases. These findings reveal distinct oscillatory and aperiodic neural pathways through which ADHD features shape temporal perception, suggesting a multidimensional neural architecture underlying atypical temporal processing in ADHD.

neuroscience↗

bioRxiv2026

Alpha oscillations and aperiodic neural dynamics jointly predict visual temporal resolution, confidence, and dependence on prior experience

Perception requires integrating sensory input over time to construct coherent experiences. Alpha oscillations have been proposed to define the temporal resolution of perception, yet empirical evidence remains inconsistent. Here we combined a sustained visual integration paradigm with resting-state EEG to investigate how oscillatory and aperiodic neural dynamics jointly shape temporal perception. Participants (n=83) viewed alternating gratings that varied in alternation speed, producing the perception of either a fused plaid (integration) or two interchanging gratings (segregation). Faster individual alpha rhythms were associated with narrower temporal integration windows, and a steeper aperiodic spectrum predicted greater perceptual precision. Moreover, individuals with slower alpha frequencies and flatter spectra showed stronger reliance on prior judgments, suggesting reduced sensory precision and increased weighting of recent experience. Subjective confidence increased with faster alpha rhythms, reflecting the clarity of sensory evidence and its consistency with prior responses. Together, these findings show that the perceptual interpretation, confidence and previous experience effects in temporal integration reflect the joint influence of alpha rhythms and aperiodic neural activity. Mechanistically, faster alpha rhythms and lower neural noise may enhance perceptual resolution by generating more precise sampling frames per time unit, leading to finer temporal perception, reduced reliance on prior experience, and greater confidence.

neuroscience↗

bioRxiv2025

Phase-Dependent EEG Decoding of Continuous Visual Stimuli

Neural oscillations support cognition and perception by organizing information across oscillatory cycles, such that different phases correspond to distinct computational states. Although animal studies strongly support this view, evidence in humans is mixed and largely based on brief, flashed stimuli. Here, we tested whether alpha oscillations, the dominant human brain rhythm, rhythmically modulate visual encoding during sustained perception. EEG was recorded while participants viewed long-lasting (2s) Gabor patches. Using a phase-dependent decoding approach, we extracted EEG activity at specific alpha phases and quantified stimulus decoding accuracy. Decoding performance varied systematically with alpha phase, following a smooth unimodal profile that peaked over occipito-parietal electrodes. These effects emerged well after stimulus onset, indicating a sustained modulation of visual processing during continuous input. Our findings demonstrate that visual information is encoded more accurately at specific alpha phases. This provides direct evidence that sensory processing is gated by intrinsic brain activity and introduces a generalizable decoding framework for linking oscillatory phase to neural information processing.

neuroscience↗

bioRxiv2023

Aperiodic EEG predicts variability of visual temporal processing

The human brain exhibits both oscillatory and aperiodic, or 1/f, activity. Although a large body of research has focused on the relationship between brain rhythms and sensory processes, aperiodic activity has often been dismissed as noise and functionally irrelevant. Prompted by recent findings linking aperiodic activity to the balance between neural excitation and inhibition, we investigated its effects on the temporal resolution of perception. We recorded EEG from participants during resting state and a task in which they detected the presence of two flashes separated by variable inter-stimulus intervals. Two-flash discrimination accuracy typically follows a sigmoid function whose steepness reflects perceptual variability or inconsistent integration/segregation of the stimuli. We found that individual differences in the steepness of the psychometric function correlated with EEG aperiodic exponents over posterior scalp sites. In other words, participants with higher levels of aperiodic activity (i.e., neural excitation) exhibited increased sensory noise, resulting in shallower psychometric curves. Our finding suggest that aperiodic EEG is linked to sensory integration processes usually attributed to the rhythmic inhibition of neural oscillations. Overall, this correspondence between aperiodic neural excitation and behavioral measures of sensory noise provides a more comprehensive explanation of the relationship between brain activity and sensory integration and represents an important extension to theories of how the brain samples sensory input over time.

neuroscience↗