Biology subjects

Veniero, D.

Publications and source records attributed to Veniero, D..

5 recordsLinked to original sources

bioRxiv2026

Alpha oscillations support attentional orienting while beta supports perceptual decision-making.

Visuospatial attention enables the selective allocation of cognitive resources to relevant stimuli. A well-established neural signature of attentional shifts is the lateralised modulation of occipito-parietal alpha power, with decreases over the hemisphere contralateral to the attended location and increases over the ipsilateral hemisphere. However, growing evidence suggests that multiple oscillatory mechanisms contribute to attentional deployment, including beta-band activity. A key unresolved question that remains is whether the same neural rhythms support the deployment of attention and the perceptual decisions that follow. Here, we recorded EEG in 26 participants (22 females) during covert visuospatial orienting and investigated how alpha- and beta-band dynamics relate to behavioural measures, namely perceptual sensitivity (d') and decision criterion (c), and whether attended location could be preferentially decoded from alpha- or beta-band activity. We found that pre-target beta phase significantly predicted decision criterion at earlier pre-target intervals, whereas perceptual sensitivity was predicted closer to target onset, suggesting that beta is related to both sensory gain and the perceptual decision. In contrast, decoding analyses revealed that attended location was most strongly discriminable from alpha-band activity, as confirmed by time-frequency analysis of decoding accuracy. Together, these findings suggest a functional dissociation between oscillatory mechanisms supporting attentional orienting and perceptual decision-making. Whereas alpha-band activity primarily reflects the allocation of attention, beta-band dynamics predict trial-by-trial variability in perceptual decisions. Significance StatementAlthough alpha oscillations are commonly viewed as the principal neural mechanism underlying visuospatial attention, mounting evidence shows that such a complex function requires the involvement of other brain rhythms. Our findings show that different components of attention are associated with distinct brain rhythms. While alpha activity primarily reflects where attention is allocated, beta oscillations relate to how sensory information is transformed into perceptual decisions. These results suggest that attentional orienting and perceptual decision-making rely on dissociable neural processes, providing a comprehensive account of how brain oscillations support goal-directed behaviour.

neuroscience↗

bioRxiv2024

Top-down and bottom-up interactions rely on nested brain oscillations.

Adaptive visual processing is enabled through the dynamic interplay between top-down and bottom-up (feedback/feedforward) information exchange, presumably propagated through brain oscillations. Here we causally tested for the oscillatory mechanisms governing this interaction in the visual system. Using concurrent TMS-EEG, we emulated top-down signals by a single TMS-pulse over the Frontal Eye Field (right-FEF), while manipulating the strength of sensory input through the presentation of moving concentric gratings (compared to a control-TMS site). FEF-TMS without sensory input led to a top-down controlled occipital phase-realignment, alongside higher fronto-occipital phase-connectivity, in the alpha/beta-band. Sensory input in the absence of FEF-TMS increased occipital gamma activity. Crucially, testing the interaction between top-down and bottom-up processes (FEF-TMS during sensory input) revealed an increased nesting of the bottom-up gamma activity in the alpha/beta-band cycles. This establishes a causal link between phase-to-power coupling and top-down modulation of feedforward signals, providing novel mechanistic insights into how attention interacts with sensory input at the neural level, shaping rhythmic sampling.

neuroscience↗

bioRxiv2023

Developmental changes in individual alpha frequency: Recording EEG data during public engagement events

Statistical power in cognitive neuroimaging experiments is often very low. Low sample size can reduce the likelihood of detecting real effects (false negatives) and increase the risk of detecting non-existing effects by chance (false positives). Here we document our experience of leveraging a relatively unexplored method of collecting a large sample size for simple electroencephalography (EEG) studies: by recording EEG in the community during public engagement and outreach events. We collected data from 346 participants (189 females, age range 6-76 years) over 6 days, totalling 29 hours, at local science festivals. Alpha activity (6-15 Hz) was filtered from 30 seconds of signal, recorded from a single electrode placed between the occipital midline (Oz) and inion (Iz) while participants rested with their eyes closed. A total of 289 good quality datasets were obtained. Using this community-based approach, we were able to replicate controlled, lab-based findings: IAF increased during childhood, reaching a peak frequency of 10.28 Hz at 28.1 years old, and slowed again in middle and older age. Total alpha power decreased linearly, but the aperiodic-adjusted alpha power did not change over the lifespan. Aperiodic slopes and intercepts were highest in the youngest participants. There were no associations between these EEG indexes and self-reported fatigue, measured by the Multidimensional Fatigue Inventory. Finally, we present a set of important considerations for researchers who wish to collect EEG data within public engagement and outreach environments.

neuroscience↗

bioRxiv2018

Subjective perceptual experience tracks the neural signature of sensory evidence accumulation during decision formation

How neural representations of low-level visual information are accessed by higher-order processes to inform decisions and give rise to conscious experience is a longstanding question. Research on perceptual decision making has revealed a late event-related EEG potential (the Centro-Parietal Positivity, CPP) to be a correlate of the accumulation of sensory evidence. We tested to what extent this evidence accumulation signal is driven by externally presented (physical) versus internally experienced (subjective) sensory evidence. The results show that the known relationship between external evidence and the evidence accumulation signal (reflected in the CPP amplitude) is mediated by the level of subjective awareness. Additionally, the CPP closely tracks the subjective perceptual evidence during both correct and incorrect trials. Hence, a remarkably close relationship exists between the evidence accumulation process (i.e. CPP) and subjective perceptual experience, suggesting that neural decision processes and components of conscious experience are tightly linked.

neuroscience↗

bioRxiv2018

Frequency and power of human alpha oscillations drift systematically and independently with time-on-task

Oscillatory neural activity is a fundamental characteristic of the mammalian brain spanning multiple levels of spatial and temporal scale. Current theories of neural oscillations and analysis techniques employed to investigate their functional significance are based on an often implicit assumption: In the absence of experimental manipulation, the spectral content of any given EEG- or MEG-recorded neural oscillator remains approximately stationary over the course of a typical experimental session (~1 hour), spontaneously fluctuating only around its dominant frequency. Here, we examined this assumption for ongoing neural oscillations in the alpha-band (8:13 Hz). We found that alpha peak frequency systematically decreased over time, while alpha-power increased. Intriguingly, these systematic changes showed partial independence of each other: Statistical source separation (independent component analysis) revealed that while some alpha components displayed concomitant power increases and peak frequency decreases, other components showed either unique power increases or frequency decreases. Interestingly, we also found these components to differ in frequency. Components that showed mixed frequency/power changes oscillated primarily in the lower alpha-band (~8-10Hz), while components with unique changes oscillated primarily in the higher alpha-band (~9-13Hz). Our findings provide novel clues on the time-varying intrinsic properties of large-scale neural networks as measured by M/EEG, with implications for the analysis and interpretation of studies that aim at identifying functionally relevant oscillatory networks or at driving them through external stimulation.

neuroscience↗