Biology subjects

Melcon, M.

Publications and source records attributed to Melcon, M..

6 recordsLinked to original sources

bioRxiv2026

From MEG to low-density EEG: Reliable estimation of brain natural frequencies and their modulation across eyes-open and eyes-closed states

Neural oscillations are central to brain function and communication, yet they are typically characterized in terms of spectral power within predefined frequency bands, potentially obscuring their underlying functional organization. An alternative framework focuses on oscillatory frequency rather than power, revealing that each brain region exhibits a characteristic, or natural, frequency that can be estimated at the voxel level using a data-driven approach. Although this framework has been successfully applied to MEG, its broader use remains limited by cost and availability. Here, we extended this approach to EEG and validated it against MEG-derived maps, assessing its robustness across EEG channel densities (high-density, 64 channels; low-density, 32 channels) and physiological states (eyes open and closed). EEG-derived maps revealed a coherent spatial organization of natural frequencies across the cortex, reproducing the large-scale posterior-to-anterior and medial-to-lateral gradients of increasing frequency previously described with MEG. Differences between MEG and EEG were mainly confined to frontal and temporal regions, likely reflecting the differential sensitivity of the two techniques to neural source configurations, whereas posterior regions showed highly similar patterns. Importantly, this organization remained stable despite reductions in EEG sensor density and was modulated by physiological state, reproducing the well-known posterior alpha dominance during eyes-closed conditions. Together, these findings demonstrate that natural frequency mapping can be extended beyond specialized MEG research environments to low-density EEG settings, offering an accessible and scalable tool for investigating brain oscillations and their alterations in neuropsychiatric conditions.

neuroscience↗

bioRxiv2023

Perception of near-threshold visual stimuli is influenced by pre-stimulus alpha-band amplitude but not by alpha phase

Ongoing brain activity preceding visual stimulation has been suggested to shape conscious perception. The underlying mechanisms are still under debate, although alpha oscillations have been pointed out as the main explanatory candidate. According to the pulsed-inhibition framework, bouts of functional inhibition arise in each alpha cycle, allowing information to be processed in a pulsatile manner. Consequently, it has been hypothesized that perceptual outcome can be influenced by the specific phase of alpha oscillations prior to the stimulus onset, although empirical findings are controversial. In this study, we aimed to shed light on the role of pre-stimulus alpha oscillations in visual perception. To this end, we recorded electroencephalographic (EEG) activity while participants performed three near-threshold visual detection tasks with different attentional involvement: a no-cue task, a non-informative cue task (50% cue validity), and an informative cue task (100% cue validity). Cluster-based permutation statistics were complemented with Bayesian analyses to test the effect of pre-stimulus oscillatory amplitude and phase on visual awareness. We additionally examined whether these effects differed on trials with low and high oscillatory amplitude, as expected from the pulsed-inhibition theory. Our results show a clear effect of pre-stimulus alpha amplitude on conscious perception, but only when alpha fluctuated spontaneously and was not modulated by attention, supporting the notion that alpha-band power indexes neural excitability. In contrast, we did not find any evidence that pre-stimulus alpha phase influences the perceptual outcome, not even when differentiating between low and high amplitude trials. Furthermore, Bayesian analysis provided moderate evidence in favor of the absence of phase effects. Taken together, our results challenge the central theoretical predictions of the pulsed-inhibition framework, at least for the particular experimental conditions used here.

neuroscience↗

bioRxiv2021

The spotlight of attention turns from rhythmic exploration-exploitation to a stable exploitation state

While traditional studies claim that visuospatial attention stays fixed at one location at a time, recent research has rather shown that attention rhythmically fluctuates between different locations at rates of prominent brain rhythms. However, little is known about the temporal dynamics of this fluctuation and, particularly, whether it changes over time. Thus, we addressed this question by investigating how visuospatial attention behaves over space and time. We recorded electroencephalographic activity of twenty-seven human participants while they performed a visuospatial cueing task, where attention was covertly oriented to the left or right visual field. In order to decode the spatial locus of attention from neural activity, we trained and tested a classifier on every timepoint of the orienting period, from the attentional cue to stimulus onset. This resulted in one temporal generalization matrix per participant, which was time-frequency decomposed to identify the sampling rhythm. Finally, a searchlight analysis was conducted to reveal the brain regions responsible for attention allocation. Our results show a dynamic evolution of the attentional spotlight, distinguishing between two states. In an early time window, attention explored both cued and uncued hemifield rhythmically at ~10 Hz. In a later time window attention focused on the cued hemifield. Classification was driven by occipital sources, while frontal regions exclusively became involved just before the spotlight settled onto the cued location. Together, our results define attentional sampling as a quasi-rhythmic dynamic process characterized by an initial rhythmic exploration-exploitation state, which is followed by a stable exploitation state.

neuroscience↗

bioRxiv2021

The natural frequencies of the resting human brain: an MEG-based atlas

Brain oscillations are considered to play a pivotal role in neural communication. However, detailed information regarding the typical oscillatory patterns of individual brain regions is surprisingly scarce. In this study we applied a multivariate data-driven approach to create an atlas of the natural frequencies of the resting human brain on a voxel-by-voxel basis. We analysed resting-state magnetoencephalography (MEG) data from 128 healthy adult volunteers obtained from the Open MEG Archive (OMEGA). Spectral power was computed in source space in 500 ms steps for 82 frequency bins logarithmically spaced from 1.7 to 99.5 Hz. We then applied k-means clustering to detect characteristic spectral profiles and to eventually identify the natural frequency of each voxel. Our results revealed a region-specific organisation of intrinsic oscillatory activity, following both a medial-to-lateral and a posterior-to-anterior gradient of increasing frequency. In particular, medial fronto-temporal regions were characterised by slow rhythms (delta/theta). Posterior regions presented natural frequencies in the alpha band, although with differentiated generators in the precuneus and in sensory-specific cortices (i.e., visual and auditory). Somatomotor regions were distinguished by the mu rhythm, while the lateral prefrontal cortex was characterised by oscillations in the high beta range (>20 Hz). Importantly, the brain map of natural frequencies was highly replicable in two independent subsamples of individuals. To the best of our knowledge, this is the most comprehensive atlas of ongoing oscillatory activity performed to date. Furthermore, the identification of natural frequencies is a fundamental step towards a better understanding of the functional architecture of the human brain.

neuroscience↗

bioRxiv2021

Clock time: a foreign measure to brain dynamics

Human thought is highly flexible, achieved by evolving patterns of brain activity across groups of cells. Neuroscience aims to understand cognition in the brain by analysing these intricate patterns. We argue this goal is impeded by the time format of our data - clock time. The brain is a system with its own dynamics and regime of time, with no intrinsic concern for the human-invented second. Here, we present the Brain Time Toolbox, a software library that retunes electrophysiology data in line with oscillations that orchestrate neural patterns of cognition. These oscillations continually slow down, speed up, and undergo abrupt changes, introducing a disharmony between the brains internal regime and clock time. The toolbox overcomes this disharmony by warping the data to the dynamics of coordinating oscillations, setting oscillatory cycles as the datas new time axis. This enables the study of neural patterns as they unfold in the brain, aiding neuroscientific inquiry into dynamic cognition. In support of this, we demonstrate that the toolbox can reveal results that are absent in a default clock time format.

neuroscience↗

bioRxiv2021

Suppression of alpha-band power underlies exogenous attention to emotional distractors

Alpha-band oscillations (8-14 Hz) are essential for attention and perception processes by facilitating the selection of relevant information. Directing visuospatial endogenous (voluntary) attention to a given location consistently results in a power suppression of alpha activity over occipito-parietal areas contralateral to the attended visual field. In contrast, the neural oscillatory dynamics underlying the involuntary capture of attention, or exogenous attention, are currently under debate. By exploiting the inherent capacity of emotionally salient visual stimuli to capture attention, we aimed to investigate whether exogenous attention is characterized by either a reduction or an increase in alpha-band activity. Electroencephalographic activity was recorded while participants completed a Posner visuospatial cueing task, in which a lateralized image with either positive, negative, or neutral emotional content competed with a target stimulus presented in the opposite hemifield. Compared with trials with no distractors, alpha power was reduced over occipital regions contralateral to distracting images. This reduction of alpha activity turned out to be functionally relevant, as it correlated with impaired behavioural performance on the ongoing task and was enhanced for distractors with negative valence. Taken together, our results demonstrate that visuospatial exogenous attention is characterized by a suppression of alpha-band activity contralateral to distractor location, similar to the oscillatory underpinnings of endogenous attention. Further, these results highlight the key role of exogenous attention as an adaptive mechanism for the efficient detection of biologically salient stimuli. HighlightsO_LIExogenous attention is indexed by alpha suppression contralateral to distractors. C_LIO_LIAlpha power decrease is enhanced by distractors with negative emotional valence. C_LIO_LILower levels of alpha power correlate with poorer task performance accuracy. C_LIO_LIThe negativity bias in exogenous attention might reflect an adaptive mechanism. C_LI

neuroscience↗