Biology subjects

Bonnefond, M.

Publications and source records attributed to Bonnefond, M..

10 recordsLinked to original sources

bioRxiv2026

Low-Frequency activity shapes fine-scale information routing in the early visual cortex

Visual processing requires flexible routing of task-relevant information across cortical hierarchies. One proposed mechanism is nested oscillatory activity, in which low-frequency rhythms dynamically modulate local excitability and inter-areal communication. However, the specific predictions of this framework have not been tested during active stimulus processing at fine spatial and temporal scales. Here, we reanalyzed local field potentials (LFPs) and multi-unit activity (MUA) recorded from V1 and V4 in macaque monkeys performing a figure-ground segregation task. We show that alpha-band activity in V1 carries information about the position of the figure and the orientation of the stimulus with fine spatial specificity within a transient post-stimulus window, a period that coincides with the emergence of figure-ground modulation and the dominant V4[->]V1 feedback. During this window, both local spiking activity and inter-areal coupling between V1 and V4 depended on alpha amplitude and on the instantaneous V1-V4 phase difference, indicating that low-frequency synchronization shapes effective communication between cortical populations. Together, these findings support the view that alpha-band activity reflect fine-scale information routing during visual processing through coordinated modulation of local excitability and hierarchical feedback interactions.

neuroscience↗

bioRxiv2026

Distinct SMA beta bursts support the development of anticipatory postural control in children

To produce smooth and coordinated movements, the brain generates anticipatory postural adjustments (APA) - feedforward motor commands that counteract predicted postural disturbances before they occur. Although APA emerge early in life, their maturation extends into early adulthood, yet little is known about the underlying neural mechanisms. Using magnetoencephalography during a naturalistic bimanual load-lifting task, we investigated anticipatory postural control in children aged 7-12 years. In this task, lifting a load from the contralateral postural forearm induces upward elbow rotation, which is anticipatorily counteracted by inhibition of Biceps brachii postural activity, stabilizing forearm posture. Surprisingly, despite greater variability in inhibition timing and less efficient forearm stabilization in children, the mechanism of anticipatory inhibition was consistent with that recently described in adults: it was mediated by transient oscillatory beta bursts (19-24 Hz), associated with reduced supplementary motor area (SMA) excitability indexed by high-gamma (90-130 Hz) power suppression, and preceded by directed influences from lateral prefrontal and ventral premotor cortex. However, burst frequency was lower in children, and an additional APA mechanism was recruited: while 19-24 Hz bursts were linked to immediate SMA suppression and stronger muscle inhibition, higher-frequency bursts (24-29 Hz) were associated with delayed ([~]100 ms) SMA suppression mediated by alpha activity (8 Hz), which attenuated post-inhibition forearm instability. These results reveal that children in middle childhood already engage adult-like neural mechanisms for anticipatory inhibition, while additionally recruiting a compensatory mechanism to counteract postural imprecision, providing new insights into the neural basis of APA maturation and its alteration in neurodevelopmental conditions.

neuroscience↗

bioRxiv2025

Dynamic and task-dependent decoding of the human attentional spotlight from MEG

Attention is a fundamental mechanism enabling the brain to overcome its limited capacity for parallel processing. In non-human primates, invasive electrophysiology has shown that attentional selection operates rhythmically, primarily within the alpha ([~]8-12 Hz) and theta ([~]4-5 Hz) bands. Whether such finely resolved control signals can be captured non-invasively in humans, and how they adapt to changing task demands, remains unclear. Using high-precision magnetoencephalography (MEG) combined with machine learning, we decoded the spatial locus of covert attention in humans performing three variants of a spatial cueing task that manipulated cue validity as well invalid trial switching rules. Spatial attention could be decoded from whole-brain MEG activity at both static and time-resolved scales, with accuracies significantly above chance (N = 30). Decoding performance decreased as cue validity was reduced, indicating that task structure shapes attentional engagement. Analysis of decoding trajectories revealed rhythmic fluctuations at [~]8-12 Hz across all tasks, demonstrating alpha-band sampling of attention. Pre-target attention became increasingly focused on the cued side, especially in the 100% Valid condition, consistent with proactive orienting. Furthermore, individual and task-specific differences in decoding strength correlated with task-variations in behavioral performance, linking the accuracy of neural attention codes to both discrimination accuracy and reaction time. These findings demonstrate that MEG can non-invasively capture dynamic, task-dependent fluctuations in spatial attention that parallel those observed in non-human primates. They reveal that attentional demands reshape the neural code for attention, modulate rhythmic sampling, and influence behavioral efficiency. This work bridges invasive primate and non-invasive human research and establishes MEG-based decoding of attention as a promising tool for mechanistic and clinical applications, including neurofeedback and attention-related interventions.

neuroscience↗

bioRxiv2025

Alpha-Beta oscillations implement inhibition of the ventral attention network during an attention task

Selective attention is a crucial mechanism that allows us to focus on relevant information while ignoring irrelevant information. Although extensive literature has proposed that alpha oscillations (7-14 Hz) suppress distractor processing, recent studies have questioned this role. In this magnetoencephalography (MEG) study, we used a modified Stroop task to investigate whether (1) alpha oscillations are associated with functional inhibition in higher-order visual regions and the ventral attention network (VAN), and (2) alpha phase adjusts in anticipation of relevant and irrelevant stimuli. We found no significant increase in pre-stimulus alpha power or phase adjustment over higher-order visual regions in the attend-color condition, consistent with the absence of a behavioral Stroop effect. However, we observed elevated alpha-beta power (10-20 Hz) in the VAN during both attend-color and attend-word conditions compared to control conditions, occurring before stimulus onset. Higher alpha-beta power in the right temporo-parietal junction correlated with faster reaction times, suggesting that inhibition of this network region facilitates task performance. This alpha-beta modulation in the VAN may represent a general mechanism for resisting distraction, preventing attentional capture by irrelevant information regardless of task condition. Additionally, we found enhanced theta power (4 Hz) over the VAN and left medial frontal gyrus (part of the cognitive control network) in both experimental conditions. Theta power correlated with improved reaction times across these regions. Furthermore, theta activity in the left medial frontal gyrus synchronized with VAN nodes, potentially indicating cross-network interaction between cognitive control and attention systems.

neuroscience↗

bioRxiv2025

High-beta bursts in SMA mediate anticipatory muscle inhibition in a bimanual motor task

In motor networks, inhibition has been associated with oscillatory activity in the mu (8-12 Hz) or beta (13-30 Hz) bands, yet how these rhythms ultimately influence muscle activity remains unclear. The Bimanual Load-Lifting Task (BLLT) elicits anticipatory inhibition of the elbow flexors in the load-supporting arm during voluntary load-lifting, providing a suitable model to study oscillatory mechanisms of muscle inhibition. We recorded magnetoencephalography (MEG) in adult participants performing the BLLT. Optimal postural stabilization occurred when Biceps brachii inhibition preceded unloading by [~]10-40 ms. Stronger muscle inhibition within this time window was associated with reduced high-gamma (90-130 Hz) power, potentially reflecting reduced excitability, and increased high-beta power in the contralateral Supplementary Motor Area (SMA), with high-gamma power reduction partially mediating the effect of high-beta power on anticipatory inhibition. Furthermore, trials containing beta bursts (22-28 Hz) exhibited both optimally timed anticipatory inhibition and concurrent reduction in high-gamma power. These findings suggest that optimal anticipatory inhibition in the load-supporting elbow flexor is linked to reduced SMA excitability mediated by inhibitory beta bursts. More broadly, they provide new evidence linking beta bursts to the inhibitory control of muscle function, and contribute to a better understanding of motor anticipation.

neuroscience↗

bioRxiv2024

Feature specific neuronal oscillations in cortical layers

The role of cortical oscillations in brain function has been extensively debated, resulting in a variety of theoretical frameworks. Using interleaved simultaneous EEG-fMRI, we examined the layer-specific relationship between oscillatory activity and visual processing. We could demonstrate that{gamma} -band activity positively correlates with feature specific signals in superficial layers, but we were able to report a deep layer contribution as well. In addition, we could demonstrate that -band power not only correlates negatively with the feature unspecific BOLD signal, but related to feature specific BOLD as well. Lower frequency was predominantly related to feature unspecific superficial layer BOLD, while upper frequency was found to be related to feature specific BOLD in superficial and deep layers. We conclude that the role of -band oscillations extends beyond widespread inhibition and might be involved in active stimulus processing on the level of visual features.

neuroscience↗

bioRxiv2023

What is a rhythm for the brain? The impact of contextual temporal variability on auditory perception

Temporal predictions can be formed and impact perception when sensory timing is fully predictable: for instance, the detection of a target sound is enhanced if it is presented on the beat of an isochronous rhythm. However, natural sensory stimuli, like speech or music, are not entirely predictable, but still possess statistical temporal regularities. We investigated whether temporal expectations can be formed in non-fully predictable contexts, and how the temporal variability of sensory contexts affects auditory perception. Specifically, we asked how "rhythmic" an auditory stimulation needs to be in order to observe temporal predictions effects on auditory discrimination performances. In this behavioral auditory oddball experiment, participants listened to auditory sound sequences where the temporal interval between each sound was drawn from gaussian distributions with distinct standard deviations. Participants were asked to discriminate sounds with a deviant pitch in the sequences. Auditory discrimination performances, as measured with deviant sound discrimination accuracy and response times, progressively declined as the temporal variability of the sound sequence increased. Temporal predictability effects ceased to be observed only for the more variable contexts. Moreover, both global and local temporal statistics impacted auditory perception, suggesting that temporal statistics are promptly integrated to optimize perception. Altogether, these results suggests that temporal predictions can be set up quickly based on the temporal statistics of past sensory events and are robust to a certain amount of temporal variability. Therefore, temporal predictions can be built on sensory stimulations that are not purely periodic nor temporally deterministic. Significance statementThe perception of sensory events is known to be enhanced when their timing is fully predictable. However, it is unclear whether temporal predictions are robust to temporal variability, which is naturally present in many auditory signals such as speech and music. In this behavioral experiment, participants listened to auditory sound sequences where the timing between each sound was drawn from distinct gaussian distributions. Participants ability to discriminate deviant sounds in the sequences was function of the temporal statistics of past events: auditory deviant discrimination progressively declined as the temporal variability of the sound sequence increased. Results therefore suggest that auditory perception is sensitive to prediction mechanisms that are involved even if temporal information is not totally predictable.

neuroscience↗

bioRxiv2020

Relating neural oscillations to laminar fMRI connectivity

Laminar fMRI holds the potential to study connectivity at the laminar level in humans. Here we analyze simultaneously recorded EEG and high resolution fMRI data to investigate how EEG power modulations, induced by a task with an attentional component, relate to changes in fMRI laminar connectivity between and within brain regions. Our results indicate that our task induced decrease in beta power relates to an increase in deep-to-deep layer coupling between regions and to an increase in deep/middle-to-superficial layer connectivity within brain regions. The attention-related alpha power decrease predominantly relates to reduced connectivity between deep and superficial layers within brain regions, since, unlike beta power, alpha power was found to be positively correlated to connectivity. We observed no strong relation between laminar connectivity and gamma band oscillations. These results indicate that especially beta band, and to a lesser extent alpha band oscillations relate to laminar specific fMRI connectivity. These differential effects for the alpha and beta bands suggest a complex picture of possibly co-occurring neural processes that can differentially affect laminar connectivity.

neuroscience↗

bioRxiv2019

Estimates of cortical column orientation improveMEG source inversion

Determining the anatomical source of brain activity non-invasively measured from EEG or MEG sensors is challenging. In order to simplify the source localization problem, many techniques introduce the assumption that current sources lie on the cortical surface. Another common assumption is that this current flow is orthogonal to the cortical surface, thereby approximating the orientation of cortical columns. However, it is not clear which cortical surface to use to define the current source locations, and normal vectors computed from a single cortical surface may not be the best approximation to the orientation of cortical columns. We compared three different surface location priors and five different approaches for estimating dipole vector orientation, both in simulations and visual and motor evoked MEG responses. We show that models with source locations on the white matter surface and using methods based on establishing correspondences between white matter and pial cortical surfaces dramatically outperform models with source locations on the pial or combined pial/white surfaces and which use methods based on the geometry of a single cortical surface in fitting evoked visual and motor responses. These methods can be easily implemented and adopted in most M/EEG analysis pipelines, with the potential to significantly improve source localization of evoked responses.

neuroscience↗

bioRxiv2019

New insights on the ventral attention network: Inhibition and recruitment during a bimodal task

Reorienting attention to unexpected events is essential in daily life. fMRI studies have revealed the involvement of the ventral attention network (VAN), including the temporo-parietal junction (TPJ), in such process. In this MEG study with 34 participants (17 women) we used a bimodal (visual/auditory) attention task to determine the neuronal dynamics associated with suppression of the activity of the VAN during top-down attention and its recruitment when information from the unattended sensory modality is involuntarily integrated. We observed an anticipatory power increase of alpha/beta (12-20 Hz) oscillations in the VAN following a cue indicating the modality to attend. Stronger VAN power increases predicted better task performance, suggesting that the VAN suppression prevents shifting attention to distractors. Moreover, the TPJ was synchronized with the frontal eye field in that frequency band, suggesting that the dorsal attention network (DAN) might participate in such suppression. Furthermore, we found a 12-20 Hz power decrease, in both the VAN and DAN, when information of both sensory modalities was congruent, suggesting an involvement of these networks for attention capture. Our results show that effective multimodal attentional reorientation includes the modulation of the VAN and DAN through upper-alpha/beta oscillations. Altogether these results indicate that the suppressing role of alpha/beta oscillations might operate beyond sensory regions. SIGNIFICANCE STATEMENTReorienting attention to unexpected events from multiple sensory sources is essential in daily life. We explored the dynamics of the ventral attention network (VAN), a set of brain regions related to attentional reorienting, when relevant information was anticipated (i.e. during top-down attention) and when unexpected congruent information from another sensory modality was presented (involuntary attentional capture). We report that activity in the alpha/beta range (12-20 Hz) within the VAN indexed both top-down and attentional capture processes. Also, the VAN was synchronized with the dorsal attention network in this frequency band, suggesting an integrated role of both networks for attentional regulation. Our results shed light on the neurophysiological mechanisms that the brain carry out for reorienting attention to relevant environmental stimuli.

neuroscience↗