Biology subjects

Bertrand, O.

Publications and source records attributed to Bertrand, O..

8 recordsLinked to original sources

bioRxiv2025

Sleep after Motor Sequence Learning Enhances Post-Movement Parietal Beta Synchronization

The neural substrates supporting the beneficial effect of sleep on motor memory consolidation are well described. However, less is known about the brain oscillatory dynamics underlying these processes. We characterized the oscillatory dynamics associated with motor sequence learning and their modulation by post-learning sleep using magnetoencephalography (MEG) in young healthy adults. After learning a motor sequence task while their brain activity was recorded with MEG, participants were distributed in two groups according to whether they slept or were totally sleep deprived during the first post-training night. Consolidation was assessed with a retest in the MEG three days after training. Behaviorally, performance improved over the consolidation interval irrespective of whether sleep was afforded during the first night. MEG results showed that initial motor sequence learning was characterized by a progressive decrease in beta Event Related Desynchronization (ERD, 18-25Hz) over bilateral motor areas. Interestingly, while these practice-related modulations of beta ERD were not influenced by the sleep status, post-learned-movement beta Event Related Synchronization (ERS) over bilateral parietal areas increased over the consolidation interval in the sleep, compared to the sleep deprived, group. These results extend current models of motor memory consolidation by identifying ERS as an oscillatory marker of sleep-dependent consolidation.

neuroscience↗

bioRxiv2020

THE DUAL-TASK COST IS DUE TO NEURAL INTERFERENCES DISRUPTING THE OPTIMAL SPATIO-TEMPORAL DYNAMICS OF THE COMPETING TASKS

Dual-tasking is extremely prominent nowadays, despite ample evidence that it comes with a performance cost: the Dual-Task (DT) cost. Neuroimaging studies have established that tasks are more likely to interfere if they rely on common brain regions, but the precise neural origin of the DT cost has proven elusive so far, mostly because fMRI does not record neural activity directly and cannot reveal the key effect of timing, and how the spatio-temporal neural dynamics of the tasks coincide. Recently, DT electrophysiological studies in monkeys have recorded neural populations shared by the two tasks with millisecond precision to provide a much finer understanding of the origin of the DT cost. We used a similar approach in humans, with intracranial EEG, to assess the neural origin of the DT cost in a particularly challenging naturalistic paradigm which required accurate motor responses to frequent visual stimuli (task T1) and the retrieval of information from long-term memory (task T2), as when answering passengers questions while driving. We found that T2 elicited neuroelectric interferences in the gamma-band (>40 Hz), in key regions of the T1 network including the Multiple Demand Network. They reproduced the effect of disruptive electrocortical stimulations to create a situation of dynamical incompatibility, which might explain the DT cost. Yet, participants were able to flexibly adapt their strategy to minimize interference, and most surprisingly, reduce the reliance of T1 on key regions of the executive control network - the anterior insula and the dorsal anterior cingulate cortex - with no performance decrement. HIGHLIGHTS- First direct evidence in humans of neural interferences between two tasks. - First explanation of the Dual-Task cost at the neural level in humans. - First Dual-Tasking study with intracranial EEG in naturalistic conditions.

neuroscience↗

bioRxiv2019

Empirical evaluation of fused EEG-MEG source reconstruction. Application to auditory mismatch generators

Since their introduction in the late eighties, Bayesian approaches for neuroimaging have opened the way to new powerful and quantitative analysis of brain data. Here, we apply this statistical framework to evaluate empirically the gain of fused EEG-MEG source reconstruction, compared to unimodal (EEG or MEG) one. Combining EEG and MEG information for source reconstruction has been consistently evidenced to enhance localization performances using simulated data. However, given considerable efforts to conduct simultaneous recordings, empirical evaluation becomes necessary to quantify the real information gain. And this is obviously not straightforward due to the ill-posedness of the inverse problem. Here, we consider Bayesian model comparison to quantify the ability of EEG, MEG and fused (EEG/MEG) inversions of individual data to resolve spatial source models. These models consisted in group-level cortical distributions inferred from real EEG, MEG and EEG/MEG brain responses. We applied this comparative evaluation to the timely issue of the generators of auditory mismatch responses evoked by unexpected sounds. These included the well-known Mismatch Negativity (MMN) but also earlier deviance responses. As expected, fused localization was evidenced to outperform unimodal inversions with larger model separability. The present methodology confirms with real data the theoretical interest of simultaneous EEG/MEG recordings and fused inversion to highly inform (spatially and temporally) source modeling. Precisely, a bilateral fronto-temporal network could be identified for both the MMN and early deviance response. Interestingly, multimodal inversions succeeded in revealing spatio-temporal details of the functional organization within the supratemporal plane that have not been reported so far, nor were visible here with unimodal inversions. The present refined auditory network could serve as priors for auditory modeling studies.

neuroscience↗

bioRxiv2018

Evidence for implicit and adaptive deployment of precision weighting during passive listening: a simultaneous EEG/MEG study

Predictive coding accounts of brain functions profoundly influence current approaches to perceptual synthesis. However, a fundamental paradox has emerged, that may be very relevant for understanding hallucinations, psychosis or cognitive inflexibility. This paradox is that in some situations surprise or prediction error related responses can decrease when predicted and yet, they can increase when we know they are predictable. This paradox is resolved by recognizing that brain responses reflect precision weighted prediction error. This then presses us to disambiguate the contributions of precision and prediction error in electrophysiology. We report, for the first time, an experimental paradigm that may be able to meet this challenge. We examined brain responses to unexpected and expected surprising sounds, assuming that the latter yield a smaller prediction error but much more amplified by a larger precision weight. Importantly, addressing this modulation requires the modelling of trial-by-trial variations of brain responses, that we reconstructed within a fronto-temporal network by combining EEG and MEG. Our results reveal an adaptive learning of surprise with larger integration of past (relevant) information in the context of expected surprises. Within the auditory hierarchy, this adaptation was found tied down to specific connections and reveals in particular and crucially precision encoding through neuronal excitability. Strikingly, these fine processes are automated as sound sequences were unattended. These findings directly speak to applications in psychiatry, where it has been suggested that a specifically impaired precision weighting is at the heart of several conditions such as schizophrenia and autism.

neuroscience↗

bioRxiv2018

BLAST : a short computerized test to measure the ability to stay on task. Normative behavioral data and detailed cortical dynamics.

1.This article provides an exhaustive description of a new short computerized test to assess on a second-to-second basis the ability of individuals to << stay on task >>, that is, to apply selectively and repeatedly task-relevant cognitive processes. The task (Bron/Lyon Attention Stability Test, or BLAST) lasts around one minute, and measures repeatedly the time to find a target letter in a two-by-two letter array, with an update of all letters every new trial across thirty trials. Several innovative psychometric measures of attention stability are proposed based on the instantaneous fluctuations of reaction times throughout the task, and normative data stratified over a wide range of age are provided by a large (>6000) dataset of participants aged 8 to 70. We also detail the large-scale brain dynamics supporting the task from an in-depth study of 32 participants with direct electrophysiological cortical recordings (intracranial EEG) to prove that BLAST involves critically large-scale executive attention networks, with a marked activation of the dorsal attention network and a deactivation of the default-mode network. Accordingly, we show that BLAST performance correlates with scores established by ADHD-questionnaires.

neuroscience↗

bioRxiv2018

Not Just A Number: Age-Related Modulations of Oscillatory Patterns Underlying Top-Down and Bottom-Up Attention.

Attention operates through top-down (TD) and bottom-up (BU) mechanisms. Recently, it has been shown that slow (alpha) frequencies index facilitatory and suppressive mechanisms of TD attention and faster (gamma) frequencies signal BU attentional capture. Ageing is characterized by increased behavioral distractibility, resulting from either a reduced efficiency of TD attention or an enhanced triggering of BU attention. However, only few studies have investigated the impact of ageing upon the oscillatory activities involved in TD and BU attention. MEG data were collected from 14 elderly and 14 matched young healthy human participants while performing the Competitive Attention Task. Elderly participants displayed (1) exacerbated behavioral distractibility, (2) altered TD suppressive mechanisms, indexed by a reduced alpha synchronization in task-irrelevant regions, (3) less prominent alpha peak-frequency differences between cortical regions, (4) a similar BU system activation indexed by gamma activity, and (5) a reduced activation of lateral prefrontal inhibitory control regions. These results show that the ageing-related increased distractibility is of TD origin.

neuroscience↗

bioRxiv2018

What is in Your Gamma? Activation of The Ventral Fronto-Parietal Attentional Network in Response to Distracting Sounds

Auditory attention operates through top-down (TD) and bottom-up (BU) mechanisms that are supported by dorsal and ventral brain networks, respectively, with the main overlap in the lateral prefrontal cortex (lPFC). A good TD/BU balance is essential to be both task-efficient and aware of our environment, yet it is rarely investigated. Oscillatory activity is a novel method to probe the attentional dynamics with evidence that gamma activity (>30Hz) could signal BU processing and thus would be a good candidate to support the activation of the ventral BU network. MEG data were collected from 21 young adults performing the Competitive Attention Task which enables simultaneous investigation of BU and TD attentional mechanisms. Distracting sounds elicited an increase in gamma activity in regions of the BU ventral network. TD attention modulated these gamma responses in regions of the inhibitory cognitive control system: the medial prefrontal and anterior cingulate cortices. Finally, distracting-sound-induced gamma activity was synchronous between the auditory cortices and several distant brain regions, notably the lPFC. We provide novel insight into the role of gamma activity (1) in supporting the activation of the BU ventral network, and (2) in subtending the TD/BU attention balance in the prefrontal cortex.

neuroscience↗

bioRxiv2018

Gap perception in bumblebees

A number of insects fly over long distances below the natural canopy where the physical environment is highly cluttered consisting of obstacles of varying shape, size and texture. While navigating within such environments animals need to perceive and disambiguate environmental features that might obstruct their flight. The most elemental aspect of aerial navigation through such environments is gap identification and passability evaluation. We used bumblebees to seek insights into the mechanisms used for gap identification when confronted with an obstacle in their flight path and behavioral compensations employed to assess gap properties. Initially, bumblebee foragers were trained to fly though an unobstructed flight tunnel that led to a foraging chamber. After the bees were familiar with this situation, we placed a wall containing a gap that unexpectedly obstructed the flight path on a return trip to the hive. The flight trajectories of the bees as they approached the obstacle wall and traversed the gap were analyzed in order to evaluate their behavior as a function of the distance between the gap and a background wall that was placed behind the gap. Bumblebees initially decelerate when confronted with an unexpected obstacle. Deceleration was first noticed when the obstacle subtended around 35{degrees} on the retina but also depended on the properties of the gap. Subsequently the bees gradually traded off their longitudinal velocity to lateral velocity and approached the gap increasing lateral displacements and lateral velocity. Bumblebees shaped their flight trajectory depending on the salience of the gap, in our case, indicated by the optic flow contrast between the region within the gap and on the obstacle, which increases with decreasing distance between the gap and the background wall. As the optic flow contrast decreased the bees spent increasing time moving laterally across the obstacles. During these repeated lateral maneuvers the bees are likely assessing gap geometry and passability.

animal behavior and cognition↗