Biology subjects

Chabardes, S.

Publications and source records attributed to Chabardes, S..

6 recordsLinked to original sources

bioRxiv2025

Decoupling simultaneous motor imagination and execution via orthogonal ECoG neural representations

The brain coordinates multiple parallel motor programs, ensuring synergy and preventing interference during movements. Yet, performance often degrades when brain-machine interfaces are used during concurrent tasks or ongoing movements. We suggest that latent neural representations may represent a strategy to solve this issue. In this study, we addressed this question using neural signals from a tetraplegic individual with partial residual motor function, implanted with a wireless epidural electrocorticography (ECoG) device. By adapting dimensionality reduction techniques, we found that motor execution and motor imagery span partially overlapping subspaces in mesoscale neural signals, shaped by specific frequency band contributions. Despite substantial shared variance, we show that identifying orthogonal, condition-specific dimensions enables successful decoding of executed and imagined movements, even when performed simultaneously. These findings show that ECoG signals can expose separable neural subspaces, allowing executed and imagined actions to be harnessed independently and in concert. This opens a promising avenue to develop brain-machine interfaces that can simultaneously control multiple external devices or operate alongside natural movements.

neuroscience↗

bioRxiv2024

Evidence for common spike-based temporal coding of overt and covert speech in pars triangularis of human Broca's area

Brocas area has long been described as a central region of cortical speech networks. Yet, its detailed role during speech production remains largely unknown and even sometimes debated. Recordings at the individual neuron level could help understand whether and how speech is encoded in this region but such data remain very scarce. Here we use direct intracortical recording in pars triangularis of human Brocas area to show that the encoding of speech in this region relies not only on spike rates but also on the precise timing of action potentials within individual spike trains. First, we found that the overall spike rate of the whole population remained unchanged between periods of rest, overt and covert speech, but that individual firing rates of a few neurons fluctuated across these conditions. These fluctuations resulted in different overall population dynamics across conditions. Next, we also observed that the temporal arrangement of spikes within individual spike trains was not purely random but also signed which sentence was produced. By matching ensemble spike trains based on inter-spike intervals, it was possible to decode which sentence had been pronounced well above chance and with a comparable accuracy than when using spike counts. Moreover, the temporal code characterizing the overt production of individual sentences was found to be largely conserved when the same sentences were covertly imagined and enabled to decode cover sentences with an accuracy 75% higher than when considering spike counts. Altogether, these results suggest the existence of 2 modes of speech encoding in Brocas area, one based on the modulation of individual firing rates and the other based on the precise temporal structure of individual spike trains, and that the latter type of encoding remains more largely conserved between overt and covert speech production.

neuroscience↗

bioRxiv2024

Subthalamic nucleus activity modifications prior to clinical impairment in a progressive model of Parkinson's disease

Parkinsons disease (PD) is diagnosed after motor symptoms appear, although non-motor symptoms emerge years earlier. Following years of pharmacological treatment, high-frequency stimulation (HFS) of the subthalamic nucleus (STN), a key hub in goal-direct behaviors, can be proposed. While HFS-STN reliably improves motor symptoms, it does not specifically address non-motor symptoms. Clarifying how STN dysfunction contributes to non-motor symptoms could thus improve STN stimulation strategies. Here, we longitudinally recorded STN local field potentials in two macaques performing a counter-demanding task during chronic low-dose MPTP treatment. This progressive model, evolving from an asymptomatic stage to motivational, cognitive and ultimately motor deficits, enabled detailed examination of non-motor stages preceding motor impairment. Each stage was associated with distinct STN electrophysiological alterations, including early loss of reward-related theta activity, subsequent disappearance of decision-related theta oscillations, and later reduction of movement-related beta rebound. In the stable parkinsonian stage, stimulation of different STN territories provided complementary behavioral effect: dorsal HFS-STN improved motor performances, whereas ventral low-frequency stimulation alleviated motivational deficits. These findings reveal a temporal link between STN dysfunction and symptom onset, and suggest site and frequency-specific stimulation as a strategy to address both motor and non-motor symptoms in PD.

neuroscience↗

bioRxiv2022

The role of the thalamus in human reinforcement learning

Although the thalamus is supposed to be involved in reinforcement-based decision-making, there is no direct evidence regarding the involvement of this subcortical structure in humans. To fill this gap, we leveraged rare intra-thalamic electrophysiological recordings in patients and found that temporally structured thalamic oscillations encode key learning signals. Our findings also provide neural insight into the computational mechanisms of action inhibition in punishment avoidance learning.

neuroscience↗

bioRxiv2019

Acoustic contamination of electrophysiological brain signals during speech production and sound perception

A current challenge of neurotechnologies is the development of speech brain-computer interfaces to restore communication in people unable to speak. To achieve a proof of concept of such system, neural activity of patients implanted for clinical reasons can be recorded while they speak. Using such simultaneously recorded audio and neural data, decoders can be built to predict speech features using features extracted from brain signals. A typical neural feature is the spectral power of field potentials in the high-gamma frequency band (between 70 and 200 Hz), a range that happens to overlap the fundamental frequency of speech. Here, we analyzed human electrocorticographic (ECoG) and intracortical recordings during speech production and perception as well as rat microelectrocorticographic ({micro}-ECoG) recordings during sound perception. We observed that electrophysiological signals, recorded with different recording setups, often contain spectrotemporal features highly correlated with those of the sound, especially within the high-gamma band. The characteristics of these correlated spectrotemporal features support a contamination of electrophysiological recordings by sound. In a recording showing high contamination, using neural features within the high-gamma frequency band dramatically increased the performance of linear decoding of acoustic speech features, while such improvement was very limited for another recording showing weak contamination. Further analysis and in vitro replication suggest that the contamination is caused by a mechanical action of the sound waves onto the cables and connectors along the recording chain, transforming sound vibrations into an undesired electrical noise that contaminates the biopotential measurements. This study does not question the existence of relevant physiological neural information underlying speech production or sound perception in the high-gamma frequency band, but alerts on the fact that care should be taken to evaluate and eliminate any possible acoustic contamination of neural signals in order to investigate the cortical dynamics of these processes.

neuroscience↗

bioRxiv2019

Toward a unified connectomic target for deep brain stimulation in obsessive-compulsive disorder

Multiple surgical targets have been proposed for treating obsessive-compulsive disorder (OCD) with deep brain stimulation (DBS). However, different targets may modulate the same neural network responsible for clinical improvement. Here we analyzed data from four cohorts of OCD patients (N = 50) that underwent DBS to the anterior limb of the internal capsule (ALIC), the nucleus accumbens (NAcc) or the subthalamic nucleus (STN). Fiber tracts that were predominantly connected to electrodes in good or poor DBS responders were isolated from a normative structural connectome and assigned a predictive value. Strikingly, the same fiber bundle was related to treatment response when independently analyzing two large training cohorts that targeted either ALIC or STN. This discriminative tract is a subsection of the ALIC and connects frontal regions (such as the dorsal anterior cingulate, dACC, and ventral prefrontal, vlPFC, cortices to the STN). When informing the tract solely based on one cohort (e.g. ALIC), clinical improvements in the other (e.g. STN) could be significantly predicted, and vice versa. Finally, clinical improvements of eight patients from a third center with electrodes in the NAcc and six patients from a fourth center in which electrodes had been implanted in both STN and ALIC were significantly predicted based on this novel tract-based DBS target. Results suggest a functional role of a limbic hyperdirect pathway that projects from dACC and vlPFC to anteriomedial STN. Obsessive-compulsive symptoms seem to be tractable by modulating the specific bundle isolated here. Our results show that connectivity-derived improvement models can inform clinical improvement across DBS targets, surgeons and centers. The identified tract is now three-dimensionally defined in stereotactic standard space and will be made openly available.

neuroscience↗