Connectome spectral analysis to track EEG task dynamics on a subsecond scale

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Scientific Machine Learning (SciML) is a recently emerged research field which combines physics-based and data-driven models for the numerical approximation of differential problems. Physics-based models rely on the physical understanding of the problem at ...

While humans are known to have several premotor cortical areas, secondary motor cortex (M2) is often considered to be the only higher -order motor area of the mouse brain and is thought to combine properties of various human premotor cortices. Here, we sho ...

Correlative light and electron microscopy (CLEM) combines light microscopy, for identifying a target via genetic labels, dyes, antibodies and morphological features, with electron microscopy, for analyzing high-resolution subcellular ultrastructures. Here, ...

Brain organoids enable the mechanistic study of human brain development and provide opportunities to explore self-organization in unconstrained developmental systems1, 2–3. Here we establish long-term, live light-sheet microscopy on unguided brain organoid ...

Restoring the ability to walk is a priority for individuals with neurological disorders or neurotraumatic injuries, given its significant impact on independence and quality of life. Multimodal closed-loop strategies that integrate robotic assistance and ne ...

Electrical stimulation of the visual nervous system could improve the quality of life of patients affected by acquired blindness by restoring some visual sensations, but requires careful optimization of stimulation parameters to produce useful perceptions. ...

Reinforcement learning (RL) is crucial for learning to adapt to new environments. In RL, the prediction error is an important component that compares the expected and actual rewards. Dopamine plays a critical role in encoding these prediction errors. In my ...

Epilepsy, a major neurological disease, requires careful diagnosis and treatment. However, the detection of epileptic seizures remains a significant challenge. Current clinical practice relies on expert analysis of EEG signals, a process that is time-consu ...

Reinforcement feedback can improve motor learning, but the underlying brain mechanisms remain underexplored. In particular, the causal contribution of specific patterns of oscillatory activity within the human striatum is unknown. To address this question, ...

Social behaviors such as cooperation are crucial for mammals. A deeper knowledge of the neuronal mechanisms underlying cooperation can be beneficial for people suffering from pathologies with impaired social behavior. Our aim was to study the brain activit ...

The brain's functional networks can be assessed using imaging techniques like functional magnetic resonance imaging (fMRI) and electroencephalography (EEG). Recent studies have suggested a link between the dynamic functional connectivity (dFC) captured by ...

Electroencephalography (EEG) data entail a complex spatiotemporal structure that reflects ongoing organi-zation of brain activity. Characterization of the spatial patterns is an indispensable step in numerous EEG processing pipelines. We present a novel me ...

Alzheimer's disease (AD) pathological changes may begin up to decades earlier than the appearance of the first symptoms of cognitive decline. Subjective cognitive decline (SCD) could be the first pre-clinical sign of possible AD, which might be followed by ...

ABS T R A C T BACKGROUND: Upper limb (UL) motor impairment following stroke is a leading cause of functional limitations in activities of daily living. Robot-assisted therapy supports rehabilitation, but how its efficacy and the underlying neural mechanism ...

An important function of the brain is to interpret incoming sensory information from the outside world to guide adaptive behavior. Understanding how and where sensory information is transformed into motor commands in a context- and learning-dependent manne ...

Recent developments in experimental techniques have enabled simultaneous recordings from thousands of neurons, enabling the study of functional cell assemblies. However, determining the patterns of synaptic connectivity giving rise to these assemblies rema ...

The brain is composed of several anatomically clearly separated structures. This parcellation is often extended into the isocortex, based on anatomical, physiological or functional differences. Here, we derive a parcellation scheme based purely on the spat ...

Objective. This study aims to design and implement the first deep learning (DL) model to classify subjects in the prodromic states of Alzheimer's disease (AD) based on resting-state electroencephalographic (EEG) signals. Approach. EEG recordings of 17 heal ...

Resting-state fMRI has proven to entail subject-specific signatures that can serve as a fingerprint to identify individuals. Conventional methods are based on building a connectivity matrix based on correlation between the average time course of pairs of b ...

Alterations of the limbic system may be present in the chronic phase of SARS-CoV-2 infection. Our aim was to study the long-term impact of this disease on limbic system-related behaviour and its associated brain functional connectivity, according to the se ...

Connectome spectral analysis to track EEG task dynamics on a subsecond scale

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Combining physics-based and data-driven models: advancing the frontiers of research with scientific machine learning

The mouse motor system contains multiple premotor areas and partially follows human

Correlative light and electron microscopy for human brain and other biological models

Morphodynamics of human early brain organoid development

Multimodal closed-loop strategies for gait recovery after spinal cord injury and stroke via the integration of robotics and neuromodulation

Decoding electroencephalographic responses to visual stimuli compatible with electrical stimulation

Unveiling the complexity of learning and decision-making

Resource-Efficient Continual Learning for Personalized Online Seizure Detection

Non-invasive stimulation of the human striatum disrupts reinforcement learning of motor skills

Involvement of prelimbic cortex neurons and related circuits in the acquisition of a cooperative learning by pairs of rats

Brain's Dynamic Functional Organization with Simultaneous EEG-fMRI Networks

Spectral representation of EEG data using learned graphs with application to motor imagery decoding

Degradation of EEG microstates patterns in subjective cognitive decline and mild cognitive impairment: Early biomarkers along the Alzheimer's Disease continuum?

Neurophysiological underpinnings of an intensive protocol for upper limb motor recovery in subacute and chronic stroke patients

Neuronal correlates of goal-directed sensorimotor transformation in sensory, motor and higher-order cortical areas

Cortical cell assemblies and their underlying connectivity: an in silico study

A parcellation scheme of mouse isocortex based on reversals in connectivity gradients

An attention-based deep learning approach for the classification of subjective cognitive decline and mild cognitive impairment using resting-state EEG

Brain Fingerprinting Using Fmri Spectral Signatures On High-Resolution Cortical Graphs

Markers of limbic system damage following SARS-CoV-2 infection