Predicting task performance from biomarkers of mental fatigue in global brain activity

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The reported rate of the occurrence of unilateral spatial neglect (USN) is highly variable likely due to the lack of validity and low sensitivity of classical tools used to assess it. Virtual reality (VR) assessments try to overcome these limitations by pr ...

The discovery that human brain connectivity data can be used as a "fingerprint " to identify a given individual from a population, has become a burgeoning research area in the neuroscience field. Recent studies have iden-tified the possibility to extract t ...

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 ...

Spinal Cord Injury (SCI) affects almost 500,000 people every year, causing complete paralysis of both legs in severe cases, with no current treatment perspective. However, new neuroengineering technologies, such as the Brain Spine Interface (BSI), have eme ...

Over the last decades, implantable neural interfaces have been extensively explored and effectively deployed to address neurological and mental health disorders. The existing solutions present several limitations. Firstly, the physical size of the implanta ...

BackgroundUnilateral spatial neglect (USN) is a debilitating neuropsychological syndrome that often follows brain injury, in particular a stroke affecting the right hemisphere. In current clinical practice, the assessment of neglect is based on old-fashion ...

Epilepsy is a common chronic neurological disorder that causes recurring seizures and affects more than 50 million people worldwide. Implantable medical devices (IMDs) are regarded as effective tools to cure patients who suffer from refractory epilepsy. Se ...

Wind energy potential in complex terrain is still poorly understood and difficult to quantify. With Switzerland’s current efforts to shift to renewable energy resources, it is now becoming even more crucial to investigate the hidden potential of wind energ ...

Micro- nano-electrodes have demonstrated superior performances in measuring attenuated intracellular action potentials from electrogenic cell cultures compared to traditional multi-electrode arrays. Yet, the understanding of the critical electrode features ...

All functions we use in our everyday life depend on a complex interplay between both cortical and subcortical brain areas, communicating in between each others. When a region is affected by either an accident, aging or neurodegenerative diseases, the whole ...

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 ...

Deep learning (DL) has been wildly successful in practice, and most of the state-of-the-art machine learning methods are based on neural networks (NNs). Lacking, however, is a rigorous mathematical theory that adequately explains the amazing performance of ...

ObjectivePrematurity is associated with a high risk of long-term behavioral problems. This study aimed to assess the prognostic utility of volumetric brain data at term-equivalent-age (TEA), clinical perinatal factors, and parental social economic risk in ...

Epilepsy is one of the most prevalent brain disorders that disrupts the lives of millions worldwide. For patients with drug-resistant seizures, there exist implantable devices capable of monitoring neural activity, promptly triggering neurostimulation to r ...

Neonatal hypoxic-ischemic (HI) encephalopathy (HIE) in term newborns is a leading cause of mortality and chronic disability. Hypothermia (HT) is the only clinically available therapeutic intervention; however, its neuroprotective effects are limited. Lacto ...

Adolescent individuals exhibit great variability in cortical dynamics and behavioral outcomes. The developing adolescent brain is highly sensitive to social experiences and environmental insults, influencing how personality traits emerge. A distinct patter ...

Diffusion Magnetic Resonance Imaging (dMRI) is a powerful non-invasive method for studying white matter tracts of the brain. However, accurate microstructure estimation with fiber orientation distribution (FOD) using existing computational methods requires ...

Implanted brain electrodes provide a unique way of electrically interfacing with individual neurons in vivo. However, chronic recording or stimulating capabilities of neural implants are often impaired by a strong immune response resulting in a fibrous sca ...

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 ...

Zebrafish have the capacity to fully regenerate the heart after an injury, which lies in sharp contrast to the irreversible loss of cardiomyocytes after a myocardial infarction in humans. Transcriptomics analysis has contributed to dissect underlying signa ...

Predicting task performance from biomarkers of mental fatigue in global brain activity

Chattez avec Graph Search

An immersive virtual reality tool for assessing left and right unilateral spatial neglect

Task matters: Individual MEG signatures from naturalistic and neurophysiological brain states

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

Brain-controlled spinal cord stimulation to restore mobility after spinal cord injury

Miniaturised, Wireless and Distributed Neural Interface Toward Cortical Visual Prosthesis

An immersive virtual reality system for ecological assessment of peripersonal and extrapersonal unilateral spatial neglect

Hardware Implementation of Digital Signal Processing Algorithms for Programmable Epilepsy Control Systems

Combining Weather Station Data and Short-Term LiDAR Deployment to Estimate Wind Energy Potential with Machine Learning: A Case Study from the Swiss Alps

Development of new volcano-shaped microelectrodes for single cell electrochemistry, electrophysiology and impedance studies

Noninvasive deep brain stimulation to modulate human behavior by means of transcranial temporal interference electrical stimulation

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

Deep Learning Meets Sparse Regularization

Behavioral outcome of very preterm children at 5 years of age: Prognostic utility of brain tissue volumes at term-equivalent-age, perinatal, and environmental factors

Enhancing Epileptic Seizure Detection with EEG Feature Embeddings

Early Neuroprotective Effects of Bovine Lactoferrin Associated with Hypothermia after Neonatal Brain Hypoxia-Ischemia in Rats

Transcriptomic analysis reveals mitochondrial pathways associated with distinct adolescent behavioral phenotypes and stress response

Robust Estimation of the Microstructure of the Early Developing Brain Using Deep Learning

Engineering Hydrogel-coated Neural Interfaces for Chronic Deep Brain Recording

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

Transcriptomic data meta-analysis reveals common and injury model specific gene expression changes in the regenerating zebrafish heart