Neurology

Motion sequencing reveals hidden patterns of repetitive behavior in a mouse model of epilepsy

Epilepsy is the 4th most prevalent neurological condition with 50 million cases worldwide. Patients with epilepsy bare a disproportionate burden of cognitive decline and psychiatric disorders which remain poorly understood and go underdressed by current anti-epileptic treatments. Furthermore, pre-clinical work on behavioral comorbidities can be hampered by current testing frameworks which rely on ...

An EMG Foundation Model for Neural Decoding

Decoding algorithms can be used to predict motor behaviour from patterns of neural activity. However, most studies rely on subject-optimized models, limiting generalization and scalability to novel subjects and tasks. Building on recent advances in deep learning and large-scale data, here we developed an EMG foundation model for neural decoding. Our model was trained on more than 197 hours of neur...

Dopamine and serotonin transients predict depressive symptom relief following deep brain stimulation of human subcallosal cingulate cortex

Recent advances in deep brain stimulation (DBS) of the subcallosal cingulate (SCC) show promise in mitigating the symptoms of treatment-resistant depr...

Temporal Dynamics of High-Frequency Oscillations in Alzheimer’s Disease: A Longitudinal Study in hAPP-J20 Mice

Alzheimer’s disease (AD) is characterized by progressive cognitive decline and increased seizure susceptibility; yet both the mechanistic and temporal...

A dataset of differentiable biologically-derived single neuron models

Biological neural networks contain diverse cell types with heterogeneous electrophysiological properties. Artificial neural networks (ANNs) model comp...

Moremi Bio Agent: Using Neisseria meningitidis Reference Data For The Double Blinded Validation of A General Purpose Biology-Trained Reasoning Model for Pathogen and Antigen Discovery

Antibodies serve as vital diagnostic and therapeutic agents due to their exceptional specificity toward antigenic targets. Mapping antibody–antigen in...

Pre-movement neural population activity in human motor cortex reflects the subsequent outcome of futsal free kicks

Recent sports science studies suggest that optimizing neural activity can enhance motor performance, but practical applications have been hindered by ...

Machine learning prediction algorithms for 2- , 5- and 10-year risk of Alzheimer’s, Parkinson’s and dementia at age 65: a study using medical records from France and the UK General Practitioners

Leveraging machine learning on electronic health records offers a promising method for early identification of individuals at risk for dementia and ne...

Heart rate fragmentation improves general anesthesia state classification using machine learning

Accurate assessment of consciousness during general anesthesia is crucial for optimizing anesthetic dosage and patient safety. Current electroencephal...

Modeling trajectories of routine blood tests as dynamic biomarkers for outcome in spinal cord injury

Early outcome prediction after acute traumatic spinal cord injury (SCI) is challenging due to pathological complexities and population heterogeneity. ...

Deep Learning–Based Early Detection of Major Adverse Cerebral Injuries in Cardiothoracic and Vascular Surgery

Despite advances in central nervous system (CNS)-protective anesthetic and surgical strategies, perioperative stroke remains a significant concern in ...

High density EEG and deep learning improves outcome prediction on the first day of coma after cardiac arrest

We assessed outcome prediction of comatose patients using a deep learning analysis applied to resting EEG on the first and second day after cardiac ar...

VIDEO BASED DETECTION OF EPILEPTIC SEIZURES USING A THREE-DIMENSIONAL CONVOLUTIONAL NEURAL NETWORK

Seizure detection in epilepsy monitoring units (EMU) is essential for the clinical assessment of drug-resistant epilepsy. Automated video analysis usi...

Social Determinants of Health and Functional Brain Connectivity Predict Long-Term Physical Activity in Older Adults with a New Cardiovascular Diagnosis

Physical activity is essential for preventing cognitive decline, stroke and dementia in older adults. A new cardiovascular diagnosis offers a critical...

Enhancing Rare Disease Education through AI-Driven Podcast Generation

Rare diseases, including many rare genetic epilepsies and neurodevelopmental disorders, present significant challenges in timely diagnosis, treatment,...

Combining Clinical Embeddings with Multi-Omic Features for Improved Patient Classification and Interpretability in Parkinson’s Disease

This study demonstrates the integration of Large Language Model (LLM)-derived clinical text embeddings from the Movement Disorder Society Unified Park...

Brain Age Gap Reduction Following Physical Exercise Mirrors Negative Symptom Improvement in Schizophrenia Spectrum Disorders

Schizophrenia spectrum disorders (SSD) are associated with accelerated brain aging, reflected in an increased brain age gap. This gap serves as a biom...

SLaM Image Bank – a real-world diverse London cohort linking brain MRI to electronic mental health and dementia records for the development of clinical decision support tools using artificial intelligence

Rapid developments are occurring in artificial intelligence (AI) and machine learning (ML) applied to neuroimaging. To date, advances in this space ha...

Improving Diagnostic Accuracy of Routine EEG for Epilepsy using Deep Learning

The diagnostic yield of routine EEG in epilepsy is limited by low sensitivity and the potential for misinterpretation of interictal epileptiform disch...

Machine learning methods to track dynamic facial function in facial palsy

For patients with facial paralysis, the wait for return of facial function and resulting vision risk from poor eye closure, difficulty speaking and ea...