Neurology

Identification of CXCR4 inhibitory activity in natural compounds using cheminformatics-guided machine learning algorithms.

Neurodegenerative disorders are characterised by progressive damage to neurons that leads to cognitive impairment and motor dysfunction. Current treatment options focus only on symptom management and palliative care, without addressing their root cause. In our previous study, we reported the upregulation of the CXC motif chemokine receptor 4 (CXCR4), in Alzheimer's disease (ad) and Parkinson's dis...

Explainable AI model reveals disease-related mechanisms in single-cell RNA-seq data

Neurodegenerative diseases (NDDs) are complex and lack effective treatment due to their poorly understood mechanism. The increasingly used data analysis from Single nucleus RNA Sequencing (snRNA-seq) allows to explore transcriptomic events at a single cell level, yet face challenges in interpreting the mechanisms underlying a disease. On the other hand, Neural Network (NN) models can handle comp...

Exploring EEG and Eye Movement Fusion for Multi-Class Target RSVP-BCI

Rapid Serial Visual Presentation (RSVP)-based Brain-Computer Interfaces (BCIs) facilitate high-throughput target image detection by identifying even...

Towards a Generalizable Speech Marker for Parkinson's Disease Diagnosis

Parkinson's Disease (PD) is a neurodegenerative disorder characterized by motor symptoms, including altered voice production in the early stages. Ea...

Integrating Language-Image Prior into EEG Decoding for Cross-Task Zero-Calibration RSVP-BCI

Rapid Serial Visual Presentation (RSVP)-based Brain-Computer Interface (BCI) is an effective technology used for information detection by detecting ...

Automated Detection of Epileptic Spikes and Seizures Incorporating a Novel Spatial Clustering Prior

A Magnetoencephalography (MEG) time-series recording consists of multi-channel signals collected by superconducting sensors, with each signal's inte...

Deep Learning-Driven Segmentation of Ischemic Stroke Lesions Using Multi-Channel MRI

Ischemic stroke, caused by cerebral vessel occlusion, presents substantial challenges in medical imaging due to the variability and subtlety of stro...

A Shape-Based Functional Index for Objective Assessment of Pediatric Motor Function

Clinical assessments for neuromuscular disorders, such as Spinal Muscular Atrophy (SMA) and Duchenne Muscular Dystrophy (DMD), continue to rely on s...

RealDiffFusionNet: Neural Controlled Differential Equation Informed Multi-Head Attention Fusion Networks for Disease Progression Modeling Using Real-World Data

This paper presents a novel deep learning-based approach named RealDiffFusionNet incorporating Neural Controlled Differential Equations (Neural CDE)...

Machine Learning-Based Differential Diagnosis of Parkinson's Disease Using Kinematic Feature Extraction and Selection

Parkinson's disease (PD), the second most common neurodegenerative disorder, is characterized by dopaminergic neuron loss and the accumulation of ab...

Data Acquisition Through Participatory Design for Automated Rehabilitation Assessment

Through participatory design, we are developing a computational system for the semi-automated assessment of the Action Research Arm Test (ARAT) for ...

Brainwide hemodynamics predict EEG neural rhythms across sleep and wakefulness in humans

The brain exhibits rich oscillatory dynamics that play critical roles in vigilance and cognition, such as the neural rhythms that define sleep. These ...

Development of convolutional neural networks for automated brain-wide histopathological analysis in mouse models of synucleinopathies

Preclinical animal models are indispensable for uncovering disease mechanisms and developing novel therapeutic interventions in synucleinopathies. Key...

Neural xenografts contribute to long-term recovery in stroke via molecular graft-host crosstalk

Stroke is a leading cause of disability and death due to the brain’s limited ability to regenerate damaged neural circuits. To date, stroke patients h...

Human whole epigenome modelling for clinical applications with Pleiades

Gene regulation in humans extends beyond the four letter genetic code. Cytosine methylation, in particular, functions as a critical epigenetic switchb...

Linking age changes in human cortical microcircuits to impaired brain function and EEG biomarkers

Human brain aging involves a variety of cellular and synaptic changes, but how these changes affect brain function and signals remains poorly understo...

Denoising 7T Structural MRI with Conditional Generative Diffusion Models

7T MRI offers ultra-high resolution and improved sensitivity for iron deposition in neurodegenerative disorders, but commonly used acquisitions are lo...

Recognizing EEG responses to active TMS vs. sham stimulations in different TMS-EEG datasets: a machine learning approach

Transcranial Magnetic Stimulation (TMS) with simultaneous Electroencephalogram (TMS-EEG) allows assessing the neurophysiological properties of cortica...

ConvNeXt-Driven Detection of Alzheimer’s Disease: A Benchmark Study on Expert-Annotated AlzaSet MRI Dataset Across Anatomical Planes

Alzheimer’s disease (AD) is a leading worldwide cause of cognitive impairment, necessitating accurate, inexpensive diagnostic tools to enable early re...

Biological Database Mining for LLM-Driven Alzheimer’s Disease Drug Repurposing

This study presents a software pipeline that leverages LLMs to apply knowledge stored in natural language (such as in pharmacological texts) and ontol...