Neurology

Exploratory decoding of TMS-EEG: Predicting TEP response to intermittent and continuous theta burst stimulation.

Theta burst stimulation (TBS) is a promising form of repetitive transcranial magnetic stimulation (rTMS) capable of modulating cortical excitability and intracortical processes, offering therapeutic potential for neurological and psychiatric disorders. However, clinical translation remains limited by high inter-subject and inter-session variability in stimulation effects. To more directly capture ...

A multimodal EMG and IMU dataset for assessing the quality of exercises designed for spatially constrained environments.

Regular physical training is essential for maintaining physical fitness in environments where exercise must be performed in limited space and without direct professional supervision. In such settings, degraded exercise execution may reduce training effectiveness and increase injury risk. To address this challenge, this study aimed to develop a methodology for collecting and processing multimodal d...

Dendro-plexing of Single Input Spikes via Multiple Synaptic Contacts Can Enhance Cortical Neuron Computation and Reduce Axonal Wiring.

A cortical neuron typically makes multiple synaptic contacts on the dendrites of its postsynaptic target neuron. The functional implications of this a...

A Structure-Based Platform for Predicting Chemical-Induced Parkinson's Disease.

Current methods for determining the neurotoxic potential of (agro)chemicals are not comprehensive enough, as is suggested by the increased incidence o...

Explainable artificial intelligence-driven visual task-specific electroencephalogram analysis for attention deficit hyperactivity disorder detection using information-theoretic feature selection.

Attention deficit hyperactivity disorder (ADHD) is a neurological disorder that primarily develops in early childhood and affects motor development, v...

Can epilepsy be predicted after the first febrile seizure? Insights from machine learning of postictal EEG.

OBJECTIVE: Febrile seizures (FS) are the most common seizures in childhood, yet identifying children at risk of developing epilepsy after the first FS...

Advances in Cell Therapy for Neural Repair.

Neural repair remains one of the foremost challenges in modern neuroscience, as damage to the central nervous system caused by injury or neurodegenera...

EEG-VLM: A Hierarchical Vision-Language Model With Multi-Level Feature Alignment and Visually Enhanced Language-Guided Reasoning for EEG Image-Based Sleep Stage Prediction.

Sleep stage classification based on electroencephalography (EEG) is fundamental for assessing sleep quality and diagnosing sleep-related disorders. Ho...

Support vector machine-driven Parkinson's disease identification: a 7-Tesla multidimensional structural MRI approach.

Parkinson's disease (PD) is a progressive neurodegenerative disorder diagnosed clinically by cardinal motor symptoms, with structural brain changes as...

Modified graph neural network-oriented optimization model for the classification of PD.

Methods for categorizing Parkinson's Disease (PD) aim to automatically distinguish among healthy individuals as well as those who have the condition i...

Unveiling an ALS Blood Transcriptomic Signature: A Machine Learning Classifier Distinct from Neurodegenerative Controls.

A cross-sectional protocol for experimental tongue high-density surface electromyography to detect and classify radiation-associated hypoglossal neuropathy.

BACKGROUND: Hypoglossal neuropathy is the most common lower cranial neuropathy detected as a delayed sequelae of Human Papillomavirus (HPV) -driven or...

Functional evaluation in adult spinal deformity can be reduced to 3 key kinematic parameters that can sufficiently predict health-related quality of life outcomes: an observational prospective study.

BACKGROUND CONTEXT: Recently, functional evaluation using 3D gait analysis (3DGA) proved to predict health-related quality-of-life (HRQOL) scores bett...

Neural estimates of language comprehension of sentences with selected action verbs in a non-literal context in the Polish language studied by permutation cluster-based analysis and decoding of the event-related potentials.

BACKGROUND: This work examines how the human brain processes mental metaphors in Polish verbal phraseologisms (a fixed, non-compositional combination ...

MotorQuant: A novel tool for motor function assessment in spinal cord injured mice.

The assessment of motor function recovery in spinal cord injury (SCI) mouse models traditionally relies on semi-quantitative methods like the Basso Mo...

Frequency Band Personalization for Seizure Network Analysis in Multifocal Patients.

Stereo-electroencephalography (SEEG) is commonly used for pre-surgical evaluation in patients with multifocal epilepsy undergoing responsive neurostim...

Innovative therapies under clinical development for ALS treatment: Small molecules.

INTRODUCTION: The clinical trial landscape for Amyotrophic Lateral Sclerosis (ALS) is a rapidly evolving field, characterized by significant obstacles...

Modulating empathy with tDCS: dissociable roles of rTPJ and lDLPFC.

BACKGROUND: Empathy relies on distinct but interacting processes for representing others' states and regulating self-oriented affect. Neuroimaging stu...

Machine Learning-Based Risk Stratification for Symptomatic Intracranial Hemorrhage and 3-month Prognosis Following Intravenous Thrombolysis.

INTRODUCTION: Intravenous thrombolysis (IVT) with tissue-type plasminogen activator (tPA) is a cornerstone of acute ischemic stroke treatment, yet its...

Effects of a Soft Robotic Exoskeleton for Gait Training on Clinical Outcomes in Patients With Parkinson Disease: Randomized Controlled Pilot Study.

BACKGROUND: Balance and gait disorders in Parkinson disease (PD) impair motor function and quality of life. OBJECTIVE: Evidence on soft exoskeleton ro...