Neurology

Language-Related Functional Connectivity in Post-Stroke Aphasia: Preliminary Findings from a Graph-Theoretical and Interpretable Machine Learning Study.

PURPOSE: To have an insight into language-related functional connectivity in post-stroke aphasia (PSA) from graph theory measurements when performing an ability-matched auditory-verbal task fMRI. METHODS: Fifty-seven PSA patients were stratified into high-level (n = 22) and low-level (n = 35) groups using an ability-matched auditory-verbal fMRI paradigm. Functional connectivity was modeled via ROI...

Non-polio enterovirus infection and electrophysiological changes in human iPSC-derived neural networks.

BACKGROUND: The non-polio enteroviruses (NPEV) enterovirus D68 (EV-D68) and enterovirus A71 (EV-A71) are highly prevalent and considered pathogens of increasing health concern due to their neurotropic potential. Severe neurological complications of usually mild and self-limiting NPEV infections include meningitis, encephalitis, and acute flaccid paralysis, especially in children and immunocompromi...

Early detection of Alzheimer's disease based on leveraging multimodal features of the clock drawing test.

BackgroundAlthough multi-task handwriting analysis has the potential to improve early detection of Alzheimer's disease (AD), the educational bias inhe...

Detecting multimorbidity patterns in Alzheimer's disease using unsupervised machine learning: A nationwide emergency department study (2007-2022).

BackgroundAlzheimer's disease (AD) patients frequently present to emergency departments (EDs) with complex comorbidities that complicate triage and ma...

Strategic Governance of Artificial Intelligence-Enabled Clinical Algorithm Development: Formative Evaluation of the Semiautomatic Clinical Algorithm Development Framework.

BACKGROUND: Health care leaders face a strategic dilemma: traditional expert-led content development ensures safety but is too slow for digital innova...

Meta-Learning Enhanced Multi-Source Domain Adaptation for zero-calibration motor imagery EEG decoding.

BACKGROUND: Motor imagery (MI) based brain-computer interface (BCI) holds promising application prospects for closed-loop neurorehabilitation in strok...

Exploratory analysis of the associations of the brain age gap with cognitive function and amyloid-β accumulation: participants selection based on metabolic and physiological blood markers.

The brain age gap (BAG) is defined as the difference between brain age estimated from MRI using artificial intelligence and chronological age, and has...

Machine learning-based quantification of neurovascular compression for correlation with trigeminal neuralgia pain outcomes.

Machine learning-generated segmentations of the trigeminal nerve and surrounding vasculature can quantitatively assess the magnitude of neurovascular ...

Transient frontal spectral events from EEG predict antidepressant response to sertraline in depression.

Resting-state scalp electroencephalography (EEG) is a promising method for predicting patient outcomes of antidepressant treatments. Machine-learning-...

Multimodal machine learning for major depressive disorder: Integrating EEG functional connectivity and clinical variables to enhance diagnostic accuracy.

The diagnosis of Major Depressive Disorder (MDD) relies heavily on subjective clinical assessments. This study evaluated various machine learning mode...

From structural evolution to an AI-driven future of 5-HT1F receptor agonists for migraine therapy.

Migraine is a prevalent and disabling neurological disorder that imposes a substantial global disease burden, particularly among women of childbearing...

A dual-branch deep learning framework for emotion recognition from EEG signals.

Mental health monitoring through emotion recognition plays an important role in early intervention and personalized healthcare systems. Traditional EE...

Perilesional neuromodulation replaces lost sensorimotor function in persons with spinal cord injury.

Spinal cord injury (SCI) results in permanent impairment of sensory, motor and autonomic function. Epidural electrical stimulation (EES) applied below...

Heart rate and sleep history encode ultradian REM sleep timing.

During sleep, the brain alternates between rapid eye movement (REM) and non-REM (NREM) sleep, with recurring REM sleep episodes forming the ultradian ...

Cell-type-specific transposon demethylation and TAD remodeling in aging mouse brain.

Aging is a major risk factor for neurodegenerative diseases, yet the underlying epigenetic mechanisms remain unclear. Here, we generated a comprehensi...

The role of emotion in sleep: a quantitative analysis using EEG data.

STUDY OBJECTIVES: The intricate interplay between sleep and emotion has garnered increasing attention due to their profound impact on human health and...

Creation of a machine learning-based model for early identification of mild cognitive impairment risk in Parkinson's disease: A PD research center-based population study.

BackgroundThis study aimed to use data from the PD-MDCNC database to develop a risk prediction model using machine learning (ML) methods for the early...

Non-Neural Post-Thyroidectomy Dysphonia: Long-Term Voice Outcomes in 527 Patients.

OBJECTIVE: To characterize non-neural post-thyroidectomy dysphonia (PTD) by analyzing long-term voice outcomes in patients with no evidence of nerve i...

Hypothalamic atrophy in progressive supranuclear palsy, assessed by convolutional neural network-based automatic segmentation.

BACKGROUND: The hypothalamus as one of the core structures in metabolic control is increasingly recognized to be morphologically altered in various ne...

OCT-based myopic index: a biological predictor for the progression of high myopia.

BACKGROUND: The growth of axial length (AL) can lead to high myopia and ocular deformation, especially causing microstructural changes in the fundus, ...