Neurology

Machine learning-based prediction of amyloid positivity using early-phase F-18 flutemetamol PET.

BackgroundPrevious studies have suggested that early-phase imaging of amyloid positron emission tomography (PET) may offer information for predicting amyloid positivity.ObjectiveThis study aimed to evaluate whether early-phase fluorine-18 flutemetamol (eFMM) PET images provide valuable information for predicting amyloid positivity using machine learning (ML) models and whether incorporating clinic...

Personalizing Responsive Neurostimulation for Epilepsy.

Over the past 20 years, responsive neurostimulation (RNS), a closed-loop device for treating certain forms of drug-resistant focal epilepsy, has become ensconced in the epileptologist's therapeutic armamentarium. Through neuromodulatory effects, RNS therapy gradually reduces seizures over years, providing diagnostically valuable intracranial recordings along the way. However, the neuromodulatory p...

Uncovering injury-specific proteomic signatures and neurodegenerative risks in single and repetitive traumatic brain injury.

Traumatic brain injury (TBI) is a major public health concern associated with an increased risk of neurodegenerative diseases including Alzheimer's di...

Cold receptor TRPM8 as a target for migraine-associated pain and affective comorbidities.

BACKGROUND: Genetic variations in the Trpm8 gene that encodes the cold receptor TRPM8 have been linked to protection against polygenic migraine, a dis...

From "time is brain" to "time is collaterals": updates on the role of cerebral collateral circulation in stroke.

BACKGROUND: Acute ischemic stroke (AIS) remains the leading cause of mortality and disability worldwide. While revascularization therapies-such as int...

Toward a Universal Map of EEG: A Semantic, Low-Dimensional Manifold for EEG Classification, Clustering, and Prognostication.

OBJECTIVE: Prognostication in patients with disorders of consciousness (DOCs) remains challenging because of heterogeneous etiologies, pathophysiologi...

Exploring the potential biomarkers between stroke and obstructive sleep apnea by WGCNA and machine learning.

BACKGROUND: Ischemic stroke (IS) and obstructive sleep apnea (OSA) are highly prevalent disorders with significant societal and individual burdens. OS...

A New Insight in Cellular and Molecular Signaling Regulation for Neural Differentiation Program.

Numerous neurological conditions impact the brain, spinal cord, and nerves, including neurodegenerative diseases such as Alzheimer's and Parkinson's d...

DynSeizureGAT: Multi-band Dynamic Graph Attention Network for Interpretable Seizure Detection and Analysis of Drug-Resistant Epilepsy Using SEEG.

The dynamic propagation of epileptic discharges complicates Drug-Resistant Epilepsy (DRE) seizure detection using traditional machine learning methods...

Real-time AI-based detection of excessive traction on the recurrent laryngeal nerve during robotic-assisted minimally invasive esophagectomy: a proof-of-concept study.

Recurrent laryngeal nerve (RLN) palsy often occurs due to excessive traction (ET) on the nerve during esophagectomy. Use of a nerve integrity monitor ...

Generalizable model to predict new or progressing compression fractures in tumor-infiltrated thoracolumbar vertebrae in an all-comer population.

OBJECTIVE: Neurosurgical evaluation is required in the setting of spinal metastases at high risk for leading to a vertebral body fracture. Both irradi...

The value of multimodal neuroimaging in the diagnosis and treatment of post-traumatic stress disorder: a narrative review.

Post-traumatic stress disorder (PTSD) is a delayed-onset or prolonged persistent psychiatric disorder caused by individuals experiencing an unusually ...

Effective workflow from multimodal MRI data to model-based prediction.

Predicting human behavior from neuroimaging data remains a complex challenge in neuroscience. To address this, we propose a systematic and multi-facet...

Super-resolution for localizing electrode grids as small, deformable objects during epilepsy surgery using augmented reality headsets.

PURPOSE: Epilepsy surgery is a potential curative treatment for people with focal epilepsy. Intraoperative electrocorticogram (ioECoG) recordings from...

The Rapid Online Cognitive Assessment for the Detection of Neurocognitive Disorder: Open-Label Study.

BACKGROUND: The rising prevalence of dementia necessitates a scalable solution to cognitive screening. Paper-based cognitive screening examinations ar...

Explainable AI predicting Alzheimer's disease with latent multimodal deep neural networks.

PURPOSE: Alzheimer's disease (AD) is a neurodegenerative disorder characterized by progressive cognitive decline. We proposed a novel latent multimoda...

Seminars in epileptology: How to diagnose status epilepticus in adults and children.

Status epilepticus (SE) can be regarded as the most severe expression of seizure activity characterized by a low probability of spontaneous cessation ...

Evaluation and Rehabilitation System for Ulnar-Innervated Muscles Facilitated by Rare Earth Oxide-Enhanced Triboelectric Sensor.

Ulnar nerve injuries often lead to muscle atrophy and reduced hand function, necessitating precise monitoring and effective rehabilitation strategies....

Multi-Scale Temporal Analysis with a Dual-Branch Attention Network for Interpretable Gait-Based Classification of Neurodegenerative Diseases.

The accurate diagnosis of neurodegenerative diseases (NDDs), such as Amyotrophic Lateral Sclerosis (ALS), Huntington's Disease (HD), and Parkinson's D...

A compact neuromorphic system for ultra-energy-efficient, on-device robot localization.

Neuromorphic computing offers a transformative pathway to overcome the computational and energy challenges faced in deploying robotic localization and...