Latest AI and machine learning research in neurology for healthcare professionals.
Per- and polyfluoroalkyl substances (PFAS) are man-made compounds that bioaccumulate in environments. Current PFAS detection technologies encounter difficulty in detecting trace concentrations and require complex data processing, limiting their on-site applicability. By leveraging biological chemical sensing systems (insect olfaction) we can detect broad ranges of PFAS. Insects’ advanced combinato...
Accurately localizing the epileptogenic network (EpiNet) remains a major barrier to effective epilepsy treatment, largely due to limited mechanistic understanding. The EpiNet is a patient-specific brain network shaped by complex, overlapping pathology. While combining biomarkers can improve localization, it also generates high-dimensional feature data that increases the risk of overfitting and red...
Recent data indicate that lipid composition has profound influence on the brain function and that changes in lipid homeostasis affect brain aging and ...
Accurately and efficiently quantifying animal behavior at scale without intensive manual labeling is a long-standing challenge for neuroscience and et...
The liver’s microenvironment consists of interconnected vascular, biliary, and neural networks that regulate homeostasis and disease progression. Howe...
Deep learning (DL) models have achieved impressive performance in EEG-based prediction tasks, but they often lack interpretability, limiting their cli...
Circadian clock genes are best known for regulating circadian rhythms, but they also play crucial roles in memory processes. This suggests that memory...
Human perception is robust under challenging conditions, for example when sensory inputs change over time. Temporal adaptation in the form of reduced ...
Accurate identification of the seizure onset zone (SOZ) using intracranial electroencephalography (iEEG) remains challenging. Although diverse methods...
Deep learning has emerged as a powerful tool for extracting meaningful patterns from electroencephalography (EEG) signals, particularly for mental wor...
Deep neural networks applied to signal processing tasks often need specialized architectural mechanisms to capture the temporal history of input signa...
Beta bursts are brief, transient increases in beta-band (13–30 Hz) EEG activity that play a key role in motor control, particularly in processes like ...
Although the autonomic sympathetic system is activated in parallel with locomotion, the underlying neural mechanisms mediating this coordination are n...
Alzheimer’s disease (AD) is a progressive and debilitating neurodegenerative disease of the central nervous system, characterized by deterioration in ...
Aberrant biomolecular condensates are implicated in multiple incurable neurological disorders, including Amyotrophic Lateral Sclerosis, Frontotemporal...
Alzheimer’s disease (AD) is a major global health concern, expected to affect 12.7 million Americans by 2050. Machine learning (ML) algorithms have be...
Single-omics approaches often provide a limited perspective on complex biological systems, whereas multi-omics integration enables a more comprehensiv...
Analyzing temporal spike patterns in nociceptors recorded via microneurography is challenging due to the use of a single recording electrode, waveform...
When we listen to music, we often feel a pleasurable urge to move to music, known as groove. While previous studies have identified musical features t...
Sensory prostheses replace dysfunctional sensory organs with electrical stimulation but currently fail to restore normal perception. Outcomes may be l...