Latest AI and machine learning research in neurology for healthcare professionals.
As artificial intelligence (AI) is increasingly integrated into medical diagnostics, it is essential that predictive models provide not only accurate outputs but also reliable estimates of uncertainty. In clinical applications, where decisions have significant consequences, understanding the confidence behind each prediction is as critical as the prediction itself. Uncertainty modelling plays a ke...
The common marmoset is an important model in biomedical and clinical research, particularly for the study of age-related, neurodegenerative, and neurodevelopmental disorders (due to their biological similarities with humans), infectious disease (due to their susceptibility to a variety of pathogens), as well as developmental biology (due to their short gestation period relative to many other prima...
Pathogenic KCNQ2 variants are associated with developmental and epileptic encephalopathy (KCNQ2-DEE), a devastating disorder characterized by neonatal...
Epileptiform discharges and neuronal hyperexcitability are key pathophysiological features of Alzheimer’s disease and related tauopathies. We previous...
Despite the availability of numerous anti-seizure medications (ASMs), drug resistance remains a major issue for people with epilepsy. The probability ...
To determine the impact of epilepsy duration and interictal spikes on functional connectivity in children with Self-Limited Epilepsy with Centrotempor...
Effective treatment of chronic pain remains hindered by the lack of drug delivery systems that simultaneously achieve long-term stability, high spatia...
Humans seamlessly process multi-voice music into a coherent perceptual whole. Yet the neural strategies supporting this experience remain unclear. One...
As spatial molecular data grow in scope and resolution, there is a pressing need to identify key spatial structures associated with disease. Current a...
Fibromyalgia (FM) involves widespread musculoskeletal pain and hypersensitivity, often accompanied by neurological, cognitive, and affective disturban...
Early and accurate detection of Alzheimer’s disease (AD) is vital for timely intervention and better patient outcomes. However, training machine learn...
Reactivation in sleep alters the structure of memories and can potentially be used to restructure upsetting representations. Reactivation can be trigg...
We introduce a simple and interpretable model for classification of electroencephalography (EEG) signals. Our focus essentially is on using deep learn...
Progress at the intersection of artificial intelligence and pediatric neuroimaging necessitates large, heterogeneous datasets to generate robust and g...
Alzheimer’s disease (AD) is a complex neurodegenerative disorder which is multifactorial in nature. Some of its characteristics are slow cognitive dec...
The olfactory bulb (OB), the first central relay of the olfactory pathway, plays a critical role in odor perception and exhibits remarkable structural...
Gait deficits present an unresolved therapeutic challenge in Parkinson’s Disease. At the behavioral level, symptoms exhibit heterogeneity, including b...
Memories are spontaneously replayed during sleep, a process thought to support memory consolidation. However, capturing this replay in humans has been...
Neurological disorders often originate from progressive brain network dysfunctions that start years before symptoms appear. How these changes emerge i...
The non-polio enteroviruses enterovirus-D68 (EV-D68) and enterovirus-A71 (EV-A71) are highly prevalent and considered pathogens of increasing health c...