Latest AI and machine learning research in neurology for healthcare professionals.
fMRI signals were traditionally seen as slow and sampled in the order of seconds, but recent technological advances have enabled much faster sampling rates. We hypothesized that high-frequency fMRI signals can capture spontaneous neural activity that index brain states. Using fast fMRI (TR=378ms) and simultaneous EEG in 27 humans drifting between sleep and wakefulness, we found that fMRI spectral ...
Abnormal tau accumulation is a hallmark of neurodegenerative tauopathies such as Progressive Supranuclear Palsy (PSP). Traditional post-mortem assessments rely on manual lesion annotation, which is time-consuming and subjective. Existing machine learning methods typically involve multi-stage, feature-based pipelines, resulting in limited scalability and reliance on handcrafted features. This work ...
Humans can experience auditory pain in response to sound, either from extremely loud noise or in cases of pain hyperacusis, where typically tolerable ...
Diffusion magnetic resonance imaging is a non-invasive neuroimaging technique that enables in vivo evaluation of white matter microstructure, providin...
skiftiTools processes three- and four-dimensional neuroimaging data, facilitating advanced statistical modelling with voxelwise data in any software o...
Schizophrenia (ScZ) is a growing global health concern that affects millions of people and puts severe pressure on healthcare systems. Early detection...
Mitochondrial dysfunction is a convergent hallmark of neurodegenerative diseases and represents a promising biomarker for early diagnosis and therapy....
Physiological artifacts pose persistent challenges in electroencephalo-gram (EEG) data acquisition, often compromising interpretation and post-analysi...
Alterations in metabolism, stress response, sleep, circadian rhythms, and neuroendocrine processes are key features of aging and neurodegeneration. Th...
Predicting symptom onset in genetic frontotemporal dementia (FTD) is crucial for advancing targeted interventions and clinical trial design. Brain cha...
Stroke rehabilitation requires continuous, individualized assessment of recovery progress to optimize treatment planning. Existing prognosis models of...
Proper brain function requires the assembly and function of diverse populations of neurons and glia. Single cell gene expression studies have mostly f...
Magnetic resonance imaging (MRI) is critical for acute stroke triage, but time-consuming, and often requires contrast injection for perfusion imaging....
Early detection of neuromuscular disorders is a major clinical challenge, with most diagnoses only occurring after considerable motor neuron degenerat...
Astrocytes regulate the activity of nearby neurons so disruption of astrocyte calcium dynamics by traumatic brain injury (TBI) could have profound con...
Information transfer in neural systems is often modeled through diffusive or synaptic mechanisms that fail to capture the contagion-like propagation o...
Inferring chronological age from magnetic resonance imaging (MRI) brain data has become a valuable tool for the early detection of neurodegenerative d...
The hypothalamus and zona incerta of the brown rat (Rattus norvegicus), a model organism important for translational neuroscience research, contain di...
Cell death is a dynamic process that unfolds through time. Live-cell time-lapse imaging captures these dynamics in a way that’s impossible for static ...
Sleep and circadian rhythms both contribute to cognitive performance, but the underlying neuronal network-level changes remain unclear. We quantified ...