809+ open-access research outputs.
Objective. Personalized transcranial electrical stimulation (tES) has gained growing attention due to the substantial inter-individual variability in brain anatomy and physiology. While previous revieโฆ
Diagnosing sleep disorders is an important focus in neuroscience and engineering, as these conditions involve issues such as insufficient sleep, frequent awakenings, and difficulty reaching deep sleepโฆ
Over the past decade, techniques enabling bidirectional modulation of neuronal activity with single cell precision have rapidly advanced in the form of two-photon optogenetic stimulation. Unlike conveโฆ
We present a new large-scale electroencephalography (EEG) dataset as part of the THINGS initiative, comprising over 1.6 million visual stimulus trials collected from 20 participants, and totaling moreโฆ
Deep learning models have been frequently used to decode a single brain-computer interface (BCI) paradigm based on electroencephalography (EEG). It is challenging to decode multiple BCI paradigms usinโฆ
Brain morphology is shaped by genetic and mechanical factors and is linked to biological development and diseases. Its fractal-like features, regional anisotropy, and complex curvature distributions hโฆ
Prompt engineering has rapidly emerged as a critical skill for effective interaction with large language models (LLMs). However, the cognitive and neural underpinnings of this expertise remain largelyโฆ
Estimating neuron location from extracellular recordings is essential for developing advanced brain-machine interfaces. Accurate neuron localization improves spike sorting, which involves detecting acโฆ
Recent studies have shown how spiking networks can learn complex functionality through error-correcting plasticity, but the resulting structures and dynamics remain poorly studied. To elucidate how thโฆ
Neurological conditions affecting visual perception create profound experiential divides between affected individuals and their caregivers, families, and medical professionals. We present the Perceptuโฆ
Electroencephalogram (EEG) signals have gained widespread adoption in brain-computer interface (BCI) applications due to their non-invasive, low-cost, and relatively simple acquisition process. The deโฆ
Accurate reconstruction of neuronal morphology is essential for classifying cell types and understanding brain connectivity. Recent advances in imaging and reconstruction techniques have greatly expanโฆ
The functional brain network emerges from the complex, coordinated activity of distinct yet connected regions, which underlie the diverse repertoire of human cognitive functions. Structural Balance Thโฆ
Toy models are highly idealized and deliberately simplified models that retain only the essential features of a system in order to explore specific theoretical questions. Long used in physics and otheโฆ
The accurate identification of individuals from functional connectomes (FCs) is critical for advancing individualized assessments in neuropsychiatric research. Traditional methods, such as Pearson's cโฆ
Predicting behavioral variables from neuroimaging modalities such as magnetic resonance imaging (MRI) has the potential to allow the development of neuroimaging biomarkers of mental and neurological dโฆ
Preclinical models of neurodevelopmental and psychiatric conditions often rely on inbred mouse strains like C57BL/6J (B6), which exhibit limited genetic and behavioral variability. This limitation hamโฆ
Recent large scale behavioral studies suggest early emergence of gender differences in mathematical performance within months of school entry. However, these findings lack direct neural evidence and aโฆ
Functional differentiation in the brain emerges as distinct regions specialize and is key to understanding brain function as a complex system. Previous research has modeled this process using artificiโฆ
Current methodologies typically integrate biophysical brain models with functional magnetic resonance imaging(fMRI) data - while offering millimeter-scale spatial resolution (0.5-2 mm^3 voxels), theseโฆ
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