Brain connectivity is an important tool for understanding the cognitive and perceptive neural mechanisms in the neuroimaging field. Many methods for estimating effective connectivity have relied on the linear regressive model. However, the linear reg...
IEEE transactions on bio-medical engineering
Nov 21, 2024
OBJECTIVE: Brain dynamic effective connectivity (dEC), characterizes the information transmission patterns between brain regions that change over time, which provides insight into the biological mechanism underlying brain development. However, most e...
Motor imagery (MI) classification has been commonly employed in making brain-computer interfaces (BCI) to manage the outside tools as a substitute neural muscular path. Effectual MI classification in BCI improves communication and mobility for people...
Annals of the New York Academy of Sciences
Nov 20, 2024
Neuromorphic engineering is a research discipline that tries to bridge the gaps between neuroscience and engineering, cognition and algorithms, and natural and artificial intelligence. Neuromorphic engineering promises revolutionary breakthroughs tha...
PURPOSE: BUDA-cEPI has been shown to achieve high-quality, high-resolution diffusion magnetic resonance imaging (dMRI) with fast acquisition time, particularly when used in conjunction with S-LORAKS reconstruction. However, this comes at a cost of mo...
International journal of neural systems
Nov 19, 2024
Stroke, an abrupt cerebrovascular ailment resulting in brain tissue damage, has prompted the adoption of motor imagery (MI)-based brain-computer interface (BCI) systems in stroke rehabilitation. However, analyzing electroencephalogram (EEG) signals f...
International journal of neural systems
Nov 19, 2024
Paroxysmal kinesigenic dyskinesia (PKD) is a rare neurological disorder marked by transient involuntary movements triggered by sudden actions. Current diagnostic approaches, including genetic screening, face challenges in identifying secondary cases ...
The detection of patients in the cognitive normal (CN), mild cognitive impairment (MCI), and Alzheimer's disease (AD) stages of neurodegeneration is crucial for early treatment interventions. However, the heterogeneity of MCI data samples poses a cha...
Emotion recognition enables machines to more acutely perceive and understand users' emotional states, thereby offering more personalized and natural interactive experiences. Given the regularity of the responses of brain activity to human cognitive p...
The objective of this study was to explore the potential of machine-learning techniques in the automatic identification and classification of brain metastases from a radiomic perspective, aiming to improve the accuracy of tumor volume assessment for ...
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