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Prefrontal Cortex

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Cortical activation in robot-assisted dynamic and static resistance training combining VR interaction: An fNIRS based pilot study.

NeuroRehabilitation
BACKGROUND: There are few isometric training systems based on upper limb rehabilitation robots. Its efficacy and neural mechanism are not well understood.

Modelling continual learning in humans with Hebbian context gating and exponentially decaying task signals.

PLoS computational biology
Humans can learn several tasks in succession with minimal mutual interference but perform more poorly when trained on multiple tasks at once. The opposite is true for standard deep neural networks. Here, we propose novel computational constraints for...

Schema formation in a neural population subspace underlies learning-to-learn in flexible sensorimotor problem-solving.

Nature neuroscience
Learning-to-learn, a progressive speedup of learning while solving a series of similar problems, represents a core process of knowledge acquisition that draws attention in both neuroscience and artificial intelligence. To investigate its underlying b...

Increased functional connectivity coupling with supplementary motor area in blepharospasm at rest.

Brain research
OBJECTIVE: To explore the abnormalities of brain function in blepharospasm (BSP) and to illustrate its neural mechanisms by assuming supplementary motor area (SMA) as the entry point.

Brain Activation Pattern Caused by Soft Rehabilitation Glove and Virtual Reality Scenes: A Pilot fNIRS Study.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Clinical studies have proved significant improvements in hand motor function in stroke patients when assisted by robotic devices. However, there were few studies on neural activity changes in the brain during execution. This study aimed to investigat...

Interpretable deep learning model for major depressive disorder assessment based on functional near-infrared spectroscopy.

Asian journal of psychiatry
BACKGROUND: Major depressive disorder (MDD) affects a substantial number of individuals worldwide. New approaches are required to improve the diagnosis of MDD, which relies heavily on subjective reports of depression-related symptoms.

Study of a PST-trained voice-enabled artificial intelligence counselor for adults with emotional distress (SPEAC-2): Design and methods.

Contemporary clinical trials
BACKGROUND: Novel and scalable psychotherapies are urgently needed to address the depression and anxiety epidemic. Leveraging artificial intelligence (AI), a voice-based virtual coach named Lumen was developed to deliver problem solving treatment (PS...

A recurrent network model of planning explains hippocampal replay and human behavior.

Nature neuroscience
When faced with a novel situation, people often spend substantial periods of time contemplating possible futures. For such planning to be rational, the benefits to behavior must compensate for the time spent thinking. Here, we capture these features ...

Identifying neuroimaging biomarkers in major depressive disorder using machine learning algorithms and functional near-infrared spectroscopy (fNIRS) during verbal fluency task.

Journal of affective disorders
One of the most prevalent psychiatric disorders is major depressive disorder (MDD), which increases the probability of suicidal ideation or untimely demise. Abnormal frontal hemodynamic changes detected by functional near-infrared spectroscopy (fNIRS...

Spatially Informed Graph Structure Learning Extracts Insights from Spatial Transcriptomics.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)
Embeddings derived from cell graphs hold significant potential for exploring spatial transcriptomics (ST) datasets. Nevertheless, existing methodologies rely on a graph structure defined by spatial proximity, which inadequately represents the diversi...