Because depression has high prevalence and cause enduring disability, it is important to predict onset of depression among community dwelling adults. In this study, we aimed to build a machine learning-based predictive model for future onset of depre...
Food exploration is an essential survival behavior in organisms. To find food efficiently, many organisms use a foraging strategy called area-restricted search (ARS) wherein individuals first turn more frequently, restricting their search to one area...
Artificial intelligence allows machines to predict human faculties such as image and voice recognition. Can machines be taught to measure pain? We argue that the two fundamental requirements for a device with 'pain biomarker' capabilities are hardwar...
Previous brain morphology-related diagnostic models for attention-deficit hyperactivity disorder (ADHD) were based on regional features. However, building a model of individual interregional morphological connectivity is a challenging task. This stud...
Auditory learning induces frequency-specific plasticity in the auditory cortex. Both the auditory cortex and thalamus are involved in the cortical plasticity; however, the precise role of the intracortical circuity remains unclear until the contribut...
Machine learning methods have been widely used in recent years for detection of neuroimaging biomarkers in regions of interest (ROIs) and assisting diagnosis of neurodegenerative diseases. The innovation of this study is to use multilevel-ROI-feature...
Artificial neural systems and nervous graph theoretical analysis rely upon the stance that the neural code is embodied in logic circuits, e.g., spatio-temporal sequences of ON/OFF spiking neurons. Nevertheless, this assumption does not fully explain ...
Gait analysis plays an important role in maintaining the well-being of human mobility and health care, and is a valuable tool for obtaining quantitative information on motor deficits in Parkinson's disease (PD). In this paper, we propose a method to ...