A5019718199- Motor Control and Adaptation
- Action Observation and Synchronization
- Functional Brain Connectivity Studies
- Neural dynamics and brain function
- Muscle activation and electromyography studies
- Neural and Behavioral Psychology Studies
- EEG and Brain-Computer Interfaces
- Free Will and Agency
- Vestibular and auditory disorders
- Visual perception and processing mechanisms
- Psychosomatic Disorders and Their Treatments
- Advanced MRI Techniques and Applications
- Tactile and Sensory Interactions
- Mental Health Research Topics
- Advanced Neuroimaging Techniques and Applications
- Robot Manipulation and Learning
- Balance, Gait, and Falls Prevention
- Memory and Neural Mechanisms
- Psychology of Moral and Emotional Judgment
- Autism Spectrum Disorder Research
- Neuroendocrine regulation and behavior
- Embodied and Extended Cognition
- Stress Responses and Cortisol
- Attention Deficit Hyperactivity Disorder
- Neuroscience and Neuropharmacology Research
The University of Tokyo
2016-2025
Advanced Telecommunications Research Institute International
2016-2025
Osaka University
2013-2018
National Institute of Information and Communications Technology
2008-2018
Research Organization of Information and Systems
1995-2016
Transnet (South Africa)
2014
Data61
2010
Nature Inspires Creativity Engineers Lab
2004
Oxford Centre for Computational Neuroscience
2004
Kyoto Research Park
2002
Although autism spectrum disorder (ASD) is a serious lifelong condition, its underlying neural mechanism remains unclear. Recently, neuroimaging-based classifiers for ASD and typically developed (TD) individuals were to identify the abnormality of functional connections (FCs). Due over-fitting interferential effects varying measurement conditions demographic distributions, no have been strictly validated independent cohorts. Here we overcome these difficulties by developing novel...
When collecting large amounts of neuroimaging data associated with psychiatric disorders, images must be acquired from multiple sites because the limited capacity a single site. However, site differences represent barrier when acquiring multisite data. We utilized traveling-subject dataset in conjunction multisite, multidisorder to demonstrate that are composed biological sampling bias and engineering measurement bias. The effects on resting-state functional MRI connectivity based pairwise...
Human capabilities in dexterously manipulating many different tools suggest modular neural organization at functional levels, but anatomical modularity underlying the has yet to be demonstrated. Although phylogenetically older parts of cerebellum is well known, comparable lateral for cognitive functions remains unknown. We investigated these issues by MRI (fMRI) based on our previous findings a cerebellar internal model tool. After subjects intensively learned manipulate two novel (the...
Quantitative examinations of internal representations for arm trajectory planning: minimum commanded torque change model. A number invariant features multijoint planar reaching movements have been observed in measured hand trajectories. These include roughly straight paths and bell-shaped speed profiles where the curvatures between transverse radial found to be different. For quantitative statistical investigations, we obtained a large amount data within wide range workspace horizontal...
Humans can acquire appropriate behaviors that maximize rewards on a trial-and-error basis. Recent electrophysiological and imaging studies have demonstrated neural activity in the midbrain ventral striatum encodes error of reward prediction. However, it is yet to be examined whether main locus reward-based behavioral learning. To address this, we conducted functional magnetic resonance (fMRI) stochastic decision task involving monetary rewards, which subjects had learn different difficulties...
The learning process of reaching movements was examined under novel environments whose kinematic and dynamic properties were altered. We used a transformation (visuomotor rotation), (viscous curl field), combination these transformations. When the subjects learned combined transformation, errors smaller if subject first separate Reaching (but not dynamic) transformation. These results suggest that brain learns multiple internal models to compensate for each has some ability combine decompose...
Abstract Previous functional imaging experiments in humans showed activation increases the posterior superior temporal gyrus and sulcus during observation of geometrical shapes whose movements appear intentional or goal-directed. We modeled a chase scenario between two objects, which chasing object used different strategies to reach target object: The chaser either followed target's path appeared predict its end position. Activation human observers was greater when adopted rather than follow...
Motor or perceptual learning is known to influence functional connectivity between brain regions and induce short-term changes in the intrinsic networks revealed as correlations slow blood-oxygen-level dependent (BOLD) signal fluctuations. However, no cause-and-effect relationship has been elucidated a specific change long-term global networks. Here, we examine hypothesis that (i.e. temporal correlation two regions) increased preserved for long time when are simultaneously activated...
Recent computational and behavioral studies suggest that motor adaptation results from the update of multiple memories with different timescales. Here, we designed a model-based functional magnetic resonance imaging (fMRI) experiment in which subjects adapted to two opposing visuomotor rotations. A model was fitted data generate time-varying regressors brain activity. We identified regional specificity timescales: particular, activity inferior parietal region anterior-medial cerebellum...
Abstract Machine learning classifiers for psychiatric disorders using resting-state functional magnetic resonance imaging (rs-fMRI) have recently attracted attention as a method directly examining relationships between neural circuits and disorders. To develop accurate generalizable classifiers, we compiled large-scale, multi-site, multi-disorder neuroimaging database. The database comprises fMRI structural images of the brain from 993 patients 1,421 healthy individuals, well demographic...
Working memory deficits are present in many neuropsychiatric diseases with diagnosis-related severity. However, it is unknown whether this common behavioral abnormality a continuum explained by neural mechanism shared across or set of discrete dysfunctions. Here, we performed predictive modeling to examine working ability (WMA) as function normative whole-brain connectivity psychiatric diseases. We built quantitative model for letter three-back task performance healthy participants, using...
Many studies have highlighted the difficulty inherent to clinical application of fundamental neuroscience knowledge based on machine learning techniques. It is difficult generalize brain markers data acquired from independent imaging sites, mainly due large site differences in functional magnetic resonance imaging. We address finding a generalizable marker major depressive disorder (MDD) that would distinguish patients healthy controls resting-state connectivity patterns. For discovery...
Abstract Electroencephalography (EEG) microstates constitute temporal map configurations that reflect the whole brain electrical state. The dynamics of EEG may serve as an effective discretization method for capturing spatiotemporally continuous neural with high resolution. In this study, we employed polarity-sensitive microstate analysis to investigate whole-brain state transitions during audiovisual oddball tasks. Moreover, examined how sensory modality and its coupling, types response...
An internal model is a neural mechanism that can mimic the input-output properties of controlled object such as tool. Recent research interests have moved on to how multiple models are learned and switched under given context behavior. Two representative computational for task switching propose distinct mechanisms, thus predicting different brain activity patterns in models. In one model, called mixture-of-experts architecture, commanded by single executive "gating network," which from other...
To assess the functional locus of visual-motor learning, computational concepts "task level" programming (determination trajectory a hand during arm reaching in Cartesian coordinates) and "manipulator joint was adopted. Because former is likely to be nonspecific latter specific, it assumed that learning at task level should transferred unpracticed hand, whereas manipulator not. Under this assumption, paradigm intermanual transfer used an aiming under rotated visual feedback. Nearly 100% from...
Functional MRI was used to test predictions from a theory of the origin human language. The gradual suggests that language and tool-use skills have similar hierarchical structure, proposes tool-manipulation are related evolution Our results show an overlap brain activity for perceiving using tools in Broca's area. location this tool use share computational principles processing complex structures common these two abilities. involvement monkeys' homologous region during neural processes...
Advances in functional magnetic resonance imaging have made it possible to provide real-time feedback on brain activity. Neurofeedback has been applied therapeutic interventions for psychiatric disorders. Since many studies shown that most disorders exhibit abnormal networks, a novel experimental paradigm named connectivity neurofeedback, which can directly modulate network, emerged as promising approach treat Here, we investigated the hypothesis neurofeedback induce aimed direction of...
Abstract Background and Hypothesis Dynamics of the distributed sets functionally synchronized brain regions, known as large-scale networks, are essential for emotional state cognitive processes. However, few studies were performed to elucidate aberrant dynamics across networks multiple psychiatric disorders. In this paper, we aimed investigate dynamic aspects aberrancy causal connections among Study Design We applied modeling (DCM) large-sample multi-site dataset with 739 participants from 4...