Artificial intelligence for brain diseases: A systematic review
Artificial intelligence (AI) is a major branch of computer science that is fruitfully used for
analyzing complex medical data and extracting meaningful relationships in datasets, for …
analyzing complex medical data and extracting meaningful relationships in datasets, for …
Nonlinear independent component analysis for principled disentanglement in unsupervised deep learning
A central problem in unsupervised deep learning is how to find useful representations of
high-dimensional data, sometimes called" disentanglement." Most approaches are heuristic …
high-dimensional data, sometimes called" disentanglement." Most approaches are heuristic …
Virtual reality in education: Focus on the role of emotions and physiological reactivity
M Vesisenaho, M Juntunen, P Häkkinen… - Journal of Virtual Worlds …, 2019 - jyx.jyu.fi
Cognitive and emotional dimensions are often linked to each other in learning experiences.
Moreover, emotions and engagement can lead to better outcomes at the cognitive level …
Moreover, emotions and engagement can lead to better outcomes at the cognitive level …
Mind-wandering in adolescents predicts worse affect and is linked to aberrant default mode network–salience network connectivity
Objective Understanding the fluctuating emotional and cognitive states of adolescents with
depressive symptoms requires fine-grained and naturalistic measurements. This study used …
depressive symptoms requires fine-grained and naturalistic measurements. This study used …
[HTML][HTML] Unsupervised representation learning of spontaneous MEG data with nonlinear ICA
Resting-state magnetoencephalography (MEG) data show complex but structured
spatiotemporal patterns. However, the neurophysiological basis of these signal patterns is …
spatiotemporal patterns. However, the neurophysiological basis of these signal patterns is …
Neurofeedback
M Hampson, S Ruiz, J Ushiba - Neuroimage, 2020 - pubmed.ncbi.nlm.nih.gov
Neurofeedback Neurofeedback Neuroimage. 2020 Sep;218:116473. doi: 10.1016/j.neuroimage.2019.116473.
Epub 2019 Dec 18. Authors Michelle Hampson 1 , Sergio Ruiz 2 , Junichi Ushiba 3 Affiliations …
Epub 2019 Dec 18. Authors Michelle Hampson 1 , Sergio Ruiz 2 , Junichi Ushiba 3 Affiliations …
Mind wandering state detection during video-based learning via EEG
S Tang, Y Liang, Z Li - Frontiers in human neuroscience, 2023 - frontiersin.org
The aim of this study is to explore the potential of technology for detecting mind wandering,
particularly during video-based distance learning, with the ultimate benefit of improving …
particularly during video-based distance learning, with the ultimate benefit of improving …
Decoding mindfulness with multivariate predictive models
Identifying the brain mechanisms that underlie the salutary effects of mindfulness meditation
and related practices is a critical goal of contemplative neuroscience. Here we suggest that …
and related practices is a critical goal of contemplative neuroscience. Here we suggest that …
Focus on the breath: Brain decoding reveals internal states of attention during meditation
Meditation practices are often used to cultivate interoception or internally-oriented attention
to bodily sensations, which may improve health via cognitive and emotional regulation of …
to bodily sensations, which may improve health via cognitive and emotional regulation of …
The heartbeat evoked potential does not support strong interoceptive sensibility in trait mindfulness
The enhancement of body awareness is proposed as one of the cognitive mechanisms that
characterize mindfulness. To date, this hypothesis is supported by self‐report and …
characterize mindfulness. To date, this hypothesis is supported by self‐report and …