A5015747771- Neural dynamics and brain function
- Neural and Behavioral Psychology Studies
- EEG and Brain-Computer Interfaces
- Model Reduction and Neural Networks
- Blind Source Separation Techniques
- Gaussian Processes and Bayesian Inference
- Generative Adversarial Networks and Image Synthesis
- Mobile Health and mHealth Applications
- Physical Activity and Health
- Behavioral Health and Interventions
- Neuroscience, Education and Cognitive Function
- Green IT and Sustainability
- Functional Brain Connectivity Studies
- Neural Networks and Applications
- Innovative Human-Technology Interaction
- Obesity, Physical Activity, Diet
Technical University of Denmark
2014-2017
Abstract We performed simultaneous recordings of electroencephalography (EEG) from multiple students in a classroom, and measured the inter-subject correlation (ISC) activity evoked by common video stimulus. The neural reliability, as quantified ISC, has been linked to engagement attentional modulation earlier studies that used high-grade equipment laboratory settings. Here we reproduce many results these using portable low-cost equipment, focusing on robustness ISC for subjects experiencing...
This paper takes a step towards temporal reasoning in dynamically changing video, not the pixel space that constitutes its frames, but latent describes non-linear dynamics of objects world. We introduce Kalman variational auto-encoder, framework for unsupervised learning sequential data disentangles two representations: an object's representation, coming from recognition model, and state describing dynamics. As result, evolution world can be imagined missing imputed, both without need to...
Correlated component analysis as proposed by Dmochowski, Sajda, Dias, and Parra (2012) is a tool for investigating brain process similarity in the responses to multiple views of given stimulus. components are identified under assumption that involved spatial networks identical. Here we propose hierarchical probabilistic model can infer level universality such multiview data, from completely unrelated representations, corresponding canonical correlation analysis, identical representations...
We propose a probabilistic generative multi-view model to test the representational universality of human information processing. The is tested in simulated data and well-established benchmark EEG dataset.
We performed simultaneous recordings of electroencephalography (EEG) from multiple students in a classroom, and measured the inter-subject correlation (ISC) activity evoked by common video stimulus. The neural reliability, as quantified ISC, has been linked to engagement attentional modulation earlier studies that used high-grade equipment laboratory settings. Here we reproduce many results these using portable low-cost equipment, focusing on robustness ISC for subjects experiencing...
<sec> <title>BACKGROUND</title> Clinical trials are expensive why it should be a priority to acquire as much data possible during the trial. The burden on participants and staff is often limiting factor amount of feasibly acquired, which may benefit from incorporating readily available small sensor-packed ubiquitous device; smartphone. </sec> <title>OBJECTIVE</title> aim this study was assess whether smartphone can assist or replace existing practices in evaluating physical activity...