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5
Feb
A new study reports for the first time functional interactions among brain rhythms in music perception using a novel, elegant, multiplex-aware approach based on a community detection algorithm.
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7
Sep
We investigated the possibility of using a machine-learning scheme in conjunction with commercial wearable EEG-devices for translating listener’s subjective experience of music into scores that can be used in popular on-demand music streaming services.
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30
Jan
The decision about the actual number of active neurons is an open issue in spike sorting, with sparsely firing neurons and background activity the most influencing factors. Dominant-sets clustering algorithm is a graph-theoretical algorithmic procedure that successfully addresses this issue. The quality of grouping in the data is evaluated with the estimation of ‘cohesiveness’, i.e. a cluster-quality measure, for each group.
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20
Sep
Applications of clustering algorithms in biomedical research are ubiquitous. However, due to the diversity of cluster analysis, the diversity of critical elements underlying different clustering algorithms can be daunting.
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- Brain-computer interfaces: where are we now?
- Imperial startup wins global competition for its brain-computer interface tech
- EEGminer: Discovering Interpretable Features of Brain Activity with Learnable Filters
- What can my brain tell me about the music I listen to ?
- A discriminative covariance-reduction approach for BCIs
- Postdoctoral Position at the SiNAPSE Institute, Singapore
- Postdoctoral position in Experimental / Theoretical Neuroscience in Heraklion, Crete
- Postdoctoral Research Position at Carnegie Mellon University
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