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Dataset . 2017
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ZENODO
Dataset . 2017
License: CC BY
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ZENODO
Dataset . 2017
License: CC BY
Data sources: ZENODO
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Post-Hoc Labeling Of Arbitrary Eeg Recordings For Data-Efficient Evaluation Of Neural Decoding Methods

Authors: Sebastian Castaño-Candamil; Andreas Meinel; Michael Tangermann;

Post-Hoc Labeling Of Arbitrary Eeg Recordings For Data-Efficient Evaluation Of Neural Decoding Methods

Abstract

EEG signals recorded from seven healthy subjects. On average, Seventy-three minutes of EEG data were recorded from 31 electrodes placed according to the extended 10-20 system. Signals are used in the paradigm-agnostic post-hoc labeled dataset generation framework for benchmarking of oscillatory neural decoding methods.

Pre-print of the paper "Post-hoc labeling of arbitrary EEG recordings for data-efficient evaluation of neural decoding methods" available at http://arxiv.org/abs/1711.08208

Keywords

neural decoding, subspace decomposition methods, oscillatory sources, dataset generation, label generation, benchmark testbench

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citations
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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