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Alexander Kraskov

Researcher at UCL Institute of Neurology

Publications -  63
Citations -  9464

Alexander Kraskov is an academic researcher from UCL Institute of Neurology. The author has contributed to research in topics: Mutual information & Pyramidal tracts. The author has an hindex of 34, co-authored 63 publications receiving 8364 citations. Previous affiliations of Alexander Kraskov include Newcastle University & Forschungszentrum Jülich.

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Estimating mutual information.

TL;DR: Two classes of improved estimators for mutual information M(X,Y), from samples of random points distributed according to some joint probability density mu(x,y), based on entropy estimates from k -nearest neighbor distances are presented.
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Reply to ``Comment on `Performance of different synchronization measures in real data: A case study on electroencephalographic signals' ''

TL;DR: It is claimed that the applied measures used in the synchronization between left and right hemisphere rat electroencephalographic channels are valuable for the study of synchronization in real data and in the particular case of EEG signals their use as complementary variables could be of clinical relevance.
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Performance of different synchronization measures in real data: A case study on electroencephalographic signals

TL;DR: In this article, the synchronization between left and right hemisphere rat electroencephalographic (EEG) channels by using various synchronization measures, namely nonlinear interdependences, phase synchronizations, mutual information, cross correlation, and the coherence function, was studied.
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On the predictability of epileptic seizures.

TL;DR: The most promising approach for prospective seizure anticipation could be a combination of bivariate and univariate measures, which provide statistically significant evidence for the existence of a preictal state.
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Object Selectivity of Local Field Potentials and Spikes in the Macaque Inferior Temporal Cortex

TL;DR: In this article, local field potentials (LFPs) arise largely from dendritic activity over large brain regions and provide a measure of the input to and local processing within an area.