Literature DB >> 17234291

Entropy changes in brain function.

Osvaldo A Rosso1.   

Abstract

The traditional way of analyzing brain electrical activity, on the basis of electroencephalography (EEG) records, relies mainly on visual inspection and years of training. Although it is quite useful, of course, one has to acknowledge its subjective nature that hardly allows for a systematic protocol. In the present work quantifiers based on information theory and wavelet transform are reviewed. The "relative wavelet energy" provides information about the relative energy associated with different frequency bands present in the EEG and their corresponding degree of importance. The "normalized total wavelet entropy" carries information about the degree of order-disorder associated with a multi-frequency signal response. Their application in the analysis and quantification of short duration EEG signals (event-related potentials) and epileptic EEG records are summarized.

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Year:  2007        PMID: 17234291     DOI: 10.1016/j.ijpsycho.2006.07.010

Source DB:  PubMed          Journal:  Int J Psychophysiol        ISSN: 0167-8760            Impact factor:   2.997


  6 in total

1.  The dynamics of EEG entropy.

Authors:  Massimiliano Ignaccolo; Mirek Latka; Wojciech Jernajczyk; Paolo Grigolini; Bruce J West
Journal:  J Biol Phys       Date:  2009-08-11       Impact factor: 1.365

2.  Neuronal dynamics enable the functional differentiation of resting state networks in the human brain.

Authors:  Marco Marino; Quanying Liu; Jessica Samogin; Franca Tecchio; Carlo Cottone; Dante Mantini; Camillo Porcaro
Journal:  Hum Brain Mapp       Date:  2018-11-15       Impact factor: 5.038

3.  Incoordination between spikes and LFPs in Aβ1-42-mediated memory deficits in rats.

Authors:  Wenwen Bai; Hu Yi; Tiaotiao Liu; Jing Wei; Xin Tian
Journal:  Front Behav Neurosci       Date:  2014-11-27       Impact factor: 3.558

4.  Analysis of complexity in the EEG activity of Parkinson's disease patients by means of approximate entropy.

Authors:  Chiara Pappalettera; Francesca Miraglia; Maria Cotelli; Paolo Maria Rossini; Fabrizio Vecchio
Journal:  Geroscience       Date:  2022-03-28       Impact factor: 7.581

5.  An Automatic Prediction of Epileptic Seizures Using Cloud Computing and Wireless Sensor Networks.

Authors:  Sanjay Sareen; Sandeep K Sood; Sunil Kumar Gupta
Journal:  J Med Syst       Date:  2016-09-15       Impact factor: 4.460

6.  Investigating neuromagnetic brain responses against chromatic flickering stimuli by wavelet entropies.

Authors:  Mayank Bhagat; Chitresh Bhushan; Goutam Saha; Shinsuke Shimjo; Katsumi Watanabe; Joydeep Bhattacharya
Journal:  PLoS One       Date:  2009-09-25       Impact factor: 3.240

  6 in total

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