Literature DB >> 11717711

Photic driving in the electroencephalogram of children and adolescents: harmonic structure and relation to the resting state.

V V Lazarev1, D M Simpson, B M Schubsky, L C Deazevedo.   

Abstract

In order to identify latent bioelectrical oscillators, 15 normal subjects (aged 9-17 years, 8 males, 7 females) were subjected to intermittent photic stimulation. The EEG amplitude spectra corresponding to the 11 fixed frequencies of stimulation presented (3-24 Hz) were combined to form "profiles" of the driving reaction in the right occipital area. The driving response varied with frequency, and was demonstrable in 70-100% of cases (using as criterion peak amplitudes 20% larger than those of the neighbors). The strongest responses were observed at the frequency closest to the alpha peak of the resting EEG. A secondary profile maximum was in the theta band. In 10 subjects, this maximum exceeded half the alpha peak (with an average of 72.4% of the alpha peak), while in the resting spectra, theta amplitudes were much lower than the alpha maxima. This responsiveness in theta activity seems to be characteristic of prepubertal and pubertal subjects. The profiles and resting EEG spectra showed a highly significant Pearson's correlation, with the peak in the theta band of the profiles being the main difference observed between them. The correlation coefficient was significantly correlated with the ratio of the maxima in the theta and alpha bands (R = -0.77, P<0.001). The correlation coefficient between profile and resting spectrum may be a useful indicator in screening methods used to reveal latent cerebral oscillators. Profiles for the second and third harmonics were correlated with those of the first harmonic (fundamental frequency), when considering the corresponding EEG frequencies. Peak frequencies in all three profiles were close to those of the individual's background alpha rhythm, and peak amplitudes in higher harmonics were not much lower than those of the fundamental frequency (mean values of 84 and 63%, for second and third harmonics, respectively).

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Year:  2001        PMID: 11717711     DOI: 10.1590/s0100-879x2001001200010

Source DB:  PubMed          Journal:  Braz J Med Biol Res        ISSN: 0100-879X            Impact factor:   2.590


  12 in total

1.  Evaluating the relationship of non-phase locked activities in the electroencephalogram during intermittent stimulation: a partial coherence-based approach.

Authors:  Antonio Mauricio F L Miranda de Sá; Antonio Fernando C Infantosi
Journal:  Med Biol Eng Comput       Date:  2007-07-05       Impact factor: 2.602

2.  A Preliminary Study on Photic Driving in the Electroencephalogram of Children with Autism across a Wide Cognitive and Behavioral Range.

Authors:  Luigi Vetri; Laura Maniscalco; Paola Diana; Marco Guidotti; Domenica Matranga; Frédérique Bonnet-Brilhault; Gabriele Tripi
Journal:  J Clin Med       Date:  2022-06-21       Impact factor: 4.964

3.  Reduced interhemispheric connectivity in childhood autism detected by electroencephalographic photic driving coherence.

Authors:  Vladimir V Lazarev; Adailton Pontes; Andrey A Mitrofanov; Leonardo C deAzevedo
Journal:  J Autism Dev Disord       Date:  2015-02

4.  Presence of strong harmonics during visual entrainment: a magnetoencephalography study.

Authors:  Elizabeth Heinrichs-Graham; Tony W Wilson
Journal:  Biol Psychol       Date:  2012-05-05       Impact factor: 3.251

5.  Modeling brain resonance phenomena using a neural mass model.

Authors:  Andreas Spiegler; Thomas R Knösche; Karin Schwab; Jens Haueisen; Fatihcan M Atay
Journal:  PLoS Comput Biol       Date:  2011-12-22       Impact factor: 4.475

6.  Rod Driven Frequency Entrainment and Resonance Phenomena.

Authors:  Christina Salchow; Daniel Strohmeier; Sascha Klee; Dunja Jannek; Karin Schiecke; Herbert Witte; Arye Nehorai; Jens Haueisen
Journal:  Front Hum Neurosci       Date:  2016-08-18       Impact factor: 3.169

7.  Alpha entrainment is responsible for the attentional blink phenomenon.

Authors:  Andrea Zauner; Robert Fellinger; Joachim Gross; Simon Hanslmayr; Kimron Shapiro; Walter Gruber; Sebastian Müller; Wolfgang Klimesch
Journal:  Neuroimage       Date:  2012-07-14       Impact factor: 6.556

8.  Age-specific mechanisms in an SSVEP-based BCI scenario: evidences from spontaneous rhythms and neuronal oscillators.

Authors:  Jan Ehlers; Diana Valbuena; Anja Stiller; Axel Gräser
Journal:  Comput Intell Neurosci       Date:  2012-12-06

9.  SSVEP response is related to functional brain network topology entrained by the flickering stimulus.

Authors:  Yangsong Zhang; Peng Xu; Yingling Huang; Kaiwen Cheng; Dezhong Yao
Journal:  PLoS One       Date:  2013-09-09       Impact factor: 3.240

10.  A new description of epileptic seizures based on dynamic analysis of a thalamocortical model.

Authors:  H Sohanian Haghighi; A H D Markazi
Journal:  Sci Rep       Date:  2017-10-19       Impact factor: 4.379

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