-
Je něco špatně v tomto záznamu ?
Age-dependent complex noise fluctuations in the brain
J. Mareš, O. Vyšata, A. Procházka, M. Vališ,
Jazyk angličtina Země Anglie, Velká Británie
Typ dokumentu časopisecké články, práce podpořená grantem
- MeSH
- dospělí MeSH
- elektrody MeSH
- elektroencefalografie přístrojové vybavení metody MeSH
- lidé středního věku MeSH
- lidé MeSH
- mladiství MeSH
- mladý dospělý MeSH
- mozek fyziologie MeSH
- počítačové zpracování signálu MeSH
- poměr signál - šum * MeSH
- senioři MeSH
- věkové faktory MeSH
- Check Tag
- dospělí MeSH
- lidé středního věku MeSH
- lidé MeSH
- mladiství MeSH
- mladý dospělý MeSH
- mužské pohlaví MeSH
- senioři MeSH
- ženské pohlaví MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
We investigated the parameters of colored noise in EEG data of 17 722 professional drivers aged 18-70. The whole study is based upon experiments showing that biological neural networks may operate in the vicinity of the critical point and that the balance between excitation and inhibition in the human brain is important for the transfer of information. This paper is devoted to the study of EEG power spectrum which can be described best by a power function with 1/f(λ) distribution and colored noise corresponding to the critical point in the EEG signal has the value of λ = 1 (purple noise). The slow accumulation of energy and its quick release is a universal property of the 1/f distribution. The physiological mechanism causing energy dissipation in the brain seems to depend on the number and strength of the connections between clusters of neurons. With ageing, the number of connections between the neurons decreases. Learning ability and intellectual performance also decrease. Therefore, age-related changes in the λ coefficient can be anticipated. We found that absolute values of λ coefficients decrease significantly with increasing age. Deviations from this rule are related to age-dependent slowing of the dominant frequency in the alpha band. Age-dependent change in the parameter and colored noise may be indicative of age-related changes in the self-organization of brain activity. Results obtained include (i) the age-dependent decrease of the absolute values of the average λ coefficient with the regression coefficient 0.005 1/year, (ii) distribution of λ value changes related to EEG frequency bands and to localization of electrodes on the scalp, and (iii) relation of age-dependent changes of colored noise and EEG energy in separate frequency bands.
Citace poskytuje Crossref.org
- 000
- 00000naa a2200000 a 4500
- 001
- bmc14063983
- 003
- CZ-PrNML
- 005
- 20140930102428.0
- 007
- ta
- 008
- 140704s2013 enk f 000 0|eng||
- 009
- AR
- 024 7_
- $a 10.1088/0967-3334/34/10/1269 $2 doi
- 035 __
- $a (PubMed)24021817
- 040 __
- $a ABA008 $b cze $d ABA008 $e AACR2
- 041 0_
- $a eng
- 044 __
- $a enk
- 100 1_
- $a Mareš, Jan $u Institute of Chemical Technology, Department of Computing and Control Engineering, Technicka 5, 166 28 Prague 6, Czech Republic.
- 245 10
- $a Age-dependent complex noise fluctuations in the brain / $c J. Mareš, O. Vyšata, A. Procházka, M. Vališ,
- 520 9_
- $a We investigated the parameters of colored noise in EEG data of 17 722 professional drivers aged 18-70. The whole study is based upon experiments showing that biological neural networks may operate in the vicinity of the critical point and that the balance between excitation and inhibition in the human brain is important for the transfer of information. This paper is devoted to the study of EEG power spectrum which can be described best by a power function with 1/f(λ) distribution and colored noise corresponding to the critical point in the EEG signal has the value of λ = 1 (purple noise). The slow accumulation of energy and its quick release is a universal property of the 1/f distribution. The physiological mechanism causing energy dissipation in the brain seems to depend on the number and strength of the connections between clusters of neurons. With ageing, the number of connections between the neurons decreases. Learning ability and intellectual performance also decrease. Therefore, age-related changes in the λ coefficient can be anticipated. We found that absolute values of λ coefficients decrease significantly with increasing age. Deviations from this rule are related to age-dependent slowing of the dominant frequency in the alpha band. Age-dependent change in the parameter and colored noise may be indicative of age-related changes in the self-organization of brain activity. Results obtained include (i) the age-dependent decrease of the absolute values of the average λ coefficient with the regression coefficient 0.005 1/year, (ii) distribution of λ value changes related to EEG frequency bands and to localization of electrodes on the scalp, and (iii) relation of age-dependent changes of colored noise and EEG energy in separate frequency bands.
- 650 _2
- $a mladiství $7 D000293
- 650 _2
- $a dospělí $7 D000328
- 650 _2
- $a věkové faktory $7 D000367
- 650 _2
- $a senioři $7 D000368
- 650 _2
- $a mozek $x fyziologie $7 D001921
- 650 _2
- $a elektrody $7 D004566
- 650 _2
- $a elektroencefalografie $x přístrojové vybavení $x metody $7 D004569
- 650 _2
- $a ženské pohlaví $7 D005260
- 650 _2
- $a lidé $7 D006801
- 650 _2
- $a mužské pohlaví $7 D008297
- 650 _2
- $a lidé středního věku $7 D008875
- 650 _2
- $a počítačové zpracování signálu $7 D012815
- 650 12
- $a poměr signál - šum $7 D059629
- 650 _2
- $a mladý dospělý $7 D055815
- 655 _2
- $a časopisecké články $7 D016428
- 655 _2
- $a práce podpořená grantem $7 D013485
- 700 1_
- $a Vyšata, Oldřich $7 xx0060120
- 700 1_
- $a Procházka, Aleš, $d 1948- $7 jo20010082307
- 700 1_
- $a Vališ, Martin, $d 1973- $7 xx0107109
- 773 0_
- $w MED00181057 $t Physiological measurement $x 1361-6579 $g Roč. 34, č. 10 (2013), s. 1269-1279
- 856 41
- $u http://iopscience.iop.org/0967-3334/34/10/1269/pdf/0967-3334_34_10_1269.pdf $y domovská stránka časopisu
- 910 __
- $a ABA008 $y 4 $z 0
- 990 __
- $a 20140704 $b ABA008
- 991 __
- $a 20140930102853 $b ABA008
- 999 __
- $a ok $b bmc $g 1031467 $s 862715
- BAS __
- $a 3
- BAS __
- $a PreBMC
- BMC __
- $a 2013 $b 34 $c 10 $d 1269-1279 $i 1361-6579 $m Physiological measurement $n Physiol Meas $x MED00181057
- LZP __
- $a Pubmed-20140704