EEG oscillations: From correlation to causality

Herrmann, Christoph S.; Strüber, Daniel; Helfrich, Randolph F.; Engel, Andreas K.

doi:10.1016/j.ijpsycho.2015.02.003

Cited by 397 publications

(354 citation statements)

References 101 publications

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“…In our study, networks of both groups showed small world network properties with significant differences in high frequencies (beta and gamma bands) with lower values for the HMA group. Beta and gamma bands express mainly local activations (Bidelman, 2015;Herrmann, Strüber, Helfrich, & Engel, 2015;Lewis, Wang, & Bastiaansen, 2015), while the lower SWN index is explained as the result of local activation and expression of the local desynchronization during the anxiety reactivity. Moreover, the CC shows higher values in HMA in the same bands as a sign of higher local segregation.…”

Section: Discussionmentioning

confidence: 99%

Math anxiety: Brain cortical network changes in anticipation of doing mathematics

Klados

Pandria

Micheloyannis

et al. 2017

International Journal of Psychophysiology

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Following our previous work regarding the involvement of math anxiety (MA) in math-oriented tasks, this study tries to explore the differences in the cerebral networks' topology between self-reported low math-anxious (LMA) and high math-anxious (HMA) individuals, during the anticipation phase prior to a mathematical related experiment. For this reason, multichannel EEG recordings were adopted, while the solution of the inverse problem was applied in a generic head model, in order to obtain the cortical signals. The cortical networks have been computed for each band separately, using the magnitude square coherence metric. The main graph theoretical parameters, showed differences in segregation and integration in almost all EEG bands of the HMAs in comparison to LMAs, indicative of a great influence of the anticipatory anxiety prior to mathematical performance.

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Section: Discussionmentioning

confidence: 99%

Math anxiety: Brain cortical network changes in anticipation of doing mathematics

Klados

Pandria

Micheloyannis

et al. 2017

International Journal of Psychophysiology

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“…He attached electrodes, which measured electrical activity, to his subject's head, amplified the signals the electrodes measured so that they could be seen by scientific equipment, and observed curves that looked like waves (Figures 1B,C) [1]. This was the discovery of what we now call electroencephalogram (EEG), the electrical activity in the brain and brain waves, which are also called oscillations.…”

Section: The Discovery Of the Brain Waves In Humansmentioning

confidence: 98%

“…Scientists hypothesized that brain waves are not just a byproduct of the brain at work, but they might actually contribute in an important way to how the brain works [1]. If brain waves repeat themselves multiple times per second, does our perception and behavior also change multiple times per second [4]?…”

Section: Oscillationmentioning

confidence: 99%

“…We thought it would give us more information if we did this experiment in reverse, so that we could tell for sure if the brain waves were directly responsible for the behavior of the participants. We wondered if we could alter the brain waves and then study how perception and individual behavior change in relation to the change in brain waves ( Figure 1E) [1]. In short, could we change brain waves to make the behavior change?…”

Section: Oscillationmentioning

confidence: 99%

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Waves of Perception

Ram¹,

Helfrich²

2017

Front. Young Minds

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“…O ritmo Gama, que atua na faixa de 35 a 80 Hz, e o ritmo Supergama, que é observado em frequências maiores de 80 Hz, podem estar associados com estados de consciência, memória e processamento da informação [6].…”

Section: Introductionunclassified

Variação Da Frequência Cerebral Medida Em Exame De Eletroencefalografia

Oliveira¹,

Ramos²,

Carrijo³

et al. 2018

Anais Do v Congresso Brasileiro De Eletromiografia E Cinesiologia E X Simpósio De Engenharia Biomédica

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Resumo: Sinais EEG são cada vez mais utilizados em diagnósticos de patologias e ainda em estudos de consciência e processamento da informação. Valores considerados normais não são estabelecidos para esse tipo de sinal, o que dificulta um diagnóstico preciso. A partir dessas considerações esse estudo tem o objetivo de avaliar a variabilidade biológica existente em sinais EEG normais, oriundos de população saudável, e EEG em coma, partindo do conceito de energia espectral do sinal EEG. Materiais e métodosNesse estudo foram analisados sinais EEG advindos de dois grupos distintos, coma e controle, autorizado pelo Comitê de Ética em Pesquisa da UFU (CEP -UFU) sob protocolo de número 54781615.6.0000.5152. A metodologia foi dividida em: Coleta dos dados, Pré-

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EEG oscillations: From correlation to causality

Cited by 397 publications

References 101 publications

Math anxiety: Brain cortical network changes in anticipation of doing mathematics

Math anxiety: Brain cortical network changes in anticipation of doing mathematics

Waves of Perception

Variação Da Frequência Cerebral Medida Em Exame De Eletroencefalografia

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