2019
DOI: 10.3389/fphy.2019.00115
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Characterization of Visuomotor/Imaginary Movements in EEG: An Information Theory and Complex Network Approach

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Cited by 29 publications
(17 citation statements)
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References 81 publications
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“…As a result, network constituents identified as most important during the pre-stimulation phase remained unaffected during the stimulation and the post-stimulation phase. As regards most important vertices from the pre-stimulation phase, our findings are in line with previous observations that reported left frontocentral brain regions to be most important with betweenness centrality (van den Heuvel and Sporns, 2013 ; Jin et al, 2014 ; Makarov et al, 2018 ) as well as parieto-occipital brain regions to be most important with eigenvector centrality (Lohmann et al, 2010 ) and closeness centrality (van den Heuvel and Sporns, 2013 ; Baravalle et al, 2019 ) during a so-called resting state condition. Together, these findings corroborate the common perspective of different centrality concepts generally identifying different constituents as most important (Lü et al, 2016 ; Bröhl and Lehnertz, 2019 ).…”
Section: Discussionsupporting
confidence: 92%
“…As a result, network constituents identified as most important during the pre-stimulation phase remained unaffected during the stimulation and the post-stimulation phase. As regards most important vertices from the pre-stimulation phase, our findings are in line with previous observations that reported left frontocentral brain regions to be most important with betweenness centrality (van den Heuvel and Sporns, 2013 ; Jin et al, 2014 ; Makarov et al, 2018 ) as well as parieto-occipital brain regions to be most important with eigenvector centrality (Lohmann et al, 2010 ) and closeness centrality (van den Heuvel and Sporns, 2013 ; Baravalle et al, 2019 ) during a so-called resting state condition. Together, these findings corroborate the common perspective of different centrality concepts generally identifying different constituents as most important (Lü et al, 2016 ; Bröhl and Lehnertz, 2019 ).…”
Section: Discussionsupporting
confidence: 92%
“…As a result, network constituents identified as most important during the pre-stimulation phase remained unaffected during the stimulation and the poststimulation phase. As regards most important vertices from the pre-stimulation phase, our findings are in line with previous observations that reported left frontocentral brain regions to be most important with betweenness centrality (van den Heuvel and Sporns, 2013;Jin et al, 2014;Makarov et al, 2018) as well as parieto-occipital brain regions to be most important with eigenvector centrality (Lohmann et al, 2010) and closeness centrality (van den Heuvel and Sporns, 2013; Baravalle et al, 2019) during a so-called resting state condition. Together, these findings corroborate the common perspective of different centrality concepts generally identifying different constituents as most important (Lü et al, 2016;Bröhl and Lehnertz, 2019).…”
Section: Modifications On the Local Network Scalesupporting
confidence: 92%
“…Studies have shown that STDP can cause neurons to synchronize or desynchronize (Talathi et al, 2008;Popovych and Tass, 2012;Popovych et al, 2013;Borges et al, 2016Borges et al, , 2017Lameu et al, 2018), and the synchronization of neural activity is bound up with brain information processing (Baravalle et al, 2019). According to the encoding scheme in this model, the best decoding case is that the neurons are synchronized with specific phases (see section "Encoding and Decoding").…”
Section: Spike-timing-dependent Plasticitymentioning
confidence: 99%