A neural mass model of cross frequency coupling
Electrophysiological signals of cortical activity show a range of possible frequency and amplitude modulations, both within and across regions, collectively known as cross-frequency coupling. To investigate whether these modulations could be considered as manifestations of the same underlying mechan...
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| Veröffentlicht in: | PloS one 2017-04, Vol.12 (4), p.e0173776-e0173776 |
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| creator | Chehelcheraghi, Mojtaba van Leeuwen, Cees Steur, Erik Nakatani, Chie |
| description | Electrophysiological signals of cortical activity show a range of possible frequency and amplitude modulations, both within and across regions, collectively known as cross-frequency coupling. To investigate whether these modulations could be considered as manifestations of the same underlying mechanism, we developed a neural mass model. The model provides five out of the theoretically proposed six different coupling types. Within model components, slow and fast activity engage in phase-frequency coupling in conditions of low ambient noise level and with high noise level engage in phase-amplitude coupling. Between model components, these couplings can be coordinated via slow activity, giving rise to more complex modulations. The model, thus, provides a coherent account of cross-frequency coupling, both within and between components, with which regional and cross-regional frequency and amplitude modulations could be addressed. |
| doi_str_mv | 10.1371/journal.pone.0173776 |
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To investigate whether these modulations could be considered as manifestations of the same underlying mechanism, we developed a neural mass model. The model provides five out of the theoretically proposed six different coupling types. Within model components, slow and fast activity engage in phase-frequency coupling in conditions of low ambient noise level and with high noise level engage in phase-amplitude coupling. Between model components, these couplings can be coordinated via slow activity, giving rise to more complex modulations. The model, thus, provides a coherent account of cross-frequency coupling, both within and between components, with which regional and cross-regional frequency and amplitude modulations could be addressed.</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0173776</identifier><identifier>PMID: 28380064</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Assemblies ; Attention ; Bifurcations ; Biology and Life Sciences ; Brain ; Brain - physiology ; Brain research ; Chlorofluorocarbons ; Chokes (Electricity) ; Coding ; Cognition ; Cognition & reasoning ; Cognitive ability ; Computer simulation ; Control theory ; Cortex (auditory) ; Cortex (temporal) ; Coupling (molecular) ; Couplings ; Deep brain stimulation ; EEG ; Electroencephalography - methods ; Electrophysiology ; Engineering ; Epilepsy ; Event-related potentials ; Excitability ; Feedback ; Frequency dependence ; Hippocampus ; Humans ; Information processing ; Information transfer ; Interneurons ; Ketamine ; Luteinizing hormone ; Mathematical models ; Mechanical engineering ; Medicine and Health Sciences ; Methods ; Models, Biological ; Modulation ; Neural circuitry ; Neural networks ; Neuroimaging ; Neuromodulation ; Neurons ; Neurons - physiology ; Noise ; Noise levels ; Oscillations ; Phase shift ; Physical Sciences ; Population ; Populations ; Propagation ; Relay ; Research and Analysis Methods ; Rhythm ; Simulation ; Sleep ; Stimulation ; Temporal lobe ; Utilities ; Visual cortex ; Visual perception</subject><ispartof>PloS one, 2017-04, Vol.12 (4), p.e0173776-e0173776</ispartof><rights>COPYRIGHT 2017 Public Library of Science</rights><rights>2017 Chehelcheraghi et al. 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To investigate whether these modulations could be considered as manifestations of the same underlying mechanism, we developed a neural mass model. The model provides five out of the theoretically proposed six different coupling types. Within model components, slow and fast activity engage in phase-frequency coupling in conditions of low ambient noise level and with high noise level engage in phase-amplitude coupling. Between model components, these couplings can be coordinated via slow activity, giving rise to more complex modulations. The model, thus, provides a coherent account of cross-frequency coupling, both within and between components, with which regional and cross-regional frequency and amplitude modulations could be addressed.</description><subject>Assemblies</subject><subject>Attention</subject><subject>Bifurcations</subject><subject>Biology and Life Sciences</subject><subject>Brain</subject><subject>Brain - physiology</subject><subject>Brain research</subject><subject>Chlorofluorocarbons</subject><subject>Chokes (Electricity)</subject><subject>Coding</subject><subject>Cognition</subject><subject>Cognition & reasoning</subject><subject>Cognitive ability</subject><subject>Computer simulation</subject><subject>Control theory</subject><subject>Cortex (auditory)</subject><subject>Cortex (temporal)</subject><subject>Coupling (molecular)</subject><subject>Couplings</subject><subject>Deep brain stimulation</subject><subject>EEG</subject><subject>Electroencephalography - methods</subject><subject>Electrophysiology</subject><subject>Engineering</subject><subject>Epilepsy</subject><subject>Event-related potentials</subject><subject>Excitability</subject><subject>Feedback</subject><subject>Frequency dependence</subject><subject>Hippocampus</subject><subject>Humans</subject><subject>Information processing</subject><subject>Information transfer</subject><subject>Interneurons</subject><subject>Ketamine</subject><subject>Luteinizing hormone</subject><subject>Mathematical models</subject><subject>Mechanical engineering</subject><subject>Medicine and Health Sciences</subject><subject>Methods</subject><subject>Models, Biological</subject><subject>Modulation</subject><subject>Neural circuitry</subject><subject>Neural networks</subject><subject>Neuroimaging</subject><subject>Neuromodulation</subject><subject>Neurons</subject><subject>Neurons - 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Academic</collection><collection>PubMed Central (Full Participant titles)</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>PloS one</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Chehelcheraghi, Mojtaba</au><au>van Leeuwen, Cees</au><au>Steur, Erik</au><au>Nakatani, Chie</au><au>Cymbalyuk, Gennady</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A neural mass model of cross frequency coupling</atitle><jtitle>PloS one</jtitle><addtitle>PLoS One</addtitle><date>2017-04-05</date><risdate>2017</risdate><volume>12</volume><issue>4</issue><spage>e0173776</spage><epage>e0173776</epage><pages>e0173776-e0173776</pages><issn>1932-6203</issn><eissn>1932-6203</eissn><abstract>Electrophysiological signals of cortical activity show a range of possible frequency and amplitude modulations, both within and across regions, collectively known as cross-frequency coupling. To investigate whether these modulations could be considered as manifestations of the same underlying mechanism, we developed a neural mass model. The model provides five out of the theoretically proposed six different coupling types. Within model components, slow and fast activity engage in phase-frequency coupling in conditions of low ambient noise level and with high noise level engage in phase-amplitude coupling. Between model components, these couplings can be coordinated via slow activity, giving rise to more complex modulations. The model, thus, provides a coherent account of cross-frequency coupling, both within and between components, with which regional and cross-regional frequency and amplitude modulations could be addressed.</abstract><cop>United States</cop><pub>Public Library of Science</pub><pmid>28380064</pmid><doi>10.1371/journal.pone.0173776</doi><tpages>e0173776</tpages><oa>free_for_read</oa></addata></record> |
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| subjects | Assemblies Attention Bifurcations Biology and Life Sciences Brain Brain - physiology Brain research Chlorofluorocarbons Chokes (Electricity) Coding Cognition Cognition & reasoning Cognitive ability Computer simulation Control theory Cortex (auditory) Cortex (temporal) Coupling (molecular) Couplings Deep brain stimulation EEG Electroencephalography - methods Electrophysiology Engineering Epilepsy Event-related potentials Excitability Feedback Frequency dependence Hippocampus Humans Information processing Information transfer Interneurons Ketamine Luteinizing hormone Mathematical models Mechanical engineering Medicine and Health Sciences Methods Models, Biological Modulation Neural circuitry Neural networks Neuroimaging Neuromodulation Neurons Neurons - physiology Noise Noise levels Oscillations Phase shift Physical Sciences Population Populations Propagation Relay Research and Analysis Methods Rhythm Simulation Sleep Stimulation Temporal lobe Utilities Visual cortex Visual perception |
| title | A neural mass model of cross frequency coupling |
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