A mean field model for movement induced changes in the beta rhythm
In electrophysiological recordings of the brain, the transition from high amplitude to low amplitude signals are most likely caused by a change in the synchrony of underlying neuronal population firing patterns. Classic examples of such modulations are the strong stimulus-related oscillatory phenom...
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| Format: | Article |
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Springer Verlag
2017
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| Online Access: | https://eprints.nottingham.ac.uk/43312/ |
| _version_ | 1848796660669349888 |
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| author | Byrne, Áine Brookes, Matthew J. Coombes, Stephen |
| author_facet | Byrne, Áine Brookes, Matthew J. Coombes, Stephen |
| author_sort | Byrne, Áine |
| building | Nottingham Research Data Repository |
| collection | Online Access |
| description | In electrophysiological recordings of the brain, the transition from high amplitude to low amplitude signals are most likely caused by a change in the synchrony of underlying neuronal population firing patterns. Classic examples of such modulations are the strong stimulus-related oscillatory phenomena known as the movement related beta decrease (MRBD) and post-movement beta rebound (PMBR). A sharp decrease in neural oscillatory power is observed during movement (MRBD) followed by an increase above baseline on movement cessation (PMBR). MRBD and PMBR represent important neuroscientific phenomena which have been shown to have clinical relevance. Here, we present a parsimonious model for the dynamics of synchrony within a synaptically coupled spiking network that is able to replicate a human MEG power spectrogram showing the evolution from MRBD to PMBR. Importantly, the high-dimensional spiking model has an exact mean field description in terms of four ordinary differential equations that allows considerable insight to be obtained into the cause of the experimentally observed time-lag from movement termination to the onset of PMBR (~ 0.5 s), as well as the subsequent long duration of PMBR (~ 1-10 s). Our model represents the first to predict these commonly observed and robust phenomena and represents a key step in their understanding, in health and disease. |
| first_indexed | 2025-11-14T19:51:31Z |
| format | Article |
| id | nottingham-43312 |
| institution | University of Nottingham Malaysia Campus |
| institution_category | Local University |
| last_indexed | 2025-11-14T19:51:31Z |
| publishDate | 2017 |
| publisher | Springer Verlag |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | nottingham-433122020-05-04T19:09:12Z https://eprints.nottingham.ac.uk/43312/ A mean field model for movement induced changes in the beta rhythm Byrne, Áine Brookes, Matthew J. Coombes, Stephen In electrophysiological recordings of the brain, the transition from high amplitude to low amplitude signals are most likely caused by a change in the synchrony of underlying neuronal population firing patterns. Classic examples of such modulations are the strong stimulus-related oscillatory phenomena known as the movement related beta decrease (MRBD) and post-movement beta rebound (PMBR). A sharp decrease in neural oscillatory power is observed during movement (MRBD) followed by an increase above baseline on movement cessation (PMBR). MRBD and PMBR represent important neuroscientific phenomena which have been shown to have clinical relevance. Here, we present a parsimonious model for the dynamics of synchrony within a synaptically coupled spiking network that is able to replicate a human MEG power spectrogram showing the evolution from MRBD to PMBR. Importantly, the high-dimensional spiking model has an exact mean field description in terms of four ordinary differential equations that allows considerable insight to be obtained into the cause of the experimentally observed time-lag from movement termination to the onset of PMBR (~ 0.5 s), as well as the subsequent long duration of PMBR (~ 1-10 s). Our model represents the first to predict these commonly observed and robust phenomena and represents a key step in their understanding, in health and disease. Springer Verlag 2017-10-01 Article PeerReviewed Byrne, Áine, Brookes, Matthew J. and Coombes, Stephen (2017) A mean field model for movement induced changes in the beta rhythm. Journal of Computational Neuroscience, 43 (2). pp. 143-158. ISSN 1573-6873 Post-movement beta rebound Movement related beta decrease Neural mass Synchrony power spectra Magnetoencephalography MEG Electroencephalography EEG Mean field https://link.springer.com/article/10.1007%2Fs10827-017-0655-7 doi:10.1007/s10827-017-0655-7 doi:10.1007/s10827-017-0655-7 |
| spellingShingle | Post-movement beta rebound Movement related beta decrease Neural mass Synchrony power spectra Magnetoencephalography MEG Electroencephalography EEG Mean field Byrne, Áine Brookes, Matthew J. Coombes, Stephen A mean field model for movement induced changes in the beta rhythm |
| title | A mean field model for movement induced changes in the beta rhythm |
| title_full | A mean field model for movement induced changes in the beta rhythm |
| title_fullStr | A mean field model for movement induced changes in the beta rhythm |
| title_full_unstemmed | A mean field model for movement induced changes in the beta rhythm |
| title_short | A mean field model for movement induced changes in the beta rhythm |
| title_sort | mean field model for movement induced changes in the beta rhythm |
| topic | Post-movement beta rebound Movement related beta decrease Neural mass Synchrony power spectra Magnetoencephalography MEG Electroencephalography EEG Mean field |
| url | https://eprints.nottingham.ac.uk/43312/ https://eprints.nottingham.ac.uk/43312/ https://eprints.nottingham.ac.uk/43312/ |