The beta component of gamma-band auditory steady-state responses in patients with schizophrenia
| dc.contributor.author | Metzner, Christoph | |
| dc.contributor.author | Steuber, Volker | |
| dc.date.accessioned | 2021-12-08T17:11:22Z | |
| dc.date.available | 2021-12-08T17:11:22Z | |
| dc.date.issued | 2021-10-14 | |
| dc.description.abstract | The mechanisms underlying circuit dysfunctions in schizophrenia (SCZ) remain poorly understood. Auditory steady-state responses (ASSRs), especially in the gamma and beta band, have been suggested as a potential biomarker for SCZ. While the reduction of 40 Hz power for 40 Hz drive has been well established and replicated in SCZ patients, studies are inconclusive when it comes to an increase in 20 Hz power during 40 Hz drive. There might be several factors explaining the inconsistencies, including differences in the sensitivity of the recording modality (EEG vs MEG), differences in stimuli (click-trains vs amplitude-modulated tones) and large differences in the amplitude of the stimuli. Here, we used a computational model of ASSR deficits in SCZ and explored the effect of three SCZ-associated microcircuit alterations: reduced GABA activity, increased GABA decay times and NMDA receptor hypofunction. We investigated the effect of input strength on gamma (40 Hz) and beta (20 Hz) band power during gamma ASSR stimulation and saw that the pronounced increase in beta power during gamma stimulation seen experimentally could only be reproduced in the model when GABA decay times were increased and only for a specific range of input strengths. More specifically, when the input was in this specific range, the rhythmic drive at 40 Hz produced a strong 40 Hz rhythm in the control network; however, in the ‘SCZ-like’ network, the prolonged inhibition led to a so-called ‘beat-skipping’, where the network would only strongly respond to every other input. This mechanism was responsible for the emergence of the pronounced 20 Hz beta peak in the power spectrum. The other two microcircuit alterations were not able to produce a substantial 20 Hz component but they further narrowed the input strength range for which the network produced a beta component when combined with increased GABAergic decay times. Our finding that the beta component only existed for a specific range of input strengths might explain the seemingly inconsistent reporting in experimental studies and suggests that future ASSR studies should systematically explore different amplitudes of their stimuli. Furthermore, we provide a mechanistic link between a microcircuit alteration and an electrophysiological marker in schizophrenia and argue that more complex ASSR stimuli are needed to disentangle the nonlinear interactions of microcircuit alterations. The computational modelling approach put forward here is ideally suited to facilitate the development of such stimuli in a theory-based fashion. | en |
| dc.description.sponsorship | TU Berlin, Open-Access-Mittel – 2021 | en |
| dc.identifier.eissn | 2045-2322 | |
| dc.identifier.pmid | 34650135 | |
| dc.identifier.uri | https://depositonce.tu-berlin.de/handle/11303/14005 | |
| dc.identifier.uri | http://dx.doi.org/10.14279/depositonce-12778 | |
| dc.language.iso | en | en |
| dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | en |
| dc.subject.ddc | 150 Psychologie | de |
| dc.subject.other | cortex | en |
| dc.subject.other | network models | en |
| dc.subject.other | neural circuits | en |
| dc.title | The beta component of gamma-band auditory steady-state responses in patients with schizophrenia | en |
| dc.type | Article | en |
| dc.type.version | publishedVersion | en |
| dcterms.bibliographicCitation.articlenumber | 20387 | en |
| dcterms.bibliographicCitation.doi | 10.1038/s41598-021-99793-w | en |
| dcterms.bibliographicCitation.issue | 1 | en |
| dcterms.bibliographicCitation.journaltitle | Scientific Reports | en |
| dcterms.bibliographicCitation.originalpublishername | Springer Nature | en |
| dcterms.bibliographicCitation.originalpublisherplace | London | en |
| dcterms.bibliographicCitation.volume | 11 | en |
| tub.accessrights.dnb | free | en |
| tub.affiliation | Fak. 4 Elektrotechnik und Informatik::Inst. Softwaretechnik und Theoretische Informatik::FG Neuronale Informationsverarbeitung | de |
| tub.affiliation.faculty | Fak. 4 Elektrotechnik und Informatik | de |
| tub.affiliation.group | FG Neuronale Informationsverarbeitung | de |
| tub.affiliation.institute | Inst. Softwaretechnik und Theoretische Informatik | de |
| tub.publisher.universityorinstitution | Technische Universität Berlin | en |
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