Post‐task responses following working memory and movement are driven by transient spectral bursts with similar characteristics

Author:

Coleman Sebastian C.1ORCID,Seedat Zelekha A.12,Pakenham Daisie O.13,Quinn Andrew J.45,Brookes Matthew J.1,Woolrich Mark W.4,Mullinger Karen J.15

Affiliation:

1. Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy University of Nottingham Nottingham UK

2. Young Epilepsy Lingfield UK

3. Clinical Neurophysiology Queen's Medical Centre, Nottingham University Hospitals NHS Trust Nottingham UK

4. Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, Department of Psychiatry University of Oxford Oxford UK

5. Centre for Human Brain Health, School of Psychology University of Birmingham Birmingham UK

Abstract

AbstractThe post‐movement beta rebound has been studied extensively using magnetoencephalography (MEG) and is reliably modulated by various task parameters as well as illness. Our recent study showed that rebounds, which we generalise as “post‐task responses” (PTRs), are a ubiquitous phenomenon in the brain, occurring across the cortex in theta, alpha, and beta bands. Currently, it is unknown whether PTRs following working memory are driven by transient bursts, which are moments of short‐lived high amplitude activity, similar to those that drive the post‐movement beta rebound. Here, we use three‐state univariate hidden Markov models (HMMs), which can identify bursts without a priori knowledge of frequency content or response timings, to compare bursts that drive PTRs in working memory and visuomotor MEG datasets. Our results show that PTRs across working memory and visuomotor tasks are driven by pan‐spectral transient bursts. These bursts have very similar spectral content variation over the cortex, correlating strongly between the two tasks in the alpha (R2 = .89) and beta (R2 = .53) bands. Bursts also have similar variation in duration over the cortex (e.g., long duration bursts occur in the motor cortex for both tasks), strongly correlating over cortical regions between tasks (R2 = .56), with a mean over all regions of around 300 ms in both datasets. Finally, we demonstrate the ability of HMMs to isolate signals of interest in MEG data, such that the HMM probability timecourse correlates more strongly with reaction times than frequency filtered power envelopes from the same brain regions. Overall, we show that induced PTRs across different tasks are driven by bursts with similar characteristics, which can be identified using HMMs. Given the similarity between bursts across tasks, we suggest that PTRs across the cortex may be driven by a common underlying neural phenomenon.

Funder

University of Nottingham

Publisher

Wiley

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