How cognitive control modulates intrinsic connectivity: A dynamic causal modeling study for cross-spectral density using Bayesian belief updating

Abstract

Event Abstract Back to Event How cognitive control modulates intrinsic connectivity: A dynamic causal modeling study for cross-spectral density using Bayesian belief updating Katharina Wegner1* 1 Ghent University, Data Analysis, Belgium How cognitive control modulates intrinsic connectivity: A dynamic causal modeling study for cross-spectral density using Bayesian belief updating Katharina Wegner1, Charles R.E. Wilson2,3, Emmanuel Procyk2,3, Daniele Marinazzo1 1 Department of Data Analysis, Ghent University, Ghent, 9000 Belgium 2 INSERM U846, Stem Cell and Brain Research Institute, Bron 69500, France 3 Université de Lyon, Lyon 1, UMR S-846, Lyon 69003, France E-Mail: katharina.wegner@ugent.be The engagement in a monotonous and tedious cognitive task over a long time span is associated with a vigilance decrement over time (time-on-task effect). In presence of such emerging mental fatigue, cognitive control (i.e. the active maintenance and flexible updating of task-relevant information) can be thought to be a requirement to maintain the current performance level and may hence increase as a task progresses. Recent work has found that neural activity in the beta band changes as a function of cognitive control (Stoll et al., 2016): Using electrocorticography (EcoG) on two macaque monkeys, it was observed that frontal beta power increased when task demands were elevated, and as the task progressed. Here, we further investigate the time-sensitive change in spectral activity on a trial-to-trial basis. To this end, we use dynamic causal modeling (DCM) of frontal and premotor spectral activity to identify how intrinsic connectivity parameters are modulated by cognitive control. By means of the separate inversion of the pre-stimulus segment of each trial we obtained ten parameters describing the intrinsic connections between four distinct neural subpopulations comprising the neural mass models that we used to fit the activity of both regions of interest, as well as the four respective synaptic constants (cf. Figure 1). For the inversion, we used a Bayesian updating scheme: The posterior parameter estimate of the current trial became the prior of the consecutive trial. This approach has been shown to be more efficient compared to the inversion of the entire time series, while yielding the same results (Cooray et al., 2016). The quantification of the between-trial changes of the synaptic and connectivity parameters can shed light on the mechanisms of actions of cognitive control in this context. Preliminary results for one monkey and each electrode are shown in Figure 2. Figure 1 Figure 2 References Cooray, G. K., Sengupta, B., Douglas, P. K., & Friston, K. (2016). Dynamic causal modelling of electrographic seizure activity using Bayesian belief updating. NeuroImage, 125, 1142-1154. Stoll, F. M., Wilson, C. R., Faraut, M. C., Vezoli, J., Knoblauch, K., & Procyk, E. (2016). The effects of cognitive control and time on frontal beta oscillations. Cerebral Cortex, 26(4), 1715-1732. Keywords: dynamic causal modeling, effective connectivity (EC), cognitive control, Time-on-task, Mental Fatigue Conference: 12th National Congress of the Belgian Society for Neuroscience, Gent, Belgium, 22 May - 22 May, 2017. Presentation Type: Poster Presentation Topic: Cognition and Behavior Citation: Wegner K (2019). How cognitive control modulates intrinsic connectivity: A dynamic causal modeling study for cross-spectral density using Bayesian belief updating. Front. Neurosci. Conference Abstract: 12th National Congress of the Belgian Society for Neuroscience. doi: 10.3389/conf.fnins.2017.94.00004 Copyright: The abstracts in this collection have not been subject to any Frontiers peer review or checks, and are not endorsed by Frontiers. They are made available through the Frontiers publishing platform as a service to conference organizers and presenters. The copyright in the individual abstracts is owned by the author of each abstract or his/her employer unless otherwise stated. Each abstract, as well as the collection of abstracts, are published under a Creative Commons CC-BY 4.0 (attribution) licence (https://creativecommons.org/licenses/by/4.0/) and may thus be reproduced, translated, adapted and be the subject of derivative works provided the authors and Frontiers are attributed. For Frontiers’ terms and conditions please see https://www.frontiersin.org/legal/terms-and-conditions. Received: 02 May 2017; Published Online: 25 Jan 2019. * Correspondence: Miss. Katharina Wegner, Ghent University, Data Analysis, Ghent, 9000, Belgium, katharina.wegner@ugent.be Login Required This action requires you to be registered with Frontiers and logged in. To register or login click here. Abstract Info Abstract The Authors in Frontiers Katharina Wegner Google Katharina Wegner Google Scholar Katharina Wegner PubMed Katharina Wegner Related Article in Frontiers Google Scholar PubMed Abstract Close Back to top Javascript is disabled. Please enable Javascript in your browser settings in order to see all the content on this page.