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Paper: PS-1B.65
Session: Poster Session 1B
Location: H Fl├Ąche 1.OG
Session Time: Saturday, September 14, 16:30 - 19:30
Presentation Time:Saturday, September 14, 16:30 - 19:30
Presentation: Poster
Publication: 2019 Conference on Cognitive Computational Neuroscience, 13-16 September 2019, Berlin, Germany
Paper Title: The cingulo-opercular network controls stimulus-response transformations with increasing efficiency over the course of learning
Manuscript:  Click here to view manuscript
License: Creative Commons License
This work is licensed under a Creative Commons Attribution 3.0 Unported License.
DOI: https://doi.org/10.32470/CCN.2019.1060-0
Authors: Janik Fechtelpeter, Hannes Ruge, Holger Mohr, Technische Universit├Ąt Dresden, Germany
Abstract: We all have experienced that the amount of effort required to perform a task can rapidly decrease over the course of practice. Previous studies have shown that short-term automatization of stimulus-response transformations is associated with a reorganization of functional coupling between different large-scale brain networks. However, it has remained an open question how changing connectivity patterns translate into more efficient stimulus-response processing over the course of learning. Here, we employed a control-theoretic approach to test the hypothesis that the amount of control energy required for stimulus-response processing decreases from early to late practice for networks involved in task control. Using fMRI data from a learning group, N = 70, and a control group, N = 67, stimulus-response transformations were modeled as trajectories of activity starting in the visual network and ending in the sensorimotor network. The stimulus-response trajectories were determined by the functional connectivity matrices derived from the fMRI data plus additional control activation exerted by task-related networks. Based on this analysis approach, we found that the cingulo-opercular network can control stimulus-response transformations with increasing efficiency over the course of learning, while no change in control energy was observed for the fronto-parietal network, highlighting the central role of the cingulo-opercular network for short-term task automatization.