A cortical network related to cognitive control revealed by theta oscillations: a MEG study.
Recent theories of cognitive control put large emphasis on theta oscillations in relation to action monitoring. Multiple EEG studies of cognitive control revealed increased power of theta oscillations restricted to midfrontal areas, while there is a substantial body of functional connectivity data demonstrating that theta oscillations may be a carrier of informational exchange over multiple cortical regions. fMRI studies revealed immense distributed networks involved in cognitive control. Paradoxically, MEG has been considered almost insensitive to theta oscillations in such an experimental context. It also remains debatable what is the functional role of such theta oscillations. An influential line of evidence links feedback-related theta oscillations to two types of prediction errors (unsigned and signed), but this distinction has not been tested during trial-end-error learning with theta activity measured beyond the midfrontal cortex.
We recorded MEG while participants were involved in trial-and-error learning within a novel multiple-choice behavioral task with complex stimulus-to-response mapping. Three conditions were analyzed: correct and erroneous trials during the initial stage of learning acquisition, as well as correct trials during stable performance. Sources of MEG activity were analyzed using minimum-norm estimation method within 4-6 Hz frequency range.
We revealed a number of bilateral cortical areas that displayed theta oscillations to the feedback signal: in addition to the "classical" medial frontal areas (the anterior part of the medial cingulate cortex and the pre-supplementary motor area), this network included the insula and the auditory cortex, the frontal operculum and posterior inferior frontal gyrus, the premotor cortex, the paracentral lobule, and the posterior part of the medial cingulate cortex. Granger causality analysis revealed overall communication directed from lateral to medial sites. During the initial stage of trial-and-error learning, we observed a strong non-differential response to feedback signal that reflected an unsigned component of the prediction error. The signed component of the prediction error was observed later – with greater theta activations after errors compared with correct responses.
Thus, using MEG, we were able to reveal a distributed network of brain areas in relation to feedback-related processing that included not only medial frontal, but also auditory areas, insula, lateral frontal, and medial parietal areas. The data obtained confirm the existence of two components of the prediction error, and this distinction was evident all over the network revealed.
The study was implemented in the framework of the Basic Research Program at the National Research University Higher School of Economics (HSE) in 2018.