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Functional networks gating the flow of information in cued affective processing

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Zitation

Teckentrup, V., Van der Meer, J., Borchardt, V., Fan, Y., Neuser, M., Fensky, L., et al. (2018). Functional networks gating the flow of information in cued affective processing. Poster presented at 11th FENS Forum of Neuroscience, Berlin, Germany.


Zitierlink: https://hdl.handle.net/21.11116/0000-0001-95BE-1
Zusammenfassung
Expectancy shapes our perception of impending events. Although an aberrant interplay between cognitive and affective processes characterizes many mental disorders, it is not well understood how top-down expectancy signals modulate future affect. We therefore use cross-correlations to track the information flow in the brain during cognitive and affective processing segregated in time.
Participants in two independent fMRI studies (N1 = 37 & N2 = 84) were instructed to expect a positive, negative or neutral stimulus based on a cue, which was then followed by an emotional picture congruent with expectancy. Also, resting-state data was acquired from the participants to correct for intrinsic baseline level fluctuations of brain function.
First, using factorial modeling of delta cross-correlations (task-rest) within fMRI time-series of the first study, we found that the magnitude of expectancy signals modulated the BOLD response to emotional pictures in the anterior cingulate and dorsomedial prefrontal cortex in opposite directions. Second, using hierarchical linear modeling, we demonstrate that expectancy signals in the anterior insula foreshadow this opposing pattern in the prefrontal cortex. Third, the results were replicated in the second, independent dataset, showing that the cross-correlation approach reliably uncovers the dynamics of information flow across datasets.
We conclude that the anterior insula serves as a hub determining the recruitment of distinct prefrontal networks at the affective stage. Taken together, our proposed method provides new insights into neuronal pathways channeling cognition and affect within well-defined brain networks and could lead to new approaches to track aberrant information processing within mental disorders.