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. 2021 May;53(10):3362-3377.
doi: 10.1111/ejn.15206. Epub 2021 May 3.

Visual processing speed is linked to functional connectivity between right frontoparietal and visual networks

Svenja Küchenhoff  1 , Christian Sorg  2   3 , Sebastian C Schneider  1   2   3 , Oliver Kohl  1 , Hermann J Müller  1 , Natan Napiórkowski  1   4 , Aurore Menegaux  1   2   3 , Kathrin Finke  1   4 , Adriana L Ruiz-Rizzo  1
Affiliations

Visual processing speed is linked to functional connectivity between right frontoparietal and visual networks

Svenja Küchenhoff et al. Eur J Neurosci. 2021 May.

Abstract

Visual information processing requires an efficient visual attention system. The neural theory of visual attention (TVA) proposes that visual processing speed depends on the coordinated activity between frontoparietal and occipital brain areas. Previous research has shown that the coordinated activity between (i.e., functional connectivity and "inter-FC") cingulo-opercular (COn) and right-frontoparietal (RFPn) networks is linked to visual processing speed. However, how inter-FC of COn and RFPn with visual networks links to visual processing speed has not been directly addressed yet. Forty-eight healthy adult participants (27 females) underwent resting-state (rs-)fMRI and performed a whole-report psychophysical task. To obtain inter-FC, we analyzed the entire frequency range available in our rs-fMRI data (i.e., 0.01-0.4 Hz) to avoid discarding neural information. Following previous approaches, we analyzed the data across frequency bins (Hz): Slow-5 (0.01-0.027), Slow-4 (0.027-0.073), Slow-3 (0.073-0.198), and Slow-2 (0.198-0.4). We used the mathematical TVA framework to estimate an individual, latent-level visual processing speed parameter. We found that visual processing speed was negatively associated with inter-FC between RFPn and visual networks in Slow-5 and Slow-2, with no corresponding significant association for inter-FC between COn and visual networks. These results provide the first empirical evidence that links inter-FC between RFPn and visual networks with the visual processing speed parameter. These findings suggest that direct connectivity between occipital and right frontoparietal, but not frontoinsular, regions support visual processing speed.

Keywords: between-network connectivity; cingulo-opercular network; resting-state fMRI; theory of visual attention; visual attention.

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References

REFERENCES

    1. Allen, E. A., Erhardt, E. B., Damaraju, E., Gruner, W., Segall, J. M., Silva, R. F., Havlicek, M., Rachakonda, S., Fries, J., Kalyanam, R., Michael, A. M., Caprihan, A., Turner, J. A., Eichele, T., Adelsheim, S., Bryan, A. D., Bustillo, J., Clark, V. P., Feldstein Ewing, S. W., … Calhoun, V. D. (2011). A baseline for the multivariate comparison of resting-state networks. Frontiers in Systems Neuroscience, 5, https://doi.org/10.3389/fnsys.2011.00002
    1. Ashburner, J. (2007). A fast diffeomorphic image registration algorithm. NeuroImage, 38(1), 95-113. https://doi.org/10.1016/j.neuroimage.2007.07.007
    1. Baria, A. T., Baliki, M. N., Parrish, T., & Apkarian, A. V. (2011). Anatomical and functional assemblies of brain BOLD oscillations. Journal of Neuroscience, 31(21), 7910-7919. https://doi.org/10.1523/JNEUROSCI.1296-11.2011
    1. Beall, E. B., & Lowe, M. J. (2007). Isolating physiologic noise sources with independently determined spatial measures. NeuroImage, 37(4), 1286-1300. https://doi.org/10.1016/j.neuroimage.2007.07.004
    1. Beckmann, C. F., Mackay, C. E., Filippini, N., & Smith, S. M. (2009). Group comparison of resting-state FMRI data using multi-subject ICA and dual regression. NeuroImage, 47(Suppl 1), S148. https://doi.org/10.1016/S1053-8119(09)71511-3

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