Overlapping attentional networks yield divergent behavioral predictions across tasks: Neuromarkers for diffuse and focused attention?
Esther X.W. Wu,
Gwenisha J. Liaw,
Rui Zhe Goh,
Tiffany T.Y. Chia,
Alisia M.J. Chee,
Monica D. Rosenberg,
B.T. Thomas Yeo,
Christopher L. Asplund
Posted 24 Jul 2019
bioRxiv DOI: 10.1101/713339 (published DOI: 10.1016/j.neuroimage.2020.116535)
Posted 24 Jul 2019
Attention is a critical cognitive function, allowing humans to select, enhance, and sustain focus on information of behavioral relevance. Attention contains dissociable neural and psychological components. Nevertheless, some brain networks support multiple attentional functions. Connectome-based Predictive Models (CPM), which associate individual differences in task performance with functional connectivity patterns, provide a compelling example. A sustained attention network model (saCPM) successfully predicted performance for selective attention, inhibitory control, and reading recall tasks. Here we constructed a visual attentional blink (VAB) model (vabCPM), comparing its performance predictions and network edges associated with successful and unsuccessful behavior to the saCPM's. In the VAB, attention devoted to a target often causes a subsequent item to be missed. Although frequently attributed to attentional limitations, VAB deficits may attenuate when participants are distracted or deploy attention diffusely. Participants (n=73; 24 males) underwent fMRI while performing the VAB task and while resting. Outside the scanner, they completed other cognitive tasks over several days. A vabCPM constructed from these data successfully predicted VAB performance. Strikingly, the network edges that predicted better VAB performance (positive edges) predicted worse selective and sustained attention performance, and vice versa. Predictions from the saCPM mirrored these results, with the network's negative edges predicting better VAB performance. Furthermore, the vabCPM's positive edges significantly overlapped with the saCPM's negative edges, and vice versa. We conclude that these partially overlapping networks each have general attentional functions. They may indicate an individual's propensity to diffusely deploy attention, predicting better performance for some tasks and worse for others.
- Downloaded 272 times
- Download rankings, all-time:
- Site-wide: 57,005 out of 88,857
- In neuroscience: 10,070 out of 15,814
- Year to date:
- Site-wide: 55,859 out of 88,857
- Since beginning of last month:
- Site-wide: 52,426 out of 88,857
Downloads over time
Distribution of downloads per paper, site-wide
- 18 Dec 2019: We're pleased to announce PanLingua, a new tool that enables you to search for machine-translated bioRxiv preprints using more than 100 different languages.
- 21 May 2019: PLOS Biology has published a community page about Rxivist.org and its design.
- 10 May 2019: The paper analyzing the Rxivist dataset has been published at eLife.
- 1 Mar 2019: We now have summary statistics about bioRxiv downloads and submissions.
- 8 Feb 2019: Data from Altmetric is now available on the Rxivist details page for every preprint. Look for the "donut" under the download metrics.
- 30 Jan 2019: preLights has featured the Rxivist preprint and written about our findings.
- 22 Jan 2019: Nature just published an article about Rxivist and our data.
- 13 Jan 2019: The Rxivist preprint is live!