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Research Article: New Research, Cognition and Behavior

Decoding Visual Spatial Attention Control

Sreenivasan Meyyappan, Abhijit Rajan, Qiang Yang, George R Mangun and Mingzhou Ding
eNeuro 13 February 2025, ENEURO.0512-24.2025; https://doi.org/10.1523/ENEURO.0512-24.2025
Sreenivasan Meyyappan
1Center for Mind and Brain, University of California, Davis, CA 95618, USA
2J. Crayton Pruitt Family Department of Biomedical Engineering, University of Florida, Gainesville, FL 32611, USA
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Abhijit Rajan
2J. Crayton Pruitt Family Department of Biomedical Engineering, University of Florida, Gainesville, FL 32611, USA
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Qiang Yang
2J. Crayton Pruitt Family Department of Biomedical Engineering, University of Florida, Gainesville, FL 32611, USA
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George R Mangun
1Center for Mind and Brain, University of California, Davis, CA 95618, USA
3Departments of Psychology and Neurology, University of California, Davis, CA 95616, USA
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Mingzhou Ding
2J. Crayton Pruitt Family Department of Biomedical Engineering, University of Florida, Gainesville, FL 32611, USA
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Abstract

In models of visual spatial attention control, it is commonly held that top-down control signals originate in the dorsal attention network, propagating to the visual cortex to modulate baseline neural activity and bias sensory processing. However, the precise distribution of these top-down influences across different levels of the visual hierarchy is debated. In addition, it is unclear whether these changes in baseline neural activity directly translate into improved performance. We analyzed attention-related baseline activity during the anticipatory period of a trial-by-trial voluntary spatial attention task, using two independent fMRI datasets, and two different analytic approaches. First, as in prior studies, univariate analysis showed that covert attention significantly enhanced baseline neural activity in higher-order visual areas contralateral to the attended visual hemifield, while effects in lower-order visual areas (e.g., V1) were weaker and more variable. Second, in contrast, multivariate pattern analysis (MVPA) revealed significant decoding of attention conditions across all visual cortical areas, with lower-order visual areas exhibiting higher decoding accuracies than higher-order areas. Third, decoding accuracy, rather than the magnitude of univariate activation, was a better predictor of a subject's stimulus discrimination performance. Finally, the MVPA results were replicated across two experimental conditions, where the direction of spatial attention was either externally instructed by a cue or based on the participants free choice decision about where to attend. Together, these findings offer new insights into the extent of attentional biases in the visual hierarchy under top-down control, and how these biases influence both sensory processing and behavioral performance.

Significance Statement Attention can be deployed in advance of stimulus processing. Understanding how top-down control of attention facilitates the processing of the attended stimuli and enhances task performance has remained a longstanding question in attention research. Here, applying multivariate pattern analysis (MVPA) to fMRI data, we showed that throughout the entire visual hierarchy including the primary visual cortex, there exist distinct neural representations for different attended information in anticipatory visual spatial attention, and the distinctiveness of these neural representations is positively associated with behavioral performance. Importantly, the MVPA findings were consistent across two experimental conditions where the direction of spatial attention was driven either by external instructions or from purely internal decisions.

Footnotes

  • This work was supported by National Institutes of Health grant MH117991 and National Science Foundation grant BCS-2318886 to G.R.M. and M.D. We thank E. Ferrer, Y. Liu, J. Bengson, T. Kelley, K. Bo, Z. Hu, and S. Kim for discussion and help with data collection and analysis.

  • Author Contribution: Sreenivasan Meyyappan: Conceptualization; formal analysis (lead); methodology (lead); writing – original draft (lead); writing – review and editing. Abhijit Rajan: Conceptualization; data curation; methodology; writing – original draft. Qiang Yang: data curation; formal analysis. George R Mangun: Conceptualization; funding acquisition; writing – review and editing. Mingzhou Ding: Conceptualization (lead); funding acquisition; writing – review and editing.

  • The authors declare no competing financial interests.

This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International license, which permits unrestricted use, distribution and reproduction in any medium provided that the original work is properly attributed.

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Decoding Visual Spatial Attention Control
Sreenivasan Meyyappan, Abhijit Rajan, Qiang Yang, George R Mangun, Mingzhou Ding
eNeuro 13 February 2025, ENEURO.0512-24.2025; DOI: 10.1523/ENEURO.0512-24.2025

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Decoding Visual Spatial Attention Control
Sreenivasan Meyyappan, Abhijit Rajan, Qiang Yang, George R Mangun, Mingzhou Ding
eNeuro 13 February 2025, ENEURO.0512-24.2025; DOI: 10.1523/ENEURO.0512-24.2025
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