September 2024
Volume 24, Issue 10
Open Access
Vision Sciences Society Annual Meeting Abstract  |   September 2024
Support for and application of a measure of neural efficiency in visual processing
Author Affiliations & Notes
  • Michael Wenger
    The University of Oklahoma
  • James Townsend
    Indiana University
  • Sarah Newbolds
    The University of Oklahoma
  • Footnotes
    Acknowledgements  NIH 1 R21 ES027909; Vice President for Research and Partnerships
Journal of Vision September 2024, Vol.24, 617. doi:https://doi.org/10.1167/jov.24.10.617
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      Michael Wenger, James Townsend, Sarah Newbolds; Support for and application of a measure of neural efficiency in visual processing. Journal of Vision 2024;24(10):617. https://doi.org/10.1167/jov.24.10.617.

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Abstract

One theme in our work characterizing the real-time characteristics of perceptual processes is the measurement of capacity, or the effects of variations in workload on processing efficiency. A core component is the hazard function of the reaction time (RT) distribution along with its integral. The former can be interpreted as an instantaneous measure of work (known as the intensity function) and the latter can be interpreted as a cumulative measure of work. We have applied this approach to a range of visual tasks, from low-level perceptual learning to high-level face perception. Here we extend that work to combine electroencephalographic (EEG) measures of brain activity and RT to form a neural efficiency score: a ratio of the hazard function of the RT distribution and the instantaneous global field power (GFP) of the EEG. This ratio measures the relationship between work accomplished and brain energy expended to perform that work. We begin by showing that the GFP can be used as a proxy for energy expended by reanalyzing data from a visual Sternberg task performed while simultaneous EEG and metabolic data were recorded.The latter allowed us to quantify metabolic energy expended (in Mj/m), and we compared this against the GFP. We show that there is a strong linear relationship between these two measures, supporting the use of the GFP in quantifying neural efficiency. We then apply this measure to data from a visual contrast detection task performed by women who were either iron deficient and non-anemic or iron sufficien, and show that neural efficiency is related to contrast thresholds and systematically differs as a function of iron status. This suggests the potential for broad use of this measure for both basic and applied questions in vision.

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