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Load-dependent relationships between frontal fNIRS activity and performance: A data-driven PLS approach.

Kimberly L Meidenbauer1, Kyoung Whan Choe2, Carlos Cardenas-Iniguez1

  • 1Environmental Neuroscience Lab, Department of Psychology, The University of Chicago, 5848 S University Avenue, Chicago, IL 60637, United States.

Neuroimage
|January 27, 2021
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Summary

Functional near-infrared spectroscopy (fNIRS) effectively tracks working memory load and brain activity. This study links fNIRS signals to N-back task performance, showing how cognitive load impacts brain activation and accuracy.

Keywords:
Cognitive loadN-back taskNeural efficiencyPartial least squaresWorking memoryfNIRS

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Area of Science:

  • Neuroscience
  • Cognitive Neuroscience
  • Biomedical Engineering

Background:

  • Neuroimaging studies often show load-dependent activation in prefrontal and parietal cortex during working memory tasks.
  • Functional near-infrared spectroscopy (fNIRS) offers a flexible, less invasive alternative to fMRI for measuring cortical hemodynamics.
  • Few fNIRS studies have explored the relationship between working memory load-dependent hemodynamic changes and behavioral performance.

Purpose of the Study:

  • To investigate the sensitivity of fNIRS to cognitive load variations in working memory.
  • To utilize advanced statistical methods to link fNIRS-measured brain activation with task performance.
  • To explore how the relationship between brain activity and accuracy changes across different working memory loads.

Main Methods:

  • Seventy participants performed an N-back task (1, 2, 3-back levels) while fNIRS data were collected from frontal and parietal regions.
  • Task-based fNIRS data were analyzed using a novel, robust statistical approach, including multivariate behavioral partial least squares (PLS).
  • The study examined the association between fNIRS signals (deoxyhemoglobin changes) and behavioral accuracy at each N-back level.

Main Results:

  • fNIRS detected significantly greater fronto-parietal activation for the 2-back compared to the 1-back task, indicating sensitivity to cognitive load.
  • Multivariate PLS analysis revealed distinct relationships between accuracy and mid-frontal fNIRS activation across N-back levels.
  • Increased mid-frontal activation (reduced deoxyhemoglobin) positively correlated with accuracy on the 3-back task, but negatively with the 1-back task, and showed no correlation with the 2-back task.

Conclusions:

  • fNIRS measurements are sensitive to working memory load, tracking hemodynamic changes associated with cognitive effort.
  • The relationship between neural activity (fNIRS signal) and task performance is modulated by cognitive load, suggesting adaptive metabolic demands.
  • This study highlights the utility of fNIRS and data-driven analyses for understanding brain-behavior relationships in cognitive tasks, paving the way for broader applications.