Abstract #5370

Physiological noise correction improves sensitivity, specificity, and reproducibility of resting-state functional connectivity in a reading model

Venkatagiri Krishnamurthy^1,2,3, Lisa C. Krishnamurthy^2,3,4, Dina M. Schwam⁵, Daphne Greenberg⁵, and Robin D. Morris^3,6

¹Dept. of Neurology, Emory University, Atlanta, GA, United States, ²Center for Visual and Neurocognitive Rehabilitation, Atlanta VAMC, Decatur, GA, United States, ³Center for Advanced Brain Imaging, GSU/GT, Atlanta, GA, United States, ⁴Dept. of Physics & Astronomy, Georgia State University, Atlanta, GA, United States, ⁵Dept. of Educational Psychology, Special Education, and Communication Disorders, Georgia State University, Atlanta, GA, United States, ⁶Dept. of Psychology, Georgia State University, Atlanta, GA, United States

Amongst several sources of noise, physiological noise (PN) from cardiac and respiratory cycles affects reliable quantification of rsFC measures such as correlation coefficient (CC). The purpose of this study is to determine the effects of PN on specificity, sensitivity and reproducibility of rsFC maps in a ‘reading’ model. We show that a combination of multiple methodologies to correct for such noise leads to improved signal fluctuations (tSNR) that culminates in higher specificity and sensitivity to neuronal fluctuations that are closer to actual ground truth. Applying our methodologies to a ‘reading’ model, we show that, irrespective of session, correction for PN results in meaningful discrimination of reading networks between typical and struggling readers.

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