Addressing Confounds in Functional Connectivity Analyses of Calcium Imaging

Elucidating functional connectivity reveals interactions between brain regions based on their in vivo activity. However, a gap exists in current statistical methods’ ability to untangle direct interactions from confounding activity due to stimuli and physiological effects, leading to a bottleneck in understanding how the brain filters and decodes information. We propose methods to remove physiological and environmental effects from calcium imaging in the rodent olfactory bulb to better isolate connectivity-related activity correlations. Our approach deconvolves brain signals by learning smooth filters leveraging generalized ridge regularization, thus producing stronger isolation of such connectivity-related activity. Our method for removing specific external correlation-causing factors is applicable in a wide variety of settings including those with different external stimuli.