State-Aware Detection. Establishing the link between neural activity and behavior is a central goal of neuroscience. One context in which to examine this link is in a sensory detection task, in which an animal is trained to report the presence of a barely perceptible sensory stimulus. In such tasks, both sensory responses in the brain and behavioral responses are highly variable. A simple hypothesis, originating in signal detection theory, is that perceived inputs generate neural activity that cross some threshold for detection. According to this hypothesis, sensory response variability would predict behavioral variability, but previous studies have not born out this prediction. Further complicating the picture, sensory response variability is partially dependent on the ongoing state of cortical activity, and in a recent study, we wondered whether this could resolve the mismatch between response variability and behavioral variability. We used a computational approach to study an adaptive observer that utilizes an ongoing prediction of sensory responsiveness to detect sensory inputs based on based on features of the spontaneous, ongoing local field potential. This observer has higher overall accuracy than the standard ideal observer. Moreover, because of the adaptation, the observer breaks the direct link between neural and behavioral variability, which could resolve discrepancies arising in past studies. We suggest new experiments to test our theory.

A. Sederberg, A. Pala, H. Zheng, B. J. He, and G. B. Stanley.  State-aware detection of sensory stimuli in the cortex of the awake mouse, PLoS Comput Biol., 15(5):e10067162019, 2019. PDF