Circuit-motivated generalized affine models characterize stimulus-dependent visual cortical shared variability

• Published in: iScience Vol. 27; no. 8; p. 110512
• Main Authors: Xia, Ji, Jasper, Anna, Kohn, Adam, Miller, Kenneth D.
• Format: Journal Article
• Language: English
• Published: United States Elsevier Inc 16.08.2024; Elsevier
• Subjects: Biological sciences; Cognitive neuroscience; Neuroscience; Sensory neuroscience; Neuroscience; Sensory neuroscience; Biological sciences; Cognitive neuroscience
• ISSN: 2589-0042; 2589-0042
• DOI: 10.1016/j.isci.2024.110512

Correlated variability in the visual cortex is modulated by stimulus properties. The stimulus dependence of correlated variability impacts stimulus coding and is indicative of circuit structure. An affine model combining a multiplicative factor and an additive offset has been proposed to explain how correlated variability in primary visual cortex (V1) depends on stimulus orientations. However, whether the affine model could be extended to explain modulations by other stimulus variables or variability shared between two brain areas is unknown. Motivated by a simple neural circuit mechanism, we modified the affine model to better explain the contrast dependence of neural variability shared within either primary or secondary visual cortex (V1 or V2) as well as the orientation dependence of neural variability shared between V1 and V2. Our results bridge neural circuit mechanisms and statistical models and provide a parsimonious explanation for the stimulus dependence of correlated variability within and between visual areas. [Display omitted] •Compare statistical models of stimulus-dependent correlated variability in V1, V2•Recurrent neural circuit mechanism informs statistical model designs•Orientation-dependent shared variability between and within V1 and V2 is affine•A modified affine model explains contrast-dependent shared variability in V2 Biological sciences; Neuroscience; Sensory neuroscience; Cognitive neuroscience