Topic: higher visual areas

Predicting neural activity in higher visual areas (HVAs) in mice during spatial navigation is challenging due to the complex interaction between spatial and temporal processing. One recent two-stream hypothesis for rodents proposed by Saleem (2020) suggests that form-based goals and detailed landmark signals are processed by cortical areas biased towards the central visual field, while self-motion signals are processed in the periphery. Inspired by this, we developed a deep learning model that splits visual input into two streams: a convolutional neural network (CNN) processed the central visu

Our ability to see and interact with the world heavily relies on the efficient and precise processing of visual information, consisting of multiple features continuously in flux. Visual perception arises from signals propagating through parallel neuronal pathways wiring the retina to both cortical (primary visual cortex, V1; higher visual areas, HVAs) and subcortical structures (thalamus; superior colliculus, SC), each with distinct functional properties and cellular compositions. However, the precise distribution of behaviorally relevant visual signals across these pathways remains unclear, a

Our brains integrate sensory information with prior-knowledge to guide decisions. However, through which neural pathways experience can adapt behavioural responses is unclear. Predator-avoidance behaviors, particularly escape from visual-threats, represent behavioral manifestations of a decision-making process essential for survival, with the threat-value undergoing constant revision. Learning if a potentially threatening stimulus is dangerous, necessitates the integration of sensory evidence, experience and context. We speculated that visual cortex, in particular higher visual areas (HVAs), w