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Numerous African American and Hispanic Students with disabilities are confronted with systemic and policy-based challenges preventing access to K-12 STEM-related and computer science education. In addition, the African American and Hispanic Students with Disabilities in the Computer Science Research Alliance conducted an NSF-funded study to understand teachers’ perceptions of district and school policies and practices that hinder the participation of African American and Hispanic students with disabilities in computer science education in Central Texas. The project’s research study fills a critical gap in the literature concerning the systemic barriers affecting African American and Hispanic students with disabilities in K12 computer science education. 

Abstract How is information distributed across large neuronal populations within a given brain area? Information may be distributed roughly evenly across neuronal populations, so that total information scales linearly with the number of recorded neurons. Alternatively, the neural code might be highly redundant, meaning that total information saturates. Here we investigate how sensory information about the direction of a moving visual stimulus is distributed across hundreds of simultaneously recorded neurons in mouse primary visual cortex. We show that information scales sublinearly due to correlated noise in these populations. We compartmentalized noise correlations into information-limiting and nonlimiting components, then extrapolate to predict how information grows with even larger neural populations. We predict that tens of thousands of neurons encode 95% of the information about visual stimulus direction, much less than the number of neurons in primary visual cortex. These findings suggest that the brain uses a widely distributed, but nonetheless redundant code that supports recovering most sensory information from smaller subpopulations.