Data from: Correlated variability in primate superior colliculus depends on functional class
Cite this dataset
Katz, Leor (2022). Data from: Correlated variability in primate superior colliculus depends on functional class [Dataset]. Dryad. https://doi.org/10.5061/dryad.12jm63z0r
Information read-out from populations of neurons depends strongly on the correlated variability within a population, termed rSC (spike count correlations). Traditionally, rSC is reported as a single value for a population of neurons comprising a brain area. However, single values, like summary statistics, can obscure underlying features of the constituent elements. We predict that in brain areas consisting of distinct subpopulations of neurons, different subpopulations will exhibit distinct levels of rSC not captured by the population rSC. We tested this idea by recording from neurons in macaque superior colliculus (SC), a structure that contains several subpopulations (or classes) of neurons based on function. We found that during guided saccade tasks, different classes of neurons exhibited differing degrees of rSC, which could not be attributed to variations in behavior. Neurons belonging to the “Delay” class displayed a particularly high rSC, especially during the delay epoch of tasks that relied on visual working memory. Our finding that rSC depends on functional class, as well as the type of task, demonstrate the importance of taking functional subpopulations into account when attempting to model or infer population coding principles in primate SC, or other areas of the brain that contain subpopulations supporting specific functions.
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