Data from: Correlated variability in primate superior colliculus depends on functional class

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.