Correlated variability modifies working memory fidelity in primate prefrontal neuronal ensembles

Neurons in the primate lateral prefrontal cortex (LPFC) encode
working memory (WM) representations via sustained firing, a
phenomenon hypothesized to arise from recurrent dynamics within
ensembles of interconnected neurons. Here, we tested this hypothesis
by using microelectrode arrays to examine spike count correlations
(rsc) in LPFC neuronal ensembles during a spatial WM task.
We found a pattern of pairwise rsc during WM maintenance indicative
of stronger coupling between similarly tuned neurons and increased
inhibition between dissimilarly tuned neurons. We then
used a linear decoder to quantify the effects of the high-dimensional
rsc structure on information coding in the neuronal ensembles.
We found that the rsc structure could facilitate or impair
coding, depending on the size of the ensemble and tuning properties
of its constituent neurons. A simple optimization procedure
demonstrated that near-maximum decoding performance could be
achieved using a relatively small number of neurons. These WMoptimized
subensembles were more signal correlation (rsignal)-
diverse and anatomically dispersed than predicted by the statistics
of the full recorded population of neurons, and they often contained
neurons that were poorly WM-selective, yet enhanced coding
fidelity by shaping the ensemble’s rsc structure. We observed a
pattern of rsc between LPFC neurons indicative of recurrent dynamics
as a mechanism forWM-related activity and that the rsc structure
can increase the fidelity ofWMrepresentations. Thus,WMcoding in
LPFC neuronal ensembles arises from a complex synergy between
single neuron coding properties and multidimensional, ensemblelevel
phenomena.