Attention Induced Gain Stabilization in Broad and Narrow-Spiking Cells in the Frontal Eye-Field of Macaque Monkeys.

UNLABELLED: Top-down attention increases coding abilities by altering firing rates and rate variability. In the frontal eye field (FEF), a key area enabling top-down attention, attention induced firing rate changes are profound, but its effect on different cell types is unknown. Moreover, FEF is the only cortical area investigated in which attention does not affect rate variability, as assessed by the Fano factor, suggesting that task engagement affects cortical state nonuniformly. We show that putative interneurons in FEF of Macaca mulatta show stronger attentional rate modulation than putative pyramidal cells. Partitioning rate variability reveals that both cell types reduce rate variability with attention, but more strongly so in narrow-spiking cells. The effects are captured by a model in which attention stabilizes neuronal excitability, thereby reducing the expansive nonlinearity that links firing rate and variance. These results show that the effect of attention on different cell classes and different coding properties are consistent across the cortical hierarchy, acting through increased and stabilized neuronal excitability. SIGNIFICANCE STATEMENT: Cortical processing is critically modulated by attention. A key feature of this influence is a modulation of "cortical state," resulting in increased neuronal excitability and resilience of the network against perturbations, lower rate variability, and an increased signal-to-noise ratio. In the frontal eye field (FEF), an area assumed to control spatial attention in human and nonhuman primates, firing rate changes with attention occur, but rate variability, quantified by the Fano factor, appears to be unaffected by attention. Using recently developed analysis tools and models to quantify attention effects on narrow- and broad-spiking cell activity, we show that attention alters cortical state strongly in the FEF, demonstrating that its effect on the neuronal network is consistent across the cortical hierarchy.