Dynamics of excitatory and inhibitory networks are differentially altered by selective attention

Abstract

Inhibition and excitation form two fundamental modes of neuronal interaction, yet we understand relatively little about their distinct roles in service of perceptual and cognitive processes. We developed a multidimensional waveform analysis to identify fast-spiking (putative inhibitory) and regular-spiking (putative excitatory) neurons in vivo and used this method to analyze how attention affects these two cell classes in visual area V4 of the extrastriate cortex of rhesus macaques. We found that putative inhibitory neurons had both greater increases in firing rate and decreases in correlated variability with attention compared with putative excitatory neurons. Moreover, the time course of attention effects for putative inhibitory neurons more closely tracked the temporal statistics of target probability in our task. Finally, the session-to-session variability in a behavioral measure of attention covaried with the magnitude of this effect. Together, these results suggest that selective targeting of inhibitory neurons and networks is a critical mechanism for attentional modulation.

Spatial attention enhances network, cellular and subthreshold responses in mouse visual cortex

“…5). This aspect of spatial contextual modulation in mouse V1 is broadly consistent with primate studies of selective visual attention 42,43 .…”

Cortical states control visual spatial perception

“…Second, pre-stimulus decorrelation-most prominent in FS neuronspreceded successful stimulus detection, as in primates (Cohen and Maunsell, 2009;Mitchell et al, 2009). However, decorrelation and FS neuron activity did not predict behavior better than RS firing rates, at odds with findings in primates (Mitchell et al, 2007;Snyder et al, 2016). This may be due to differences in RS and FS neuron identification in higher mammals (Constantinople et al, 2009;Soares et al, 2017;Vigneswaran et al, 2011).…”

Simultaneous multi-area recordings suggest that attention improves performance by reshaping stimulus representations

“…How could a reshaping of the representation of an attended stimulus be implemented? The 263 simplest mechanism would make use of the oft observed signatures of attention such as changes 264 in firing rate gain 2,3,23 or pairwise noise correlations [5][6][7]9,[20][21][22][31][32][33][34][35][36][37] . We investigated the possibility 265 that these simple response changes can account for the attention-related improvement in the 266 stimulus information decoded using both the Choice and SC decoders in two stages.…”