Attention exerts a powerful influence on visual perception. The impact of attention on neuronal activity manifests at early visual information processing stages and progressively increases throughout the visual cortical hierarchy. However, the neuronal mechanisms of attention are unresolved. In particular, the rules governing attentional modulation of individual neurons, whether they are facilitated or suppressed by attention, are not known. To obtain a more granular or neuron- and circuit-level understanding of the mechanisms of attention, and to directly test the feature similarity gain model in V1, we compared attentional modulation with neuronal feature selectivity across a large population of V1 neurons in alert and behaving macaque monkeys trained on an attention-demanding contrast-change detection task. We utilized emerging multi-electrode array technology to record simultaneously from V1 neurons spanning all 6 cortical layers so that we could characterize the laminar position and physiological response properties of diverse V1 neuronal populations. We found significant relationships between attentional modulation and neuronal position within the cortical hierarchy, neuronal physiology, and neuronal feature selectivity. Our results support the feature similarity gain model and further suggest that attentional modulation depends critically upon the match between neuronal feature selectivity and the features required for the task.

Attention is a critical component of visual perception; however, the mechanisms of attention at the granular level are poorly understood. One possible mechanism by which attention modulates neuronal activity is to control the efficacy of communication between connected neurons; however, it is unclear whether attention alters communication efficacy across a variety of neuronal circuits. In parallel, attentional modulation of neuronal firing rate is not uniform but depends upon the match between neuronal feature selectivity and the feature required for successful task completion. Here we tested whether modulation of communication efficacy is a viable mechanism of attention by assessing whether it is consistent across a variety of neuronal circuits and dependent upon the type of information conveyed in each circuit. We identified monosynaptically connected pairs of V1 neurons through cross-correlation of neuronal spike trains recorded in adult female macaque monkeys performing attention-demanding contrast-change detection tasks. Attention toward the stimulus in the receptive field of recorded neurons significantly facilitated the efficacy of communication among connected pairs of V1 neurons. The amount of attentional enhancement depended upon neuronal physiology, with larger facilitation for circuits conveying information about task-relevant features. Furthermore, presynaptic activity was more determinant of attentional enhancement of communication efficacy than postsynaptic activity, and feedforward local circuits often displayed the largest facilitation with attention. Together, these findings highlight attentional modulation of communication efficacy as a generalized mechanism of attention and demonstrate that attentional modulation at the granular level depends on the relevance of feature-specific information conveyed by neuronal circuits.

Correlations and inferred causal interactions among local field potentials (LFPs) simultaneously recorded in distinct visual brain areas can provide insight into how visual and cognitive signals are communicated between neuronal populations. Based on the known anatomical connectivity of hierarchically organized visual cortical areas and electrophysiological measurements of LFP interactions, a framework for interareal frequency-specific communication has emerged. Our goals were to test the predictions of this framework in the context of the early visual pathways and to understand how attention modulates communication between the visual thalamus and primary visual cortex. We recorded LFPs simultaneously in retinotopically aligned regions of the visual thalamus and primary visual cortex in alert and behaving macaque monkeys trained on a contrast-change detection task requiring covert shifts in visual spatial attention. Coherence and Granger-causal interactions among early visual circuits varied dynamically over different trial periods. Attention significantly enhanced alpha-, beta-, and gamma-frequency interactions, often in a manner consistent with the known anatomy of early visual circuits. However, attentional modulation of communication among early visual circuits was not consistent with a simple static framework in which distinct frequency bands convey directed inputs. Instead, neuronal network interactions in early visual circuits were flexible and dynamic, perhaps reflecting task-related shifts in attention. NEW & NOTEWORTHY Attention alters the way we perceive the visual world. For example, attention can modulate how visual information is communicated between the thalamus and cortex. We recorded local field potentials simultaneously in the visual thalamus and cortex to quantify the impact of attention on visual information communication. We found that attentional modulation of visual information communication was not static, but dynamic over the time course of trials.

The local field potential (LFP) contains rich information about activity in local neuronal populations. However, it has been challenging to establish direct links between LFP modulations and task-relevant behavior or cognitive processes, such as attention. We sought to determine whether LFP amplitude or phase modulations are predictive of the allocation of visual spatial attention. LFPs were recorded simultaneously in multiple early visual brain structures of alert macaque monkeys performing attention-demanding detection and discrimination tasks. Attention directed toward the receptive field of recorded neurons generated systematically larger phase shifts in high-beta- and low-gamma-frequency LFPs compared with LFP phase shifts on trials in which attention was directed away from the receptive field. This attention-mediated temporal advance corresponded to ~10 ms. LFP phase shifts also correlated with reaction times when monkeys were engaged in the tasks. Importantly, attentional modulation of LFP phase was consistent across monkeys, tasks, visual brain structures, and cortical layers. In contrast, attentional modulation of LFP amplitude varied across frequency bands, visual structures/layers, and tasks. Because LFP phase shifts were robust, consistent, and predictive of spatial attention, they could serve as a reliable marker for attention signals in the brain. NEW & NOTEWORTHY Local field potentials (LFPs) reflect the activity of spatially localized populations of neurons. Whether alterations in LFP activity are indicative of cognitive processes, such as attention, is unclear. We found that shifts in the phase of LFPs measured in multiple visual brain areas reliably predicted the focus of spatial attention. LFP phase shifts could therefore serve as a marker for behaviorally relevant attention signals in the brain.

The effects of visual spatial attention on neuronal firing rates have been well characterized for neurons throughout the visual processing hierarchy. Interestingly, the mechanisms by which attention generates more or fewer spikes in response to a visual stimulus remain unknown. One possibility is that attention boosts the likelihood that synaptic inputs to a neuron result in spikes. We performed a novel analysis to measure local field potentials (LFPs) just prior to spikes, or reverse spike-triggered LFP “wavelets”, for neurons recorded in primary visual cortex (V1) of monkeys performing a contrast change detection task requiring covert shifts in visual spatial attention. We used dimensionality reduction to define LFP wavelet shapes with single numerical values and we found that LFP wavelet shape changes correlated with changes in neuronal firing rate. We then tested whether a simple classifier could predict monkeys’ focus of attention from LFP wavelet shape. LFP wavelet shapes sampled in discrete windows were predictive of the locus of attention for some neuronal types. These findings suggest that LFP wavelets are a useful proxy for local network activity influencing spike generation and changes in LFP wavelet shape are predictive of the focus of attention.