Paying attention to natural scenes in area V1.

Natural scene responses in the primary visual cortex are modulated simultaneously by attention and by contextual signals about scene statistics stored across the connectivity of the visual processing hierarchy. We hypothesized that attentional and contextual signals interact in V1 in a manner that primarily benefits the representation of natural stimuli, rich in high-order statistical structure. Recording from two macaques engaged in a spatial attention task, we found that attention enhanced the decodability of stimulus identity from population responses evoked by natural scenes, but not by synthetic stimuli lacking higher-order statistical regularities. Population analysis revealed that neuronal responses converged to a low-dimensional subspace only for natural stimuli. Critically, we determined that the attentional enhancement in stimulus decodability was captured by the natural-scene subspace, indicating an alignment between the attentional and natural stimulus variance. These results suggest that attentional and contextual signals interact in V1 in a manner optimized for natural vision.

Stimulus-specific plasticity of macaque V1 spike rates and gamma.

When a visual stimulus is repeated, average neuronal responses typically decrease, yet they might maintain or even increase their impact through increased synchronization. Previous work has found that many repetitions of a grating lead to increasing gamma-band synchronization. Here, we show in awake macaque area V1 that both repetition-related reductions in firing rate and increases in gamma are specific to the repeated stimulus. These effects show some persistence on the timescale of minutes. Gamma increases are specific to the presented stimulus location. Further, repetition effects on gamma and on firing rates generalize to images of natural objects. These findings support the notion that gamma-band synchronization subserves the adaptive processing of repeated stimulus encounters.

High-density electrophysiological recordings in macaque using a chronically implanted 128-channel passive silicon probe.

OBJECTIVE: The analysis of interactions among local populations of neurons in the cerebral cortex (e.g. within cortical microcolumns) requires high resolution and high channel count recordings from chronically implanted laminar microelectrode arrays. The request for high-density recordings of a large number of recording sites can presently only be accomplished by probes realized using complementary metal-oxide-semiconductor (CMOS) technology. In preparation for their use in non-human primates, we aimed for neural probe validation in a head-fixed approach analyzing the long-term recording capability. APPROACH: We examined chronically implanted silicon-based laminar probes, realized using a CMOS technology in combination with micromachining, to record from the primary visual cortex (V1) of a monkey. We used a passive CMOS probe that had 128 electrodes arranged at a pitch of 22.5 µm in four columns and 32 rows on a slender shank. In order to validate the performance of a dedicated microdrive, the overall dimensions of probe and interface boards were chosen to be compatible with the final active CMOS probe comprising integrated circuitry. MAIN RESULTS: Using the passive probe, we recorded simultaneously local field potentials (LFP) and spiking multiunit activity (MUA) in V1 of an awake behaving macaque monkey. We found that an insertion through the dura and subsequent readjustments of the chronically implanted neural probe was possible and allowed us to record stable LFPs for more than five months. The quality of MUA degraded within the first month but remained sufficiently high to permit mapping of receptive fields during the full recording period. SIGNIFICANCE: We conclude that the passive silicon probe enables semi-chronic recordings of high quality of LFP and MUA for a time span exceeding five months. The new microdrive compatible with a commercial recording chamber successfully demonstrated the readjustment of the probe position while the implemented plug structure effectively reduced brain tissue movement relative to the probe.

Stimulus complexity shapes response correlations in primary visual cortex.

Spike count correlations (SCCs) are ubiquitous in sensory cortices, are characterized by rich structure, and arise from structured internal dynamics. However, most theories of visual perception treat contributions of neurons to the representation of stimuli independently and focus on mean responses. Here, we argue that, in a functional model of visual perception, featuring probabilistic inference over a hierarchy of features, inferences about high-level features modulate inferences about low-level features ultimately introducing structured internal dynamics and patterns in SCCs. Specifically, high-level inferences for complex stimuli establish the local context in which neurons in the primary visual cortex (V1) interpret stimuli. Since the local context differentially affects multiple neurons, this conjecture predicts specific modulations in the fine structure of SCCs as stimulus identity and, more importantly, stimulus complexity varies. We designed experiments with natural and synthetic stimuli to measure the fine structure of SCCs in V1 of awake behaving macaques and assessed their dependence on stimulus identity and stimulus statistics. We show that the fine structure of SCCs is specific to the identity of natural stimuli and changes in SCCs are independent of changes in response mean. Critically, we demonstrate that stimulus specificity of SCCs in V1 can be directly manipulated by altering the amount of high-order structure in synthetic stimuli. Finally, we show that simple phenomenological models of V1 activity cannot account for the observed SCC patterns and conclude that the stimulus dependence of SCCs is a natural consequence of structured internal dynamics in a hierarchical probabilistic model of natural images.