Differential clustering of visual and choice- and saccade-related activity in macaque V3A and CIP

Abstract

Neurons in sensory and motor cortices tend to aggregate in clusters with similar functional properties. Within the primate dorsal ("where") pathway, an important interface between three-dimensional (3-D) visual processing and motor-related functions consists of two hierarchically organized areas: V3A and the caudal intraparietal (CIP) area. In these areas, 3-D visual information, choice-related activity, and saccade-related activity converge, often at the single-neuron level. Characterizing the clustering of functional properties in areas with mixed selectivity, such as these, may help reveal organizational principles that support sensorimotor transformations. Here we quantified the clustering of visual feature selectivity, choice-related activity, and saccade-related activity by performing correlational and parametric comparisons of the responses of well-isolated, simultaneously recorded neurons in macaque monkeys. Each functional domain showed statistically significant clustering in both areas. However, there were also domain-specific differences in the strength of clustering across the areas. Visual feature selectivity and saccade-related activity were more strongly clustered in V3A than in CIP. In contrast, choice-related activity was more strongly clustered in CIP than in V3A. These differences in clustering may reflect the areas' roles in sensorimotor processing. Stronger clustering of visual and saccade-related activity in V3A may reflect a greater role in within-domain processing, as opposed to cross-domain synthesis. In contrast, stronger clustering of choice-related activity in CIP may reflect a greater role in synthesizing information across functional domains to bridge perception and action.NEW & NOTEWORTHY The occipital and parietal cortices of macaque monkeys are bridged by hierarchically organized areas V3A and CIP. These areas support 3-D visual transformations, carry choice-related activity during 3-D perceptual tasks, and possess saccade-related activity. This study quantifies the functional clustering of neuronal response properties within V3A and CIP for each of these domains. The findings reveal domain-specific cross-area differences in clustering that may reflect the areas' roles in sensorimotor processing.

Keywords: choice signals; neuronal clustering; oculomotor; sensorimotor; vision.

Graphical abstract

Figure 1.

Visual stimuli and tilt discrimination task. A: slant-tilt coordinates for planar surface orientation. Tilt (T) specifies the direction that the plane is oriented in depth. Slant (S) specifies how much it is oriented in depth. Dots were rendered with perspective and stereoscopic cues (shown here as red-green anaglyphs). B: planes were presented at 4 distances with fixation at 57 cm. C: tilt discrimination task. A central target was fixated for 300 ms. A plane then appeared for 1,000 ms while fixation was maintained. The fixation target and plane then disappeared, and 8 choice targets appeared. A saccade was made to the target at the perceived nearest side of the plane.

Figure 2.

Clustering of 3-dimensional (3-D) pose tuning. A: example tuning curves of neuronal pairs from V3A [Pearson correlation (r_V) = 0.91 and absolute differences in tolerance of 3-D orientation tuning curve shape to distance (|ΔTolerance|) = 0.12, pose discrimination index (|ΔPDI|) = 0.02, orientation preference (|Δθ_V|) = 15°, tuning bandwidth (|Δλ₂|) = 1.21, tuning anisotropy (|Δλ₁|) = 3.20, axis of tuning anisotropy (|Δϕ|) = 30°, and distance preferences (|ΔD|) = 4 cm] and caudal intraparietal area (CIP) (r_V = 0.80, |ΔTolerance| = 0.03, |ΔPDI| = 0.05, |Δθ_V| = 17°, |Δλ₂| = 0.78, |Δλ₁| = 0.59, |Δϕ| = 18°, |ΔD| = 13 cm). Heat maps show 3-D orientation tuning at each distance, plotted in slant-tilt coordinates (Fig. 1A). B: r_V between tuning curves of neuronal pairs in V3A (top, orange) and CIP (bottom, blue). C: |ΔTolerance|. D: |ΔPDI|. In B–D, triangles mark median values. Dashed vertical lines mark median values obtained by chance.

Figure 3.

Clustering of 3-dimensional (3-D) orientation tuning. A: example tuning curve from V3A (top) with Bingham fit (r = 0.96; bottom). Inset, the Bingham parameter values. B: absolute differences in the orientation preferences of neuronal pairs (|Δθ_V|) in V3A (top, orange) and caudal intraparietal area (CIP) (bottom, blue), plotted over an equal area axis. C: absolute differences in tuning bandwidths (|Δλ₂|). D: absolute differences in tuning anisotropies (|Δλ₁|). E: absolute differences in the axes of tuning anisotropy (|Δϕ|). In B–E, triangles mark median values. Dashed vertical lines mark median values obtained by chance.

Figure 4.

Bingham parameters. To illustrate how orientation tuning depends on parameters λ₂ (tuning bandwidth), λ₁ (tuning anisotropy), and ϕ (axis of tuning anisotropy), tuning curves were modeled with a preferred tilt of 90° and slant of 30°. A: changing λ₂ with λ₁ = 0. B: changing λ₁ with λ₂ = 3 and ϕ = 90°. C: changing ϕ with λ₁ = −2.5 and λ₂ = 3.

Figure 5.

Clustering of preferred distance. Absolute differences in the distance preferences of neuronal pairs (|ΔD|) in V3A (left, orange) and caudal intraparietal area (CIP) (right, blue). Triangles mark median values. Dashed vertical lines mark median values obtained by chance.

Figure 6.

Clustering of choice-related activity. A: choice activity was measured during the presentation of frontoparallel planes, which were task ambiguous (cf. Fig. 1C). B: example tuning curves of neuronal pairs from V3A [left; Pearson correlation (r_C) = 0.91 and absolute differences in choice preference (|Δθ_C|) = 1°, half-width at half-height (|ΔHWHH_C|) = 6°, and choice discrimination index |ΔCDI| = 0.09] and caudal intraparietal area (CIP) (right; r_C = 0.97, |Δθ_C| = 10°, |ΔHWHH_C| = 11°, |ΔCDI| = 0.10). Colors correspond to different neurons. Data points are mean z-scored responses, and curves are von Mises fits. Insets, θ_C, HWHH_C, and CDI. C: r_C between tuning curves of neuronal pairs in V3A (top, orange) and CIP (bottom, blue). D: |Δθ_C|. E: |ΔHWHH_C|. F: |ΔCDI|. In C–F, triangles mark median values. Dashed vertical lines mark median values obtained by chance.

Figure 7.

Clustering of saccade-related activity. A: visually guided saccade task. A central target was fixated for 1,300 ms. The fixation target then disappeared, and a saccade target appeared at 1 of 8 locations. A saccade was then made to that target. B: example tuning curves of neuronal pairs from V3A [left; Pearson correlation (r_S) = 0.99 and absolute differences in saccade direction preferences (|Δθ_S|) = 5°, half-width at half-height (|ΔHWHH_S|) = 3°, and saccade discrimination index (|ΔSDI|) = 0.01] and caudal intraparietal area (CIP) (right; r_S = 0.97, |Δθ_S|= 1°, |ΔHWHH_S| = 5°, |ΔSDI| = 0.02). Colors correspond to different neurons. Data points are mean responses, and curves are von Mises fits. Insets, θ_S, HWHH_S, and SDI. C: r_S between tuning curves of neuronal pairs in V3A (top, orange) and CIP (bottom, blue). D: |Δθ_S|. E: |ΔHWHH_S|. F: |ΔSDI|. In C–F, triangles mark median values. Dashed vertical lines mark median values obtained by chance.