Spatiotemporal properties of optic flow and vestibular tuning in the cerebellar nodulus and uvula

Abstract

Convergence of visual motion and vestibular information is essential for accurate spatial navigation. Such multisensory integration has been shown in cortex, e.g., the dorsal medial superior temporal (MSTd) and ventral intraparietal (VIP) areas, but not in the parieto-insular vestibular cortex (PIVC). Whether similar convergence occurs subcortically remains unknown. Many Purkinje cells in vermal lobules 10 (nodulus) and 9 (uvula) of the macaque cerebellum are tuned to vestibular translation stimuli, yet little is known about their visual motion responsiveness. Here we show the existence of translational optic flow-tuned Purkinje cells, found exclusively in the anterior part of the nodulus and ventral uvula, near the midline. Vestibular responses of Purkinje cells showed a remarkable similarity to those in MSTd (but not PIVC or VIP) neurons, in terms of both response latency and relative contributions of velocity, acceleration, and position components. In contrast, the spatiotemporal properties of optic flow responses differed from those in MSTd, and matched the vestibular properties of these neurons. Compared with MSTd, optic flow responses of Purkinje cells showed smaller velocity contributions and larger visual motion acceleration responses. The remarkable similarity between the nodulus/uvula and MSTd vestibular translation responsiveness suggests a functional coupling between the two areas for vestibular processing of self-motion information.

Figure 1.

Two single-peaked examples of NU Purkinje cell responses during 3D vestibular and visual (optic flow) translation. A, Top, Congruent example cell. Color-contour maps, showing 3D direction tuning profiles (Lambert cylindrical projection) at peak time for vestibular (1.12 s) and visual (0.9 s) responses with preferred directions: [azimuth, elevation] = [−86°, −18°] and [−94°, −12°], respectively. Tuning curves along the margins illustrate mean firing rates plotted versus elevation or azimuth (averaged across azimuth or elevation, respectively). Bottom, Response PSTHs. Red stars indicate significant responses. B, Opposite example cell. Vestibular: [azimuth, elevation] = [131°, 22°] and peak time, 1.18 s; Visual: [azimuth, elevation] = [−48°, 25°] and peak time, 0.98 s.

Figure 2.

Double-peaked example of NU Purkinje cell responses during 3D vestibular translation. A, Response PSTHs. Red (t = 0.9 s) and blue (t = 1.42 s) stars indicate significant responses at the two peak times. B, Color-contour maps, showing 3D direction tuning profiles (Lambert cylindrical projection) at the two peak times: first peak [azimuth = 130°, elevation = 15°], second peak [azimuth = −55°, elevation = −10°].

Figure 3.

Summary of vestibular and visual response types and location along anterior–posterior and mediolateral coordinates. A, B, Percentage of different categories of neurons in response to vestibular (A) and visual (B) translation. C–F, Reconstructed locations of Purkinje cells recorded during vestibular (n = 56, blue) and visual (n = 56, orange) stimulation. DDI plotted as a function of anterior–posterior (C and D; 0 corresponds to the location of the abducens nuclei) and mediolateral (E and F; 0 corresponds to the midline) coordinates. Data are shown separately for each animal and each symbol corresponds to a single neuron: squares (animal V: vestibular, n = 31; visual, n = 30); circles (animal P: vestibular, n = 14; visual, n = 10); and triangles (animal F: vestibular, n = 11; visual, n = 16). Filled and open symbols represent cells with significant and not significant modulation, respectively.

Figure 4.

Comparison between vestibular and visual responses. A, Distribution of preferred directions in 3D. Each data point represents a preferred azimuth and elevation of a single cell for vestibular (blue symbols, n = 50) and visual (orange symbols, n = 15) conditions (only significantly tuned cells are included): squares (animal V: vestibular, n = 28; visual, n = 9); circles (animal P: vestibular, n = 12; visual, n = 1); and triangles (animal F: vestibular, n = 10; visual, n = 5). Data are plotted on Cartesian axes that represent the Lambert cylindrical equal-area projections of the spherical stimulus space. Histograms along the top and right sides show the corresponding marginal distributions (blue filled bars for vestibular and orange bars for visual). B, Distribution of the absolute difference between vestibular and visual preferred directions (|Δ preferred direction|) (n = 11). C, D, Scatter plots of the maximum response amplitude and DDI for Purkinje cells tested with both vestibular and visual stimuli (n = 42). Purple symbols indicate cells with significant tuning to both visual and vestibular stimuli (n = 11, ANOVA, p < 0.01). Black symbols show cells that were spatially and temporally tuned during only vestibular, but not during visual stimuli (n = 25). Open symbols correspond to cells with no significant tuning for both vestibular and visual stimuli (n = 6).

Figure 5.

Comparison of responses of cerebellar NU and cortical areas (PIVC, VIP, and MSTd). Cumulative distributions were plotted for vestibular (left) and visual (right) responses. A, B, DDIs. C, D, Peak-to-trough response amplitude (R_max-R_min). E, F, Neural response variance, computed as the SSE around the mean response. Data for cortical areas have been replotted from Chen et al. (2011a,b).

Figure 6.

Distribution of peak times. A, The 2 s motion stimuli: stimulus velocity (red curve), acceleration (green curve), and position (blue curve). B, Distributions of peak times for single-peaked Purkinje cells during vestibular (dark bars, n = 32) and visual (light gray bars, n = 10) stimulation. Stimulus velocity (red curve), acceleration (green curve), and position (blue curve) are superimposed. C, Distributions of peak times for double-peaked Purkinje cells during vestibular motion only (n = 15). Dark gray bars: early peak times; white dashed bars: late peak times. D, Comparison of peak times for single-peaked cells in NU (n = 32) and in cortical PIVC (n = 59), VIP (n = 58), and MSTd (n = 127). E, F, Comparison of peak times for vestibular double-peaked cells among different areas: early peak times and late peak times (NU, n = 15; PIVC, n = 66; VIP, n = 26; MSTd, n = 43). Data for cortical areas have been replotted from Chen et al. (2011a,b).

Figure 7.

Example of best-fit acceleration model (Acc) to the spatiotemporal vestibular responses of a double-peaked Purkinje cell (same example as shown in Fig. 2). A, Direction-time color plot illustrating how direction tuning evolves over the time course of the response (spatial and temporal resolution: 45° and 100 ms, respectively). B, Model fits (left) and corresponding response residuals (right): acceleration (model Acc, r² = 0.735), velocity (model Vel, r² = 0.35), acceleration + velocity (model AccVel, r² = 0.74, w_a = 0.9, w_v = 0.1), and acceleration + velocity + position (model AccVelPos, r² = 0.741, w_a = 0.9, w_v = 0.1, w_p = 0.07). C, Response PSTHs for eight directions in the median plane together with superimposed curve-fitting lines for each model: Acc (black), Vel (red), AccVel (green).

Figure 8.

Example of best-fit velocity model (Vel) to the spatiotemporal vestibular responses of a single-peaked Purkinje cell. A, Direction-time color plot illustrating how direction tuning evolves over the time course of the response (spatial and temporal resolution: 45° and 100 ms, respectively). B, Model fits (left) and corresponding response residuals (right): model Acc, r² = 0.4; model Vel, r² = 0.77; model AccVel, r² = 0.775, w_a = 0.08, w_v = 0.92), model AccVelPos, r² = 0.78, w_p = 0.1). C, Response PSTHs for eight directions in the horizontal plane together with superimposed curve-fitting lines for each model: Acc (black), Vel (red), AccVel (green).

Figure 9.

Example of best-fit acceleration + velocity model (AccVel) to the spatiotemporal vestibular responses of a single-peaked Purkinje cell. A, Direction-time color plot illustrating how direction tuning evolves over the time course of the response (spatial and temporal resolution: 45° and 100 ms, respectively). B, Model fits (left) and corresponding response residuals (right): model Acc (r² = 0.53); model Vel (r² = 0.59); model AccVel (r² = 0.81, w_a = 0.54, w_v = 0.46); model AccVelPos (r² = 0.816, w_p = 0.03). C, Response PSTHs for eight directions in the frontal plane together with superimposed curve-fitting lines for each model: Acc (black), Vel (red), AccVel (green).

Figure 10.

Example of best-fit acceleration + velocity + position model (AccVelPos) to the spatiotemporal vestibular responses of a single-peaked Purkinje cell. A, Direction-time color plot illustrating how direction tuning evolves over the time course of the response (spatial and temporal resolution: 45° and 100 ms, respectively). B, Model fits (left) and corresponding response residuals (right): model Acc (r² = 0.49); model Vel (r² = 0.51); model AccVel (r² = 0.6, w_a = 0.49, w_v = 0.51); model AccVelPos (r² = 0.714, w_p = 0.6). C, Response PSTHs for eight directions in the frontal plane together with superimposed curve-fitting lines for each model: Acc (black), Vel (red), AccVel (green), AccVelPos (blue).

Figure 11.

Population summary of curve-fitting analysis in cerebellar NU for vestibular (left) and visual (right) responses. A, B, Percentage of Purkinje cells according to the best-fit model (Acc, Vel, AccVel, AccVelPos) for vestibular (A) and visual (B) responses. C, D, Cumulative distribution of fit model coefficients (r²) for vestibular (C) and visual (D) responses.

Figure 12.

Summary of model weights. Comparison of weights (w_a, w_v, w_p) calculated from best-fit model for NU and PIVC, VIP, and MSTd. A, B, Cumulative distributions of the ratio of acceleration to velocity weights (w_a/w_v) from model AccVel during vestibular (NU, n = 39; PIVC, n = 45; VIP, n = 30; MSTd, n = 48) and visual (NU, n = 11; VIP, n = 76; MSTd, n = 119) stimuli. Histograms along the top show the distributions of vestibular and visual weight ratios (w_a/w_v) for NU Purkinje cells, color coded according to the best model fit. C, Comparison of vestibular and visual weight ratios (w_a/w_v) for multisensory Purkinje cells (n = 11). D, E, Cumulative distributions of the position weights (w_p) from model AccVelPos during vestibular (NU, n = 39; PIVC, n = 45; VIP, n = 30; MSTd, n = 48) and visual (NU, n = 11; VIP, n = 76; MSTd, n = 119) stimuli. Histograms along the top show the distributions of vestibular and visual position weights for NU Purkinje cells, color coded according to the best model fit. F, Comparison of vestibular and visual position weights (w_p) for multisensory Purkinje cells (n = 11). Data for cortical areas have been replotted from Chen et al. (2011a,b).

Figure 13.

Summary of response latency obtained from the best-fit model. A, B, Cumulative distributions of response latency for vestibular (NU, n = 39; PIVC, n = 45; VIP, n = 30, MSTd, n = 48) and visual (NU, n = 11; VIP, n = 76, MSTd, n = 119) stimuli. Marginal histograms on top show the distributions of vestibular and visual response latencies for NU Purkinje cells, color coded according to the best model fit. C, Comparison of vestibular and visual response latency for multisensory Purkinje cells (n = 11). Solid line illustrates the diagonal.