Functional specializations of the ventral intraparietal area for multisensory heading discrimination

Abstract

The ventral intraparietal area (VIP) of the macaque brain is a multimodal cortical region with directionally selective responses to visual and vestibular stimuli. To explore how these signals contribute to self-motion perception, neural activity in VIP was monitored while macaques performed a fine heading discrimination task based on vestibular, visual, or multisensory cues. For neurons with congruent visual and vestibular heading tuning, discrimination thresholds improved during multisensory stimulation, suggesting that VIP (like the medial superior temporal area; MSTd) may contribute to the improved perceptual discrimination seen during cue combination. Unlike MSTd, however, few VIP neurons showed opposite visual/vestibular tuning over the range of headings relevant to behavior, and those few cells showed reduced sensitivity under cue combination. Our data suggest that the heading tuning of some VIP neurons may be locally remodeled to increase the proportion of cells with congruent tuning over the behaviorally relevant stimulus range. VIP neurons also showed much stronger trial-by-trial correlations with perceptual decisions (choice probabilities; CPs) than MSTd neurons. While this may suggest that VIP neurons are more strongly linked to heading perception, we also find that correlated noise is much stronger among pairs of VIP neurons, with noise correlations averaging 0.14 in VIP as compared with 0.04 in MSTd. Thus, the large CPs in VIP could be a consequence of strong interneuronal correlations. Together, our findings suggest that VIP neurons show specializations that may make them well equipped to play a role in multisensory integration for heading perception.

Figure 1.

Heading task and behavioral performance. A, Monkeys were seated on a motion platform and were translated forward along different heading directions in the horizontal plane to provide vestibular stimulation. A projector mounted on the platform displayed images of a 3D star field, and thus provided visual motion (optic flow) stimulation. B, After fixating a visual target, the monkey experienced forward motion with a small leftward or rightward (arrow) component, and subsequently reported his perceived heading (“left” vs “right”) by making a saccadic eye movement to one of two targets. C, The inertial motion stimulus followed a Gaussian velocity profile over the stimulus duration of 2 s (dashed line). The corresponding acceleration profile was biphasic (solid lines) with a peak acceleration of 1 m/s² (shown as the output of a linear accelerometer attached to the motion platform). D, Example psychometric functions from one session. The proportion of “rightward” decisions is plotted as a function of heading direction. Red, green, and blue symbols represent data from the vestibular, visual, and combined conditions, respectively. Smooth curves are best-fitting cumulative Gaussian functions. E, F, Average psychophysical thresholds from two monkeys (monkey U, n = 31 and monkey C, n = 64) for each of the three stimulus conditions, and predicted thresholds computed from optimal cue integration theory (cyan). Error bars indicate SEM.

Figure 2.

Examples of neuronal tuning and neurometric functions for one congruent cell (A–C) and one opposite cell (D–F). A, D, Heading tuning curves measured in the horizontal plane (red, vestibular; green, visual). The 0° heading denotes straight forward translation, whereas positive/negative numbers indicate rightward/leftward directions, respectively. B, E, Responses of the same neurons during the heading discrimination task, tested with a narrow range of heading angles placed symmetrically around straight ahead (0°). C, F, Neurometric functions computed by ROC analysis. Smooth curves show best-fitting cumulative Gaussian functions. Neuronal thresholds were as follows: congruent cell (A–C): 8.6, 10.6, and 4.7°; opposite cell, 5.2, 4.6, and 19.7°, for vestibular, visual, and combined data, respectively.

Figure 3.

Improvement in neuronal sensitivity under cue combination depends on congruency of visual and vestibular tuning. A, Scatter plot of the ratio of the threshold measured in the combined condition relative to the prediction for optimal cue integration (Gu et al., 2008) versus the local CI (see Materials and Methods). Cyan symbols are used for congruent neurons with CI > 0.4 (n = 36); magenta symbols are used for opposite neurons with CI < −0.4 (n = 5); black symbols mark intermediate neurons for which −0.4 < CI < 0.4 (n = 15). Dashed horizontal line: threshold in the combined condition is equal to the prediction. Solid line shows type II linear regression. Triangles and circles denote data from monkeys C and U, respectively. B, Marginal distributions comparing this ratio for opposite (magenta), intermediate (black), and congruent (cyan) VIP neurons. Arrowheads illustrate geometric mean values.

Figure 4.

Summary of neuronal threshold and choice probability (middle 1 s). A, Distributions of neuronal/psychophysical threshold (N/P) ratio for monkey U (filled bars) and monkey C (hatched bars). Arrowheads illustrate geometric mean N/P ratios. B, Distributions of CP, with filled bars denoting cells with CPs significantly different from chance (CP = 0.5). Arrowheads illustrate mean values. C, CP plotted against neuronal threshold (circles, monkey U; triangles, monkey C), shown separately for vestibular-only (red, n = 15), visual-only (green, n = 24), and multisensory (black, n = 56) cells. Filled symbols denote neurons for which the CP was significantly different from 0.5. Solid lines are linear regressions. Different columns show vestibular (left, n = 71), visual (middle, n = 80), and combined (right, n = 95) responses.

Figure 5.

CP as a function of congruency of tuning. CPs for vestibular (A), visual (B), and combined responses (C), are plotted as a function of the CI. Filled symbols denote neurons for which the CP was significantly different from 0.5. Cyan, magenta, and black symbols are used for congruent (n = 36), opposite (n = 5), and intermediate (n = 15) neurons, respectively. Circles and triangles show data from monkey U and monkey C. Solid lines show linear regressions.

Figure 6.

Combined condition responses are well approximated by linear weighted summation. A, Predicted responses from weighted linear summation are strongly correlated with measured responses under the combined condition (r = 0.99, p ≪ 0.001). Each symbol represents the response of one neuron at one heading angle (after spontaneous activity is subtracted). Cyan, magenta, and black symbols are used for congruent (n = 36), opposite (n = 5), and intermediate (n = 15) neurons, respectively. B, Distribution of correlation coefficients from the linear regression fits. Three cases with negative (but not significant) R² values are not shown. C, Visual and vestibular weights derived from the best fit of the linear weighted sum model for each neuron with significant R² values (black bars in B). Arrowheads illustrate mean values. Solid line shows linear regression. Circles, monkey U; triangles, monkey C.

Figure 7.

Relationship between local and global measures of visual/vestibular congruency. A, Global congruency, defined as the difference between vestibular/visual preferred headings, |Δ Preferred Heading|, computed from horizontal plane tuning curves (as in Gu et al., 2006; Chen et al., 2011c). B, Scatter plot comparing the global measure (from A) and the local measure (CI; see Materials and Methods). Blue circles represent cells with unimodal heading tuning curves for both the vestibular and visual conditions. Orange triangles denote neurons with bimodal heading tuning in either the vestibular or visual condition. Data are only shown for multisensory neurons (n = 56). C, D, Global and local tuning curves for two cells (marked “1” and “2” in B) for which local and global congruency measures do not agree well. Cells 1 and 2 would be classified as opposite based on global congruency (|Δ Preferred Heading| = 124.9 and 158.4°), or congruent based on local congruency (CI = 0.74 and 0.82). Red, vestibular tuning curves; green, visual tuning curves.

Figure 8.

Time course of population responses, neuronal threshold, and CP. A, B. Average forward motion (0° heading) population responses from VIP (A) and MSTd (B). Data from discrimination trials in which the animal made choices in favor of the preferred (violet) or non-preferred (dark yellow) direction are compared with data obtained during passive fixation (black). Vertical lines indicate the onset and offset of the stimulus. C, D. Average neuronal thresholds (C) and CP (D) for VIP (orange) and MSTd (black) cells. Left, Vestibular (VIP: n = 71; MSTd: n = 164), middle, visual (VIP: n = 80; MSTd: n = 178); right, combined (VIP: n = 95; MSTd: n = 182). Dotted horizontal lines in D indicate chance level (CP = 0.5). All responses are computed from a 400 ms sliding window and a step size of 50 ms. Shaded areas around each mean illustrate 95% confidence intervals.

Figure 9.

Measuring noise correlation (r_noise) between pairs of single neurons recorded simultaneously from the same electrode. A, B, Examples of vestibular (A) and visual (B) heading tuning curves for a pair of simultaneously recorded VIP neurons (solid and dashed black curves). Responses are plotted as a function of heading direction in the horizontal plane, with 0° indicating a straight forward trajectory. Error bars indicate SEM. C, D, Normalized responses from the same two neurons were weakly correlated across trials during vestibular (C) and visual (D) stimulation, with noise correlation values of r_noise = 0.50 and 0.59, respectively. Dotted lines mark the unity-slope diagonal.

Figure 10.

Properties of noise correlations for the VIP population. A, Comparison of noise correlations measured during visual and vestibular stimulation (n = 139). B, Comparison of noise correlations measured during the passive fixation-only task and the active heading discrimination task (n = 10), shown separately for visual and vestibular responses.

Figure 11.

Comparison of the interneuronal correlations between VIP and MSTd. A, B, Average (±95% CI) time course of noise correlation (r_noise) in area VIP (orange) and MSTd (black) during vestibular (A) and visual (B) stimulation (VIP: n = 139; MSTd: n = 67). C, D, Relationship between r_noise and signal correlation (r_signal) in area VIP (orange) and MSTd (black) during vestibular (C) and visual (D) stimulation. Data are separated into those recorded from naive (open symbols, VIP: n = 75; MSTd: n = 25) and trained (filled symbols, n = 64; MSTd: n = 42) animals. Lines show linear regression fits to the data from each area (pooled across naive and trained animals). E, F, VIP data with significant tuning either to vestibular or visual stimuli for each pair, now separated into the type of recorded pair. MM (Multisensory + Multisensory), both cells were multisensory (n = 14); UM (Unisensory + Multisensory), one cell was multisensory, the other unisensory (n = 21); and UU (Unisensory + Unisensory), both cells were unisensory (n = 29). Lines represent regression fits (ANCOVA). Only data recorded from a single electrode are shown (MSTd data from Gu et al., 2011).