We recorded from 103 MSTd neurons (from four monkeys) and 101 VIP neurons (from three monkeys), all of which were significantly tuned for heading defined by optic flow (see Materials and Methods
). Each neuron was first characterized as unisensory (visual-only) or multisensory (significantly tuned to both visual and vestibular heading stimuli) based on responses measured during a heading tuning protocol (Gu et al., 2006
, see Materials and Methods). This protocol consisted of either real (vestibular
condition) or visually-simulated (visual
condition) straight translational movements along either 26 possible directions sampled evenly on a sphere (Gu et al., 2006
) or 8 directions sampled within the horizontal plane. Inertial motion of the subject was achieved via a motion platform, and optic flow was presented by a projector mounted on the motion platform.
Multisensory neurons (MSTd: 42/103; VIP: 37/101) were significantly tuned (ANOVA, p<0.05) to heading for both visual and vestibular stimuli, as illustrated by the example cell in . The 3D heading tuning profile for each stimulus condition is shown as a color-contour map in which mean firing rate is plotted as a function of azimuth (abscissa) and elevation (ordinate). This cell exhibited broad, roughly sinusoidal tuning during inertial motion, with a heading preference at 192° azimuth and 25° elevation, corresponding to a leftward and slightly downward trajectory (Vestibular
condition, ). The heading preference in response to optic flow was roughly opposite, at 16° azimuth and −28° elevation, corresponding to a rightward and slightly upward trajectory (Visual
condition, ). Thus, this is an example of an “opposite” cell (Gu et al., 2006
; Takahashi et al., 2007
; Chen et al., 2011a
Across the population of neurons, heading tuning was classified as congruent or opposite by computing the absolute difference in heading preference (|Δ Preferred Heading|) between responses to the two modalities, an angle that varies between 0° and 180°. In this context, congruent cells were defined as having |Δ Preferred Heading| < 90° and opposite cells were defined as having |Δ Preferred Heading| ≥ 90°.
Examples of joint disparity-direction tuning
Once a cell was characterized as visual-only or multisensory (either congruent or opposite), we measured the joint disparity and direction tuning of the neuron using a protocol in which 8 directions of motion, spaced 45° apart in the fronto-parallel plane, were presented at 5 or 9 different binocular disparities, for a total of 45 or 72 disparity-direction combinations (see Materials and Methods). shows the joint disparity-direction tuning of the example cell, illustrated as a color-contour map, where the abscissa specifies motion direction (0 °–360°) and the ordinate represents horizontal binocular disparity (0°, ±1.6 ° and ±3.2°). This example neuron shows strong direction tuning at each disparity tested, but was not significantly disparity-selective (main effect of disparity, two-way ANOVA, p=0.14). Thus, this particular MSTd neuron did not respond differently to moving random dots at different horizontal disparities.
Three different patterns of interaction of disparity and direction are illustrated by the example neurons in and . shows data for a congruent cell from area MSTd, which was selective for both direction of motion and binocular disparity (two-way ANOVA, p<0.001 for both main effects). The cell preferred the same binocular disparities for all motion directions and had the same preferred direction for all disparities (, left and top curves, respectively). In other words, direction and disparity tuning were separable for this neuron. For disparity-selective cells, we quantified selectivity for near vs. far depth using a Depth Sign Discrimination Index (DSDI, Eqn. 3
), which varies from −1 (strong near preference) to +1 (strong far preference). For the neuron in , DSDI values measured for each motion direction ranged from 0.597 to 0.884, with a global DSDI of 0.707. Responses like those seen in were common among our sample of disparity-selective neurons (see below).
Figure 3 Joint direction-disparity tuning profile for a non-DDD, disparity-tuned, congruent MSTd cell. For this neuron, direction and disparity tuning are essentially separable, such that disparity tuning is similar for different directions and direction tuning (more ...)
Figure 4 Examples of two DDD neurons from area MSTd. (A) For this cell, disparity preference reversed for opposite motion directions (left), and direction preference reversed for near versus far disparities (top). (B) For this neuron, disparity preference reversed (more ...)
A different type of direction-disparity interaction is shown by the example neuron of . The cell’s overall disparity selectivity was not significant when pooled across directions (main effect of disparity, two-way ANOVA, p=0.91), but the disparity × direction interaction was highly significant (p<0.001). Moreover, this cell showed a clear reversal in disparity preference for opposite motion directions. Specifically, the cell preferred near disparities (DSDI < 0) for directions 270°, 0° and 315° (, left), but preferred far disparities (DSDI > 0) for directions 90°, 135°, and 180°. Analogously, this cell’s direction preference also depended sharply on binocular disparity: for far disparities, the cell preferred motion that was upward and to the left on the screen (, top), whereas for near disparities the cell preferred downward/rightward motion. We refer to this property as direction-dependent disparity (DDD) tuning (see Materials and Methods for classification criteria and Discussion for notes on interpretation). This sort of interaction has been previously reported in MSTd (Roy and Wurtz, 1990
; Roy et al., 1992
, see Discussion).
The cell illustrated in is another DDD cell, but one with a qualitatively different pattern of results. For this neuron, the depth-sign preference (near/far) again reversed as a function of motion direction, such that the cell preferred far disparities for directions 0°, 45° and 315° (, left), but near disparities for most other directions. However, unlike the cell in , the preferred direction of motion was consistent across all binocular disparities (, top). This was the dominant type of DDD tuning encountered in our sample of neurons, and this pattern of results occurs because the disparity tuning curves for different directions of motion do not cross (e.g., , left), even as the disparity preference reverses. Note that the two DDD cells in are both unisensory (visual-only) MSTd neurons. summarizes how DSDI changes with motion direction for the three disparity-selective exemplar neurons in , . For the non-DDD cell of , DSDI is fairly constant across directions. In contrast, DSDI varies in a sinusoidal-like manner for the two DDD cells of .
Across our sample of MSTd neurons, 72/103 (70%) were disparity-selective and these were classified as non-DDD (n=49, 48%) or DDD (23, 22%) cells (). Most DDD cells in MSTd (17/23) were unisensory, visual-only neurons, which did not respond to vestibular stimulation. Indeed, DDD cells constituted 37% (17/46) of all disparity-selective, visual-only cells. In contrast, only 6 DDD cells were multisensory, and these were evenly split between congruent and opposite cells. Only 5/23 DDD neurons, all of which were unisensory (visual-only) cells, reversed their disparity preference across motion directions and reversed their direction preference across disparities (e.g., ). Thus, the large majority (18/23, 78%) of DDD cells maintained their direction preference across disparities, while the disparity preference changed with direction (e.g., ).
Statistics of disparity tuning in MSTd and VIP.
Results from VIP were markedly different from MSTd (). First, there were fewer (41/101, 41%) disparity-selective cells in VIP. Second, only 5 of these neurons fulfilled the criteria to be DDD cells and none of these cells clearly reversed their direction preference across disparities. The vast majority (36/41, 88%) of disparity-selective VIP neurons were non-DDD cells. This difference in the incidence of DDD cells between MSTd and VIP was statistically significant (p < 0.001, χ2 test).
summarizes how DSDI varied as a function of motion direction for DDD and non-DDD cells in MSTd and VIP. To combine data across neurons, the DSDI vs. direction curve for each cell was shifted along the abscissa to align the data such that the peak DSDI for all cells occurred at a direction of 90 deg (see Materials and Methods). As illustrated in , the average DSDI of DDD cells depended strongly on motion direction, whereas non-DDD cells showed a much more modest dependence (). To quantify this distinction, we calculated the difference in DSDI between two opposite directions, 90° and 270°. This difference averaged 1.14±0.07 for DDD cells in MSTd, versus 0.43±0.05 for non-DDD cells (p <0.001, Wilcoxon test). Similarly, for VIP, the average difference in DSDI was 1.15±0.08 for DDD cells versus 0.45±0.04 for non-DDD cells (p< 0.001).
Figure 5 Population summary of dependence of DSDI on motion direction. Data are averaged across all disparity-selective neurons from MSTd (A, C) and VIP (B, D), and are shown separately for DDD (A, B) and non-DDD (C, D) cells. Data are color-coded to represent (more ...)
Note that some of the direction dependence of DSDI may result simply from our procedure of aligning all curves at their peak DSDI. To assess this, we permuted the data across directions for each neuron, and computed the distribution of DSDI values expected by chance when any true directional dependence of DSDI is destroyed by permutation. For non-DDD cells from both MSTd and VIP, the average difference in DSDI between 90° and 270° was ~0.3 following permutation. Thus, although the modulation of DSDI with direction for non-DDD cells was significantly greater than that expected by chance (p < 0.01), this modulation was quite modest relative to that exhibited by DDD neurons.
As noted above, most DDD cells did not reverse both their direction and disparity preferences. We performed an additional analysis to quantify the incidence of these effects across the population of DDD neurons. For each DDD cell, we found the pair of opposite directions (180° apart) that produced the maximal absolute difference in DSDI. For this purpose, we refer to the direction with the larger maximal response as ‘preferred’ and the opposite direction as ‘null’ (e.g., , inset a). For near disparities (≤ −1.6°), we compute the average difference in firing rate between the preferred and null direction curves and we plotted this value on the abscissa of the scatter plot in . Similarly, for far disparities (≥ + 1.6°), we plotted the average response difference between preferred and null directions on the ordinate of the scatter plot. Thus, data points that fall in the upper-left or lower-right quadrants of the scatter plot indicate neurons that reversed both direction preference and disparity preference, such as the examples shown in insets a and e. Data points that fall in the upper-right or lower-left quadrants indicate neurons that reverse disparity preference but not direction preference (e.g., insets b, c). Clearly most neurons fall in the upper-right quadrant indicating that they do not reverse direction preference.
Figure 6 Population summary of response patterns for DDD cells. For each neuron, the scatter plot shows the difference in average response between preferred and null directions at far disparities (ordinate) vs. the corresponding difference in response at near (more ...)
We now return to non-DDD neurons, to summarize their disparity and velocity tuning properties. For disparity-selective non-DDD cells, we computed a global DSDI across all motion directions to summarize disparity selectivity (see Materials and Methods). The mean DSDI for non-DDD cells in VIP (−0.317±0.050, SE) was significantly less (Wilcoxon rank test, p<0.001) than that for MSTd (0.100±0.062), as illustrated in . In MSTd, 22 cells had DSDI values significantly larger than zero and 16 cells had DSDI significantly <0. In contrast, only 4 cells in VIP had a significantly positive DSDI, whereas 29 cells had significantly negative DSDI values. This difference indicates a significant shift toward near disparity preferences in VIP (see also Colby et al., 1993
). There was no significant difference between DSDI distributions of multisensory and visual-only neurons in either MSTd (p=0.83, χ2
test) or VIP (p=0.28, χ2
test). Importantly, both near- and far-preferring cells were encountered in roughly equal proportions among multisensory cells, with no significant difference in the distribution of DSDI between congruent and opposite cells (MSTd: p=0.84, χ2
test; VIP: p=0.86). It was clearly not the case that congruent cells generally had near depth preferences and opposite cells typically preferred far depths, as would be expected from the motion parallax hypothesis (see Introduction).
Figure 7 Population summary of DSDI and speed preferences. (A), (B) Distributions of the global DSDI (computed across all motion directions) for disparity-selective non-DDD neurons from areas MSTd (n=49) and VIP (n=36). (C), (D) Distributions of preferred speed (more ...)
In addition to DSDI, speed tuning also differed between VIP and MSTd (p < 0.001, χ2 test), as illustrated in . Specifically, VIP cells preferred higher speeds than MSTd cells. Among 41 MSTd neurons tested, 14 (34%) preferred the highest speed (64°/s), and 10 (24%) preferred the second highest speed (32°/s). In contrast, 64/73 (88%) of VIP cells preferred 64°/s and 7 (10%) preferred 32°/s. There was no significant difference in speed preference between multisensory and unisensory neurons for either MSTd (p =0.19, χ2 test) or VIP (p =0.26, χ2 test).
We also pooled all non-DDD data from MSTd and VIP together to test whether there is a significant correlation between DSDI and preferred speed. There was indeed such a correlation between the global DSDI of non-DDD cells and speed preference (r = −0.46, p = 0.005, Spearman rank correlation, n=36). Neurons that preferred slow speeds also preferred far depths, and vice-versa. This correlation was driven partially by differences between areas given that VIP cells prefer high speeds and have near disparity preferences. Nevertheless, there was still a marginally significant relationship between DSDI and speed preference when only MSTd cells were considered (r = −0.49, p = 0.063, Spearman rank correlation, n=15).
Other stimulus parameters, like dot density (p=0.38, Wilcoxon matched-pairs test) and speed (p=0.90, F (1, 99) =0.033, ANCOVA), had no effect on the depth-sign selectivity of MSTd neurons, as illustrated in , respectively (shown for non-DDD cells only).
Figure 8 Dependence of DSDI on dot density and stimulus speed. Data are shown for non-DDD cells from area MSTd. (A) DSDI measured at a higher dot density (0.01 dots.deg−2) is plotted against DSDI measured at the standard density (0.002 dots.deg−2 (more ...)
Comparison of disparity tuning properties among areas MSTd, VIP, and MT
To quantify disparity tuning curves for MSTd and VIP neurons, we computed a disparity discrimination index (DDI; Eqn. 1
) for each of the 8 directions of motion. The disparity tuning curve for the direction with the largest DDI was then fit with a Gabor function, as long as tuning was significant (ANOVA, p<0.01). These criteria were met for 63 MSTd and 39 VIP neurons. Of these, the disparity tuning curves of 55 MSTd cells and 29 VIP cells were well fit by a Gabor function (R2
> 0.8) and these responses were used for quantitative comparisons with area MT.
shows disparity tuning curves and Gabor fits for four example neurons, two DDD cells one non-DDD cell from MSTd, as well as one non-DDD neuron from VIP. Data on the left show disparity tuning for the maximum DDI direction, with solid curves illustrating Gabor fits. Data on the right show tuning curves for the opposite direction of motion, along with Gabor fits when tuning was significant (ANOVA, p<0.01). The majority of MSTd and VIP cells preferred either near or far disparities and had monotonic tuning curves within the range of disparities tested. The DDD cell of preferred near disparities for the max DDI direction and far disparities for the opposite direction, with monotonic tuning for both directions. In contrast, the DDD cell of shows opposite depth-sign preferences and has non-monotonic tuning. The non-DDD MSTd cell of shows clearly peaked tuning with a preference near zero disparity, which was not common in MSTd or VIP. Finally, the non-DDD VIP cell of shows monotonic tuning to near disparities for one direction of motion and no significant disparity tuning for the other direction.
Figure 9 Example disparity tuning curves and Gabor fits for MSTd and VIP neurons. For each neuron/row, disparity tuning is shown for the direction of maximum DDI (left) and for the direction 180° opposite to it (right). Data are shown for two DDD cells (more ...)
summarizes the disparity tuning properties of MSTd (red) and VIP (blue) neurons, and compares them with data from area MT (green, data from DeAngelis and Uka, 2003
). Note that all cells are included in , whereas only neurons with significant disparity tuning and good Gabor fits are included in . Overall, the strength of disparity tuning in area MT (median DDI = 0.74) is significantly greater (p<0.001, Mann-Whitney U test) than that seen in MSTd and VIP (median DDI = 0.57 and 0.54, respectively), whereas the difference between MSTd and VIP was marginal (p=0.028, Mann-Whitney U test). There was no significant correlation between DDI and speed preference for area MSTd (p=0.73, Spearman rank correlation) or VIP (p = 0.46) separately, nor when data from these areas were pooled (p=0.52). In contrast, DDI depended significantly on speed preference in MT, such that neurons preferring fast speeds tended to have weaker disparity selectivity (DeAngelis and Uka, 2003
Striking differences between areas are evident in the range of disparity preferences and the breadth of tuning. As shown in , neurons in MSTd and VIP are tuned to a much broader range of disparities than cells in MT. VIP neurons show a strong bias toward near preferences (median = −2.21°) whereas disparity preferences in MSTd are fairly balanced (median =0.02°), and this difference is significant (p=0.003, Mann-Whitney U test). By comparison, disparity preferences in MT are much more tightly distributed around zero disparity, with a slight bias toward near preferences (median =−0.16°) (DeAngelis and Uka, 2003
). shows that median disparity frequencies in MSTd (0.11) and VIP (0.10) were similar (p=0.53), and were significantly lower than in MT (0.29, p<0.001, Mann-Whitney U test). The lower disparity frequencies in MSTd/VIP are consistent with the observation that disparity tuning in these areas was most commonly monotonic, with a preference for large far or near disparities.
It is important to be sure that these differences in disparity tuning parameters between areas are not an indirect effect of differences in receptive field eccentricity between recordings from the three areas. As shown in , eccentricities were indeed systematically smaller in the MT recordings than in MSTd/VIP. Note, however, that the greater range of disparity preferences and lower disparity frequencies observed in MSTd/VIP cannot be attributed to eccentricity. Within the range of eccentricities sampled in all three areas (~10–25°), disparity preferences in area MT are much more narrowly distributed than those in MSTd/VIP (), and disparity frequencies in MT are substantially larger than those in MSTd/VIP ().