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Department of Neurobiology, Washington University School of Medicine, St. Louis, Missouri
Submitted 7 December 2004; accepted in final form 7 January 2005
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ABSTRACT |
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 TOP ABSTRACT INTRODUCTIONMETHODSRESULTSDISCUSSIONAPPENDIXGRANTSACKNOWLEDGMENTSREFERENCES |
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INTRODUCTION |
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TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONAPPENDIXGRANTSACKNOWLEDGMENTSREFERENCES |
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). Although the rotational VOR (RVOR) has been well characterized at both behavioral and neurophysiological levels, the neural mechanisms and computations underlying the generation of compensatory eye movements during translation are less well understood. In fact, there are several lines of evidence to suggest that the translational VOR (TVOR) might be organized differently from the RVOR. First, the signals carried by primary semicircular canal and otolith afferents differ in their dynamic properties. For example, primary otolith afferents encode linear head acceleration, whereas the semicircular canals code most closely for head velocity over a mid- to high-frequency range (Fernandez and Goldberg 1971, 1976). Second, unlike the semicircular canals where all afferents innervating a single receptor organ exhibit identical spatial selectivity, multidirectional motion information is encoded within a single otolith organ, suggesting the potential requirement for a unique convergence of sensory information. Third, the geometrical relationships required to ensure appropriate ocular counterrotation in response to translation imply a strong dependency of the TVOR on target location and require changes in both the gain and direction of compensatory responses depending on the binocular fixation state. Finally, there is increasing evidence that, at least in cats, the synaptic organization of otolith–ocular pathways is different from that of the semicircular canals (Imagawa et al. 1995; Schwindt et al. 1973; Uchino et al. 1994, 1996, 1997). Based on these differences at both sensory and motor levels, as well as the existence of potentially unique neuroanatomical connections, it was proposed that the sensorimotor processing of canal and otolith signals in the RVOR and TVOR is at least partially distinct (Angelaki et al. 2001; Green 2000; Green and Galiana 1998; for a review see also Angelaki 2004).
In the case of the RVOR, it has been well established that the most direct vestibuloocular connections are based on a 3-neuron–arc pathway (Baker et al. 1969; Precht et al. 1969; Schwindt et al. 1973) in which the key 2nd-order neurons are located in the rostral vestibular nuclei (VN). Based on their response characteristics during head-stationary target fixation, smooth pursuit and different combinations of visual and rotational vestibular stimulations, distinct populations of eye-movement–sensitive cells have been identified in the RVOR pathways. These include position–vestibular–pause (PVP), burst–tonic (BT), and eye–head (EH) neurons (Chubb et al. 1984; Fuchs and Kimm 1975; Keller and Daniels 1975; Keller and Kamath 1975; King et al. 1976; McFarland and Fuchs 1992; Miles 1974; Scudder and Fuchs 1992; Tomlinson and Robinson 1984). At least a subset of all three groups of neurons have been confirmed to be premotor cells, making direct projections to either the contralateral or the ipsilateral abducens nucleus (McCrea et al. 1987; Scudder and Fuchs 1992) or to the ipsilateral oculomotor nucleus by the ascending tract of Dieters (Chen-Huang and McCrea 1998; McCrea et al. 1987).
Little is currently known about the neural elements and sensorimotor transformations for the TVOR. Over the past years, a few studies have examined the responses of eye-movement–sensitive VN neurons during translational motion (Angelaki et al. 2001; King et al. 2003). Several other studies have also examined neural activities during eccentric rotation, when the stimulus includes both rotational and translational components (Chen-Huang and McCrea 1999a, b; McConville et al. 1994). Collectively these investigations have shown that each neuron type encodes translation and rotation signals differently. Specifically, it was shown that type I PVP cells, the main interneurons in the RVOR pathway, do not modulate during TVOR cancellation (Angelaki et al. 2001; King et al. 2003). By eliciting an identical movement of both eyes at a viewing distance of 20 cm, we previously compared responses during translation and pursuit, without incorporating assumptions regarding the explicit contribution of eye position and velocity signals to cell activities at different frequencies and viewing distances (Angelaki et al. 2001). These results suggested that during translation at midrange frequencies (0.5 Hz), the activities of most premotor cells are dominated by motorlike (i.e., eye-movement–related) signals during translation. This is in contrast to the case of rotation, where PVP and EH cells demonstrate significant sensitivities to both head movement and eye-movement–related signals. It was thus speculated that, although the same subsets of neurons may participate in both reflexes, the pattern of sensory signal flow might be very different for the translational as compared with the rotational components of the VOR (see also Angelaki 2004; Green 2000; Green and Galiana 1998).
The present study represents a more thorough characterization of the properties of these cells during 0.5-Hz rotation, translation and pursuit, for two different viewing distances, 20 and 80 cm. The goals of the current experiments were 3-fold. First, to investigate whether the observation of more motorlike responses for the TVOR compared with the RVOR also holds true for different viewing distances. Second, to examine whether other aspects of neural response modulation (e.g., neuronal phase, as well as VOR cancellation responses) depended on viewing distance. Last, we sought to test whether neural modulation under stable gaze conditions could be satisfactorily predicted from a linear superposition of their responses during pursuit and those during VOR cancellation. Although this issue has been previously addressed for the RVOR (Cullen and McCrea 1993; Cullen et al. 1993; Roy and Cullen 2003; Scudder and Fuchs 1992), it has never before been investigated under near-viewing conditions. In the latter situation, pursuit and head movement sensitivities cannot simply be summed because of the fact that a given head rotation results in a pursuit (retinal slip) stimulus whose amplitude depends on viewing distance (see APPENDIX). Furthermore, a linear superposition of signals has never been investigated in the case of the TVOR, where the effect of viewing distance is much larger. Because the goal was to directly compare neural responses to rotation, translation, and pursuit in the presence of similar eye movements, this study has focused on the characterization of the steady-state sinusoidal responses of PVP, BT, and EH neurons at a frequency where animals can reliably pursue (e.g., 0.5 Hz). Because type I PVP neurons (typically encountered more laterally in the VN; Scudder and Fuchs 1992) appear to carry motorlike signals during translation (Angelaki et al. 2001; King et al. 2003), our interest here has focused more on other cell types, including BT cells that have not been adequately characterized in past studies during translation. Thus in contrast to many previous investigations, most of our electrode penetrations aimed more medially in the VN, including many electrode tracks into the nucleus prepositus hypoglossi (PH) and its border with the medial VN. Preliminary results of this work have appeared in abstract form (Meng et al. 2004).
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METHODS |
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TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONAPPENDIXGRANTSACKNOWLEDGMENTSREFERENCES |
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Experiments were carried out in 3 juvenile Macacca mulatta and 2 Macacca fascicularis monkeys that were prepared for chronic recording of binocular eye movements and single-unit activities. Animals were chronically implanted with a delrin head-restraint ring that was anchored to the skull by stainless steel inverted T-bolts. For single-unit recording from the brain stem, a delrin platform was stereotaxically secured to the skull and fitted inside the head ring. The platform had staggered rows of holes (spaced 0.8 mm apart) that extended from the midline to the area overlying the vestibular nuclei bilaterally. For 4 of the animals, the platform was implanted with a 10° lateral/medial slant, to allow better access to the PH. In separate surgeries, all animals were also implanted with dual eye coils on both eyes (cf. Angelaki 1998; Angelaki et al. 2000). Eye coils were calibrated both before implantation and daily during experiments, as explained in detail elsewhere (Angelaki 1998; Angelaki et al. 2000; McHenry and Angelaki 2000). Subsequent to the eye coil surgeries, animals were sufficiently trained to fixate and pursue visual targets. All surgical procedures were performed under sterile conditions in accordance with institutional and National Institutes of Health guidelines.
Experimental setup
During experiments, the monkeys were seated in a primate chair that was secured inside the inner gimbal of a vestibular turntable consisting of a linear sled on top of a yaw-axis rotator (Neurokinetics, Pittsburgh, PA). In all experiments, the head was positioned such that the horizontal stereotaxic plane was earth-horizontal. The yaw axis was used to study neurons during rotations in the horizontal plane. The translational stimulus profiles were generated using the linear sled that moved in an earth-horizontal plane. Stimulus presentation and data acquisition were controlled with custom-written scripts within the Spike2 software environment using the Cambridge Electronics Device (CED, model power 1401) data-acquisition system.
Animals were trained to fixate and pursue a small target light that was back-projected onto a flat screen using a laser and x–y mirror galvanometer system (General Scanning), which was secured on the wall of the room. This system also provided a world-fixed target for the RVOR and TVOR. In these experiments, the screen was placed either 20 or 80 cm away from the animal. For fixation, smooth pursuit, and world-fixed targets during rotation and lateral translation, the galvanometer was controlled directly by the Spike2 scripts and the CED system. An additional laser was mounted on top of the turntable, which, because it moved with the animal, provided a head-fixed target during rotational and translational motion for VOR cancellation tasks. The behavioral performance of the animal was continuously monitored using electronic windows, which ensured that right and left eye positions were maintained within 1.5° of ideal target fixation. This "eye-in-window" signal was monitored by the CED for on-line juice reward delivery and was saved for off-line analyses. Behavioral windows for each eye were calculated on-line on the basis of the geometrical relationships that should govern appropriate target fixation or ideal target stabilization for a given motion of the target and/or head movement (Angelaki et al. 2000; McHenry and Angelaki 2000). Juice rewards were typically given at a frequency of once every 2 s, as long as the gaze directions of both eyes were within the specified behavioral windows.
Eye movements were measured with a 3-field magnetic search coil system (16-in. cube; CNC Engineering, Seattle, WA) that was attached to the inner gimbal of the turntable. Binocular eye movements were recorded in 3 dimensions. For each recording session, the voltage signals of the dual eye-coils, the 3-D linear accelerometer signals (mounted on fiberglass members that firmly attached the animal's head ring to the inner gimbal of the rotator), as well as velocity and position feedback signals from the rotator and/or linear sled were anti-alias filtered (200 Hz, 6-pole Bessel), digitized at a rate of 833.33 Hz (CED, model 1401, 16-bit resolution), and stored on a PC for off-line analysis.
Extracellular recordings were obtained using epoxy-coated, etched tungsten microelectrodes (2–4 M
impedance; FHC, Bowdoinham, ME). Electrodes were inserted into 26-gauge stainless steel canulas (outside diameter of 457 µm) and then advanced through a predrilled hole in the recording platform into the brain and manipulated vertically with a remote-controlled mechanical microdrive. Neural activity was amplified, filtered (300 Hz to 6 kHz), and passed both to an audio amplifier and to a BAK Instruments dual time–amplitude window discriminator, the output of which was displayed on an oscilloscope. For each recorded cell, acceptance pulses from the BAK window discriminator were used to trigger the event channel of the CED data-acquisition system that stored the time of the spike at a 10-µs resolution.
Neural recordings
Explorations for vestibular and eye-movement–sensitive cells concentrated in the rostral medial part of the vestibular nuclei and the nucleus prepositus hypoglossi, areas that previously have been shown to contain eye-movement–sensitive cells, many of which project directly to the abducens and oculomotor nuclei (Cullen and McCrea 1993; McCrea et al. 1987; Scudder and Fuchs 1992). To locate these areas, the abducens nuclei were first identified in each animal on the basis of the characteristic burst–tonic activity of the neurons (Fuchs and Luschei 1970; Fuchs et al. 1988). Penetrations then concentrated within a 3 x 3-mm area 2 starting platform holes (1.6 mm) posterior to the center of the abducens nucleus. Once a vestibular nucleus or prepositus neuron was isolated, a specific set of protocols was used to characterize its properties. First, neural activities were recorded during sinusoidal horizontal rotation (0.5 Hz; ±10° for both the 80- and 20-cm targets) with the animal fixating either a central world-fixed target (stable gaze in space) or a central, head-fixed target (RVOR cancellation). The axis of rotation was always earth-vertical and located in the midsagittal plane, intersecting the line connecting the 2 auditory meatii. Second, neural activities were recorded during horizontal and vertical sinusoidal smooth pursuit (0.5 Hz; ±10° for the 80-cm target, ±12° for the 20-cm target). The increase of pursuit amplitude for the near-target condition was done to evoke the same eye movement as that during the RVOR (because during near-target viewing, the RVOR has a gain greater than unity). Third, the static eye position and saccadic sensitivities of cells were evaluated by recording neural activities during fixation and visually guided saccades to different targets with eccentricities extending ±20° horizontally and vertically.
Finally, recorded cells were also tested during 0.5-Hz lateral translation. With the target at 80 cm, the peak amplitude of translation was 0.1 G (±10-cm displacement). This was the maximum motion that could be delivered by the sled and resulted in compensatory eye movements with a peak amplitude of about 22°/s (7°), a value that was slightly less than those during RVOR and pursuit (about 31°/s, 10°). At a viewing distance of 20 cm, the amplitude of linear displacement under stable gaze conditions was reduced to 0.04 G, to elicit a compensatory response of about 12°. This translational stimulus was chosen to match the ocular deviations required to maintain target fixation with those elicited during yaw rotation and the horizontal smooth pursuit paradigms. For the TVOR cancellation task at a viewing distance of 20 cm, both amplitudes (±0.1 and ±0.04 G) were used.
Data analyses
All data were analyzed off-line using Matlab (The MathWorks, Natick, MA). Eye position was calibrated and expressed as 3-D rotation vectors, as described in detail elsewhere (Angelaki 1998; Angelaki et al. 2000). Positive directions were leftward and downward. Saccades and fast phases of nystagmus were identified and removed through a semiautomated computer algorithm based on a higher derivative of eye velocity (Angelaki 1998; Angelaki and Hess 1994). The algorithm offered manual inspection of the automatically detected fast phases and allowed the experimenter to correct potential misidentifications. For each recorded run, neural data were also "desaccaded " using a window that extended from 50 ms before to 100–200 ms after each saccade (Scudder and Fuchs 1992).
To estimate the gain and phase during rotation, translation, and pursuit, "desaccaded " neural activity from multiple stimulus cycles was folded in time into a single-cycle instantaneous frequency response for each stimulus condition. This was done as follows: First, for each spike, an occurrence time was logged. Instantaneous firing rate (IFR) was then calculated as 1/interspike interval and assigned to the middle of the interval. For each stimulus cycle (e.g., nth cycle), an integral (n – 1) times the period was subtracted from the timing for all of the instantaneous frequency values for that specific cycle. (For example, for a frequency of 1 Hz, this would be 1 s for cycle 2, 2 s for cycle 3, etc.) The result is to "fold" all instantaneous frequency values into a single stimulus cycle. This procedure provides no averaging because all spike occurrences are represented in time. Only portions of data in which the positions of both eyes were within ±1° of the target were included in the folding and further analyses. The peak amplitude and phase of eye velocity, head velocity, and linear acceleration, as well as neural firing rates during translation, rotation, and pursuit were then determined by fitting a sine function (1st and 2nd harmonics and a DC offset) to the overlaid data using a nonlinear least-squares algorithm based on the Levenberg–Marquardt method. Only cells for which the 2nd to 1st harmonic ratio was <0.5 were included for analyses.
For pursuit responses, neural gains were always expressed in spikes · s–1 per deg · s–1 of evoked eye velocity. For rotation and translation stimuli, neural response gains were expressed either relative to the sensory stimulus or relative to the evoked eye movement. Thus similar to previous studies, rotational gains were expressed as spikes · s–1 per deg · s–1 of head rotation. Similarly, response gains during translation were expressed relative to the linear acceleration stimulus, in units of spikes · s–1 · G–1 (with G = 9.81 m/s2). Peak response gains <0.1 spikes · s–1 per deg · s–1 (for rotation and pursuit) or 60 spikes · s–1 · G–1 (for translation) were considered unresponsive. In addition, rotational and translational responses under stable gaze conditions were also expressed in spikes · s–1 per deg · s–1 of evoked eye velocity, by dividing peak firing rate with peak eye velocity. Phase was expressed as the difference (in degrees) between peak neural activity and peak head (for rotation and translation) or eye (for pursuit) velocity. Positive stimulus directions were leftward for both rotation and translation. Because data were typically recorded from both sides of the brain stem, phase values in all plots have been adjusted to represent neural activities from the left side. Thus phases close to zero correspond to ipsilateral eye/head preferences, whereas phases close to 180° represent contralateral eye/head preferences. Fixation data and multiple linear regression analyses were used to estimate the eye position sensitivity of the neurons.
Based on the saccadic, pursuit, and RVOR responses, each cell was classified into one of 4 groups (Scudder and Fuchs 1992).
To evaluate correlations between parameters, we used linear regression. Because variables were independent of each other, regression lines were obtained by minimizing the perpendicular offset of the data to the line (custom-written script in Matlab). The statistics of these regressions were evaluated as follows: Bootstrapping with replacement was performed on the data and a new slope was computed for each bootstrap. This gave a distribution of slopes, and 95 or 99% confidence intervals were computed as the 2.5–97.5 or 0.5–99.5% confidence intervals of the distribution. Other statistical comparisons were based on ANOVA with viewing distance as a repeated measure.
Histology
Three animals used for single-unit recordings in these studies have been analyzed for histological confirmation of recording locations based on electrode track identification and/or neuroanatomical tracer injection. For example, in one of the animals (animal T, where approximately one third of the neurons were recorded), a neural tracer [biotinylated dextran amine (BDA)] was injected after termination of all experiments in one of the recording locations at the medial boarder of the medial VN, 
1.2 mm caudal to the abducens (Fig. 1). Animals were deeply anesthetized (pentobarbital sodium) and perfused transcardially with a 2% paraformaldehyde and 2% glutaraldehyde solution. The brain was removed, sectioned (80 µm), and counterstained (alternate sections with cresyl violet and Weil). An approximate recording location map was reconstructed, using the penetration records and identified location of the abducens nucleus. Based on these histological analyses, all data included in this analysis were located within the vicinity of the medial VN and PH, 
1 mm posterior to the abducens nuclei. Notice, however, that other than a qualitative assessment of the medial/lateral location, we did not identify cells as specifically located within the PH, the marginal zone, or the medial VN (McFarland and Fuchs 1992). Thus the BT population whose responses have been described here includes neurons throughout the medial–lateral extent of our penetrations.
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RESULTS |
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TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONAPPENDIXGRANTSACKNOWLEDGMENTSREFERENCES |
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Responses from two typical EH neurons, one with contralateral, the other with ipsilateral eye and head movement sensitivity, as the animal tracked far and near targets have been illustrated in Figs. 2 and 3. The contralateral EH cell in Fig. 2 was recorded in the right VN and increased its firing rate with a small lag with respect to leftward-directed eye velocity during horizontal pursuit or approximately in phase with leftward-directed head velocity during yaw RVOR cancellation. Because pursuit responses were larger than RVOR cancellation responses, the firing rate of the cell reversed modulation direction (relative to the head velocity stimulus) when stabilizing a world-fixed target during rotation. In this condition the eyes and head moved in opposite directions such that the cell increased its firing rate during rightward-directed head or leftward-directed eye velocity. During TVOR cancellation, when the animal made no eye movements, there was no modulation. As will be summarized below (Table 1), this was typical of most c-EH cells. In contrast, during translation while fixating a world-fixed target, a robust modulation was observed that was consistent with its response during rotation and pursuit (i.e., the cell increased its firing rate during rightward motion that elicited leftward eye movements). The pattern of response modulation did not change when these stimuli were delivered while the animal was fixating a near target at 20 cm (Fig. 2, bottom).
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; Lisberger et al. 1994), eye and head modulations during translation were congruent. This was a common finding for all cell types we studied: the neuron's preference during TVOR cancellation could not be predicted on the basis of its responses to rotation. Like the c-EH cell responses of Fig. 2, the properties of this i-EH neuron were similar during fixation of a far and near target, despite the difference in vergence angle (Fig. 3, top and bottom panels). The cell responses illustrated in Figs. 2 and 3 were representative of EH neurons. Although only 3 (15%) c-EH cells responded during TVOR cancellation, this was true of a larger percentage of i-EH neurons (17/35, 49%). The group with the largest proportion (53%) of cells responding during TVOR cancellation was the type II PVP neurons (Table 1). In contrast, we did not encounter type I PVP cells that exhibited a clear modulation during translation in the absence of eye movements. Similarly, none of the i-BT or c-BT cells (located throughout the medial–lateral extent of our penetrations and thus presumably located either in the VN or PH) was modulated during TVOR cancellation (Table 1). In the following, we examine the properties of these cells in more detail, starting first with their responses during VOR cancellation in the absence of eye movement and continuing with their properties under stable gaze conditions with a focus on their relationship to the motor responses during pursuit.
Neural response properties during RVOR and TVOR cancellation
The cancellation response gains of the neurons during rotation and translation have been plotted, separately for each cell type, in Fig. 4. During RVOR cancellation, response gain was independent of response type (ANOVA, P > 0.05), but depended on viewing distance [repeated-measures ANOVA, F(1,41) = 8.3, P < 0.01]. Specifically, the peak modulation of all cell groups tended to be slightly larger for 80 cm, compared with 20 cm (1.22 ± 0.99 vs. 1.07 ± 0.89 spikes · s–1 per deg · s–1, respectively; see inset in Fig. 4, top). The opposite result was seen during TVOR cancellation, where neural response gains averaged 257 ± 261 versus 328 ± 323 spikes · s–1 · G–1 for 80 and 20 cm, respectively. The significantly higher TVOR response gain for near compared with far targets [repeated-measures ANOVA, F(1,14) = 16.5, P < 0.01] depended on cell type [F(3,14) = 5.4, P = 0.01]. Specifically, only the EH cells (but not type II PVP cells) showed a large increase in response modulation during near-target viewing (see the insets in Fig. 4, bottom). Because none of the type I PVP or BT cells modulated during TVOR cancellation (Table 1), these neuron types were excluded from this comparison. There was also no consistent relationship between neural response gain to rotation and translation (R2 = 0.05, P > 0.05).
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During translation while stabilizing a world-fixed target, the eye movement that must be generated for the same sensory stimulus is larger the closer the target is to the subject (Paige and Tomko 1991; Schwarz et al. 1989). Thus to study cell modulation under stable gaze conditions we first quantified whether neural response gain changed under far- versus near-viewing conditions in a fashion similar to oculomotor behavior. Accordingly, gains for the 20-cm target distance have been plotted versus the respective values for the 80-cm distance in Fig. 6. Note that to compare the relationships between neural responses and the motor output, all data have been expressed as neural gains relative to the respective eye velocity evoked (i.e., as spikes · s–1 per deg · s–1). Thus, responses that fall along the unity slope indicate a viewing distance–dependent change in cell activities equivalent to the change in ocular gain. For the RVOR, neural response gains were slightly lower for near- compared with far-viewing conditions [1.4 ± 0.9 vs. 1.6 ± 1.0 spikes · s–1 per deg · s–1, repeated-measures ANOVA, F(1,55) = 12.7, P < 0.01]. Post hoc analysis showed that this effect was attributed to type II PVP cells, whose gains averaged 1.5 ± 1.0 and 1.8 ± 1.2 spikes · s–1 per deg · s–1 for 20 and 80 cm, respectively (Fig. 6, top, magenta squares). At present there is no evidence that type II PVP neurons represent interneurons in the RVOR pathways. Thus it is worth emphasizing that all cell types known to be key RVOR interneurons (type I PVP, BT, and EH cells) exhibited responses that scaled proportional to eye velocity.
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Neural response phase during stable gaze rotation/translation and pursuit did not depend on viewing distance, as illustrated in Fig. 10, which plots the respective phase values for those neurons whose responses were obtained at both viewing distances (repeated-measures ANOVA, P > 0.05). The bar histograms on the left and bottom sides of the graphs illustrate the phase distributions of all cells whose responses were obtained at that viewing distance. Means (±SD) from these histograms are also summarized in Fig. 11. Notice that, although the comparisons of phase for the two viewing distances in Fig. 10 use only neurons tested under both viewing distances, the plots in Fig. 11 summarize the means and variability of all cells tested at either distance. Another difference between the figures is that the means shown in Fig. 11 have been plotted in the same range, independently of the ipsilateral/contralateral preference of each neuron type. This way, direct comparisons can be made between Eye-ipsi and Eye-contra cells of the same neuron type. As shown in previous studies (Cullen and McCrea 1993; Cullen et al. 1993; Lisberger et al. 1994; Scudder and Fuchs 1992), neuron types differed in response phase during pursuit eye movements. Those with the largest phase lags (relative to eye velocity) were the BT and PVP cells. In contrast, EH neuron phases were more variable and could either lead or lag eye velocity (Fig. 11, top; see also Table 2).
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Can the responses during stable gaze be predicted as a sum of pursuit and cancellation activities?
One of the goals of the present study was to investigate whether viewing distance had any effect on the extent to which neural responses during gaze stabilization reflect a linear superposition of processed vestibular and visual sensory signals. A detailed explanation of the analysis to follow is provided in the APPENDIX. Briefly, the linear superposition hypothesis would expect that the firing rate sensitivity to head motion under world-fixed target stabilization conditions (expressed relative to rotational or linear head velocity) is equivalent to the sum/difference (depending on choice of signs) of the cell's sensitivity during head-fixed target stabilization (VOR cancellation) and a scaled estimate of its sensitivity to target motion, which we are approximating as its sensitivity to eye motion. Figure 12 plots the actual neural response gain under stable gaze conditions as a function of the respective value computed according to the linear superposition hypothesis. Both visual inspection and quantitative analysis (Table 3) suggest the following: 1) The linear superposition hypothesis held under far-viewing, but not necessarily under near-viewing, conditions. Accordingly, the slopes of the linear regression lines drawn through the data for all cell types were not significantly different from unity for the 80-cm distance, but were statistically different for the 20-cm distance (Table 3, last row). 2) The departure from linearity at 20 cm was stronger for the TVOR than the RVOR, resulting in slopes that were 0.81 and 0.93, respectively (Table 3). For the RVOR, the largest departure from linearity was seen in the type I PVP and i-EH cells. In contrast, for the TVOR, it was both the EH and the type II PVP cells that deviated the most from the linear addition predictions.
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DISCUSSION |
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TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONAPPENDIXGRANTSACKNOWLEDGMENTSREFERENCES |
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, we have provided further evidence that under near-target viewing conditions (20 cm) at 0.5 Hz, PVP, EH, and BT cells all exhibit predominantly motorlike response properties during translation. In contrast, for the RVOR this is true only for BT cells. We have also shown here that during far-target viewing (80 cm), this result did not always hold true. Not all type II PVP and i-EH neurons exhibited purely motorlike responses during translation, suggesting that under far-target conditions it is possible to observe the contribution of a small, more sensory-related response component in the activities of these cell types (Figs. 7 and 8). ; King et al. 2003), none of the type I PVP and few of the c-EH cells modulated their firing rates during low-frequency translation while animals suppressed the TVOR. In contrast, approximately half of the type II PVP and i-EH neurons, both of which increase their firing rates with ipsilateral eye movement (i.e., they are both Eye-ipsi cells), modulated their firing rates during TVOR cancellation. Therefore the present results support the notion that Eye-ipsi and Eye-contra neurons may have distinct roles in the generation of the TVOR (Angelaki et al. 2001). In the following, we expand on each of these results in reverse order, that is, by first discussing the linear superposition hypothesis and the implications for the dependency of response properties on viewing distance. We will then address how these observations relate to where and how the sensorimotor transformations for the TVOR take place.
Linear superposition hypothesis
Several studies in the past have investigated the question of a linear superposition of signals for the RVOR (Chubb et al. 1984; Cullen and McCrea 1993; King et al. 1976; Tomlinson and Robinson 1984). Early investigations of vertical PVP neurons suggested that their responses during RVOR cancellation were similar to those during compensatory eye movement in the dark (King et al. 1976; Tomlinson and Robinson 1984). At approximately the same time, Chubb et al. (1984) reported that the responses of vertical PVP neurons during the RVOR were best explained by a linear addition of the eye and head movement signals computed from smooth pursuit and RVOR cancellation data. Notably, however, a few years later, Cullen and McCrea (1993) found that horizontal PVP firing rates during RVOR cancellation were lower than those observed during rotation in the dark after the estimated contribution of eye position signals was subtracted out. Similarly, Scudder and Fuchs (1992) reported that stable-gaze PVP responses were not well predicted by their estimated head velocity sensitivities during RVOR cancellation and the estimated motor-related (i.e., eye position and/or velocity) components of their activities during pursuit. In the case of EH cells an earlier study showed that the responses of these cells were poorly correlated with the response that would have been predicted from the vectorial sum of their eye velocity sensitivity during smooth pursuit and their RVOR cancellation responses (Cullen et al. 1993). However, more recently, Roy and Cullen (2003) reported linear summation for EH cells when higher-order models of cell firing rates were used.
In these previous studies, estimates of the degree to which different signals contribute to a cell's response have typically been made by parsing out cell firing rates according to their estimated eye movement and/or head movement sensitivities. However, there have been discrepancies in the conclusions reached regarding linear summation, likely because these sensitivity values were often isolated during different experimental paradigms and the analyses relied on different simplified model descriptions of the signal contributions to cell firing rates. Our approach differs from approaches used in previous studies in that we avoid making assumptions with respect to appropriate models for sensory- versus motor-related responses. Specifically, we do not decompose neural firing rates into eye position, eye velocity, and/or head velocity components but instead have used a simple mathematical logic that relates neural response modulation to the respective known sensory contributions, i.e., rotational or translational motion and target motion (see APPENDIX). We have also tried to eliminate the possibility of potential differences in amplitude-related nonlinearities by adjusting the motion magnitudes during rotation and translation such that the amplitudes of the evoked eye movements were similar to those elicited during pursuit. In addition to testing the predictions of the linear superposition hypothesis in a reasonably assumption- and model-free manner, we were also interested in the question of whether viewing distance had an effect on linearity.
When considering all cell types together, our analyses showed that the linear superposition hypothesis held true for both the RVOR and the TVOR for a far (80 cm), although not for a near (20 cm), target. This difference was particularly strong for the TVOR, as illustrated by the fact that linear regression slopes were significantly lower than unity, suggesting that stable gaze responses were smaller than what would have been expected based on the linear superposition hypothesis (Table 3). There are at least two possible explanations for the apparent breakdown of linearity under near-viewing conditions. First, it could be that there are nonlinear aspects of signal processing related to cancellation, particularly during near-target viewing. For example, in addition to reflex scaling with viewing distance being dependent on current viewing location it could be that this scaling depends on the current task context with a scaling of sensory signals being less during cancellation than when a movement is required to stabilize a world-fixed target. However, if true, one might expect the linear superposition hypothesis to underestimate rather than overestimate actual stable gaze responses, as observed here. Alternatively this observation could reflect the presence of nonlinearities in the premotor circuitry related to the neural mechanisms underlying viewing-distance–dependent gain changes (Khojasth-Lakelayeh and Galiana 2003; also see Green 2000). For example, as recently proposed by Khojasth-Lakelayeh and Galiana (2003), particular cell types may engage in nonlinear summation of incoming activity with sensitivities that vary as a function of current ocular set point.
Our results also showed that the firing rates of type I PVP neurons during rotation under stable gaze conditions (for both the 20- and 80-cm target distances) were lower than those predicted based on a linear summation of cell responses during pursuit and RVOR cancellation. This finding seems at variance with that of Cullen and McCrea (1993), who reported that RVOR cancellation responses were lower than the respective RVOR modulation in the dark after correction for the estimated eye position sensitivity of the cell. This observation was used to suggest evidence for a parametric modulation of rotation signals within the VOR circuitry. The present results are not consistent with such a conclusion because a parametrically reduced RVOR cancellation response would have resulted in an underestimation of stable gaze responses, whereas the opposite was observed here. We believe that the different analysis methods, and in particular the failure to account appropriately for the full eye-movement–or motor-related signal contribution to the cells in the Cullen and McCrea (1993) analysis (i.e., signals components related to the kinematic parameters of eye movement other than simply eye position) are responsible for the differences in the conclusions reached in the two studies. This is further suggested by recent investigations of EH cell activities using higher-order models (Roy and Cullen 2003).
Response parameters for different vergence angles
A common property for all cell types was that response phase did not change for far- versus near-viewing conditions. In contrast, we found neural response gains to differ with viewing distance and that this difference depended on both cell type and the motion condition (rotation or translation). For example, during RVOR cancellation, response gains (expressed relative to the sensory stimulus) were slightly smaller for a near versus far target. A similar small difference has also been reported by Chen-Huang and McCrea (1999a). If indeed viewing-location–related changes in reflex behavior are achieved by central nonlinearities that change the dynamic characteristics of the premotor system as a function of fixation location, as recently suggested by Khojasth-Lakelayeh and Galiana (2003) (also see Green 2000), this might provide one explanation for the smaller RVOR cancellation gains. For TVOR cancellation, only EH cells exhibited a dependency on viewing distance, with near-target responses being larger than far-target responses. Similar results have also been reported for EH cells during eccentric rotation by McConville et al. (1996). Interestingly, type II PVP neurons, the only other cell type that modulates during TVOR cancellation, did not change their response amplitude for far- versus near-target viewing. Because this neuron type has not been studied in previous eccentric rotation studies, no comparisons are currently possible.
During the VOR while fixating a world-fixed target, we compared the amplitude of modulation for far and near targets relative to the amplitude of the horizontal eye velocity evoked. We found that all cell types scaled their firing rates with distance. However, type II PVP neurons and i-EH cells did not scale their amplitude of modulation as much as necessary to generate the eye movement. These results suggest that these neurons carry, in addition to an eye-movement–related motor signal, an additional component that is not scaled as much as required by vergence angle. The fact that this difference was correlated with the cell's peak modulation during TVOR cancellation (Fig. 7) suggests that a sensory vestibular signal that does not scale with vergence as much as the eye movement might be present in the responses of these cells. A viewing distance–independent component was also present in the activities of these neurons during high-frequency (4 Hz) translation in the absence of visual feedback (Meng and Angelaki 2003).
Sensorimotor transformations in the TVOR
The present results further support our previous conclusion (Angelaki et al. 2001) that, at least at 0.5 Hz, the activities of all cell types are dominated by "motorlike " signals during translation under near-viewing conditions. In addition, the present results also show that this property does not hold true for type II PVP and i-EH cells under far-viewing conditions where a small but significant sensory contribution can be observed, presumably because of the proportionately smaller motor-related signal contribution (i.e., smaller behavioral responses and therefore a smaller motor-related contribution to central activities). The sensorimotor processing in the TVOR continues to remain a challenge. This is by no means surprising, given the computational complexities that underlie the generation of these responses; these include the temporal processing from linear acceleration to motoneuron firing rates, the scaling by viewing distance and eye position, and the premotor processing necessary to compute a neural estimate of translational motion (for a review see Angelaki 2004). Given the multiple computational steps necessary, and the very weak mono- and disynaptic neuroanatomical projections from utricular afferents to abducens and medial rectus motoneurons (Imagawa et al. 1995; Schwindt et al. 1973; Uchino et al. 1994, 1996, 1997), it remains likely that polysynaptic pathways represent the main signal flow for the TVOR. Eye-contra neurons (including type I PVP, BT, and c-EH cells), all of which exhibit "motorlike " responses during translation, still remain likely candidates for providing the bulk of TVOR signals to motoneurons just as in the case of the RVOR (Green et al. 2004; Meng and Angelaki 2003). But how do translation-selective signals with the appropriate dynamic characteristics get to these neurons? At present, there is no clear answer to this question. Utricular pathways to premotor cells could potentially involve indirect pathways by eye-ipsi–sensitive neuron types (Angelaki et al. 2001), pathways through the nodulus and fastigial nuclei (Angelaki et al. 2004; Newlands et al. 2003), and/or the cerebellar floculus/ventral paraflocculus (Baloh et al. 1995; Crane et al. 2000; Snyder and King 1996). These questions remain important challenges that await future experimentation.
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APPENDIX |
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TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONAPPENDIXGRANTSACKNOWLEDGMENTSREFERENCES |
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(s), and to the target velocity stimulus, 
(s), then we can write
 |
(s) = –(s). Thus
 |
 |
(s) 
–(s), because the eyes are displaced from the center of rotation of the head, such that the target both rotates and translates relative to the frontal eye plane. In this case, target velocity can be approximated as
 |
). Accordingly
 |
 |
(s)] is equivalent to the sum/difference (depending on choice of signs) of the cell's sensitivity during head-fixed target stabilization A(s) and its sensitivity to the target stimulus T(s), after scaling as a function of viewing distance. If the eyes track the target ideally, then 
(s) = (s), and we can assume that the neuron's sensitivity during pursuit expressed relative to eye velocity is a good approximation of B(s).
For translational motion, if we again assume that the cell's firing rate during world-fixed target stabilization reflects a linear summation of neural responses to the linear velocity stimulus 
(s) and to the motion of the target relative to the eyes (s), the cell's firing rate FR(s) can be described as
 |
During translation the target moves linearly (in cm/s) relative to the head, such that its motion relative to the eye in units of deg/s can be expressed as
 |
During space-fixed target stabilization, lin(s) = –(s). Accordingly
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GRANTS |
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TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONAPPENDIXGRANTSACKNOWLEDGMENTSREFERENCES |
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ACKNOWLEDGMENTS |
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TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONAPPENDIXGRANTSACKNOWLEDGMENTSREFERENCES |
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FOOTNOTES |
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Address for reprint requests and other correspondence: D. Angelaki, Dept. of Anatomy and Neurobiology, Box 8108, Washington University School of Medicine, 660 South Euclid Avenue, St. Louis, MO 63110 (E-mail: angelaki{at}pcg.wustl.edu)
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REFERENCES |
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