Spatio-temporal Tuning of Optic Flow Inputs to the Vestibulocerebellum in Pigeons: Differences between Mossy and Climbing Fibre Pathways

The pretectum, accessory optic system (AOS) and the vestibulocerebellum (VbC) have been implicated in the analysis of optic flow and generation of the optokinetic response. Recently, using drifting sine-wave gratings as stimuli, it has been shown that pretectal and AOS neurons exhibit spatio-temporal tuning. In this respect there are two groups: fast neurons, which prefer low spatial frequency (SF) and high temporal frequency (TF) gratings, and slow neurons, which prefer high SF low TF gratings. In pigeons, there are two pathways from the pretectum and AOS to the VbC: a climbing fibre (CF) pathway to Purkinje cells (P-cells) via the inferior olive and a direct mossy fibre (MF) pathway to the granular layer (GL). In the present study we assessed spatio-temporal tuning in the VbC of ketamine-anaesthetized pigeons using standard extracellular techniques. Recordings were made from 17 optic flow sensitive units in the GL, presumably granule cells or MF rosettes, and the complex spike activity (CSA) of 39 P-cells, which reflects CF input. Based on spatio-temporal tuning to gratings moving in the preferred direction, 8 GL units were classified as fast units, with a primary response to low SF high TF gratings (mean = 0.13cpd/8.24Hz), whereas 9 were slow units preferring high SF low TF gratings (mean = 0.68cpd/0.30Hz). CSA was almost exclusively tuned to slow gratings (mean = 0.67cpd/0.35Hz). We conclude that MF input to the VbC is from both fast and slow cells in the AOS and pretectum, whereas the CF input is primarily tuned to slow gratings. Spatio-temporal tuning in the Vestibulocerebellum JN-00815-2004.R1 3 Self-motion through an environment consisting of stationary objects and surfaces results in distinct patterns of visual motion across the entire retina. These characteristic patterns are referred to as ‘optic flow’ or ‘flowfields’ (Gibson 1954). The analysis of optic flow is important for the generation of optokinetic responses, such as optokinetic nystagmus and the opto-collic reflex, which facilitate gaze stabilization (for review see Ilg 1997; see also Robinson 1981; Carpenter 1988; birds, Gioanni et al. 1981, 1983a,b; Gioanni 1988). Gaze stabilization is important to prevent the degradation of visual acuity (Westheimer and McKee 1975) and enhance velocity discrimination (Nakayama 1981). Numerous studies, utilizing micro-stimulation, lesion, and electrophysiological methods, have implicated nuclei in the accessory optic system (AOS) and pretectum in the analysis of optic flow and the generation of optokinetic responses (for reviews see Simpson 1984; Simpson et al. 1988; Grasse and Cynader 1990). The AOS and pretectum are highly conserved, and homologous structures have been identified in mammalian and avian species (Fite 1985; McKenna and Wallman 1985a; Weber 1985). The mammalian AOS consists of the medial, lateral, and dorsal terminal nuclei (MTN, LTN, and DTN, respectively), which are equivalent to the nucleus of the basal optic root (nBOR) in birds. Likewise the pretectal nucleus of the optic tract (NOT) of mammals is equivalent to the avian pretectal nucleus lentiformis mesencephali (LM) (for reviews, see Simpson 1984; Simpson et al. 1988). Physiological recordings from the AOS and pretectum from numerous species have shown that neurons in these nuclei have large, contralateral receptive fields and exhibit direction-selectivity to large-field moving stimuli rich in visual texture (NOT: Collewijn 1975a,b; Hoffman and Schoppmann 1975, 1981; Hoffmann et al. 1988; Spatio-temporal tuning in the Vestibulocerebellum JN-00815-2004.R1 4 Hoffmann and Distler 1989; Volchan et al. 1989; Klauer et al. 1990; Mustari and Fuchs 1990; Distler and Hoffmann 1993; Ilg and Hoffmann 1996; Yakushin et al. 2000: LM: Katte and Hoffmann 1980; McKenna and Wallman 1981, 1985b; Winterson and Brauth 1985; Fite et al. 1989; Fan et al. 1995; Wylie and Frost 1996: MTN/LTN; Simpson et al. 1979; Grasse and Cynader 1982; Grasse et al. 1984; Soodak and Simpson, 1988; nBOR, Burns and Wallman 1981; Morgan and Frost 1981; Gioanni et al. 1984; Wylie and Frost 1990; Rosenberg and Ariel 1990; Kogo et al. 1998, 2002; Ariel and Kogo 2001). Recent neurophysiological studies that used largefield sinusoidal gratings as stimuli showed that pretectal and AOS neurons show spatio-temporal tuning. This was first shown in the wallaby NOT (Ibbotson et al. 1994), and subsequently in the pigeon nBOR and LM (Wolf-Oberhollenzer and Kirschfeld 1994; Wylie and Crowder 2000; Crowder and Wylie 2001; Crowder et al. 2003a,b). These studies found that pretectal and AOS neurons fall into two groups based on a the location of the peak (maximal) response in the spatiotemporal domain: slow cells were maximally sensitive to motion at low temporal frequency (TF < 1 Hz) and high spatial frequency (SF > 0.25 cycles per degree, cpd), whereas fast cells were maximally sensitive to high TF (> 1 Hz) and low SF (< 0.25 cpd) sine wave gratings. Figure 1A depicts the fast and slow regions in the spatio-temporal domain. Ibbotson and Price (2001) noted that the spatio-temporal preferences of the fast and slow units in the pretectum of wallabies and pigeons were remarkably similar. We must caution that the fast/slow distinction is not so simplistic. It is not uncommon for a slow neuron to show a secondary peak in the fast region, or a fast neuron to show a secondary peak in the slow region (Ibbotson et al. 1994; Wylie and Crowder 2000; Spatio-temporal tuning in the Vestibulocerebellum JN-00815-2004.R1 5 Crowder and Wylie 2001; Crowder et al. 2003a). Such neurons likely receive inputs from fast and slow subunits. The AOS and pretectum provide input to the optic flow sensitive neurons in the vestibulocerebellum (VbC) (for reviews see Simpson 1984; Simpson et al. 1988; birds, Clarke 1977; Brecha et al. 1980). In birds, there are two inputs from the LM and nBOR to the VbC: an indirect climbing fibre (CF) pathway through the medial column of the inferior olive (mcIO; Clarke 1977; Brecha et al. 1980; Gamlin and Cohen 1988; Arends and Voogd 1989; Lau et al. 1998; Wylie et al. 1999; Crowder et al. 2000; Wylie 2001; Winship and Wylie 2001, 2003) and a direct mossy fibre (MF) pathway that is mainly restricted to folium IXcd (Brauth and Karten 1977; Clarke 1977; Brecha and Karten 1979; Brecha et al. 1980; Gamlin and Cohen 1988; Wylie and Linkenhoker 1996; Wylie et al. 1997). The CF pathway to the VbC exists in mammals (for reviews see Simpson 1984; Simpson et al. 1988). The complex spike activity (CSA) of VbC Purkinje cells, which reflects CF input (Thach 1967), is direction-selective for particular patterns of optic flow (Simpson et al. 1981; Graf et al. 1988; Kano et al. 1990; Kusonoki et al. 1990; Wylie and Frost 1993, 1999; Wylie et al. 1998). The MF pathway has also been reported in turtles and fish (Finger and Karten 1978; Reiner and Karten 1978; Fan et al. 1993), but not in several mammalian species (Kawasaki and Sato 1980; Blanks et al. 1983; Giolli et al. 1984). Winfield et al. (1978) reported a direct MF pathway from the MTN to the VbC in the chinchilla, although this finding has been contested (Giolli et al. 1984). In this study, in effort to determine whether the fast or slow cells in the AOS and pretectum feed the MF and CF pathways to the VbC, we recorded the responses of units in the granular Spatio-temporal tuning in the Vestibulocerebellum JN-00815-2004.R1 6 layer of folium IXcd and the CSA of VbC Purkinje cells to sine wave gratings of varying TF and SF. Methods Surgery and Extracellular Recording The methods reported herein conform to the guidelines established by the Canadian Council on Animal Care and approved by the Biosciences Animal Care and Policy Committee at the University of Alberta. Silver King pigeons (obtained from a local supplier) were anaesthetized using an intramuscular ketamine (65mg/kg) and xylazine (8mg/kg) mixture. Depth of anaesthesia was monitored via toe pinch and supplemental doses were administered as necessary. Body temperature was maintained via a thermal probe and heating pad (Fine Science Tools). The pigeons were placed in a stereotaxic apparatus with ear bars and beak adapter such that the orientation of the head conformed to the atlas of Karten and Hodos (1967). Sufficient bone and dura was removed to allow access to the VbC. Glass micropipettes with tip diameters of 4-5μm filled with 2M NaCl were used for the extracellular recordings. Micropipettes were advanced through the VbC via an hydraulic microdrive (Frederick Haer). The extracellular signal was amplified, filtered, and fed to a data acquisition unit (Cambridge Electronic Designs (CED) 1401plus). The data was analysed off-line using Spike2 for Windows (CED). This included spike sorting and the construction of peri-stimulus time histograms (PSTHs). Spatio-temporal tuning in the Vestibulocerebellum JN-00815-2004.R1 7 Stimuli and Stimulus Presentation The procedures for stimulus construction and presentation were essentially identical to those described in previous studies from this lab that examined the spatiotemporal tuning of nBOR and LM units (Wylie and Crowder 2000; Crowder et al. 2003a,b, 2004). All stimuli were generated by a VSGThree (Cambridge Research Systems) graphics computer and back-projected (InFocus LP750) onto a screen measuring 90°×75° (width × height) that was positioned in the most responsive area of the receptive field. Upon identification and isolation of the CSA of P-cells or a GL unit, the direction preference and approximate receptive field boundaries were qualitatively determined by moving a large (90o X 90o) hand-held visual stimulus, consisting of black bars, squiggles, and dots on a white background, throughout the visual field. Subsequently, spatio-temporal tuning was quantified using 36-42 combinations of sinewave gratings of varying SF (0.03-2 cycles per degree, cpd) and TF (0.03-24 cycles per second, Hz) moving in the preferred and anti-preferred direction for that unit. The contrast of the sine wave gratings was 0.95 [(LuminanceMAXLuminanceMIN)/(LuminanceMAX+LuminanceMIN)] and the mean luminance was 65cd/m. The refresh rate was 80Hz. Each sweep for a particular SF/TF combination consisted of 4 seconds of motion in the preferred direction, a 3 second pause, 4 seconds of motion in the anti-preferred direction, followed by a 4 second pause. During the pauses the stimulus was a uniform gray of the standard mean luminance. Firing rates were averaged over 2 to 12 sweeps, and mean firing rates for motion in the preferred and anti-preferred direction were computed over the entire 4 second motion segment. For CSA, the firing rate is typically very low, thus we tried to obtain as many sweeps as possible (up to 12) Spatio-temporal tuning in the Vestibulocerebellum JN-00815-2004.R1 8 for each SF/TF combination. This was generally not a problem as the units are not difficult to hold for long periods of time. For GL units, the firing rate is higher (at least 10-fold), but the units were extremely difficult to isolate and hold for long durations. We required a minimum of 2 sweeps, assuming the unit was well isolated. Quantification and Illustration of Spatio-Temporal Tuning To graphically illustrate tuning in the spatio-temporal domain, for each unit a contour plot of the mean firing rate as a function of SF and TF was made using Sigma Plot. TF and SF were plotted on the ordinate and abscissa, respectively, and firing rate (minus spontaneous rate) was plotted on the z-axis. The location of maximal excitation was referred to as the primary peak of the contour plot. A peak of lesser magnitude was termed a secondary peak. Concluding that a contour plot contained a single peak vs. two peaks was somewhat subjective (see contour plots in Figures 1B, 2 and 3). To be classified as a secondary peak, it had to be clearly separable from the background activity and distinct from the primary peak by visual inspection, and a consistent response of greater than 40% the magnitude of the primary peak was necessary. (The contour plots shown in Figures 1B and 3C are representative in this regard). To identify the precise location of the primary and secondary peaks, each peak was fit to a 2-D Gaussian function using a slightly modified version of the method of Perrone and Thiele (2001): G(u,ω) = {exp[-(u ́)/σ x ]} X {exp[-(ω ́)/ σ y ]} + P where u ́ = (u – x) cos θ + (ω – y) sin θ Spatio-temporal tuning in the Vestibulocerebellum JN-00815-2004.R1 9 ω ́ = (u – x) sin θ + (ω – y) cos θ where u is ln (SF), ω is ln (TF), θ is the angle of the Gaussian, (x,y) is the location of the peak of the Gaussian, σ x and σ y are the spread of the Gaussian in the u ́ and ω ́ dimensions, respectively, and P is a constant reflecting the spontaneous activity of the cell. σ x, σ y, x, y, θ, and P were optimized to minimize the sum of the mean error between the actual and G values using the solver function in Microsoft Excel. Not all of the data points from the contour plots were necessarily included the Gaussian fits. In cases where there were two peaks in the contour plot, the points corresponding to each peak were fit separately (e.g. see Fig. 3C,D). In addition, for some contour plots with single peaks spurious values distant from the peak were omitted (e.g. Fig. 2A,B and C,D). In order to determine whether the CSA and GL primary peaks were located in the fast or slow regions of the spatio-temporal domain, we first used a hierarchical cluster analysis to divide a group of 118 cells from previous studies of LM and nBOR (Wylie and Crowder 2000; Crowder and Wylie 2001; Crowder et al. 2003a,b) into two groups based on the SF (x) and TF (y) of their primary peaks. (These are plotted in Figure 4C). Post-hoc inspection of the classification showed that the two largest clusters corresponded to fast and slow cells. We then determined a linear discriminant function to discriminate fast from slow cells using the cluster analysis results as a training set. The discriminant function was then used to calculate the posterior probabilities of fast or slow memberships for GL units and the CSA of P-cells recorded in the present study. All analyses were conducted in R (Ihaka & Gentleman 1996). We used the hclust() function from the “stats" library, with the “Ward’s" method, to perform the cluster analysis. The Spatio-temporal tuning in the Vestibulocerebellum JN-00815-2004.R1 10 lda() function of the MASS library (Venables & Ripley 2002) was used for the linear discriminant analysis. Quantification of Velocity Tuning In addition to providing the location of the spatio-temporal peak, the Gaussian function was also used to evaluate velocity tuning (velocity = TF/SF) following the procedure used by Priebe et al. (2003; a variant of a method devised by Levitt et al. (1994). Units showing velocity tuning would have a θ value approaching 45. When plotted on a contour plot, the peak of a unit tuned to velocity is elongated and oriented such that it has a slope of about 1 on log-log axes. This contrasts with a unit that shows “spatio-temporal independence”, i.e. it responds maximally to a given TF irrespective of the SF. Such a unit would have a non-oriented peak in the contour plot (i.e. θ approaching 0 or 90). To evaluate whether a unit showed velocity tuning as opposed to spatiotemporal independence, the primary peak for each unit was fit to a 2-D Gaussian as described above but with θ constrained to either 45 o to provide the velocity-tuned prediction, or to 0/90 to provide the independent prediction. We then computed the partial correlation of the actual response with the velocity or independent prediction using the following equations: Rind = (ri – viv'√((1-rv2)(1-riv2)) Rvel = (rv – iiv'√((1-ri2)(1-riv2)) where Rind and Rvel are the partial correlations of the actual response to the independent and velocity predictions, respectively; ri is equal to the correlation of actual response with Spatio-temporal tuning in the Vestibulocerebellum JN-00815-2004.R1 11 the independent prediction; rv is the correlation of the actual data with the velocity prediction; and riv is the correlation of the two predictions. The statistical significance of Rvel and Rind was calculated by performing a Fisher Z-transform on the correlation coefficients {Zf=1/2 ln[(1+R)/(1-R)]}, and then calculating the difference between these z-scores (Papoulis 1990): zdiff = (Zfv-Zfi)/((1/(Nv-3))+1/(Ni-3))1/2 where Zfv is the Fisher Z-transform for Rvel, Zfi is the Fisher Z-transform for Rind, and Nv=Ni=number of SF/TF combinations used in the best-fit Gaussian. With this statistic, cells were categorized as velocity-tuned if zdiff ≥1.65 and Rvel was significantly greater than 0. Likewise cells were categorized as independent if zdiff≤-1.65) and Rind was significantly greater than 0. Cells not meeting these criteria were termed unclassifiable (1.65>zdiff>-1.65). The conventional criterion probability of 0.1 was used (Crow et al. 1960). This criterion has been justified by the fact that this method is not a true test for statistical significance, but a convenient way to reduce data (see Movshon et al. 1985; Gizzi et al. 1990; Scannell et al. 1996). Histology In some cases dye spots were made at recording sites in the granular layer via iontophoretic injection of pontamine sky blue. At the end of these experiments, animals were given a lethal overdose of sodium pentobarbital (100 mg/kg) and immediately perfused with ice-cold saline followed by 4% paraformaldehyde in phosphate buffer (PB). The brains were extracted and post-fixed (4% paraformaldehyde in PB with 30% sucrose) for 2-12 hours and then placed in 30% sucrose solution in PB for 12-24 hours. Spatio-temporal tuning in the Vestibulocerebellum JN-00815-2004.R1 12 Frozen coronal sections (40 μm thick) through VbC were collected and mounted onto gelatine-coated slides. Sections were counterstained with neutral red and light microscopy was used to localize dye spots. Results We recorded the spatio-temporal tuning of 17 GL units and the CSA of 39 P-cells in VbC from 19 birds in this study. CSA was recorded in the molecular layer of folia IXcd and X, and displayed the characteristic low spontaneous activity of about 1 spikes/s (0.98 ± 0.11 spikes/s; mean ± s.e.m.). Visually-sensitive GL units were extremely difficult to isolate and hold, but were easily distinguished from CSA by a much higher spontaneous rate (26.10 ± 3.68 spikes/s; mean ± s.e.m.). The dye spots made at GL recording sites were all located in the granular layer of folia IXc,d. As expected, in response to the battery of drifting sine wave gratings, CSA and visual GL units showed clear spatio-temporal tuning. Spatio-Temporal Tuning of GL units Consistent with previous studies, only a fraction (less than 10%) of the GL units were modulated by optic flow stimuli (Fan et al. 1993; Waespe et al. 1981). Moreover, consistent with Wylie et al. (1993), we found that the visual GL units had monocular receptive fields in either the ipsilateral (n = 11) or contralateral (n = 6) visual field, and showed directional tuning to largefield stimuli. Different direction preferences (similar to those in LM and nBOR) were observed, but GL units with dissimilar direction selectivity did not have any apparent differences with respect to spatio-temporal tuning. Spatio-temporal tuning in the Vestibulocerebellum JN-00815-2004.R1 13 Figure 1B shows a contour plot illustrating the spatio-temporal tuning of a GL unit. This unit had a primary peak in the fast zone, and a slightly smaller secondary peak in the slow zone. Based on the best-fit Gaussian, the primary peak was localized to SF = 0.10 cpd, TF = 13.47 Hz and the secondary peak was located at SF = 1.0 cpd, TF = 0.28 Hz. PSTHs on the right show the unit’s modulation during stimulation in the preferred and antipreferred direction for gratings of three different SF – TF combinations during a single sweep. The first 4 seconds show response to movement in the preferred direction, followed by a 3 second pause, 4 seconds of motion in the anti-preferred direction, and another 3 second pause. Clear excitation and inhibition to motion in the preferred and anti-preferred direction, respectively, are seen for PSTHs in the primary peak (SF = 0.125 cpd, TF = 16 Hz) and secondary peak (SF = 1 cpd, TF = 0.5 Hz), though this modulation is clearly greater for the primary peak. Considerably less modulation is seen outside these peaks (i.e. SF = 0.25 cpd, TF = 2 Hz). Evident in the PSTHs, the responses included both transient and steady state components. (This was the also the case for CSA). Transients and other temporal factors have been extensively analyzed in previous studies of spatio-temporal tuning in the AOS and pretectum (Ibbotson et al. 1994; Price and Ibbotson 2002; Wolf-Oberhollenzer and Kirschfeld 1994) and will not be analyzed further in this paper. Figure 2 shows the contour plots of the spatio-temporal tuning of two additional GL units. The unit in Fig. 2A showed a single peak in the fast region. Figure 2B shows the plot of the normalized best-fit Gaussian for this unit. The peak was located at SF = 0.06 cpd, TF = 2.03 Hz. Figure 2C,D show the contour plot and normalized best-fit Gaussian, respectively, for a GL unit with a single peak in the slow zone (SF = 1.0 cpd, Spatio-temporal tuning in the Vestibulocerebellum JN-00815-2004.R1 14 TF = 0.03 Hz). Eight (47.1%) GL units had a single peak in the contour plot (as in Fig. 2), whereas 9 of the GL units (52.9%) had secondary peaks in their contour plots (as in Fig. 1B). Secondary peaks were always located in the opposite spatio-temporal domain and had a magnitude, on average, 73.4% the size of the primary peak (range, 43.4 98.5%). Figure 4A plots the locations of the primary peaks of all 17 GL units, as determined from the best-fit Gaussians. As described in the methods, the locations of the peaks were assigned to either the fast or slow regions based on previous data of spatiotemporal tuning of LM and nBOR neurons (Wylie and Crowder 2000; Crowder and Wylie 2001; Crowder et al. 2003a,b). In Figure 4C the primary peaks of nBOR and LM neurons is plotted along with data from the current study. Eight (47.1%) GL units were classified as fast cells (low SFs/high TFs; mean = 0.13cpd/8.24Hz), whereas 9 (52.9%) GL units were slow cells (high SFs/low TFs; mean = 0.68cpd/0.30Hz; see also Table 1). The clustering into fast (white diamonds) and slow (grey diamonds) groups can be clearly seen in Fig. 4A (see also Fig. 4C). Figure 5A and 5B show the normalized average contour plots of spatio-temporal tuning for slow and fast GL units, respectively. These were calculated by normalizing the contour plot of each unit, then averaging across all 9 slow units and 8 fast units. While the slow units clearly respond maximally to the gratings in the slow region, and the fast units clearly respond more to fast gratings, note the influence of the subset of units (9 GL units) that had secondary peaks in the region opposite the primary peak. Five fast units had secondary peaks in the slow zone and 4 slow units had secondary peaks in the fast regions. Spatio-temporal tuning in the Vestibulocerebellum JN-00815-2004.R1 15 Spatio-Temporal Tuning of the CSA of Purkinje Cells Previous studies in pigeons have shown that VbC Purkinje cells have binocular, virtually panoramic receptive fields, and the CSA responds best to optic flow patterns resulting from self-translation or self-rotation along/about a particular axis in 3dimensional space (Wylie and Frost, 1993, 1999; Wylie et al., 1998). Based on the orientation of the preferred axis of rotation/translation, there are two classes of rotation neurons and four-classes of translation neurons. Rotation-sensitive neurons in VbC respond best to optic flow rotating about either the vertical axis (VA) or an axis orientated 45 contralateral to the midline in the horizontal plane (45 c azimuth). Translation-sensitive neurons respond best to translational optic flow moving upward or downward along the VA, forward along an axis at 45 c azimuth, or backward along an axis orientated at 45 ipsilateral azimuth. In the present study, all six classes were represented in the sample of 39 units (24 rotation neurons, and 15 translation neurons). The different groups did not differ with respect to spatio-temporal tuning, thus they have all been grouped together. Figure 3 shows representative contour plots and best-fit Gaussians for the CSA of 2 Purkinje cells. In Figure 3A,B, a cell with a single peak in the slow domain of the contour plot is illustrated. From the best-fit Gaussian, the peak was located at SF = 0.66 cpd, TF = 0.18 Hz. In Figure 3C,D, a cell with a primary peak in the slow zone and a secondary peak in the fast zone is shown. From the best-fit Gaussian the primary peak was located at 0.77cpd/0.10 Hz and the secondary peak was located at 0.11 cpd/18.0 Hz. Of the 39 CSA recordings, 11 (28.2%) of the contour plots showed a single peak, whereas 28 (71.8%) showed a secondary peak as well. On average, the secondary peak Spatio-temporal tuning in the Vestibulocerebellum JN-00815-2004.R1 16 was 69.8% (range, 51.2 – 97.9%) the size of the primary peak. For 2 of these units the magnitude of the secondary peak was greater than 90% of the primary peak, making the assignment of primary and secondary peak more problematic. Figure 4B plots the locations of the primary peaks of the CSA of 39 P-cells in this study. These are also plotted in Figure 4C along with the GL units and the nBOR and LM data from previous studies (Wylie and Crowder 2000; Crowder and Wylie 2001; Crowder et al. 2003a,b). Using the linear discriminate function described previously, 38 (97.4%) of the CSA units were classified as slow units (mean = 0.67cpd/0.35Hz; grey hexagons in 4A), while one unit was classified as a fast unit (white hexagon in Fig. 4C, primary peak at 0.10cpd/0.55Hz). This fast unit had a secondary peak of approximately equal magnitude (96.5%) located in the slow zone (0.42cpd/0.43Hz). Twenty-seven of the 38 slow units had secondary peaks, and 25 of these were in the fast region. Figure 5C shows the normalized average contour plots of spatio-temporal tuning for the CSA of all 39 P-cells. The average plots clearly illustrate the dominance of slow spatio-temporal tuning in CSA, though the influence of secondary peaks in a subset of CSA (71.8%) is apparent with the smaller peak in the fast region. Note the similarity of the contour plots for the slow GL units and the CSA. Note also that the peaks for the slow GL units and CSA are sharper than that of the fast units, reflecting the fact that for the fast units the primary peaks are not as tightly clustered (Fig. 4A). Velocity-Like Tuning In Figure 3A, note that peak for this unit is elongated, and oriented such that it has a slope of about 1 on a log-log axis. This suggests that the cell shows velocity tuning Spatio-temporal tuning in the Vestibulocerebellum JN-00815-2004.R1 17 (velocity = TF/SF) to about 0.25 /sec (see diagonal scale on the contour plot). As the response is not independent of SF, this has been more appropriately termed velocity-like tuning (Zanker et al. 1999; Crowder et al. 2003a). In the present study, many of the peaks that were in the slow zone were oriented such that they approached velocity-like tuning (e.g. Fig. 1B, 2C, 3A). As described in the methods, following Priebe et al. (2003), neurons were classified as velocity tuned, independent, or unclassified based on the partial correlations of the actual data for each unit to velocity and independent predictions. Using the criteria described in the methods, the CSA of 10 (26.3%) slow Pcells showed velocity-like tuning, 5 (13.2%) showed independence, and 23 (60.5%) fell into the unclassified group. The single fast CSA was also unclassified. For the 8 fast GL units, 4 (50%) showed SF/TF independence, 1(12.5%) was velocity-tuned and 3 (37.5%) were in the unclassified group. For the 9 slow GL units, all fell into the unclassified group. Figure 6 shows a scatter plot of Rvel vs. Rind for all units. For convenience, the black solid lines have been added to provide an approximation of the divisions between velocity-tuned, unclassified, and independent regions. This line represents the statistical criteria separating these groups based on 24 points in the best-fit Gaussian. (The actual number of points in the best-fit Gaussians ranged from 12-42 (mean = 24), hence this line is an approximation between the divisions). Note the CSA that showed velocity tuning in the upper left (black hexagons) and the fast GL units that showed SF/TF-independence in the bottom right (white diamonds with black borders). Spatio-temporal tuning in the Vestibulocerebellum JN-00815-2004.R1 18 Discussion In this study we examined the spatio-temporal tuning of the CSA of VbC Purkinje cells and GL units in folium IXcd of the VbC in response to largefield sine-wave gratings of varying SF and TF drifting in the preferred direction. We found that these units were tuned in the spatio-temporal domain. GL units could be classified into two groups: fast units showed a maximal response to low SF/high TF gratings, whereas slow units showed a maximal response to high SF/low TF. In contrast all but one of the CSA recordings was classified as a slow unit. Comparison with Spatio-Temporal Tuning in the Pretectum and AOS Spatio-temporal tuning in the optokinetic system was originally demonstrated by Ibbotson et al. (1994), who recorded from the pretectum in wallabies. Subsequently, Wylie and Crowder (2000) showed strikingly similar results in the pretectal nucleus LM and the nBOR of the AOS in pigeons (Wolf-Oberhollenzer and Kirschfeld 1994; Crowder and Wylie 2001; Crowder et al. 2003a,b). The results from these previous studies closely parallel those in this study. Like CSA and GL units, LM and nBOR neurons had a primary peak located in either the fast or slow zone. In LM, fast units were more common than slow units (66% vs. 34%), but in nBOR slow units were more common than fast units (75% vs. 25%). In the present study, we found that GL units included fast and slow units, whereas CSA was clearly tuned to slow gratings. Table 1 summarizes the mean preferred SF/TF combinations from studies of LM, nBOR, and the VbC of pigeons (Wylie and Crowder 2000; Crowder and Wylie 2001; Crowder et al. 2003a; present study). The average preferred SF/TF combinations for the slow units in Spatio-temporal tuning in the Vestibulocerebellum JN-00815-2004.R1 19 LM and nBOR were 0.67cpd/0.55Hz and 0.53cpd/0.30Hz, respectively (Wylie and Crowder 2000; Crowder and Wylie 2001; Crowder et al. 2003a), which is quite close to the values for the slow GL units (0.68cpd/0.30Hz) and CSA (0.67cpd/0.35Hz) in the present study. Likewise, the average preferred SF/TF combinations for the fast units in LM and nBOR were 0.10cpd/2.49Hz and 0.08cpd/2.84Hz, respectively (Wylie and Crowder 2000; Crowder et al. 2003a), which is close to the values for the fast GL units (0.13cpd/8.24Hz) from the present study. In Fig. 4C, data from the current study of the VbC and previous studies of spatio-temporal tuning in LM and nBOR is collapsed onto a single plot: black hexagons show the primary peak locations in the spatio-temporal domain of recordings of the CSA of P-cells in VbC (n = 39; present study); black diamonds show primary peak locations for GL units in VbC (n = 17; present study); grey triangles show the primary peaks of LM units (n = 64; Wylie and Crowder 2000); and the primary peaks of units from nBOR (n = 55) are represented by grey squares (Crowder and Wylie 2001; Crowder et al. 2003a). The fast and slow populations form distinct clusters. The distribution of primary peaks within the fast and slow regions is similar for LM, nBOR, and VbC units. In the present study we also found that the many of the contour plots of GL unit responses and CSA often included secondary peaks, almost always in the opposite region. This was also the case for many nBOR and LM neurons (Wylie and Crowder 2000; Crowder and Wylie 2001; Crowder et al. 2003a), and some NOT neurons in wallabies (Ibbotson et al. 1994). Spatio-temporal tuning in the Vestibulocerebellum JN-00815-2004.R1 20 Projections of Fast and Slow Neurons in the AOS and Pretectum to the VbC Figure 7 shows a cartoon of the projections of the nBOR and LM to the VbC. There is an indirect CF pathway through the medial column of the inferior olive (mcIO; Clarke 1977; Brecha et al. 1980; Gamlin and Cohen 1988; Arends and Voogd 1989; Lau et al. 1998; Wylie et al. 1999; Crowder et al. 2000; Wylie 2001; Winship and Wylie 2001, 2003) and a direct MF pathway that is restricted to folium IXcd (Brauth and Karten 1977; Clarke 1977; Brecha and Karten 1979; Brecha et al. 1980; Gamlin and Cohen 1988; Wylie and Linkenhoker 1996; Wylie et al. 1997). Our results suggest that the slow neurons in LM and nBOR make up the primary input to the CF pathway, while the MF pathway receives major inputs from fast and slow neurons in LM and nBOR. This is not to say that the CSA does not respond to fast gratings. Clearly many of the units have a secondary peaks in the fast region of the contour plot (Fig. 3C; see also Fig. 5C), as do many slow neurons in LM and nBOR (Wylie and Crowder 2000; Crowder and Wylie 2001; Crowder et al. 2003a), thus there is clearly an integration of fast and slow information in the CF pathway. Nonetheless we contend that the CF pathway receives input almost exclusively from cells in nBOR and LM that are maximally sensitive to slow gratings. Although the CF pathway from the AOS and pretectum to the VbC exists in all mammals (for reviews see Simpson 1984; Simpson et al. 1988), a direct MF projection from the AOS and pretectum to the VbC has not been identified in mammals, with the possible exception of a controversial MTN-VbC projection in the chinchilla (Winfield et al. 1978). However, there may be several indirect MF pathways from the pretectum and AOS to the VbC. Most of the MF input to the VbC arises in the vestibular nuclei and the Spatio-temporal tuning in the Vestibulocerebellum JN-00815-2004.R1 21 prepositus hypoglossi (Voogd et al. 1996; Ruigrok 2003) but there are also projections originating in the reticular formation, the raphe nuclei, and neurons located within and around the medial longitudinal fasciculus (Blanks et al. 1983; Sato et al. 1983; Gerrits et al. 1984; Langer et al. 1985; Ruigrok 2003; for review see Voogd et al. 1996). The NOT and the AOS project to many of these structures, including the vestibular nuclei, the medial and dorsolateral nuclei of the basilar pontine complex, the mesencephalic reticular formation, the prepositus hypoglossi and the nucleus reticularis tegmenti pontis (Itoh 1977; Terasawa et al. 1979; Cazin et al. 1982; Holstege and Collewijn 1982; Giolli et al. 1984, 1985, 1988; Torigoe et al. 1986a,b; for review see Simpson et al. 1988). Thus, it is possible that optic flow information reaches the VbC from the AOS and pretectum via an indirect MF pathway in mammalian species. It would be interesting to see if this information arises from fast and/or slow neurons. Function of Fast and Slow Neurons Ibbotson et al. (1994) described the potential role of the slow and fast NOT neurons in the generation and maintenance of OKN. The fast units would respond maximally when retinal slip velocity (RSV) is high, whereas the slow neurons would be involved when the RSV is low, such as providing the error signal when the OKN gain is high (see Ibbotson et al. (1994) and Wylie and Crowder (2000) for detailed discussions). From the findings of the present study it follows that the MF inputs are involved when RSV is high and low, but the CF inputs are primarily involved when RSV is low. However, again we caution against such a stark simplification: the contour plots of many Spatio-temporal tuning in the Vestibulocerebellum JN-00815-2004.R1 22 of the CSA recordings showed a secondary peak in the fast zone. Thus, the CSA of these Purkinje cells would not be silent to fast optic flow stimuli. Velocity-Like Tuning vs. Spatio-Temporal Independence In the present study we found that many of the peaks in the slow zone were oriented such that they had a slope approximating one on log-log axes. That is, these units showed a peak response to a particular stimulus velocity (TF/SF), irrespective of the SF used. As the response maxima were dependent upon SF, we (Crowder et al. 2003a) have previously called this velocity-like tuning. (True velocity tuning would appear as a flattened ridge in the contour plot). Crowder et al. (2003) concluded that the majority of the slow units in LM and nBOR showed velocity-like tuning whereas the fast units were TF-tuned (i.e. SF/TF independent). However, Crowder et al. (2003a) did not provide a quantitative test in this regard, and one can infer from Priebe et al. (2003) that there is a danger in overstating the degree of velocity-like tuning. Thus, we adopted the partial correlation outlined by Priebe et al. (2003) to compare velocity-tuned and SF/TFindependent predictions. The tendency of slow CSA to show velocity tuning is apparent in Figure 6, but only 26% showed significant velocity tuning compared to the independence prediction. 13.1% showed significant SF/TF-independence but most (60.5%) fell into the unclassified group, i.e. somewhere between velocity tuning and SFTF independence. Consistent with Crowder et al. (2003a), SF/TF-independence was more common with the fast GL units (50%). Following Zanker et al. (1999), Crowder et al. (2003a) argued that velocity-like tuning reflects the properties of an ‘unbalanced’ Reichardt detector. Generally speaking, the more unbalanced the detector, the more the Spatio-temporal tuning in the Vestibulocerebellum JN-00815-2004.R1 23 response approaches velocity tuning. Thus, with respect to velocity tuning vs. SF/TFindependence, the responses we observed suggest that the input units might vary with respect to the degree to which the detector is balanced. GL units: Granule Cells or Mossy Fibre Rosettes? There is precious little data regarding the physiological properties of MF inputs to the granule cell layer, presumably because these cells are small and difficult to isolate and hold. In fact, it is unclear whether the GL units recorded in the present study represent MF rosettes or granule cells. This is not necessarily a critical issue for the present study, as recordings from either would allow us to determine if fast or slow units in the pretectum and AOS feed the MF pathway to the VbC. Fan et al. (1993) and Ariel and Fan (1993) recorded the visual responses of units in the GL in the turtle cerebellum using an in vitro preparation with eyes attached. Similar to pigeons (present study, Wylie et al. 1993), these units exhibited direction selectivity to large-field patterns but only respond to stimulation of the contralateral eye. 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Control of ocular pursuit.Exp Brain Res 131: 433-447, 2000. Zanker JM, Srinivasan MV, and Egelhaaf M. Speed tuning in elementary motiondetectors of the correlation type. Biol Cybern 80: 109-16, 1999. Spatio-temporal tuning in the VestibulocerebellumJN-00815-2004.R1 37 Figure CaptionsFigure 1: Spatio-temporal tuning in the accessory optic system (AOS), pretectum, andvestibulocerebellum (VbC). In Fig.1A, the approximate spatio-temporal preferences forfast and slow neurons in the mammalian and avian AOS and pretectum are illustrated(Ibbotson et al. 1994; Wylie and Crowder 2000; Crowder and Wylie 2001; Crowder et al.2003a,b; Wolf-Oberhollenzer and Kirschfeld 1994). Fig. 1B shows the contour plot andperi-stimulus time histograms (PSTHs) of spatio-temporal tuning for a granular layer(GL) unit in the VbC. The contour plot shows the firing rate in response to sine wavegratings of varying spatial (abscissa) and temporal (ordinate) frequencies drifting in thepreferred direction for the unit. The plot is shaded such that white represents the SF –TFcombinations resulting in maximal excitation and black indicates minimal excitation.This unit was spatio-temporally tuned with primary peak in the fast zone, and a slightlylesser peak in the slow zone. PSTHs on the right show the unit’s modulation duringstimulation in the preferred (upward) and antipreferred (downward) direction for gratingsof three different SF–TF combinations during a single sweep. The top, middle, andbottom PSTHs show the unit’s response to gratings of 0.125cpd/16 Hz, 0.25cpd/2Hz, and1cpd/0.5Hz, respectively. Firing rate is indicated by spikes per second (spikes/s) on they-axis and time in seconds is shown on the x-axis. Grey diagonal lines overlaying thecontour plot indicate particular velocities (TF/SF) from0.06/s to 256/s. See text foradditional details. Figure 2: Contour Plots and Best-fit Gaussians for representative granular layer (GL)units. Fig. 2A shows the contour plot of the spatio-temporal tuning of a fast GL unit with Spatio-temporal tuning in the VestibulocerebellumJN-00815-2004.R1 38 a single peak. Fig. 2B shows the plot of the normalized Gaussian for the unit in 2A, asdetermined using the slightly modified equation of Perrone and Thiele (2001). Fig. 2Cand 2D show the contour plot and best-fit Gaussian plot, respectively, of the spatio-temporal tuning of a GL unit with a single peak in the slow zone. See caption to Fig. 1and text for additional details. Figure 3: Contour plots and Gaussian plots for the complex spike activity ofrepresentative Purkinje cells (CSA of P-cells). Fig. 3A shows the contour plot of thespatio-temporal tuning of a P-cell with a single peak in the slow zone. Fig. 3B shows theplot of the normalized 2-D Gaussian for the unit in 3A. In 3C, a P-cell with a primarypeak in the slow zone and a secondary peak in the fast zone is shown. The normalized 2-D Gaussian for this unit is plotted in 3D. See captions to Fig. 1 and 2 and the text foradditional details. Figure 4: Spatio-temporal tuning of granular layer (GL) units and the complex spikeactivity of Purkinje cells (CSA of P-cells). In these plots, the primary peak locations inthe spatio-temporal domain for all GL units (4A) and the CSA of all P-cells (4B) areindicated. In Fig. 4A, 8 of the units had a primary peak in the fast spatio-temporaldomain (white diamonds), while 9 had a primary peak in the slow zone (grey diamonds).In Fig. 4B, 38 of the 39 peaks fall within the slow zone (grey hexagons). The remainingP-cell had a primary peak at 0.10cpd/0.55Hz (white hexagon). In Fig. 4C, data from thecurrent study of the VbC and previous studies of spatio-temporal tuning in LM andnBOR is collapsed onto a single plot: black hexagons show the primary peak locations of Spatio-temporal tuning in the VestibulocerebellumJN-00815-2004.R1 39 the CSA of 39 P-cells in VbC (present study); black diamonds show primary peaklocations for 17 GL units in VbC (present study); grey triangles show the primary peaksof 64 LM units (Wylie and Crowder 2000); and the primary peaks of 55 units from nBORare represented by grey squares (Crowder and Wylie 2001; Crowder et al. 2003a). Seetext for details. Figure 5: Normalized average contour plots of spatio-temporal tuning. Figures 5A, 5B,and 5C respectively show the normalized average plots for the 9 slow granular layer (GL)units, 8 fast GL units, and complex spike activity of 39 Purkinje cells (CSA of P-cells)recorded in this study. See captions for Figs. 1-4 and text for additional details. Figure 6: Scatter plots of partial correlations for velocity (Rvel) and spatio-temporallyindependent (Rind) tuning. Each data point indicates the degree to which a particulargranular layer (GL) unit or the complex spike activity (CSA) of a Purkinje cell arecorrelated with velocity and SF/TF-independent predictions. The data space is dividedinto three regions based on statistical criteria approximated by the solid black lines.Velocity tuned, unclassifiable, or spatio-temporally independent cells fall in the upperleft, middle, or lower right areas of the scatter plot, respectively. Slow CSA, slow GLunits, fast CSA, and fast GL units are represented by black hexagons, grey diamonds,white hexagons with black borders, and white diamonds with black borders, respectively.Slow CSA was velocity tuned in 10 instances, while a single fast GL unit showed velocitytuning. See text for additional details. Spatio-temporal tuning in the VestibulocerebellumJN-00815-2004.R1 40 Figure 7: Optic flow input from the accessory optic system (AOS) and pretectum to thevestibulocerebellum (VbC) in pigeons. This schematic illustrates the mossy fibre (MF)and climbing fibre (CF) inputs arriving at the VbC from the retinal recipient nuclei of theAOS (nucleus of the basal optic root, nBOR) and pretectum (lentiformis mesencephali,LM) and the medial column of the inferior olive (mcIO), respectively. The results of thisstudy indicate that the CF input to Purkinje cells in the VbC is primarily from slow cellsin LM and nBOR, whereas MF input to the granular layer arises in both fast and slowcells in LM and nBOR. ml, molecular layer; Pcl, Purkinje cell layer; wm, cerebellarwhite matter. Spatio-temporal tuning in the VestibulocerebellumJN-00815-2004.R1 41 Fast CellsSlow Cells n(% total) SF (cpd) TF (Hz) Velocity(/s)n(% total) SF (cpd) TF (Hz) velocity(/s) PigeonnBOR 13 (25%) 0.078 2.8436.2 #[70.8*] 40 (75%) 0.530.300.57[0.75*]PigeonLM 23 (66%) 0.102.4925.8[52.3*] 12 (34%) 0.670.550.82[1.08*]PigeonGL unit 8 (47%) 0.138.2463.4[69.8*] 9 (53%) 0.680.300.4[0.5*]PigeonCSA 1 (3%) 0.100.555.5#[5.5*] 38 (97%) 0.670.350.5[0.5*]#meanTF/meanSF. *arithmetic mean. Table 1Preferred spatial frequencies (SFs), temporal frequencies (TFs), and velocities of fast andslow neurons. Average SFs, TFs, and velocities of the primary peaks are shown for thefast and slow neurons in the pigeon nucleus of the basal optic root (nBOR; Crowder et al.,2003a) and lentiformis mesencephali (LM; from Wylie and Crowder, 2001), and granularlayer (GL) units and the complex spike activity (CSA) of Purkinje cells in thevestibulocerebellum (present study).