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University Laboratory of Physiology, University of Oxford, Oxford United Kingdom
Submitted 16 June 2005; accepted in final form 12 September 2005
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ABSTRACT |
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INTRODUCTION |
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). The superficial layers of the SC receive visual inputs, whereas the deeper layers also receive auditory and tactile inputs, which often converge on individual neurons to generate multisensory response properties (Stein et al. 2004). Visual, auditory, and tactile inputs to the SC are arranged to form topographically aligned maps of space, the registration of which tends to be maintained even when the eyes move (Hartline et al. 1995; Jay and Sparks 1984; Peck et al. 1995; Populin et al. 2004). As a consequence, multisensory signals are integrated at the single neuron level to facilitate the control of motor commands that give rise to orienting movements of the eyes, head, and body.
Whereas visual and somatosensory maps are formed by topographic projections from the retina and body surface, respectively, a topographic representation of auditory space has to be computed using acoustic localization cues generated by the head and outer ears. These cues comprise interaural time and level differences (ITDs and ILDs), together with the direction-dependent spectral filtering of sounds by the head and external ears (King et al. 2001; Wightman and Kistler 1993). Previous studies have shown that mammalian SC neurons are sensitive to a combination of ILDs (Hirsch et al. 1985; Middlebrooks 1987; Middlebrooks and Knudsen 1987; Palmer and King 1985; Wise and Irvine 1983, 1985) and spectral cues (Carlile and King 1994; King et al. 1994; Palmer and King 1985). Sensitivity to ITDs, the dominant cue for auditory localization of low-frequency sounds by humans (Wightman and Kistler 1992), has been demonstrated in the cat SC by closed-field stimulation but only to values outside the physiological range (Hirsch et al. 1985; Yin et al. 1985). The contribution of this binaural cue to the formation of the auditory space map in mammals therefore remains uncertain.
The spatial receptive fields (SRFs) of auditory neurons are typically measured by presenting sounds in the free field. More recently, SRFs in the auditory nerve (Poon and Brugge 1993), lateral superior olive (Tollin and Yin 2002a,b), inferior colliculus (IC) (Behrend et al. 2004; Delgutte et al. 1999; Euston and Takahashi 2002; Sterbing et al. 2003), auditory cortex (Brugge et al. 1994, 1996; Mrsic-Flogel et al. 2001, 2005; Nelken et al. 1998; Schnupp et al. 2001), and SC (Sterbing et al. 2002) have been mapped with virtual acoustic space (VAS) stimuli. This approach involves delivering via earphones sounds that are digitally manipulated to simulate the filtering effects of the head and outer ears (King et al. 2001; Wightman and Kistler 1989). Because sounds can be rapidly presented from randomized directions without having to employ large speaker arrays or physically move a speaker to different locations, VAS stimulation enables SRFs to be measured at high spatial resolution. Furthermore, sound localization cues can be independently manipulated in ways that are impossible with free-field stimulation.
In this study, we used individualized VAS stimuli to measure the SRFs of auditory units in the ferret midbrain. The stimuli were first validated by comparing both acoustical measurements and neuronal responses obtained with free field and VAS stimulation. We then used VAS stimuli to obtain more detailed information about the auditory spatial response properties of SC neurons than provided by previous free-field studies as well as to explore their dependence on ITDs.
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METHODS |
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Seven adult (aged 
4 mo) pigmented ferrets (Mustela putorius) with normal hearing (assessed by otoscopic examination and tympanometry) were used in this study. All surgical procedures were approved by local ethical review committee and licensed by the UK Home Office. The animals were anesthetized by an intramuscular injection of alphaxalone/alphadolone acetate (Saffan, 2 mg/kg, Mallinckrodt Veterinary, Uxbridge, UK). During surgery, bupivacaine hydrochloride (Marcain Polyamp, Astrazeneca UK, Luton UK) was applied topically, and supplementary doses of Saffan were given as required via a cannula implanted in the radial vein. Body temperature was monitored by a rectal probe and maintained with a feedback electric blanket at 
38°C. The first stage of each experiment involved measuring the animal’s head-related transfer function (HRTF) so that individualized VAS stimuli could be constructed, followed by electrophysiological recordings from either the IC or the SC.
Preparation for acoustical recordings
A damped polythene probe tube (30 mm long, 0.86 mm ID, 1.52 mm OD) was passed through each ear canal wall in such a way as to emerge caudally behind the pinna. The tubes were secured internally with a small flange, which abutted against the canal wall, and externally with a rubber O ring that was pressed against the skin. The animal was then placed in a stereotaxic frame and fitted with blunt ear bars, and the skull was exposed. A steel bar (7 mm diam) was attached to the skull with steel screws and dental cement (Simplex Rapid, Austenal Dental, Harrow, UK), so that the head could be supported from behind. At this stage in the SC experiments (n = 6), the stereotaxic frame was removed, the incisions in the scalp closed, and the external ears carefully repositioned according to measurements made prior to surgery. Condenser microphones (miniature KE-4-211-2 microphone capsules, Sennheiser, High Wycombe, UK) were attached to the probe tubes, and the animal was transferred to an anechoic chamber for free-field acoustic recordings, which were carried out prior to preparation for electrophysiological recording. To allow a more direct comparison between free-field and VAS SRFs, the acoustical measurements for the IC experiment were conducted immediately prior to recording with the craniotomy performed and all recording equipment in place.
Acoustical recording
A loudspeaker (KefT27, KEF Audio, Maidstone, UK) mounted on a computer-controlled motorized hoop (radius: 65 cm) was used to present broadband signals (512-point Golay codes) (Zhou et al. 1992) from 63 different directions at 16° intervals in azimuth from –160 to +160° and at six vertical angles from +80 to –60° elevation. The sampled positions were arranged so that their diagonal separation was 34°. The generation of the Golay codes and the recording of the microphone signals were performed digitally using TDT system 2 A/D and D/A converters (sample rate of 80 kHz, Tucker-Davis Technologies, Alachua, FL) and 30-kHz anti-alias filters. The microphone signals were analyzed for each stimulus direction to calculate a spectral transfer function containing both the animal’s HRTF and the transfer characteristics of the loudspeaker and probe microphones. The ITDs were extracted from the microphone signals by cross-correlation of the impulse responses after low-pass filtering (0–4 kHz). An in situ calibration to remove the transfer functions of the probe microphones and in-ear headphones used for presenting the VAS stimuli was then carried out. Minimum phase filters were calculated from the equalized amplitude spectra using the Hilbert transform. VAS stimuli consisted of short (100 ms) Gaussian noise burst with 5 ms raised cosine onset and offset ramps, which were convolved with the appropriate minimum phase filters for each direction, and delayed to generate the appropriate ITD. Although frequency-dependent ITDs are excluded by this approach, psychophysical studies in humans have shown that the minimum-phase-plus-delay method adequately approximates the HRTF phase spectrum as long as the low-frequency ITD is appropriate (Kulkarni et al. 1999). The VAS stimuli were not "frozen" because new Gaussian noise bursts were used for each stimulus presentation.
Electrophysiological recording
At the conclusion of the acoustical measurements, anesthesia was switched to an intravenous infusion (Perfusor Secura FT infusor, B. Braun Melsungen, Germany) of ketamine/medetomidine (Ketaset, 5 mg · kg–1 · h–1, Fort Dodge Animal Health, Southampton, UK; Domitor, 10 µg · kg–1 · h–1) in Hartmann’s solution. A tracheal cannula was implanted, and the animal was ventilated (7025 respirator, Ugo Basile, Milano, Italy) with oxygen-enriched air. Atropine sulfate (0.06 mg · kg–1 · h–1, Animal Care, York, UK) and dexamethasone (0.5 mg · kg–1 · h–1, Dexadreson, Intervet UK, Milton Keynes, UK) were administered intramuscularly to reduce mucus secretions in the airways and minimize cerebral edema, respectively.
In six ferrets, a craniotomy was performed over the occipito-parietal cortex above the right SC. In the remaining animal, the craniotomy was positioned more caudally, so that recordings could be made from the IC. The dura was removed and the exposed cortex was protected by 2% agar in saline. The agar was supported by a rim of dental acrylic. The left eye was dilated with atropine and fitted with a zero-refractive power contact lens. To eliminate eye movements, pancuronium bromide muscle relaxant was added to the infusate (0.2 mg · kg–1 · h–1, Pavulon, N.V. Organon, the Netherlands). We monitored the depth of anesthesia and the physiological condition of the animal by continuous measurement of the electrocardio- and electroencephalograph (ECG and EEG; using either custom-built amplifiers or a Datex-Ohmeda anesthesia monitor, Hatfield, UK), end tidal CO2 (using either a 47210A capnometer, Hewlett Packard GmbH, Boeblingen, Germany or Datex-Ohmeda monitor), and arterial oxyhemoglobin saturation (Datex-Ohmeda monitor).
Single-unit activity was recorded extracellularly using a tungsten-in-glass electrode (0.1–10 M
) lowered vertically through the cortex and into the midbrain. The electrode signals were band-pass filtered (500 Hz to 5 kHz), amplified (
15,000 times) and digitized at 25 kHz. Electrolytic lesions (–5 µA for 5 s) were made in most electrode penetrations in which acoustically responsive units were isolated, to allow for histological confirmation of recording sites.
Visual and auditory stimuli
The SC was located by presenting a diffuse flashing light positioned a few centimetres from the contralateral eye. The superficial visual layers of the SC were usually encountered at a depth of 6 mm below the cortical surface. We determined the direction of the maximum visual response of multiunit activity recorded in these layers using an LED mounted on the motorized hoop.
The electrode was then advanced into the deeper layers of the SC to search for auditory responses by presenting contralateral broadband noise bursts. These stimuli were delivered via commercial Panasonic earphone drivers (RP-HV297, Bracknell, UK), coupled to an otoscope speculum that was inserted into each ear canal. When an auditory response was identified, the threshold of the unit was determined by presenting unfiltered noise bursts to the contralateral ear (100-ms duration with an inter-stimulus interval of 1,000 ms) at a range of sound levels. Threshold was taken as the lowest sound level to elicit an increase in firing rate that was significantly greater (P 0.05) than the unit’s resting level. The spatial receptive fields (SRFs) of most units were measured at two sound levels, one near threshold (typically 5–15 dB above unit threshold) and a second at a level well above threshold (typically 25–35 dB above unit threshold). SRFs were measured by presenting VAS stimuli in a random order from the same sound directions used for measuring the HRTF. This process was repeated until 10–20 responses for each virtual stimulus direction had been collected. The mean evoked spike rate at each stimulus position was then used to estimate the unit’s SRF (see following text).
Two stimulus conditions were used to investigate the contribution of ITDs to the spatial tuning of SC units (Fig. 1). The natural cue condition involved presenting sounds from each position with all sound localization cues co-varying naturally, as they would with a real free-field sound source. In the fixed cue condition, the ITDs were maintained at a fixed value and did not co-vary with the ILDs and spectral cues. This was achieved by delaying the sound reaching the left ear by 200 µs, close to the maximum value produced by the separation of the ears, for all 63 virtual sound locations. The sound therefore arrived at the right ear first (ipsilateral to the SC from which the recordings were made) and had an interaural delay corresponding to a source at 90° to the animal’s right. This ITD was chosen because it represented a value to which no units in the right SC would be expected to be tuned. Consequently, the ITDs were fixed at a value inappropriate for the normal location of an SRF.
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Analysis of results
Stimulus generation and data acquisition were controlled using BrainWare (Tucker-Davis Technologies). This software stored the latency and shapes of all spikes that crossed an arbitrary amplitude threshold determined by the user. These data were saved for off-line analysis. Whenever possible we digitally isolated single units by sorting evoked spikes based on their shape. The response period for each unit was individually determined from the poststimulus time histogram (PSTH). In all cases, firing rates had returned to spontaneous background levels by 400 ms after stimulus onset. Response magnitude was measured relative to the spontaneous activity of the neuron, which was obtained from a second window drawn between 500 and 1,000 ms after stimulus onset.
The raw data were exported to Matlab R14 (Mathworks, Natick, MA) with which all further analysis was carried out. SRFs were visualized by producing a smoothed map projection showing the average response rate for each sound direction. Smoothing was done by interpolation of the averaged responses over a uniform grid of 7.5° resolution using biharmonic spline interpolation. To avoid discontinuities due to extrapolation over positions above and behind the animal (along the "dateline" and at the "north pole" of our spherical coordinate system), we extended the matrix maps to cover a -200 to +200° azimuth range by copying values across from the opposite edge, i.e., from –160 to +200° and from +160 to –200°. This ensured that the algorithm could interpolate smoothly and without discontinuities across the full ±180° azimuthal range. For each SRF, we calculated the 50 and 75% response areas (rad2) corresponding to the total angular extent of the regions within which the response exceeded a stated percentage of the unit’s maximal response (estimated from the mean response at the 5 most effective virtual stimulus positions).
The 50 and 75% response areas provide a measure of the overall responsiveness of a cell across different spatial locations but do not indicate whether the SRF is focused around a single preferred stimulus direction. For example, a multi-peaked SRF could still have a small total 75% area. We therefore derived the centroid (or center of mass) for each SRF. The centroid provides a way of quantifying the preferred sound direction of each unit as well as determining the sharpness of this tuning. The centroid was calculated by modeling the response field as a sphere of unit radius, where the "mass density" in each direction was given by the observed response strength in the corresponding direction (see Mrsic-Flogel et al. 2005 for the full derivation of the centroid). The direction of the centroid vector was calculated as a volume integral by approximating the model sphere as a sum of pyramids, the bases of which are at the surface and the apices of which are at the center of the sphere. The direction of the centroid vector summarizes the overall directional preference of the SRF, whereas its length gives an indication of how sharply tuned the SRF is in that direction. The theoretical maximum length of the centroid (for an SRF responding to a single sound direction) is 0.75, the distance of the center of a pyramid of unit height from its apex. The interpolated map, centroid direction vector and visual best direction recorded in the superficial layers of the same electrode penetration were then displayed using a Kavraisky 5 equal-area projection (see Fig. 7).
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Units with low spike rates or unreliable responses often have centroids with unreliable directions. For example, a burst of spikes at a single stimulus presentation could spuriously displace the centroid direction toward that sound-source location. To eliminate units with misleading centroids we used a Monte Carlo approach to resample (with replacement) each SRF 10,000 times and derive the centroid statistics for each. SRFs were excluded if the SE of the simulated centroid directions exceeded 3°.
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RESULTS |
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To show that our VAS stimuli accurately replicate the animal’s own HRTF, we have to demonstrate that the HRTF-filtered noise bursts faithfully recreate the amplitude spectra of the corresponding free-field stimuli. Furthermore, we must show that comparable neuronal spatial tuning can be recorded with VAS and free-field stimulation.
The implanted probe microphones made it possible to record our VAS stimuli at the same location within the ear canal where the HRTF was initially measured. Figure 2 shows the amplitude spectra measured from each ear for VAS and free-field stimuli from three different sound-source directions. The spectra are almost identical in each case. Figure 3 shows the differences between the VAS and free-field amplitude spectra over 30 sampled sound directions (same directions at which the neural responses are shown in Fig. 4). At most locations, these differences were negligible (<1 dB in 80% of cases; <3 dB in 90%) and constant across frequency, indicating that the VAS stimuli faithfully replicate the spectral cues arising from real free-field stimuli. For some directions, however, the amplitude spectra exhibited larger differences at higher frequencies. This is caused by the poor signal-to-noise ratio at higher frequencies for stimuli presented on the side contralateral to the microphone.
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), it is possible to make inferences about the fidelity of our VAS stimuli from a comparison of the virtual SRF centroid directions with the best direction of the overlying visual responses (see following text). In addition, we performed a direct physiological validation by comparing VAS SRFs with those obtained using free-field stimulation. This was done using a population of 11 units recorded from the central nucleus of the IC in one animal. We chose the IC rather than the SC because the more robust responses obtained in this nucleus were suited for making quantitative comparisons of data recorded over the longer periods of time required to map the SRFs using both forms of stimulation. Figures 4 and 5 show examples of three of these units where SRFs were recorded at corresponding sound levels using both free-field and VAS stimuli. The responses of the unit shown in Fig. 4, where two sets of VAS and free-field recordings were conducted around an hour apart from the same unit, clearly illustrate the stability of the SRFs. Indeed, the coefficients derived from cross-correlation of the spike rates in the response window for each mode of stimulation were almost identical for the two sets of recordings. The SRFs for the two units shown in Fig. 5 were quite different from one another, with the response illustrated in Fig. 5B being more sharply tuned than that in Fig. 5A. Once again, however, the responses obtained using free-field and VAS stimuli were extremely similar, with correlation coefficients close to one in each case.
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, we compared the SRFs by calculating correlation coefficients between the free-field and VAS data. The r values in the top right of each panel indicate the correlation coefficients of VAS and free-field recordings (based on all the sound directions sampled, including the other elevations) conducted at adjacent points in time. For example, unit 8 with two VAS and two free-field recordings has three r values listed; from top to bottom: VAS1/free-field1, VAS2/free-field1, and VAS2/free-field2.
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Units 3 and 11 showed excellent correspondence between VAS and free-field and were stable on re-recording. The r values of these recordings ranged from 0.81 to 0.96. Those units in which the SRF was determined only once with each form of stimulation exhibited no evidence of response drift and had high r values in the range of those found in units 3 and 11. The response of unit 8 was less stable between the two pairs of recordings, responding more strongly during the second VAS and free-field recordings. Despite this, the correlation between the VAS and free-field responses within each recording pair was high (r > 0.85). Only unit 5 showed systematic differences between VAS and free-field across recordings. Of the four r values (ranging from 0.76 to 0.79) for this unit, two were not significantly greater than chance, confirming that, in this instance, the correlation between the free-field and VAS recordings was poor. The range of r values for all 11 IC units was 0.63 to 0.96, with a mean of 0.84. These values are comparable to those reported by Keller et al. (1998).
Auditory receptive fields of SC neurons measured with normal localization cues
A total of 48 acoustically responsive units were isolated from the SC of six ferrets. Three of these were excluded from further analysis according to the criteria described in METHODS. A total of 88 recordings were made, 79 of which passed our exclusion criteria. The SRFs of most units comprised a single peak, usually in the contralateral hemifield (Fig. 7). There was considerable variation in the size of the SRFs and in the magnitude of the maximum response obtained at corresponding sound levels relative to unit threshold. In keeping with previous free-field measurements of spatial tuning in the ferret SC (King and Hutchings 1987), the narrower axis of the 75% area typically covered 30°.
Effect of altering sound level
Of the 45 remaining SC units, we recorded 13 at one sound level only and 32 at two sound levels. The difference in sound level over all units was 18 ± 7 (SD) dB. For two neurons, we re-recorded one of the sound levels to test for unit stability. Our level analyses are therefore conducted on 34 pairs of SRFs. Increasing sound level resulted in a significant (paired t-test, t = 3.271, df = 33, P < 0.003) increase in the maximum response of the units (Fig. 8A) as well as a significant (paired t-test, t = 3.591, df = 33, P < 0.002) increase in the size of the 75% area (Fig. 8B). Increasing the sound level also led to a small decrease in centroid vector length, although this decrease was not significant over the population as a whole (paired t-test, t = –1.138, df = 33, P = 0.263; Fig. 8C). A shorter centroid vector would have indicated a less sharply tuned response. Although there was no systematic effect of sound level on the centroid length over the population, Monte-Carlo analysis of individual units showed that 17/34 SRF pairs (16/32 units) had significantly different centroid lengths between the two conditions (P 0.05). Of these 16 units, 12 showed a significant decrease in centroid length as the sound level was increased.
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Previous free-field studies of the ferret SC (e.g., King and Hutchings 1987; King et al. 1998) have shown that the best azimuths of visual units recorded in the superficial layers are arranged to form a map that corresponds closely in its spatial extent, magnification, and orientation with the auditory representation in the deeper layers of the nucleus. We have explored this relationship further for two reasons. First confirming that auditory virtual SRFs are aligned with the visual responses would provide further evidence as to the fidelity of our VAS stimuli. Second, by using the visual map as a template against which to compare the auditory SRFs, we can examine the contribution of ITDs to the topographic organization of the auditory representation.
In this study, we focused mainly on how the auditory SRFs vary with the location of the units along the rostrocaudal axis of the SC. This is the axis along which stimulus azimuth is represented. For each acoustically responsive unit, we compared the azimuth of the SRF centroid vector with the visual best azimuth recorded in the same electrode penetration (Fig. 10). The centroid directions of auditory units recorded in the rostral third of the SC spanned the anterior quadrant with the most rostral units being tuned to ipsilateral sound directions. This same region of the SC also represents frontal visual space. As the location of the recording electrode was moved toward the caudal end of the SC, the auditory centroid vectors and visual best azimuths shifted systematically toward more posterior regions of the contralateral hemifield. Because we did not undertake any free-field SC recordings in the present study, we have included in Fig. 10 data from a previous study (King et al. 1998) in which the preferred sound directions were derived from auditory spatial response profiles mapped at a single elevation (gray crosses in this figure). These measures of spatial selectivity are not equivalent, as the centroid vector is based on the relative response of the unit throughout the SRF and can therefore be located away from the sound location evoking the strongest response (see Fig. 7A). Nevertheless, the great majority of auditory centroid vectors fell within or very close to the distribution of best azimuths from the earlier free-field study.
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The virtual SRFs of 32 of 45 SC units were recorded using two randomly interleaved ITD conditions. The purpose of this was to investigate the possible contribution of ITDs to the generation of the map of auditory space in the SC. The SRFs recorded when all sound localization cues were allowed to vary naturally were compared with those obtained with a fixed ITD of +200 µs for all sound directions (see METHODS). This time delay would correspond to a sound originating from 90° to the right (ipsilateral to the recorded SC). Unless the virtual sound-source originated from this direction, the fixed ITD cues conflicted with the other localization cues. Because most of the units were recorded at more than one sound level, we obtained a total of 54 recordings in the fixed ITD condition and 79 in which ITDs were allowed to vary naturally.
We compared the topographic alignment of the visual and auditory maps using SRFs generated with natural cues and with fixed ITDs (Fig. 11). Despite the reduction of spatial information available in the fixed ITD condition, the auditory centroid vectors continued to co-vary with the visual best positions at both suprathreshold (Fig. 11A) and near-threshold (B) sound levels. We also looked for an effect of ITD on centroid direction, centroid length, 50% SRF area and maximum response strength (Fig. 12). Of these parameters, only the length of the centroid vector (Fig. 12B) showed a significant overall change, decreasing in value in the fixed ITD condition (paired t-test, t = 3.583, df = 53, P < 0.001).
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0.05) in 17/32 units for at least one of the four measured parameters. A smaller subset of units showed a significant effect for at least one measure of spatial tuning (Monte Carlo analysis, indicated by circled data points in Fig. 12). For example, 7/32 units displayed a significant change in SRF area with 2/32 units showing a change in centroid direction when the ITD was fixed. Examples of individual SRFs recorded in the two ITD conditions are shown in Fig. 13. These illustrate cases where holding the ITD constant had either no effect (Fig. 13, A and B) or induced a significant change (Fig. 13, C–F) in one of the spatial tuning measures.
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DISCUSSION |
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Fidelity of the virtual acoustic space stimuli
Validation of the VAS stimuli was achieved by comparing the amplitude spectra of the free-field and VAS signals measured with probe microphones implanted into the ear canals and also by a comparison of SRFs of the same IC units recorded with each form of sound presentation. Although the central nucleus of the IC does not contain a map of auditory space, the SRFs found there are sufficiently discrete and inhomogeneous (see also Behrend et al. 2004; Sterbing et al. 2003) to justify using the stronger responses recorded in this nucleus to compare the spatial tuning obtained with free-field and VAS stimulation.
We did find a discrepancy between some of the very high-frequency components of the amplitude spectra of the free-field and VAS stimuli for sounds presented on the contralateral side, which arose because these signals were attenuated by the head to the noise level of our recording system. However, the bandwidth of these differences is almost certainly too narrow to be preserved after the sound has been filtered by the cochlea. Overall, the correlation between both acoustical and physiological measures was very high and comparable to that reported in other studies (Behrend et al. 2004; Keller et al. 1998; Sterbing et al. 2003). We can therefore conclude that our VAS stimuli reliably simulated the real sound sources. A similar conclusion was reached by comparing judgements made by human listeners of the apparent locations of free-field and virtual sound sources that had been synthesized in the same way as in the present study (Wightman and Kistler 1989).
Representation of space in the SC
The fidelity of the VAS stimuli was further confirmed by the similarity between the virtual SRFs measured here and the auditory spatial tuning reported in previous free-field studies of the SC. With the exception of a few units in the ferret SC where the SRFs were mapped in more detail (King and Hutchings 1987), most free-field experiments have measured spatial response profiles along a single azimuth or elevation or attempted to estimate the location of the borders of the SRF. Nevertheless, we found that the properties of the VAS SRFs closely resemble those reported in free-field studies of the ferret (King and Hutchings 1987) and other species (King and Palmer 1983; Middlebrooks and Knudsen 1984).
Increasing the sound level resulted in a systematic increase in maximum firing rate and in the response area of the units, confirming results found in previous free-field studies (King and Hutchings 1987; King and Palmer 1983; Middlebrooks and Knudsen 1984). Around 40% of units showed a small but significant change in the direction of the centroid vector, which resulted from a non-uniform increase in SRF area with sound level. There was, however, no systematic shift in preferred sound direction across the population of neurons (Fig. 9) and the distribution of centroid directions with recording site within the SC was very similar at near-threshold and suprathreshold sound levels (Fig. 10). A similar result was noted with free-field stimulation (Carlile and King 1994; King et al. 1994; Middlebrooks and Knudsen 1984).
We did observe more scatter in the auditory map than reported in the free-field studies. In particular, the range of centroid direction vectors of units recorded in rostral SC was larger than that of the best azimuths, as defined by the peak of the spatial response profile, in our earlier free-field studies of the ferret SC (e.g., King and Hutchings 1987; King et al. 1998). Our acoustical measurements and recordings in the IC suggest that this apparent mismatch is unlikely to arise because the VAS stimulation did not adequately replicate the free-field sound source. On the other hand, Behrend et al. (2004) showed that the presence of recording equipment around the animal’s head can alter virtual SRFs. Such equipment was obviously in place in the free-field experiments but not when the VAS stimuli were generated for the SC experiments in the present study. Acoustic distortions produced by the recording equipment could therefore contribute to the differences between the azimuth maps observed with VAS and free-field stimulation. Another possibility is that these differences might reflect our use of the centroid as a measure of spatial selectivity, which is based on the whole receptive field rather than the region of maximum response only. This latter possibility is likely, given that, in contrast to the free-field studies, we did not exclude units with very broad or multi-peaked SRFs.
Although the distribution of centroid direction vectors for individual units was quite scattered, the average SRFs obtained by pooling data within discrete regions of the SC revealed a clear topographic shift in spatial selectivity with recording site. The broad spatial tuning of the auditory units is consistent with the coarsely tuned movement fields of deep SC neurons (McIlwain 1991; Lee et al. 1988; Sparks et al. 1976). Thus the location of the stimulus and the vector of the orienting movements elicited by it both appear to be specified by the spatial distribution of activity across a population of SC neurons. Estimates of neuronal discrimination values from the responses of space-mapped neurons in the external nucleus of the IC in the barn owl also suggest that the ability of the animal to detect a change in sound-source direction is based on a shift in the population response of these neurons (Bala et al. 2003).
Role of ITDs in location selectivity of SC neurons
Cue-trading experiments have shown that low-frequency ITDs are the primary cue for localization by humans in the horizontal plane (Wightman and Kistler 1992). Tuning to ITDs is also known to underlie the representation of sound azimuth in the optic tectum of the barn owl (Olsen et al. 1989) as well as the behavioral responses of this species (Poganiatz et al. 2001). In contrast, previous recording studies suggest that the map of space in the mammalian SC is based mainly on ILDs and spectral cues. This is supported by the broad, multi-peaked frequency tuning of SC neurons, which is dominated by high frequencies (Carlile and Pettigrew 1987; Hirsch et al. 1985; King and Carlile 1994; King and Palmer 1983; Middlebrooks 1987; Wise and Irvine 1983) and by the presence of a topographic variation in ILD sensitivity along the rostrocaudal axis of the nucleus (Hirsch et al. 1985; Wise and Irvine 1985). Moreover, the changes in spatial tuning observed following occlusion (Middlebrooks 1987; Palmer and King 1985) or passively moving one ear (Middlebrooks and Knudsen 1987), or after removal of the external ear structures (Carlile and King 1994; Schnupp et al. 1998), are consistent with a combination of ILDs and spectral cues being the primary determinants of the spatial selectivity of mammalian SC neurons. Sensitivity to ITDs has been demonstrated in cat SC neurons (Hirsch et al. 1985), but because response latencies decrease with increasing sound level, this could provide a mechanism underlying the processing of ILDs rather than a basis for the representation of auditory space (Yin et al. 1985).
A unique advantage of VAS stimulation is the capacity to manipulate independently the acoustic cues available and therefore to assess their contribution to auditory localization (King et al. 2001). This has been done in human psychophysical (Martin et al. 2004; Wightman and Kistler 1992, 1997) and neurophysiological studies (Delgutte et al. 1999; Nelken et al. 1998; Tollin and Yin 2002a,b). By holding ITDs at a constant value while allowing ILDs and spectral cues to vary naturally, we found that the properties of the SRFs of a minority of SC neurons did change significantly, perhaps reflecting the broad ITD sensitivity demonstrated by Hirsch et al. (1985) in the cat. However, there was no overall shift in the centroid direction vectors, which continued to co-vary with the visual receptive fields mapped at the same SC locations. Although behavioral measurements have shown that ferrets can certainly localize sounds using ITDs (A. Schulz, J.W.H. Schnupp, and A. J. King, unpublished observations), our results indicate that these binaural cues make little contribution to the map of auditory space in the SC and are therefore presumably processed by other pathways within the midbrain.
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GRANTS |
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ACKNOWLEDGMENTS |
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FOOTNOTES |
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Address for reprint requests and other correspondence: A. J. King, University Laboratory of Physiology, Parks Road, Oxford OX1 3PT, UK (E-mail: andrew.king{at}physiol.ox.ac.uk)
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REFERENCES |
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