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Division of Biology 216-76, California Institute of Technology, Pasadena, California
Submitted 8 August 2005; accepted in final form 2 November 2005
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ABSTRACT |
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INTRODUCTION |
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Lesions in the tectal pathway render owls unable to accurately localize sound in the area of space represented by the damaged regions (Wagner 1993
). During inactivation experiments, the probability of performing an accurate orienting behavior toward sounds decreased (Knudsen and Knudsen 1996a
; Knudsen et al. 1993
). However, the owls regain their normal localizing ability in the course of a few weeks (Knudsen et al. 1993
; Wagner 1993
). A "forebrain sound localization pathway" that extends from the midbrain to the forebrain via the thalamus appears to be also involved in this localizing ability and recovery (Cohen and Knudsen 1994
, 1995
, 1998
; Cohen et al. 1998
; Knudsen et al. 1993
; Wagner 1993
). Consistent with this hypothesis, lesion or inactivation of both pathways permanently impairs the owl's ability to localize sounds (Knudsen and Knudsen 1996a
; Knudsen et al. 1993
; Wagner 1993
). Thus owls seem to use either tectal or forebrain structures to determine sound direction. The space-specific neurons of the forebrain do not receive projections from the midbrain map (Arthur 2002
; Cohen et al. 1998
; Knudsen and Knudsen 1983
; Proctor and Konishi 1997
). However, both the forebrain and midbrain representations of auditory space use information on binaural cues produced by the same lower brain stem areas. These binaural cues are the interaural level difference (ILD) and the interaural time difference (ITD), which are processed in separate brain stem pathways (Fig. 1). For the owl, ILD and ITD encode the vertical and horizontal coordinates of sound direction, respectively (Moiseff 1989
).
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METHODS |
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Acoustic stimuli
Custom software was used to generate sound stimuli, data collection and analysis. Acoustic stimuli were delivered by a stereo analog interface (DD1; Tucker Davis Technologies) through a calibrated earphone assembly. Tonal, broadband, and narrowband noise stimuli (50-ms duration, 5-ms linear rise/fall time) were presented once per second. Broadband stimuli had a band-pass of 112 kHz. Narrowband signals were 1-kHz bandwidth noise.
Spikes were recorded during a time window set to start 100 ms before the stimulus onset and ending 200 ms after stimulus offset. ITD was varied in steps of 30 µs, ILD in steps of 5 dB, and frequency in steps of 100 Hz. We averaged the response
10 randomized repetitions of the same stimulus. The stimulus intensity could be varied independently for each ear using a pair of digitally controlled attenuators (PA4, Tucker Davis Technologies).
All recordings were performed in a double-walled sound-attenuating chamber. Each earphone consisted of a speaker (Knowles 1914) and a microphone (Knowles 1319) encased in a custom-made metal delivery piece (5 mm long and 7 mm diam) that fits the owl's ear canal. The gaps between the earphone assembly and the ear canal were filled with silicone impression material (Gold Velvet II, All American Laboratory). Simultaneous measurement of sound with both the B&K and the Knowles microphones made it possible to translate the voltage output of the Knowles into sound intensity in dB SPL. The Knowles microphones were then used to calibrate the earphone assemblies at the beginning of each experiment. The calibration data contained the amplitudes and phase angles measured in steps of 100 Hz. The computer automatically smoothed irregularities in amplitude and phase of the frequency response of each earphone from 0.5 to 12 kHz.
Data collection
The activity of single neurons in Ov and ICx was recorded extracellularly with tungsten electrodes (1M
, 0.005-in, A-M Systems). Action potentials were amplified, filtered (Amplifier System, µA-200, Beckman Electronic Shop), and converted to transistor-transistor logic (TTL) pulses with a spike discriminator (SD1, Tucker Davis Technologies). The data were stored in a computer via a time converter (ET1, Tucker Davis Technologies) and an A/D converter (DD1, Tucker Davis Technologies) with a sampling rate of 48 kHz and 16-bit resolution.
Ov was localized using stereotaxic coordinates and locating its tonotopically organized region (Proctor 1993
; Proctor and Konishi 1997
). ICx was localized stereotaxically and by its physiological response properties (Knudsen and Konishi 1978
; Peña and Konishi 2000
, 2001
). The electrodes were advanced with a microdrive (Motion Controller, Model PMC 100, Newport) in steps of 100 µm until the nucleus was reached. The size of the steps was then reduced to 24 µm to search and isolate single units. The neurons were recorded every approximately 100 µm in the dorsoventral plane.
The number of impulses obtained for specific values of stimulus parameters such as frequency, ITD and ILD constitutes the raw data in this study. The stimulus parameters were randomly varied during the recording of neural responses. For each Ov and ICx neuron we examined the ITD, ILD, and frequency tuning (Fig. 2). We computed: mean firing rate as a function of ITD (ITD curves), varied in 30-µs steps within a range from 300 to 300 µs (negative ITDs indicate ipsilateral ear leading); mean firing rate as a function of ILD (ILD curves), varied in steps of 5 dB in a range from 30 to 30 dB (negative ILDs mean left ear louder); and mean firing rate as a function of the stimulus frequency changed in steps of 100 Hz at a constant sound intensity of 40 dB SPL (iso-intensity frequency tuning curve).
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We first determined that a neuron was "sensitive" to ITD or ILD by visual inspection of the tuning curves obtained with broadband noise stimulation. The ITD tuning was later confirmed by the statistics used in fitting the ITD curves obtained with tonal stimulation. The "best ITD " and "best ILD " elicited the maximum response in the ITD and ILD curves, respectively. In the case of ITD curves with multiple peaks of similar amplitude, we used the peak closest to 0 µs. We used the best ITD to collect the ILD curves and the best ILD to collect the ITD curves. These ITD and ILD values were then used to obtain the neuron's frequency tuning curve. An Ov neuron was classified as broadly tuned to frequency when it responded to a frequency band equal to or larger than the median half-height width of the iso-intensity frequency tuning curves in the ICx neurons sample (1.4 kHz). In all neurons that were initially considered tuned to ITD and broadly tuned to frequency, we examined the ITD sensitivity across frequency. We performed the same analysis on space-specific neurons of ICx to compare results obtained under identical experimental conditions.
The tuning to ITD in periodic signals (tones) can be expressed in terms of phase differences between the sound arriving to the left and right ears. The interaural phase difference that elicits the maximum mean response will be called the mean interaural phase (MIP) (Goldberg and Brown 1969
). ITD curves for tones in Ov and ICx do not show the clear sinusoidal shape of lower brain stem neurons that allows MIP computation by fitting the data to cosine functions (Peña et al. 1996
; Viete et al. 1997
). Instead, we obtained MIP by folding the ITD curves into a single period of the stimulating frequency, converting ITD to interaural phase difference (IPD), and fitting the data to a Gaussian function using the least-square method. The center of the Gaussian fit was used as MIP. We used visual inspection of each fit and the
2 statistical test, based on the residuals between the data and the model, and the degrees of freedom of the fitting equation, to evaluate the goodness of each fit. Only the cells whose fits passed the
2 test (P < 0.05) were used for further analysis. We then performed a linear regression of the MIP versus stimulating-frequency and quantified the difference between the data and the regression line by computing the mean of the squared differences between each point and the regression line. We carried out the same analysis for Ov and ICx neurons.
We studied the ITD tuning across frequency by examining the relationship between MIP and stimulus frequency. We used the residuals between the data and the regression line to quantify the linearity of this relationship. For linear relationships, this is also the most precise method to determine the characteristic delay (CD) of the neurons (Rose et al. 1966
; Yin and Kuwada 1983
). Neurons that have a CD respond to a value of ITD with the same relative firing rate at all stimulus frequencies. In such cells, plotting the MIP against the stimulating frequency yields a line whose slope is the CD.
The width of the main peaks of the ITD curves for broadband noise and tones were measured at 50% of the distance between the minimum and maximum response level ("half-height width"). The same criteria were used to measure the frequency-tuning width in iso-intensity frequency tuning curves.
Histology
The recording sites were marked in the last experiment by iontophoretic injection of tracers [fluorescein (FDA) and tetramethylrhodamine (RDA) conjugated dextran amines] and electrolytic lesions in the previously recorded regions of Ov and ICx (Fig. 2, A and B). Four to 6 days after tracer injection, the owls were overdosed with sodium pentobarbital (Nembutal, Abbot Laboratories) and perfused with saline followed by 2% paraformaldehyde (Fisher Scientific). Brains were blocked in the plane of the electrode penetration, removed from the skull and placed in 30% sucrose until they sank. They were then cut in 60-µm sections and mounted on slides to verify the location of the recording site. The electrode locations of previous experiments were extrapolated using records of the stereotaxic coordinates of each recording site.
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RESULTS |
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Frequency tuning
We obtained iso-intensity frequency tuning curves in Ov (Fig. 2, E and H) and ICx neurons (Fig. 2K). The best frequencies, frequencies that elicited the maximum response of the neuron, in Ov neurons varied from 0.7 to 7.1 kHz (median = 4.3 kHz). Their frequency tuning width varied from 0.2 to 7.8 kHz (median = 1.7 kHz). The best frequencies of ICx neurons varied from 2.0 to 6.2 kHz (median = 5.2 kHz), and their frequency tuning width varied from 0.4 to 3.4 kHz (median = 1.4 kHz). There was no significant difference in the frequency tuning width in both nuclei (t-test, P = 0.31). The comparison of best frequencies showed a distribution with significantly lower mean in Ov neurons than in ICx (t-test, P < 0.00001; Fig. 3).
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ITD sensitivity
In Ov, ITD curves measured with broadband noise varied from having multiple undistinguishable maxima (phase ambiguous) to a distinctly larger response to a unique ITD (Fig. 2, C and F). These results are consistent with previous work (Proctor 1993
). Of the 325 Ov neurons included in this study, 42.2% (n = 137) presented a phase ambiguous ITD tuning curve, while the rest responded maximally to a single ITD. All ICx neurons recorded (n = 52; Fig. 2I) showed a main peak at a single ITD.
We compared the half-height width of the main peak in ITD tuning curves obtained for broadband noise signals and tones in Ov and ICx (see METHODS). Only broadly frequency-tuned Ov neurons were used to measure the ITD tuning width in broadband noise. The mean half-height width of the ITD curves was 175.6 ± 125.7 µs (median = 136 µs, n = 148) in Ov. The same measurement in ICx neurons, with similar frequency response bands, yielded significantly smaller values (mean half-height width = 77.1 ± 27.3 µs; median = 69 µs; n = 52; t-test, P < 0.0001; Fig. 4A).
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ITD tuning across frequency
We compared the relationship between MIP (see METHODS) and the stimulating frequency in Ov and ICx. We used cells having frequency tuning curves wider than 2 kHz to select for neurons with broader tuning than the coincidence detector neurons of the nucleus laminaris (Peña et al. 2001
). This ensured that frequency convergence had taken place along the processing stream leading to each of these neurons. If this relationship is linear, there is a frequency-independent ITD that elicits the same relative response in the neurons. This frequency-independent ITD is called the "characteristic delay" of the neurons (CD) (Rose et al. 1966
; Yin and Kuwada 1983
). A lack of linear relationship between phase and frequency indicates that the tuning to ITD varies with frequency and that the neurons have no CD.
We computed the linear regression of the MIP versus frequency plots in 61 Ov neurons and 37 space-specific neurons of ICx (Fig. 5). These neurons met the following selection criteria: the frequency tuning curves of Ov neurons had a half-height width of
2 kHz, four or more stimulating frequencies had been tested for each neuron, and the fit of all the ITD curves passed the
2 test. Whereas ICx neurons showed the conspicuous frequency-independent tuning to ITD observed in previous studies (Takahashi and Konishi 1986
), Ov neurons did not. We quantified the deviation from linearity of the relationship between MIP and the stimulating frequency by computing the mean squared difference between the data points and the regression line (see METHODS). The mean squared difference in Ov (0.0022 ± 0.0049) was significantly larger than in ICx (0.00065 ± 0.00051, P < 0.029, t-test) indicating that MIP values across frequency are more aligned in the latter. To rely on periodic ITD curves for the measurement of MIP, we used tonal stimulation. However, narrowband stimulation, which is a better representation of a natural sound, yielded similar results (Fig. 6).
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DISCUSSION |
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The width of the main peaks in the ITD curves for broadband stimuli in Ov is significantly broader than in ICx neurons. Because we used broadband signals delivered dichotically, without compensating for the individual neuron's pattern of ITD tuning across frequencies, it remains to be tested if these neurons are more broadly tuned in natural conditions such as in free-field experiments. However, the weaker dependence of the width of the ITD peaks on the stimulating frequency in ICx than in Ov is consistent with nonlinear processes occurring in ICx, which sharpen the tuning to ITD (Fujita and Konishi 1991
).
The neurons of the owl's ICx perform across-frequency integration to extract the frequency independent ITD from its phase equivalents, i.e.; they resolve phase ambiguity (Mazer 1998
; Peña and Konishi 2000
; Takahashi and Konishi 1986
). This computation is necessary for the head-turn-orienting behavior toward a sound source in a unique and unequivocal direction (Saberi et al. 1999
). However, experimental evidence suggests that owls can use the forebrain representation to perform the same behavioral task (Knudsen and Knudsen 1996a
; Knudsen et al. 1993
; Wagner 1993
). Because some Ov neurons tend to integrate high frequencies along a constant ITD, this information is presumably available to the forebrain as well. This is consistent with multiunit studies in the forebrain that show frequency independent tuning to ITD in the high-frequency range (Miller and Knudsen 2003
).
Given that low frequencies contribute significantly to the ITD tuning across frequency in Ov neurons, the difference between the midbrain and forebrain processing of auditory space may rest in the use of different frequency bands to extract information related to sound direction. Recent studies in mammals do not find frequency independent ITD tuning, i.e., a characteristic delay, in the low-frequency range. These results have been explained by a convergence from more than one binaural coincidence detector line (McAlpine et al. 1998
). Other studies in mammals determined that a great proportion of thalamic neurons had characteristic delays at neither the peak nor the trough of the ITD curve (Stanford et al. 1992
), which is also consistent with convergence across ITD channels. On the other hand, the high-frequency neurons of the tectal pathway of barn owls show characteristic delays (Takahashi and Konishi 1986
) despite the ability to adjust the ITD tuning in a frequency-specific manner (Gold and Knudsen 2000
). Thus the owl's brain may be using ITD information differently at high and low frequencies. Because the barn owl can perform ITD detection in both high and low frequencies, it constitutes a good model to evaluate unifying hypotheses on sound localization of birds and mammals (Harper and McAlpine 2004
).
A question of biological importance is what information the spatially tuned areas of the midbrain and the forebrain encode that requires two distinct types of representation. The clustered arrangement of space-specific neurons described in some forebrain areas of the owl (Cohen and Knudsen 1994
, 1995
, 1998
; Knudsen et al. 1977
) indicates that the continuous representation of spatial cues observed in the midbrain and brain stem (Carr and Konishi 1990
; Knudsen 1982
; Knudsen and Konishi 1978
; Manley et al. 1988
; Mogdans and Knudsen 1993
, 1994
; Olsen et al. 1989
; Sullivan and Konishi 1986
; Wagner et al. 1987
) no longer applies in forebrain structures. Although the possibility of curved or distorted maps in Ov cannot be ruled out without combining the recording of the neurons with stimulation in the free field, our results are consistent with the absence of a topographic representation of space. Because the spatial dimensions of neural representations impose limitations on coding dimensions, an isomorphic two-dimensional map may no longer be possible if information other than the one in consideration is being represented or if the computation has changed. Presumably, the forebrain supports diverse and complex functions involving auditory spatial information. For example, it has been shown that the inactivation of the owl's auditory arcopallium interrupts memory-guided orienting responses (Knudsen and Knudsen 1996b
), and that the forebrain is involved in the identification and discrimination of complex auditory stimuli in mammals (Diamond and Neff 1957
; Diamond et al. 1962
; Geissler and Ehret 2004
; Heffner and Heffner 1984
; Petersen et al. 1988
; Poremba et al. 2004
; Zatorre et al. 1992
). Thus a different organization may be required to combine the representation of auditory space with other parameters of the sound. However, if the forebrain expands the number of variables used to compute auditory space itself in addition to frequency-independent coordinates of ITD and ILD, a departure from a continuous representation may also become necessary. The frequency-dependent tuning to ITD of Ov neurons described here is consistent with this viewpoint.
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GRANTS |
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ACKNOWLEDGMENTS |
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Present address of M. L. Pérez: Dept. de Fisiología, Facultad de Medicina, Montevideo, Uruguay.
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FOOTNOTES |
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Present address and address for reprint requests and other correspondence: J. L. Peña, Dept. of Neuroscience, Albert Einstein College of Medicine, Rose F. Kennedy Center, Rm 529, Bronx, NY 10461 (E-mail: jpena{at}aecom.yu.edu)
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REFERENCES |
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Carr CE and Konishi M. A circuit for detection of interaural time differences in the brain stem of the barn owl. J Neurosci 10: 32273246, 1990.[Abstract]
Cohen YE and Knudsen EI. Auditory tuning for spatial cues in the barn owl basal ganglia. J Neurophysiol 72: 285298, 1994.
Cohen YE and Knudsen EI. Binaural tuning of auditory units in the forebrain archistriatal gaze fields of the barn owl: local organization but no space map. J Neurophysiol 15: 51525168, 1995.
Cohen YE and Knudsen EI. Representation of frequency in the primary auditory field of the barn owl forebrain. J Neurophysiol 76: 36823692, 1996.
Cohen YE and Knudsen EI. Representation of binaural spatial cues in field L of the barn owl forebrain. J Neurophysiol 79: 879890, 1998.
Cohen YE and Knudsen EI. Map versus clusters: different representations of auditory space in the midbrain and forebrain. Trends Neurosci 22: 128135, 1999.[CrossRef][Web of Science][Medline]
Cohen YE, Miller GL, and Knudsen EI. Forebrain pathway for auditory space processing in the barn owl. J Neurophysiol 79: 891902, 1998.
Diamond IT, Goldberg JM, and Neff WD. Tonal discrimination after ablation of auditory cortex. J Neurophysiol 25: 22335, 1962.
Diamond IT and Neff WD. Ablation of temporal cortex and discrimination of auditory patterns. J Neurophysiol 20: 300315, 1957.
Fujita I and Konishi M. The role of GABAergic inhibition in processing of interaural time difference in the owl's auditory system. J Neurosci 11: 722739, 1991.[Abstract]
Geissler DB and Ehret G. Auditory perception vs. recognition: representation of complex communication sounds in the mouse auditory cortical fields. Eur J Neurosci 19: 10271040, 2004.[CrossRef][Web of Science][Medline]
Gold JI and Knudsen EI. Abnormal auditory experience induces frequency-specific adjustements in unit tuning for binaural localization cues in the optic tectum of juvenile owls. J Neurosci 20: 862877, 2000.
Goldberg JM and Brown PB. Response of binaural neurons of dog superior olivary complex to dichotic tonal stimuli: some physiological mechanisms of sound localization. J Neurophysiol 32: 613636, 1969.
Heffner H and Heffner RS. Temporal lobe lesions and perception of species-specific vocalizations by macaques. Science 226: 7576, 1984.
Harper NS and McAlpine D. Optimal population coding of an auditory spatial cue. Nature 430: 682686, 2004.[CrossRef][Medline]
Knudsen EI. Auditory and visual maps of space in the optic tectum of the owl. J Neurosci 2: 11771194, 1982.[Abstract]
Knudsen EI and Knudsen PF. Space-mapped auditory projections from the inferior colliculus to the optic tectum in the barn owl (Tyto alba). J Comp Neurol 218: 187196, 1983.[CrossRef][Web of Science][Medline]
Knudsen EI and Knudsen PF. Contribution of the forebrain archistriatal gaze field to auditory orienting behavior in the barn owl. Exp Brain Res 108: 2332, 1996a.[Web of Science][Medline]
Knudsen EI and Knudsen PF. Disruption of auditory spatial working memory by inactivation of the forebrain archistriatum in barn owl. Nature 383: 428431, 1996b.[CrossRef][Medline]
Knudsen EI, Knudsen PF, and Masino T. Parallel pathways mediating both sound localization and gaze control in the forebrain and midbrain of the barn owl. J Neurosci 13: 28372852, 1993.[Abstract]
Knudsen EI and Konishi M. A neural map of auditory space in the owl. Science 200: 795797, 1978.
Knudsen EI and Konishi M. Mechanisms of sound localization in the barn owl (Tyto alba). J Comp Physiol [A] 133: 1321, 1979.
Knudsen EI, Konishi M, and Pettigrew JD. Receptive fields of auditory neurons in the owl. Science 198: 12781280, 1977.
Manley GA, Köppl C, and Konishi M. A neural map of interaural intensity differences in the brain stem of the barn owl. J Neurosci 8: 26652676, 1988.[Abstract]
Mazer JA. How the owl resolves auditory coding ambiguity. Proc Natl Acad Sci USA 95: 1093210937, 1998.
McAlpine D, Jiang D, Shackleton TM, and Palmer AR. Convergent input from brain stem coincidence detectors onto delay-sensitive neurons in the inferior colliculus. J Neurosci 18: 60266039, 1998.
Miller GL and Knudsen EI. Adaptive plasticity in the auditory thalamus of juvenile barn owl. J Neurosci 23: 10591065, 2003.
Moiseff A. Bi-coordinate sound localization by the barn owl. J Comp Physiol 164: 637644, 1989.
Moiseff A and Konishi M. Neuronal and behavioral sensitivity to binaural time differences in the owl. J Neurosci 1: 4048, 1981.[Abstract]
Mogdans J and Knudsen EI. Early monaural occlusion alters the neural map of interaural level differences in the inferior colliculus of the barn owl. Brain Res 613: 2938, 1993.
Mogdans J and Knudsen EI. Representation of interaural level differences in the VLVp, the first site of binaural comparison in the barn owl's auditory system. Hear Res 74: 148164, 1994.[CrossRef][Web of Science][Medline]
Olsen JF, Knudsen EI, and Esterly SD. Neural maps of interaural time and intensity differences in the optic tectum of the barn owl. J Neurosci 9: 25912605, 1989.[Abstract]
Peña JL and Konishi M. Cellular mechanisms for resolving phase ambiguity in the owl's inferior colliculus. Proc Natl Acad Sci USA 97: 1178711792, 2000.
Peña JL and Konishi M. Auditory spatial receptive fields created by multiplication. Science 292: 249252, 2001.
Peña JL and Konishi M. From postsynaptic potentials to spikes in the genesis of auditory spatial receptive fields. J Neurosci 22: 56525658, 2002.
Peña JL, Viete S, Albeck Y, and Konishi M. Tolerance to sound intensity of binaural coincidence detection in the nucleus laminaris of the owl. J Neurosci 16: 70467054, 1996.
Peña JL, Viete S, Funabiki K, Saberi K, and Konishi M. Cochlear and neural delays the for coincidence detection in owls. J Neurosci 21: 94559459, 2001.
Petersen SE, Fox PT, Posner MI, Mintun M, and Raichle ME. Positron emission tomographic studies of the cortical anatomy of single-word processing. Nature 33 1: 585589, 1988.
Poremba A, Malloy M, Saunders RC, Carson RE, Herscovitch P, and Mishkin M. Species-specific calls evoke asymmetric activity in the monkey's temporal poles. Nature 427: 448451, 2004.[CrossRef][Medline]
Proctor L. Characterization of the Auditory Thalamic Nucleus of the Barn Owl (PhD thesis). Pasadena, CA: California Institute of Technology, 1993.
Proctor L and Konishi M. Representation of sound localization cues in the auditory thalamus of the barn owl. Proc Natl Acad Sci USA 94: 1042110425, 1997.
Rose JE, Gross NB, Geisler CD, and Hindi JE. Some neural mechanisms in the inferior colliculus of the cat which may be relevant to localization of a sound source. J Neurophysiol 29: 288314, 1966.
Saberi K, Takahashi Y, Farahbod H, and Konishi M. Neural bases of an auditory illusion and its elimination in owls. Nat Neurosci 2: 656659, 1999.[CrossRef][Web of Science][Medline]
Stanford TR, Kuwada S, and Batra R. A comparison of the time sensitivity of neurons in the inferior colliculus and thalamus of the anesthetized rabbit. J Neurosci 12: 32003216, 1992.[Abstract]
Sullivan WE and Konishi M. Neural map of interaural phase difference in the owl's brain stem. Proc Natl Acad Sci USA 83: 84008404, 1986.
Takahashi T and Konishi M. Selectivity for interaural time difference in the owl's midbrain. J Neurosci 6: 34133422, 1986.[Abstract]
Takahashi T, Wagner H, and Konishi M. Role of commissural projections in the representation of bilateral auditory space in the barn owl's inferior colliculus. J Comp Neurol 281: 545554, 1989.[CrossRef][Web of Science][Medline]
Viete S, Peña JL, and Konishi M. Effects of interaural intensity difference on the processing of interaural time difference in the owl's nucleus laminaris. J Neurosc 17: 18151824, 1997.
Wagner H. Sound-localization deficits induced by lesions in the barn owl's auditory space map. J Neurosc 13: 371386, 1993.[Abstract]
Wagner H, Takahashi T, and Konishi M. Representation of interaural time difference in the central nucleus of the barn owl's inferior colliculus. J Neurosci 7: 31053116, 1987.[Abstract]
Yin TCT and Kuwada S. Binaural interaction in low-frequency neurons in inferior colliculus of the cat. III. Effects of changing frequency. J Neurophysiol 50: 10201042, 1983.
Zatorre RJ, Evans AC, Meyer E, and Gjedde A. Lateralization of phonetic and pitch discrimination in speech processing. Science 256: 846849, 1992.
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