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1Department of Physiology and Biophysics, Neuroscience Research Group, Faculty of Medicine, University of Calgary, Calgary, Alberta, Canada; and 2Department of Neurobiology, University of Ulm, Ulm, Germany
Submitted 5 April 2004; accepted in final form 17 August 2004
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ABSTRACT |
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 TOP ABSTRACT INTRODUCTIONMETHODSRESULTSDISCUSSIONGRANTSACKNOWLEDGMENTSREFERENCES |
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INTRODUCTION |
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TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONGRANTSACKNOWLEDGMENTSREFERENCES |
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; Liberman 1978) but show great variability in the central auditory system, including primary-like, closed, tilted, narrow, broad, symmetrical, unsymmetrical, and multi-peaked (complex) shapes. These various shapes of the FTCs are the result of the integration of excitatory and inhibitory inputs over a broad frequency range (e.g., Casseday and Covey 1992; Egorova et al. 2001; Ehret and Merzenich 1988; Lu and Jen 2001; Suga 1969; Sutter et al. 1999; Yang et al. 1992; Young et al. 1988).
The auditory cortex (AC) can influence, via corticofugal projections, neural response properties to sounds in lower centers of the ascending auditory pathway. Thus cortical plasticity induced by learning or state of vigilance (e.g., Edeline 2003; Scheich et al. 1997; Suga et al. 2002; Weinberger 1998) may feed back to the ascending auditory system. For the central nucleus of the inferior colliculus (ICC), such feedback has been shown in electrophysiological studies on bats (Ma and Suga 2001; Sun et al. 1989; Yan and Suga 1996, 1998; Zhang and Suga 1997; Zhang et al. 1997; Zhou and Jen 2000a, b) and other mammals (Syka and Popelá
; 1984; Syka et al. 1988; Torterolo et al. 1998; Yan and Ehret 2001, 2002). Focal stimulation or suppression in the mustached bat's fovea region, the Doppler-shifted-CF processing area (Suga and Jen 1976), of the AC lead to a shift of best frequencies (BFs) of ICC neurons away from or toward the frequency of the cortical tonotopy where the cortical output is manipulated (Zhang and Suga 2000; Zhang et al. 1997). Electrical stimulation at a given frequency of the cortical tonotopy of the big brown bat shift the BFs of ICC neurons toward the stimulated cortical frequency without much influence on the tuning curve shape (Gao and Suga 2000; Yan and Suga 1998). Such an egocentric shift is also seen in the mouse ICC (Yan and Ehret 2001, 2002). Altogether corticofugal modulation greatly shifts ICC BFs. This should practically alter the FTC shapes. So far, it is not clear how corticofugal activity might change FTC shapes or selectivity of frequency tuning and thus the spectral analysis of sounds by neurons in the ICC.
Here, we quantified the influence of the AC on the FTCs of ICC neurons for the same neurons before and after cortical activation. The FTC classification according to Egorova et al. (2001) was introduced to analyze possible effects of corticofugal modulation on neurons of different FTC shape in a quantitative way. This classification (classes I–IV) contains all seven classes of FTCs from a previous study on the ICC of the mouse (Ehret and Moffat 1985) and is compatible in the relative numbers of neurons per class with measurements in the cat ICC (Ehret and Merzenich 1988) and primary auditory cortex (Sutter 2000). We show that corticofugal activation not only changes neuronal BFs and minimum thresholds (MTs) but also has differential effects on the sharpness of frequency tuning. The direction (sharpness increase or decrease) and magnitude of the effect depends on the FTC shape before cortical activation. Our data support the hypothesis that the auditory cortex significantly modulates local balances between excitation and inhibition in the auditory midbrain and thus specifies frequency tuning to preferentially process sounds of behavioral significance that have repeatedly elicited activity at a certain spot of the tonotopy of the primary AC before.
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METHODS |
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TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONGRANTSACKNOWLEDGMENTSREFERENCES |
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Twenty-five female house mice (Mus musculus, outbred strain, NMRI) aged 6–12 wk and weighing 23–31 g were used in the present experiments. All animals were housed with littermates of the same sex in plastic (Makrolon) type III cages with free access to food and water and with a 12-h day-night cycle. Animals were anesthetized with mixture of ketamine (Ketavet, 120 mg/kg ip) and xylazine (Rompun, 5 mg/kg ip). Additional doses of ketamine (35 mg/kg) and xylazine (1 mg/kg) were applied when necessary to keep the animal in a quiet and motionless state during the experiment. The scalp overlaying the dorsal skull was removed, and the animal's head was fixed in a head holder by rigidly clamping between the palate and nasal/frontal bones. The mouth bar was adjusted to align bregma and lambda points of the skull in a horizontal plane. Two holes of 
2 mm in diameter were drilled in the skull to expose the ICC and AC, both of the left side, which was contralateral to the position of the loudspeakers. The dura over the colliculus was removed. After surgery, the animal was placed in an electrically shielded and sound-attenuated chamber on a feedback-controlled heating pad that maintained its rectal temperature at 37 ± 1°C during the experiment. At the end of the experiment, the still-anesthetized animal was killed by cervical dislocation. The experiments were carried out in accordance with the European Communities Council Directive (86/609/EEC) and were approved by the appropriate authority (Regierungspräsidium Tübingen, Germany).
Acoustic stimulation
Series of tone bursts of 60-ms length (5-ms linear rise and decay times) and 250-ms intervals were generated by a voltage-controlled frequency generator (Wavetek 193) and an electronic switch. Frequencies were read with a counter (Tektronix DC504) and the waveforms were displayed on an oscilloscope (Tectronix 5111A). Series of DC voltages, generated with a CED 1401plus and Spike2 software, were fed to the VCG IN of the frequency generator to systematically vary its output frequency. Tone bursts were adjusted in amplitude (Kenwood RA 920A) and sent via a power amplifier (Denon PMA 1060) to a dynamic loudspeaker (Thiel C2 33/8) and via a voltage amplifier (Hewlett-Packard, 465A) and power supply to a condenser loudspeaker (Machmerth et al. 1975). Both loudspeakers were placed 45° to the right and 40 cm away from the mouse sagittal plane (Egorova et al. 2001). Sound amplitude, expressed in dB sound pressure level (SPL), was calibrated at the right ear of the animal with a Bruel and Kjaer condenser microphone (No. 4135) with measuring amplifier (No. 2636). With the same measuring system and a spectrum analyzer (Ono Sokki CF-5220), the sound spectrum was checked for distortion products. The frequency spectrum of the sound field at the ear of the animal was flat within ±7 dB between 3 and 75 kHz and distortion products of the speakers were 
35 dB below the levels of the generated tones.
Electrical stimulation of the auditory cortex
Cortical stimulation was the same as in Yan and Ehret (2002). A parylene-insulated tungsten microelectrode (WPI TM33C20KT, impedance 2 M
) was used to locate the auditory cortex and to roughly determine the tonotopic organization of the primary auditory field (compare Stiebler et al. 1997). At a certain location of the tonotopy of the primary auditory field (primary auditory cortex, AI), the electrode was driven into the cortex perpendicularly to the brain surface, and the BF and MT were determined audiovisually in layer III/IV of the cortex. Then the electrode was advanced to a depth of 700 µm below the surface of the AI for stimulation of the cortical layer V (Paxinos and Franklin 2001; Sidman et al. 1971). Layer V pyramidal cells of the AI send massive descending projections to the ICC (Doucet et al. 2003). An indifferent electrode was placed on the brain surface just beside the stimulating electrode. A 1-ms long monophasic electrical pulse with 500-nA constant negative current was created by a constant current isolator (WPI A360) that was triggered with the CED 1401-plus. Every electrical pulse was synchronized to the offset of a tone burst of which frequency and amplitude was set at the BF and 10 dB above MT of the measured cortical neurons, respectively (Yan and Ehret 2002). The combined acoustic and electric stimuli were delivered to the cortex through the stimulating electrode at a rate of 4/s for 7 min. With regard to recommended microstimulation of the human cortex (Dostrovski 1999), we used the same type of electrode and stimulus at about one-third of current density over time.
This stimulation paradigm ensured a constant relationship between acoustical and electrical stimulation in which the AI neurons were never electrically stimulated before the tone-evoked response had occurred (response latencies of AI neurons are 10–30 ms for tone bursts with 5-ms rise/fall times) (Phillips 1998). Thus the contingency of the tonal and electrical stimulation is comparable with a conditioning paradigm using the electrical pulses as an unconditioned stimulus evoking a cortical response and the tone bursts as the stimuli to be conditioned (conditioned stimulus). The cortical response to every tone stimulus is reinforced by a presumably strong response to the electric pulse.
Data acquisition
Activities of neurons in the central nucleus of the ICC, located according to their coordinates relative to the lambda point of the skull (see Egorova et al. 2001; Stiebler and Ehret 1985), were recorded by using the same type of tungsten electrodes as mentioned above. Multiunit recordings were amplified 10,000 times and filtered with a band-pass of 0.3–10 kHz (WPI DAM 80 preamplifier and Rockland 852 filter). Once the recording was stable and the BF was estimated audiovisually, frequency-amplitude scanning was used to measure the frequency-tuning curves of collicular neurons. One frequency scan consisted of 21 blocks. In block 1–20, the frequency of the tone burst was systematically varied in steps of 1 or 0.5 kHz. The last block had no stimulus. Identical scans were repeated five times with 300-ms intervals at a given amplitude. After a 5-s interval, the frequency scans were repeated at another amplitude. Frequency scans were done at amplitude steps between 0 and 100 dB attenuation with 5 dB/step. Responses of collicular neurons were monitored on the oscilloscope and stored together with tone-trigger signals on tapes by a RACAL 4-channel tape recorder. Without moving the recording electrode, the whole recording procedure was done immediately before and 3 h after cortical stimulation. We have shown already that with this stimulus paradigm, the maximum effects of cortical stimulation were reached at 2–4 h after stimulation (Yan and Ehret 2001). In this way, we obtained one set of data (1 cortical stimulation site, 1 collicular recording site) from each animal.
Control measurements were done in two mice either with only tone stimulation not paired with electrical stimulation of the primary auditory cortex or with paired (tone + electrical) stimulation of non-AI cortex (dorsoposterior field) (see Stiebler et al. 1997).
Data processing
Stimulus, trigger, and data files recorded on tapes were played back and analyzed off-line with a DISCOVERY data-acquisition system (DATAWAVE Tech.). Single-unit action potentials, usually of two to five units, were isolated from the multiunit recording by using eight parameters of the action-potential waveform, i.e., peak, valley, height, width, peak time, valley time, and two user-defined time-voltage values (see details in Yan et al. 2002, 2003). Single-unit data were automatically sorted and stored in an UFF file (DATAWAVE Tech) and eventually displayed in dot rasters, peristimulus time histograms (PSTs), and cumulative PSTs (PSTCs). Spike numbers of each frequency-amplitude block were counted based on five identical stimuli. The excitatory frequency-tuning curve was derived from threshold responses in each frequency-amplitude block. The criterion for threshold was the boundary between a block showing more than one spike and a block showing no response. In case of the influence of spontaneous activity, the threshold was set between blocks differing by at least one spike depending on the spontaneous rate (Suga et al. 1997).
The FTC shapes before and after cortical stimulation were characterized and compared on the basis of the following measures: 1) MT: the lowest dB SPL producing an excitatory response; 2) BF: the frequency at the MT; 3) bandwidth of frequency tuning: the width in kHz of the FTC at 10, 30, 50, and 70 dB above MT; 4) quality factor (Q value): Q10, Q30, Q50, and Q70 were calculated by dividing the BF by the bandwidth at 10, 30, 50, or 70 dB above threshold (BW10, BW30, BW50, or BW70), respectively; 5) slopelow and slopehigh: slopes at the low-frequency (slopelow) and high-frequency (slopehigh) sides of FTCs were calculated in dB/octave by using the values at MT/BF and the frequency and SPL values at 60 dB above MT; 6) level tolerance: as a measure to express the change of FTC bandwidth with increasing SPL, the FTC bandwidth at 60 dB above MT was divided by the bandwidth at 10 dB above MT; 7) asymmetry index (ASI): The ASI was calculated as ASI = (a – b)/(a + b) with a representing the bandwidth between BF and the low-frequency (left) side of the FTC and b the bandwidth between BF and the high-frequency (right) side of the FTC, both at 60 dB above MT. This asymmetry index leads to values between -1 and +1. When the ASI is zero, the FTC is symmetric with reference to the BF. The corticofugally evoked changes in all of these parameters were expressed by the differences in the values before and after cortical activation (poststimulus minus prestimulus).
Statistics
The t-test or nonparametric U test, paired t-test or Wilcoxon matched-pairs signed-rank test, 
2 test, and one-way ANOVA (all 2-tailed) were employed to compare differences among groups of data. A P value <0.05 was considered to be of significant difference. Except stated otherwise, average data, and their variability are presented in the text and the figures as means ± SD.
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RESULTS |
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TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONGRANTSACKNOWLEDGMENTSREFERENCES |
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Because BF shifts as a function of the BF difference between collicular and cortical neurons were independent of the neuronal class as shown in Fig. 3, BF shifts of class I–III neurons were plotted as a function of the BF difference between cortical and collicular neurons (Fig. 4A). Positive (negative) BF shifts were seen in collicular neurons with BFs lower (higher) than stimulated cortical BFs. The relationship between BF shift and BF difference was linear (n = 66) for BF differences between about -10 to +14 kHz (Fig. 4A) as has been shown by Yan and Ehret (2002). The larger the BF difference between cortical and collicular neurons, the larger was the shift in collicular BFs (Fig. 4A). Hence, the average absolute difference between collicular and cortical BFs was significantly larger before than after cortical activation, 6.0 ± 4.6 versus 3.4 ± 3.9 kHz (P < 0.001). The shift in collicular BFs was independent from the classes of collicular neurons.
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Changes in sharpness of collicular frequency tuning
The bandwidths of collicular FTCs systematically changed after cortical activation according to the shifts in collicular BFs and MTs. These changes are shown for four amplitude levels above MT in Fig. 5 (A, a–d, and B, a–d). When the BF showed no or little (between –4 and +2 kHz) shift, bandwidths became either wider (positive values) or narrower (negative values; Fig. 5A). Larger BF shifts to either higher or lower BFs caused a widening of the FTC bandwidths at all amplitude levels. When the BF shifted to lower values, the increase in bandwidths was systematically related to the shift in BFs for measurements taken at 10 and 30 dB above threshold (r = 0.53, P < 0.05 and r = 0.58, P < 0.01, respectively). This is indicated by the regression lines in Fig. 5A, a and b.
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The preceding changes in sharpness of collicular tuning were explicitly different among the neurons of the three classes of tuning curves. This is quantified in Fig. 6. Class I neurons significantly increased the bandwidths of their FTCs measured at 10, 30, and 50 dB above MT (Fig. 6A, left) after compared with before cortical stimulation. At the same time, the Q values (BF/FTC-bandwidth at a given level above MT) did not show a significant change or even increased at 70 dB above MT (Fig. 6A, right). Class II neurons showed large increases of bandwidths and corresponding decreases of Q values (Fig. 6B), i.e., FTCs of class II neurons broadened after cortical stimulation. On the other hand, FTC bandwidths of class III neurons generally decreased and Q values increased (Fig. 6C), leading to a sharper tuning in many of these neurons. By definition, a bandwidth increase must lead to a Q-value decrease, if the BF of a neuron remains constant. Because BFs of most collicular neurons from all classes of tuning curves changed after cortical stimulation (Figs. 3, 4A, and 5A), changes in FTC bandwidths and in Q values are not equivalent measures here.
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Classes I–III of collicular neurons are defined and discriminated by the slopes of their low-frequency (slopelow) and high-frequency (slopehigh) sides (Fig. 1, A and C). Figure 7 shows the slopelow and slopehigh of class I–III neurons before (
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) cortical activation. In class I neurons, slopelow and slopehigh were either increased or decreased resulting in a larger variation of slopes after cortical activation (Fig. 7A). The average slopelow and slopehigh before cortical activation were 74.75 ± 28.8 and 377.63 ± 131.0 dB/octave, respectively. They changed to 71.25 ± 71.0 and 574.55 ± 502.4 dB/octave, respectively, after cortical activation. Because of the large increase of variability of slopes, these changes were not statistically significant. Cortical activation decreased slopelow values of class II neurons (Fig. 7B) from 386.97 ± 292.8 to 148.44 ± 79.1 dB/octave (P < 0.001) and slopehigh values from 1081.21 ± 640.9 to 855.36 ± 918.4 dB/octave (0.05 < P < 0.06). In class III neurons, both slopelow and slopehigh were increased from 81.49 ± 18.9 to 117.98 ± 77.8 dB/octave (nonsignificantly) and from 154.07 ± 58.3 to 302.01 ± 165.9 dB/octave (P < 0.001), respectively.
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2-test, P < 0.001). Qualitatively, about two-thirds of the class II neurons lost their sharp tuning, whereas about two-thirds of the class III neurons became much more sharply tuned after cortical activation. Table 1 summarizes the proportions of neurons in the four FTC classes before and after cortical activation. Clearly, the proportions of class II neurons with sharp tuning at high- and low-frequency sides and class III neurons with broad tuning at high- and low-frequency sides decreased. In contrast, the percentage of class I neurons with broad tuning at low-frequency side and sharp tuning at high-frequency side was increased.
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The changes in frequency tuning after cortical activation (changes of bandwidths, Q values, slopes of tuning curves) affect the level tolerance, i.e., the level dependence of the widths of the FTC, of collicular neurons. A measure of level tolerance is the ratio between the FTC bandwidth at 10 dB and 60 dB above threshold. A ratio close to 1.0 indicates a high level tolerance, i.e., a frequency selectivity that is rather independent of the sound level. Figure 9 shows that the average level tolerance of class II neurons was significantly decreased (P < 0.05), the level tolerance of class III neurons significantly increased (P < 0.05) after cortical stimulation. On average, the level tolerance of class I neurons was not changed.
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Asymmetry indexes differed significantly between the groups of neurons (ANOVA, P < 0.001; t-test for each of the comparisons P < 0.01). On average, neurons of class I had an asymmetry index (ASI) of 0.66 ± 0.12, class II neurons of 0.45 ± 0.21, and class III neurons of 0.27 ± 0.24. This indicates that more class III neurons than neurons of the other classes had rather symmetric FTCs (ASI closer to 0) and even negative ASIs (high-frequency branch of the FTC wider than the low-frequency branch); this was never the case in the other neurons (Fig. 10). Class I neurons had the most asymmetric FTCs with the low-frequency branch always being much wider than the high-frequency branch (ASI has positive, large values). Figure 10 shows how collicular ASIs change as a function of the original ASI. A positive change of the ASI indicates that the low-frequency branch widened and/or the high-frequency branch narrowed more than the respective other branch after the cortical activation. A negative change of the ASI occurred when the low-frequency branch of the FTC narrowed and/or the high-frequency branch widened more than the respective other branch. There was a significant correlation between ASI change and original ASI for class II neurons only (Fig. 10B). This regression line shows that class II neurons of high or low asymmetry before cortical activation tended to become more or less symmetric, respectively, after cortical activation.
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Neither acoustical stimulation alone (2 neurons examined) nor the pairing of acoustical stimulation with electrical stimulation in the dorsoposterior field of the AC (3 neurons examined) changed the BFs, MTs, or shapes and classes of FTCs of ICC neurons. Two neurons were of class I, one of class II, and two of class III. The shapes of the FTCs of the neurons were compared by superimposing the FTC plots.
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DISCUSSION |
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TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONGRANTSACKNOWLEDGMENTSREFERENCES |
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Studies on bats have shown only some minor plasticity of frequency tuning of ICC neurons in response to repetitive tone stimulation without electrical reinforcer (Ma and Suga 2003; Suga et al. 2000; Yan and Suga 1998). The bats were stimulated by tone bursts at a rate of 10/s for 30 min. In our control experiment with only acoustical stimulation, tone bursts were presented at a much lower rate (4/s) for a much shorter time (7 min) than in the bats, so that we did not expect and actually did not observe any changes in frequency tuning to acoustic stimulation alone.
The here-applied pairing of tone bursts with electrical stimulation for the activation of the primary auditory cortex at a given location of its tonotopy had profound effects on BFs (Yan and Ehret 2001), MTs, tuning and dynamic ranges (Yan and Ehret 2002), and frequency tuning curves in the ICC (present study) taken 3 h after the conditioning of the AC. Shifts of BFs in the ICC had not fully recovered 8 h after cortical conditioning (Yan and Ehret 2001). Such a long phase of plasticity in the auditory midbrain induced by auditory cortical conditioning seems not to be reported before.
There are immediate effects of local electrical stimulation of the AC on tone responses in the ICC. These corticofugal effects are excitatory or inhibitory, occur at a short latency, and disappear within milliseconds or seconds (Bledsoe et al. 2003; Jen et al. 1998) or 30 min (Zhou and Jen 2000b) after the end of AC stimulation. Corticofugal effects with regard to inducing BF shifts in the ICC last for a maximum of about 3 h after conditioning the AC with electrical stimulation or combined acoustical and electrical stimulation (Ma and Suga 2001; Yan and Suga 1998; Zhang and Suga 2000). In the cases of pairing acoustical with electrical stimuli (Yan and Suga 1998; Zhang and Suga 2000), four equally spaced electrical pulses were presented over the first 6 ms of the 20-ms-long tone bursts. Considering tone-response latencies of AI neurons of >10 ms (e.g., Goldstein and Abeles 1975; Phillips 1998) the electrical stimulation of the AC had ended before the AC could respond to the tone. Hence, this is a case of backward conditioning of AC neurons, which, in general, is a very ineffective conditioning strategy (e.g., Tarpy and Mayer 1978). Thus it can be understood that the combined stimulation (electric and acoustic) of the AC did not add in effect to the changes produced by electrical stimulation alone (Yan and Suga 1998).
If an effective forward conditioning is used by, for example, presenting tone bursts followed by an aversive stimulus (electrical leg stimulation) (Gao and Suga 1998, 2000; Ji et al. 2001) or tone bursts followed by electrical stimulation of the basal forebrain (Bakin and Weinberger 1996; Bjordahl et al. 1998; Kilgard and Merzenich 1998; Ma and Suga 2003), changes in BFs and response strength of neurons in the AC are lasting longer than 3 h and, depending on the stimulation parameters, even longer than 24 h. However, conditioning effects on neurons in the ICC still last for less than 3 h (Gao and Suga 1998, 2000; Ji et al. 2001) or less than 5 h (Ma and Suga 2003). In our stimulus paradigm, the plastic changes in ICC neurons last >8 h. The presumably decisive differences between the above-mentioned and our forward conditioning paradigm concern the presentation of the reinforcing stimulus to the AC. Different from the reinforcing electrical leg stimulation or basal forebrain stimulation, the stimulus in our study is a direct stimulation of particular loci of the AC where the neuronal BF represented the frequency of the conditioned tone. We propose that this cortical congruence of acoustical with electrical stimulation in a forward conditioning paradigm is responsible for the long-lasting plasticity in the ICC observed here. This hypothesis has to be tested in further experiments.
Contribution of cortical and local factors to ICC plasticity
The primary auditory cortex (AI) is apparently responsible for the plastic changes in the ICC frequency tuning because activation of other auditory cortical areas does not affect the frequency tuning of ICC neurons as shown in the present (control with stimulation in the dorsoposterior field) and other reports (Yan and Suga 1996; Zhang and Suga 1997). Further, inactivation of the AI by application of muscimol before the cortical conditioning abolishes changes in frequency tuning in the ICC (Gao and Suga 1998). This shows that corticofugal influence is necessary for the induction of collicular plasticity in the frequency domain. If the AI is inactivated, however, after changes of frequency tuning in the ICC have been established according to cortical conditioning, these changes persist without further corticofugal control for the same time as in the case of the intact AC (Gao and Suga 1998). This suggests that the ICC has its own mechanisms for maintaining plasticity of frequency tuning independent of permanent corticofugal feedback. Provided that the corticofugal system is working, it seems even possible that neurons of the ICC can change their frequency tuning independently of whether BF changes in the AC in response to conditioning occur or not because suppression of cholinergic effects by application of atropine to the AC prevents BF shifts in response to conditioning in the AC but not in the ICC (Ji et al. 2001). Taken together, these data suggest that plasticity of frequency tuning in the ICC is both under corticofugal and local control.
Corticofugal and local factors of plasticity of frequency tuning in the ICC are also evident from our present data. The cortical factors are demonstrated by the systematical relationships of the changes in ICC BFs and MTs to the differences between cortical and collicular BFs or MTs (Figs. 2–4). If BFs and MTs of collicular neurons are very similar to those of the activation center of the cortex, cortical activity does not change the average identity of collicular neurons, not BFs or MTs or properties of frequency tuning (Fig. 4, A and B, values at 0 BF difference; Fig. 5, A and B, values at 0 BF or MT shift). If BFs and/or MTs are different, collicular neurons mostly lose their identity with regard to BF, MT, and shape of FTC. As a general effect, changes in FTC bandwidths (Fig. 5) appear to be linked to MT shifts because FTCs tend to sharpen (decrease of bandwidths) when MTs in the ICC are decreased (negative shifts in Fig. 5B) or to broaden when MTs are increased (positive MT shifts in Fig. 5B).
The local factors are demonstrated by the fact that many details of the plasticity of frequency tuning in the ICC depend on the tuning-curve class of particular neurons (Figs. 6–10). Neurons in the four tuning-curve classes largely reflect local properties of excitatory and inhibitory inputs to the neurons (Egorova et al. 2001) and neurons of classes II and III are distributed along spatial gradients on frequency-band laminae of the ICC (Ehret et al. 2003; Hage and Ehret 2003). Neurons of just these two classes respond differently to cortical conditioning. FTCs of class II neurons tend to broaden, whereas those of class III neurons to sharpen (Fig. 6, B and C, Q values) in both classes more or less asymmetrically with regard to the BF. The steeper the slopes of the FTCs are before cortical activation (Fig. 8), the larger are these asymmetric changes. The general result of all these changes is an assimilation of the tuning-curve shapes of class II and III neurons to the shapes of class I neurons (increase in the number of class I neurons, Table 1) and of the level tolerances among the neurons of the different classes (Fig. 9) after cortical stimulation.
The classification of FTC shapes must be understood as a simplified method to analyze the continuous variability of tuning-curve shapes and their alterations by corticofugal modulation. The criteria for the assessment of the FTC shapes into four classes and the percentages of neurons in classes found here (Fig. 1) are consistent with earlier studies on the ICC of the anesthetized mouse (Egorova et al. 2001; Ehret et al. 2003; Hage and Ehret 2003), cat (Ehret and Merzenich 1988), and guinea pig (Le Beau et al. 2001). The classification of ICC tuning-curve shapes of the decerebrated cat into three classes by Ramachandran et al. (1999) is based on excitatory FTCs and inhibition of spontaneous activity by tone bursts. The proportions of neurons in FTC classes comparable with ours are very different. For example, 70% of ICC neurons in the decerebrated cat have closed FTCs compared with only 5% in the anesthetized cat (Ehret and Merzenich 1988) and 8% in the anesthetized mouse (Egorova et al. 2001). Whether anesthesia in our present experiment or the lack of corticofugal influences in the decerebrated cat has a significant influence on the assessment of tuning-curve shapes (and their plasticity) is subject of further study.
Suggested mechanisms of corticofugal control
Direct glutamatergic projections from the primary auditory cortex to the ICC (Feliciano and Potashner 1995) appear to be weaker than projections to the pericentral collicular nuclei (mainly data from cats and rats) (e.g., Herbert et al. 1991; Huffman and Henson 1990; Winer et al. 1998) but still they are substantial and topographically arranged (Saldaña et al. 1996). Corticofugal fibers end in the ICC with excitatory synapses predominantly at the distal dendrites of collicular neurons of very similar BF, which may themselves be excitatory or inhibitory (GABAergic) (Saldaña et al. 1996; see also discussion there). Thus corticofugal innervation has a direct modulatory influence on neurons in the ICC that may facilitate the responses of neurons of matched BF and MT without altering their FTC shapes (Fig. 3, A2, B2, and C2). If the corticofugal activity is acting on a neuron of matched BF but nonmatched, i.e., higher, MT, the corticofugal excitation could lower the neuron's tone threshold as it is seen in many class III neurons (Fig. 4C and 5B). In the case of neurons of nonmatched BF, there is an inhibitory net-effect causing an increase of tone response threshold (Fig. 4C) and a resulting increase in the tuning-curve bandwidth (Fig. 5B). The reason for this inhibitory net effect may then be the missing excitatory corticofugal influence because of BF mismatch and an inhibitory influence on the examined neuron by corticofugal excitation of GABAergic neurons of a frequency-band lamina in the neighborhoods of the lamina containing the examined neuron. Previous studies have shown GABAergic inhibition intrinsic to the ICC influencing excitatory and inhibitory receptive fields of ICC neurons (e.g., Faingold et al. 1989; Fuzessery and Hall 1996; Le Beau et al. 1996; Lu and Jen 2001; Palombi and Caspary 1996; Pollak and Park 1993; Yang et al. 1992). That is, inhibition between frequency-band laminae has been show as well as GABAergic neurons that could mediate this inhibition (e.g., Oliver et al. 1994). Altogether, the plastic changes in ICC neurons evoked by local cortical conditioning follow a center-surround pattern (center is excitatory, surround is inhibitory) as described before (Yan and Ehret 2002).
Differential reshaping of FTCs may also be approached by local differences of corticofugal effects on the three-dimensional ICC. Class III neurons are found preferentially in the periphery of a physiologically defined frequency-band lamina of the ICC with a gradient of decreasing numbers toward its core (Ehret et al. 2003; Hage and Ehret 2003). Thus class III neurons are most abundant in the lateral, caudal, and medial ICC. These locations are bordered by the pericentral nuclei of the ICC that receive the most intense innervation by corticofugal fibers (e.g., Huffman and Henson 1990; Herbert et al. 1991; Hofstetter and Ehret 1992; Winer et al. 1998). When the corticofugal projections excite the GABAergic neurons in the pericentral nuclei projecting to the ICC (Jen et al. 1998, 2001), we can expect the largest inhibitory effects of cortical activation to occur in the peripheral regions of the ICC, just where class III neurons are most abundant (Ehret et al. 2003; Hage and Ehret 2003), leading to the observed increase of FTC sharpness (Figs. 6 and 7).
In our previous study (Yan and Ehret 2002), we discussed the possibility that part of the corticofugally induced changes in the ICC could be mediated via corticofugal influences on the cochlea, cochlear nucleus and/or superior olivary complex. Results from electrical stimulation (100 nA) at a rate of 5/s for 7 min in the Doppler-shifted CF-processing area of the mustached bat's AC have shown corticofugally induced BF shifts in the ICC (Zhang and Suga 2000) but no influence on the cochlear microphonic potential (Xiao and Suga 2002). Changes in the cochlear microphonic potentials were seen only after electrical pulses were delivered at a rate of 33/s (Xiao and Suga 2002). From these data, one could assume no corticofugal effect of our stimulus paradigm on cochlear hair cells if looking only at the rate of 4/s and a duration of 7 min of our electrical stimulation (500 nA). By considering, however, that we stimulated the AC effectively in a forward-conditioning paradigm with pairs of tones and electrical pulses, corticofugally mediated changes even down to the cochlear level cannot be ruled out and are investigated now.
Functional considerations
Although the presently applied cortical conditioning paradigm with pairs of tones and electrical pulses is artificial and may have produced stronger corticofugal effects than expected from the use of biological stimuli for conditioning, our data certainly show that the AI can change frequency filtering in the auditory midbrain, which is specified differently for neurons of different tuning-curve shapes. Considering the center-surround organization of ICC plasticity in the frequency domain, the processing of a frequency of interest in a sound representing the BFs of activated cortical neurons, is enhanced in the ICC (BF-matched neurons). The inhibition of BF-unmatched neurons in the surround is maximally about one critical band wide toward both lower and higher frequencies with reference to a given BF (Yan and Ehret 2001). This width of inhibition resembles the BF distance between neighboring frequency-band laminae of the ICC (Schreiner and Langner 1997). This close relationship between the bandwidths of frequency resolution of the auditory system (expressed by the psychophysical measure of critical bands) and the frequency bandwidths of corticofugal adjustment of FTCs in the ICC suggests that a main function of auditory cortical efferents is to support spectral resolution of sounds. Thus corticofugal control in the center of frequency-band laminae of the ICC, working mainly via influences on neurons of class I and II tuning curves, seems to be an important factor to improve the perception of frequency components of biological significance, especially in background noise.
In the periphery of BF-matched frequency-band laminae, corticofugal influences decrease the tone-response thresholds and increase the frequency selectivity of class III neurons. These neurons seem to be specialized for time-domain processing because their spatial distribution on frequency-band laminae coincides with distributions of onset-spiking neurons that are able to respond to fast changes of frequency sweeps (Hage and Ehret 2003). Thus the auditory cortex sensitizes these class III neurons by decreasing their response threshold and specifying their frequency tuning to respond to fast changes in frequencies similar to the BF of the cortical activation. Cortical activation by disturbing noise off the frequency of a tone of interest would increase lateral inhibition in class III neurons with the effect of narrowing their FTCs to improve again time-critical processing of frequencies of interest.
On the first view, the assimilation of the class II and III FTC shapes to the class I shapes (Table 1) may be regarded as a transient change of specialized frequency filters to auditory-nerve like (general purpose) neurons in the ICC mediated by corticofugal activity. By considering the spatial distribution of FTC types in the ICC, however, it seems that the auditory cortex can adjust the auditory midbrain function in the spectral domain to improve both spectral and time-critical processing via its differential influence on specialized groups of neurons.
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TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONGRANTSACKNOWLEDGMENTSREFERENCES |
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TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONGRANTSACKNOWLEDGMENTSREFERENCES |
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Address for reprint requests and other correspondence: J. Yan, Dept. of Physiology and Biophysics, Neuroscience Research Group, Faculty of Medicine, University of Calgary, 3330 Hospital Drive, N.W., Rm193B, Calgary, Alberta, T2N 4N1, Canada, (E-mail: juyan{at}ucalgary.ca)
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Bjordahl TS, Dimyan MA, and Weinberger NM. Induction of long-term receptive field plasticity in the auditory cortex of the guinea pig by stimulation of the nucleus basalis. Behav Neurosci 112: 467–479, 1998.[CrossRef][Web of Science][Medline]
Bledsoe SC, Shore SE, and Guitton MJ. Spatial representation of corticofugal input in the inferior colliculus: a multicontact silicon probe approach. Exp Brain Res 153: 530–542, 2003.[CrossRef][Web of Science][Medline]
Casseday JH and Covey E. Frequency tuning properties of neurons in the inferior colliculus of an FM bat. J Comp Neurol 319: 34–50, 1992.[CrossRef][Web of Science][Medline]
Dostrovski J. Invasive techniques in humans: microelectrode recordings and microstimulation. In: Modern Techniques in Neuroscience Research, edited by Windhorst U and Johansson, H. Berlin: Springer-Verlag, 1999, p. 1199–1210.
Doucet JR, Molavi DL, and Ryugo DK. The source of corticocollicular and corticobulbar projections in area Te1 of the rat. Exp Brain Res 153: 461–466, 2003.[CrossRef][Web of Science][Medline]
Edeline JM. The thalamo-cortical auditory receptive fields: regulation by the states of vigilance, learning and the neuromodulatory systems. Exp Brain Res 153: 554–572, 2003.[CrossRef][Web of Science][Medline]
Egorova M, Ehret, G. Vartanian I, and Esser KH. Frequency response areas of neurons in the mouse inferior colliculus. I. Threshold and tuning characteristics. Exp Brain. Res 140: 145–161, 2001.[CrossRef][Web of Science][Medline]
Ehret G, Egorova M, Hage SR, and Müller BA. Spatial map of frequency-tuning curve shapes in the mouse inferior colliculus. Neuroreport 14: 1365–1369, 2003.[CrossRef][Web of Science][Medline]
Ehret G and Merzenich MM. Complex sound analysis (frequency resolution, filtering and spectral integration) by single units of the inferior colliculus of the cat. Brain Res Rev 13: 139–163, 1988.
Ehret G and Moffat AJM. Inferior colliculus of the house mouse II. Singe-unit responses to tones, noise and tone-noise combinations as a function of sound intensity. J Comp Physiol [A] 56: 619–635, 1985.
Faingold CL, Gehlbach G, and Caspary DM. On the role of GABA as an inhibitory neurotransmitter in inferior colliculus neurons: iontophoretic studies. Brain Res 500: 302–312, 1989.[CrossRef][Web of Science][Medline]
Feliciano M and Potashner S. Evidence for a glutamatergic pathway from the guinea pig auditory cortex to the inferior colliculus. J Neurochem 65: 1348–1357, 1995.[Web of Science][Medline]
Fuzessery ZM and Hall JC. Role of GABA in shaping frequency tuning and creating FM sweep selectivity in the inferior colliculus. J Neurophysiol 76: 1059–1073, 1996.
Gao E and Suga N. Experience-dependent corticofugal adjustment of midbrain frequency map in bat auditory system. Proc Natl Acad Sci USA 95: 12663–12670, 1998.
Gao E and Suga N. Experience-dependent plasticity in the auditory cortex and the inferior colliculus of bat: role of the corticofugal system. Proc Natl Acad Sci USA 97: 8081–8086, 2000.
Goldstein MH and Abeles M. Single unit activity in the auditory cortex. In: Handbook of Sensory Physiology: Auditory System, Vol. V/2, edited by Keidel WD and Neff WD. Berlin: Springer-Verlag, 1975, p. 199–218.
Hage SR and Ehret G. Mapping responses to frequency sweeps and tones in the inferior colliculus of house mice. Eur J Neurosci 18: 2301–2312, 2003.[CrossRef][Web of Science][Medline]
Herbert H, Aschoff A, and Ostwald J. Topography of projections from the auditory cortex to the inferior colliculus in the rat. J Comp Neurol 304: 103–122, 1991.[CrossRef][Web of Science][Medline]
Hofstetter KM and Ehret G. The auditory cortex of the mouse: connections of the ultrasonic field. J Comp Neurol 323: 370–386, 1992.[CrossRef][Web of Science][Medline]
Huffman RF and Henson OW Jr. The descending auditory pathway and acousticomotor system: connections with the inferior colliculus. Brain Res Rev 15: 295–323, 1990.[CrossRef][Medline]
Jen PHS, Chen QC, and Sun X. Corticofugal regulation of auditory sensitivity in the bat inferior colliculus. J Comp Physiol [A] 183: 683–697, 1998.[CrossRef][Medline]
Jen PHS, Sun X, and Chen QC. An electrophysiological study of neural pathways for corticofugally inhibited neurons in the central nucleus of the inferior colliculus of the big brown bat, Eptesicus fuscus. Exp Brain Res 137: 292–302, 2001.[CrossRef][Web of Science][Medline]
Ji W, Gao E, and Suga N. Effects of acetylcholine and atropine on plasticity of central auditory neurons caused by conditioning in bats. J Neurophysiol 86: 211–225, 2001.
Kiang NYS, Watanabe T, Thomas EC, and Clark LF. Discharge Patterns of Single Fibers in the Cat's Auditory Nerve. Cambridge, MA: MIT Press, 1965.
Kilgard MP and Merzenich MM. Cortical map reorganization enabled by nucleus basalis activity. Science 279: 1714–1718, 1998.
Le Beau FEN, Rees A, and Malmierca MS. Contribution of GABA- and glycine-mediated inhibition to the monaural temporal response properties of neurons in the inferior colliculus. J Neurophysiol 75: 902–919, 1996.
Le Beau FEN, Malmierca MS, and Rees A. Iontophoresis in vivo demonstrates a key role for GABAA and glycinergic inhibition in shaping frequency response areas in the inferior colliculus of the guinea pig. J Neurosci 21: 7303–7312, 2001.
Liberman MC. Auditory-nerve responses from cats raises in a low-noise chamber. J Acoust Soc Am 63: 442–455, 1978.[CrossRef][Web of Science][Medline]
Lu Y and Jen PHS. GABAergic and glycinergic neural inhibition in excitatory frequency tuning of bat inferior collicular neurons. Exp Brain Res 141: 331–339, 2001.[CrossRef][Web of Science][Medline]
Ma X and Suga N. Corticofugal modulation of duration-tuned neurons in the midbrain auditory nucleus in bats. Proc Natl Acad Sci USA 98: 14060–14065, 2001.
Ma X and Suga N. Augmentation of plasticity of the central auditory system by the basal forebrain and/or somatosensory cortex. J Neurophysiol 89: 90–103, 2003.
Machmerth H, Theiss D, and Schnitzler HU. Konstruktion eines Luftschallgebers mit konstantem Frequenzgang im Bereich von 15 kHz–130 kHz. Acustica 34: 81–85, 1975.
Oliver DL, Winer JA, Beckius GE, and Saint Marie RL. Morphology of GABAergic neurons in the inferior colliculus of the cat. J Comp Neurol 340: 27–42, 1994.[CrossRef][Web of Science][Medline]
Palombi PS and Caspary DM. GABA inputs control discharge rate primarily within frequency receptive fields of inferior colliculus neurons. J Neurophysiol 75: 2211–2219, 1996.
Paxinos G and Franklin KBJ. The Mouse Brain in Stereotaxic Coordinates (2nd ed.). San Diego: Academic, 2001.
Phillips DP. Factors shaping the response latencies of neurons in the cat's auditory cortex. Behav Brain Res 93: 33–41, 1998.[CrossRef][Web of Science][Medline]
Pollak GD and Park TJ. The effects of GABAergic inhibition on monaural response properties of neurons in the mustache bat's inferior colliculus. Hear Res 65: 99–117, 1993.[CrossRef][Web of Science][Medline]
Ramachandran R, Davis KA, and May BJ. Single-unit responses in the inferior colliculus of decerebrate cats. I. Classification based on frequency response maps. J Neurophysiol 82: 152–163, 1999.
Saldaña E, Feliciano M, and Mugnaini E. Distribution of descending projections from primary auditory neocortex to inferior colliculus mimics the topography of intracollicular projections. J Comp Neurol 371: 15–40, 1996.[CrossRef][Web of Science][Medline]
Scheich H, Stark H, Zuschratter W, Ohl FW, and Simonis CE. Some functions of primary auditory cortex in learning and memory formation. Adv Neurol 73: 179–193, 1997.[Web of Science][Medline]
Schreiner CE and Langner G. Laminar fine structure of frequency organization in auditory midbrain. Nature 388: 383–386, 1997.[CrossRef][Medline]
Sidman RL, Angevine JB, and Pierce ET. Atlas of the Mouse Brain and Spinal Cord. Boston: Harvard University Press, 1971.
Stiebler I and Ehret G. Inferior colliculus of the house mouse. I. A quantitative study of tonotopic organization, frequency representation, and tone-threshold distribution. J Comp Neurol 238: 65–76, 1985.[CrossRef][Web of Science][Medline]
Stiebler I, Neulist R, Fichtel I, and Ehret G. The auditory cortex of the house mouse: left-right differences, tonotopic organization and quantitative analysis of frequency representation. J Comp Physiol [A] 181: 559–571, 1997.[CrossRef][Medline]
Suga N. Classification of inferior colliculus neurones of bats in terms of responses to pure tones, FM sounds and noise bursts. J Physiol 200: 555–574, 1969.
Suga N and Jen PHS. Disproportionate tonotopic representation for processing CF-FM sonar signals in the mustached bat auditory cortex. Science 194: 542–544, 1976.
Suga N, Gao E, Zhang Y, Ma X, and Olsen JF. The corticofugal system for hearing: Recent progress. Proc Natl Acad Sci USA 97: 11807–11814, 2000.
Suga N, Xiao Z, Ma X, and Ji W. Plasticity and corticofugal modulation for hearing in adult animals. Neuron 36: 9–18, 2002.[CrossRef][Web of Science][Medline]
Suga N, Yan J, and Zhang Y. Cortical maps for hearing and egocentric selection for self-organization. Trends Cogn Sci 1: 1–14, 1997.[CrossRef]
Sun X, Jen PHS, Sun D, and Zhang S. Corticofugal influences on the responses of bat inferior collicular neurons to sound stimulation. Brain Res 495: 1–8, 1989.[CrossRef][Web of Science][Medline]
Sutter ML. Shapes and level tolerances of frequency tuning curves in primary auditory cortex: quantitative measures and population codes. J Neurophysiol 84: 1012–1025, 2000.
Sutter ML, Schreiner CE, McLean M, O'Connor N, and Loftus WC. Organization of inhibitory frequency-receptive fields in cat primary auditory cortex. J Neurophysiol 82: 2358–2371, 1999.
Syka J and Popelá J. Inferior colliculus in the rat: neuronal responses to stimulation of the auditory cortex. Neurosci Lett 51: 235–240, 1984.[CrossRef][Web of Science][Medline]
Syka J, Popelá J, Druga R, and Vlková A. Descending central auditory pathway—structure and function. In: Auditory Pathway: Structure and Function, edited by Syka J and Masterton RB. New York: Plenum, 1988, p. 279–292.
Tarpy RM and Mayer RE. Foundations of Learning and Memory. Glenview, IL: Scott, Foresman, 1978.
Torterolo P, Zurita P, Pedemonte M, and Velluti RA. Auditory cortical efferent actions upon inferior colliculus unitary activity in the guinea pig. Neurosci Lett 249: 172–176, 1998.[CrossRef][Web of Science][Medline]
Weinberger NM. Physiological memory in primary auditory cortex: characteristics and mechanisms. Neurobiol Learn Mem 70: 226–251, 1998.[CrossRef][Web of Science][Medline]
Winer JA, Larue DT, Diehl JJ, and Hefti BJ. Auditory cortical projections to the cat inferior colliculus. J Comp Neurol 400: 147–174, 1998.[CrossRef][Web of Science][Medline]
Xiao Z and Suga N. Modulation of cochlear hair cells by the auditory cortex in the mustached bat. Nat Neurosci 5: 57–65, 2002.[CrossRef][Web of Science][Medline]
Yan J and Ehret G. Corticofugal reorganization of the midbrain tonotopic map in mice. Neuroreport 12: 3313–3316, 2001.[CrossRef][Web of Science][Medline]
Yan J and Ehret G. Corticofugal modulation of midbrain sound processing in the house mouse. Eur J Neurosci 16: 119–128, 2002.[CrossRef][Web of Science][Medline]
Yan J and Suga N. Corticofugal modulation of time-domain processing of biosonar information in bats. Science 273: 1100–1103, 1996.[Abstract]
Yan W and Suga N. Corticofugal modulation of the midbrain frequency map in the bat auditory system. Nat Neurosci 1: 54–58, 1998.[CrossRef][Web of Science][Medline]
Yan J, Zhang Y, Jia Z, Taverna FA, McDonald RJ, Muller RU, and Roder JC. Place-cell impairment in glutamate receptor 2 mutant mice. J Neurosci 22: RC204 (1–5), 2002.
Yan J, Zhang Y, Roder J, and McDonald RJ. Aging effects on spatial tuning of hippocampal place cells in mice. Exp Brain Res 150: 184–193, 2003.[Web of Science][Medline]
Yang L, Pollak GD, and Resler C. GABAergic circuits sharpen tuning curves and modify response properties in the mustache bat inferior colliculus. J Neurophysiol 68: 1760–1774, 1992.
Young ED, Shofner WP, White JA, Robert JM, and Voigt HF. Response properties of cochlear nucleus neurons in relationship to physiological mechanisms. In: Auditory Function: Neurobiological Bases of Hearing, edited by Edelman GM, Gall WE, and Cowan WM. New York: Wiley, 1988, p. 277–312.
Zhang Y and Suga N. Corticofugal amplification of subcortical responses to single-tone stimuli in the mustached bat. J Neurophysiol 78: 3489–3492, 1997.
Zhang Y and Suga N. Modulation of responses and frequency tuning of thalamic and collicular neurons by cortical activation in mustached bat. J Neurophysiol 84: 325–333, 2000.
Zhang Y, Suga N, and Yan J. Corticofugal modulation of frequency processing in bat auditory system. Nature 387: 900–903, 1997.[CrossRef][Medline]
Zhou X and Jen PHS. Corticofugal inhibition compresses all types of rate-intensity functions of inferior collicular neurons in the big brown bat. Brain Res 881: 62–68, 2000a.[CrossRef][Web of Science][Medline]
Zhou X and Jen PHS. Brief and short-term corticofugal modulation of subcortical responses in the big brown bat, Eptesicus fuscus. J Neurophysiol 84: 3083–3087, 2000b.
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