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Proceedings of the National Academy of Sciences of the United States of America logoLink to Proceedings of the National Academy of Sciences of the United States of America
. 2008 Mar 10;105(11):4423–4428. doi: 10.1073/pnas.0800009105

Enduring effects of early structured noise exposure on temporal modulation in the primary auditory cortex

Xiaoming Zhou *,†,‡, Michael M Merzenich *,‡
PMCID: PMC2393777  PMID: 18332439

Abstract

Studies have shown that acoustic experiences significantly contribute to the functional shaping of the structural organization and signal processing capacities of the mammalian auditory system during postnatal development. Here, we show how an early epoch of exposure to structured noise influences temporal processing in the rat primary auditory cortex documented immediately after exposure and again in adulthood. Pups were continuously exposed to broadband-pulsed noise across the critical period for auditory system development. Immediately after cessation of exposure at postnatal day ≈35 (P35) or ≈55 days later (i.e., P90) in other rats, the temporal modulation-transfer functions of cortical neurons were documented. We found that pulsed noise exposure at a low modulation rate significantly decreased cortical responses to repetitive stimuli presented across a range of higher modulation rates. The highest temporal rate at which temporal modulation-transfer function was at half of its maximum was reduced when compared with naïve rats. Low-rate pulsed noise exposure also decreased cortical response synchronization at higher stimulus rates, as shown by vector strength and Rayleigh statistic measures. These postexposure changes endured into adulthood. These findings bear significant implications for the role of early sound experiences as contributors to the ontogeny of human auditory and language-related abilities and impairments.

Keywords: cortical plasticity, critical period, temporal modulation-transfer function, temporal processing

Sounds in natural environments, such as animal vocalizations and human speech, have complex temporal structures. The importance of temporal structure in acoustic communication and orientation has been demonstrated in many behavioral, psychological, and neurophysiological studies. The auditory cortex plays a critical role in the perception of time-varying features of aural speech and of other complex acoustic stimuli. In humans, speech comprehension is correlated with responses of cortical neurons to temporal envelopes of speech (1), and individuals with impaired language abilities have impaired successive signal evoked cortical responses (2, 3).

Earlier studies in different subprimate animal species have shown that cortical neurons display different temporal filtering properties (e.g., low-pass, responding to sound trains below certain rates, or band-pass, responding best to a specific rate, etc.) (4–7). In general, cortical neurons respond to repetitive sounds at far lower rates and with poorer temporal precision when compared with auditory nerve fibers or neurons in subcortical auditory nuclei and, in most mammalian species, are not able to follow individual sound presented at rates faster than ≈20 pulses per second (pps). It has been argued that for those more rapidly occurring stimuli (e.g., stimuli with repetition rate >100 pps), cortical neurons might apply a rate code instead of a temporal code (stimulus-synchronized responses) to represent the temporal structure (7). Most natural sounds, such as animal vocalizations and human speech, are primarily modulated by rates of less than ≈50 pps (8), and are likely coded by cortical neurons via stimulus event-synchronized responses.

Functional development of the mammalian auditory system is substantially influenced by acoustic environments in early life (9). It has been shown that passive exposure to sounds within the critical period can induce various large-scale reorganizations of the primary auditory cortex (A1), such as alterations in tonotopic maps and the response specificities of neurons. These modifications depend strongly on the spectrotemporal structure of sounds heard during this critical period. Exposing rat pups to pulsed tones of a specific frequency, for example, results in an over-representation of that frequency and broader-than-normal receptive fields in cortical field A1 (10). If rat pups are exposed to temporally modulated noises, the tonotopic organization of A1 is degraded, and there is a premature closure of the critical period (11, 12). If rat pups are exposed to continuous noise, however, tonotopicity in A1 is poorly developed, and this degraded condition persists (13). Although these studies indicate that early acoustic experiences significantly contribute to the functional shaping of the structural organization and signal processing capacities of the A1, they have mainly focused on spectral domain processing. Two of these studies did report that continuous noise exposure early in life altered temporal response properties of cortical neurons. Those changes were reversed after exposed rats were returned to normal environments (13, 14). The effects on cortical spectral processing induced by exposing rats to sounds with different spectrotemporal structures have varied substantially as a function of the temporal features of the applied stimuli (10–13). It remains to be determined whether or not cortical temporal information processing is influenced by early pulsed noise (PN) exposure. To understand and model the development of environmentally shaped signal processing in A1, it is necessary to isolate the specific consequence of pulsed sound exposure on cortical temporal processing.

By exposing rat pups to PN during the critical period, we here document postexposure changes in cortical temporal response properties. In contrast to continuous noise exposure, these changes induced by PN exposure persist into adulthood. Because speech and other animal vocalizations require significant temporal processing of acoustic inputs, data presented here have significant implications for understanding the origins of human auditory and language-related abilities and impairments.

Results

Frequency Representation in PN-Exposed Rats Recorded at Approximately Postnatal Day 35 (P35).

In naïve rats (n = 4), the frequency representation of A1 was complete and orderly, with isofrequency representational bands oriented approximately orthogonal to an orderly sound frequency representational (tonotopic) gradient (Fig. 1A Upper). Tuning curves of neurons within A1 were generally V-shaped, with a clear characteristic frequency (CF) defined at the low threshold peak (Fig. 1B a and b). In PN-exposed rats (n = 4), however, most tuning curves within A1 were flat-peaked or multi peaked (Fig. 1 A Lower and B c and d). Comparison of bandwidth measured at 20 dB above threshold (BW20) showed that these tuning curves recorded in PN-exposed rats were much more broadly tuned than those in naïve rats (Fig. 1Ca; unpaired t test, P < 0.03–0.00001). The predominantly less-selective tuning curves in A1 of PN-exposed rats manifested the degraded spectral selectivity induced by early PN exposure.

Fig. 1.

Fig. 1.

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Postexposure changes in cortical frequency representation. (A) Representative auditory cortical CF maps from naïve (Upper) and PN-exposed (Lower) rats recorded at approximately P35. The color of each polygon indicates the CF for neurons recorded at that site (see scale in Upper Right). Gray polygon in PN-exposed rat represents the flat-peaked or multipeaked tuning curve recorded at that site. A,anterior; D, dorsal; o, non-A1 site; x, unresponsive cortical site. (B) Representative examples of tonal receptive fields recorded from the sites marked in maps in A. (C) Comparisons of average receptive field bandwidth (BW20) at different CF ranges (a), tonotopic index (b), latency (c), and response threshold (d) between naïve and PN-exposed rats. Bin size = ≈1.5 octaves. *, P < 0.03–0.00001. Error bars represent means ± SE.

We also quantified the precision of A1 tonotopicity for both rat groups by calculating the tonotopic index (see Materials and Methods). As shown in Fig. 1Cb, average indices in PN-exposed rats were significantly larger than were these in naïve rats (unpaired t test, P < 0.002), showing that a disordered tonotopic map resulted from early PN exposure. However, no significant differences were found in response latencies (Fig. 1Cc; unpaired t test, P > 0.7) and sound intensity thresholds (Fig. 1Cd; unpaired t test, all P values > 0.1) of A1 neurons between PN-exposed and naïve rats. These results are consistent with those recorded in ref. 11.

Temporal Responses in PN-Exposed Rats Recorded at Approximately P35.

Representations of temporal modulation rates in A1 of both naïve and PN-exposed rats were examined by recording cortical responses to CF tonal pulses presented at variable repetition rates. In naïve rats, most cortical neurons could follow repeated stimuli at and below rates of 10 pps, with each brief tone evoking approximately the same number of spikes as did the first tone in the train. At higher repetition rates, numbers of responses per tone fell off rapidly. Neurons at only a few sites responded regularly to rates as high as 15 pps (Fig. 2A Upper). By contrast, most A1 neurons in PN-exposed rats only followed stimuli at or below repetition rates of ≈7 pps (Fig. 2A Lower). To measure these effects, we constructed temporal modulation-transfer functions (tMTFs), in which normalized cortical responses were defined as a function of stimulus repetition rates. As described in Materials and Methods, tMTFs were categorized as either low-pass, band-pass, or band-reject based on their shapes. In naïve rats, more than half of sampled tMTFs were low-pass (57%). The remainders were either band-pass (29%) or band-reject (14%). In PN-exposed rats, however, the number of low-pass tMTFs (74%) increased, whereas those of band-pass (23%) or band-reject tMTFs (3%) decreased (χ2 test, P < 0.001).

Fig. 2.

Fig. 2.

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Postexposure changes in cortical responses to repetitive stimuli. (A) Dot raster plot examples of cortical responses to pulse trains of different repetition rate recorded from naïve (Upper) and PN-exposed (Lower) rats. Red lines indicate pulse durations. (Insert) shows tMTF for each raster plot example. Unfilled circle and dashed line show fh½ and 50% of maximal normalized response for each tMTF, respectively. (B) Average tMTFs for all recordings obtained from naïve and PN-exposed rats. *, P < 0.03–0.00001. Error bars represent means ± SE.

Although different types of tMTFs were observed across sites, the average tMTF took a low-pass form in both rat groups (Fig. 2B). This low-pass function fell off rapidly above ≈10 pps in naïve rats and above ≈7 pps in PN-exposed rats. Overall, normalized response rates in PN-exposed rats decreased at high repetition rates (>7 pps) but were increased at low rates compared with naïve rats (unpaired t test, P < 0.03–0.00001).

The cortical capacity for processing high-rate stimuli can be illustrated by determining the highest temporal rate at which tMTF was at half of its maximum (fh½). Fig. 3A shows representative fh½ maps from naïve and PN-exposed rats in which each polygon was assigned the fh½ measured at that site. In general, the fh½ obtained at most sites for PN-exposed rats were lower than for naïve rats (Fig. 3A Lower vs. Upper). This observation was further confirmed by quantitative comparison of distribution for all fh½ values obtained from both rat groups. As show in Fig. 3B, there was a significant leftward shift of fh½ distribution for PN-exposed rats compared with naïve rats, indicating a decreased rate-following ability induced by low-rate PN exposure (Kolmogorov–Smirnov test, P < 0.0001). To examine whether the reduction of fh½ was related to the CF of each site, we compared fh½ values obtained from both rat groups by binning their CF values into three ≈1.5-octave-wide categories (Fig. 3C). Results showed that average fh½ values were significantly smaller for PN-exposed rats than for naïve rats across all CF ranges (unpaired t test, P < 0.05–0.00001). We observed significant negative correlations between fh½ and response latency in naïve rats (Fig. 3D, black circles; correlation analysis, r = −0.5, P < 0.0001), as demonstrated by previous studies (6, 15). The same tendency, however, was not found in PN-exposed rats (Fig. 3D, yellow circles; correlation analysis, r = −0.11, P > 0.1).

Fig. 3.

Fig. 3.

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Postexposure changes in fh½. (A) Representative auditory cortical fh½ maps for naïve and PN-exposed rats with their CF maps shown in Fig. 1A. The color of each polygon indicates the fh½ recorded at that site. An unfilled polygon represents that tMTF was not recorded at that site. (B) Cumulative frequency histograms showing a significant leftward shift of the fh½ distribution for PN-exposed rats compared with naïve rats (Kolmogorov–Smirnov test, P < 0.0001). (C) Average fh½ values for all recording sites in both rat groups for each of three CF ranges. Bin size = ≈1.5 octaves. *, P < 0.05–0.00001. Error bars represent means ± SE. (D) Scatter plots of fh½ as a function of latency for both rat groups.

For those sites with band-pass tMTFs (recording sites = 52 for naïve rats and 42 for PN-exposed rats, respectively), we were able to determine the best repetition rates (BRRs) at which normalized responses were at least 50% larger than these obtained at low and high rates. It is interesting to note that various BRRs (ranging from 4 to 12.5 pps) appeared to distribute over approximately all frequency bands in both naïve and PN-exposed rats when plotted as a function of CF determined at each site (Fig. 4A Upper). However, although most sites in naïve rats preferred the stimuli repetition rate of 10 pps, most sites in PN-exposed rats preferred 7 pps (Fig. 4A Lower). PN exposure significantly decreased the number of sites with BRRs of 10 pps but increased the number of sites with BRRs of 7 and 4 pps, compared with naïve rats (χ2 test, P < 0.01).

Fig. 4.

Fig. 4.

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Postexposure changes in BRRs and cortical response dynamics. (A) BRR as a function of CF for those sites with band-pass tMTFs in naïve and PN-exposed rats (Upper) and the distribution of BRRs (Lower). (B) Average vector strengths measured at different pulse repetition rates for all recordings in naïve and PN-exposed rats (Upper) and average Rayleigh statistics (Lower). *, P < 0.02–0.00001. Error bars represent means ± SE. (C) Compound PSTHs recorded from naïve (Upper) and PN-exposed (Lower) rats showing recovery dynamics after cortical neurons were activated by tonal stimuli with onsets at 50 ms. Green area shows suppression after spikes activated by tonal stimuli, and red area shows “rebound” excitability. Dashed lines and filled arrows indicate average spontaneous activity and the end of poststimulation suppression, respectively. Error bars represent means ± SE. (Insets) Scatter plots of fh½ as a function of duration between excitatory peak and rebound excitatory peak of individual sites for both rat groups.

Changes in Cortical Response Dynamics Induced by PN Exposure.

To further characterize cortical spike timing relative to stimulus phase, we calculated vector strengths, which quantify the precision of spike timing to successive stimuli, and Rayleigh statistics, which estimate the significance level of the vector strength, taking into account the total number of spikes. Although the average vector strength and Rayleigh statistic as a function of stimulus repetition rates displayed the same band-pass characteristics for both rat groups, these curves shifted leftward and peaked at lower repetition rates after low-rate PN exposure (peaked at 7 pps in PN-exposed rats vs. 10 pps in naïve rats; Fig. 4B, yellow vs. black lines). In general, both vector strength and Rayleigh statistic of PN-exposed rats were smaller at high repetition rates (i.e., 10–20 pps) but were larger at low rates (i.e., 4 or 7 pps) than naïve rats (unpaired t test, P < 0.02–0.00001).

To examine whether noise exposure altered the dynamics of cortical excitability after sound stimulation, we obtained compound peristimulus time histograms (PSTHs) for both rat groups. As shown in Fig. 4C, there was a brief period of suppression as indicated by a below-spontaneous discharge rate after a burst of spikes activated by tonal stimuli (green area in Fig. 4C), and then a period of enhanced or “rebound” excitability manifested by an above-spontaneous discharge rate (red area in Fig. 4C). Although the strength of poststimulus suppression did not differ between the two rat groups (unpaired t test comparing suppression at the maximum, P > 0.5), the duration of suppression for PN-exposed rats was significantly longer than for naïve rats (≈90 ms vs. ≈70 ms). Moreover, the rebound excitation was greater for PN-exposed rats than for naïve rats (unpaired t test comparing excitability at the maximum, P < 0.02) although the duration of excitation was similar (≈80 ms). To quantitatively compare the dynamics of cortical excitability between the two rat groups, we measured duration from excitatory peak to rebound excitatory peak for individual sites. Results showed that the average peak-peak duration obtained from PN-exposed rats was significantly larger than that from naïve rats (164 ± 2 ms vs. 137 ± 2 ms, unpaired t test, P < 0.00001). Also, the peak–peak duration of individual sites were significantly correlated with their fh½ values in both rat groups (correlation analysis, r = −0.59, P < 0.0001 for naïve rats and r = −0.49, P < 0.0001 for PN-exposed rats, respectively).

Enduring Effects on Cortical Temporal Responses Recorded at Approximately P90.

Earlier studies have shown that cortical changes induced by early continuous noise are reversible by later normal auditory experiences (13). To evaluate the long-term impact of PN exposure, three PN-exposed rats were returned to a standard housing condition and tMTFs of cortical area for these rats were reconstructed at approximately P90 (i.e., ≈55 days after exposure cessation). The average tMTF, fh½, vector strength, and Rayleigh statistic were compared with those of age-matched naïve rats (n = 3). As summarized in Fig. 5, the data obtained from PN-exposed rats mapped at approximately P90 were significantly different from those of naïve rats but generally comparable to those of PN-exposed rats mapped at approximately P35 (ANOVA, P < 0.05–0.00001 for each comparison denoted with an asterisk in Fig. 5 A and D–F, and Kruskal-Wallis test, P < 0.0001 for Fig. 5C). These data indicate that PN exposure has enduring effects on cortical temporal information processing.

Fig. 5.

Fig. 5.

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Average tMTFs (A), fh½ maps (B), cumulative frequency histograms of fh½ (C), average fh½ values at different CF ranges (D), vector strengths (E), and Rayleigh statistics (F) obtained from PN-exposed rats mapped at ≈55 days after exposure cessation (i.e., approximately P90) or immediately after exposure (i.e., approximately P35), illustrated with age-matched naïve rats (i.e., approximately P90). Bin size = ≈1.5 octaves. *, P < 0.05–0.00001. Error bars represent means ± SE.

Discussion

Consistent with earlier studies (11, 12), we showed that early PN exposure significantly increased the tonotopic index (degraded tonotopicity) of A1 and broadened frequency tuning (i.e., BW20) of A1 neurons. We further showed that the normalized response rates for PN-exposed rats were lower at high stimulus repetition rates (i.e., >7 pps) than in naïve rats, indicating decreased cortical responses to high-rate stimuli after noise exposure. Correspondingly, average tMTF was shifted leftward in PN-exposed rats, resulting in significantly lower fh½ values compared with naïve animals. The number of low-pass tMTF sites that preferred low repetition rates was significantly increased in PN-exposed rats. BRRs for those band-pass tMTFs also shifted to lower rates compared with naïve rats. These observations were further confirmed by vector strength and Rayleigh statistic analyses that showed that both measures in PN-exposed rats were significantly smaller at high rates relative to naïve rats. All of the above data clearly demonstrate a reduced ability of cortical neurons to respond to repeated stimuli in PN-exposed rats. Thus, early structured noise exposure results in disrupted A1 tonotopicity, degraded frequency tuning for neurons in A1, and reduced representations of high repetition rate sounds in A1.

It should be noted that anesthesia has been shown to affect the cortical response to successive stimuli (16, 17). However, anesthesia would not create a bias in estimations made in PN-exposed versus naïve rats because of identical anesthetic conditions during recording for both rat groups.

We have shown that postexposure alterations in cortical response dynamics after PN exposure endure into adulthood. By contrast, previous studies that applied continuous noise exposure during the critical period reported that noise-rearing did not necessarily permanently impair cortical temporal processing into adulthood; the cortex returned to “normal” after animals were returned to a normal acoustic environment (13, 14). A similar difference in the duration of exposure-induced plasticity has been reported in spectral domain development of A1 when rats were exposed to pulsed (11, 12) or continuous (13) noise during the critical-period epoch. It has been proposed that PN-rearing prematurely advances the timing of critical-period closure for cortical plasticity, whereas continuous noise rearing, in contrast, results in the delay of critical-period closure. Therefore, in this latter case, once the noise is eliminated, the still-open critical-period window permutes the development of relatively normal spectral receptive field properties (13). By contrast, no mere exposure-based (critical-period) reversal can occur in the PN case, because the critical period has long since ended. Together, these results suggest that the role of patterned acoustic inputs for critical-period plasticity in cortical field A1 is important in both spectral and temporal domains.

Using a two-tone stimulus paradigm, it has been shown that the duration of poststimulation suppression significantly influences the ability of cortical neurons to respond to successive acoustic stimuli (14). Here, we estimate the dynamics of cortical excitability, using compound PSTHs generated by tonal stimuli. We showed that the duration of poststimulation suppression was longer and the rebound excitation greater for neurons in PN-exposed than in naïve rats. This may explain the facilitation of PN-exposed rat responses at some low repetition rates, in which fh½ values of tMTFs were significantly decreased. The duration of excitatory peak to rebound excitatory peak was significantly correlated with fh½ in both rat groups, further supporting the argument that noise-induced degradation in cortical temporal processing stems from an alteration in the dynamics of cortical poststimulation suppression.

Earlier studies demonstrated that cochlear injury can be generated by high intensity sound exposure (100–120 dB SPL). This damage is usually accompanied by elevated sound intensity thresholds (18–21). It was recently shown that such noise-induced peripheral hearing loss also affects cortical tMTFs to amplitude-modulated noises in cats (22). In the present study, we applied moderate noise stimuli (i.e., 65-dB SPL), which did not induce cochlear damage, as shown by fact that response thresholds and latencies recorded in PN-exposed rats were not significantly different from those recorded in naïve rats (11). Thus, the observed changes in cortical temporal response properties after noise exposure clearly originated in the central auditory system. Because there is a dramatic change in modulation response characteristics recorded at the cortical level, at least much of these recorded effects maybe accounted for by intrinsic cortical remodeling. However, thalamo-cortical synapses and subcortical neural connectivity also contribute to regulating cortical poststimulation suppression (23, 24). Experience-induced plasticity of spectral domain processing has been documented in the inferior colliculus of mice (25) and rats (26). We cannot exclude the possibility that the observed postexposure changes in cortical response dynamics are partly the result of feed-forward responses reflecting experience-dependent changes in subcortical sources.

In human populations, fundamental deficits in cortical temporal processing affect general hearing and underlie poor language and reading skills (2, 27–32). In babies, such deficits strongly predict older-age deficits in language and reading abilities (3, 33). A study that showed that adaptive computer training aimed at reducing acoustic temporal integration times significantly improved speech and language comprehension abilities of children with specific language impairments further supports the argument that there is a causal relationship between the speed of successive-signal processing and an individual's aural language abilities (34). In a modern society, developing infants and children are constantly bombarded by temporally complex noises in their everyday environments. Much of that noise is modulated at or near the modulation rates for human speech. Moreover, a brain that is impaired in its ability to make accurate spectral or spectrotemporal distinctions because its processes are noisy will distort its processing machinery to exaggerate its representation of syllable-rate (low frequency) modulations (35, 36). We hypothesize that this could explain why many language-impaired children are able to identify and sequence acoustic inputs at these low rates (<4–5 events per second) but not at the higher rates that often apply for intrasyllabic acoustic information.

In summary, we have shown that rats reared in structured noise repeated at low temporal rates show reduced cortical representations of high-rate sounds and that postexposure changes endure into adulthood. These data strongly imply that internal process noise or external environmental noise in early life can potentially contribute to auditory and language-related impairments in later life. Further study of the underlying mechanisms would bear great practical and theoretical importance.

Materials and Methods

All experiment procedures used in this study were approved by the Animal Care and Use Committees at the University of California, San Francisco.

Early Exposure of Rat Pups.

Rat pups (Sprague–Dawley) and their mothers were placed in a sound-shielded test chamber from P7 to P35. An 8-h light/16-h dark cycle was established. Fifty-millisecond noise pulses (5-ms ramps) delivered at 65-dB SPL were applied from a speaker placed ≈15 cm above rats at 4 pps at 1-s intervals to minimize adaptation effects. Energy for PN stimuli was essentially flat across a broad frequency spectrum (0.2–30 kHz). No abnormalities in the behavior of either the mother or pups could be detected during PN exposure. The weights of all pups and mothers were continuously monitored, and there was no weight loss compared with naïve rats, indicating normal lactation. Activity patterns during waking and sleep exhibited no evidence of stress.

Electrophysiological Recordings.

Electrophysiological recording of cortical responses was conducted at approximately P35 and approximately P90 for matched groups of PN-exposed rats and naïve control rats. Rats were anesthetized with sodium pentobarbital (50 mg per kg of body weight). Throughout the surgical procedures and during the recording session, a state of areflexia was maintained with supplemental doses of 8 mg/ml dilute pentobarbital injected i.p. The trachea was cannulated to ensure adequate ventilation, and the cisternae magnum was drained of cerebrospinal fluid to minimize cerebral edema. The skull was secured in a head holder, leaving the ears unobstructed. After reflecting the right temporalis muscle, the auditory cortex was exposed and the dura was resected. The cortex was maintained under a thin layer of viscous silicone oil to prevent desiccation.

Cortical responses were recorded with parylene-coated tungsten microelectrodes (1–2 megohms at 1 kHz; FHC). Recording sites were chosen to evenly sample from the auditory cortex while avoiding blood vessels and were marked on a magnified digital image of the cortical surface vasculature. At each recording site, the microelectrode was lowered orthogonally into the cortex to a depth of 480–550 μm (layers 4 and 5), where vigorous stimulus-driven responses were recorded. Acoustic stimuli were generated by using TDT System III (Tucker–Davis Technologies) and delivered to the left ear through a calibrated earphone (STAX 54) with a sound tube positioned inside the external auditory meatus. A software package (SigCal, SigGen, and Brainware; Tucker-Davis Technologies) was used to calibrate the earphone, generate acoustic stimuli, monitor cortical response properties online, and store data for offline analysis. The evoked spikes of a neuron or a small cluster of neurons were collected at each site.

Cortical Mapping and Data Analysis.

Frequency tuning curves were reconstructed by presenting pure tones of 50 frequencies (1–30 kHz, 25-ms duration, 5-ms ramps) at eight sound intensities (0- to 70-dB SPL in 10-dB increments) to the contralateral ear in a random, interleaved sequence at a rate of 2 pps. The CF of a cortical site was defined as the frequency at the tip of the V-shaped tuning curve. For flat-peaked tuning curves, CF was defined as the midpoint of the plateau at threshold. For tuning curves with multiple peaks, CF was defined as the frequency at the most sensitive tip (i.e., with lowest threshold). Response bandwidths (BW20s) of tuning curves were measured for all sites. The response latency was defined as the time from stimulus onset to the earliest response, using PSTHs of responses to all tone pips.

To document cortical tMTFs (15), trains of six tonal pulses (25-ms duration with 5-ms ramps at 60-dB SPL) were delivered through the speaker four times at each of eight repetition rates (2, 4, 7, 10, 12.5, 15, 17.5, and 20 pps) in a randomly interleaved sequence. The tone frequency was set at the CF of each site. Cortical responses were collected from 200 ms before the first tone pip to at least 200 ms after the sixth tone pip. The normalized cortical response for each repetition rate was calculated as the average response to the last five pulses divided by the response to the first pulse. The tMTF is the normalized cortical response as a function of the temporal rate. Only spikes occurring from 5 to 40 ms after each tone onset were used to calculate the tMTFs. The shape of the tMTFs was categorized as one of the following: (i) Low-pass, responses obtained at low repetition rates was 50% greater than that obtained at high rates. (ii) Band-pass, responses obtained at the most preferred repetition rate were 50% greater than that obtained at low and high rates. For convenience, most preferred repetition rate was defined as the BRR. (iii) Band-reject, responses obtained at specific repetition rate were 50% smaller than that obtained at low and high rates. In addition, the cortical ability for processing repetitive stimuli was estimated with the highest temporal rate at which the tMTF was at half of its maximum (referred to as fh½).

Vector strength and Rayleigh statistic were used to quantify how well responses were time-locked to the repetitive pulses (15), using the following equation:

graphic file with name zpq01108-9493-m01.jpg

where n = total number of spikes, ti (i = 1, 2, …n) is the time between the onset of the first pulses and the ith spike, and T is the interstimulus interval. Spikes that occurred during a 6T period after the onset of the first tonal pulse were included to compute vector strength. A value of one indicates perfect synchronization between spikes and repeated stimuli, whereas a value of zero indicates no synchronization. Rayleigh statistic is 2n(vector strength)2, which assesses the statistical significance of the vector strength (37). Values >5.991 indicate statistically significant (P < 0.05) phase locking. Because the circular spike distribution is not strictly a von Mises distribution, the Rayleigh statistic may underestimate the nonuniformity of the distribution. The data of tMTF, vector strength, and Rayleigh statistic could not be viewed online. They were analyzed automatically only after each experiment was completed, and therefore were not subject to experimenter bias or error.

The area of A1 was defined as described in ref. 11. To generate A1 maps, Voronoi tessellation (a Matlab routine) was performed to create tessellated polygons, with electrode penetration sites at their centers. Each polygon was assigned the characteristics (e.g., CF or fh½) of the corresponding penetration site. In this way, every point on the surface of the auditory cortex was linked to the characteristics experimentally derived from a sampled cortical site that was closest to this point.

We used an index to quantitatively describe the precision of tonotopicity in A1 (10). The line connecting the two most anterior and posterior penetrations within A1 was used as a reference for the tonotopic axis. We then rotated each map to orient the tonotopic axis horizontally. After rotation, new x coordinates of penetrations in each rat were normalized to be within a range from 0.0 to 1.0, and penetration sites were plotted according to their CFs and x coordinates. The logarithmic frequency range (1–30 kHz) was converted to a linear range (0–1). We defined the index as the average minimal distance from each data point to the line connecting (0, 0) and (1, 1). The larger the index, the more disordered the tonotopicity of the tonotopic map.

Acknowledgments.

We thank S. Bao for assistance with data analysis; C. Atencio, J. Shih, and T. Babcock for technical support; and R. C. Froemke and L. Wilbrecht for reading an earlier version of this paper. This work was supported by National Institutes of Health Grant NS-10414, the Sandler Fund, and the Coleman Fund.

Footnotes

The authors declare no conflict of interest.

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