## Abstract

Several functional brain attributes reflecting neocortical activity have been found to be enhanced in musicians compared to non-musicians. Included are the N1m evoked magnetic field, P2 and right-hemispheric N1c auditory evoked potentials, and the source waveform of the magnetically recorded 40 Hz auditory steady state response (SSR). We investigated whether these functional brain attributes measured by EEG are sensitive to neuroplastic remodeling in non-musician subjects. Adult non-musicians were trained for 15 sessions to discriminate small changes in the carrier frequency of 40 Hz amplitude modulated pure tones. P2 and N1c auditory evoked potentials were separated from the SSR by signal processing and found to localize to spatially differentiable sources in the secondary auditory cortex (A2). Training enhanced the P2 bilaterally and the N1c in the right hemisphere where auditory neurons may be specialized for processing of spectral information. The SSR localized to sources in the region of Heschl’s gyrus in primary auditory cortex (A1). The amplitude of the SSR (assessed by bivariate T2 in 100 ms moving windows) was not augmented by training although the phase of the response was modified for the trained stimuli. The P2 and N1c enhancements observed here and reported previously in musicians may reflect new tunings on A2 neurons whose establishment and expression are gated by input converging from other regions of the brain. The SSR localizing to A1 was more resistant to remodeling, suggesting that its amplitude enhancement in musicians may be an intrinsic marker for musical skill or an early experience effect.

## Introduction

It is well established that the frequency tuning of neurons in the mammalian auditory cortex is not hardwired after early development but can be altered in the adult brain by experience with behaviorally significant acoustic signals (Buonomano and Merzenich, 1998). Plastic modification induced by aversive conditioning in adult guinea pigs has been documented for neurons in primary (A1, auditory core) and secondary (A2, belt/parabelt) regions of the auditory cortex well as in the medial, dorsal and ventral divisions of the auditory thalamus (Edeline, 1999). When brain regions are contrasted within the same conditioning procedure, tone-evoked plasticity is expressed more commonly by neurons in A2 (96%) than by neurons in A1 (63%; Diamond and Weinberger, 1984). Using owl monkeys, Recanzone et al. (1993) found that appetitive discrimination training for small changes in spectral pitch enhanced the cortical territory representing the trained frequencies in A1 by a factor exceeding 5. The sharpness of tuning and temporal response properties of multiunit recordings were also modified for the trained frequencies in this study. Training at acoustic discrimination in the owl monkey using amplitude modulated (AM) tones varying either in carrier frequency (Blake et al., 2002) or AM rate (Beitel et al., 2003) increased the spiking activity of A1 neurons for stimuli associated with reward compared to stimuli that were not.

Neural plasticity of the magnitude seen in these animal studies suggests that remodeling of the human auditory cortex by behavioral training should be expressed in auditory evoked potentials (AEPs) and magnetic fields (AEFs) which reflect the activities of populations of neurons in the brain. Consistent with this hypothesis, AEPs and AEFs evoked by musical stimuli are enhanced in musicians who have processed such stimuli extensively in their environment compared to non-musicians who have not. Enhancement has been reported for the magnetic N1m (Pantev et al., 1998), the electrical P2 (Shahin et al., 2003), and the right-sided electrical N1c (Shahin et al., 2003), each of which localizes to spatially differentiable centers of activation in the region of A2 where neuroplastic remodeling is robustly expressed. The auditory N19–P30 middle latency waveform, which has been localized by magnetic and electrical source imaging (Scherg and von Cramon, 1986; Godey et al., 2001; Yvert et al., 2001) and by intracortical measurements (Celesia, 1976; Liégeois-Chauvel et al., 1993; Godey et al., 2001;) to Heschl’s gyrus (A1), is also enhanced in musicians (Schneider et al., 2002). This waveform underlies the 40 Hz auditory steady-state response (Galambos et al., 1981; Gutschalk et al., 1999) and is correlated with the anteromedial extent of this anatomic structure and with measured musical skill (Schneider et al., 2002). However, while enhancement of these functional brain attributes in musicians may be of neuroplastic origin, one cannot rule out the possibility that enhancement results from prenatal influences or a genetic code that guides the development of auditory cortex and shapes the decision to train musically.

A more direct approach to assessing the expression of neuroplastic processes in AEPs and AEFs is to measure these responses when subjects are trained at novel acoustic discriminations. Recent studies by Eaton and Roberts (1999), Tremblay et al. (2001) and Atienza et al. (2002) indicate that at least one transient response of the AEP, the P2 with a latency of ∼185 ms, is enhanced when such training is carried out under laboratory conditions. These results are congruent with the hypothesis that enhancement of the P2 AEP when evoked by musical stimuli in musicians (Shahin et al., 2003) is a consequence of the extensive prior experience that musicians have had with such stimuli in the context of musical performance. In the present paper, we evaluated neuroplastic properties of several components of the AEP by training non-musician subjects to discriminate small changes in the carrier frequency of 40 Hz AM pure tones. This stimulus procedure allowed us to separate the P2 and other transient AEPs of interest whose sources are known to localize to A2 from the 40 Hz steady-state response (SSR) whose cortical sources reside more specifically in A1. Our goals were to (i) determine which of these AEP components reflecting activity in spatially distributed regions of the auditory cortex is sensitive to remodeling by neuroplastic mechanisms, and to (ii) begin to describe the network behavior that underlies remodeling of human auditory cortex by experience.

## Materials and Methods

### Source Modeling

Source analysis of the average-referenced AEP field patterns (N1, N1c, P2 and the 40 Hz SSR) was carried out using BESA 2000 (MEGIS GmbH, Munich, Germany). Analyses were conducted separately for each stimulus set and test session using the group averaged data. Two regional sources were used to describe the cortical generators for each AEP component (one source in each hemisphere, constrained to localize symmetrically following Scherg and von Cramon, 1986). Sources were determined at the peak of the AEP waveform (root mean squared transformed) within the same latency windows used for analyzing amplitude peaks in the EEG data. Medial/lateral (x), anterior/posterior (y), and inferior/superior (z) coordinates of each regional source were recorded together with dipole moment. The residual variance of the source model averaged 1.4%, 3.5%, 4.8%, and 1.8% for the N1, N1c, P2 and SSR, respectively (2.7% overall), with no fit exceeding 7.0% residual variance. It should be noted that regional sources determined by BESA use three orthogonal vectors (one in each plane) to describe cortical activations contributing to AEPs. These vectors were investigated further as described in the results section, to provide information on the relative contribution of tangential and radial vectors to N1 and N1c transient responses and SSR waveforms.

### Statistical Evaluation

Changes in behavioral performance and in transient AEPs induced by discrimination training were evaluated by repeated-measures ANOVAs. Analyses applied to the two test sessions included the variables before/after training and stimulus set (S1 stimuli of the trained set and the two control sets). Pre-planned contrasts were evaluated by conventional t-tests and post hoc contrasts with the Least Significant Difference test. Peak amplitude and latency were analyzed for the AEPs, and, for behavioral performance, the metrics P, d′, discrimination threshold, and slope of the psychophysical functions determined for each stimulus set. All probabilities are two-tailed unless otherwise stated.

Monte Carlo methods were used to evaluate the 40 Hz SSR. The presence of an SSR for each subject and test session was not in doubt; T2 for the 40 Hz Fourier component exceeded 45 in all subjects and 100 ms moving windows. In order to contrast the test sessions for training effects, we generated the distribution of T2 under the null hypothesis for each subject and stimulus set using the procedure of Manly (1991). For each moving window 144 trials were taken at random from the maximum of 288 trials that were available after artifact rejection in the first test session (before training), and a further 144 trials were taken the trials available in the second test session (after training). These 288 trials were used to calculate T2 when no difference was expected between before/after measurements. This constituted one simulation. One thousand of these simulations were performed for each stimulus set to approximate the distribution of T2 under the null hypothesis. Although these simulations were conducted separately for each subject, the results across subjects were similar, and we found that a critical value of T2 = 8.0 created a rejection region of P < 0.01 for all subjects considered singly. In order to determine a critical value to apply to a T2 map of a group of subjects, we combined one randomly selected ‘null hypothesis’ map from each subject into a group mean map, and repeated this process 1000 times to generate a distribution for this map under the null hypothesis. In this case a critical value of T2 = 4.5 was found to depict P < 0.05 and T2 = 6.0 to depict P < 0.01. The SSR was evaluated at several electrode sites but the response in the 40 Hz region was maximal at Fz and only the results for this electrode are reported.

## Results

### Behavioral Performance

Behavioral performance (P) on the trained stimulus set is shown over the 15 sessions of training in Figure 2A, where performance on the opening and closing test sessions is also depicted. Performance improved rapidly from the opening test session and then more gradually thereafter. A significant main effect of training sessions [F(14,92) = 4.72, P < 0.001] was found, as were significant preplanned contrasts between training sessions 1 and 15 [t(7) = 3.86, P = 0.006] and 3 and 13 [t(7) = 2.68, P = 0.03] which corroborated gradual improvement throughout the training series. Performance on the test sessions given before and after training is contrasted for the trained stimulus set and the two control sets in Figure 2B. Main effects were found for before/after [F(1,7) = 19.27, P = 0.003] and for stimulus set [F(2,14) = 7.32, P = 0.006] and as well as an interaction of these variables [F(2,14) = 22.01, P < 0.001]. Performance improved after training on all three stimulus sets, but more so for the 2.0 kHz set [t(7) = 6.90, P < 0.001] than for the 1.8 kHz [t(7) = 2.66, P = 0.04] and 2.2 kHz [t(7) = 2.72, P = 0.03] untrained stimuli.

Training effects were corroborated by d′ and by psychophysical functions calculated for each subject. When averaged over subjects d′ increased from 0.99 at the outset of training (sessions 1–3 collapsed) to 1.59 at the end of training (sessions 13–15 collapsed), giving t(7) = 4.69, P = 0.002. Psychophysical functions are shown for each stimulus set in Figure 2C. Discrimination thresholds (Δf at P = 0.5) decreased from 20.3, 20.2 and 16.7 Hz prior to training for the 1.8, 2.0 and 2.2 kHz sets, respectively, to 9.3 Hz for the trained 2.0 kHz set and to 16.0 and 11.6 Hz for the 1.8 and 2.2 kHz sets, respectively. These results gave rise to a main effect of before/after [F(1,7) = 7.624, P = 0.028] and to an interaction with stimulus set [F(2,14) = 6.289, P = 0.011] which was attributable to before/after differences appearing for the trained stimuli [t(7) = 2.99, P = 0.02] but not for either of the control sets. When the threshold of discrimination at 2.0 kHz was divided by stimulus frequency after training (Δf/f), a ratio of 0.46% was found which is similar to ratios reported by discrimination studies using unmodulated tones (He et al., 1998). The slope of the psychophysical function after training was steepest for the 2.0 kHz trained stimulus set and shallowest for the 1.8 kHz control set (Fig. 2C), but differences in slope among the stimulus sets did not reach significance.

Six subjects returned for a retention test on the 2.0 kHz stimulus set 2 months after their last test session. Performance at retention (P = 0.63) was lower than on the last training session [P = 0.75, t(5) = –2.80, P = 0.038] but remained better than in the first test block [P = 0.32, t(5) = 3.76, P = 0.013].

### Transient AEPs

N1 and P2 transient responses evoked by the S1 reached their amplitude maxima at frontal electrodes with a polarity reversal at occipital sites. Time domain averages at the frontal electrode (Fz) and global field power (root mean square of all electrodes) are shown for the trained 2.0 kHz S1 in Figure 3A,B where N1 and P2 components are identified (pre-training latencies of 116 ms and 172 ms, respectively). The early occurring P1 (pre-training latency 57 ms) is also identified in these traces. Scalp topographies are shown for the N1 and P2 at their post-training amplitude maxima in Figure 3D. These results show that discrimination training resulted in an enhancement of P2 amplitude. When referred to the pre-stimulus baseline, P2 amplitude increased from 0.65 µV before training to 1.46 µV after training [t(7) = 6.03, P < 0.001], corresponding to an increase of 124% for the group as a whole. Enhancement of the P2 was also prominent in global field power (Fig. 3B). On the other hand, N1 and P1 amplitude tended to decrease after training, but these effects did not reach significance.

P2 amplitude is shown before and after training for each stimulus set in Figure 4A, referenced in this case to the peak of the N1 (P2–N1 amplitude) in order to remove influences attributable to variability in the N1. Analysis of variance revealed a main effect of before/after [F(1,7) = 6.7, P = 0.036] but the interaction of before/after with stimulus set was not significant. When the stimulus sets were examined separately, before/after differences in P2 amplitude were found to be significant only for the trained 2 kHz stimulus set [t(7) = 4.26, P = 0.008]. However, differences for the control sets were in the direction of training and suggested partial generalization of P2 enhancement to the untrained stimuli. Correlations were calculated between before/after differences in P2–N1 amplitude and the behavioral measure P for the trained stimulus set alone, and when the three stimulus sets were combined. These correlations were positive but none reached significance.

Acquisition of the enhanced P2 (referenced to the pre-stimulus baseline) over sessions is shown in Figure 4C which includes training sessions 3 and 13 as well as the opening and closing test sessions. A main effect of sessions was found for this measure [F(3,21) = 4.15, P = 0.019] which was attributable to increases in P2 amplitude occurring on the 13th session of training and on the closing test session compared to session 3 and pre-training performance (P < 0.015 or better). For purposes of comparison, Figure 4C also depicts changes observed in the amplitude of P1 and N1 responses referenced to their pre-stimulus baselines. Main effects of sessions did not reach significance for either measure (P = 0.16 and 0.084 for P1 and N1, respectively).

Figure 3C depicts changes occurring over sessions in a fourth AEP component that reached its amplitude maximum at electrode T8 over the right hemisphere. We identified this surface-negative component as the N1c in accordance with properties described by Woods (1995). The N1c was distinguishable from the N1 and P2 by its radial orientation, by its latency (155 ms) falling between that of these two AEPs, and by its preferential expression in the right hemisphere. Discrimination training enhanced the N1c between the two test sessions for the trained S1 stimulus [t(7) = 3.81, P = 0.007], gradually over the training series [see Fig. 4C; main effect of sessions F(3,21) = 4.05, P = 0.02]. Before/after training differences in N1c amplitude for the trained and control stimulus sets are shown in Figure 4B. Although before/after differences were largest for the trained stimulus set, enhancement generalized as well to the 2.2 kHz control set where before/after differences reached significance [t(7) = 2.89, P = 0.023]. Analysis of variance revealed a main effect of before/after [F(1,7) = 9.52, P = 0.018], but main effects or interactions involving stimulus set did not reach significance. We also searched for an N1c occurring in the left hemisphere (electrode T7) in each test session. An enhanced polarity-inverted response was observed after training at a peak latency (155 ms) that corresponded with the amplitude maximum of the N1c recorded in the right hemisphere. However, the before/after training difference in the polarity inverted response was not significant at its amplitude maximum (t = –0.84), nor were before/after differences detected at any other time point in the T7 trace of the left hemisphere.

We also examined the effect of discrimination training on the latency of the P1, N1, N1c and P2 responses evoked by the trained S1. N1 latency decreased from 116 ms in the first test session to 107 ms in the closing test session, t(7) = 7.94, P < 0.001. This effect was obtained in every subject and can be seen in Figure 3A,B (time domain traces and global field power). P1 and P2 latency, and N1c latency in the right hemisphere, did not change with discrimination training when measured at their amplitude maxima. However, the leading edge of the P2 and N1c waveforms tended to commence earlier after training compared to their pre-training baselines (see Fig. 3A,C).

A time domain trace of the 40 Hz SSR evoked by the 2.0 kHz S1 after training is depicted in the lower trace of Figure 1B at its amplitude maximum (Fz electrode). Neither responding at this electrode nor SSR global field power differed between test sessions administered before and after training when calculated over the 1 s S1 period. However, fine grained dynamics were revealed by T2 when 100 ms windows were moved across the 40 Hz waveform at Fz in 10 ms time steps. Figure 5A gives the results for a representative subject. Two polar plots are shown (right side), each containing vectors depicting SSR amplitude and phase on the 288 accepted test trials in a single 100 ms window before (upper, test 1) and after (lower, test 2) discrimination training. Although phase covers 360° and is variable across single trials, the end point of the mean vector (resultant, shown as the red arrow) is shifted from the origin in both polar plots, indicating that a 40 Hz SSR is present. Spectral plots of T2 are shown to the left of Figure 5A and indicate that a 40 Hz SSR was present throughout the stimulation period before (upper plot) and after (middle plot) training (all T2 > 45). The lower spectral plot in Figure 5A shows the T2 difference between the two test sessions before and after training for this subject, scaled for Monte Carlo significance at T2= 8.0, P < 0.01. Before/after differences reached significance particularly in the first half of the S1 stimulation period, with patches of significance appearing subsequently.

Similar findings were obtained for all subjects to which this analysis was applied. The results are collapsed across subjects in Figure 5B where the before/after T2 difference is thresholded for significance at T2 = 4.5 (P < 0.05, light blue; T2 = 6.0, P < 0.01, yellow and above). Results are shown for the trained S1 (2.0 kHz) as well as for the S1s of the untrained 1.8 kHz and 2.2 kHz stimulus sets. Time-domain traces of the 40 Hz SSR evoked by the 2.0 kHz S1 before and after training are superimposed above the T2difference map for the 2.0 kHz stimulus. Significant before/after differences were observed in the SSR evoked by the trained S1, particularly in the time interval 150–225 ms after S1 onset, with brief epochs of significance appearing thereafter. Integration of the T2 statistic over the time interval 50–400 ms at 40 Hz found that before/after differences were stronger for the trained 2.0 kHz S1 than for the untrained 1.8 kHz S1 [t(5) = 2.29, P = 0.035, one-tailed test] while differences between the 2.0 kHz and 2.2 kHz S1 stimuli were not significant. These results indicate that generalization occurred from training on the 2.0 kHz set to the 2.2 kHz control set, but not to the 1.8 kHz control set.

Augmentation of the SSR within the interval 150–225 ms raises the question of whether the T2 results shown in Figure 5B might alternatively be attributed to a 40 Hz spectral component of the transient P2 which was also augmented in the vicinity of this time window. To assess this hypothesis, we evaluated 40 Hz activity in the absence of the SSR when N1 and P2 transient responses were evoked by unmodulated 2.0 kHz tones. The results are shown in Figure 5C where the N1/P2 waveform evoked by the unmodulated tone is superimposed on 40 Hz activity evaluated by T2 at the same scaling used for the upper two T2 maps of Figure 5A. 40 Hz activity was detected between 30 and 50 ms where middle latency responses or transient gamma band responses were expected (Pantev et al., 1991). However, this activity subsided by ∼80 ms and did not extend into the latency window encompassing N1 and P2 transient responses. These findings indicate that T2 differences observed for the 2.0 kHz AM S1 (Fig. 5B) are not likely to be attributable to a high-frequency component of the enhanced P2 transient response, because no such component was detected in the latency window of the P2 in the unmodulated control condition. Rather, the two responses appeared to be separate brain events.

Changes in the SSR induced by training and detected by T2 could be generated by changes in the amplitude or phase of the SSR, or both. In order to address this question, we first calculated mean SSR amplitude and phase delay (difference between stimulus phase and response phase) for each subject and 100 ms window during the S1 stimulus. The results are shown in Figure 5D for the group as a whole where SSR amplitude and phase delay (middle panels) are aligned to the transient N1/P2 waveform obtained before and after training (top panel). For convenience, T2values comparing group before/after SSR differences for the trained S1 are plotted over time in the bottom panel of Figure 5D, with light and dark shading indicating P < 0.05 and P < 0.01, respectively. Light shading is extended into the upper panels of Figure 5 to identify the region of maximum T2 difference. Inspection of phase delay during the first test session (blue trace) shows that SSR phase shortened gradually commencing ∼100 ms post-stimulus and reaching asymptote ∼400 ms. After training (red trace) SSR phase advanced by ∼0.3 radians (4.8% of the wave period of the SSR) with respect to pre-training performance within this time interval, commencing near but persisting beyond the leading edge of the P2 waveform. Phase advances tended to recur subsequently during the S1 interval, coinciding with significant differences in the T2 difference map. On the other hand, before/after differences in SSR amplitude were less apparent during the S1 (Fig. 5D, second panel), although a small enhancement is seen during the interval 100–200 ms after stimulus onset. Supplementary analyses not presented in the figure showed that this enhancement was closely paralleled by an increase in phase coherence with no change in absolute vector length, suggesting that it was secondary to a reduction of phase variability around its central tendency during this interval. Multiple regression applied to T2 differences recorded for the group during the S1 yielded R = 0.455 [F(2,96) = 15.5, P < 0.00001] to which before/after differences in phase contributed [t(96) = 5.00, P < 0.00001] but differences in mean vector length did not [t(96) = –0.54, P = 0.41]. These findings indicate that discrimination training modified the temporal properties of the 40 Hz SSR but had little effect on the absolute amplitude of this response. A computer animation showing phase and amplitude dynamics of the mean vector for a representative subject throughout the S1 can be viewed at www.psychology.mcmaster.ca/hnplab.

### Source Analyses

The spatial coordinates of regional sources modeled from the grand averaged data for each AEP (N1, N1c, P2 and SSR) were evaluated by analyses of variance collapsing first over before/after test sessions (to examine effects of stimulus set) and then over stimulus sets (to examine effects of before/after). No effects of stimulus set or before/after were found, except for the sources of the P2 which shifted to be more inferior when training had been completed [z coordinate, F(3,12) = 13.53, P = 0.0007]. However, main effects attributable to AEP were found in both of these analyses. When the six localizations determined for each AEP (three stimulus sets before and after training) were collapsed into a single data set, main effects of AEP were significant for the medial lateral (x) coordinate [F(3,15) = 25.97, P < 0.00001], anterior–posterior (y) coordinate [F(3,15) = 9.22, P = 0.001], and inferior–superior (z) coordinate [F(3,15) = 24.95, P < 0.00001]. The modeled sources for each AEP are co-registered on the average brain of BESA 2000 in Figure 6 in order to visualize their relative positions. Post hoc contrasts showed that cortical sources underlying the N1 and N1c were centered lateral with respect to those of the P2 in the region of the auditory cortex (P < 0.01 or better, axial view), while sources of the SSR were medial with respect to P2, N1 and N1c sources (P < 0.03 or better). P2 sources were also centered anterior with respect to sources of the N1, N1c and SSR (P < 0.05 or better), and superior with respect to these sources (minimum P < 0.0001) when averaged before and after training. These results which confirm SSR sources medial to those of the N1 and P2 are consistent with previous studies which have localized SSR generators by source modeling (Scherg and von Cramon, 1986; Pantev et al., 1996a; Gutschalk et al., 1999; Engelien et al., 2000; Godey et al., 2001; Yvert et al., 2001; Schneider et al., 2002; Shahin et al., 2003) and by intracortical measurements (Celesia, 1976; Liégeois-Chauvel et al., 1993; Godey et al., 2001) to the region of Heschl’s gyrus. Differentiation of P2 from N1 and N1c sources and from those of the SSR is in agreement with previous findings which have localized P2 and N1 sources to the region of A2 (Scherg and von Cramon, 1986; Pantev et al., 1996b; Picton et al., 1999) including for P2 sites anterior to the auditory core (Hari et al., 1987; Joutsiniemi et al., 1989; Pantev et al., 1996b). P2 sources may reflect activation centered in anterior auditory belt regions of A2 which receive reciprocal connections from other belt areas and from parabelt zones that project reciprocally to prefrontal cortex (Kaas and Hackett, 1998; Hackett et al., 2001). N1 and N1c sources may reflect activation of posterior and lateral parabelt regions which have dense connections with caudal and rostral parts of the superior temporal gyrus. A note of caution regarding differentiation of P2, N1, and N1c sources within A2 is that source analysis estimates only centers of activation and cannot resolve overlapping generators of similar orientation or determine their spatial extent.

Dipole moment was also contrasted for each AEP before and after training, using the three stimulus sets as the unit of observation. This analysis revealed a main effect of before/after [F(1,4) = 12.83, P = 0.023] and an interaction of before/after with AEP [F(3,12) = 6.331, P = 0.008]. Both of these effects were attributable to enhanced dipole moments occurring for the P2 in each stimulus set after training [F(1,4) = 18.06, P = 0.013] compared with the other AEPs. Dipole moment was not significantly enhanced after training for any other component in either hemisphere. However, subsequent analyses showed that the regional source fitted to the N1 field pattern contained a radially oriented vector that was augmented after discrimination training only in the right hemisphere, with an amplitude peak near 148 ms when the N1 source model was applied to the N1c time interval. This suggests that dipole moment calculated for the regional source fitted to the N1c field pattern contained contributions arising from the temporally overlapping N1 that obscured changes in radially oriented N1c activity. We also examined the contribution of the three orthogonal vectors of the SSR regional source to the SSR waveform after discrimination training, following the procedure of Scherg and von Cramon (1986). The regional model accounted for 97.9% of the observed field pattern when the three vectors were included. Goodness of fit decreased to 93.3% when only a single tangential source was used to model the field pattern, whereas a single radial source accounted for only 6.3% of the variability in the recorded field pattern. These findings indicate that activity modeled by the tangential vector was the principal contributor to the SSR waveform.

## Discussion

We trained non-musician subjects to discriminate small increases in the pitch of a 2.0 kHz standard stimulus, using 40 Hz AM modulated pure tones as the discriminative stimuli. Amplitude modulation allowed us to separate the 40 Hz auditory SSR whose generators localize to the region of Heschl’s gyrus in A1 from transient responses of the AEP (N1, N1c, P2) whose modeled centers of activation are spatially differentiable in A2. Discrimination improvement was accompanied by enhancement of the P2 (latency 172 ms) and of the N1c (in the right hemisphere, latency 155 ms), indicating an increase in synchronous neural activity in A2 after training on the discrimination task. The 40 Hz SSR, on the other hand, gave a different picture of cortical dynamics. Overall, there was no overall amplitude enhancement of the SSR; instead we observed a shortening of phase within a latency window coinciding with the onset of the P2 with brief advances in phase reappearing subsequently during the S1. These findings suggest that training at pitch discrimination did not expand the cortical representation for the 2.0 kHz S1 in A1. Instead, temporal properties of the SSR representation were modified by experience on the task. Because both transient and steady-state responses were affected by training, it appears that neural activity was modified in distributed regions of the auditory cortex, particularly in A2 where plasticity appears to be widely expressed in animal studies (Diamond and Weinberger, 1984).

Enhancement of the P2 transient response by acoustic training appears to be a robust phenomenon. To our knowledge, this effect was first described by Eaton and Roberts (1999) in a preliminary study using the present methods. Working independently, Tremblay et al. (2001) observed enhancement of the P2 when non-musician subjects were trained to discriminate temporal features of speech signals. More recently, Atienza et al. (2002) found an enhancement of the P2 when subjects were trained to detect pitch deviants in a short stream of pitch stimuli. In each of these studies P2 amplitude increased by ∼100% when measured from the amplitude peak of the N1 which did not change with training in any study. These results indicate that the neural mechanisms underlying the P2 brain event are sensitive to remodeling by experience. Heretofore this component of the AEP has received little attention in studies of auditory perception, perhaps because in the absence of a training manipulation the P2 shows more limited dynamics.

Enhancement of the N1c by acoustic training has not previously been reported. The expression of the N1c in the right hemisphere in our study where subjects were processing pitch cues is consistent with functional and anatomical evidence for specialization of auditory neurons in this hemisphere for processing of spectral information. Compared to homologous auditory neurons in the left hemisphere, neurons in the right hemisphere are characterized by higher synaptic densities, more closely spaced cortical columns, and comparatively less myelination, which are features that may favor spectral integration of acoustic signals (Zatorre and Belin, 2001). Woods (1995) noted that because its expression is variable, less is known about the N1c component of the AEP compared to other components. A key to expression and enhancement of the right-sided N1c may be the presence of multiple auditory objects in a stimulus sequence that must be distinguished by their spectral properties in order for the subject to comply with task requirements.

In contrast to the P2 and N1c, the N1 (latency 107 ms) was not amplified by discrimination training in our study or in the aforementioned EEG studies of acoustic discrimination. However, enhancement of its magnetic counterpart the N1m by training at pitch discrimination has been reported by Menning et al. (2000). It should be noted that an augmented P2 brain event commencing within the N1 latency window would subtract from N1 amplitude in electrical recordings, but not necessarily in magnetic recordings owing to the insensitivity of magnetic sensors to radial currents contributing to the P2. This factor could explain discrepant EEG and MEG findings with regard to N1 amplitude enhancement. Although N1 amplitude was not modified, N1 latency diminished by 9 ms after training in our study. Competition among synapses favoring fast inputs could generate a latency shift of this magnitude (Song et al., 2000), as could an overlapping of AEP components. In the latter respect it may be noteworthy that N1c and P2 responses tended to commence earlier after training within a time interval coinciding with the onset of the N1 (see Fig. 3A,C). When we modeled the N1 field pattern with a regional source, a radial component appeared in the right hemisphere with an early onset latency that could have reflected a contribution arising from the N1c.

The cortical sources that we modeled for the P2, N1, and N1c were consistent with previous studies that differentiated these sources localizing within A2 from sources of the 40 Hz SSR which localize more medially to Heschl’s gyrus in the auditory core (Pantev et al., 1993; Schneider et al., 2002; Shahin et al., 2003). However, the changes that we observed in the SSR after training did not include amplitude enhancements that were expected on the basis of research in owl monkeys where increased spiking of A1 neurons (Blake et al., 2002) and expansion of the tonotopic representation in A1 (Recanzone et al., 1993) were found for stimuli associated with reward. Rather, our results are more in line with those of Kilgard et al. (2001) which show that behavioral conditioning with multiple frequencies tends to preserve segregated tonotopic representations in A1. Several factors may account for the different findings among these studies including the training procedures that were used, their duration, whether the relevant rules for cortical reorganization were optimized, and whether the methods used to measure cortical reorganization were sensitive to the changes that occurred. With respect to the latter variable it should be noted that our results do not appear to be attributable to insensitivity of the SSR to the anatomy or functional organization of Heschl’s gyrus. Schneider et al. (2002) found that the N19-P30 source waveform underlying the SSR was augmented by 102% in musician compared to non-musician subjects, when extracted by deconvolution from AM rates near 39 Hz. The SSR source waveform also correlated highly (r = 0.87) with the volume of gray matter in the anteromedial portion of Heschl’s gyrus well as with musical aptitude (r = 0.71). In our study temporal modulation of the SSR generalized more to the untrained 2.2 kHz S1 than to the untrained 1.8 kHz S1, perhaps because subjects were trained to detect only increases from 2.0 kHz (range 2.0–2.1 kHz) and experienced no stimuli below 2.0 kHz during training. Although behavioral performance did not differ significantly between the two control sets, behavioral performance was consistently better on the 2.2 kHz set as assessed by P, d′, discrimination thresholds, and the slope of psychophysical functions obtained after discrimination training.

Modification of distributed auditory cortical representations in the present study raises the question of how remodeling was achieved and expressed in the AEP. Detailed laminar analyses of multiple unit activity in relation to current sinks and sources in the auditory cortex of the awake monkey suggest that positive-going surface potentials of the P1–N1–P2 complex are generated principally by depolarization of pyramidal neurons in neocortical layers III–VI, while surface negativities reflect depolarization of apical dendrites in the upper neocortical laminae [see Fig. 1 (Fishman et al., 2000) and Fig. 2 (Fishman et al., 1998)]. Results summarized by Mitzdorf (1994) for the cat and for auditory middle latency responses of the rat by Sukov and Barth (1998) are consistent with this interpretation, although a role for hyperpolarization in primate cortex cannot be ruled out (Schroeder et al., 1995). If this interpretation is provisionally accepted for the P2 and N1c components of the human AEP, our results imply that more pyramidal neurons were depolarizing synchronously in A2 after training on the discrimination task than before training commenced. Modulation of the neocortical mantle by the basal forebrain (nucleus basalis magnocellularis, NBM) is one possible source of these enhancements. This structure, which has been implicated in neuroplastic remodeling by many researchers (e.g. Weinberger et al., 1990; Dykes, 1997; Wenk, 1997; Edeline, 1999), contains large cholinergic and GABAergic neurons that project to targets in the neocortex in a broadly tuned corticotopic arrangement (Jiménez-Capdeville et al., 1997). Because GABAergic fibers synapse on inhibitory interneurons (Freund and Meskenaite, 1992), coactivation of cholinergic and GABAergic pathways acts synergistically to increase the sensitivity of pyramidal cells to their afferent inputs, shortening response latency by a magnitude similar to that which we observed in SSR phase after training (Metherate and Ashe, 1993) and strengthening synaptic connections on auditory neurons by a Hebbian correlation rule (Metherate and Weinberger, 1990; Cruikshank and Weinberger, 1996; Kilgard and Merzenich, 1998). These findings suggest that modulation of the neocortical mantle by the NBM serves an attention-like function that gates plastic changes at the synapse and facilitates their expression in performance after synaptic remodeling has occurred. When measured by slow cortical potentials (Pirch, 1993; Pirch et al., 1983), modulation by the NBM has an onset latency resembling that of the auditory N1/P2 complex, as do top-down signals from prefrontal cortex which may converge on auditory neurons and serve an additional teaching role (Tomita et al., 1999). Although strengthening of modulation itself by conditioning (Rigdon and Pirch, 1986) could account for augmented P2 responses, evidence summarized by Dykes (1997) indicates that additional cortical neurons are likely to become tuned to the task stimuli during training and to contribute to progressive improvements in behavioral performance such as those observed in our study. Network behavior of this nature would be expected to influence plastic remodeling of sensory modalities in addition to audition, although not necessarily at the same latencies observed in the auditory case.

Possible constraints on interpretation of present findings should be acknowledged. Enhancements in the amplitude of P2 and N1c responses could in principle be attributed either to an increase in the number of neurons activated by a stimulus or to an increase in the synchrony of their depolarization. Calculations reported by Hari (1990) suggest that increases in synchronous activity representing 5% of the neurons in a cortical area 1 mm2 can account for a scalp recorded AEP. We cannot unequivocally assess the relative contributions of number of neurons or synchrony to enhancement of P2 and N1c transient responses in our study. However, because the temporal envelopes of the augmented P2 and N1c responses were broad and did not appear to change notably after training, an increased number of contributing neurons may have been the more significant variable. Auditory neurons are also sensitive to eye position and the spatial location of acoustic stimuli (Werner-Reiss et al., 2003). This raises the question of whether eye position or head movements induced by the processing of visual feedback cues may have contributed to training effects on AEPs. This would appear to be unlikely, because test sessions before and after training were carried out under identical conditions in which visual feedback cues were eliminated. It is also not clear how undetected head or eye movements directed toward a darkened feedback light in the center of the visual field could preferentially influence the right-sided N1c, or explain P2 enhancements reported in studies by Atienza et al. (2002) and Tremblay et al. (2001) which used different feedback arrangements (feedback after only blocks of trials, or no feedback during testing, respectively).

Shahin et al. (2003) recently reported that P2 responses evoked by musical tones in violinists and pianists were larger than those observed in non-musician subjects, as were right-sided N1cs. These results could have been predicted from the present findings owing to the different training histories of musicians and non-musicians with respect to tones of musical timbre. On the other hand, our findings with regard to the effects of training on the 40 Hz SSR suggest a dissociation of transient and SSR components of the AEP, with neuroplastic transient responses expressing as amplitude enhancements in training studies and in musicians but 40 Hz SSR enhancements in musicians only (Schneider et al., 2002) where they may be an anatomical marker for musical skill. However, we cannot exclude the possibility that other training procedures may modify SSR amplitude and its anatomical substrate, depending on the type of training that is given, its duration, and when it is delivered in the course of brain development.

This research was supported by grants from the Canadian Institutes of Health Research (Operating and NET) and the Natural Sciences and Engineering Research Council of Canada.

Figure 1. (A) Waveform and spectrum of the 40 Hz AM stimulus at 2.0 kHz (the standard stimulus of the trained stimulus set). (B) Auditory evoked potential elicited by the 2.0 kHz stimulus of A on test trials administered after 15 sessions of training for pitch discrimination. Middle trace: auditory evoked potential (high-pass filtered at 1 Hz) shows the 40 Hz SSR riding on a low frequency transient waveform. Upper trace: P1, N1 and P2 transient responses are set into relief by low-pass filtering at 15 Hz to remove the 40 Hz component. Lower trace: band pass filtering (30–50 Hz) singles out the 40 Hz SSR. Each step on the ordinate is 1 µV (each trace referenced to zero). (C) Single trial T2 analysis of the 40 Hz SSR. SSR amplitude on each trial is represented by vector length and phase by the angle θ. Vector end points do not include the origin when a steady state response is present.

Figure 1. (A) Waveform and spectrum of the 40 Hz AM stimulus at 2.0 kHz (the standard stimulus of the trained stimulus set). (B) Auditory evoked potential elicited by the 2.0 kHz stimulus of A on test trials administered after 15 sessions of training for pitch discrimination. Middle trace: auditory evoked potential (high-pass filtered at 1 Hz) shows the 40 Hz SSR riding on a low frequency transient waveform. Upper trace: P1, N1 and P2 transient responses are set into relief by low-pass filtering at 15 Hz to remove the 40 Hz component. Lower trace: band pass filtering (30–50 Hz) singles out the 40 Hz SSR. Each step on the ordinate is 1 µV (each trace referenced to zero). (C) Single trial T2 analysis of the 40 Hz SSR. SSR amplitude on each trial is represented by vector length and phase by the angle θ. Vector end points do not include the origin when a steady state response is present.

Figure 2. Behavioral performance. (A) The performance measure P (hit rate corrected for false alarms) is plotted over 15 sessions of discrimination training and on the opening (Test 1) and closing (Test 2) test sessions. Data are for the trained 2.0 kHz stimulus set. (B) Performance on test blocks administered before and after discrimination training is contrasted for the trained stimulus set (2.0 kHz) and for control sets (1.8 and 2.2 kHz) above and below the trained stimuli. (C) Psychophysical functions before and after training on the three stimulus sets.

Figure 2. Behavioral performance. (A) The performance measure P (hit rate corrected for false alarms) is plotted over 15 sessions of discrimination training and on the opening (Test 1) and closing (Test 2) test sessions. Data are for the trained 2.0 kHz stimulus set. (B) Performance on test blocks administered before and after discrimination training is contrasted for the trained stimulus set (2.0 kHz) and for control sets (1.8 and 2.2 kHz) above and below the trained stimuli. (C) Psychophysical functions before and after training on the three stimulus sets.

Figure 3. Effect of discrimination training on transient AEPs. (A) Augmentation of the P2 evoked by the trained S1 stimulus. P1, N1 and P2 AEPs are identified and shown for the opening (black, Test 1) and closing (gray, Test 2) test sessions. (B) Global field power evoked by the trained S1 stimulus over all electrodes. (C) Augmentation of the N1c in the right hemisphere by discrimination training. (D) Scalp topographies are given for N1, N1c and P2 at their post-training amplitude maxima.

Figure 3. Effect of discrimination training on transient AEPs. (A) Augmentation of the P2 evoked by the trained S1 stimulus. P1, N1 and P2 AEPs are identified and shown for the opening (black, Test 1) and closing (gray, Test 2) test sessions. (B) Global field power evoked by the trained S1 stimulus over all electrodes. (C) Augmentation of the N1c in the right hemisphere by discrimination training. (D) Scalp topographies are given for N1, N1c and P2 at their post-training amplitude maxima.

Figure 4. Acquisition of changes in transient AEPs. (A) P2–N1 amplitude is shown on test sessions before and after training for each stimulus set. The 2.0 kHz set was trained. (B) N1c amplitude on test sessions before and after training for each stimulus set. (C) Acquisition of P2 and N1c enhancements over discrimination training. Changes observed for the P1 and N1 are also shown. Response amplitude is referenced to the pre-stimulus baseline and depicted for test session 1, training sessions 3 and 13, and test session 2 (labeled Sessions 1–4, respectively).

Figure 4. Acquisition of changes in transient AEPs. (A) P2–N1 amplitude is shown on test sessions before and after training for each stimulus set. The 2.0 kHz set was trained. (B) N1c amplitude on test sessions before and after training for each stimulus set. (C) Acquisition of P2 and N1c enhancements over discrimination training. Changes observed for the P1 and N1 are also shown. Response amplitude is referenced to the pre-stimulus baseline and depicted for test session 1, training sessions 3 and 13, and test session 2 (labeled Sessions 1–4, respectively).

Figure 5. Effect of discrimination training on the 40 Hz SSR. (A) T2 analysis applied to a representative subject. Polar plots in the right panels depict the 40 Hz SSR in a single 100 ms window 50 ms after onset of the trained S1, on test blocks given before (upper, test 1) and after (lower, test 2) discrimination training. Each vector is a single trial. The spray of vectors is concentrated in the lower right quadrants indicating that an SSR is present (the red arrows are mean vectors). Corresponding T2 plots are shown in the left panels of the figure (upper panel test 1, middle panel test 2). The lower left panel shows the T2 difference map obtained for this subject, thresholded for significant before/after differences (T2 = 8.0, P < 0.01, red) in the SSR. T2 differences were more prominent in the first half of the stimulation period. (B) T2 difference maps are shown for the group as a whole for the trained S1 (2.0 kHz) and control (1.8 and 2.2 kHz) S1 stimuli. Maps are thresholded at T2 = 4.5 (P < 0.05, light blue; T2 = 6.0, P < 0.01, yellow and above). Time domain traces of the 40 Hz SSR are superimposed above the 2.0 kHz map (dark blue before training, red after). Before/after T2 differences were observed for the 2.0 kHz S1 in the interval 100–225 ms after stimulus onset with brief periods of significance reappearing thereafter. Generalization to the untrained 2.2 kHz S1 but not to the 1.8 kHz S1 is seen. (C) Evaluation of 40 Hz activity in control subjects tested for discrimination using unmodulated stimuli. The N1/P2 transient response evoked by the unmodulated 2.0 kHz S1 is superimposed on the T2 map. No 40 Hz activity was observed to overlap the N1/P2 transient waveform evoked by this stimulus. (D) Middle panels: changes in SSR amplitude (mean vector) and phase delay (difference between stimulus and response phase) during the S1 interval on test trials before (test 1) and after (test 2) training, for the group as a whole. For convenience the transient N1/P2 waveform evoked by the trained S1 (top panel) and the group T2 difference at each time point (bottom panel) are aligned to these data. The shaded areas in the T2 measure denote level of significance and are extended to the upper panels to identify the region of the largest T2 effect. A phase advance occurring in the interval 100–225 ms after training was the principal source of the T2 difference in this interval and in subsequent intervals during the S1 (see phase delay panel). Periods of significance in the T2 difference map over the duration of the S1 correlated with changes in SSR phase delay (P < 0.0001) but not with changes in SSR amplitude measured as the mean vector (P > 0.40).

Figure 5. Effect of discrimination training on the 40 Hz SSR. (A) T2 analysis applied to a representative subject. Polar plots in the right panels depict the 40 Hz SSR in a single 100 ms window 50 ms after onset of the trained S1, on test blocks given before (upper, test 1) and after (lower, test 2) discrimination training. Each vector is a single trial. The spray of vectors is concentrated in the lower right quadrants indicating that an SSR is present (the red arrows are mean vectors). Corresponding T2 plots are shown in the left panels of the figure (upper panel test 1, middle panel test 2). The lower left panel shows the T2 difference map obtained for this subject, thresholded for significant before/after differences (T2 = 8.0, P < 0.01, red) in the SSR. T2 differences were more prominent in the first half of the stimulation period. (B) T2 difference maps are shown for the group as a whole for the trained S1 (2.0 kHz) and control (1.8 and 2.2 kHz) S1 stimuli. Maps are thresholded at T2 = 4.5 (P < 0.05, light blue; T2 = 6.0, P < 0.01, yellow and above). Time domain traces of the 40 Hz SSR are superimposed above the 2.0 kHz map (dark blue before training, red after). Before/after T2 differences were observed for the 2.0 kHz S1 in the interval 100–225 ms after stimulus onset with brief periods of significance reappearing thereafter. Generalization to the untrained 2.2 kHz S1 but not to the 1.8 kHz S1 is seen. (C) Evaluation of 40 Hz activity in control subjects tested for discrimination using unmodulated stimuli. The N1/P2 transient response evoked by the unmodulated 2.0 kHz S1 is superimposed on the T2 map. No 40 Hz activity was observed to overlap the N1/P2 transient waveform evoked by this stimulus. (D) Middle panels: changes in SSR amplitude (mean vector) and phase delay (difference between stimulus and response phase) during the S1 interval on test trials before (test 1) and after (test 2) training, for the group as a whole. For convenience the transient N1/P2 waveform evoked by the trained S1 (top panel) and the group T2 difference at each time point (bottom panel) are aligned to these data. The shaded areas in the T2 measure denote level of significance and are extended to the upper panels to identify the region of the largest T2 effect. A phase advance occurring in the interval 100–225 ms after training was the principal source of the T2 difference in this interval and in subsequent intervals during the S1 (see phase delay panel). Periods of significance in the T2 difference map over the duration of the S1 correlated with changes in SSR phase delay (P < 0.0001) but not with changes in SSR amplitude measured as the mean vector (P > 0.40).

Figure 6. Localizations of the cortical sources of N1, N1c and P2 transient responses and the 40 Hz SSR determined from the grand averaged data. The coordinate system is shown in the inset.

Figure 6. Localizations of the cortical sources of N1, N1c and P2 transient responses and the 40 Hz SSR determined from the grand averaged data. The coordinate system is shown in the inset.

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