Annemarie Seither-Preisler

Studies of tonotopy based on wave N100 of the auditory evoked field are problematic

There is still dissension as to whether the auditory evoked field (AEF) reflects tonotopy in the auditory cortex. That notwithstanding, particularly the pronounced AEF wave occurring about 100 ms after stimulus onset (N100 m) is increasingly used for the investigation of issues such as cortical reorganization and representation of virtual pitch. Thus, it appears to be time for a critical revaluation of the supposed tonotopic organization of the N100 m generator. In the present magnetoencephalography study, the response to tonebursts of 500 ms duration, monaurally presented 60 dB above threshold, was recorded with a 37-channel axial gradiometer system over the hemisphere contralateral to the side of stimulation. The stimulus frequencies were 250, 500, 1000, and 2000 Hz. About 250 stimuli of each type were presented in random order in four independent sessions at intervals uniformly distributed between 2 and 2.8 s. An analysis of 19 hemispheres in 10 normal-hearing subjects showed a high intraindividual reproducibility, but also a substantial interindividual variability. In most cases, the dipole location either exhibited no significant frequency dependence at all, the dipoles for the four frequencies were not orderly aligned, or the data disagreed with the single-dipole model. In the few cases showing an arrangement of dipoles consistent with the assumption of an orderly tonotopic cortical map, the most relevant coordinate varied from subject to subject. Regarding theses results, it seems crucial to understand wave N100 m on the basis of individual subjects, whereas conclusions relying on mean dipole locations for groups of subjects are problematic.

Localization of Primary Auditory Cortex in Humans by Magnetoencephalography

Brief auditory stimuli activate the primary auditory cortex (PAC) earlier than any other cortical area so, within a certain latency range, the PAC is the only cortical source contributing to the auditory evoked field (AEF). Nevertheless, there is no AEF component specific to PAC that can be reliably detected in all individuals. The present study suggests that a peak in the first temporal derivative of the magnetic field at about 20 ms (dP20m) is a genuine correlate of PAC activity. AEFs in response to clicks presented to the right ear were recorded with a 37-channel axial gradiometer system positioned over the left hemisphere in nine normal-hearing subjects. More than 8500 stimuli were presented in each of two independent sessions at a rate of approximately 3/s. The dipole coordinates for the dP20m derived from the two sessions typically differed by only a few millimeters. Coregistration of the dipoles with structural magnetic resonance images suggests that dP20m arises from an area close to the retroinsular origin of Heschls gyrus. Although the dP20m is simply the point of steepest slope on the well-known middle-latency peak, P30m or Pam, it would appear that dP20m and P30m do not have the same cortical origin. Evidence is provided that P30m receives major contributions from at least two distinct cortical areas, only one of which is PAC.

Piano tones evoke stronger magnetic fields than pure tones or noise, both in musicians and non-musicians

Regarding the net firing rate of the auditory nerve, the strongest response is to be expected when the input energy is spread as evenly as possible over the cochlea rather than being concentrated at a particular location. In some respects, this effect seems to be preserved up to the auditory cortex, but conflicting results have been reported as well. Here, we compared the auditory evoked fields (AEF) elicited by a pure tone and two sounds causing a more wide-spread cochlear activation: a piano tone as a representative of a complex tone, and bandpass noise. The stimuli had the same intensity (60 dB above threshold), and the center frequency of the noise corresponded to the fundamental frequency of the tones (1047 Hz, two octaves above middle C). Among the 26 subjects were 11 musicians and 11 persons who never played an instrument. At a latency of about 50 ms (wave P50m), the piano tone and the noise yielded stronger responses than the pure tone, in accordance with the concepts about the auditory periphery. By contrast, around 100 ms (wave N100m), the noise clearly elicited the smallest response, whereas the strongest response was elicited again by the piano tone. Musicians and non-musicians did not significantly differ concerning the responses to pure tones and piano tones. Thus, previous claims that an enhanced response to piano tones indicates use-dependent reorganization in musicians are not supported by the present data.

Sensitivity of the Neuromagnetic N100m Deflection to Spectral Bandwidth: A Function of the Auditory Periphery?

The amplitude of the auditory evoked field (AEF) component N100m in response to tonal stimuli of varying spectral bandwidth and periodicity was compared with simulated peripheral activity patterns of the auditory nerve (AN). The AEF of ten subjects was recorded with a 37-channel axial gradiometer system (four independent measurement sessions per hemisphere). The simulated peripheral activity was characterized using measures derived from spike probabilities of the AN. Stimuli were pure tones, narrow-band harmonic complex tones (spectrum: 4–4.8 kHz), and broad-band harmonic complex tones (spectrum: 800 Hz–4.8 kHz) with periodicities of 100, 200, and 400 Hz. The intensity of all stimuli was set to 65 dB above the absolute thresholds. Both the simulated AN activity and measured cortical response amplitudes increased consistently with spectral bandwidth. This suggests that the enhanced sensitivity of the N100m amplitude to broad-band complex tones is to some extent a function of the auditory periphery.

Tone sequences with conflicting fundamental pitch and timbre changes are heard differently by musicians and nonmusicians.

An Auditory Ambiguity Test (AAT) was taken twice by nonmusicians, musical amateurs, and professional musicians. The AAT comprised different tone pairs, presented in both within-pair orders, in which overtone spectra rising in pitch were associated with missing fundamental frequencies (F0) falling in pitch, and vice versa. The F0 interval ranged from 2 to 9 semitones. The participants were instructed to decide whether the perceived pitch went up or down; no information was provided on the ambiguity of the stimuli. The majority of professionals classified the pitch changes according to F0, even at the smallest interval. By contrast, most nonmusicians classified according to the overtone spectra, except in the case of the largest interval. Amateurs ranged in between. A plausible explanation for the systematic group differences is that musical practice systematically shifted the perceptual focus from spectral toward missing-F0 pitch, although alternative explanations such as different genetic dispositions of musicians and nonmusicians cannot be ruled out. ((c) 2007 APA, all rights reserved).

Interaction between the neuromagnetic responses to sound energy onset and pitch onset suggests common generators

The pitch‐onset response (POR) is a negative component of the auditory evoked field which is elicited when the temporal fine structure of a continuous noise is regularized to produce a pitch perception without altering the gross spectral characteristics of the sound. Previously, we showed that the latency of the POR is inversely related to the pitch value and its amplitude is correlated with the salience of the pitch, suggesting that the underlying generators are part of a pitch‐processing network [Krumbholz, K., Patterson, R.D., Seither‐Preisler, A., Lammertmann, C. & Lütkenhöner, B. (2003) Cereb. Cortex,13, 765–772]. The source of the POR was located near the medial part of Heschls gyrus. The present study was designed to determine whether the POR originates from the same generators as the energy‐onset response (EOR) represented by the N100m/P200m complex. The EOR to the onset of a noise, and the POR to a subsequent transition from noise to pitch, were recorded as the time interval between the noise onset and the transition varied from 500 to 4000 ms. The mean amplitude of the POR increased by ≈ 5.9 nA.m with each doubling of the time between noise onset and transition. This suggests an interaction between the POR and the EOR, which may be based on common neural generators.

Evidence of pitch processing in the N100m component of the auditory evoked field

The latency of the N100m component of the auditory evoked field (AEF) is sensitive to the period and spectrum of a sound. However, little attention was paid so far to the wave shape at stimulus onset, which might have biased previous results. This problem was fixed in the present study by aligning the first major peaks in the acoustic waveforms. The stimuli were harmonic tones (spectral range: 800-5000 Hz) with periods corresponding to 100, 200, 400, and 800 Hz. The frequency components were in sine, alternating or random phase. Simulations with a computational model suggest that the auditory-nerve activity is strongly affected by both the period and the relative phase of the stimulus, whereas the output of the more central pitch processor only depends on the period. Our AEF data, recorded from the right hemisphere of seven subjects, are consistent with the latter prediction: The latency of the N100m depends on the period, but not on the relative phase of the stimulus components. This suggests that the N100m reflects temporal pitch extraction, not necessarily implying that the underlying generators are directly involved in this analysis.

Different Modes of Pitch Perception and Learning-Induced Neuronal Plasticity of the Human Auditory Cortex

We designed a melody perception experiment involving eight harmonic complex tones of missing fundamental frequencies (hidden auditory object) to study the short-term neuronal plasticity of the auditory cortex. In this experiment, the fundamental frequencies of the complex tones followed the beginning of the virtual melody of the tune “Frère Jacques”. The harmonics of the complex tones were chosen so that the spectral melody had an inverse contour when compared with the virtual one. Evoked magnetic fields were recorded contralaterally to the ear of stimulation from both hemispheres. After a base line measurement, the subjects were exposed repeatedly to the experimental stimuli for 1 hour a day. All subjects reported a sudden change in the perceived melody, indicating possible reorganization of the cortical processes involved in the virtual pitch formation. After this switch in perception, a second measurement was performed. Cortical sources of the evoked gamma-band activity were significantly stronger and located more medially after a switch in perception. Independent Component Analysis revealed enhanced synchronization in the gamma-band frequency range. Comparing the gamma-band activation of both hemispheres, no laterality effects were observed. The results indicate that the primary auditory cortices are involved in the process of virtual pitch perception and that their function is modifiable by laboratory manipulation.

Neural Biomarkers for Dyslexia, ADHD, and ADD in the Auditory Cortex of Children

Dyslexia, attention deficit hyperactivity disorder (ADHD), and attention deficit disorder (ADD) show distinct clinical profiles that may include auditory and language-related impairments. Currently, an objective brain-based diagnosis of these developmental disorders is still unavailable. We investigated the neuro-auditory systems of dyslexic, ADHD, ADD, and age-matched control children (N = 147) using neuroimaging, magnetencephalography and psychoacoustics. All disorder subgroups exhibited an oversized left planum temporale and an abnormal interhemispheric asynchrony (10–40 ms) of the primary auditory evoked P1-response. Considering right auditory cortex morphology, bilateral P1 source waveform shapes, and auditory performance, the three disorder subgroups could be reliably differentiated with outstanding accuracies of 89–98%. We therefore for the first time provide differential biomarkers for a brain-based diagnosis of dyslexia, ADHD, and ADD. The method allowed not only allowed for clear discrimination between two subtypes of attentional disorders (ADHD and ADD), a topic controversially discussed for decades in the scientific community, but also revealed the potential for objectively identifying comorbid cases. Noteworthy, in children playing a musical instrument, after three and a half years of training the observed interhemispheric asynchronies were reduced by about 2/3, thus suggesting a strong beneficial influence of music experience on brain development. These findings might have far-reaching implications for both research and practice and enable a profound understanding of the brain-related etiology, diagnosis, and musically based therapy of common auditory-related developmental disorders and learning disabilities.

The effect of cross-channel synchrony on the perception of temporal regularity

Temporal models of pitch are based on the assumption that the auditory system measures the time intervals between neural events, and that pitch corresponds to the most common time interval. The current experiments were designed to test whether time intervals are analyzed independently in each peripheral channel, or whether the time-interval analysis in one channel is affected by synchronous activity in other channels. Regular and irregular click trains were filtered into narrow frequency bands to produce target and flanker stimuli. The threshold for discriminating a regular target from an irregular distracter click train was measured in the presence of an irregular masker click train in the target band, as a function of the frequency separation between the target band and a flanker band. The flanker click train was either regular or irregular. The threshold for detecting the regular target was 5-7 dB lower when the flanker was regular. The data indicate that the detection of temporal regularity (and thus, pitch) involves cross-channel processes that can operate over widely separated channels. Model simulations suggest that these cross-channel processes occur after the time-interval extraction stage and that they depend on the similarity, or consistency, of the time-interval patterns in the relevant channels.