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.

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).

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.

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.