Moving in synchrony with an auditory rhythm requires predictive action based on neurodynamic representation of temporal information. Although it is known that a regular auditory rhythm can facilitate rhythmic movement, the neural mechanisms underlying this phenomenon remain poorly understood. In this experiment using human magnetoencephalography, 12 young healthy adults listened passively to an isochronous auditory rhythm without producing rhythmic movement. We hypothesized that the dynamics of neuromagnetic beta-band oscillations (ϳ20 Hz)-which are known to reflect changes in an active status of sensorimotor functions-would show modulations in both power and phase-coherence related to the rate of the auditory rhythm across both auditory and motor systems. Despite the absence of an intention to move, modulation of beta amplitude as well as changes in cortico-cortical coherence followed the tempo of sound stimulation in auditory cortices and motor-related areas including the sensorimotor cortex, inferior-frontal gyrus, supplementary motor area, and the cerebellum. The time course of beta decrease after stimulus onset was consistent regardless of the rate or regularity of the stimulus, but the time course of the following beta rebound depended on the stimulus rate only in the regular stimulus conditions such that the beta amplitude reached its maximum just before the occurrence of the next sound. Our results suggest that the time course of beta modulation provides a mechanism for maintaining predictive timing, that beta oscillations reflect functional coordination between auditory and motor systems, and that coherence in beta oscillations dynamically configure the sensorimotor networks for auditory-motor coupling.

Acoustic stimuli are processed throughout the auditory projection pathway, including the neocortex, by neurons that are aggregated into 'tonotopic' maps according to their specific frequency tunings. Research on animals has shown that tonotopic representations are not statically fixed in the adult organism but can reorganize after damage to the cochlea or after training the intact subject to discriminate between auditory stimuli. Here we used functional magnetic source imaging (single dipole model) to measure cortical representations in highly skilled musicians. Dipole moments for piano tones, but not for pure tones of similar fundamental frequency (matched in loudness), were found to be enlarged by about 25% in musicians compared with control subjects who had never played an instrument. Enlargement was correlated with the age at which musicians began to practise and did not differ between musicians with absolute or relative pitch. These results, when interpreted with evidence for modified somatosensory representations of the fingering digits in skilled violinists, suggest that use-dependent functional reorganization extends across the sensory cortices to reflect the pattern of sensory input processed by the subject during development of musical skill.

Neural imaging studies have shown that the brains of skilled musicians respond differently to musical stimuli than do the brains of non-musicians, particularly for musicians who commenced practice at an early age. Whether brain attributes related to musical skill are attributable to musical practice or are hereditary traits that influence the decision to train musically is a subject of controversy, owing to its pedagogic implications. Here we report that auditory cortical representations measured neuromagnetically for tones of different timbre (violin and trumpet) are enhanced compared to sine tones in violinists and trumpeters, preferentially for timbres of the instrument of training. Timbre specificity is predicted by a principle of use-dependent plasticity and imposes new requirements on nativistic accounts of brain attributes associated with musical skill.

Abstract& In music, melodic information is thought to be encoded in two forms, a contour code (up/down pattern of pitch changes) and an interval code (pitch distances between successive notes). A recent study recording the mismatch negativity (MMN) evoked by pitch contour and interval deviations in simple melodies demonstrated that people with no formal music education process both contour and interval information in the auditory cortex automatically. However, it is still unclear whether musical experience enhances both strategies of melodic encoding. We designed stimuli to examine contour and interval information separately. In the contour condition there were eight different standard melodies (presented on 80% of trials), each consisting of five notes all ascending in pitch, and the corresponding deviant melodies (20%) were altered to descending on their final note. The interval condition used one five-note standard melody transposed to eight keys from trial to trial, and on deviant trials the last note was raised by one whole tone without changing the pitch contour. There was also a control condition, in which a standard tone (990.7 Hz) and a deviant tone (1111.0 Hz) were presented. The magnetic counterpart of the MMN (MMNm) from musicians and nonmusicians was obtained as the difference between the dipole moment in response to the standard and deviant trials recorded by magnetoencephalography. Significantly larger MMNm was present in musicians in both contour and interval conditions than in nonmusicians, whereas MMNm in the control condition was similar for both groups. The interval MMNm was larger than the contour MMNm in musicians. No hemispheric difference was found in either group. The results suggest that musical training enhances the ability to automatically register abstract changes in the relative pitch structure of melodies. &

Dancing to music involves synchronized movements, which can be at the basic beat level or higher hierarchical metrical levels, as in a march (groups of two basic beats, one-two-one-two . . .) or waltz (groups of three basic beats, one-two-three-one-two-three . . .). Our previous human magnetoencephalography studies revealed that the subjective sense of meter influences auditory evoked responses phase locked to the stimulus. Moreover, the timing of metronome clicks was represented in periodic modulation of induced (non-phase locked) ␤-band (13-30 Hz) oscillation in bilateral auditory and sensorimotor cortices. Here, we further examine whether acoustically accented and subjectively imagined metric processing in march and waltz contexts during listening to isochronous beats were reflected in neuromagnetic ␤-band activity recorded from young adult musicians. First, we replicated previous findings of beat-related ␤-power decrease at 200 ms after the beat followed by a predictive increase toward the onset of the next beat. Second, we showed that the ␤ decrease was significantly influenced by the metrical structure, as reflected by differences across beat type for both perception and imagery conditions. Specifically, the ␤-power decrease associated with imagined downbeats (the count "one") was larger than that for both the upbeat (preceding the count "one") in the march, and for the middle beat in the waltz. Moreover, beamformer source analysis for the whole brain volume revealed that the metric contrasts involved auditory and sensorimotor cortices; frontal, parietal, and inferior temporal lobes; and cerebellum. We suggest that the observed ␤-band activities reflect a translation of timing information to auditory-motor coordination.

We examined beta- (approximately 20 Hz) and gamma- (approximately 40 Hz) band activity in auditory cortices by means of magnetoencephalography (MEG) during passive listening to a regular musical beat with occasional omission of single tones. The beta activity decreased after each tone, followed by an increase, thus forming a periodic modulation synchronized with the stimulus. The beta decrease was absent after omissions. In contrast, gamma-band activity showed a peak after tone and omission, suggesting underlying endogenous anticipatory processes. We propose that auditory beta and gamma oscillations have different roles in musical beat encoding and auditory-motor interaction.

Older adults often have difficulty understanding speech in a noisy environment or with multiple speakers. In such situations, binaural hearing improves the signal-to-noise ratio. How does this binaural advantage change with increasing age? Using magnetoencephalography, we recorded cortical activity evoked by changes in interaural phase differences of amplitude-modulated tones. These responses occurred for frequencies up to 1225 Hz in young subjects but only up to 940 Hz in middle-aged and 760 Hz in older adults. Behavioral thresholds also decreased with increasing age but were more variable, likely because some older adults make effective use of compensatory mechanisms. The reduced frequency range for binaural hearing became significant in middle age, before decline in hearing sensation and the morphology of cortical responses, which became apparent only in the older subjects. This study provides evidence from human physiological data for the early onset of biological aging in binaural hearing.

Hemispheric asymmetries during auditory sensory processing were examined using whole-head magnetoencephalographic recordings of auditory evoked responses to monaurally and binaurally presented amplitude-modulated sounds. Laterality indices were calculated for the transient onset responses (P1m and N1m), the transient gamma-band response, the sustained field (SF) and the 40 Hz auditory steady-state response (ASSR). All response components showed laterality toward the hemisphere contralateral to the stimulated ear. In addition, the SF and ASSR showed right hemispheric (RH) dominance. Thus, laterality of sustained response components (SF and ASSR) was distinct from that of transient responses. ASSR and SF are sensitive to stimulus periodicity. Consequently, ASSR and SF likely reflect periodic stimulus attributes and might be relevant for pitch processing based on temporal stimulus regularities. In summary, the results of the present studies demonstrate that asymmetric organization in the cerebral auditory cortex is already established on the level of sensory processing.