title: Listening to rhythms activates motor and premotor cortices.
abstract: We used functional magnetic resonance imaging (fMRI) to identify brain areas involved in auditory rhythm perception. Participants listened to three rhythm sequences that varied in temporal predictability. The most predictable sequence was an isochronous rhythm sequence of a single interval (ISO). The other two sequences had nine intervals with unequal durations. One of these had interval durations of integer ratios relative to the shortest interval (METRIC). The other had interval durations of non-integer ratios relative to the shortest interval (NON-METRIC), and was thus perceptually more complex than the other two. In addition, we presented unpredictable sequences with randomly distributed intervals (RAN). We tested two hypotheses. Firstly, that areas involved in motor timing control would also process the temporal predictability of sensory cues. Therefore, there was no active task included in the experiment that could influence the participant perception or induce motor preparation. We found that dorsal premotor cortex (PMD), SMA, preSMA, and lateral cerebellum were more active when participants listen to rhythm sequences compared to random sequences. The activity pattern in supplementary motor area (SMA) and preSMA suggested a modulation dependent on sequence predictability, strongly suggesting a role in temporal sensory prediction. Secondly, we hypothesized that the more complex the rhythm sequence, the more it would engage short-term memory processes of the prefrontal cortex. We found that the superior prefrontal cortex was more active when listening to METRIC and NON-METRIC compared to ISO. We argue that the complexity of rhythm sequences is an important factor in modulating activity in many of the rhythm areas. However, the difference in complexity of our stimuli should be regarded as continuous.
authors.affiliation: Wellcome Trust Centre for Neuroimaging, Institute of Neurology, University College London, London, UK. s.bengtsson@fil.ion.ucl.ac.uk
authors.forename: Sara L
authors.initials: SL
authors.lastname: Bengtsson
authors.forename: Fredrik
authors.initials: F
authors.lastname: Ullén
authors.forename: H Henrik
authors.initials: HH
authors.lastname: Ehrsson
authors.forename: Toshihiro
authors.initials: T
authors.lastname: Hashimoto
authors.forename: Tomonori
authors.initials: T
authors.lastname: Kito
authors.forename: Eiichi
authors.initials: E
authors.lastname: Naito
authors.forename: Hans
authors.initials: H
authors.lastname: Forssberg
authors.forename: Norihiro
authors.initials: N
authors.lastname: Sadato
mesh_terms: D000161:Acoustic Stimulation; D000328:Adult; D001307:Auditory Perception / Q000502:physiology; D003627:Data Interpretation, Statistical; D004576:Electromyography; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008279:Magnetic Resonance Imaging; D008297:Male; D009044:Motor Cortex / Q000502:physiology*; D018482:Muscle, Skeletal / Q000502:physiology; D009146:Music / Q000523:psychology*; D017397:Prefrontal Cortex / Q000502:physiology*; D055815:Young Adult