Cortical Mu Rhythms During Action and Passive Music Listening

Brain systems supporting body movement are active during music listening in the absence of overt movement. This covert motor activity is not well understood, but some theories propose a role in auditory timing prediction facilitated by motor simulation. One question is how music-related covert motor activity relates to motor activity during overt movement. We address this question using scalp electroencephalogram by measuring mu rhythms-- cortical field phenomena associated with the somatomotor system that appear over sensorimotor cortex. Lateralized mu enhancement over hand sensorimotor cortex during/just before foot movement in foot vs. hand movement paradigms is thought to reflect hand movement inhibition during current/prospective movement of another effector. Behavior of mu during music listening with movement suppressed has yet to be determined. We recorded 32-channel EEG (N=17) during silence without movement, overt movement (foot/hand), and music listening without movement. Using an Independent Component Analysis-based source equivalent dipole clustering technique, we identified three mu-related clusters, localized to left primary motor and right and midline premotor cortices. Right foot tapping was accompanied by mu enhancement in the left lateral source cluster, replicating previous work. Music listening was accompanied by similar mu enhancement in the left, as well as midline, clusters. We are the first to report, and also to source-resolve, music-related mu modulation in the absence of overt movements. Covert music-related motor activity has been shown to play a role in beat perception (1). Our current results show enhancement in somatotopically organized mu, supporting overt motor inhibition during beat perception.

Physiological Activity and Artefacts in Epileptic Brain in Subdural EEG

‘Physiological activity and artefacts in epileptic brain in subdural EEG’ reviews intracranial appearances of physiological brain rhythms in each brain region, many of which are also seen on scalp EEG. The alpha rhythm has been described as originating from multiple occipital and extra-occipital cortical generators variously overlapping and influencing each other, probably under the relative control of a central pacemaker. Another more focal pattern has been described in intracranial EEG recordings in the calcarine region, with a third rhythm arising in midtemporal regions, not detectable in scalp EEG, with a frequency in the alpha or theta range. Lambda waves, sleep structures, and mu rhythms over motor cortex can also be detected on subdural electrodes. On a region-by-region basis, intracranial EEG appearances are summarized, including brain oscillations in hippocampus and motor cortex and their modifiers, as well as ongoing rhythms in cingulum. Common sources of physiological and non-physiological artefacts are reviewed.

Neurofeedback training produces normalization in behavioural and electrophysiological measures of high-functioning autism

Autism spectrum disorder (ASD) is a neurodevelopmental condition exhibiting impairments in behaviour, social and communication skills. These deficits may arise from aberrant functional connections that impact synchronization and effective neural communication. Neurofeedback training (NFT), based on operant conditioning of the electroencephalogram (EEG), has shown promise in addressing abnormalities in functional and structural connectivity. We tested the efficacy of NFT in reducing symptoms in children with ASD by targeting training to the mirror neuron system (MNS) via modulation of EEG mu rhythms. The human MNS has provided a neurobiological substrate for understanding concepts in social cognition relevant to behavioural and cognitive deficits observed in ASD. Furthermore, mu rhythms resemble MNS phenomenology supporting the argument that they are linked to perception and action. Thirty hours of NFT on ASD and typically developing (TD) children were assessed. Both groups completed an eyes-open/-closed EEG session as well as a mu suppression index assessment before and after training. Parents filled out pre- and post-behavioural questionnaires. The results showed improvements in ASD subjects but not in TDs. This suggests that induction of neuroplastic changes via NFT can normalize dysfunctional mirroring networks in children with autism, but the benefits are different for TD brains.