Reaching movement onset- and end-related characteristics of EEG spectral power modulations.

The spectral power of intracranial field potentials shows movement-related modulations during reaching movements to different target positions that in frequencies up to the high-γ range (approximately 50 to above 200 Hz) can be reliably used for single-trial inference of movement parameters. However, identifying spectral power modulations suitable for single-trial analysis for non-invasive approaches remains a challenge. We recorded non-invasive electroencephalography (EEG) during a self-paced center-out and center-in arm movement task, resulting in eight reaching movement classes (four center-out, four center-in). We found distinct slow (≤5 Hz), µ (7.5-10 Hz), ß (12.5-25 Hz), low-γ (approximately 27.5-50 Hz), and high-γ (above 50 Hz) movement onset- and end-related responses. Movement class-specific spectral power modulations were restricted to the ß band at approximately 1 s after movement end and could be explained by the sensitivity of this response to different static, post-movement electromyography (EMG) levels. Based on the ß band, significant single-trial inference of reaching movement endpoints was possible. The findings of the present study support the idea that single-trial decoding of different reaching movements from non-invasive EEG spectral power modulations is possible, but also suggest that the informative time window is after movement end and that the informative frequency range is restricted to the ß band.

Movement related activity in the high gamma range of the human EEG.

Electrocorticographic (ECoG) recordings obtained using intracranially implanted electrodes in epilepsy patients indicate that high gamma band (HGB) activity of sensorimotor cortex is focally increased during voluntary movement. These movement related HGB modulations may play an important role in sensorimotor cortex function. It is however currently not clear to what extent this type of neural activity can be detected using non-invasive electroencephalography (EEG) and how similar HGB responses in healthy human subjects are to those observed in epilepsy patients. Using the same arm reaching task, we have investigated spectral power changes both in intracranial ECoG recordings in epilepsy patients and in non-invasive EEG recordings optimized for detecting HGB activity in healthy subjects. Our results show a common HGB response pattern both in ECoG and EEG recorded above the sensorimotor cortex contralateral to the side of arm movement. In both cases, HGB activity increased around movement onset in the 60-90 Hz range and became most pronounced at reaching movement end. Additionally, we found EEG HGB activity above the frontal midline possibly generated by the anterior supplementary motor area (SMA), a region that was however not covered by the intracranial electrodes used in the present study. In summary, our findings show that HGB activity from human sensorimotor cortex can be non-invasively detected in healthy subjects using EEG, opening a new perspective for investigating the role of high gamma range neuronal activity both in function and dysfunction of the human cortical sensorimotor network.

Hand movement direction decoded from MEG and EEG.

Brain activity can be used as a control signal for brain-machine interfaces (BMIs). A powerful and widely acknowledged BMI approach, so far only applied in invasive recording techniques, uses neuronal signals related to limb movements for equivalent, multidimensional control of an external effector. Here, we investigated whether this approach is also applicable for noninvasive recording techniques. To this end, we recorded whole-head MEG during center-out movements with the hand and found significant power modulation of MEG activity between rest and movement in three frequency bands: an increase for < or = 7 Hz (low-frequency band) and 62-87 Hz (high-gamma band) and a decrease for 10-30 Hz (beta band) during movement. Movement directions could be inferred on a single-trial basis from the low-pass filtered MEG activity as well as from power modulations in the low-frequency band, but not from the beta and high-gamma bands. Using sensors above the motor area, we obtained a surprisingly high decoding accuracy of 67% on average across subjects. Decoding accuracy started to rise significantly above chance level before movement onset. Based on simultaneous MEG and EEG recordings, we show that the inference of movement direction works equally well for both recording techniques. In summary, our results show that neuronal activity associated with different movements of the same effector can be distinguished by means of noninvasive recordings and might, thus, be used to drive a noninvasive BMI.

A rapid sound-action association effect in human insular cortex.

BACKGROUND: Learning to play a musical piece is a prime example of complex sensorimotor learning in humans. Recent studies using electroencephalography (EEG) and transcranial magnetic stimulation (TMS) indicate that passive listening to melodies previously rehearsed by subjects on a musical instrument evokes differential brain activation as compared with unrehearsed melodies. These changes were already evident after 20-30 minutes of training. The exact brain regions involved in these differential brain responses have not yet been delineated. METHODOLOGY/PRINCIPAL FINDING: Using functional mri (fmri), we investigated subjects who passively listened to simple piano melodies from two conditions: in the 'actively learned melodies' condition subjects learned to play a piece on the piano during a short training session of a maximum of 30 minutes before the fMRI experiment, and in the 'passively learned melodies' condition subjects listened passively to and were thus familiarized with the piece. We found increased fMRI responses to actively compared with passively learned melodies in the left anterior insula, extending to the left fronto-opercular cortex. The area of significant activation overlapped the insular sensorimotor hand area as determined by our meta-analysis of previous functional imaging studies. CONCLUSIONS/SIGNIFICANCE: Our results provide evidence for differential brain responses to action-related sounds after short periods of learning in the human insular cortex. As the hand sensorimotor area of the insular cortex appears to be involved in these responses, re-activation of movement representations stored in the insular sensorimotor cortex may have contributed to the observed effect. The insular cortex may therefore play a role in the initial learning phase of action-perception associations.