Power changes in specific frequency bands are typical brain responses during motor planning or preparation. Many studies have demonstrated that, in addition to the premotor, supplementary motor, and primary sensorimotor areas, the prefrontal area contributes to generating such responses. However, most brain-computer interface (BCI) studies have focused on the primary sensorimotor area and have estimated movements using postonset period brain signals. Our aim was to determine whether the prefrontal area could contribute to the prediction of voluntary movement types before movement onset. In our study, electrocorticography (ECoG) was recorded from six epilepsy patients while performing two self-paced tasks: hand grasping and elbow flexion. The prefrontal area was sufficient to allow classification of different movements through the area's premovement signals (−2.0 s to 0 s) in four subjects. The most pronounced power difference frequency band was the beta band (13–30 Hz). The movement prediction rate during single trial estimation averaged 74% across the six subjects. Our results suggest that premovement signals in the prefrontal area are useful in distinguishing different movement tasks and that the beta band is the most informative for prediction of movement type before movement onset.

Somatosensation plays pivotal roles in the everyday motor control of humans. During active movement, there exists a prominent high-gamma (HG >50 Hz) power increase in the primary somatosensory cortex (S1), and this provides an important feature in relation to the decoding of movement in a brain-machine interface (BMI). However, one concern of BMI researchers is the inflation of the decoding performance due to the activation of somatosensory feedback, which is not elicited in patients who have lost their sensorimotor function. In fact, it is unclear as to how much the HG component activated in S1 contributes to the overall sensorimotor HG power during voluntary movement. With regard to other functional roles of HG in S1, recent findings have reported that these HG power levels increase before the onset of actual movement, which implies neural activation for top-down movement preparation or sensorimotor interaction, i.e., an efference copy. These results are promising for BMI applications but remain inconclusive. Here, we found using electrocorticography (ECoG) from eight patients that HG activation in S1 is stronger and more informative than it is in the primary motor cortex (M1) regardless of the type of movement. We also demonstrate by means of electromyography (EMG) that the onset timing of the HG power in S1 is later (49 ms) than that of the actual movement. Interestingly, we show that the HG power fluctuations in S1 are closely related to subtle muscle contractions, even during the pre-movement period. These results suggest the following: (1) movement-related HG activity in S1 strongly affects the overall sensorimotor HG power, and (2) HG activity in S1 during voluntary movement mainly represents cortical neural processing for somatosensory feedback.

Humans can easily detect vibrotactile stimuli up to several hundred hertz, but underlying large-scale neuronal processing mechanisms in the cortex are largely unknown. Here, we investigated the macroscopic neural correlates of various vibrotactile stimuli including artificial and naturalistic ones in human primary and secondary somatosensory cortices (S1 and S2, respectively) using electrocorticography (ECoG). We found that tactile frequency-specific high-gamma (HG, 50–140 Hz) activities are seen in both S1 and S2 with different temporal dynamics during vibration (>100 Hz). Stimulus-evoked S1 HG power, which exhibited short-delayed peaks (50–100 ms), was attenuated more quickly in vibration than in flutter (<50 Hz), and their attenuation patterns were frequency-specific within vibration range. In contrast, S2 HG power, which was activated much later than that of S1 (150–250 ms), strikingly increased with increasing stimulus frequencies in vibration range, and their changes were much greater than those in S1. Furthermore, these S1-S2 HG patterns were preserved in naturalistic stimuli such as coarse/fine textures. Our results provide persuasive evidence that S2 is critically involved in neural processing for high-frequency vibrotaction. Therefore, we propose that S1-S2 neuronal co-operation is crucial for full-range, complex vibrotactile perception in human.

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