Decoding covert somatosensory attention by a BCI system calibrated with tactile sensation

© 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.Objective: We propose a novel calibration strategy to facilitate the decoding of covert somatosensory attention by exploring the oscillatory dynamics induced by tactile sensation. Methods: It was hypothesized that the similarity of the oscillatory pattern between stimulation sensation (SS, real sensation) and somatosensory attentional orientation (SAO) provides a way to decode covert somatic attention. Subjects were instructed to sense the tactile stimulation, which was applied to the left (SS-L) or the right (SS-R) wrist. The BCI system was calibrated with the sensation data and then applied for online SAO decoding. Results: Both SS and SAO showed oscillatory activation concentrated on the contralateral somatosensory hemisphere. Offline analysis showed that the proposed calibration method led to greater accuracy than the traditional calibration method based on SAO only. This is confirmed by online experiments, where the online accuracy on 15 subjects was 78.8±13.1%, with 12 subjects >70% and 4 subject >90%. Conclusion: By integrating the stimulus-induced oscillatory dynamics from sensory cortex, covert somatosensory attention can be reliably decoded by a BCI system calibrated with tactile sensation. Significance: Indeed, real tactile sensation is more consistent during calibration than SAO. This brain-computer interfacing approach may find application for stroke and completely locked-in patients with preserved somatic sensation.University Starter Grant of the University of Waterloo (No. 203859) National Natural Science Foundation of China (Grant No. 51620105002

Metacognitive awareness of covert somatosensory attention corresponds to contralateral alpha power

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Dynamic Oscillatory Interactions Between Neural Attention and Sensorimotor Systems

The adaptive and flexible ability of the human brain to preference the processing of salient environmental features in the visual space is essential to normative cognitive function, and various neurologically afflicted patient groups report negative impacts on visual attention. While the brain-bases of human attentional processing have begun to be unraveled, very little is known regarding the interactions between attention systems and systems supporting sensory and motor processing. This is essential, as these interactions are dynamic; evolving rapidly in time and across a wide range of functionally defined rhythmic frequencies. Using magnetoencephalography (MEG) and a range of novel cognitive paradigms and analytical techniques, this work attempts to fill critical gaps in this knowledge. Specifically, we unravel the role of dynamic oscillatory interactions between attention and three sensorimotor systems. First, we establish the importance of sub-second occipital alpha (8 – 14 Hz) oscillatory responses in visual distractor suppression during selective attention (Chapter 1) and their essential role in fronto-parietal attention networks during visual orienting (Chapter 2). Next, we examine the divergent effects of directed attention on multi-frequency primary somatosensory neural oscillations in the theta (4 – 8 Hz), alpha, and beta (18 – 26 Hz) bands (Chapter 3). Finally, we extend these findings to the motor system (Chapter 4), and find that the frontal and parietal beta-frequency oscillations known to support motor planning and execution are modulated equivalently by differing subtypes of attentional interference, whereas frontal gamma (64 – 84 Hz) oscillations specifically index the superadditive effect of this interference. These findings provide new insight into the dynamic nature of attention-sensorimotor interactions in the human brain, and will be the foundation for groundbreaking new studies of attentional deficits in patients with common neurological disorders (e.g., Alzheimer’s disease, HIV-associated neurocognitive disorders, Parkinson’s disease). With an enhanced knowledge of the temporal and spectral definitions of these impairments, new therapeutic interventions utilizing frequency-targeted neural stimulation can be developed