Multimodal neural interfaces for augmenting human cognition

Research output: Contribution to journalArticle

Abstract

Within the next decade multimodal neural interfaces (MNI’s) could begin to transform society by expanding human cognitive abilities. Embodiments of such interfaces will include a combination of biometric and environmental sensors working in cooperation with noninvasive brain stimulation or neuromodulation devices to optimize human cognitive processes. These MNI’s may, for example, monitor psychophysiological arousal using pupillometry and responsively stimulate noradrenergic activity in a manner to enhance sustained attention or vigilance. Other near-term applications may include MNI’s that are designed to enable an individual to maintain a particular state of calm or flow state during stressful tasks by using algorithms to generate auricular vagal nerve stimulation waveforms based on real-time heart rate variability and electroencephalography data. Numerous other possibilities remain. The present paper provides a brief overview of several different types of biometric sensors and the neurophysiological systems they can monitor. This information is provided in context of their present limitations, as well as how neurophysiological sensors may be used in combination with noninvasive brain stimulation (NIBS) methods to augment human cognition and performance. Overall the paper attempts to provide a balanced and realistic examination of the issues remaining to be solved or addressed in order to reliably enhance human cognition. Efforts that combine high quality sensors for monitoring neurophysiological signatures of attention and psychophysiological markers of arousal with scientificallygrounded neurostimulation approaches in an integrated MNI solution will be necessary to achieve reliable and reproducible cognitive augmentation facilitated by future MNI’s.

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Keywords

  • Augmented cognition
  • Brain machine interface
  • Human intelligence
  • Human performance
  • Neuromodulation

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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