Abstract
Certain brain disorders resulting from brainstem infarcts, traumatic brain injury, cerebral palsy, stroke, and amyotrophic lateral sclerosis, limit verbal communication despite the patient being fully aware. People that cannot communicate due to neurological disorders would benefit from a system that can infer internal speech directly from brain signals. In this review article, we describe the state of the art in decoding inner speech, ranging from early acoustic sound features, to higher order speech units. We focused on intracranial recordings, as this technique allows monitoring brain activity with high spatial, temporal, and spectral resolution, and therefore is a good candidate to investigate inner speech. Despite intense efforts, investigating how the human cortex encodes inner speech remains an elusive challenge, due to the lack of behavioral and observable measures. We emphasize various challenges commonly encountered when investigating inner speech decoding, and propose potential solutions in order to get closer to a natural speech assistive device.
Highlights
Neural engineering research has made tremendous advances in decoding motor (Ajiboye et al, 2017) or visual neural signals (Lewis et al, 2015) for assisting and restoring lost functions in patients with disabling neurological conditions
We focused on studies that have used electrocorticographic (ECoG) recordings in the human cortex, as this promising technique allows monitoring brain activity with high spatial, temporal, and spectral resolution, as compared to electroencephalographic recordings, and the electrodes cover broader brain areas compared to intracortical recordings (Ritaccio et al, 2015)
We described the potential of using decoding models to unravel neural mechanisms associated with complex speech functions
Summary
Neural engineering research has made tremendous advances in decoding motor (Ajiboye et al, 2017) or visual neural signals (Lewis et al, 2015) for assisting and restoring lost functions in patients with disabling neurological conditions. Only in rare cases, patients are implanted with such electrodes, and it remains exclusively for clinical purposes; the implantation time provides a unique opportunity to investigate human brain functions, with high spatial (millimeters), temporal (milliseconds), and spectral resolution (0–500 Hz) It covers broad brain areas (typically frontal, temporal, and parietal cortex), which is beneficial given the complex and widely distributed network associated with speech. Brain activity evoked by different stimuli are averaged and compared in order to provide new insights about the neural mechanisms under study Decoding these cognitive functions in real-time for targeting brain-machine interfaces requires more sophisticated predictive modeling. In a linear regression model, the output is a weighted sum of input features
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
