Recent studies have shown that the feasibility of speech brain-computer interfaces (BCIs) as a clinically valid treatment in helping nontonal language patients with communication disorders restore their speech ability. However, tonal language speech BCI is challenging because additional precise control of laryngeal movements to produce lexical tones is required. Thus, the model should emphasize the features from the tonal-related cortex. Here, we designed a modularized multistream neural network that directly synthesizes tonal language speech from intracranial recordings. The network decoded lexical tones and base syllables independently via parallel streams of neural network modules inspired by neuroscience findings. The speech was synthesized by combining tonal syllable labels with nondiscriminant speech neural activity. Compared to commonly used baseline models, our proposed models achieved higher performance with modest training data and computational costs. These findings raise a potential strategy for approaching tonal language speech restoration.
BACKGROUND To be efficient, intraoperative task-presentation systems must accurately present various language and cognitive tasks to patients undergoing awake surgery, and record behavioral data without compromising convenience of surgery. OBJECTIVE To present an integrated brain mapping task-presentation system we developed and evaluate its effectiveness in intraoperative task presentation. METHODS The Brain Mapping Interactive Stimulation System (Brain MISS) is a flexible task presentation system that adjusts for patient comfort, needs of the surgeon, and operating team, with multivideo recording for patients’ behavior. A total of 48 patients from 3 centers underwent intraoperative language task test during awake brain surgery with the Brain MISS. Each patient was assigned 5 questions each on picture naming, reading, and listening comprehension before and during awake surgeries. The accuracy of intraoperative stimulus-response (without electrical stimulation) was recorded. The Brain MISS was to be considered effective, if the lower limit of 95% CI of patients’ intraoperative response was ≥80% and also if the accuracy of intraoperative response of all patients was statistically higher than 80%. RESULTS All patients successfully underwent intraoperative assessment with the Brain MISS. The overall accuracy of stimulus response was 95.8% (95% CI 90.18%-100.00%), with the lower limit being higher than 80% and the response accuracy also significantly being higher than 80% in all patients (P = .006). CONCLUSION The Brain MISS is a portable and effective system for presenting and streamlining complicated language and cognitive tasks during awake surgery. It can also record standardized patient response data for neuroscientific research.
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