Dataset Information

Nanofabricated Ultraflexible Electrode Arrays for High-Density Intracortical Recording.

ABSTRACT: Understanding brain functions at the circuit level requires time-resolved simultaneous measurement of a large number of densely distributed neurons, which remains a great challenge for current neural technologies. In particular, penetrating neural electrodes allow for recording from individual neurons at high temporal resolution, but often have larger dimensions than the biological matrix, which induces significant damage to brain tissues and therefore precludes the high implant density that is necessary for mapping large neuronal populations with full coverage. Here, it is demonstrated that nanofabricated ultraflexible electrode arrays with cross-sectional areas as small as sub-10 µm2 can overcome this physical limitation. In a mouse model, it is shown that these electrodes record action potentials with high signal-to-noise ratio; their dense arrays allow spatial oversampling; and their multiprobe implantation allows for interprobe spacing at 60 µm without eliciting chronic neuronal degeneration. These results present the possibility of minimizing tissue displacement by implanted ultraflexible electrodes for scalable, high-density electrophysiological recording that is capable of complete neuronal circuitry mapping over chronic time scales.

SUBMITTER: Wei X

PROVIDER: S-EPMC6010728 | biostudies-literature | 2018 Jun

REPOSITORIES: biostudies-literature

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Nanofabricated Ultraflexible Electrode Arrays for High-Density Intracortical Recording.

Wei Xiaoling X Luan Lan L Zhao Zhengtuo Z Li Xue X Zhu Hanlin H Potnis Ojas O Xie Chong C

Advanced science (Weinheim, Baden-Wurttemberg, Germany) 20180310 6

Understanding brain functions at the circuit level requires time-resolved simultaneous measurement of a large number of densely distributed neurons, which remains a great challenge for current neural technologies. In particular, penetrating neural electrodes allow for recording from individual neurons at high temporal resolution, but often have larger dimensions than the biological matrix, which induces significant damage to brain tissues and therefore precludes the high implant density that is ...[more]

PMID: 29938162

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Project description:ObjectiveTo evaluate the potential of intracortical electrode array signals for brain-computer interfaces (BCIs) to restore lost speech, we measured the performance of decoders trained to discriminate a comprehensive basis set of 39 English phonemes and to synthesize speech sounds via a neural pattern matching method. We decoded neural correlates of spoken-out-loud words in the 'hand knob' area of precentral gyrus, a step toward the eventual goal of decoding attempted speech from ventral speech areas in patients who are unable to speak.ApproachNeural and audio data were recorded while two BrainGate2 pilot clinical trial participants, each with two chronically-implanted 96-electrode arrays, spoke 420 different words that broadly sampled English phonemes. Phoneme onsets were identified from audio recordings, and their identities were then classified from neural features consisting of each electrode's binned action potential counts or high-frequency local field potential power. Speech synthesis was performed using the 'Brain-to-Speech' pattern matching method. We also examined two potential confounds specific to decoding overt speech: acoustic contamination of neural signals and systematic differences in labeling different phonemes' onset times.Main resultsA linear decoder achieved up to 29.3% classification accuracy (chance = 6%) across 39 phonemes, while an RNN classifier achieved 33.9% accuracy. Parameter sweeps indicated that performance did not saturate when adding more electrodes or more training data, and that accuracy improved when utilizing time-varying structure in the data. Microphonic contamination and phoneme onset differences modestly increased decoding accuracy, but could be mitigated by acoustic artifact subtraction and using a neural speech onset marker, respectively. Speech synthesis achieved r = 0.523 correlation between true and reconstructed audio.SignificanceThe ability to decode speech using intracortical electrode array signals from a nontraditional speech area suggests that placing electrode arrays in ventral speech areas is a promising direction for speech BCIs.

Dataset Information

Nanofabricated Ultraflexible Electrode Arrays for High-Density Intracortical Recording.

Publications

Nanofabricated Ultraflexible Electrode Arrays for High-Density Intracortical Recording.

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