Distributed feedforward and feedback cortical processing supports human speech production
Proceedings of the National Academy of Sciences of the United States of America, ISSN: 1091-6490, Vol: 120, Issue: 42, Page: e2300255120
2023
- 7Citations
- 8Captures
- 11Mentions
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Metrics Details
- Citations7
- Citation Indexes7
- Captures8
- Readers8
- Mentions11
- News Mentions11
- News11
Most Recent News
Single-neuronal elements of speech production in humans
Nature, Published online: 31 January 2024; doi:10.1038/s41586-023-06982-w Neuropixels recordings from the language-dominant prefrontal cortex reveal a structured organization of planned words, an encoding cascade of phonetic representations by prefrontal neurons in humans and a cellular process that could support the production of speech.
Article Description
Speech production is a complex human function requiring continuous feedforward commands together with reafferent feedback processing. These processes are carried out by distinct frontal and temporal cortical networks, but the degree and timing of their recruitment and dynamics remain poorly understood. We present a deep learning architecture that translates neural signals recorded directly from the cortex to an interpretable representational space that can reconstruct speech. We leverage learned decoding networks to disentangle feedforward vs. feedback processing. Unlike prevailing models, we find a mixed cortical architecture in which frontal and temporal networks each process both feedforward and feedback information in tandem. We elucidate the timing of feedforward and feedback–related processing by quantifying the derived receptive fields. Our approach provides evidence for a surprisingly mixed cortical architecture of speech circuitry together with decoding advances that have important implications for neural prosthetics.
Bibliographic Details
Proceedings of the National Academy of Sciences
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