A speech planning network for interactive language use

Gregg A. Castellucci, Christopher K. Kovach, Matthew A. Howard, Jeremy D. W. Greenlee and Michael A. Long ()
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Gregg A. Castellucci: New York University Langone Medical Center
Christopher K. Kovach: University of Iowa
Matthew A. Howard: University of Iowa
Jeremy D. W. Greenlee: University of Iowa
Michael A. Long: New York University Langone Medical Center

Nature, 2022, vol. 602, issue 7895, 117-122

Abstract: Abstract During conversation, people take turns speaking by rapidly responding to their partners while simultaneously avoiding interruption1,2. Such interactions display a remarkable degree of coordination, as gaps between turns are typically about 200 milliseconds3—approximately the duration of an eyeblink4. These latencies are considerably shorter than those observed in simple word-production tasks, which indicates that speakers often plan their responses while listening to their partners2. Although a distributed network of brain regions has been implicated in speech planning5–9, the neural dynamics underlying the specific preparatory processes that enable rapid turn-taking are poorly understood. Here we use intracranial electrocorticography to precisely measure neural activity as participants perform interactive tasks, and we observe a functionally and anatomically distinct class of planning-related cortical dynamics. We localize these responses to a frontotemporal circuit centred on the language-critical caudal inferior frontal cortex10 (Broca’s region) and the caudal middle frontal gyrus—a region not normally implicated in speech planning11–13. Using a series of motor tasks, we then show that this planning network is more active when preparing speech as opposed to non-linguistic actions. Finally, we delineate planning-related circuitry during natural conversation that is nearly identical to the network mapped with our interactive tasks, and we find this circuit to be most active before participant speech during unconstrained turn-taking. Therefore, we have identified a speech planning network that is central to natural language generation during social interaction.

Date: 2022
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DOI: 10.1038/s41586-021-04270-z

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