The Neural Mechanism of Speech Communication in Marmosets (NSR)

In a recent article published in the National Science Review (National Science Review, NSR), researchers reported that specific neuronal populations in the primary auditory cortex of non-human primate marmosets, which selectively respond to different marmosets Simple or compound calling sounds of the same kind made by monkeys, and show sensitivity to the sequence and sequence interval of the calling sounds
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This study shows that in awake non-human primates, there is a wide range of inhibition and promotion between the responses evoked by the call sound, which provides a basis for further research on the neural circuit mechanism of voice communication
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The neural basis of human language is a major puzzle in the field of neuroscience
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Marmosets, non-human primates, have rich voice communication behaviors, and are considered to be an excellent animal model for studying the neural mechanisms of complex voice communication
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Previous functional imaging and electrophysiological studies of the primate auditory system have shown that neurons in the anterior temporal region show a higher preference for complex sounds, while in the posterior temporal region, such as the primary auditory cortex (A1), neurons are It is famous for its tonal sensitivity
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In addition to frequency preference, A1 neurons are also sensitive to specific frequency-time domain characteristics of sound such as harmony, frequency domain and time domain modulation
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An electrophysiological study of anesthetized marmosets found that A1 neurons selectively respond to simple Twitter calls
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However, it is not clear whether A1 neurons can selectively respond to a wide range of natural calling sounds, including simple calling sounds and compound calling sounds (consisting of two simple calling sounds)
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An equally important and unknown question is whether the call-evoked response is only due to the sensitivity of neurons to specific local frequency-time-domain features of the sound, or whether the overall perception of various sound components is required
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Recently, in a study jointly conducted by Pu Muming's research group and Wang Liping's research group of the Center for Excellence in Brain Science and Intelligent Technology of the Chinese Academy of Sciences (Institute of Neuroscience), researchers achieved two-photon functional imaging of neurons in the A1 population of awake marmoset monkeys
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Using this method, the researchers found that a large number of neurons in A1 selectively responded to different simple and compound calling sounds of the same kind, but did not respond to pure tones
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Further research on compound call sound selective neurons shows that their response is very sensitive to the sequence and interval of simple call sound components
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The selective response of these compound calling sounds is only for naturally occurring compound calling sounds rather than artificially constructed compound calling sounds, and they are completely eliminated by mild anesthesia
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These findings confirm the existence of a large number of call-sound-selective neuron groups in A1 of awake marmosets, indicating that the early sound processing of the auditory system is more complicated than imagined
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The study reported for the first time in the world that there is a population of neurons that are selective for marmoset calling sounds in the primary auditory cortex of awake marmosets.
It was found that these neurons are highly sensitive to the sequence and interval of the calling sound components, and it also revealed the calling sound.
There are extensive inhibition and promotion effects among the evoked responses, which provide an important basis for further research on the neural circuit mechanism of voice communication
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The above results were published in National Science Review under the title of "Distinct neuron populations for simple and compound calls in the primary auditory cortex of awake marmosets", Researcher Pu Muming and Researcher Wang Liping, Center for Excellence in Innovation in Brain Science and Intelligent Technology (Institute of Neuroscience), Chinese Academy of Sciences As the co-corresponding author, Zeng Huanhuan, a postdoctoral fellow at the Center for Excellence in Brain Science and Intelligent Technology of the Chinese Academy of Sciences, is the first author
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The research was funded by the Chinese Academy of Sciences and the Shanghai Science and Technology Commission
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Link to the paper: https://doi.
org/10.
1093/nsr/nwab126