Auditory decisions in the supplementary motor area. (July 2021)

• Record Type: Journal Article
• Authors: Morán, Isaac; Perez-Orive, Javier; Melchor, Jonathan; Figueroa, Tonatiuh; Lemus, Luis
• Is Part Of: Progress in neurobiology. Volume 202(2021)
• Publication Date: 2021-07
• Subjects: dPC demixed principal component -- dPCA demixed principal component analysis -- nT non-Target sound -- P1 first temporal position of sounds -- P2 second temporal position of sounds -- P3 third temporal position of sounds -- PCA principal component analysis -- SMA supplementary motor area -- T target sound -- VC green visual cue; Word recognition -- Choices -- Premotor cortex -- Macaque -- Psychophysics; Neurobiology -- Periodicals; Neurology -- Periodicals; Neurology -- Periodicals; Neurobiologie -- Périodiques; 612.8
• DOI: 10.1016/j.pneurobio.2021.102053
• Languages: English
• ISSNs: 0301-0082

Abstract

Highlights: Rhesus monkeys can learn and categorize numerous complex sounds, including words. SMA participates in the categorizing of sounds that give rise to behavioral choices. SMA population coding shifts from acoustic to motor representations during the task. Abstract: In human speech and communication across various species, recognizing and categorizing sounds is fundamental for the selection of appropriate behaviors. However, how does the brain decide which action to perform based on sounds? We explored whether the supplementary motor area (SMA), responsible for linking sensory information to motor programs, also accounts for auditory-driven decision making. To this end, we trained two rhesus monkeys to discriminate between numerous naturalistic sounds and words learned as target (T) or non-target (nT) categories. We found that the SMA at single and population neuronal levels perform decision-related computations that transition from auditory to movement representations in this task. Moreover, we demonstrated that the neural population is organized orthogonally during the auditory and the movement periods, implying that the SMA performs different computations. In conclusion, our results suggest that the SMA integrates acoustic information in order to form categorical signals that drive behavior.