info:eu-repo/semantics/article
Neurally driven synthesis of learned, complex vocalizations
Registro en:
Arneodo, Ezequiel Matías; Chen, Shukai; Brown, Daril E.; Gilja, Vikash; Gentner, Timothy Q.; Neurally driven synthesis of learned, complex vocalizations; Cell Press; Current Biology; 31; 15; 8-2021; 3419-3425
0960-9822
CONICET Digital
CONICET
Autor
Arneodo, Ezequiel Matías
Chen, Shukai
Brown, Daril E.
Gilja, Vikash
Gentner, Timothy Q.
Resumen
Brain machine interfaces (BMIs) hold promise to restore impaired motor function and serve as powerful tools to study learned motor skill. While limb-based motor prosthetic systems have leveraged nonhuman primates as an important animal model,1–4 speech prostheses lack a similar animal model and are more limited in terms of neural interface technology, brain coverage, and behavioral study design.5–7 Songbirds are an attractive model for learned complex vocal behavior. Birdsong shares a number of unique similarities with human speech,8–10 and its study has yielded general insight into multiple mechanisms and circuits behind learning, execution, and maintenance of vocal motor skill.11–18 In addition, the biomechanics of song production bear similarity to those of humans and some nonhuman primates.19–23 Here, we demonstrate a vocal synthesizer for birdsong, realized by mapping neural population activity recorded from electrode arrays implanted in the premotor nucleus HVC onto low-dimensional compressed representations of song, using simple computational methods that are implementable in real time. Using a generative biomechanical model of the vocal organ (syrinx) as the low-dimensional target for these mappings allows for the synthesis of vocalizations that match the bird's own song. These results provide proof of concept that high-dimensional, complex natural behaviors can be directly synthesized from ongoing neural activity. This may inspire similar approaches to prosthetics in other species by exploiting knowledge of the peripheral systems and the temporal structure of their output. Fil: Arneodo, Ezequiel Matías. University of California; Estados Unidos. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Física La Plata. Universidad Nacional de La Plata. Facultad de Ciencias Exactas. Instituto de Física La Plata; Argentina Fil: Chen, Shukai. University of California; Estados Unidos Fil: Brown, Daril E.. University of California; Estados Unidos Fil: Gilja, Vikash. University of California; Estados Unidos Fil: Gentner, Timothy Q.. The Kavli Institute For Brain And Mind; Estados Unidos. University of California; Estados Unidos