Convergent vocal representations in parrot and human forebrain motor networks

Abstract

Cortical networks for the production of spoken language in humans are organized by phonetic features1,2, such as articulatory parameters3,4 and vocal pitch5,6. Previous research has failed to find an equivalent forebrain representation in other species7–11. To investigate whether this functional organization is unique to humans, here we performed population recordings in the vocal production circuitry of the budgerigar (Melopsittacus undulatus), a small parrot that can generate flexible vocal output12–15, including mimicked speech sounds16. Using high-density silicon probes17, we measured the song-related activity of a forebrain region, the central nucleus of the anterior arcopallium (AAC), which directly projects to brainstem phonatory motor neurons18–20. We found that AAC neurons form a functional vocal motor map that reflects the spectral properties of ongoing vocalizations. We did not observe this organizing principle in the corresponding forebrain circuitry of the zebra finch, a songbird capable of more limited vocal learning21. We further demonstrated that the AAC represents the production of distinct vocal features (for example, harmonic structure and broadband energy). Furthermore, we discovered an orderly representation of vocal pitch at the population level, with single neurons systematically selective for different frequency values. Taken together, we have uncovered a functional representation in a vertebrate brain that displays unprecedented commonalities with speech-related motor cortices in humans. This work therefore establishes the parrot as an important animal model for investigating speech motor control and for developing therapeutic solutions for addressing a range of communication disorders22,23. Using advanced brain-recording techniques, parrots were found to have a brain organization for vocal control similar to humans, making them an important model for studying speech and for developing potential treatments for communication disorders.