The neural language of song: Brain mechanisms for sensorimotor syntax control

Descrizione del progetto

Substrati neurali della sintassi gerarchica

Le regole della sintassi gerarchica definiscono il modo in cui le unità semplici vengono organizzate per formarne di più complesse e le sequenze motorie obbediscono a tali regole, che si tratti di allacciarsi le scarpe o di cantare una canzone. Finanziato dal Consiglio europeo della ricerca, il progetto NeuralSyntax mira a studiare il canto dei canarini e a decifrare le regole della sintassi gerarchica attraverso l’indagine delle sequenze comportamentali e neurali in essere. Sulla base dei loro studi precedenti, che hanno identificato gli stati neurali nascosti in grado di conservare una memoria delle sillabe cantate per diversi secondi e prevedere le transizioni imminenti, il team cercherà di analizzare i meccanismi di transizione esistenti con l’obiettivo di svelare l’attività neurale alla base delle transizioni tra le sillabe, della selezione della sillaba successiva, dell’adattamento delle regole sintattiche per le nuove canzoni e del rimodellamento stagionale di tali regole.

Obiettivo

Our motor sequences obey syntax rules. From tying shoes to giving a speech, choosing the next action requires our brain to remember past actions, bridge across many seconds, and apply rules that create hierarchical syntax. Whereas past studies revealed how primary motor cortex drives actions, we poorly understand the transition mechanisms by which the brain strings actions into hierarchical variable sequences. The key obstacle is identifying deep hierarchical syntax rules in behavior and in neural sequences. This obstacle is met by studying birdsong that naturally segments to sequences of syllables. In the zebra finch, juveniles learn once from a tutor and fix a single sequence driven by a robust song-locked activity. Here, to study hierarchical syntax rules I will use canaries: virtuosos that learn and adapt such rules along and across seasons. Canaries produce a huge repertoire of songs that enable separate analysis of neural states and syllable acoustics when studying their rich and dynamic syntax rules. My previous work in canaries identified hidden neural states that keep a memory of sung syllables over several seconds and predict upcoming transitions. Here, I leverage this model to dissect transition mechanisms and elucidate: 1) neural activity in the premotor nucleus HVC that underlies flexible transitions between syllables; 2) integration of auditory and thalamic inputs for applying hierarchical syntax rules to select the next syllable; 3) neural state dynamics when adapting syntax rules for new songs; and 4) seasonal remodeling of HVC via neurogenesis. We use imaging, electrophysiology, and neural network simulations that integrate data across behavior, neural activity, and circuit levels of analysis. Our work will map the process by which basal ganglia and thalamocortical circuits generate and adapt hierarchical syntax rules over time, sensory, and social contexts, and might offer insights to dysfunction of motor sequence control in maladaptive conditions.