NMVLRBG · Neural mechanisms of vocal learning: role of the basal ganglia
FP7 — People (Marie Curie Actions)
- Duration
- 2010-09-01 → 2014-08-31
- EU contribution
- €100,000
- Participants
- 1
- Scheme
- MC-IRG
Lines connect the coordinator with its partners.
Results in brief
Neural mechanisms of vocal learning: role of the basal ganglia
Human speech is a complex sensorimotor skill and vocal learning is one of the most striking cognitive abilities of the brain. As other motor skills, vocal learning naturally emerges from our experience and vocal production is performed without awareness. Such complex motor skill learning requires the acquisition of a given movement sequence, which is learned slowly over several training sessions. Cortical and basal ganglia (BG) networks are involved in the acquisition of motor skills, and their operation is likely optimized by learning mechanisms, each unique to the cortex and BG. How do BG and cortical network interact to successfully imprint long-lasting memories of optimal sensorimotor transformation underlying motor skills? If the BG drive learning in the premotor network, how can motor skill rely only on the premotor network after learning? Songbirds use learned vocalizations to communicate and offer a unique model to study the neural mechanisms of vocal learning. The goal of the present project is to reveal the microscopic (cellular, neuronal) factors that underlie sensorimotor learning in general and vocal learning in particular. To this end, we investigate the neural mechanisms of BG-driven sensorimotor learning in songbirds. Our project combines an experimental approach (chronic neural recording in awake bird, manipulation of single neuron activity through light-activated ion channels) and a theoretical one (development of a mathematical model of the song system). Long-term applications of the proposed research project are numerous, from medicine to robotic. They include, but are not limited to, the discovery of original therapies for language disorders or the design of new algorithms for learning in artificial neural network. On the theoretical side, our studies have revealed that learning the coordination of multiple gestures, the adaptation process for the different gestures can interfere destructively or constructively depending on the similarities between the sensory representation of gestures and the overlap in their neuronal representations. Destructive interferences can result in a drastic slowdown of the adaptation. As a result of interference, the time to adapt varies non-linearly with the number of gestures learned. We also demonstrate how shaping the reinforcement signals or shaping the task can accelerate the learning dramatically by reducing destructive interferences. We argue that experimentally investigating the dynamics of reward-driven sensorimotor adaptation for more than one gesture can shed light on the underlying learning rules. Additionally, we have revealed that there are universal temporal features during babbling-like vocalizations in human and non-human vocal learners and demonstrate how emerging spatiotemporal neuronal variability can produce such behavioral variability. The results points toward a general mechanism for producing universal babbling behavior based on a simple network architecture recently revealed in songbirds. On the experimental side, we have shown the implication of the BG-thalamo-cortical loop in seasonal song plasticity in songbirds. Indeed, the BG loop participates to the additional acoustic variability observed in autumn when the birds resume singing after a silent summer. This is in-line with the role of the BG loop in adding frequency variability in song syllable during juvenile learning in zebra finches, and clearly points to a similar role of the loop during adult song plasticity. Moreover, we find that the global song structure of song (song duration, phrase duration and inter-syllable gap duration), which is clearly affected by seasonal plasticity, is also influenced by the BG loop. While this result is in contrast with the classical role assigned to the BG loop in closed-ended learner songbirds, it opens a new animal model for the study of BG function in adult plasticity. We are currently recording neuronal activity in the GB activity to reveal the underlying mechanisms. Finally, we found an unexpected projection from the deep cerebellar nuclei to the BG, opening a new line of research to investigate the function of the cerebellum and the cerebello-BG interaction in sensorimotor learning in the songbird model.
Data: CORDIS, © European Union
Project objective
Motor skills are acquired through sensorimotor learning and can be executed without awareness. Experimental evidence suggests that the acquisition and execution of motor skills rely on multiple neural networks. On one hand, the basal ganglia (BG) are necessary for the acquisition of a motor skill through sensorimotor learning, but not for its execution later on. On the other hand, premotor networks, such as cortical motor areas, are required for both the learning and execution of motor skills. The respective role of the BG and premotor networks in sensorimotor learning however remains unclear. We aim to deepen our knowledge of the neural mechanisms underlying the acquisition of motor skills and to understand the respective contribution of BG and premotor networks during this process. Our general hypothesis is that DA-dependent learning in the GB drive plastic vocal production during early phases of vocal learning, while extended practice allows cortical premotor networks to be “trained” by the BG output, and to become capable of driving vocal production independently of the BG. To test this hypothesis, we will set up a comprehensive theoretical model of the song system relying heavily on available physiological, anatomical and behavioral data. In this model, we will investigate possible mechanisms allowing the optimization of the vocal output through learning in the BG circuit followed by a transfer of the motor control to the premotor networks. Experimentally testable predictions of the model will be formulated in terms of activity changes in the BG and premotor networks. We will use innovative experimental techniques to test these predictions and collect further data about neural activity in the song system. In particular, we will record song-related neural activity and investigate changes in functional connectivity in the circuit in vivo in a paradigm of adult song learning.
Original text from CORDIS.
Participants
- CENTRE NATIONAL DE LA RECHERCHE SCIENTIFIQUE CNRS · ParisCoordinatorFrance
Links
Data: CORDIS, © European Union
