Cerebellar circuits for locomotor learning in space and time

Informacje na temat projektu

LOCOLEARN

Identyfikator umowy o grant: 866237

DOI

10.3030/866237

Projekt został zamknięty

Data podpisania przez KE 10 Kwietnia 2020

Data rozpoczęcia 1 Maja 2020

Data zakończenia 30 Kwietnia 2026

Finansowanie w ramach

• EXCELLENT SCIENCE - European Research Council (ERC)

Koszt całkowity

€ 1 999 375,00

Wkład UE

€ 1 999 375,00

Koordynowany przez

FUNDACAO D. ANNA DE SOMMER CHAMPALIMAUD E DR. CARLOS MONTEZ CHAMPALIMAUD
Portugal

Periodic Reporting for period 3 - LOCOLEARN (Cerebellar circuits for locomotor learning in space and time)

Okres sprawozdawczy: 2023-05-01 do 2024-10-31

Podsumowanie kontekstu i ogólnych celów projektu

Every movement we make requires us to coordinate our actions precisely in space and time. This proposal aims to understand how that remarkable coordination is achieved by neural circuits controlling movement. The cerebellum plays a critical role in keeping movements calibrated and coordinated, and it is thought to do this in part through a motor learning process in which predictable perturbations of movement are gradually compensated. Cerebellum-dependent forms of motor learning have been identified for a variety of behaviors, including locomotion, and locomotor learning is used as a rehabilitative therapy in human patients. We recently established locomotor learning in mice, using a custom-built, transparent split-belt treadmill that controls the speeds of the two sides of the body independently and allows for high-resolution behavioral readouts. Here, we will combine quantitative analysis of locomotor behavior with genetic circuit dissection to answer two fundamental questions: How are cerebellar outputs read out by downstream circuits, to calibrate spatial and temporal components of movement? and How are instructive signals for spatial and temporal learning encoded by cerebellar inputs? These studies will allow us to bridge levels of analysis to understand how cerebellar learning mechanisms convert behaviorally-relevant sensorimotor error signals into calibration signals that ensure accurate and coordinated movements in space and time for a wide range of behaviors.

Prace wykonane od początku projektu do końca okresu sprawozdawczego oraz najważniejsze dotychczasowe rezultaty

Supervised learning depends on instructive signals that shape the output of neural circuits to support learned changes in behavior. We published a preprint (Silva et al., bioRxiv 2022) in which we used cell-type specific optogenetic perturbations activity in specific cerebellar cell types to systematically evaluate their contributions to delay eyeblink conditioning, a form of cerebellum-dependent learning. Our findings reveal a necessary and sufficient role for climbing fibers and corresponding Purkinje cell complex spike-events as instructive signals for associative cerebellar learning. This work provides some of the strongest evidence to date linking activity in specific cell types with behavioral learning.

Innowacyjność oraz oczekiwany potencjalny wpływ (w tym dotychczasowe znaczenie społeczno-gospodarcze i szersze implikacje społeczne projektu)

In ongoing work we are extending our analyses of instructive signals for cerebellar learning (Silva et al., bioRxiv 2022) to their role in achieving and maintaining coordinated walking patterns in response to changes in the environment. These studies involve measuring and manipulating activity in defined cerebellar cell types, as well as their inputs and outputs, during complex, whole-body locomotor behaviors. Ongoing and future experiments will: 1) Use circuit tracing combined with manipulation of specific cerebellar outputs to identify downstream pathways for spatial and temporal locomotor learning, 2) Investigate the necessity and sufficiency of climbing fiber instructive signals for cerebellar learning via optogenetic perturbation of their activity, and 3) Image complex spike activity from populations of Purkinje cells during locomotion and learning to ask how spatial and temporal error signals are encoded within the cerebellum. These studies will allow us to bridge levels of analysis and begin to understand how cerebellar learning mechanisms convert behaviorally-relevant error signals into calibration signals that ensure accurate and coordinated movements in space and time for a wide range of behaviors.