Motor primitives in space and time via targeted gain modulation in cortical networks.
Nat Neurosci
; 21(12): 1774-1783, 2018 12.
Article
en En
| MEDLINE
| ID: mdl-30482949
ABSTRACT
Motor cortex (M1) exhibits a rich repertoire of neuronal activities to support the generation of complex movements. Although recent neuronal-network models capture many qualitative aspects of M1 dynamics, they can generate only a few distinct movements. Additionally, it is unclear how M1 efficiently controls movements over a wide range of shapes and speeds. We demonstrate that modulation of neuronal input-output gains in recurrent neuronal-network models with a fixed architecture can dramatically reorganize neuronal activity and thus downstream muscle outputs. Consistent with the observation of diffuse neuromodulatory projections to M1, a relatively small number of modulatory control units provide sufficient flexibility to adjust high-dimensional network activity using a simple reward-based learning rule. Furthermore, it is possible to assemble novel movements from previously learned primitives, and one can separately change movement speed while preserving movement shape. Our results provide a new perspective on the role of modulatory systems in controlling recurrent cortical activity.
Texto completo:
1
Bases de datos:
MEDLINE
Asunto principal:
Aprendizaje
/
Corteza Motora
/
Movimiento
/
Red Nerviosa
/
Neuronas
Tipo de estudio:
Qualitative_research
Límite:
Animals
Idioma:
En
Revista:
Nat Neurosci
Asunto de la revista:
NEUROLOGIA
Año:
2018
Tipo del documento:
Article
País de afiliación:
Reino Unido