IFIBYNE   05513
INSTITUTO DE FISIOLOGIA, BIOLOGIA MOLECULAR Y NEUROCIENCIAS
Unidad Ejecutora - UE
congresos y reuniones científicas
Título:
Neuronal Networks for Motor Control
Autor/es:
LIDIA SZCZUPAK
Lugar:
Cordoba
Reunión:
Congreso; XXXIII Congreso Annual de la Sociedad Argentina de Investigación en Neurociencias; 2018
Institución organizadora:
Sociedad Argentina de Investigación en Neurociencias
Resumen:
Neural networks that control animal movement are, on one hand, hierarchically organized and, on the other hand, highly distributed. The study of such networks requires the implementation of experimental strategies that allow simultaneous recordings at multiple levels within the nervous system to evaluate how these levels interact to generate a coherent behavioral output.The nervous system of leeches presents unique advantages for the understanding on how motor control networks function. Leeches display robust locomotive and defensive behaviors. The simplicity of the organism structure is reflected in the relative simplicity of its nervous system formed by a chain of identical ganglia flanked by two brains, one in the head and the other in the tail. Neurons in each ganglion are not type representative units but they play well-defined functions, that are complementary shared with as few as one other neuron to very few other neurons.The study of how the crawling motor pattern is organized in the leech nervous system had shed light on the role played by motoneurons in motor control. Previously conceived as mere output units, motoneurons shape the crawling motor pattern via recurrent inhibitory circuits, and through the interaction with the central pattern generator. Thus in addition to well-known proprioceptive feedback mechanism, the output of motoneurons participates in the pattern generation.The results obtained throughout the analysis of the crawling network do not contradict the hierarchical nature of motor networks but shed light on how the processing of feedforward and feedback signals are essential to shape a behavioral output.