Réseau locomoteur spinal

Résumé

Le réseau locomoteur spinal, ou central pattern generator (CPG) en anglais, est un réseau de neurones localisé dans la moelle spinale responsable de la locomotion. La particularité de ce réseau est qu’il peut fonctionner de manière autonome, indépendamment des commandes descendantes et des retours sensoriels . Après avoir été activé par le cortex moteur ou d'autres régions supraspinales telles que la région mésencéphalique locomotrice (MLR en anglais), ce réseau peut générer à lui seul l’activité locomotrice. Historique

1700 : intuition de l’implication de la moelle épinière dans la genèse de la locomotion a été pressentie à l’époque de la civilisation égyptienne. Le papyrus Edwin Smith faisait la liaison entre lésion spinale et fonction motrice des membres .
1910 : Charles Scott Sherrington traite du rôle prédominant des informations proprioceptives musculaires dans l’élaboration d’activités locomotrices rythmiques qu’il limitait à une succession de boucles réflexe

Source officielle

https://fr.wikipedia.org/wiki/R%C3%A9seau_locomoteur_spinal

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CPG-based prostheses control

Marc Louis

In this thesis we describe a strategy to control robotic knees and ankles. A dynamical system is used to generate a position trajectory to control a servo motor replacing the missing joint. The dynamical system consists in a pool of coupled oscillators modeling a central pattern generator (CPG). As a first step, anthropometric trajectories of the knee and ankle are learned by the system through the convergence of the oscillators to the specific frequencies, corresponding amplitudes and phase relations. The same system is then used to play back these trajectories. As a sensory feedback to trigger the playback we use one adaptive frequency oscillator to synchronized with the acceleration from the thigh. We use a bipedal model in a physics-based robot simulation environment to test the proposed system. Finally we present a simple hardware implementation of this system on the Agonist-Antagonist Active Knee prototype.

2010

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Reverse engineering the motor control system

Berat Denizdurduran

Mammalian motor control is implemented by a combination of different networks and system, working coherently to plan the movement of the body or a limb and to execute this movement a dynamical environment. While it is believed that complex, voluntary movements are planned in the motor areas of the cortex, the execution of the movement is controlled by a combination of cortical and cerebellar networks together with central pattern generators and reflex circuits in the spinal cord. In this thesis, we propose an abstract model that captures the basic properties of mammalian motor control, using the example of two different movements: arm movements as well as locomotion. Our model consists of three parts: first a high-level network, that learns movements, using a combination of actor-critic based reinforcement learning and Optimal Control theory. The second part corresponds to spinal reflex circuits that execute basic movements of the musculo-skeletal system. They are modeled by a simple neural network, that learns the dynamic properties of the muscoloskeletal system by the mechanism of spontaneous motor activity (muscle twithing) combined with a Hebbian learning rule. We demonstrate that this network can learn the antagonistic control of joint movements. The final part of the model is a cerebellar network, that translates a complex movement trajectory, such as reaching, and activates the spinal reflex circuits to execute the movement. The mapping between the cerebellar neurons and the spinal reflex circuits are trained with artificial neural networks. Using a musculoskeletal arm model, we demonstrate that the proposed neural motor control model can generate the movement to arbitrary goal position.

EPFL2019

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Spinal V1 neurons inhibit motor targets locally and sensory targets distally

Yann Roussel

Rostro-caudal coordination of spinal motor output is essential for locomotion. Most spinal interneurons project axons longitudinally to govern locomotor output, yet their connectivity along this axis remains unclear. In this study, we use larval zebrafish to map synaptic outputs of a major inhibitory population, V1 (Eng1(+)) neurons, which are implicated in dual sensory and motor functions. We find that V1 neurons exhibit long axons extending rostrally and exclusively ipsilaterally for an average of 6 spinal segments; however, they do not connect uniformly with their post-synaptic targets along the entire length of their axon. Locally, V1 neurons inhibit motor neurons (both fast and slow) and other premotor targets, including V2a, V2b, and commissural premotor neurons. In contrast, V1 neurons make robust long-range inhibitory contacts onto a dorsal horn sensory population, the commissural primary ascending neurons (CoPAs). In a computational model of the ipsilateral spinal network, we show that this pattern of short-range V1 inhibition to motor and premotor neurons underlies burst termination, which is critical for coordinated rostro-caudal propagation of the loco motor wave. We conclude that spinal network architecture in the longitudinal axis can vary dramatically, with differentially targeted local and distal connections, yielding important consequences for function.

CELL PRESS2021

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