A NEURAL-NETWORK FOR CODING OF TRAJECTORIES BY TIME-SERIES OF NEURONAL POPULATION VECTORS
A NEURAL-NETWORK FOR CODING OF TRAJECTORIES BY TIME-SERIES OF NEURONAL POPULATION VECTORS
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DOI：
10.1162/neco.1994.6.1.19
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发表时间：
1994-01-01
影响因子：
2.9
通讯作者：
GEORGOPOULOS, AP
中科院分区：
文献类型：
--
作者：
LUKASHIN, AV;GEORGOPOULOS, AP
神经元群体向量是运动皮层中定向调谐细胞群的组合方向趋势的度量。实验发现，可以通过将连续时刻计算的总体向量从头到尾相加来构建神经轨迹，从而预测肢体运动的轨迹。在本文中，我们考虑种群向量动态演化的模型。模拟退火算法用于调整反馈神经网络的连接强度，使其通过群体向量序列生成给定的轨迹。对于不同的轨迹重复此操作。无论网络生成的轨迹类型如何，所得的连接强度集都揭示了一个共同特征：即平均连接强度与连接中涉及的神经元对的首选方向之间的角度负相关。根据最近有关运动皮层内神经元连接的实验结果对结果进行了讨论。
The neuronal population vector is a measure of the combined directional tendency of the ensemble of directionally tuned cells in the motor cortex. It has been found experimentally that a trajectory of limb movement can be predicted by adding together population vectors, tip-to-tail, calculated for successive instants of time to construct a neural trajectory. In the present paper we consider a model of the dynamic evolution of the population vector. The simulated annealing algorithm was used to adjust the connection strengths of a feedback neural network so that it would generate a given trajectory by a sequence of population vectors. This was repeated for different trajectories. Resulting sets of connection strengths reveal a common feature regardless of the type of trajectories generated by the network: namely, the mean connection strength was negatively correlated with the angle between the preferred directions of neuronal pair involved in the connection. The results are discussed in the light of recent experimental findings concerning neuronal connectivity within the motor cortex.