Sussillo David, Churchland Mark M, Kaufman Matthew T, Shenoy Krishna V
Department of Electrical Engineering and Neurosciences Program, Stanford University, Stanford, California, USA.
Department of Neuroscience, Grossman Center for the Statistics of Mind, David Mahoney Center for Brain and Behavior Research, Kavli Institute for Brain Science, Columbia University Medical Center, New York, New York, USA.
Nat Neurosci. 2015 Jul;18(7):1025-33. doi: 10.1038/nn.4042. Epub 2015 Jun 15.
It remains an open question how neural responses in motor cortex relate to movement. We explored the hypothesis that motor cortex reflects dynamics appropriate for generating temporally patterned outgoing commands. To formalize this hypothesis, we trained recurrent neural networks to reproduce the muscle activity of reaching monkeys. Models had to infer dynamics that could transform simple inputs into temporally and spatially complex patterns of muscle activity. Analysis of trained models revealed that the natural dynamical solution was a low-dimensional oscillator that generated the necessary multiphasic commands. This solution closely resembled, at both the single-neuron and population levels, what was observed in neural recordings from the same monkeys. Notably, data and simulations agreed only when models were optimized to find simple solutions. An appealing interpretation is that the empirically observed dynamics of motor cortex may reflect a simple solution to the problem of generating temporally patterned descending commands.
运动皮层中的神经反应如何与运动相关，这仍是一个悬而未决的问题。我们探讨了这样一种假设，即运动皮层反映了适合生成具有时间模式的传出指令的动力学。为了使这一假设形式化，我们训练循环神经网络来重现伸手抓物的猴子的肌肉活动。模型必须推断出能够将简单输入转化为肌肉活动的时间和空间复杂模式的动力学。对经过训练的模型的分析表明，自然的动力学解决方案是一个低维振荡器，它产生必要的多相指令。在单神经元和群体水平上，这个解决方案都与在同一只猴子的神经记录中观察到的情况非常相似。值得注意的是，只有当模型经过优化以找到简单解决方案时，数据和模拟结果才会一致。一个有吸引力的解释是，从经验上观察到的运动皮层动力学可能反映了生成具有时间模式的下行指令问题的一个简单解决方案。
