Neurobiology Research Unit, Okinawa Institute of Science and Technology Graduate University Okinawa, Japan.
Front Comput Neurosci. 2013 Sep 13;7:119. doi: 10.3389/fncom.2013.00119. eCollection 2013.
The dopamine-dependent plasticity of the cortico-striatal synapses is considered as the cellular mechanism crucial for reinforcement learning. The dopaminergic inputs and the calcium responses affect the synaptic plasticity by way of the signaling cascades within the synaptic spines. The calcium concentration within synaptic spines, however, is dependent on multiple factors including the calcium influx through ionotropic glutamate receptors, the intracellular calcium release by activation of metabotropic glutamate receptors, and the opening of calcium channels by EPSPs and back-propagating action potentials. Furthermore, dopamine is known to modulate the efficacies of NMDA receptors, some of the calcium channels, and sodium and potassium channels that affect the back propagation of action potentials. Here we construct an electric compartment model of the striatal medium spiny neuron with a realistic morphology and predict the calcium responses in the synaptic spines with variable timings of the glutamatergic and dopaminergic inputs and the postsynaptic action potentials. The model was validated by reproducing the responses to current inputs and could predict the electric and calcium responses to glutamatergic inputs and back-propagating action potential in the proximal and distal synaptic spines during up- and down-states. We investigated the calcium responses by systematically varying the timings of the glutamatergic and dopaminergic inputs relative to the action potential and found that the calcium response and the subsequent synaptic potentiation is maximal when the dopamine input precedes glutamate input and action potential. The prediction is not consistent with the hypothesis that the dopamine input provides the reward prediction error for reinforcement learning. The finding suggests that there is an unknown learning mechanisms at the network level or an unknown cellular mechanism for calcium dynamics and signaling cascades.
纹状体中间神经元的电室模型构建及其在多巴胺和谷氨酸信号转导中的应用
纹状体中间神经元的电室模型构建及其在多巴胺和谷氨酸信号转导中的应用
纹状体中间神经元的电室模型构建及其在多巴胺和谷氨酸信号转导中的应用
皮层-纹状体突触的多巴胺依赖性可塑性被认为是强化学习的关键细胞机制。多巴胺能输入和钙反应通过突触棘中的信号级联影响突触可塑性。然而,突触棘内的钙浓度取决于多种因素,包括离子型谷氨酸受体的钙内流、代谢型谷氨酸受体激活引起的细胞内钙释放以及 EPSP 和逆行动作电位引起的钙通道开放。此外,多巴胺被认为可以调节 NMDA 受体、一些钙通道以及影响动作电位逆行传播的钠钾通道的效能。在这里,我们构建了具有真实形态的纹状体中间神经元的电室模型,并预测了谷氨酸能和多巴胺能输入以及突触后动作电位的时变对突触棘内钙反应的影响。该模型通过复制对电流输入的响应得到了验证,并可以预测在上升和下降状态下,谷氨酸能输入和逆行动作电位在近端和远端突触棘中的电和钙反应。我们通过系统地改变谷氨酸能和多巴胺能输入相对于动作电位的时间来研究钙反应,发现当多巴胺输入先于谷氨酸输入和动作电位时,钙反应和随后的突触增强最大。该预测与多巴胺输入为强化学习提供奖励预测误差的假设不一致。这一发现表明,在网络水平或钙动力学和信号级联的未知细胞机制中存在未知的学习机制。