Model Neuron Encoding the Realistic Learning Rule

描述（由申请人提供）：活动依赖性突触修饰、长时程增强（LTP）和抑制（LTD）在神经网络的信息处理和存储中至关重要。因此，理解突触修饰的机制对于理解学习和记忆功能至关重要。我们的长期研究目标是了解海马神经网络中突触修饰是如何参与信息处理的。然而，中枢神经网络的复杂性阻碍了仅通过生物学方法解决这些问题。因此，我们建议联合收割机电生理和计算建模的方法来开发一个模型神经元系统编码相关的突触前和突触后活动诱导的大鼠海马脑片的突触修饰。这些研究将使我们能够预测突触修饰如何调节神经元网络中的多个时空不同的输入，这超出了目前的电生理技术。 先前我们已经通过海马CAI神经元的电生理学研究证明：1）5 Hz下的相关活动可以诱导LTP或LTD，这取决于突触前和突触后激活的精确定时，2）激活位点的LTP存在的窄时间窗（15 ms）两侧是LTD的两个时间窗，其可以从受刺激的（同突触的）部位传播到未受刺激的（异突触的）部位，3）LTP和LTD之间的转变发生在25 ms内，这是40 Hz振荡的特征时间。此外，突触后Ca 2+，来自Ca 2+内流通过N-甲基-D-天冬氨酸受体和钙的差异释放从内部存储通过ryanodine和IP 3受体，调节活动诱导的突触修饰的极性和输入特异性。我们的研究结果表明，活动依赖性突触修饰和海马中位置细胞的振荡模式之间存在联系，这被认为是空间记忆的原因。 使用一个综合的方法，结合电生理学，Ca 2+和光学成像，并在海马切片的计算建模，我们特别旨在解决以下问题：1）什么是突触可塑性的传播从激活的突触到非激活的突触的时空模式？我们将描述LTP和LTD在突触后沿着树突状乔木或突触前通过逆行信号传导的传播。2)抑制性神经元如何参与决定神经网络中突触修饰的极性和程度？3)在突触后神经元中，不同通路上基于尖峰定时的突触修饰是如何整合的？利用尖峰定时为基础的诱导协议，我们将研究如何起源于各种时空差异的输入信号可以集成在一个单一的突触后神经元。这些研究将大大有助于我们理解学习和记忆的细胞和分子基础。

DESCRIPTION (provided by applicant): Activity-dependent synaptic modifications, long-term potentiation (LTP) and depression (LTD) are essential in information processing and storage in neural networks. Thus, understanding mechanisms of synaptic modifications are crucial in understanding learning and memory functions. The long-term goal of our research is to understand how synaptic modifications are involved in information processing in hippocampal neural network. However, the complexity of central neural networks hinders addressing these issues through biological approaches alone. Therefore, we propose to combine electrophysiologic and computational modeling approaches to develop a model neuron system encoding synaptic modifications induced by correlated pre- and postsynaptic activity in rat hippocampal slices. These studies will enable us to predict how synaptic modifications modulate the multiple spatiotemporal-distinct inputs in neuronal networks that is beyond current electrophysiological techniques. Previously we have demonstrated by electrophysiological studies in hippocampal "CAI neurons that 1) correlated activity at 5 Hz can induce either LTP or LTD, depending on the precise timing of pre-and postsynaptic activation, 2) a narrow time window (15 ms) that exists for LTP of the activated site is flanked by two time windows for LTD, which can spread from stimulated (homosynaptic) to non-stimulated (heterosynaptic) sites, 3) the transition between LTP and LTD occurs within 25 ms, a characteristic time for 40 Hz oscillations. Furthermore, the postsynaptic Ca2+, derived from Ca2+ influx via N-methyl-D-aspartate receptors and a differential release of Ca2+ from internal stores via ryanodine and IP3 receptors, regulates both polarity and input specificity of activity-induced synaptic modificalion. Our findings suggest a link between activity-dependent synaptic modifications and oscillation patters of place cells in the hippocampus, which are believed to be responsible for spatial memory. Using an integrative approach that combines electrophysiology, Ca2+ and optical imaging, and computational modeling in hippocampal slices, we specifically aims to address following questions: 1) What is the spatiotemporal pattern of spread of synaptic plasticity from activated synapses to non-activated synapses? We will characterize the spread of LTP and LTD postsynaptically along the dendritic arbor or presynaptically via retrograde signaling. 2) How are inhibitory neurons involved in determination of polarity and extent of synaptic modifications in neural networks? 3) How are spike-timing based synaptic modifications at different pathways integrated in a postsynaptic neuron? Taking advantage of the spike-timing based induction protocol, we will investigate how signals originated from inputs with various spatiotemporal differences can be integrated in a single postsynaptic neuron. These studies will contribute significantly to our understanding the cellular and molecular basis of learning and memory.