Hiratani Naoki, Fukai Tomoki
Department of Complexity Science and Engineering, The University of TokyoKashiwa, Japan; Laboratory for Neural Circuit Theory, RIKEN Brain Science InstituteWako, Japan.
Laboratory for Neural Circuit Theory, RIKEN Brain Science Institute Wako, Japan.
Front Neural Circuits. 2016 May 31;10:41. doi: 10.3389/fncir.2016.00041. eCollection 2016.
In the adult mammalian cortex, a small fraction of spines are created and eliminated every day, and the resultant synaptic connection structure is highly nonrandom, even in local circuits. However, it remains unknown whether a particular synaptic connection structure is functionally advantageous in local circuits, and why creation and elimination of synaptic connections is necessary in addition to rich synaptic weight plasticity. To answer these questions, we studied an inference task model through theoretical and numerical analyses. We demonstrate that a robustly beneficial network structure naturally emerges by combining Hebbian-type synaptic weight plasticity and wiring plasticity. Especially in a sparsely connected network, wiring plasticity achieves reliable computation by enabling efficient information transmission. Furthermore, the proposed rule reproduces experimental observed correlation between spine dynamics and task performance.
在成年哺乳动物的皮层中，每天都有一小部分树突棘产生和消除，即使在局部回路中，由此产生的突触连接结构也是高度非随机的。然而，尚不清楚特定的突触连接结构在局部回路中是否具有功能优势，以及除了丰富的突触权重可塑性之外，为何还需要突触连接的产生和消除。为了回答这些问题，我们通过理论和数值分析研究了一个推理任务模型。我们证明，通过结合赫布型突触权重可塑性和布线可塑性，一种稳健有益的网络结构自然出现。特别是在稀疏连接的网络中，布线可塑性通过实现高效的信息传输来实现可靠的计算。此外，所提出的规则再现了实验观察到的树突棘动力学与任务表现之间的相关性。
