Bhalla Upinder Singh
National Centre for Biological Sciences, Tata Institute of Fundamental Research, Bangalore, India.
Elife. 2017 Apr 19;6:e25827. doi: 10.7554/eLife.25827.
Sequences of events are ubiquitous in sensory, motor, and cognitive function. Key computational operations, including pattern recognition, event prediction, and plasticity, involve neural discrimination of spatio-temporal sequences. Here, we show that synaptically-driven reaction-diffusion pathways on dendrites can perform sequence discrimination on behaviorally relevant time-scales. We used abstract signaling models to show that selectivity arises when inputs at successive locations are aligned with, and amplified by, propagating chemical waves triggered by previous inputs. We incorporated biological detail using sequential synaptic input onto spines in morphologically, electrically, and chemically detailed pyramidal neuronal models based on rat data. Again, sequences were recognized, and local channel modulation downstream of putative sequence-triggered signaling could elicit changes in neuronal firing. We predict that dendritic sequence-recognition zones occupy 5 to 30 microns and recognize time-intervals of 0.2 to 5 s. We suggest that this mechanism provides highly parallel and selective neural computation in a functionally important time range.
事件序列在感觉、运动和认知功能中无处不在。关键的计算操作,包括模式识别、事件预测和可塑性,都涉及对时空序列的神经辨别。在这里,我们表明树突上由突触驱动的反应扩散途径可以在与行为相关的时间尺度上执行序列辨别。我们使用抽象信号模型表明,当连续位置的输入与由先前输入触发的传播化学波对齐并被其放大时,选择性就会出现。我们基于大鼠数据,在形态学、电学和化学方面详细的锥体神经元模型中,通过将序列突触输入到棘上来纳入生物学细节。同样,序列被识别出来,并且假定的序列触发信号下游的局部通道调制可以引发神经元放电的变化。我们预测树突序列识别区域占据5到30微米,并识别0.2到5秒的时间间隔。我们认为这种机制在功能重要的时间范围内提供了高度并行和选择性的神经计算。