Processing properties of ON and OFF pathways for Drosophila motion detection.
Processing properties of ON and OFF pathways for Drosophila motion detection.
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DOI：
10.1038/nature13427
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发表时间：
2014-08-28
期刊：
影响因子：
64.8
通讯作者：
Desplan, Claude
中科院分区：
文献类型：
--
作者：
Behnia, Rudy;Clark, Damon A.;Carter, Adam G.;Clandinin, Thomas R.;Desplan, Claude
处理亮度时空变化以提取视觉运动线索的算法和神经回路一直是深入研究的焦点。一个有影响力的模型，即哈森斯坦 - 赖夏特相关器（HRC），依赖于对两个空间上分离的输入通道进行差分时间滤波，使一个输入信号相对于另一个延迟。特定方向的运动导致这些延迟和未延迟的亮度信号同时到达大脑中的后续处理步骤；然后这些信号被非线性放大以产生方向选择性反应（图1A）。果蝇方面的近期研究已经确定了两条对移动的亮边或暗边有选择性反应的平行通路。这些通路中的每一条都需要对传入信号应用两个关键处理步骤：空间输入通道之间的差分延迟，以及对亮度增加和减少信号的不同处理。通过体内膜片钳记录，我们证明了四种髓质神经元实现了这两个处理步骤。神经元Mi1和Tm3对亮度增加有选择性反应，Mi1的反应相对于Tm3延迟。相反，Tm1和Tm2对亮度减少有选择性反应，Tm1的反应相比于Tm2延迟。值得注意的是，利用这些测量结果对HRC模型进行约束所产生的输出与先前测量的运动探测器特性一致，包括时间频率调谐以及对亮边和暗边的特异性。我们提出Mi1和Tm3对负责检测亮边的相关器的延迟和未延迟输入通道进行关键处理，而Tm1和Tm2在检测移动暗边中起类似作用。我们的数据表明，特定的髓质神经元具有响应特性，使其能够实现HRC中相关操作之前的算法步骤，揭示了长期以来在果蝇中寻求的运动检测神经基质的要素。
The algorithms and neural circuits that process spatiotemporal changes in luminance to extract visual motion cues have been the focus of intense research. An influential model, the Hassenstein-Reichardt correlator (HRC), relies on differential temporal filtering of two spatially separated input channels, delaying one input signal with respect to the other. Motion in a particular direction causes these delayed and non-delayed luminance signals to arrive simultaneously at a subsequent processing step in the brain; these signals are then nonlinearly amplified to produce a direction-selective response (Figure 1A). Recent work in Drosophila has identified two parallel pathways that selectively respond to either moving light or dark edges. Each of these pathways requires two critical processing steps to be applied to incoming signals: differential delay between the spatial input channels, and distinct processing of brightness increment and decrement signals. Using in vivo patch-clamp recordings, we demonstrate that four medulla neurons implement these two processing steps. The neurons Mi1 and Tm3 respond selectively to brightness increments, with the response of Mi1 delayed relative to Tm3. Conversely, Tm1 and Tm2 respond selectively to brightness decrements, with the response of Tm1 delayed compared to Tm2. Remarkably, constraining HRC models using these measurements produces outputs consistent with previously measured properties of motion detectors, including temporal frequency tuning and specificity for light vs. dark edges. We propose that Mi1 and Tm3 perform critical processing of the delayed and non-delayed input channels of the correlator responsible for the detection of light edges, while Tm1 and Tm2 play analogous roles in the detection of moving dark edges. Our data shows that specific medulla neurons possess response properties that allow them to implement the algorithmic steps that precede the correlative operation in the HRC, revealing elements of the long-sought neural substrates of motion detection in the fly.
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