Borst Alexander
Max Planck Institute for Biological Intelligence, Martinsried, Germany.
J Comput Neurosci. 2025 Sep 26. doi: 10.1007/s10827-025-00914-5.
Visual interneurons come in many different flavors, representing luminance changes at one location as ON or OFF signals with different dynamics, ranging from purely sustained to sharply transient responses. While the functional relevance of this representation for subsequent computations like direction-selective motion detection is well understood, the mechanisms by which these differences in dynamics arise are unclear. Here, I study this question in the fly optic lobe. Taking advantage of the known connectome I simulate a network of five adjacent optical columns each comprising 65 different cell types. Each neuron is modeled as an electrically compact single compartment, conductance-based element that receives input from other neurons within its column and from its neighboring columns according to the intra- and inter-columnar connectivity matrix. The sign of the input is determined according to the known transmitter type of the presynaptic neuron and the receptor on the postsynaptic side. In addition, some of the neurons are given voltage-dependent conductances known from the fly transcriptome. As free parameters, each neuron has an input and an output gain, applied to all its input and output synapses, respectively. The parameters are adjusted such that the spatio-temporal receptive field properties of 13 out of the 65 simulated neurons match the experimentally determined ones as closely as possible. Despite the fact that all neurons have identical leak conductance and membrane capacitance, this procedure leads to a surprisingly good fit to the data, where specific neurons respond transiently while others respond in a sustained way to luminance changes. This fit critically depends on the presence of an H-current in some of the first-order interneurons, i.e., lamina cells L1 and L2: turning off the H-current eliminates the transient response nature of many neurons leaving only sustained responses in all of the examined interneurons. I conclude that the diverse dynamic response behavior of the columnar neurons in the fly optic lobe starts in the lamina and is created by their different intrinsic membrane properties. I predict that eliminating the hyperpolarization-activated current by RNAi should strongly affect the dynamics of many medulla neurons and, consequently, also higher-order functions depending on them like direction-selectivity in T4 and T5 neurons.
视觉中间神经元有多种不同类型,它们将一个位置的亮度变化表示为具有不同动态特性的开或关信号,范围从纯粹持续的到急剧瞬态的反应。虽然这种表示对于后续诸如方向选择性运动检测等计算的功能相关性已得到很好理解,但这些动态差异产生的机制尚不清楚。在这里,我在果蝇视叶中研究这个问题。利用已知的连接体,我模拟了一个由五个相邻光柱组成的网络,每个光柱包含65种不同的细胞类型。每个神经元被建模为一个电紧凑的单室、基于电导的元件,它根据柱内和柱间连接矩阵从其所在柱内的其他神经元以及相邻柱接收输入。输入的符号根据突触前神经元已知的递质类型和突触后一侧的受体来确定。此外,一些神经元具有从果蝇转录组中得知的电压依赖性电导。作为自由参数,每个神经元分别有一个输入增益和一个输出增益,应用于其所有输入和输出突触。调整这些参数,以使65个模拟神经元中的13个的时空感受野特性尽可能紧密地匹配实验确定的特性。尽管所有神经元具有相同的漏电导和膜电容,但这个过程导致对数据的拟合出奇地好,其中特定神经元对亮度变化做出瞬态反应,而其他神经元则以持续方式做出反应。这种拟合关键取决于一些一级中间神经元(即外膝体细胞L1和L2)中H电流的存在:关闭H电流会消除许多神经元的瞬态反应特性,在所有检查的中间神经元中只留下持续反应。我得出结论,果蝇视叶中柱状神经元多样的动态反应行为始于外膝体,并由它们不同的内在膜特性产生。我预测,通过RNA干扰消除超极化激活电流应该会强烈影响许多髓质神经元的动态特性,因此也会影响依赖于它们的高阶功能,如T4和T5神经元中的方向选择性。