Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724.
Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724
Proc Natl Acad Sci U S A. 2019 May 7;116(19):9610-9615. doi: 10.1073/pnas.1706012116. Epub 2019 Apr 24.
The connections between neurons determine the computations performed by both artificial and biological neural networks. Recently, we have proposed SYNSeq, a method for converting the connectivity of a biological network into a form that can exploit the tremendous efficiencies of high-throughput DNA sequencing. In SYNSeq, each neuron is tagged with a random sequence of DNA-a "barcode"-and synapses are represented as barcode pairs. SYNSeq addresses the analysis problem, reducing a network into a suspension of barcode pairs. Here, we formulate a complementary synthesis problem: How can the suspension of barcode pairs be used to "clone" or copy the network back into an uninitialized tabula rasa network? Although this synthesis problem might be expected to be computationally intractable, we find that, surprisingly, this problem can be solved efficiently, using only neuron-local information. We present the "one-barcode-one-cell" (OBOC) algorithm, which forces all barcodes of a given sequence to coalesce into the same neuron, and show that it converges in a number of steps that is a power law of the network size. Rapid and reliable network cloning with single-synapse precision is thus theoretically possible.
神经元之间的连接决定了人工神经网络和生物神经网络执行的计算。最近，我们提出了 SYNSeq，这是一种将生物网络的连接转换为可以利用高通量 DNA 测序的巨大效率的方法。在 SYNSeq 中，每个神经元都被标记上一段随机的 DNA 序列——“条形码”——而突触则表示为条形码对。SYNSeq 解决了分析问题，将网络简化为条形码对的悬浮液。在这里，我们提出了一个互补的合成问题：悬浮的条形码对如何被用来“克隆”或复制网络回到一个未初始化的空白网络？尽管这个合成问题可能在计算上是难以处理的，但我们发现，令人惊讶的是，这个问题可以通过仅使用神经元局部信息来有效地解决。我们提出了“一个条形码一个细胞”（OBOC）算法，它迫使给定序列的所有条形码都合并到同一个神经元中，并表明它在网络大小的幂次的几个步骤中收敛。因此，具有单突触精度的快速可靠的网络克隆在理论上是可能的。
