Biased randomness: a fundamental connectivity mechanism for associative brain centers

总结 揭示神经元连接的基本机制，使联想脑中心能够学习， 神经科学的重要目标。在黑腹果蝇的蘑菇体中， 细胞接收来自嗅觉投射神经元的输入。每个投射神经元连接到50个肾小球之一 在触角叶，主要的嗅觉处理中心。我们之前的研究表明， 连接是随机的，因为不存在优先会聚到给定凯尼恩细胞上的肾小球集合。 然而，肾小球在凯尼恩细胞输入中并不以相等的频率表示。某些肾小球 代表人数明显过多或不足，即使均匀分布是最佳的， 学习绩效我们建议测试这种非均匀分布的想法，我们称之为 “有偏随机性”，服务于一个重要的功能，即倾向于联想的学习能力， 大脑会集中于某些行为学上相关的刺激为了验证这个想法，首先， 肾小球将在三个不同的果蝇物种进行比较，并研究差异的相关性 化学感受生态学（具体目标1）。其次，肾小球代表性的分子调节剂将是 在D.黑腹动物来操纵单个肾小球的代表性，并测试对 蘑菇体中的嗅觉表征和学习（具体目标2）。该提案中的研究 揭示神经元连接性被微调以倾向于 学习特别相关的刺激，从而可能占认知偏差。 1

SUMMARY Uncovering fundamental mechanisms of neuronal connectivity that enable associative brain centers to learn is an important goal of neuroscience. In the Drosophila melanogaster mushroom body, the constituent Kenyon cells receive input from olfactory projection neurons. Each projection neuron connects to one of the 50 glomeruli in the antennal lobe, the primary olfactory processing center. Our previous work has shown that these connections are random in that there are no sets of glomeruli converging preferentially onto a given Kenyon cell. However, the glomeruli are not represented with equal frequency among Kenyon cell inputs. Certain glomeruli are significantly overrepresented or underrepresented, even though a uniform distribution would be optimal for learning performance. We are proposing to test the idea that this non-uniform distribution, which we termed ‘biased randomness’, serves an important function, namely to predispose the learning ability of an associative brain center towards certain ethologically pertinent stimuli. To test this idea, first, the representation of individual glomeruli will be compared in three different Drosophila species and investigated for correlations to differences in chemosensory ecology (Specific Aim 1). Second, molecular regulators of glomerular representation will be identified in D. melanogaster to manipulate the representation of individual glomeruli and test for effects on olfactory representation in the mushroom body and learning (Specific Aim 2). The research in this proposal has the potential to reveal a fundamental mechanism by which neuronal connectivity is fine-tuned to predispose learning towards particularly pertinent stimuli, thus possibly accounting for cognitive biases. 1