Biased randomness: a fundamental connectivity mechanism for associative brain centers

摘要 揭示使联想脑中心能够学习的神经元连接的基本机制 神经科学的一个重要目标。在果蝇的蘑菇体中，组成Kenyon的 细胞接受来自嗅觉投射神经元的输入。每个投射神经元连接到50个肾小球中的一个 在触角叶，主要的嗅觉处理中心。我们之前的工作表明，这些 连接是随机的，因为没有一组肾小球优先会聚到给定的Kenyon细胞上。 然而，肾小球在Kenyon细胞输入中的出现频率并不相同。某些肾小球 明显过高或过低，即使均匀分布对 学习表现。我们提议测试这种非均匀分布的想法，我们称之为 有偏随机性是一种重要的功能，即使联想词的学习能力提前 大脑集中在某些与行为相关的刺激上。为了检验这一观点，首先，个体的表征 我们将对三种不同果蝇的肾小球进行比较，并研究它们之间的相关性 化学感觉生态学(具体目标1)。第二，肾小球代表性的分子调节器将是 在黑腹小球虫中识别，以操纵单个肾小球的表示并测试对 蘑菇体和学习中的嗅觉表征(特定目标2)。这项提案中的研究已经 揭示神经元连通性被微调到易感的基本机制的可能性 对特别相关的刺激进行学习，因此可能是认知偏差的原因。 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