Generation and manipulation of combinatorial connectivity in olfactory perception

摘要 这一提议解决的中心问题是，大脑如何将几乎无限的对象表示为“范畴”-- 这是一个没有标签的世界“(埃德尔曼，1976)。这个问题在嗅觉方面尤其严重，因为身体上的气味 信号没有明显的维度。而本能意义是通过神经的结构被赋予的 理论上，学习机制可以从缺乏经验的电路中选择与经验相关的表征 一种先验结构。以此类推，脊椎动物的适应性免疫系统通过Se-Se-2来防御新的入侵者。 从随机产生的池中选择性地扩增携带强结合抗体的B细胞。有多混乱- 任何系统都不理解开发过程中的组合连接形式。数值化 脊椎动物嗅皮层和其他联想学习中心的复杂性，包括小脑，髋关节- 校园后，内嗅皮层使发育研究复杂化。相反，我们建议解决这个问题 问题在节肢动物的数字简化嗅觉学习中心，蘑菇体。虽然这件事 大脑区域的功能类似于大脑皮层或小脑，将物体表示为感觉和视觉的组合。 在大量刺激下，果蝇蘑菇体只有2000个内源性神经元。这些固有的凯尼恩细胞接收 3-10个嗅觉输入，每个细胞接受不同的输入。各个Kenyon细胞的输入集合是 不可预测-知道某个特定单元格的一个输入并不能说明该单元格还会收到哪些其他输入。 要问在开发过程中非结构化连接模式是如何形成的，我们首先使用各种技术- Niques操纵Kenyon细胞和它们传入的嗅觉输入之间的比率，以便识别 设置单个Kenyon细胞的输入数量的机制。其次，我们正在测试变异是否 突触前和突触后细胞表面分子的表达允许连接性的变化- 在他们之间。对相关大脑区域的感觉输入的数量复杂性和密度进行了理论分析 “优化”感官对象的表示，这些模式的改变预计会退化神经 以及刺激物之间的行为差异。如果成功，我们将生产一个发育机制的模型- 神经产生神经元对复杂的感觉刺激做出反应，这可以用于研究发育- 脊椎动物联想学习区域的感觉输入和组织；这项研究还将创建 操纵果蝇蘑菇体的连接参数以明确测试连接如何的技术 参数规定了刺激的表示和分离，以及它们的改变如何改变感知和 学习。

ABSTRACT The central problem addressed by this proposal is how the brain represents almost limitless objects to “catego- rize an unlabeled world” (Edelman, 1976). This problem is particularly acute in olfaction, because physical odor signals are not obviously dimensional. While instinctual meanings are imparted through the structure of neural circuits, learning mechanisms can theoretically select experience-relevant representations from circuits lacking a priori structure. By analogy, the vertebrate adaptive immune system defends against novel invaders by se- lectively amplifying B cells carrying strongly binding antibodies from a randomly produced pool. How unstruc- tured, combinatorial connectivity forms during development is not understood in any system. The numerical complexity of vertebrate olfactory cortex and other associative learning centers including the cerebellum, hip- pocampus, and entorhinal cortex complicates developmental studies. Instead, we propose to address this question in the numerically simplified olfactory learning center of arthropods, the mushroom body. While this brain area performs a function similar to the cortex or cerebellum, representing objects as combinations of sen- sory stimuli, the fruit fly mushroom body has only 2000 intrinsic neurons. These intrinsic Kenyon cells receive 3-10 olfactory inputs, with each cell receiving different inputs. The sets of inputs to individual Kenyon cells are unpredictable—knowing one input to a particular cell does not illuminate which other inputs that cell receives. To ask how unstructured connectivity pattern forms during development, we are first using a variety of tech- niques to manipulate the ratio between Kenyon cells and their incoming olfactory inputs in order to identify mechanisms that set the number of inputs to individual Kenyon cells. Second, we are testing whether variation in expression of cell surface molecules across pre- and post-synaptic cells allows variation in connectivity be- tween them. The quantitative complexity and density of sensory inputs to associative brain areas are theorized to “optimize” representations of sensory objects, with alterations in these patterns expected to degrade neural and behavioral distinctions among stimuli. If successful, we will produce a model of the developmental mecha- nisms that generate neurons responding to complex sensory stimuli that can be applied to studying develop- ment and organization of sensory inputs to vertebrate associative learning areas; this study will also create techniques to manipulate the wiring parameters of the Drosophila mushroom body to explicitly test how wiring parameters dictate stimulus representation and separation, and how their alteration alters perception and learning.