The neural mechanisms that lead to sparse coding within the midbrain of weakly electric fish

导致弱电鱼中脑稀疏编码的神经机制

• 批准号: RGPIN-2020-04199
• 负责人: Chacron, Maurice
• 金额: $ 2.91万
• 依托单位: McGill University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2022
• 资助国家: 加拿大
• 起止时间: 2022-01-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=763285
• 关键词: neural; mechanisms; lead; sparse; coding

As you are reading this text, neurons in your brain allow you to distinguish the various letters forming words and sentences, thereby forming a neural representation that changes from brain area to brain area. While neurons in more peripheral areas (e.g., your retina) tend to respond to the physical attributes of the sensory input (e.g., the luminance and contrast of the image), neurons in more central brain areas (e.g., your visual cortices) instead tend to respond more to abstract features (e.g., the letter "d" but not the letter "b"), despite obvious similarities (e.g., one is the mirror image of the other). This is known as "response selectivity" and has been observed across systems (visual, auditory, somatosensory, olfactory) and species ranging from insects to us. At the same time, neurons in more central brain areas become more tolerant to identity preserving transformations of sensory input (e.g., a neuron would respond to the letter "d" irrespective of size or font). This is known as invariance and has also been observed across systems and species. Perhaps the best-known example of invariance is the so-called "Jennifer Anniston" neuron that respond to pictures of the actress irrespective of viewpoint but not of another person (e.g., Halle Berry). There thus needs to be a balance between selectivity, which aims at restricting the stimuli that give rise to neural responses and invariance, which instead aims at expanding the stimuli that give rise to neural responses. Such a balance is absolutely essential in order for us to recognize other people and objects in our environment, thereby allowing us to successfully interact with our environment. However, the mechanisms that lead to selectivity and invariance are poorly understood in general in vertebrates, and even less is known about how a balance between both is achieved. Here I propose to study these using a combination of neural recordings and behavioral approaches using the electrosensory system of weakly electric fish. This model system shares many similarities with our auditory and visual systems and has the advantage of well-characterized anatomy and circuitry. Moreover, sensory stimuli can easily be mimicked in the laboratory and will give rise to reliable behavioral responses. Using new technology that allows us to record from large neural ensembles, we will be able to understand how network (i.e., how neural circuits are organized in the brain) versus intrinsic (i.e., how various components of the single neuron) interact to achieve a tradeoff between selectivity and invariance. The results of this research are expected to further our understanding of basic brain function and could potentially be used to understand how the tradeoff between selectivity and invariance is achieved in higher vertebrates.

当你阅读这篇文章时，你大脑中的神经元使你能够区分构成单词和句子的各种字母，从而形成一个从大脑区域到大脑区域变化的神经表征。当更多外围区域的神经元（例如，你的视网膜）倾向于对感官输入的物理属性（例如，图像的亮度和对比度）做出反应时，更多中枢大脑区域的神经元（例如，你的视觉皮层）倾向于对抽象特征（例如，字母“d”而不是字母“b”）做出更多反应，尽管有明显的相似性（例如，一个是另一个的镜像）。这就是所谓的“反应选择性”，已经在各个系统（视觉、听觉、体感、嗅觉）和从昆虫到人类的各种物种中观察到。与此同时，大脑中心区域的神经元对保持身份的感觉输入转换变得更有容忍度（例如，神经元会对字母“d”做出反应，而不管字母的大小或字体）。这就是所谓的不变性，在系统和物种之间也可以观察到。也许最著名的不变性例子是所谓的“詹妮弗·安妮斯顿”神经元，它对女演员的照片做出反应，而不考虑其他观点（如哈莉·贝瑞）。因此，需要在选择性和不变性之间取得平衡，选择性旨在限制引起神经反应的刺激，而不变性旨在扩大引起神经反应的刺激。这样的平衡对于我们识别环境中的其他人和物体是绝对必要的，从而使我们能够成功地与环境互动。然而，在脊椎动物中，导致选择性和不变性的机制通常知之甚少，而对于如何实现两者之间的平衡则知之甚少。在这里，我建议使用神经记录和使用弱电鱼的电感觉系统的行为方法相结合来研究这些。该模型系统与我们的听觉和视觉系统有许多相似之处，并且具有良好的解剖和电路特征。此外，感官刺激可以很容易地在实验室中被模仿，并将产生可靠的行为反应。使用允许我们记录大型神经系统的新技术，我们将能够理解网络（即，神经回路如何在大脑中组织）与内在（即，单个神经元的各种组件如何相互作用）如何在选择性和不变性之间实现权衡。这项研究的结果有望进一步加深我们对基本脑功能的理解，并有可能用于理解高等脊椎动物是如何在选择性和不变性之间实现权衡的。