Brain-wide representations of behavior during aversive internal states in C. elegans

线虫厌恶的内部状态下的全脑行为表征

• 批准号: 10638999
• 负责人: Steven Willem Flavell
• 金额: $ 38.1万
• 依托单位: MASSACHUSETTS INSTITUTE OF TECHNOLOGY
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-03-01 至 2028-02-29
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10638999
• 关键词: Animal Model; Animals; Arousal; Atlases; Behavior; Behavioral; Behavioral Paradigm; Brain; Brain region; Caenorhabditis elegans; Calcium; Cells; Complex; Computer Models; Cues; Data; Data Set; Eating; Environment; Generations; Genetic; Goals; Hour; Image; Infection; Modality; Modeling; Moods; Motivation; Motor; Motor output; Nematoda; Nervous System; Neuromodulator; Neurons; Output; Pathway interactions; Population; Process; Role; Sensory; Signal Transduction; Stereotyping; Stimulus; Structure; System; Time; Work; behavior influence; flexibility; imaging approach; insight; neural; neural circuit; neural correlate; neural model; neuromechanism; neuroregulation; pathogen; pathogenic bacteria; programs; tool; virtual

As animals navigate their environments, their nervous systems transition between a wide range of internal states that influence how sensory information is processed and how behaviors are generated. These states of arousal, motivation, and mood typically persist for long durations of time, from minutes to hours, and exert widespread effects across multiple sensory modalities and motor systems. Although most animals organize their behavioral outputs in this state-like fashion, the neural mechanisms that underlie the generation of these states are poorly understood. One prevailing hypothesis to explain how internal states are generated suggests that fast timescale neural dynamics, which underlie moment-by-moment behavioral changes, might be controlled over slower timescales by ascending pathways, most notably the neuromodulatory systems. Indeed, small, defined subsets of neuromodulator-producing neurons can elicit internal state transitions in many animals. Moreover, recent population-level recordings of neural activity have revealed that internal states are accompanied by widespread, distributed changes in activity across many brain regions. Remarkably, recent work has also shown that granular, moment-by-moment motor actions are reflected in neural activity across many brain regions. This gives rise to a view that sensory signals, granular behavioral signals, and internal state signals all co-occur in most brain circuits. However, how population-level activity encodes a diverse set of behavioral parameters and how this encoding is influenced by internal states to give rise to state-dependent behavioral changes is unknown. Here, we propose to tackle this problem in the nematode C. elegans, whose crystalline nervous system, well-defined set of motor programs, and genetic tractability should make it possible to build complete models of how neural activity encodes behavior across distinct states. This proposal builds off new preliminary data. First, we developed a new recording platform that enables brain-wide calcium imaging of freely-moving C. elegans with simultaneous quantification of the diverse motor programs of the animal. We also built computational models that relate neural activity to behavior with a high degree of precision. Surprisingly, this reveals that many C. elegans neurons encode multiple ongoing motor programs and these encodings flexibly change over time. Moreover, we have developed two behavioral paradigms in which we can elicit robust, stereotyped aversive internal states that unfold over either minutes-long (Aim 1) or hours-long (Aim 2) timescales. We now propose to decipher how each neuron across the C. elegans brain encodes precise behavioral features, creating an atlas of how behaviors are encoded across the nervous system. We will then determine how minutes- or hours-long internal states modulate neural activity across the brain. The comprehensive datasets that we will generate, along with the computational models that we will build, will give rise to a clear understanding of internal state structure in this animal and reveal basic principles that should guide future research in many animal models.

当动物在它们的环境中航行时，它们的神经系统在各种各样的神经元之间转换。 影响感官信息处理和行为产生的内部状态。这些 觉醒、动机和情绪状态通常会持续很长一段时间，从几分钟到几小时，并且 对多种感觉方式和运动系统产生广泛的影响。虽然大多数动物组织起来 他们的行为输出在这种状态一样的方式，神经机制的基础，这些产生 各国都不太了解。解释内部状态如何产生的一个流行假设 这表明，快速时间尺度的神经动力学，这是每时每刻的行为变化的基础，可能 在较慢的时间尺度上由上行通路控制，最明显的是神经调节系统。 事实上，产生神经调节剂的神经元的小的、确定的子集可以引起神经元的内部状态转换。 许多动物。此外，最近的群体水平的神经活动记录显示，内部 状态伴随着许多大脑区域的广泛分布的活动变化。 值得注意的是，最近的研究还表明，颗粒状的，每时每刻的运动动作反映在 神经活动在许多大脑区域。这就产生了一种观点，即感官信号，颗粒行为 信号和内部状态信号在大多数大脑回路中都同时出现。然而，人口水平的活动 编码一组不同的行为参数，以及这种编码如何受到内部状态的影响， 引起依赖于状态的行为变化是未知的。在此，我们建议在 线虫C.优雅，其水晶神经系统，定义明确的运动程序集，和遗传 易处理性应该使我们有可能建立一个完整的模型，来研究神经活动是如何编码行为的。 不同的国家。这一建议建立在新的初步数据基础上。首先，我们开发了一个新的记录平台 能够对自由移动的C进行全脑钙成像与同时定量的 动物的各种运动程序。我们还建立了计算模型，将神经活动与 行为具有高度的精确性。令人惊讶的是，这表明许多C。线虫神经元编码 多个正在进行的运动程序，并且这些编码随时间灵活地改变。而且我们 发展了两种行为模式，我们可以从中引出强大的，刻板的厌恶性内部状态， 在几分钟（目标1）或几小时（目标2）的时间尺度上展开。我们现在提议破译如何 跨C的每个神经元。elegans大脑编码精确的行为特征，创建一个地图集， 行为是通过神经系统编码的。然后我们将确定几分钟或几小时长的 内部状态调节整个大脑的神经活动。我们将生成的综合数据集， 沿着我们将要建立的计算模型，将使我们对内部状态有一个清晰的理解 结构，并揭示了应该指导许多动物模型未来研究的基本原则。