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.

当动物在其环境中航行时，它们的神经系统在多种 影响感觉信息如何处理以及行为如何生成的内部状态。这些 唤醒、动机和情绪的状态通常会持续很长时间，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。尽管大多数动物都有组织 他们以这种类似状态的方式进行行为输出，这些神经机制是产生这些行为的基础 人们对国家知之甚少。解释内部状态如何产生的一种流行假设 表明快速时间尺度的神经动力学，它是每时每刻的行为变化的基础，可能会 通过上行通路（尤其是神经调节系统）在较慢的时间尺度上进行控制。 事实上，产生神经调节剂的神经元的小而明确的子集可以引发内部状态转换 许多动物。此外，最近的人口水平神经活动记录表明，内部 状态伴随着许多大脑区域的广泛、分布式的活动变化。 值得注意的是，最近的研究还表明，细粒度的、每时每刻的运动动作都反映在 许多大脑区域的神经活动。这引发了一种观点，即感觉信号、细粒度行为 信号和内部状态信号在大多数大脑回路中同时出现。然而，人口水平的活动如何 对一组不同的行为参数进行编码，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尚不清楚。在此，我们建议解决这个问题 线虫秀丽隐杆线虫，其晶体神经系统，明确的运动程序集和遗传 易处理性应该使得建立神经活动如何编码行为的完整模型成为可能 不同的状态。该提案建立在新的初步数据的基础上。首先，我们开发了一个新的录音平台 能够对自由移动的线虫进行全脑钙成像，同时对 动物的不同运动程序。我们还建立了将神经活动与 行为具有高精度。令人惊讶的是，这表明许多秀丽隐杆线虫神经元编码 多个正在进行的运动程序和这些编码会随着时间的推移而灵活地改变。此外，我们还有 开发了两种行为范式，我们可以在其中引发强烈的、刻板的厌恶的内部状态 在几分钟（目标 1）或几小时（目标 2）的时间尺度上展开。我们现在建议破译如何 秀丽隐杆线虫大脑中的每个神经元都编码精确的行为特征，从而创建了一个关于如何进行行为的地图集 行为是通过神经系统编码的。然后我们将确定持续多分钟或几小时 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， 连同我们将建立的计算模型，将产生对内部状态的清晰理解 该动物的结构并揭示了指导许多动物模型未来研究的基本原理。