Understanding the neuronal mechanisms of closed-loop olfaction

了解闭环嗅觉的神经机制

• 批准号: 10708995
• 负责人: Dinu Florentin ALBEANU
• 金额: $ 55.18万
• 依托单位: COLD SPRING HARBOR LABORATORY
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-09-22 至 2027-07-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10708995
• 关键词: Adaptive Behaviors; Anterior; Attention; Auditory; Auditory area; Behavioral; Brain; Code; Compensation; Coupling; Data; Environment; Esthesia; Face; Feeling; Fiber; Future; Genetic; Head; Head Movements; Individual; Investigation; Knowledge; Label; Laboratories; Lateral; Learning; Link; Location; Maps; Modality; Modeling; Modernization; Monitor; Motor; Movement; Mus; Nature; Neurons; Odors; Olfactory Cortex; Olfactory Pathways; Perception; Photometry; Probability; Process; Pyramidal Cells; Reporting; Rewards; Role; Sampling; Sensory; Shapes; Signal Transduction; Smell Perception; Somatosensory Cortex; Source; Specificity; Stimulus; Techniques; Testing; Update; Vertebrates; Visual; alertness; area striata; cell cortex; cell type; expectation; experience; experimental study; flexibility; genetic signature; insight; light weight; neural; neural circuit; novel; olfactory nuclei; optogenetics; predictive modeling; response; sensory input; somatosensory; tool

Project Summary In nature, sensory perception and motor processing operate in closed-loop. Self-generated movements impact sensory input, and sensory inputs guide future motor commands. Through experience, the brain may learn the reciprocal relationship between sensory inputs and movements in the form of generative sensorimotor models that predict the sensory consequences of upcoming actions. In vertebrates, olfaction is intrinsically linked to motor action through sniffing, and just as for other sensory modalities, via head and body movements. Due to technical challenges, however, most studies in laboratory settings have probed olfactory processing during passive odor sampling. Even when investigating odor-driven navigation, the effect of movements on odor responses has rarely been analyzed. Here we will test the central hypothesis that, in closed-loop olfaction, mice generate olfacto-motor predictions on the sensory consequences of their actions, which further guide odor sampling movements. At the circuit level, we hypothesize that specific olfactory cortex circuits represent olfacto- motor prediction errors, computed by comparing odor input and movement-related predictions of the expected odor input. We plan to test these hypotheses using a novel closed-loop odor localization task (Smellocator) developed in our group, together with a rich repertoire of sensorimotor perturbations, state-of-the-art recordings and cell-type circuit analysis tools with increasing levels of specificity. ● To this end, we will first investigate whether under closed-loop coupling of movements and odor sensing, mice detect olfacto-motor errors, and further compensate for them. In the Smellocator task, head-fixed mice learn to steer a lightweight lever with their paws to control the lateral location of an odor source according to a fixed-gain sensorimotor mapping rule. In catch trials, we will transiently alter the relationship between lever movement and odor displacement via a range of precise, unexpected sensorimotor perturbations. Preliminary data indicate that expert mice successfully compute sensorimotor prediction errors, and quickly engage in fine corrective movements triggered by these perturbations in an individual specific manner. • Then, we will investigate whether the olfactory cortex (piriform vs. anterior olfactory nucleus) represents olfacto- motor prediction errors in face of transient surprises. We will check whether brief sensorimotor perturbations trigger sudden changes in cortical activity (mismatch responses). We will refine our analysis to determine if different semilunar and pyramidal cells types (e.g. Netrin+, Cux1+, Tbr1+, Tle4+) represent primarily sensory inputs vs. olfacto-motor errors by combining distributed recordings and modern genetic labeling strategies. • Finally, we will investigate whether the olfactory cortex enables adaptation in the presence of persistent olfacto- motor errors. We will change the sensorimotor mapping rules in blocks of trials, and across behavioral sessions, and compare the roles of specific cell types in supporting sensorimotor adaptation taking advantage of flexible optogenetic suppression strategies.

项目摘要 在自然界中，感觉知觉和运动处理是在闭合环路中运行的。自产生的运动影响 感觉输入和感觉输入指导着未来的运动指令。通过经验，大脑可能会学习到 以生成性感觉运动模型为形式的感觉输入与运动的相互关系 来预测即将到来的行动的感官后果。在脊椎动物中，嗅觉本质上与 通过嗅觉进行运动，就像其他感官方式一样，通过头部和身体运动。由于 然而，技术挑战，大多数实验室环境下的研究都探索了嗅觉加工过程 被动气味采样。即使在调查气味驱动的导航时，移动对气味的影响 很少有人对这些回应进行分析。在这里，我们将检验中心假设，在闭合嗅觉中， 老鼠对其行为的感官后果产生嗅觉运动预测，从而进一步引导气味 采样动作。在电路水平上，我们假设特定的嗅皮层电路代表事实- 马达预测误差，通过比较气味输入和预期运动相关的预测来计算 气味输入。我们计划使用一种新的闭环气味定位任务(SmelLocator)来测试这些假设 在我们组开发的，连同丰富的感觉运动扰动曲目，最先进的录音 以及细胞类型的电路分析工具，具有越来越高的特异性。 为此，我们将首先调查在运动和气味感觉的闭环耦合下，小鼠 检测实际电机错误，并进一步对其进行补偿。在SmelLocator任务中，头部固定的小鼠学习 用它们的爪子操纵轻量级杠杆，根据固定的增益控制气味源的横向位置 感应器运动映射规则。在渔获试验中，我们将暂时改变杠杆移动和 通过一系列精确的、意想不到的感应器运动扰动进行气味置换。初步数据显示， 专家老鼠成功地计算出感觉运动预测误差，并迅速进行精细校正 由这些扰动以个体特定的方式触发的运动。 ·然后，我们将调查嗅皮层(梨状核与前嗅核)是否代表嗅觉- 面对瞬时意外时的马达预测误差。我们将检查是否存在短暂的感觉运动扰动 触发皮质活动的突然变化(失配反应)。我们将改进我们的分析以确定 不同类型的半月和锥体细胞(如Netrin+、CUX1+、Tbr1+、Tle4+)主要代表感觉 通过结合分布式记录和现代遗传标记策略，将输入与实际运动错误进行比较。 ·最后，我们将研究嗅觉皮质是否能够在持续的嗅觉- 马达故障。我们将在多个试验和跨行为会话中改变感觉运动映射规则， 并比较了特定细胞类型在支持感觉运动适应方面的作用，利用灵活的 光遗传抑制策略。