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，闭环的感觉感知和运动处理操作。自我生成的运动影响 感觉输入和感觉输入指导未来电动机命令。通过经验，大脑可能会学习 感官输入与运动形式的相互关系，以通用感官模型的形式 这预测了即将采取的行动的感官后果。在脊椎动物中，嗅觉与 通过嗅探和其他感觉方式通过头部和身体运动进行运动。由于 然而，技术挑战，实验室环境中的大多数研究都探讨了嗅觉处理 被动气味采样。即使研究气味驱动导航，运动对气味的影响 响应很少被分析。在这里，我们将测试中心假设，即在闭环嗅觉中， 小鼠对其动作的感觉后果产生olfacto运动预测，这进一步指导了otor 采样运动。在电路级别，我们假设特定的嗅觉皮层电路代表olfacto- 电机预测错误，通过比较预期的气味输入和与运动相关的预测计算 气味输入。我们计划使用新型的闭环气味定位任务（气味）来检验这些假设 在我们的小组中开发，以及最先进的录音的感官摄动的丰富曲目 和细胞类型电路分析工具的特异性水平提高。 ●为此，我们将首先调查运动和气味敏感性的闭环耦合，小鼠 检测Olfacto-Motor错误，并进一步补偿它们。在嗅觉器任务中，固定的老鼠学会 根据固定增益，用爪子转向轻巧的杠杆以控制气味源的横向位置 感觉运动映射规则。在捕捉试验中，我们将暂时改变杠杆运动与 气味通过一系列精确的，意外的感觉运动扰动。初步数据表明 专家小鼠成功计算感觉运动预测错误，并迅速进行纠正效果 这些扰动以各个特定方式触发的运动。 •然后，我们将研究嗅觉皮质（梨状和前嗅觉核）是否代表olfacto- 面对瞬态惊喜的运动预测错误。我们将检查是否简短的感觉运动扰动 触发皮质活性突然变化（不匹配反应）。我们将完善我们的分析以确定是否 不同的半图和锥体细胞类型（例如Netrin+，Cux1+，TBR1+，TLE4+）代表主要感觉 通过组合分布式记录和现代遗传标记策略，输入与olfacto-Motor错误。 •最后，我们将研究嗅觉的皮质是否可以在存在持续的olfacto-存在下适应 电机错误。我们将在试验块和行为会议中更改感觉运动映射规则， 并比较特定细胞类型在支持感觉运动适应中的作用 光遗传学抑制策略。