Predictive coding impairment in mouse models of autistic spectrum disorders

自闭症谱系障碍小鼠模型中的预测编码障碍

• 批准号: 2605098
• 金额: --
• 依托单位: University of Edinburgh
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2021
• 资助国家: 英国
• 起止时间: 2021 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2605098
• 关键词: Predictive; coding; impairment; mouse; models

Theoretical work and psychophysical studies have led to the hypothesis that autism phenotypes may be manifestations of an underlying impairment in predictive abilities. Within this theoretical framework, autism is characterized by a greater weighting of sensory information in updating internal representations of the environment. With compromised prediction skills, an individual with autism faces an environment in which events occur unexpectedly and without cause. Therefore, an insistence on sameness or stereotyped and repetitive behaviours can be seen as attempts to provide a reassuring sense of a predictable environment in a world otherwise filled with unexpected changes. Testing the hypothesis of predictive coding requires an experimental design in which predictions are constrained experimentally. One possibility is to use learned associations between behaviour and sensory feedback. For example, sensory feedback couples in a predictable way to motor output. Hence, the experimental assumption is that signals generated during movement that are fed back to sensory areas should constitute an experience-dependent prediction of sensory feedback. Recent studies in the mouse primary visual cortex (V1) have tested whether top-down projections to V1 carry a prediction of visual input based on motor output. Using a virtual reality environment combined with two- photon calcium imaging, these experiments have identified a neuronal circuit for visual flow predictions between the cortical area Anterior Cingulate Cortex (ACC) and V1 (Leinweber et al., 2017). Aims The aim of this project is to test whether visual flow predictions are disrupted in the primary visual cortex of mouse models of ASDs. We plan to use mouse models of fragile X syndrome (Fmr1 -/y ), and SYNGAP happloinsufficiency (Syngap1 +/- ), as two well established models to determine how these mutations affect the propagation of neural activity through cortical networks, focussing on sensory areas where inputs are readily controllable. Specifically, the project is organized around 3 aims: Aim 1: To characterize movement-related activity of ACC axons in V1 of mouse models of fragile X syndrome (Fmr1 -/y ), and SYNGAP happloinsufficiency (Syngap1 +/- ). Aim 2: To establish the contribution of measured top-down inputs to V1 activity through the development of a computational model of the V1 circuit. Aim 3. To test pharmacological treatments that rescue cortical dysfunction in Fmr1 -/y and Syngap1 +/- mice.ReferencesLeinweber, Marcus, Daniel R. Ward, Jan M. Sobczak, Alexander Attinger, and Georg B. Keller. 2017. "A Sensorimotor Circuit in Mouse Cortex for Visual Flow Predictions." Neuron 95 (6): 1420-1432.e5. 2017.

理论工作和心理物理学研究得出这样的假设：自闭症表型可能是预测能力潜在障碍的表现。在这个理论框架内，自闭症的特点是在更新环境的内部表征时感觉信息的权重更大。由于预测能力受损，自闭症患者面临着事件意外无缘无故发生的环境。因此，坚持千篇一律或刻板和重复的行为可以被视为试图在一个充满意外变化的世界中提供一种可预测环境的令人安心的感觉。测试预测编码的假设需要实验设计，其中预测受到实验限制。一种可能性是利用行为和感觉反馈之间习得的关联。例如，感觉反馈以可预测的方式耦合到电机输出。因此，实验假设是，运动过程中产生的反馈到感觉区域的信号应构成感觉反馈的依赖于经验的预测。最近对小鼠初级视觉皮层 (V1) 的研究测试了对 V1 的自上而下投影是否可以预测基于运动输出的视觉输入。这些实验利用虚拟现实环境与双光子钙成像相结合，确定了皮质区域前扣带皮层 (ACC) 和 V1 之间用于视觉流预测的神经元回路（Leinweber 等人，2017）。目的 该项目的目的是测试 ASD 小鼠模型的初级视觉皮层中的视觉流预测是否受到干扰。我们计划使用脆性 X 综合征 (Fmr1 -/y ) 和 SYNGAP happloinsufficiency (Syngap1 +/- ) 的小鼠模型，作为两个成熟的模型来确定这些突变如何影响神经活动通过皮层网络的传播，重点关注输入易于控制的感觉区域。具体来说，该项目围绕 3 个目标进行组织： 目标 1：表征脆性 X 综合征 (Fmr1 -/y ) 和 SYNGAP happloinsufficiency (Syngap1 +/- ) 小鼠模型 V1 中 ACC 轴突的运动相关活动。 目标 2：通过开发 V1 电路的计算模型，确定测量的自上而下输入对 V1 活动的贡献。目标 3. 测试挽救 Fmr1 -/y 和 Syngap1 +/- 小鼠皮质功能障碍的药物治疗。参考文献Leinweber、Marcus、Daniel R. Ward、Jan M. Sobczak、Alexander Attinger 和 Georg B. Keller。 2017.“小鼠皮层中用于视觉流预测的感觉运动电路。”神经元 95 (6)：1420-1432.e5。 2017年。