Where Top-Down Meets Bottom-Up: Cell-Type Specific Connectivity Map of the Whisker System.

IF 2.7 4区 医学 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
Neuroinformatics Pub Date : 2024-07-01 Epub Date: 2024-05-20 DOI:10.1007/s12021-024-09658-6
Nicolas Rault, Tido Bergmans, Natasja Delfstra, Bisley J Kleijnen, Fleur Zeldenrust, Tansu Celikel
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引用次数: 0

Abstract

Sensorimotor computation integrates bottom-up world state information with top-down knowledge and task goals to form action plans. In the rodent whisker system, a prime model of active sensing, evidence shows neuromodulatory neurotransmitters shape whisker control, affecting whisking frequency and amplitude. Since neuromodulatory neurotransmitters are mostly released from subcortical nuclei and have long-range projections that reach the rest of the central nervous system, mapping the circuits of top-down neuromodulatory control of sensorimotor nuclei will help to systematically address the mechanisms of active sensing. Therefore, we developed a neuroinformatic target discovery pipeline to mine the Allen Institute's Mouse Brain Connectivity Atlas. Using network connectivity analysis, we identified new putative connections along the whisker system and anatomically confirmed the existence of 42 previously unknown monosynaptic connections. Using this data, we updated the sensorimotor connectivity map of the mouse whisker system and developed the first cell-type-specific map of the network. The map includes 157 projections across 18 principal nuclei of the whisker system and neuromodulatory neurotransmitter-releasing. Performing a graph network analysis of this connectome, we identified cell-type specific hubs, sources, and sinks, provided anatomical evidence for monosynaptic inhibitory projections into all stages of the ascending pathway, and showed that neuromodulatory projections improve network-wide connectivity. These results argue that beyond the modulatory chemical contributions to information processing and transfer in the whisker system, the circuit connectivity features of the neuromodulatory networks position them as nodes of sensory and motor integration.

Abstract Image

自上而下与自下而上的结合:胡须系统的细胞类型特异性连接图
感觉运动计算将自下而上的世界状态信息与自上而下的知识和任务目标整合在一起,从而形成行动计划。啮齿动物的胡须系统是主动感知的主要模型,有证据表明神经调节神经递质会影响胡须的控制,影响胡须的频率和振幅。由于神经调节神经递质大多从皮层下核团释放,并有长程投射到达中枢神经系统的其他部分,因此绘制自上而下神经调节控制感觉运动核团的回路图将有助于系统地研究主动感知的机制。因此,我们开发了一个神经信息目标发现管道,以挖掘艾伦研究所的小鼠脑连接图谱。通过网络连通性分析,我们确定了胡须系统的新推定连接,并从解剖学角度证实了 42 个以前未知的单突触连接的存在。利用这些数据,我们更新了小鼠胡须系统的感觉运动连接图谱,并绘制了第一张细胞类型特异性网络图。该图谱包括横跨胡须系统 18 个主要神经核和神经调节神经递质释放的 157 个投射。通过对该连接组进行图网络分析,我们确定了细胞类型特异性枢纽、源和汇,提供了单突触抑制性投射进入上升通路所有阶段的解剖学证据,并表明神经调节性投射改善了整个网络的连接性。这些结果表明,除了胡须系统中信息处理和传递的化学调节贡献外,神经调节网络的电路连接特征也使它们成为感觉和运动整合的节点。
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来源期刊
Neuroinformatics
Neuroinformatics 医学-计算机:跨学科应用
CiteScore
6.00
自引率
6.70%
发文量
54
审稿时长
3 months
期刊介绍: Neuroinformatics publishes original articles and reviews with an emphasis on data structure and software tools related to analysis, modeling, integration, and sharing in all areas of neuroscience research. The editors particularly invite contributions on: (1) Theory and methodology, including discussions on ontologies, modeling approaches, database design, and meta-analyses; (2) Descriptions of developed databases and software tools, and of the methods for their distribution; (3) Relevant experimental results, such as reports accompanie by the release of massive data sets; (4) Computational simulations of models integrating and organizing complex data; and (5) Neuroengineering approaches, including hardware, robotics, and information theory studies.
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