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Revealing neural circuits underlying zebrafish behavior using mesoscopic light field microscopy

Revealing neural circuits underlying zebrafish behavior using mesoscopic light field microscopy
使用介观光场显微镜揭示斑马鱼行为背后的神经回路
批准号:
10300922
负责人:
Oliver Strides Cossairt
金额:
$67.4万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2021
资助国家:
美国
项目状态:
已结题
起止时间:
2021-09-01 至 2024-08-31

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ABSTRACT A critical step towards understanding how neural circuits drive behavior is the ability to record the activity of all neurons in an organism while it interacts with its environment in an unconstrained manner. A promising vertebrate model system in this regard is the zebrafish larva, which performs complex visually-driven behaviors such as hunting from an early age, and due to its transparency allows large-scale neural imaging at single- neuron resolution. However so far most investigations into the neural basis of zebrafish hunting behavior have used tethered fish which are unable to move freely. While some new assays have recently begun to overcome this limitation, these still significantly perturb the fish’s natural hunting behavior by requiring both an extremely shallow water depth, and rapid cancellation of lateral movement in order to maintain the fish within the field of view. Here we will develop a new `MesoLFM’ imaging technology overcoming both of these limitations, thus permitting the neural basis of truly unconstrained hunting behavior to be investigated for the first time in zebrafish. We will achieve this by combining light field microscopy (LFM), an electrically tunable lens (ETL), and the MesoLens, a giant microscope objective with a 4x/0.47 NA objective, a 10 mm working distance and a 5 mm field of view. LFM allows single-shot capture of 3D volumes, enabling imaging at many Hz. The ETL removes the need for rapid stage or objective movements in z, enabling imaging in relatively deep water. The MesoLens allows long sequences of movements to be captured within a single field of view, enabling imaging of hunting without the need for rapid xy motion cancellation. First, we will perform optical simulations of MesoLFM in order to determine the optimal parameters for components such as the microlens array. Second, we will construct the MesoLFM according to these specifications, and calibrate it using measurements of fluorescent beads and a standard resolution target. Third, we will directly demonstrate MesoLFM imaging of the zebrafish brain. Together this work will establish a new platform for investigating the neural bases of unconstrained behavior. In a future R01 application we will use the MesoLFM to reveal how neural circuits drive natural goal-directed behavior and decision-making.
期刊论文(2)
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会议论文
DOI: 10.3389/fncir.2023.1087993
发表时间: 2023
期刊: Frontiers in neural circuits
影响因子: 3.5
作者: []
通讯作者:
DOI: 10.3389/fnins.2023.1127574
发表时间: 2023
期刊: FRONTIERS IN NEUROSCIENCE
影响因子: 4.3
作者: [Hasani, Hamid, Sun, Jipeng, Zhu, Shuyu I., Rong, Qiangzhou, Willomitzer, Florian, Amor, Rumelo, McConnell, Gail, Cossairt, Oliver, Goodhill, Geoffrey J.]
通讯作者: Goodhill, Geoffrey J.
Next-Generation Cardiovascular MRI powered by Artificial Intelligence
  • 批准号:
    10226541
  • 项目类别:
  • 资助金额:
    $18.98万
  • 财政年份:
    2021
  • 负责人:
    Oliver Strides Cossairt
  • 依托单位:
海外基金