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基于激光散斑对比成像的光激活诱导的脑血流模式。

Cerebral blood flow patterns induced by photoactivation based on laser speckle contrast imaging.

作者信息

Zhu Xuan, Shi Liang, Li Pengcheng, Lu Jinling

机构信息

Britton Chance Center for Biomedical Photonics and MoE Key Laboratory for Biomedical Photonics, Advanced Biomedical Imaging Facility, Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China.

State Key Laboratory of Digital Medical Engineering, Key Laboratory of Biomedical Engineering of Hainan Province, School of Biomedical Engineering, Hainan University, Sanya 572025, China.

出版信息

Biomed Opt Express. 2024 Nov 8;15(12):6739-6755. doi: 10.1364/BOE.541444. eCollection 2024 Dec 1.

Abstract

Neurovascular coupling (NVC) is crucial for maintaining brain function and holds significant implications for diagnosing neurological disorders. However, the neuron type and spatial specificity in NVC remain poorly understood. In this study, we investigated the spatiotemporal characteristics of local cerebral blood flow (CBF) driven by excitatory (VGLUT2) and inhibitory (VGAT) neurons in the mouse sensorimotor cortex. By integrating optogenetics, wavefront modulation technology, and laser speckle contrast imaging (LSCI), we achieved precise, spatially targeted photoactivation of type-specific neurons and real-time CBF monitoring. We observed three distinct CBF response patterns across different locations: unimodal, bimodal, and biphasic. While unimodal and bimodal patterns were observed in different locations for both neuron types, the biphasic pattern was exclusive to inhibitory neurons. Our results reveal the spatiotemporal complexity of NVC across different neuron types and demonstrate our method's ability to analyze this complexity in detail.

摘要

神经血管耦合(NVC)对于维持脑功能至关重要,对神经系统疾病的诊断也具有重要意义。然而,NVC中的神经元类型和空间特异性仍知之甚少。在本研究中,我们研究了小鼠感觉运动皮层中由兴奋性(VGLUT2)和抑制性(VGAT)神经元驱动的局部脑血流(CBF)的时空特征。通过整合光遗传学、波前调制技术和激光散斑对比成像(LSCI),我们实现了对特定类型神经元的精确、空间靶向光激活和实时CBF监测。我们在不同位置观察到三种不同的CBF反应模式:单峰、双峰和双相。虽然两种神经元类型在不同位置均观察到单峰和双峰模式,但双相模式仅见于抑制性神经元。我们的结果揭示了不同神经元类型的NVC的时空复杂性,并证明了我们的方法详细分析这种复杂性的能力。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6b65/11640580/21437a4af870/boe-15-12-6739-g001.jpg

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