用于监测小鼠皮质表面血流动力学的小型无绳点检测器。

IF 3 3区 医学 Q2 BIOCHEMICAL RESEARCH METHODS
Journal of Biomedical Optics Pub Date : 2025-02-01 Epub Date: 2025-03-19 DOI:10.1117/1.JBO.30.S2.S23904
Anupam Bisht, Govind Peringod, Linhui Yu, Ning Cheng, Grant R Gordon, Kartikeya Murari
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引用次数: 0

摘要

意义:过去已经提出了几种用于临床前研究的小型光学神经成像设备,模拟台式仪器。然而,它们通常相对较大、复杂且耗电,限制了它们在自由移动的动物中进行长期测量的可用性。此外,在分析长期信号的算法开发方面的研究有限。目的:我们的目标是开发一种具有成本效益,易于使用的小型化内在光学监测系统(TinyIOMS),该系统可以可靠地用于记录自发和刺激引起的血流动力学变化,并根据血流动力学特征进一步群集脑状态。方法:设计和制作了一种带电池的TinyIOMS (8mm × 13mm × 9mm, 1.2 g)。一个标准的基于摄像机的宽视场系统(WFIOS)被用来验证TinyIOMS信号。接下来,使用TinyIOMS连续记录慢性植入小鼠的刺激诱发活动和自发活动7小时。我们进一步展示了一个动物长达2天的间歇性记录。采用无监督机器学习算法对TinyIOMS信号进行分析。结果:我们观察到TinyIOMS数据与WFIOS数据相当。使用TinyIOMS记录的刺激诱发活动可根据刺激强度进行区分。使用TinyIOMS,我们成功地实现了7小时的连续记录和长达2天的间歇记录,这些记录放置在动物住房设施的家庭笼子中,即在受控的实验室环境之外。使用无监督机器学习算法(k -means聚类),我们观察到将数据分为代表睡眠和清醒状态的两个簇,准确率为91%。然后将相同的算法应用于为期2天的数据集,其中出现了类似的集群。结论:TinyIOMS可用于小鼠长期血流动力学监测。结果表明,该装置适用于与行为视频监控和外部刺激同步进行的自由运动小鼠行为研究中的测量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Tetherless miniaturized point detector device for monitoring cortical surface hemodynamics in mice.

Significance: Several miniaturized optical neuroimaging devices for preclinical studies mimicking benchtop instrumentation have been proposed in the past. However, they are generally relatively large, complex, and power-hungry, limiting their usability for long-term measurements in freely moving animals. Further, there is limited research in the development of algorithms to analyze long-term signals.

Aim: We aim to develop a cost-effective, easy-to-use miniaturized intrinsic optical monitoring system (TinyIOMS) that can be reliably used to record spontaneous and stimulus-evoked hemodynamic changes and further cluster brain states based on hemodynamic features.

Approach: We present the design and fabrication of TinyIOMS ( 8    mm × 13    mm × 9    mm 3 , 1.2 g with battery). A standard camera-based widefield system (WFIOS) is used to validate the TinyIOMS signals. Next, TinyIOMS is used to continuously record stimulus-evoked activity and spontaneous activity for 7 h in chronically implanted mice. We further show up to 2 days of intermittent recording from an animal. An unsupervised machine learning algorithm is used to analyze the TinyIOMS signals.

Results: We observed that the TinyIOMS data is comparable to the WFIOS data. Stimulus-evoked activity recorded using the TinyIOMS was distinguishable based on stimulus magnitude. Using TinyIOMS, we successfully achieved 7 h of continuous recording and up to 2 days of intermittent recording in its home cage placed in the animal housing facility, i.e., outside a controlled lab environment. Using an unsupervised machine learning algorithm ( k -means clustering), we observed the grouping of data into two clusters representing asleep and awake states with an accuracy of 91 % . The same algorithm was then applied to the 2-day-long dataset, where similar clusters emerged.

Conclusions: TinyIOMS can be used for long-term hemodynamic monitoring applications in mice. Results indicate that the device is suitable for measurements in freely moving mice during behavioral studies synchronized with behavioral video monitoring and external stimuli.

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来源期刊
CiteScore
6.40
自引率
5.70%
发文量
263
审稿时长
2 months
期刊介绍: The Journal of Biomedical Optics publishes peer-reviewed papers on the use of modern optical technology for improved health care and biomedical research.
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