Literature DB >> 23020395

A fast neuronal signal-sensitive continuous-wave near-infrared imaging system.

Zhongxing Zhang1, Bailei Sun, Hui Gong, Lei Zhang, Jinyan Sun, Bangde Wang, Qingming Luo.   

Abstract

We have developed a continuous-wave near-infrared imaging system to measure fast neuronal signals. We used a simultaneous sampling method with a separate high-speed analog-to-digital converter for each input channel, which provides a much larger point sample in a digital lock-in algorithm, higher temporal resolution, and lower crosstalk among detected channels. Without any analog filter, digital lock-in detection with a large point sample suppresses noise excellently, making the system less complex and offering better flexibility. In addition, using a custom-made collimator, more photons can reach the brain tissue due to the smaller divergence angle. Performance analysis shows high detection sensitivity (on the order of 0.1 pW) and high temporal resolution (~50 Hz, 48 channels). Simulation experiments show that intensity changes on the order of 0.01% can be resolved by our instrument when averaging over approximately 500 stimuli. In vivo experiments over the motor cortex show that our instrument can detect fast neuronal signals in the human brain.

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Year:  2012        PMID: 23020395     DOI: 10.1063/1.4752021

Source DB:  PubMed          Journal:  Rev Sci Instrum        ISSN: 0034-6748            Impact factor:   1.523


  3 in total

1.  Lock-in-photon-counting-based highly-sensitive and large-dynamic imaging system for continuous-wave diffuse optical tomography.

Authors:  Weiting Chen; Xin Wang; Bingyuan Wang; Yihan Wang; Yanqi Zhang; Huijuan Zhao; Feng Gao
Journal:  Biomed Opt Express       Date:  2016-01-15       Impact factor: 3.732

Review 2.  Frequency-Domain Techniques for Cerebral and Functional Near-Infrared Spectroscopy.

Authors:  Sergio Fantini; Angelo Sassaroli
Journal:  Front Neurosci       Date:  2020-04-07       Impact factor: 4.677

3.  Connectivity properties in the prefrontal cortex during working memory: a near-infrared spectroscopy study.

Authors:  Jinyan Sun; Fang Liu; Haixian Wang; Anping Yang; Chenyang Gao; Zhicong Li; Xiangning Li
Journal:  J Biomed Opt       Date:  2019-03       Impact factor: 3.170

  3 in total

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