| Autor: |
Jing Li, Fan Yang, Kathleen Zhang, Shiqiang Wu, James Niemeyer, Mingrui Zhao, Peijuan Luo, Nan Li, Rongxin Li, Dan Li, Weihong Lin, Jyun-you Liou, Theodore H. Schwartz, Hongtao Ma |
| Jazyk: |
angličtina |
| Rok vydání: |
2024 |
| Předmět: |
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| Zdroj: |
NeuroImage, Vol 299, Iss , Pp 120816- (2024) |
| Druh dokumentu: |
article |
| ISSN: |
1095-9572 |
| DOI: |
10.1016/j.neuroimage.2024.120816 |
| Popis: |
Accurate interpretation of in vivo wide-field fluorescent imaging (WFFI) data requires precise separation of raw fluorescence signals into neural and hemodynamic components. The classical Beer-Lambert law-based approach, which uses concurrent 530-nm illumination to estimate relative changes in cerebral blood volume (CBV), fails to account for the scattering and reflection of 530-nm photons from non-neuronal components leading to biased estimates of CBV changes and subsequent misrepresentation of neural activity. This study introduces a novel linear regression approach designed to overcome this limitation. This correction provides a more reliable representation of CBV changes and neural activity in fluorescence data. Our method is validated across multiple datasets, demonstrating its superiority over the classical approach. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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Full Text from ScienceDirect