Domenic H. Cerri
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Domenic H. Cerri has a total of 5 co-authors. Here are the top co-authors by number of shared publications:
- Li-Ming Hsu
Center for Animal MRI, University of North Carolina at Chapel Hill, Chapel Hill, USA
1 shared publication - Tzu-Hao Harry Chao
Center for Animal MRI, University of North Carolina at Chapel Hill, Chapel Hill, USA
1 shared publication - Tzu-Wen W. Wang
Univ. of North Carolina at Chapel Hill School of Medicine
1 shared publication - Wei-Ting Zhang
Center for Animal MRI, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
1 shared publication - Yen-Yu Ian Shih
Center for Animal MRI, University of North Carolina at Chapel Hill, Chapel Hill, USA
1 shared publication
Latest Publications
- Open Access
- 5 January 2022
- Published by SPIE-Intl Soc Optical Eng in Neurophotonics
- Vol. 9 (03) , 032205-25
Computing hemodynamic response functions from concurrent spectral fiber-photometry and fMRI data
Our interpretation of functional MRI data is built on the assumption that neuronal and vascular responses are tightly coupled.1,2 The process by which changes in local neural activity lead to changes in cerebral blood flow (CBF) and blood volume3 is often termed neurovascular coupling and this relationship can be described mathematically with a hemodynamic response function (HRF). Early fMRI studies typically assigned a single canonical human HRF across brain regions (hereafter as canonical HRF), derived from two gamma functions.4 However, emerging evidence shows that neurovascular coupling can be substantially different between species, brain regions, and physiological conditions.5 – 10 Thus, use of the canonical HRF could lead to inaccurate interpretation of fMRI data, especially in preclinical studies that often utilize anesthetized non-human species. Some recent fMRI studies have adapted to use empirically derived HRFs (hereafter as empirical HRFs), but these current approaches have notable limitations (to be discussed in the next paragraph), and a majority of studies still rely on the canonical HRF.11 – 13 Therefore, the development of techniques to acquire flexible, accessible, brain-region specific HRF is paramount as the number of hemodynamic animal studies continues to grow.
- 5 January 2022
- Published by SPIE-Intl Soc Optical Eng in Neurophotonics
- Vol. 9 (03) , 032205-25
Open AccessComputing hemodynamic response functions from concurrent spectral fiber-photometry and fMRI data
Our interpretation of functional MRI data is built on the assumption that neuronal and vascular responses are tightly coupled.1,2 The process by which changes in local neural activity lead to changes in cerebral blood flow (CBF) and blood volume3 is often termed neurovascular coupling and this relationship can be described mathematically with a hemodynamic response function (HRF). Early fMRI studies typically assigned a single canonical human HRF across brain regions (hereafter as canonical HRF), derived from two gamma functions.4 However, emerging evidence shows that neurovascular coupling can be substantially different between species, brain regions, and physiological conditions.5 – 10 Thus, use of the canonical HRF could lead to inaccurate interpretation of fMRI data, especially in preclinical studies that often utilize anesthetized non-human species. Some recent fMRI studies have adapted to use empirically derived HRFs (hereafter as empirical HRFs), but these current approaches have notable limitations (to be discussed in the next paragraph), and a majority of studies still rely on the canonical HRF.11 – 13 Therefore, the development of techniques to acquire flexible, accessible, brain-region specific HRF is paramount as the number of hemodynamic animal studies continues to grow.