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Modelling the fMRI BOLD signal based on fiber-optic calcium recordings
Understanding better blood flow control in the brain is crucial for more efficient diagnostics and treatments using fMRI. The project aim is to create a model of the fMRI BOLD signal based on different cellular activity measurements, and see witch one correlates better with in vivo data.
Keywords: Neuroscience, data analysis, computational model, fMRI, bioinformatics
MRI is widely used in both clinics and research, however the generation of the fMRI blood oxygen level dependent (BOLD) signal is still unclear and not always directly correlated to neuronal activity. In our lab we are investigating the biological basis of the BOLD signal and neurovascular coupling by studying the contribution of neurons but also astrocytes and other cell types in this process. For the purpose we are using a combination of calcium- based sensors for optical imaging while simultaneously performing fMRI in mice. In order to elucidate this process better, we would like to develop a computational model that would predict the BOLD response shape based solely on calcium data, and compare it with in vivo data. For references see Schulz et al., Nature Methods 2012.
MRI is widely used in both clinics and research, however the generation of the fMRI blood oxygen level dependent (BOLD) signal is still unclear and not always directly correlated to neuronal activity. In our lab we are investigating the biological basis of the BOLD signal and neurovascular coupling by studying the contribution of neurons but also astrocytes and other cell types in this process. For the purpose we are using a combination of calcium- based sensors for optical imaging while simultaneously performing fMRI in mice. In order to elucidate this process better, we would like to develop a computational model that would predict the BOLD response shape based solely on calcium data, and compare it with in vivo data. For references see Schulz et al., Nature Methods 2012.
The student is expected to develop a computational model of the BOLD response based on fluorescence data measurements using Python. A computer sciences background, good statistics and an ability to work independently are required. The project should last approx. 2 months or longer.
The student is expected to develop a computational model of the BOLD response based on fluorescence data measurements using Python. A computer sciences background, good statistics and an ability to work independently are required. The project should last approx. 2 months or longer.
Please send a brief introduction and a CV to: Dr.Zhiva Skachokova, skachokova@biomed.ee.ethz.ch
Please send a brief introduction and a CV to: Dr.Zhiva Skachokova, skachokova@biomed.ee.ethz.ch