|ZFIN ID: ZDB-PUB-140815-1|
Hierarchy of Neural Organization in the Embryonic Spinal Cord: Granger-Causality Graph Analysis of Calcium Imaging Data
De Vico Fallani, F., Corazzol, M., Sternberg, J., Wyart, C., Chavez, M.
|Source:||IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society 23(3): 333-41 (Journal)|
|Registered Authors:||Wyart, Claire|
|PubMed:||25122836 Full text @ IEEE Trans Neural Syst Rehabil Eng|
De Vico Fallani, F., Corazzol, M., Sternberg, J., Wyart, C., Chavez, M. (2015) Hierarchy of Neural Organization in the Embryonic Spinal Cord: Granger-Causality Graph Analysis of Calcium Imaging Data. IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society. 23(3):333-41.
ABSTRACTThe recent development of genetically encoded calcium indicators enables monitoring in vivo the activity of neuronal populations. Most analysis of these calcium transients relies on linear regression analysis based on the sensory stimulus applied or the behavior observed. To estimate the basic properties of the functional neural circuitry, we propose a networkbased approach based on calcium imaging recorded at single cell resolution. Differently from previous analysis based on cross-correlation, we used Grangercausality estimates to infer activity propagation between the activities of different neurons. The resulting functional networks were then modeled as directed graphs and characterized in terms of connectivity and node centralities. We applied our approach to calcium transients recorded at low frequency (4 Hz) in ventral neurons of the zebrafish spinal cord at the embryonic stage when spontaneous coiling of the tail occurs. Our analysis on population calcium imaging data revealed a strong ipsilateral connectivity and a characteristic hierarchical organization of the network hubs that supported established propagation of activity from rostral to caudal spinal cord. Our method could be used for detecting functional defects in neuronal circuitry during development and pathological conditions.