Establishment of an optimized and automated workflow for whole brain probing of neuronal activity.

Abstract

Behaviors are encoded by widespread neural circuits within the brain that change with age and experience. Immunodetection of the immediate early gene c-Fos has been successfully used for decades to reveal neural circuits active during specific tasks or conditions. Our objectives here were to develop and benchmark a workflow that circumvents classical temporal and spatial limitations associated with c-Fos quantification. We combined c-Fos immunohistochemistry with c-Fos driven Cre-dependant tdTomato expression in the TRAP2 mice, to visualize and perform a direct comparison of neural circuits activated at different times or during different tasks. By using open-source software (QuPath and ABBA), we established a workflow that optimize and automate cell detection, cell classification (e.g. c-Fos vs. c-Fos/tdTomato) and whole brain registration. We demonstrate that this workflow, based on fully automatic scripts, allows accurate cell number quantification with minimal interindividual variability. Further, interrogation of brain atlases at different scales (from simplified to detailed) allows gradually zooming on brain regions to explore spatial distribution of activated cells. We illustrate the potential of this approach by comparing patterns of neuronal activation in various contexts (two vigilance states, complex behavioral tasks...), in separate groups of mice or at two time points in the same animals. Finally, we explore software (BrainRender) for intuitive representation of the results. Altogether, this automated workflow accessible to all labs with some expertise in histology, allows an unbiased, fast and accurate analysis of the whole brain activity pattern at the cellular level, in various contexts.

Competing Interest Statement

The authors have declared no competing interest.

Footnotes

* two elements have been added : - "provided script" section : link to the github containing all the scripts -"Supplementary information" section and figures : Contains "Extended data figure 1 to 6" and source data allowing production of the figures.

* https://github.com/sebastien-cabrera/Scripts-for-quantification-and-analysis-CABRERA-et-al.