BrainLine: An Open Pipeline for Connectivity Analysis of Heterogeneous Whole-Brain Fluorescence Volumes

Thomas L Athey; Matthew A Wright; Marija Pavlovic; Vikram Chandrashekhar; Karl Deisseroth; Michael I Miller; Joshua T Vogelstein

doi:10.1101/2023.02.28.530429

BrainLine: An Open Pipeline for Connectivity Analysis of Heterogeneous Whole-Brain Fluorescence Volumes

bioRxiv [Preprint]. 2023 Mar 1:2023.02.28.530429. doi: 10.1101/2023.02.28.530429.

Authors

Thomas L Athey^{1

2}, Matthew A Wright³, Marija Pavlovic⁴, Vikram Chandrashekhar¹, Karl Deisseroth^{4

5

6

7}, Michael I Miller^{1

2

8

9}, Joshua T Vogelstein^{1

2

8

9}

Affiliations

¹ Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA.
² Institute of Computational Medicine, Johns Hopkins University, Baltimore, MD, USA.
³ Department of Psychiatry, Weill Cornell Medicine, New York, NY, USA.
⁴ Department of Bioengineering, Stanford University, Stanford, CA, USA.
⁵ CNC Program, Stanford University, Stanford, CA, USA.
⁶ Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA.
⁷ Howard Hughes Medical Institute, Stanford University, Stanford, CA, USA.
⁸ Center for Imaging Science, Johns Hopkins University, Baltimore, MD, USA.
⁹ Kavli Neuroscience Discovery Institute, Johns Hopkins University, Baltimore, MD, USA.

Abstract

Whole-brain fluorescence images require several stages of computational processing to fully reveal the neuron morphology and connectivity information they contain. However, these computational tools are rarely part of an integrated pipeline. Here we present BrainLine, an open-source pipeline that interfaces with existing software to provide registration, axon segmentation, soma detection, visualization and analysis of results. By implementing a feedback based training paradigm with BrainLine, we were able to use a single learning algorithm to accurately process a diverse set of whole-brain images generated by light-sheet microscopy. BrainLine is available as part of our Python package brainlit: http://brainlit.neurodata.io/ .

Publication types

Preprint

Abstract

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