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Enabling cellular-resolution connectomic analysis of the primate cortex: Sharing data on cortico-cortical connectivity through an open access web platform

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Majka P., Chan J., Shi B., Wolkowicz I. H., Jermakow N., Rosa M.
Acta Neurobiologiae Experimentalis
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2017
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tom 77
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nr Suppl.1
INTRODUCTION: Processes such as perception, action and cognition are determined by the connectivity between different neuronal groups. Understanding the principles of this network is a core objective of present-day neuroscience. Several animal models are used to investigate this relationship between structure and function, among them marmosets, which recently came to prominence. They are small monkeys (300–400 g) but their brain retains all defining features of the primate brain. AIM(S): The aim is to create a publicly available, the world’s most comprehensive repository of the afferent cortico-cortical connectivity of any primate species, enabling a new level of analysis and modelling. The connectome will be publicly available on‑line making it possible to flexibly access all the data via a graphical front-end or via an application programming interface. METHOD(S): The already available body of data comprises results of over 100 monosynaptic retrograde tracer injections in marmosets. The brains were cut in 40 µm sections. The sections were plotted using an epifluorescence microscope, and stained for Nissl substance. To map individual injections into the atlas space, a previously established pipeline was used. RESULTS: The current version of the portal is available at http://marmoset.braincircuits.org. It allows one to access unprocessed experimental data, mostly injections in dorsal prefrontal cortex, parietal and occipital lobes. Additionally, the locations of individual cells are expressed in atlas-based stereotaxic coordinates which allows one to perform either area-based or parcellation-free connectivity analyses. CONCLUSIONS: The release of open access connectomes is known for triggering numerous follow-up modelling and theoretical studies. In a longer perspective, the unique nature of data in our project will help to understand how the highly complex network of neuronal connections enable brain functions in primates, and, in general, in mammals. FINANCIAL SUPPORT: The project is supported by the Australian Research Council grant (DP140101968) and International Neuroinformatics Coordinating Facility Seed Funding grant.
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Whole-brain mapping of neuroplasticity in different experimental paradigms in mice - a computational perspective

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Bednarek S., Jermakow N., Stefaniuk M., Pawlowska M., Wojcik D. K., Majka P.
Acta Neurobiologiae Experimentalis
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2019
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tom 79
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nr Suppl.1
INTRODUCTION: Imaging of entire brains at cellular resolution, enabled by light-sheet fluorescence microscopy (LSFM) and optical tissue clearing, offers insights into neural activity at a high magnification while preserving the brain‑wide context. AIM(S): We propose a set of open-source computational tools that address three fundamental challenges associated with the analysis of LSFM images of entire rodent brains, namely: management of voluminous imaging data, alignment to a reference atlas, and object detection and localization. METHOD(S): The data for each brain, such as multichannel acquisitions and spatial information, are compressed and stored in an HDF5-based container as a pyramid of resolutions to facilitate and standardize data access and manipulation. Unlike most other alignment approaches, our pipeline is not only guided by standard similarity metrics such as mutual information, but also utilizes Deep Convolutional Neural Networks to generate label maps corresponding to specific brain structures such as main white matter tracts or dentate gyrus. This step significantly increases the accuracy and robustness of the registration procedure. The c‑Fos‑positive nuclei are identified and quantified with the help of another neural network trained on synthetic data, generated to simulate the original nuclei which eliminated the laborious process of manual image annotation. The software was applied to investigate c-Fos-mediated neuroplasticity in iDISCO-cleared brains in experimental paradigms of appetitive and aversive learning and alcohol addiction. RESULTS: Voxel-wise statistical analysis revealed brain areas involved in the neuroplasticity of alcohol addiction and appetitive or aversive learning in mice. CONCLUSIONS: We demonstrate the ability of our software to combine efficient data management, accurate atlas alignment, and object detection to facilitate LSFM analyses. FINANCIAL SUPPORT: ERA‑NET NEURON/17/2017 grant from NCBR, G2631 grant from NCN.
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