Whole mouse brain connectomics

Abstract

Methods have been developed to allow quantitative connectivity of the whole fixed mouse brain by means of magnetic resonance imaging (MRI). We have translated what we have learned in clinical imaging to the very special domain of the mouse brain. Diffusion tensor imaging (DTI) of perfusion fixed specimens can now be performed with spatial resolution of 45 μm 3 , that is, voxels that are 21,000 times smaller than the human connectome protocol. Specimen preparation has been optimized through an active staining protocol using a Gd chelate. Compressed sensing has been integrated into high performance reconstruction and post processing pipelines allowing acquisition of a whole mouse brain connectome in <12 hr. The methods have been validated against retroviral tracer studies. False positive tracts, which are especially problematic in clinical studies, have been reduced substantially to~28%. The methods have been streamlined to provide high-fidelity, whole mouse brain connectomes as a routine study. The data package provides holistic insight into the mouse brain with anatomic definition at the meso-scale, quantitative volumes of subfields, scalar DTI metrics, and quantitative tractography. K E Y W O R D SConnectomes, mouse brain, MR histology, MRI

Diffusion Tensor Imaging-Based Studies at the Group-Level Applied to Animal Models of Neurodegenerative Diseases

“…DTI-based connectomics have already been applied to mouse models of genetic risk factors for late onset AD for identifying vulnerable brain networks (Badea et al, 2019 ). Whole mouse brain structural connectomics (Shibata et al, 2015 ; Allan Johnson et al, 2019 ) have already been verified by neuron tracing data (Chen et al, 2015 ; Sinke et al, 2018 ; Wang et al, 2018 ).…”

“…There is a growing number of large-scale connectomes for preclinical models obtained with DTI ex vivo (Nouls et al, 2018 ; Allan Johnson et al, 2019 ) and increasingly in vivo (Gimenez et al, 2017 ; Haber et al, 2017 ; Müller et al, 2019 ). At the same time, single-neuron resolution connectomes are being obtained for the whole mouse brain (Ho et al, 2014 ) or for individual structures (e.g., Commisso et al, 2018 ) using viral tracing tools and optical imaging.…”

“…Therefore, it is anticipated that further improvement of the technology, using machine-learning approaches that can use optical counterparts as “gold standard,” will result in improvement in tracing, in particular in terms of reduced false positives (Maier-Hein et al, 2017 ). Of note, the resolution of the DTI-MRI datasets for murine models is progressively increasing, thanks to the adoption of ultra-high-field, ex-vivo acquisition (Allan Johnson et al, 2019 ). On the other hand, the acquisition of whole-brain optical images in cleared specimens (Ueda et al, 2020 ), which are going to have the same overall format of MRI images in terms of explored volume and reference points (and therefore could be normalized to standardized templates), may be anticipated to make for easier and faster integration with DTI-MRI.…”

Heritability of the Mouse Brain Connectome

“…Calamante et al have developed higher resolution tract density methods for connectomics in post mortem specimens at 100 um3 with 30 angular samples [25]. To enable comparison across the range of applications (human, mouse, in vivo, post mortem), we proposed the resolution index (RI), i.e., the product of the spatial and angular resolution [14]. RI for the human connectome was 128 [12].…”

“…Errors in tractography that result from crossing and merging fibers can result in substantial false positive connections. We have addressed many of these technical challenges by developing improved MRI protocols and unique hardware and encoding methods [13,14]. We have validated and streamlined methods [9,13] that enable the required high throughput for quantitative genetic studies of large murine cohorts [13,14].…”