scholarly journals Structural connectome topology relates to regional BOLD signal dynamics in the mouse brain

2017 ◽  
Vol 27 (4) ◽  
pp. 047405 ◽  
Author(s):  
Sarab S. Sethi ◽  
Valerio Zerbi ◽  
Nicole Wenderoth ◽  
Alex Fornito ◽  
Ben D. Fulcher
Keyword(s):  
Mouse Brain ◽  
Bold Signal ◽  
Structural Connectome

scholarly journals Network analysis of mesoscale mouse brain structural connectome yields modular structure that aligns with anatomical regions and sensory pathways

2019 ◽  
Author(s):  
Bernard A. Pailthorpe
Keyword(s):  
Mouse Brain ◽  
3D Visualization ◽  
Visual Complexity ◽  
Network Models ◽  
Structural Features ◽  
Biologically Relevant ◽  
Sensory Pathways ◽  
Structural Connectome ◽  
Sensory Motor ◽  
Cortical Association Areas

AbstractThe Allen mesoscale mouse brain structural connectome is analysed using standard network methods combined with 3D visualizations. The full region-to-region connectivity data is used, with a focus on the strongest structural links. The spatial embedding of links and time evolution of signalling is incorporated, with two-step links included. Modular decomposition using the Infomap method produces 8 network modules that correspond approximately to major brain anatomical regions and system functions. These modules align with the anterior and posterior primary sensory systems and association areas. 3D visualization of network links is facilitated by using a set of simplified schematic coordinates that reduces visual complexity. Selection of key nodes and links, such as sensory pathways and cortical association areas together reveal structural features of the mouse structural connectome consistent with biological functions in the sensory-motor systems, and selective roles of the anterior and posterior cortical association areas of the mouse brain. Time progression of signals along sensory pathways reveals that close links are to local cortical association areas and cross modal, while longer links provide anterior-posterior coordination and inputs to non cortical regions. The fabric of weaker links generally are longer range with some having brain-wide reach. Cortical gradients are evident along sensory pathways within the structural network.Author’s SummaryNetwork models incorporating spatial embedding and signalling delays are used to investigate the mouse structural connectome. Network models that include time respecting paths are used to trace signaling pathways and reveal separate roles of shorter vs. longer links. Here computational methods work like experimental probes to uncover biologically relevant features. I use the Infomap method, which follows random walks on the network, to decompose the directed, weighted network into 8 modules that align with classical brain anatomical regions and system functions. Primary sensory pathways and cortical association areas are separated into individual modules. Strong, short range links form the sensory-motor paths while weaker links spread brain-wide, possibly coordinating many regions.

scholarly journals Resolution and b value dependent Structural Connectome in ex vivo Mouse Brain

2022 ◽  
Author(s):  
Stephanie Crater ◽  
Surendra Maharjan ◽  
Yi Qi ◽  
Qi Zhao ◽  
Gary Cofer ◽  
...  
Keyword(s):  
Spatial Resolution ◽  
Mouse Brain ◽  
Diffusion Mri ◽  
Angular Resolution ◽  
Ex Vivo ◽  
B Value ◽  
High Angular Resolution ◽  
Preclinical Studies ◽  
High Quality ◽  
Structural Connectome

Diffusion magnetic resonance imaging has been widely used in both clinical and preclinical studies to characterize tissue microstructure and structural connectivity. The diffusion MRI protocol for the Human Connectome Project (HCP) has been developed and optimized to obtain high-quality, high-resolution diffusion MRI (dMRI) datasets. However, such efforts have not been fully explored in preclinical studies, especially for rodents. In this study, high quality dMRI datasets of mouse brains were acquired at 9.4T system from two vendors. In particular, we acquired a high-spatial resolution dMRI dataset (25 um isotropic with 126 diffusion encoding directions), which we believe to be the highest spatial resolution yet obtained; and a high-angular resolution dMRI dataset (50 um isotropic with 384 diffusion encoding directions), which we believe to be the highest angular resolution compared to the dMRI datasets at the microscopic resolution. We systematically investigated the effects of three important parameters that affect the final outcome of the connectome: b value (1000 s/mm2 to 8000 s/mm2), angular resolution (10 to 126), and spatial resolution (25 um to 200 um). The stability of tractography and connectome increase with the angular resolution, where more than 50 angles are necessary to achieve consistent results. The connectome and quantitative parameters derived from graph theory exhibit a linear relationship to the b value (R2 > 0.99); a single-shell acquisition with b value of 3000 s/mm2 shows comparable results to the multi-shell high angular resolution dataset. The dice coefficient decreases and both false positive rate and false negative rate gradually increase with coarser spatial resolution. Our study provides guidelines and foundations for exploration of tradeoffs among acquisition parameters for the structural connectome in ex vivo mouse brain.

Author response for "Hemovasculogenic origin of blood vessels in the developing mouse brain"

2020 ◽  
Author(s):  
Miguel A. Gama Sosa ◽  
Rita De Gasperi ◽  
Gissel M. Perez ◽  
Patrick R. Hof ◽  
Gregory A. Elder
Keyword(s):  
Blood Vessels ◽  
Mouse Brain ◽  
Author Response ◽  
Developing Mouse Brain

Regional Frontal Lobe Response Magnitudes During Affective Shifting Covary With Resting Heart Rate Variability in Healthy Volunteers

2016 ◽  
Vol 30 (4) ◽  
pp. 165-174 ◽  
Author(s):  
Ryan Smith ◽  
John J.B. Allen ◽  
Julian F. Thayer ◽  
Richard D. Lane
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Healthy Subjects ◽  
Emotional Reactivity ◽  
Bold Signal ◽  
Resting Heart Rate ◽  
Functional Magnetic Resonance ◽  
Absolute Value ◽  
Cardiac Vagal Control ◽  
Resting Heart Rate Variability

Abstract. We hypothesized that in healthy subjects differences in resting heart rate variability (rHRV) would be associated with differences in emotional reactivity within the medial visceromotor network (MVN). We also probed whether this MVN-rHRV relationship was diminished in depression. Eleven healthy adults and nine depressed subjects performed the emotional counting stroop task in alternating blocks of emotion and neutral words during functional magnetic resonance imaging (fMRI). The correlation between rHRV outside the scanner and BOLD signal reactivity (absolute value of change between adjacent blocks in the BOLD signal) was examined in specific MVN regions. Significant negative correlations were observed between rHRV and average BOLD shift magnitude (BSM) in several MVN regions in healthy subjects but not depressed subjects. This preliminary report provides novel evidence relating emotional reactivity in MVN regions to rHRV. It also provides preliminary suggestive evidence that depression may involve reduced interaction between the MVN and cardiac vagal control.

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