Biology subjects

Nieman, B. J.

Publications and source records attributed to Nieman, B. J..

3 recordsLinked to original sources

bioRxiv2018

Genetic and behavioural requirements for structural brain plasticity

1Human MRI studies show that experience can lead to changes in the volume of task-specific brain regions; however, the behavioural and molecular processes driving these changes remain poorly understood. Here, we used in-vivo mouse MRI and RNA sequencing to investigate the neuroanatomical and transcriptional changes induced by environmental enrichment, exercise, and social interaction. Additionally, we asked whether the volume changes require CREB, a transcription factor critical for memory formation and neuronal plasticity. Enrichment rapidly increased cortical and hippocampal volume, and these effects were not attributable to exercise or social interaction. Instead, they likely arise from learning and sensorimotor experience. Nevertheless, the volume changes were not attenuated in mice with memory impairments caused by loss of CREB, indicating that these effects are driven by processes distinct from this canonical learning and memory pathway. Finally, within brain regions that underwent volume changes, enrichment increased the expression of genes associated with axonogenesis, dendritic spine development, synapse structural plasticity, and neurogenesis, suggesting these processes underlie the volume changes detected with MRI.

neuroscience↗

bioRxiv2017

Structural covariance of brain region volumes is associated with both structural connectivity and transcriptomic similarity

An organizational pattern seen in the brain, termed structural covariance, is the statistical association of pairs of brain regions in their anatomical properties. These associations, measured across a population as covariances or correlations usually in cortical thickness or volume, are thought to reflect genetic and environmental underpinnings.\n\nHere, we examine the biological basis of structural volume covariance in the mouse brain. We first examined large scale associations between brain region volumes using an atlas-based approach that parcellated the entire mouse brain into 318 regions over which correlations in volume were assessed, for volumes obtained from 153 mouse brain images via high-resolution MRI. We then used a seed-based approach and determined, for 108 different seed regions across the brain and using mouse gene expression and connectivity data from the Allen Institute for Brain Science, the variation in structural covariance data that could be explained by distance to seed, transcriptomic similarity to seed, and connectivity to seed.\n\nWe found that overall, correlations in structure volumes hierarchically clustered into distinct anatomical systems, similar to findings from other studies and similar to other types of networks in the brain, including structural connectivity and transcriptomic similarity networks. Across seeds, this structural covariance was significantly explained by distance (17% of the variation, up to a maximum of 49% for structural covariance to the visceral area of the cortex), transcriptomic similarity (13% of the variation, up to maximum of 28% for structural covariance to the primary visual area) and connectivity (15% of the variation, up to a maximum of 36% for structural covariance to the intermediate reticular nucleus in the medulla) of covarying structures. Together, distance, connectivity, and transcriptomic similarity explained 37% of structural covariance, up to a maximum of 63% for structural covariance to the visceral area. Additionally, this pattern of explained variation differed spatially across the brain, with transcriptomic similarity playing a larger role in the cortex than subcortex, while connectivity explains structural covariance best in parts of the cortex, midbrain, and hindbrain. These results suggest that both gene expression and connectivity underlie structural volume covariance, albeit to different extents depending on brain region, and this relationship is modulated by distance.

neuroscience↗

bioRxiv2017

Mouse MRI shows brain areas larger in males emerge earlier than those larger in females

2Sex differences exist in behaviours, disease and neuropsychiatric disorders. Sexual dimorphisms however, have yet to be studied across the whole brain and across a comprehensive time course of postnatal development. We used manganese-enhanced MRI (MEMRI) to longitudinally image male and female C57BL/6J mice across 9 time points, beginning at postnatal day 3. We recapitulated findings on canonically dimorphic areas, demonstrating the ability of MEMRI to study neuroanatomical sex differences. We discovered, upon whole-brain volume correction, that neuroanatomical regions larger in males develop early in life, while regions larger in females develop in peripubertal life. Furthermore, we found groups of areas with shared sexually dimorphic developmental trajectories that reflect behavioural and functional networks, and expression of genes involved with sex processes. Our results demonstrate the ability of MEMRI to reveal comprehensive developmental differences between male and female brains, which will improve our understanding of sex-specific predispositions to various neuropsychiatric disorders.

neuroscience↗