Understanding the organizational principles of the cortex is a fundamental goal of neuroscience. However, due to the complexity of the cortex and the difficulty of obtaining meaningful and precise measurements in vivo, it remains astonishingly hard to describe even fundamental principles of cortical organization.
One important approach to address this issue is to compare and connect findings from different species. Consistent observations across species can help to strengthen a particular hypothesis, and cross-species divergence can help us understand how different cortices – including our own – have evolved and acquired their unique capacities. A major challenge is the translation of findings from animal studies to the human brain because most measurement techniques used in animal research are too invasive to be applied in humans. Magnetic resonance imaging (MRI) is an important exception because it can be used to safely investigate human brain structure and function, and is increasingly applied in small animals such as rodents. Therefore, MRI is a useful tool to bridge findings across different species. Such findings can then be further connected to other, more specific measures that are available in experimental animals.
Recently, several human MRI studies have introduced large-scale spatial gradients derived from resting-state functional connectivity data, as a data-driven representation of the intrinsic organization of the cortex. However, the functional and evolutionary significance of these spatial gradients remains poorly understood. In this project, we used functional connectivity data from resting-state fMRI in mice and derived spatial gradients reflecting the functional organization of the mouse cortex. We then took advantage of the large data resources available for the mouse brain to relate the functional connectivity gradients to the spatial organization of gene expression patterns.
We were initially interested to see whether we could find a relationship between the functional connectivity gradients and a) the distance to different cortical regions such as the evolutionary origins of the cortex, and the primary sensory areas, and b) the expression of genes encoding for neuromodulator receptors, specifically serotonin receptors. We further performed an exploratory analysis into the broader relationship between the functional connectivity gradients and gene expression patterns.
While we could not arrive at any conclusion regarding the gene expression related to neuromodulators, we obtained and published compelling findings about the relationship of functional connectivity gradients to the evolutionary origins of the cortex, to primary sensory regions, and to dominant spatial patterns of overall gene expression.
