Periodic Reporting for period 1 - LC-FMRI (Deciphering the effects of locus coeruleus activity on whole-brain dynamics and neurovascular coupling)
Período documentado: 2019-09-01 hasta 2021-08-31
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.
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.
We used four different resting-state fMRI data sets acquired in lightly anesthetized mice in order to ensure that our findings are robust across different data sets. For each data set the data from all mice was pooled, preprocessed and subjected to a dimensionality reduction procedure to obtain the functional connectivity gradients. We focused on the six gradients of functional connectivity that explained the majority of variance in the data and were stable across data sets.
We found that the first, or principal, gradient of functional connectivity shows a striking overlap with a spatial axis between two regions that have previously been described as the evolutionary origins of the cortex, the archicortex and the paleocortex (see Figure). Additional gradients reflect sensory specialization as well as a hierarchy from primary sensory regions to areas associated with higher cognitive functions. We believe that these spatial gradients reflect fundamental organizational principles of the mouse cortex, such as a) the evolutionary trajectory of cortical growth from the two origins, and b) the specialization of the cortex to process sensory information and abstract that information in order to inform higher level functions. While some of these gradients strongly resemble observations in the human cortex, the overall pattern in the mouse cortex emphasizes the specialization of areas that process direct sensory input from the environment, over a global functional hierarchy that enables higher level cognition in humans.
We further used the gene expression data provided as part of the Allen Mouse Brain Atlas and related it to the functional connectivity gradients. Due to the insufficient quality of the expression data from individual genes, we could neither confirm nor dismiss our original hypotheses regarding an association of specific functional connectivity gradients with the distribution of neuromodulator receptors. However, we then performed an exploratory analysis in which we pooled all available gene expression data and performed another dimensionality reduction. This approach allowed us to obtain clean and stable maps, reflecting the overall pattern of gene expression across the mouse cortex. We found a strong relationship between these gene expression patterns and the functional connectivity gradients. While it is hard to interpret the expression data after pooling all genes, this finding shows that the gradient organization is consistent across different meaningful descriptors of cortical organization.
The results of this study were published in a peer-reviewed article in Neuroimage and further disseminated via twitter.
We found that the first, or principal, gradient of functional connectivity shows a striking overlap with a spatial axis between two regions that have previously been described as the evolutionary origins of the cortex, the archicortex and the paleocortex (see Figure). Additional gradients reflect sensory specialization as well as a hierarchy from primary sensory regions to areas associated with higher cognitive functions. We believe that these spatial gradients reflect fundamental organizational principles of the mouse cortex, such as a) the evolutionary trajectory of cortical growth from the two origins, and b) the specialization of the cortex to process sensory information and abstract that information in order to inform higher level functions. While some of these gradients strongly resemble observations in the human cortex, the overall pattern in the mouse cortex emphasizes the specialization of areas that process direct sensory input from the environment, over a global functional hierarchy that enables higher level cognition in humans.
We further used the gene expression data provided as part of the Allen Mouse Brain Atlas and related it to the functional connectivity gradients. Due to the insufficient quality of the expression data from individual genes, we could neither confirm nor dismiss our original hypotheses regarding an association of specific functional connectivity gradients with the distribution of neuromodulator receptors. However, we then performed an exploratory analysis in which we pooled all available gene expression data and performed another dimensionality reduction. This approach allowed us to obtain clean and stable maps, reflecting the overall pattern of gene expression across the mouse cortex. We found a strong relationship between these gene expression patterns and the functional connectivity gradients. While it is hard to interpret the expression data after pooling all genes, this finding shows that the gradient organization is consistent across different meaningful descriptors of cortical organization.
The results of this study were published in a peer-reviewed article in Neuroimage and further disseminated via twitter.
The work carried out during this action is the first to describe functional connectivity gradients in the mouse cortex. The obtained findings are important for two major reasons. First, they extend the evidence for an intrinsic cortical organization that can be described in terms of spatial gradients to a new species. This supports the relevance of similar findings obtained in humans. In particular, our findings lend additional credibility for an evolutionary interpretation of such gradients, by a) providing a direct link between one of the dominant spatial gradients and the evolutionary origins of the cortex, and b) introducing the view that the differences between functional gradients observed in humans and mice reflect the functional specialization of each species.
Second, our study links functional connectivity gradients to gene expression as an independent descriptor of cortical organization. Cortical gene expression data is not available in the extent, coverage and quality for the human brain as it is for the mouse brain, underlining the value of bridging findings between species in order to exploit different data sources. The strong association between dominant gene expression patterns and functional connectivity gradients observed in our data provides further evidence that the gradients reflect important aspects of cortical organization, rather than variance specific to fMRI as a measurement technique.
Overall, our work contributes to an emerging body of literature that describes cortical organization in terms of spatial gradients and evolutionary trajectories. While it is just one piece in the puzzle, each such piece brings us closer to understanding the fundamental organizational principles of the cortex. The significance of such understanding can hardly be overstated as the cortex is at once the site of most capacities that we believe to make us distinctly human, and one of the greatest remaining mysteries in the life sciences.
Second, our study links functional connectivity gradients to gene expression as an independent descriptor of cortical organization. Cortical gene expression data is not available in the extent, coverage and quality for the human brain as it is for the mouse brain, underlining the value of bridging findings between species in order to exploit different data sources. The strong association between dominant gene expression patterns and functional connectivity gradients observed in our data provides further evidence that the gradients reflect important aspects of cortical organization, rather than variance specific to fMRI as a measurement technique.
Overall, our work contributes to an emerging body of literature that describes cortical organization in terms of spatial gradients and evolutionary trajectories. While it is just one piece in the puzzle, each such piece brings us closer to understanding the fundamental organizational principles of the cortex. The significance of such understanding can hardly be overstated as the cortex is at once the site of most capacities that we believe to make us distinctly human, and one of the greatest remaining mysteries in the life sciences.