Cortical blood flow can be modulated by local activity across a range of species; from barrel-specific blood flow in the rodent somatosensory cortex to the human cortex, where BOLD-fMRI reveals numerous functional borders. However, it appears that the distribution of blood capillaries largely ignores these functional boundaries. Here we report that, by contrast, astrocytes, a major player in blood-flow control, show a striking morphological sensitivity to functional borders. Specifically, we show that astrocyte processes are structurally confined by barrel boundaries in the mouse, by the border of primary auditory cortex in the rat and by layers IIIa/b and Cytochrome Oxidase (CO)-blobs boundaries in the human primary visual cortex. Thus, astrocytes which are critical elements in neuro-hemodynamic coupling show a significant anatomical segregation along functional boundaries across different mammalian species. These results may open a new anatomical marker for delineating functional borders across species, including post-mortem human brains.
Animal experimentation: All the animal experiments were approved by the Institutional Animal Care and Use Committee of the Weizmann Institute. Protocol number 20640915-2.
Human subjects: Right human brain occipital lobe was provided by the Netherlands Brain Bank
- Doris Y Tsao, California Institute of Technology, United States
© 2016, Eilam et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
Mathys et al. conducted the first single-nucleus RNA-seq (snRNA-seq) study of Alzheimer’s disease (AD) (Mathys et al., 2019). With bulk RNA-seq, changes in gene expression across cell types can be lost, potentially masking the differentially expressed genes (DEGs) across different cell types. Through the use of single-cell techniques, the authors benefitted from increased resolution with the potential to uncover cell type-specific DEGs in AD for the first time. However, there were limitations in both their data processing and quality control and their differential expression analysis. Here, we correct these issues and use best-practice approaches to snRNA-seq differential expression, resulting in 549 times fewer DEGs at a false discovery rate of 0.05. Thus, this study highlights the impact of quality control and differential analysis methods on the discovery of disease-associated genes and aims to refocus the AD research field away from spuriously identified genes.
The strength of a fear memory significantly influences whether it drives adaptive or maladaptive behavior in the future. Yet, how mild and strong fear memories differ in underlying biology is not well understood. We hypothesized that this distinction may not be exclusively the result of changes within specific brain regions, but rather the outcome of collective changes in connectivity across multiple regions within the neural network. To test this, rats were fear conditioned in protocols of varying intensities to generate mild or strong memories. Neuronal activation driven by recall was measured using c-fos immunohistochemistry in 12 brain regions implicated in fear learning and memory. The interregional coordinated brain activity was computed and graph-based functional networks were generated to compare how mild and strong fear memories differ at the systems level. Our results show that mild fear recall is supported by a well-connected brain network with small-world properties in which the amygdala is well-positioned to be modulated by other regions. In contrast, this connectivity is disrupted in strong fear memories and the amygdala is isolated from other regions. These findings indicate that the neural systems underlying mild and strong fear memories differ, with implications for understanding and treating disorders of fear dysregulation.