scholarly journals Dissect Relationships Between Gene Co-expression and Functional Connectivity in Human Brain

2021 ◽  
Vol 15 ◽  
Author(s):  
Xue Zhang ◽  
Yingying Xie ◽  
Jie Tang ◽  
Wen Qin ◽  
Feng Liu ◽  
...  
Keyword(s):  
Gene Expression ◽  
Functional Connectivity ◽  
Human Brain ◽  
Functional Networks ◽  
Expression Data ◽  
Biological Functions ◽  
Functional Connections ◽  
Postmortem Brains ◽  
Specific Association ◽  
Cortical Regions

Although recent evidence indicates an association between gene co-expression and functional connectivity in human brain, specific association patterns remain largely unknown. Here, using neuroimaging-based functional connectivity data of living brains and brain-wide gene expression data of postmortem brains, we performed comprehensive analyses to dissect relationships between gene co-expression and functional connectivity. We identified 125 connectivity-related genes (20 novel genes) enriched for dendrite extension, signaling pathway and schizophrenia, and 179 gene-related functional connections mainly connecting intra-network regions, especially homologous cortical regions. In addition, 51 genes were associated with connectivity in all brain functional networks and enriched for action potential and schizophrenia; in contrast, 51 genes showed network-specific modulatory effects and enriched for ion transportation. These results indicate that functional connectivity is unequally affected by gene expression, and connectivity-related genes with different biological functions are involved in connectivity modulation of different networks.

scholarly journals recount-brain: a curated repository of human brain RNA-seq datasets metadata

2019 ◽  
Author(s):  
Ashkaun Razmara ◽  
Shannon E. Ellis ◽  
Dustin J. Sokolowski ◽  
Sean Davis ◽  
Michael D. Wilson ◽  
...  
Keyword(s):  
Gene Expression ◽  
Human Brain ◽  
Gene Expression Data ◽  
Differential Expression Analysis ◽  
Controlled Vocabulary ◽  
The Cancer Genome Atlas ◽  
Tissue Type ◽  
Expression Data ◽  
Rna Seq ◽  
Human Brain Tissue

AbstractThe usability of publicly-available gene expression data is often limited by the availability of high-quality, standardized biological phenotype and experimental condition information (“metadata”). We released the recount2 project, which involved re-processing ∼70,000 samples in the Sequencing Read Archive (SRA), Genotype-Tissue Expression (GTEx), and The Cancer Genome Atlas (TCGA) projects. While samples from the latter two projects are well-characterized with extensive metadata, the ∼50,000 RNA-seq samples from SRA in recount2 are inconsistently annotated with metadata. Tissue type, sex, and library type can be estimated from the RNA sequencing (RNA-seq) data itself. However, more detailed and harder to predict metadata, like age and diagnosis, must ideally be provided by labs that deposit the data.To facilitate more analyses within human brain tissue data, we have complemented phenotype predictions by manually constructing a uniformly-curated database of public RNA-seq samples present in SRA and recount2. We describe the reproducible curation process for constructing recount-brain that involves systematic review of the primary manuscript, which can serve as a guide to annotate other studies and tissues. We further expanded recount-brain by merging it with GTEx and TCGA brain samples as well as linking to controlled vocabulary terms for tissue, Brodmann area and disease. Furthermore, we illustrate how to integrate the sample metadata in recount-brain with the gene expression data in recount2 to perform differential expression analysis. We then provide three analysis examples involving modeling postmortem interval, glioblastoma, and meta-analyses across GTEx and TCGA. Overall, recount-brain facilitates expression analyses and improves their reproducibility as individual researchers do not have to manually curate the sample metadata. recount-brain is available via the add_metadata() function from the recount Bioconductor package at bioconductor.org/packages/recount.

scholarly journals Functional segregation of the human basal forebrain using resting state neuroimaging

2017 ◽  
Author(s):  
Ross D. Markello ◽  
R. Nathan Spreng ◽  
Wen-Ming Luh ◽  
Adam K. Anderson ◽  
Eve De Rosa
Keyword(s):  
Functional Connectivity ◽  
Resting State ◽  
Basal Forebrain ◽  
Nucleus Basalis ◽  
Functional Networks ◽  
List Type ◽  
Functional Connections ◽  
Diagonal Band ◽  
Hippocampal Complex

AbstractThe basal forebrain (BF) is poised to play an important neuromodulatory role in brain re-gions important to cognition due to its broad projections and complex neurochemistry. While significant in vivo work has been done to elaborate BF function in nonhuman rodents and primates, comparatively limited work has examined the in vivo function of the human BF. In the current study we used multi-echo resting state functional magnetic resonance imaging (rs-fMRI) from 100 young adults (18-34 years) to assess the potential segregation of human BF nuclei as well as their associated projections. Bottom-up clustering of voxel-wise functional connectivity maps yielded adjacent functional clusters within the BF that closely aligned with the distinct, hypothesized nuclei important to cognition: the nucleus basalis of Meynert (NBM) and the me-dial septum/diagonal band of Broca (MS/DB). Examining their separate functional connections, the NBM and MS/DB revealed distinct projection patterns, suggesting a conservation of nuclei-specific functional connectivity with homologous regions known to be anatomically innervated by the BF. Specifically, the NBM demonstrated coupling with a widespread cortical network as well as the amygdala, whereas the MS/DB revealed coupling with a more circumscribed net-work, including the orbitofrontal cortex and hippocampal complex. Collectively, these in vivo rs-fMRI data demonstrate that the human BF nuclei support functional networks distinct as-pects of resting-state functional networks, suggesting the human BF may be a neuromodulatory hub important for orchestrating network dynamics.HighlightsThe basal forebrain NBM and the MS/DB support two distinct functional networksFunctional networks closely overlap with known anatomical basal forebrainBasal forebrain networks are distinct from known resting-state functional networks

scholarly journals The Role of the Human Brain Neuron-Glia-Synaptic Composition in Forming Resting State Functional Connectivity Networks

2021 ◽  
Author(s):  
Sayan Kahali ◽  
Marcus E Raichle ◽  
Dmitriy A Yablonskiy
Keyword(s):  
Functional Connectivity ◽  
Human Brain ◽  
Resting State ◽  
Functional Networks ◽  
Bold Signal ◽  
Neuronal Density ◽  
Functional Relationships ◽  
Wide Range ◽  
Functional Units ◽  
The Brain

While significant progress has been achieved in studying resting state functional networks in a healthy human brain and in a wide range of clinical conditions, many questions related to their relationship to the brain's cellular constituents remain open. In this paper we use quantitative Gradient Recalled Echo (qGRE) MRI for in vivo quantitative mapping of human brain cellular composition, and BOLD (blood oxygen level dependent) MRI resting state data from the Human Connectome Project to explore how the brain cellular constituents relate to resting state functional networks. Our results show that the BOLD-signal-defined synchrony of connections between cellular circuits in network-defined individual functional units is mainly associated with the regional neuronal density, while the strength of the functional connectivity between functional units is influenced not only by the neuronal but also glia and synaptic components of brain tissue cellular constituents. Data show that these cellular-functional relationships are most evident in the infra-slow frequency range (0.01-0.16 Hz) of brain activity, which is known to be linked with fluctuations of the BOLD signal. These mechanisms lead to a rather broad distribution of resting state functional network properties. We found that visual networks with the highest neuronal density (but lowest density of glial cells and synapses) exhibit the strongest coherence of BOLD signal in individual functional units, as well as the strongest intra-network connectivity. The Default Mode Network (DMN) is positioned near the opposite part of the spectrum with relatively low coherence of the BOLD signal but a remarkably balanced cellular content enabling DMN prominent role in the overall organization of the brain and the hierarchy of functional networks in health and disease.

scholarly journals Insights into TREM2 biology by network analysis of human brain gene expression data

2013 ◽  
Vol 34 (12) ◽  
pp. 2699-2714 ◽  
Author(s):  
Paola Forabosco ◽  
Adaikalavan Ramasamy ◽  
Daniah Trabzuni ◽  
Robert Walker ◽  
Colin Smith ◽  
...  
Keyword(s):  
Gene Expression ◽  
Network Analysis ◽  
Human Brain ◽  
Gene Expression Data ◽  
Expression Data ◽  
Brain Gene Expression

scholarly journals Genetically defined cellular correlates of the baseline brain MRI signal

2018 ◽  
Vol 115 (41) ◽  
pp. E9727-E9736 ◽  
Author(s):  
Jie Wen ◽  
Manu S. Goyal ◽  
Serguei V. Astafiev ◽  
Marcus E. Raichle ◽  
Dmitriy A. Yablonskiy
Keyword(s):  
Functional Connectivity ◽  
Human Brain ◽  
Brain Activity ◽  
Brain Mri ◽  
Blood Oxygenation ◽  
Brain Atlas ◽  
Functional Connections ◽  
Fmri Signal ◽  
Useful Signal

fMRI revolutionized neuroscience by allowing in vivo real-time detection of human brain activity. While the nature of the fMRI signal is understood as resulting from variations in the MRI signal due to brain-activity-induced changes in the blood oxygenation level (BOLD effect), these variations constitute a very minor part of a baseline MRI signal. Hence, the fundamental (and not addressed) questions are how underlying brain cellular composition defines this baseline MRI signal and how a baseline MRI signal relates to fMRI. Herein we investigate these questions by using a multimodality approach that includes quantitative gradient recalled echo (qGRE), volumetric and functional connectivity MRI, and gene expression data from the Allen Human Brain Atlas. We demonstrate that in vivo measurement of the major baseline component of a GRE signal decay rate parameter (R2t*) provides a unique genetic perspective into the cellular constituents of the human cortex and serves as a previously unidentified link between cortical tissue composition and fMRI signal. Data show that areas of the brain cortex characterized by higher R2t* have high neuronal density and have stronger functional connections to other brain areas. Interestingly, these areas have a relatively smaller concentration of synapses and glial cells, suggesting that myelinated cortical axons are likely key cortical structures that contribute to functional connectivity. Given these associations, R2t* is expected to be a useful signal in assessing microstructural changes in the human brain during development and aging in health and disease.

scholarly journals Intrinsic network activity in human brain organoids

2021 ◽  
Author(s):  
Tal Sharf ◽  
Tjitse van der Molen ◽  
Elmer Guzman ◽  
Stella M.K. Glasauer ◽  
Gabriel Luna ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Human Brain ◽  
Network Activity ◽  
Field Potentials ◽  
Network Graph ◽  
Developmental Anatomy ◽  
Functional Connections ◽  
Phase Alignment ◽  
Neuropsychiatric Diseases ◽  
Spiking Activity

AbstractHuman brain organoids replicate much of the cellular diversity and developmental anatomy of the human brain. However, the physiological behavior of neuronal circuits within organoids remains relatively under-explored. With high-density CMOS microelectrode arrays and shank electrodes, we probed broadband and three-dimensional spontaneous activity of human brain organoids. These recordings simultaneously captured local field potentials (LFPs) and single unit activity. From spiking activity, we estimated a directed functional connectivity graph of synchronous neural network activity which showed a large number of weak functional connections enmeshed within a network skeleton of significantly fewer strong connections. Increasing the intrinsic inhibitory tone with a benzodiazepine altered the functional network graph of the organoid by suppressing the network skeleton. Simultaneously examining the spontaneous LFPs and their phase alignment to spiking showed that spike bursts were coherent with theta oscillations in the LFPs. An ensemble of spikes phase-locked to theta frequency oscillations were strongly interconnected as a sub-network within the larger network in which they were embedded. Our results demonstrate that human brain organoids have self-organized neuronal assemblies of sufficient size, cellular orientation, and functional connectivity to co-activate and generate field potentials from their collective transmembrane currents that phase-lock to spiking activity. These results point to the potential of brain organoids for the study of neuropsychiatric diseases, drug mechanisms, and the effects of external stimuli upon neuronal networks.

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