brain atlas
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2022 ◽  
Vol 15 ◽  
Author(s):  
Artur Agaronyan ◽  
Raeyan Syed ◽  
Ryan Kim ◽  
Chao-Hsiung Hsu ◽  
Scott A. Love ◽  
...  

The olive baboon (Papio anubis) is phylogenetically proximal to humans. Investigation into the baboon brain has shed light on the function and organization of the human brain, as well as on the mechanistic insights of neurological disorders such as Alzheimer’s and Parkinson’s. Non-invasive brain imaging, including positron emission tomography (PET) and magnetic resonance imaging (MRI), are the primary outcome measures frequently used in baboon studies. PET functional imaging has long been used to study cerebral metabolic processes, though it lacks clear and reliable anatomical information. In contrast, MRI provides a clear definition of soft tissue with high resolution and contrast to distinguish brain pathology and anatomy, but lacks specific markers of neuroreceptors and/or neurometabolites. There is a need to create a brain atlas that combines the anatomical and functional/neurochemical data independently available from MRI and PET. For this purpose, a three-dimensional atlas of the olive baboon brain was developed to enable multimodal imaging analysis. The atlas was created on a population-representative template encompassing 89 baboon brains. The atlas defines 24 brain regions, including the thalamus, cerebral cortex, putamen, corpus callosum, and insula. The atlas was evaluated with four MRI images and 20 PET images employing the radiotracers for [11C]benzamide, [11C]metergoline, [18F]FAHA, and [11C]rolipram, with and without structural aids like [18F]flurodeoxyglycose images. The atlas-based analysis pipeline includes automated segmentation, registration, quantification of region volume, the volume of distribution, and standardized uptake value. Results showed that, in comparison to PET analysis utilizing the “gold standard” manual quantification by neuroscientists, the performance of the atlas-based analysis was at >80 and >70% agreement for MRI and PET, respectively. The atlas can serve as a foundation for further refinement, and incorporation into a high-throughput workflow of baboon PET and MRI data. The new atlas is freely available on the Figshare online repository (https://doi.org/10.6084/m9.figshare.16663339), and the template images are available from neuroImaging tools & resources collaboratory (NITRC) (https://www.nitrc.org/projects/haiko89/).


Author(s):  
Sophie Stenger ◽  
Sebastian Bludau ◽  
Hartmut Mohlberg ◽  
Katrin Amunts

AbstractBrain areas at the parahippocampal gyrus of the temporal–occipital transition region are involved in different functions including processing visual–spatial information and episodic memory. Results of neuroimaging experiments have revealed a differentiated functional parcellation of this region, but its microstructural correlates are less well understood. Here we provide probability maps of four new cytoarchitectonic areas, Ph1, Ph2, Ph3 and CoS1 at the parahippocampal gyrus and collateral sulcus. Areas have been identified based on an observer-independent mapping of serial, cell-body stained histological sections of ten human postmortem brains. They have been registered to two standard reference spaces, and superimposed to capture intersubject variability. The comparison of the maps with functional imaging data illustrates the different involvement of the new areas in a variety of functions. Maps are available as part of Julich-Brain atlas and can be used as anatomical references for future studies to better understand relationships between structure and function of the caudal parahippocampal cortex.


Author(s):  
Kimberly C. Olney ◽  
Kennedi T. Todd ◽  
Praveen N. Pallegar ◽  
Tanner D. Jensen ◽  
Mika P. Cadiz ◽  
...  

AbstractThe choroid plexus, a tissue responsible for producing cerebrospinal fluid, is found predominantly in the lateral and fourth ventricles of the brain. This highly vascularized and ciliated tissue is made up of specialized epithelial cells and capillary networks surrounded by connective tissue. Given the complex structure of the choroid plexus, this can potentially result in contamination during routine tissue dissection. Bulk and single-cell RNA sequencing studies, as well as genome-wide in situ hybridization experiments (Allen Brain Atlas), have identified several canonical markers of choroid plexus such as Ttr, Folr1, and Prlr. We used the Ttr gene as a marker to query the Gene Expression Omnibus database for transcriptome studies of brain tissue and identified at least some level of likely choroid contamination in numerous studies that could have potentially confounded data analysis and interpretation. We also analyzed transcriptomic datasets from human samples from Allen Brain Atlas and the Genotype-Tissue Expression (GTEx) database and found abundant choroid contamination, with regions in closer proximity to choroid more likely to be impacted such as hippocampus, cervical spinal cord, substantia nigra, hypothalamus, and amygdala. In addition, analysis of both the Allen Brain Atlas and GTEx datasets for differentially expressed genes between likely “high contamination” and “low contamination” groups revealed a clear enrichment of choroid plexus marker genes and gene ontology pathways characteristic of these ciliated choroid cells. Inclusion of these contaminated samples could result in biological misinterpretation or simply add to the statistical noise and mask true effects. We cannot assert that Ttr or other genes/proteins queried in targeted assays are artifacts from choroid contamination as some of these differentials may be due to true biological effects. However, for studies that have an unequal distribution of choroid contamination among groups, investigators may wish to remove contaminated samples from analyses or incorporate choroid marker gene expression into their statistical modeling. In addition, we suggest that a simple RT-qPCR or western blot for choroid markers would mitigate unintended choroid contamination for any experiment, but particularly for samples intended for more costly omic profiling. This study highlights an unexpected problem for neuroscientists, but it is also quite possible that unintended contamination of adjacent structures occurs during dissections for other tissues but has not been widely recognized.


2022 ◽  
Vol 15 ◽  
Author(s):  
Wangli Cai ◽  
Yujing Zhou ◽  
Lidi Wan ◽  
Ruiling Zhang ◽  
Ting Hua ◽  
...  

Functional constipation, which belongs to the functional gastrointestinal disorder (FGID), is a common disease and significantly impacts daily life. FGID patients have been progressively proven with functional and structural alterations in various brain regions, but whether and how functional constipation affects the brain gray matter volume (GMV) remains unclear; besides, which genes are associated with the GMV changes in functional constipation is largely unknown. On account of the structural MRI image from the 30 functional constipation patients and 30 healthy controls (HCs), GMV analysis showed that functional constipation patients had significantly decreased GMV in the right orbital prefrontal cortex (OFC), left precentral gyrus (PreG), and bilateral thalamus (THA). Correlation analysis showed that the self-rating depressive scale, patient assessment of constipation quality of life (PAC-QOL), and Wexner constipation scores were negatively correlated with GMV of the OFC and negative correlations between PAC-QOL score and GMV of the bilateral THA. Based on the Allen Human Brain Atlas, a cross-sample spatial correlation was conducted and found that 18 genes’ expression values showed robust correlations with GMV changes in functional constipation patients. These outcomes highlight our recognition of the transcriptional features related to GMV changes in functional constipation and could be regarded as candidates to detect biological mechanisms of abnormality in functional constipation patients.


2022 ◽  
Author(s):  
Edita Bulovaite ◽  
Zhen Qiu ◽  
Maximilian Kratschke ◽  
Adrianna Zgraj ◽  
David G. Fricker ◽  
...  
Keyword(s):  

2021 ◽  
Author(s):  
Matej Murgaš ◽  
Paul Michenthaler ◽  
Murray Bruce Reed ◽  
Gregor Gryglewski ◽  
Rupert Lanzenberger

Changes in distribution of associated molecular targets have been reported across several neuropsychiatric disorders. However, the high-resolution topology of most proteins is unknown and simultaneous in vivo measurement in multi-receptor systems is complicated. To account for the missing proteomic information, mRNA transcripts are typically used as a surrogate. Nonetheless, post-transcriptional and post-translational processes might cause the discrepancy between the final distribution of proteins and gene expression patterns. Therefore, this study aims to investigate ex vivo links between mRNA expression and corresponding receptor density in the human cerebral cortex. To this end, autoradiography data on the density of 15 different receptors in 38 brain regions were correlated with the expression patterns of 50 associated genes derived from microarray data (mA), RNA sequencing data (RNA-Seq) provided by the Allen Human Brain Atlas and predicted mRNA expression patterns (pred-mRNA). Spearman's rank correlation was used to evaluate the possible links between proteomic data and mRNA expression patterns. Correlations between mRNA and protein density varied greatly between targets: Positive associations were found for e.g. the serotonin 1A (pred-mRNA: rs = 0.708; mA: rs = 0.601) or kainate receptor (pred-mRNA: rs = 0.655; mA: rs = 0.601; RNA-Seq: rs = 0.575), while most of the investigated target receptors showed low or negative correlations. The high variability in the correspondence of mRNA expression and receptor warrants caution when inferring the topology of molecular targets in the brain from transcriptome data. This highlights the longstanding value of molecular imaging data and the need for comprehensive proteomic data.


2021 ◽  
Author(s):  
Edita Bulovaite ◽  
Zhen Qiu ◽  
Maximillian Kratschke ◽  
Adrianna Zgraj ◽  
David Fricker ◽  
...  

Protein turnover is required for synapse maintenance and remodelling and may impact memory duration. We quantified the lifetime of postsynaptic protein PSD95 in individual excitatory synapses across the mouse brain and lifespan, generating the Protein Lifetime Synaptome Atlas. Excitatory synapses have a wide range of protein lifetimes that may extend from a few hours to several months, with distinct spatial distributions in dendrites, neuron types and brain regions. Short protein lifetime (SPL) synapses are enriched in developing animals and in regions controlling innate behaviors, whereas long protein lifetime (LPL) synapses accumulate during development, are enriched in the cortex and CA1 where memories are stored, and are preferentially preserved in old age. The protein lifetime synaptome architecture is disrupted in an autism model, with synapse protein lifetime increased throughout the brain. These findings add a further layer to synapse diversity in the brain and enrich prevailing concepts in behavior, development, ageing and brain repair.


2021 ◽  
Author(s):  
Zhilei Xu ◽  
Mingrui Xia ◽  
Xindi Wang ◽  
Xuhong Liao ◽  
Tengda Zhao ◽  
...  

Macroscopic functional connectomic analyses have identified sets of densely connected regions in the human brain, known as connectome hubs, which play a vital role in understanding network communication, cognitive processing, and brain disorders. However, anatomical locations of functional connectome hubs are largely inconsistent and less reproducible among extant reports, partly due to inadequate sample size and differences in image processing and network analysis. Moreover, the genetic signatures underlying the robust connectome hubs remain unknown. Here, we conduct the first worldwide voxelwise meta-connectomic analysis by pooling resting-state functional MRI data of 5,212 healthy young adults across 61 independent international cohorts with harmonized image processing and network analysis protocols. We identify highly consistent and reproducible functional connectome hubs that are spatially distributed in multiple heteromodal and unimodal regions, with the most robust findings mainly located in lateral parietal regions. These connectome hubs show unique, heterogeneous connectivity profiles and are critical for both intra- and inter-network communications. Using transcriptome data from the Allen Human Brain Atlas and BrainSpan Atlas as well as machine learning, we demonstrate that these robust hubs are significantly associated with a transcriptomic pattern dominated by genes involved in the neuropeptide signaling pathway, neurodevelopmental processes, and cellular metabolic processes. This pattern represents microstructural and metabolic substrates underlying the development and functioning of brain hubs. Together, these results highlight robustness of macroscopic connectome hubs of the human brain and their potential cellular and molecular underpinnings and have implications for understanding how brain hubs support the connectome organization in health and disease.


2021 ◽  
Author(s):  
Wieslaw L. Nowinski

AbstractHuman brain atlas development is predominantly research-oriented and the use of atlases in clinical practice is limited. Here I introduce a new definition of a reference human brain atlas that serves education, research and clinical applications, and is extendable by its user. Subsequently, an architecture of a multi-purpose, user-extendable reference human brain atlas is proposed and its implementation discussed. The human brain atlas is defined as a vehicle to gather, present, use, share, and discover knowledge about the human brain with highly organized content, tools enabling a wide range of its applications, massive and heterogeneous knowledge database, and means for content and knowledge growing by its users. The proposed architecture determines major components of the atlas, their mutual relationships, and functional roles. It contains four functional units, core cerebral models, knowledge database, research and clinical data input and conversion, and toolkit (supporting processing, content extension, atlas individualization, navigation, exploration, and display), all united by a user interface. Each unit is described in terms of its function, component modules and sub-modules, data handling, and implementation aspects. This novel architecture supports brain knowledge gathering, presentation, use, sharing, and discovery and is broadly applicable and useful in student- and educator-oriented neuroeducation for knowledge presentation and communication, research for knowledge acquisition, aggregation and discovery, and clinical applications in decision making support for prevention, diagnosis, treatment, monitoring, and prediction. It establishes a backbone for designing and developing new, multi-purpose and user-extendable brain atlas platforms, serving as a potential standard across labs, hospitals, and medical schools.


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