A novel brain partition highlights the modular skeleton shared by structure and function

Elucidating the intricate relationship between brain structure and function, both in healthy and pathological conditions, is a key challenge for modern neuroscience. Recent progress in neuroimaging has helped advance our understanding of this important issue, with diffusion images providing information about structural connectivity (SC) and functional magnetic resonance imaging shedding light on resting state functional connectivity (rsFC). Here, we adopt a systems approach, relying on modular hierarchical clustering, to study together SC and rsFC datasets gathered independently from healthy human subjects. Our novel approach allows us to find a common skeleton shared by structure and function from which a new, optimal, brain partition can be extracted. We describe the emerging common structure-function modules (SFMs) in detail and compare them with commonly employed anatomical or functional parcellations. Our results underline the strong correspondence between brain structure and resting-state dynamics as well as the emerging coherent organization of the human brain.Work supported by Ikerbasque: The Basque Foundation for Science, Euskampus at UPV/EHU, Gobierno Vasco (Saiotek SAIO13-PE13BF001) and Junta de Andalucía (P09-FQM-4682) to JMC; Ikerbasque Visiting Professor to SS; Junta de Andalucía (P09-FQM-4682) and Spanish Ministry of Economy and Competitiveness (FIS2013-43201-P) to MAM; the European Union’s Seventh Framework Programme (ICT-FET FP7/2007-2013, FET Young Explorers scheme) under grant agreement n. 284772 BRAIN BOW (www.brainbowproject.eu) and by the Joint Italy—Israel Laboratory on Neuroscience to PB. For results validation (figure S8), data were provided by the Human Connectome Project, WU-Minn Consortium (Principal Investigators: David Van Essen and Kamil Ugurbil; 1U54MH091657) funded by the 16 NIH Institutes and Centers that support the NIH Blueprint for Neuroscience Research; and by the McDonnell Center for Systems Neuroscience at Washington University

Resting state cortico-thalamic-striatal connectivity predicts pesponse to dorsomedial prefrontal rTMS in major depressive disorder

Despite its high toll on society, there has been little recent improvement in treatment efficacy for Major Depressive Disorder (MDD). The identification of biological markers of successful treatment response may allow for more personalized and effective treatment. Here we investigate whether resting state functional connectivity predicted response to treatment with rapid transcranial magnetic stimulation (rTMS) to dorsomedial prefrontal cortex (dmPFC). Twenty five individuals with treatment-refractory MDD underwent a 4-week course of dmPFC-rTMS. Before and after treatment, subjects received resting state functional MRI scans and assessments of depressive symptoms using the Hamilton Depresssion Rating Scale (HAMD17). We found that higher baseline cortico-cortical connectivity (dmPFC-subgenual cingulate and subgenual cingulate to dorsolateral PFC) and lower cortico-thalamic, cortico-striatal and cortico-limbic connectivity were associated with better treatment outcomes. We also investigated how changes in connectivity over the course of treatment related to improvements in HAMD17 scores. We found that successful treatment was associated with increased dmPFC-thalamic connectivity and decreased sgACC-caudate connectivity, Our findings provide insight into which individuals might respond to rTMS treatment and the mechanisms through which these treatments work

Sequential morphological characteristics of murine fetal liver hematopoietic microenvironment in Swiss Webster mice

Embryonic hematopoiesis occurs via dynamic development with cells migrating into various organs. Fetal liver is the main hematopoietic organ responsible for hematopoietic cell expansion during embryologic development. We describe the morphological sequential characteristics of murine fetal liver niches that favor the settlement and migration of hematopoietic cells from 12 days post-coitum (dpc) to 0 day post-partum. Liver sections were stained with hematoxylin and eosin, Lennert’s Giemsa, Sirius Red pH 10.2, Gomori’s Reticulin, and Periodic Acid Schiff/Alcian Blue pH 1.0 and pH 2.5 and were analyzed by bright-field microscopy. Indirect imunohistochemistry for fibronectin, matrix metalloproteinase-1 (MMP-1), and MMP-9 and histochemistry for naphthol AS-D chloroacetate esterase (NCAE) were analyzed by confocal microscopy. The results showed that fibronectin was related to the promotion of hepatocyte and trabecular differentiation; reticular fibers did not appear to participate in fetal hematopoiesis but contributed to the physical support of the liver after 18 dpc. During the immature phase, hepatocytes acted as the fundamental stroma for the erythroid lineage. The appearance of myeloid cells in the liver was related to perivascular and subcapsular collagen, and NCAE preceded MMP-1 expression in neutrophils, an occurrence that appeared to contribute to their liver evasion. Thus, the murine fetal liver during ontogenesis shows two different phases: one immature and mainly endodermic (<14 dpc) and the other more developed (endodermic-mesenchymal; >15 dpc) with the maturation of hepatocytes, a better definition of trabecular pattern, and an increase in the connective tissue in the capsule, portal spaces, and liver parenchyma. The decrease of hepatic hematopoiesis (migration) coincides with hepatic maturation

The Connectome Visualization Utility: Software for Visualization of Human Brain Networks

In analysis of the human connectome, the connectivity of the human brain is collected from multiple imaging modalities and analyzed using graph theoretical techniques. The dimensionality of human connectivity data is high, and making sense of the complex networks in connectomics requires sophisticated visualization and analysis software. The current availability of software packages to analyze the human connectome is limited. The Connectome Visualization Utility (CVU) is a new software package designed for the visualization and network analysis of human brain networks. CVU complements existing software packages by offering expanded interactive analysis and advanced visualization features, including the automated visualization of networks in three different complementary styles and features the special visualization of scalar graph theoretical properties and modular structure. By decoupling the process of network creation from network visualization and analysis, we ensure that CVU can visualize networks from any imaging modality. CVU offers a graphical user interface, interactive scripting, and represents data uses transparent neuroimaging and matrix-based file types rather than opaque application-specific file formats

Building connectomes using diffusion MRI: why, how and but

Why has diffusion MRI become a principal modality for mapping connectomes in vivo? How do different image acquisition parameters, fiber tracking algorithms and other methodological choices affect connectome estimation? What are the main factors that dictate the success and failure of connectome reconstruction? These are some of the key questions that we aim to address in this review. We provide an overview of the key methods that can be used to estimate the nodes and edges of macroscale connectomes, and we discuss open problems and inherent limitations. We argue that diffusion MRI-based connectome mapping methods are still in their infancy and caution against blind application of deep white matter tractography due to the challenges inherent to connectome reconstruction. We review a number of studies that provide evidence of useful microstructural and network properties that can be extracted in various independent and biologically-relevant contexts. Finally, we highlight some of the key deficiencies of current macroscale connectome mapping methodologies and motivate future developments

Uncovering Enhancer Functions Using the α-Globin Locus

Over the last three decades, studies of the α- and β-globin genes clusters have led to elucidation of the general principles of mammalian gene regulation, such as RNA stability, termination of transcription, and, more importantly, the identification of remote regulatory elements. More recently, detailed studies of α-globin regulation, using both mouse and human loci, allowed the dissection of the sequential order in which transcription factors are recruited to the locus during lineage specification. These studies demonstrated the importance of the remote regulatory elements in the recruitment of RNA polymerase II (PolII) together with their role in the generation of intrachromosomal loops within the locus and the removal of polycomb complexes during differentiation. The multiple roles attributed to remote regulatory elements that have emerged from these studies will be discussed

Programmed cell death and its role in inflammation

Cell death plays an important role in the regulation of inflammation and may be the result of inflammation. The maintenance of tissue homeostasis necessitates both the recognition and removal of invading microbial pathogens as well as the clearance of dying cells. In the past few decades, emerging knowledge on cell death and inflammation has enriched our molecular understanding of the signaling pathways that mediate various programs of cell death and multiple types of inflammatory responses. This review provides an overview of the major types of cell death related to inflammation. Modification of cell death pathways is likely to be a logical therapeutic target for inflammatory diseases