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Non-human primate neuroimaging is a rapidly growing area of research that promises to transform and scale translational and cross-species comparative neuroscience. Unfortunately, the technological and methodological advances of the past two decades have outpaced the accrual of data, which is particularly challenging given the relatively few centers that have the necessary facilities and capabilities. The PRIMatE Data Exchange (PRIME-DE) addresses this challenge by aggregating independently acquired non-human primate magnetic resonance imaging (MRI) datasets and openly sharing them via the International Neuroimaging Data-sharing Initiative (INDI). Here, we present the rationale, design, and procedures for the PRIME-DE consortium, as well as the initial release, consisting of 25 independent data collections aggregated across 22 sites (total = 217 non-human primates). We also outline the unique pitfalls and challenges that should be considered in the analysis of non-human primate MRI datasets, including providing automated quality assessment of the contributed datasets., (Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.)

Studies that seek to predict the brain microstructure based on MRI require precise alignment of processed brain histology slices to the corresponding 3D MRI data. However, achieving such alignment is a challenging problem, due to tissue distortions and the different contrasts seen in MRI and the processed tissue. Here we present a pipeline for aligning a histology volume to the MRI data of the tissue and to a stereotaxic brain atlas. To this end, we segment the volume of the brain from ex-vivo MRI data, align the MRI data obtained in the native space to an MRI stereotaxic template and create a 3D printed model (a mold or cradle) that precisely fits the brain. The pipeline then makes it possible to create grooves in the 3D model, for guiding blades for cutting slabs of tissue. Placing the brain in the brain-specific 3D printed model aligns the tissue to the MRI data by default. Aligning the MRI data to an MRI stereotaxic template makes it possible to section histology slices parallel to the standard stereotaxic axes of the atlas. This facilitates comparisons to other MRI contrasts and to images of processed tissue aligned to the standard space, while maintaining the high-resolution of the tissue images along the standard stereotaxic plane. Guiding the positioning of the grooves according to species-specific anatomical information from the co-registered atlas facilitates region-specific histology. The pipeline we introduce can be used to create brain-specific sectioning models for a variety of species, including humans, primates, and rodents. To demonstrate the generalizability of the pipeline across species, we show models generated for macaques and rats.

Melanoma is the leading cause of skin cancer mortality. The major cause of melanoma mortality is metastasis to distant organs, frequently to the brain. The microenvironment plays a critical role in tumourigenesis and metastasis. In order to treat or prevent metastasis, the interactions of disseminated tumour cells with the microenvironment at the metastatic organ have to be elucidated. However, the role of brain stromal cells in facilitating metastatic growth is poorly understood. Astrocytes are glial cells that function in repair and scarring of the brain following injury, in part via mediating neuroinflammation, but the role of astrocytes in melanoma brain metastasis is largely unresolved. Here we show that astrocytes can be reprogrammed by human brain-metastasizing melanoma cells to express pro-inflammatory factors, including the cytokine IL-23, which was highly expressed by metastases-associated astrocytes in vivo. Moreover, we show that the interactions between astrocytes and melanoma cells are reciprocal: paracrine signalling from astrocytes up-regulates the secretion of the matrix metalloproteinase MMP2 and enhances the invasiveness of brain-metastasizing melanoma cells. IL-23 was sufficient to increase melanoma cell invasion, and neutralizing antibodies to IL-23 could block this enhanced migration, implying a functional role for astrocyte-derived IL-23 in facilitating the progression of melanoma brain metastasis. Knocking down the expression of MMP2 in melanoma cells resulted in inhibition of IL-23-induced invasiveness. Thus, our study demonstrates that bidirectional signalling between melanoma cells and astrocytes results in the formation of a pro-inflammatory milieu in the brain, and in functional enhancement of the metastatic potential of disseminated melanoma cells., (Copyright © 2015 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.)

Recent studies from our group and others using quantitative fMRI methods have found that variations of the coupling ratio of blood flow (CBF) and oxygen metabolism (CMRO2) responses to a stimulus have a strong effect on the BOLD response. Across a number of studies an empirical pattern is emerging in the way CBF and CMRO2 changes are coupled to neural activation: if the stimulus is modulated to create a stronger response (e.g., increasing stimulus contrast), CBF is modulated more than CMRO2; on the other hand, if the brain state is altered such that the response to the same stimulus is increased (e.g., modulating attention, adaptation, or excitability), CMRO2 is modulated more than CBF. Because CBF and CMRO2 changes conflict in producing BOLD signal changes, this finding has an important implication for conventional BOLD-fMRI studies: the BOLD response exaggerates the effects of stimulus variation but is only weakly sensitive to modulations of the brain state that alter the response to a standard stimulus. A speculative hypothesis is that variability of the coupling ratio of the CBF and CMRO2 responses reflects different proportions of inhibitory and excitatory evoked activity, potentially providing a new window on neural activity in the human brain.

This paper introduce a fast and efficient solver for simulating the induced (eddy) current distribution in the brain during transcranial magnetic stimulation procedure. This solver has been integrated with MRI and neuronavigation software to accurately model the electromagnetic field and show eddy current in the head almost in real-time. To examine the performance of the proposed technique, we used a 3D anatomically accurate MRI model of the 25 year old female subject.

Several studies posit energy as a constraint on the coding and processing of information in the brain due to the high cost of resting and evoked cortical activity. This suggestion has been addressed theoretically with models of a single neuron and two coupled neurons. Neural mass models (NMMs) address mean-field based modeling of the activity and interactions between populations of neurons rather than a few neurons. NMMs have been widely employed for studying the generation of EEG rhythms, and more recently as frameworks for integrated models of neurophysiology and functional MRI (fMRI) responses. To date, the consequences of energy constraints on the activity and interactions of ensembles of neurons have not been addressed. Here we aim to study the impact of constraining energy consumption during the resting-state on NMM parameters. To this end, we first linearized the model, then used stochastic control theory by introducing a quadratic cost function, which transforms the NMM into a stochastic linear quadratic regulator (LQR). Solving the LQR problem introduces a regime in which the NMM parameters, specifically the effective connectivities between neuronal populations, must vary with time. This is in contrast to current NMMs, which assume a constant parameter set for a given condition or task. We further simulated energy-constrained stochastic control of a specific NMM, the Wilson and Cowan model of two coupled neuronal populations, one of which is excitatory and the other inhibitory. These simulations demonstrate that with varying weights of the energy-cost function, the NMM parameters show different time-varying behavior. We conclude that constraining NMMs according to energy consumption may create more realistic models. We further propose to employ linear NMMs with time-varying parameters as an alternative to traditional nonlinear NMMs with constant parameters.

Hyperactivation of beta-catenin-T-cell-factor (TCF)-regulated gene transcription is a hallmark of colorectal cancer (CRC). The cell-neural adhesion molecule L1CAM (hereafter referred to as L1) is a target of beta-catenin-TCF, exclusively expressed at the CRC invasive front in humans. L1 overexpression in CRC cells increases cell growth and motility, and promotes liver metastasis. Genes induced by L1 are also expressed in human CRC tissue but the mechanisms by which L1 confers metastasis are still unknown. We found that signaling by the nuclear factor kappaB (NF-kappaB) is essential, because inhibition of signaling by the inhibitor of kappaB super repressor (IkappaB-SR) blocked L1-mediated metastasis. Overexpression of the NF-kappaB p65 subunit was sufficient to increase CRC cell proliferation, motility and metastasis. Binding of the L1 cytodomain to ezrin - a cytoskeleton-crosslinking protein - is necessary for metastasis because when binding to L1 was interrupted or ezrin gene expression was suppressed with specific shRNA, metastasis did not occur. L1 and ezrin bound to and mediated the phosphorylation of IkappaB. We also observed a complex containing IkappaB, L1 and ezrin in the juxtamembrane region of CRC cells. Furthermore, we found that L1, ezrin and phosphorylated p65 are co-expressed at the invasive front in human CRC tissue, indicating that L1-mediated activation of NF-kappaB signaling involving ezrin is a major route of CRC progression.