Genome scale mapping of brain gene expression.

Two new approaches, voxelation and gene expression tomography (GET), permit multiplex acquisition of gene expression patterns in the brain. Both methods result in volumetric images of gene expression analogous to those produced in biomedical imaging systems. Voxelation employs analysis of spatially registered cubes from the brain, whereas GET entails analysis of parallel slices obtained by rotation about multiple axes. These methods have been used to investigate neurologic diseases and their models in both humans and mice. The results of these studies are discussed, as is the future of high-throughput gene expression mapping in the brain.     

Decoding brain responses to pixelized images in the primary visual cortex: implications for visual cortical prostheses

Visual cortical prostheses have the potential to restore partial vision. Still limited by the low-resolution visual percepts provided by visual cortical prostheses, implant wearers can currently only "see" pixelized images, and how to obtain the specific brain responses to different pixelized images in the primary visual cortex(the implant area) is still unknown. We conducted a functional magnetic resonance imaging experiment on normal human participants to investigate the brain activation patterns in response to 18 different pixelized images. There were 100 voxels in the brain activation pattern that were selected from the primary visual cortex, and voxel size was 4 mm × 4 mm × 4 mm. Multi-voxel pattern analysis was used to test if these 18 different brain activation patterns were specific. We chose a Linear Support Vector Machine(LSVM) as the classifier in this study. The results showed that the classification accuracies of different brain activation patterns were significantly above chance level, which suggests that the classifier can successfully distinguish the brain activation patterns. Our results suggest that the specific brain activation patterns to different pixelized images can be obtained in the primary visual cortex using a 4 mm × 4 mm × 4 mm voxel size and a 100-voxel pattern.     

Application of PET-MRI registration techniques to cat brain imaging

In positron emission tomography (PET) studies of diseased animals, it is very useful to have accurate anatomical information as a reference. In human studies, anatomical information is usually obtained from magnetic resonance imaging (MRI) of the subject with retrospective registration of the subject's PET image to the MRI. A number of PET-MRI registration techniques are used for this purpose. However, the utility of these methods has not been tested for animals image registration. This paper studies the feasibility of applying two currently used human brain PET-MRI registration techniques to cat brain images. METHODS: Three cats were anesthetized with isoflurane gas, and PET images were acquired with H(2)(15)O, benzodiazepine receptor ligand 11C-flumazemil (FMZ), dopamine receptor ligand 11C-nemonapride (NEM) and fluorodeoxy glucose (18F-FDG). The four PET scans were acquired consecutively within the same day while the cat remained fixed in the scanner. We also obtained T1-weighted and T2-weighted MRI of the cats in a 4.7 T unit. The PET images were registered to MRI using two human brain registration techniques: a semi-automatic method (SAM), which is a two-step method based on the extraction of the midsagittal plane, and an automatic method (AMIR) method that minimizes PET pixel variance within spatially connected segments determined by MRI. RESULTS: T2-weighted MRI provided better structural information than T1 MRI. FMZ did, while FDG or H(2)O PET images did not, provide a structural outline of the brain. The FMZ PET image was registered to MRI satisfactorily using SAM. The striatum visualized in nemonapride PET image re-sliced with the same parameters matched the striatum identified in T2-weighted MRI. Registration by AMIR was successful by inspection for FMZ, FDG or H(2)O PET images in only one of the three cats. The registration error of SAM was estimated to be less than 2 mm or 2 degrees. CONCLUSION: A satisfactory registration of FMZ-PET to T2-weighted MRI of the cat brain was obtained by a two-step manual registration technique. This will enhance the usefulness of PET in the field of cerebral pathophysiology.     

The future of genomic profiling of neurological diseases using blood

Sequencing of the human genome and new microarray technology make it possible to assess all genes on a single chip or array. Recent studies show different patterns of gene expression related to different tissues and diseases, and these patterns of gene expression are beginning to be used for diagnosis and treatment decisions in various types of lymphoid and solid malignancies. Because of obvious problems obtaining brain tissue, progress in genomics of neurological diseases has been slow. To address this, we demonstrated that different types of acute injury in rodent brain produced different patterns of gene expression in peripheral blood. These animal studies have now been extended to human studies. Two groups have shown that there are specific genomic profiles in the blood of patients after ischemic stroke that are highly sensitive and specific for predicting stroke. Other recent studies demonstrate specific genomic profiles in the blood of patients with Down syndrome, neurofibromatosis, tuberous sclerosis, Huntington disease, multiple sclerosis, Tourette syndrome, and others. In addition, data demonstrate specific profiles of gene expression in the blood related to different drugs, toxins, and infections. Although all of these studies are still preliminary basic scientific endeavors, they suggest that this approach will have clinical applications to neurological diseases in humans.     

Regional and Voxel‐Wise Comparisons of Blood Flow Measurements Between Dynamic Susceptibility Contrast Magnetic Resonance Imaging (DSC‐MRI) and Arterial Spin Labeling (ASL) in Brain Tumors

The objective of the current study was to evaluate the regional and voxel‐wise correlation between dynamic susceptibility contrast (DSC) and arterial spin labeling (ASL) perfusion magnetic resonance imaging (MRI) measurement of cerebral blood flow (CBF) in patients with brain tumors. Thirty patients with histologically verified brain tumors were evaluated in the current study. DSC‐MRI was performed by first using a preload dose of gadolinium contrast, then collecting a dynamic image acquisition during a bolus of contrast, followed by posthoc contrast agent leakage correction. Pseudocontinuous ASL was collected using 30 pairs of tag and control acquisition using a 3‐dimensional gradient‐echo spin‐echo (GRASE) acquisition. All images were registered to a high‐resolution anatomical atlas. Average CBF measurements within regions of contrast‐enhancement and T2 hyperintensity were evaluated between the two modalities. Additionally, voxel‐wise correlation between CBF measurements obtained with DSC and ASL were assessed. Results demonstrated a positive linear correlation between DSC and ASL measurements of CBF when regional average values were compared; however, a statistically significant voxel‐wise correlation was only observed in around 30‐40% of patients. These results suggest DSC and ASL may provide regionally similar, but spatially different measurements of CBF.     

Expression patterns of epidermal growth factor receptor and fibroblast growth factor receptor 1 mRNA in fetal human brain

Factors that interact with the epidermal growth factor and fibroblast growth factor receptors have numerous effects in the central nervous system (CNS), inducing the proliferation of CNS stem cells and astrocytes and the survival and differentiation of neurons. Both receptors are expressed in the embryonic rodent brain in proliferative and nonproliferative regions, suggesting roles in numerous developmental processes. However, the roles of these factors in human brain development are not known. In the current study, we examined the expression of human epidermal growth factor receptor (HEGFR) and human fibroblast growth factor receptor 1 (HFGFR1) mRNAs in the human fetal brain. The expression of both receptors is strikingly conserved relative to previously reported patterns in the rodent. In the germinal zones, the sites of cellular proliferation, HFGFR1 was expressed primarily in the ventricular zone, whereas HEGFR was expressed in the subventricular zone, suggesting different roles in CNS progenitor proliferation. Differential expression was also observed in other brain areas examined, including the hippocampus and the cerebellum. The current study suggests that HEGFR and HFGFR1 are likely to play different roles during human brain development, but that these roles will be similar to those observed in the rodent brain.     

Activation pattern reproducibility: Measuring the effects of group size and data analysis models

The reproducibility of patterns from brain activation experiments has been examined only for suprathreshold spatially localized foci. Scatter plots comparing signal levels across all pairs of Talairach voxels for pairs of functional activation images provide an alternative approach for assessing reproducibility. Image-wide, signal-level reproducibility may be quantitatively summarized using pattern similarity measures such as the Pearson product-moment correlation, ρ. Empirical population distributions of ρ for many pair-wise image comparisons, generated using statistical resampling techniques, may be used to examine the impact of a wide range of experimental variables. We demonstrate the use of such empirical ρ-histograms to measure changes in reproducibility for [¹⁵O]-water PET scans of a simple motor task as a function of group size and data analysis model. Hum. Brain Mapping 5:312–316, 1997. © 1997 Wiley-Liss, Inc.     

Comparison of a non‐stationary voxelation‐corrected cluster‐size test with TFCE for group‐Level MRI inference

Two powerful methods for statistical inference on MRI brain images have been proposed recently, a non‐stationary voxelation‐corrected cluster‐size test (CST) based on random field theory and threshold‐free cluster enhancement (TFCE) based on calculating the level of local support for a cluster, then using permutation testing for inference. Unlike other statistical approaches, these two methods do not rest on the assumptions of a uniform and high degree of spatial smoothness of the statistic image. Thus, they are strongly recommended for group‐level fMRI analysis compared to other statistical methods. In this work, the non‐stationary voxelation‐corrected CST and TFCE methods for group‐level analysis were evaluated for both stationary and non‐stationary images under varying smoothness levels, degrees of freedom and signal to noise ratios. Our results suggest that, both methods provide adequate control for the number of voxel‐wise statistical tests being performed during inference on fMRI data and they are both superior to current CSTs implemented in popular MRI data analysis software packages. However, TFCE is more sensitive and stable for group‐level analysis of VBM data. Thus, the voxelation‐corrected CST approach may confer some advantages by being computationally less demanding for fMRI data analysis than TFCE with permutation testing and by also being applicable for single‐subject fMRI analyses, while the TFCE approach is advantageous for VBM data. Hum Brain Mapp 38:1269–1280, 2017. © 2016 Wiley Periodicals, Inc.     

Strategy for the formation of parametric images under conditions of low injected radioactivity applied to PET studies with the irreversible monoamine oxidase A tracers [11C]clorgyline and deuterium-substituted [11C]clorgyline.

The construction of parametric positron emission tomography images of enzyme or receptor concentration obtained using irreversibly binding radiotracers presents problems not usually encountered with reversibly binding radiotracers. Difficulties are most apparent in brain regions having low blood flow and/or high enzyme or receptor concentration and are exacerbated with noisy data. This is especially true when minimal doses of radiotracer are administered. A comparison was recently reported of the irreversible monoamine oxidase A (MAO A) radiotracers [11C]clorgyline (CLG) and deuterium-substituted [11C]clorgyline (CLG-D) in the human brain using region of interest (ROI) analysis in which the authors observed an unexpected loss of image contrast with CLG-D compared with CLG. In order to more fully investigate patterns of binding of these irreversibly binding radiotracers, a strategy was devised to reduce noise in the generation of parametric images of the model term related to enzyme or receptor concentration. The generalized linear least squares (GLLS) method of Feng et al. (1995), a rapid linear method that is unbiased, was used for image-wide parameter estimation. Since GLLS can fail in the presence of large amounts of noise, local voxels were grouped within the image to increase the signal, and the GLLS method was combined with the standard nonlinear estimation methods when necessary. Voxels were grouped together depending on their proximity and whether they fell within a specified range of the time-integrated image. It was assumed that voxels meeting both criteria are functionally related. Simulations reflecting varying enzyme concentrations were performed to assess precision and accuracy of parameter estimates in the presence of varying amounts of noise. Using this approach, images were generated of the combination parameter lambdak3 (lambda = K1/k2, where K1 and k2 are plasma-to-tissue and tissue-to-plasma transport constants, respectively) that is related to enzyme concentration as well as images of the transport constant K1 for individual subjects. Reasonably high-quality images of both K1 and lambdak3 were obtained for CLG and CLG-D for individual subjects even with low injected doses averaging 6 mCi. While there were no differences in the K1 images, the lambdak3 images revealed the loss of contrast previously reported for CLG-D using the ROI analysis. This method should be generalizable to other tracers and should facilitate the analysis of group differences.     

FDG-PET images quantified by probabilistic atlas of brain and surgical prognosis of temporal lobe epilepsy

PURPOSE: This study evaluated the relation between hypometabolism, diagnosed by fluorodeoxyglucose positron emission tomography (FDG-PET), and the surgical outcome of a large and homogeneous series of cases of mesial temporal lobe epilepsy (mTLE), by using a probabilistic atlas of the human brain (statistical probabilistic anatomical maps: SPAM). METHODS: Ninety-five surgically proven intractable mTLE patients and 22 age-matched controls were spatially normalized to the average brain PET template of international consortium of brain mapping (ICBM). The diagnosis of mTLE was confirmed by the presence of hippocampal sclerosis on magnetic resonance imaging (MRI) and video-EEG monitoring. Counts from normalized PET images were multiplied by the probability from 98 volumes of interest (VOIs) of SPAM. Asymmetric indexes (AIs) reflecting the severity of hypometabolism were calculated by counts of selected 12 VOIs from SPAM images in both temporal lobes. Extent of hypometabolism was determined by the number of voxels showing decreased metabolism in each VOI segmented by SPAM. RESULTS: Of the 95 patients studied, 76 (80%) were seizure free, and 19 (20%) had postoperative seizures for the > or =2-year follow-up period. No significant association between the severity of hypometabolism in each VOI of the temporal lobe and surgical outcome was identified (p > 0.05). The number of voxels showing decreased hypometabolism was not significantly different between the good- and poor-outcome groups (p > 0.05). CONCLUSIONS: Our results demonstrated that focal severity and extent of hypometabolism quantified by a probabilistic atlas of brain were not related to the surgical outcome in mTLE patients who had hippocampal sclerosis on MRI. We should develop a more localized and specified anatomic map for mTLE for further results.     

TorsinA expression is detectable in human infants as young as 4 weeks old

Familial, early onset, generalized torsion dystonia is the most common and severe primary dystonia. The majority of cases are caused by a 3-bp deletion (GAG) in the coding region of the DYT1 (TOR1A) gene. The cellular and regional distribution of torsinA protein and its message has been described previously in several regions of normal adult human and rodent brain. This study examines the expression of torsinA in the developing human brain of fetuses, infants and children up to 7 years of age in four selected brain regions. Expression of torsinA protein was detectable beginning at 4 to 8 weeks of age postnatally in the cerebellum (Purkinje cells), substantia nigra (dopaminergic neurons), hippocampus and basal ganglia. Prominent torsinA immunoreactivity was not seen before 6 weeks of age postnatally, a period associated with synaptic remodeling, process elimination and the beginning of myelination. Our results indicate that torsinA protein expression is temporally and spatially regulated and is present in all brain regions studied by the age of 2 months on into adulthood.     

Lysosomal Cathepsin Protease Gene Expression Profiles in the Human Brain During Normal Development

Cathepsin protease genes are necessary for protein homeostasis in normal brain development and function. The diversity of the 15 cathepsin protease activities raises the question of what are the human brain expression profiles of the cathepsin genes during development from prenatal and infancy to childhood, adolescence, and young adult stages. This study, therefore, evaluated the cathepsin gene expression profiles in 16 human brain regions during development by quantitative RNA-sequencing data obtained from the Allen Brain Atlas resource. Total expression of all cathepsin genes was the lowest at the early prenatal stage which became increased at the infancy stage. During infancy to young adult phases, total gene expression was similar. Interestingly, the rank ordering of gene expression among the cathepsins was similar throughout the brain at the age periods examined, showing (a) high expression of cathepsins B, D, and F; (b) moderate expression of cathepsins A, L, and Z; (c) low expression of cathepsins C, H, K, O, S, and V; and (d) very low expression of cathepsins E, G, and W. Results show that the human brain utilizes well-defined, balanced patterns of cathepsin gene expression throughout the different stages of human brain development. Knowledge gained by this study of the gene expression profiles of lysosomal cathepsin proteases among human brain regions during normal development is important for advancing future investigations of how these cathepsins are dysregulated in lysosomal-related brain disorders that affect infants, children, adolescents, and young adults.     

Decoding the individual finger movements from single‐trial functional magnetic resonance imaging recordings of human brain activity

Multivariate pattern classification analysis (MVPA) has been applied to functional magnetic resonance imaging (fMRI) data to decode brain states from spatially distributed activation patterns. Decoding upper limb movements from non‐invasively recorded human brain activation is crucial for implementing a brain–machine interface that directly harnesses an individual's thoughts to control external devices or computers. The aim of this study was to decode the individual finger movements from fMRI single‐trial data. Thirteen healthy human subjects participated in a visually cued delayed finger movement task, and only one slight button press was performed in each trial. Using MVPA, the decoding accuracy (DA) was computed separately for the different motor‐related regions of interest. For the construction of feature vectors, the feature vectors from two successive volumes in the image series for a trial were concatenated. With these spatial–temporal feature vectors, we obtained a 63.1% average DA (84.7% for the best subject) for the contralateral primary somatosensory cortex and a 46.0% average DA (71.0% for the best subject) for the contralateral primary motor cortex; both of these values were significantly above the chance level (20%). In addition, we implemented searchlight MVPA to search for informative regions in an unbiased manner across the whole brain. Furthermore, by applying searchlight MVPA to each volume of a trial, we visually demonstrated the information for decoding, both spatially and temporally. The results suggest that the non‐invasive fMRI technique may provide informative features for decoding individual finger movements and the potential of developing an fMRI‐based brain–machine interface for finger movement.     

3D modelling, gene expression mapping and post-mapping image analysis in the developing human brain

As human brain development proceeds, there are complex changes in size and shape, most notably in the developing forebrain. Molecular technologies enable us to characterise the gene expression patterns that underlie these changes. To interpret these patterns the location of expression must be identified and, often, gene expression patterns compared for several genes or across several developmental stages. To facilitate interpretation we have generated a set of three-dimensional models using a recently developed technique, optical projection tomography. The models act as a framework onto which gene expression patterns are mapped and anatomical domains identified using custom-designed software, MAPaint. Here, we demonstrate their use to compare forebrain development at two embryonic stages (Carnegie stages 18 and 21; 44 and 52 days post conception, respectively) and as a means of recording, storing and visualising gene expression data for three example genes EMX1, EMX2 and OTX2. Anatomical domains were also mapped to the models and the comparison of gene expression and anatomical data is demonstrated at Carnegie stage 21. The three-dimensional models and sophisticated software facilitate the analysis and visualisation of morphological changes and gene expression patterns during early brain development and can be applied to the development of other complex structures.     

LRRK2 expression linked to dopamine-innervated areas

OBJECTIVE: Leucine-rich repeat kinase 2 (LRRK2) has been linked to Parkinson's disease. Our study explores the expression of LRRK2 in human and rodent brain tissue. METHODS: We analyzed LRRK2 gene activity at the cellular level using in situ hybridization. RESULTS: We found a high and strikingly specific expression of LRRK2 mRNA in rodent striatum and parts of cortex and no signals in dopamine neurons. In human tissue, LRRK2 mRNA was found in the corresponding brain areas caudatus and putamen at lower levels and dopamine neurons were also devoid of LRRK2 mRNA. Expression levels in striatal tissue did not differ between Parkinson's disease patients and control subjects. INTERPRETATION: Unlike all other genes so far linked to Parkinson's disease, our results demonstrate that LRRK2 expression is particularly high in brain dopaminoceptive areas.     

Pig brain stereotaxic standard space: mapping of cerebral blood flow normative values and effect of MPTP-lesioning

The analysis of physiological processes in brain by position emission tomography (PET) is facilitated when images are spatially normalized to a standard coordinate system. Thus, PET activation studies of human brain frequently employ the common stereotaxic coordinates of Talairach. We have developed an analogous stereotaxic coordinate system for the brain of the Gottingen miniature pig, based on automatic co-registration of magnetic resonance (MR) images obtained in 22 male pigs. The origin of the pig brain stereotaxic space (0, 0, 0) was arbitrarily placed in the centroid of the pineal gland as identified on the average MRI template. The orthogonal planes were imposed using the line between stereotaxic zero and the optic chiasm. A series of mean MR images in the coronal, sagittal and horizontal planes were generated. To test the utility of the common coordinate system for functional imaging studies of minipig brain, we calculated cerebral blood flow (CBF) maps from normal minipigs and from minipigs with a syndrome of parkisonism induced by 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP)-poisoning. These maps were transformed from the native space into the common stereotaxic space. After global normalization of these maps, an undirected search for differences between the groups was then performed using statistical parametric mapping. Using this method, we detected a statistically significant focal increase in CBF in the left cerebellum of the MPTP-lesioned group. We expect the present approach to be of general use in the statistical parametric mapping of CBF and other physiological parameters in living pig brain.     

Study of cerebral gene expression densities using Voronoi analysis

As the available public cerebral gene expression image data increasingly grows, the demand for automated methods to analyze such large amount of data also increases. An important study that can be carried out on these data is related to the spatial relationship between gene expressions. Similar spatial density distribution of expression between genes may indicate they are functionally correlated, thus the identification of these similarities is useful in suggesting directions of investigation to discover gene interactions and their correlated functions. In this paper, we describe the use of a high-throughput methodology based on Voronoi diagrams to automatically analyze and search for possible local spatial density relationships between gene expression images. We tested this method using mouse brain section images from the Allen Mouse Brain Atlas public database. This methodology provided measurements able to characterize the similarity of the density distribution between gene expressions and allowed the visualization of the results through networks and Principal Component Analysis (PCA). These visualizations are useful to analyze the similarity level between gene expression patterns, as well as to compare connection patterns between region networks. Some genes were found to have the same type of function and to be near each other in the PCA visualizations. These results suggest cerebral density correlations between gene expressions that could be further explored.     

3D-catFISH: a system for automated quantitative three-dimensional compartmental analysis of temporal gene transcription activity imaged by fluorescence in situ hybridization

Fluorescence in situ hybridization (FISH) of neural activity-regulated, immediate-early gene (IEG) expression provides a method of functional brain imaging with cellular resolution. This enables the identification, in one brain, of which specific principal neurons were active during each of two distinct behavioral epochs. The unprecedented potential of this differential method for large-scale analysis of functional neural circuits is limited, however, by the time-intensive nature of manual image analysis. A comprehensive software tool for processing three-dimensional, multi-spectral confocal image stacks is described which supports the automation of this analysis. Nuclei counterstained with conventional DNA dyes and FISH signals indicating the sub-cellular distribution of specific, IEG RNA species are imaged using different spectral channels. The DNA channel data are segmented into individual nuclei by a three-dimensional multi-step algorithm that corrects for depth-dependent attenuation, non-isotropic voxels, and imaging noise. Intra-nuclear and cytoplasmic FISH signals are associated spatially with the nuclear segmentation results to generate a detailed tabular/database and graphic representation. Here we present a comprehensive validation of data generated by the automated software against manual quantification by human experts on hippocampal and parietal cortical regions (96.5% concordance with multi-expert consensus). The high degree of reliability and accuracy suggests that the software will generalize well to multiple brain areas and eventually to large-scale brain analysis.