Linear registration to a standard space is one of the major steps in processing and analyzing magnetic resonance images (MRIs) of the brain. Here we present an overview of linear stereotaxic MRI registration and compare the performance of 5 publicly available and extensively used linear registration techniques in medical image analysis.

Techniques of stereotaxic surgery are commonly used in research laboratories by a range of students, technicians, and researchers. To meet the evolving requirements imposed by international legislation, and to promote the implementation of 3R rules (replacement, reduction, and refinement) by reducing experimental error, animal morbidity, and mortality, it is essential that standard operating procedures and proper conduct following such complex surgeries be precisely described and respected. The present report shows how refinements of our own neurosurgical techniques over decades, have significantly reduced the number of animals (rats) used in experiments and improved the animals' well-being during the post-surgical recovery period. The current pre-, per-, and post-surgical procedures used in our laboratory are detailed. We describe the practical aspects of stereotaxic neurosurgery that have been refined in our laboratory since 1992 and that cover various areas including appropriate anesthesia and pain management during and after surgery, methods to determine the stereotaxic coordinates, and the best approach to the target brain structure. The application of these optimal surgical methods that combine reliable and reproducible results with an acute awareness of ethics and animal welfare leads to a significant reduction in the number of animals included in experimental research in accordance with ethical and regulatory rules as required by the European Directive on laboratory animal welfare.

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Understanding amazingly complex brain functions and pathologies requires a complete cerebral vascular atlas in stereotaxic coordinates. Making a precise atlas for cerebral arteries and veins has been a century-old objective in neuroscience and neuropathology. Using micro-optical sectioning tomography (MOST) with a modified Nissl staining method, we acquired five mouse brain data sets containing arteries, veins, and microvessels. Based on the brain-wide vascular spatial structures and brain regions indicated by cytoarchitecture in one and the same mouse brain, we reconstructed and annotated the vascular system atlas of both arteries and veins of the whole mouse brain for the first time. The distributing patterns of the vascular system within the brain regions were acquired and our results show that the patterns of individual vessels are different from each other. Reconstruction and statistical analysis of the microvascular network, including derivation of quantitative vascular densities, indicate significant differences mainly in vessels with diameters less than 8 μm and large than 20 μm across different brain regions. Our precise cerebral vascular atlas provides an important resource and approach for quantitative studies of brain functions and diseases.

Replication defective lentiviruses or retroviruses are capable of stably integrating transgenes into the genome of an infected host cell. This technique has been widely used to encode fluorescent proteins, opto- or chemo-genetic controllers of cell activity, or heterologous expression of human genes in model organisms. These viruses have also successfully been used to deliver recombinases to relevant target sites in transgenic animals, or even deliver small hairpin or micro RNAs in order to manipulate gene expression. While these techniques have been fruitful, they rely on transgenic animals (recombinases) or frequently lack high efficacy and specificity (shRNA/miRNA). In contrast, the CRISPR/Cas system uses an exogenous Cas nuclease which targets specific sites in an organism's genome via an exogenous guide RNA in order to induce double stranded breaks in DNA. These breaks are then repaired by non-homologous end joining (NHEJ), producing insertion and deletion (indel) mutations that can result in deleterious missense or nonsense mutations. This manuscript provides detailed methods for the design, production, injection, and validation of single lenti/retro virus particles that can stably transduce neurons to express a fluorescent reporter, Cas9, and sgRNAs to knockout genes in a model organism.

Neurotrophic keratopathy (NK), a consequence of sensory denervation of the cornea, must be better understood in order to develop new approaches to therapy. The purpose of this study was to create a rat model for neurotrophic keratopathy by denervating the trigeminal nerve through a ventral approach with stereotaxic surgery. Stereotaxic coordinates were measured in 46 male Sprague Dawley rat cadavers for localization of V1. After further refining the coordinates in nine live animals, radiofrequency ablation was chosen as an effective method of disrupting the innervation to the cornea. Fifty-two live rats were treated with radiofrequency ablation to define the anatomical localization of the lesion by utilizing gross and histopathological studies. A gross lesion of the trigeminal nerve and/or ganglion was observed in 47 (90%) of the 52 animals. Histopathological studies revealed that all 52 animals had anatomical damage of the trigeminal innervation to the eye. Low mortality and little morbidity were observed in these animals. We have developed a rat model for neurotrophic keratopathy that is simple to produce, accurate in creating a lesion by utilizing stereotaxic techniques combined with radiofrequency ablation, and successful in decreasing morbidity and mortality.

We tested the hypothesis that transient microinjury to the brain elicits cellular and humoral responses that stimulate hippocampal neurogenesis. Brief stereotaxic insertion and removal of a microneedle into the right hippocampus resulted in (a) significantly increased expression of granulocyte-colony stimulating factor (G-CSF), the chemokine MIP-1a, and the proinflammatory cytokine IL12p40; (b) pronounced activation of microglia and astrocytes; and (c) increase in hippocampal neurogenesis. This study describes immediate and early humoral and cellular mechanisms of the brain's response to microinjury that will be useful for the investigation of potential neuroprotective and deleterious effects of deep brain stimulation in various neuropsychiatric disorders.

The gray short-tailed opossum (Monodelphis domestica) is a small marsupial gaining recognition as a laboratory animal in biomedical research. Despite numerous studies on opossum neuroanatomy, a consistent and comprehensive neuroanatomical reference for this species is still missing. Here we present the first three-dimensional, multimodal atlas of the Monodelphis opossum brain. It is based on four complementary imaging modalities: high resolution ex vivo magnetic resonance images, micro-computed tomography scans of the cranium, images of the face of the cutting block, and series of sections stained with the Nissl method and for myelinated fibers. Individual imaging modalities were reconstructed into a three-dimensional form and then registered to the MR image by means of affine and deformable registration routines. Based on a superimposition of the 3D images, 113 anatomical structures were demarcated and the volumes of individual regions were measured. The stereotaxic coordinate system was defined using a set of cranial landmarks: interaural line, bregma, and lambda, which allows for easy expression of any location within the brain with respect to the skull. The atlas is released under the Creative Commons license and available through various digital atlasing web services.

Infection of the Central Nervous System (CNS) by the encapsulated fungus Cryptococcus neoformans can lead to high mortality meningitis, most commonly in immunocompromised patients. While the mechanisms by which the fungus crosses the blood-brain barrier to initiate infection in the CNS are well recognized, there are still substantial unanswered questions about the disease progression once the fungus is established in the brain. C. neoformans is characterized by a glucuronoxylomannan (GXM)-rich polysaccharide capsule which has been implicated in immune evasion, but its role during the host CNS infection needs further elucidation. Therefore, the present study aims to examine these key questions about the mechanisms underlying cryptococcal meningitis progression and the impact of fungal GXM release by using an intracerebral rodent infection model via stereotaxic surgery. After developing brain infection, we analyzed distinct brain regions and found that while fungal load and brain weight were comparable one-week post-infection, there were region-specific histopathological (with and without brain parenchyma involvement) and disease manifestations. Moreover, we also observed a region-specific correlation between GXM accumulation and glial cell recruitment. Furthermore, mortality was associated with the presence of subarachnoid hemorrhaging and GXM deposition in the meningeal blood vessels and meninges in all regions infected. Our results show that using the present infection model can facilitate clinical and neuropathological observations during the progression of neurocryptococcosis. Importantly, this mouse model can be used to further investigate disease progression as it develops in humans.

Positron emission tomography (PET) is a non-invasive imaging tool for the evaluation of brain function and neuronal activity in normal and diseased conditions with high sensitivity. The macaque monkey serves as a valuable model system in the field of translational medicine, for its phylogenetic proximity to man. To translation of non-human primate neuro-PET studies, an effective and objective data analysis platform for neuro-PET studies is needed.

A stereotaxic brain atlas of the basal ganglia and thalamus of Macaca fascicularis presented here is designed with a surgical perspective. In this regard, all coordinates have been referenced to a line linking the anterior and posterior commissures (ac-pc line) and considering the center of the ac at the midline as the origin of the bicommissural space. The atlas comprises of 43 different plates (19 coronal levels, 10 sagittal levels and 14 horizontal levels). In addition to 'classical' cyto- and chemoarchitectural techniques such as the Nissl method and the acetylcholinesterase stain, several immunohistochemical stains have been performed in adjacent sections, including the detection of tyrosine hydroxylase, enkephalin, neurofilaments, parvalbumin and calbindin. In comparison to other existing stereotaxic atlases for M. fasicularis, this atlas has two main advantages: firstly, brain cartography is based on a wide variety of cyto- and chemoarchitectural stains carried out on adjacent sections, therefore enabling accurate segmentation. Secondly and most importantly, sagittal and horizontal planes are included. Sagittal planes are very useful for calculating oblique trajectories, whereas, clinical researchers engaged in neuroimaging studies will be more familiar with horizontal sections, as they use horizontal (also called "axial") brain images in their daily routine of their clinical practices.

This study constructs a rat brain T2 -weighted magnetic resonance imaging template including olfactory bulb and a compatible digital atlas. The atlas contains 624 carefully delineated brain structures based on the newest (2005) edition of rat brain atlas by Paxinos and Watson. An automated procedure, as an SPM toolbox, was introduced for spatially normalizing individual rat brains, conducting statistical analysis and visually localizing the results in the Atlas coordinate space. The brain template/atlas and the procedure were evaluated using functional images between rats with the right side middle cerebral artery occlusion (MCAO) and normal controls. The result shows that the brain region with significant signal decline in the MCAO rats was consistent with the occlusion position.

A stroke that includes the primary visual cortex unilaterally leads to a loss of visual field (VF) representation in the hemifield contralateral to the damage. While behavioral procedures for measuring the VF, such as perimetry, may indicate that a patient cannot see in a particular area, detailed psychophysical testing often detects the ability to perform detection or discrimination of visual stimuli ("blindsight"). The aim of this study was to determine whether functional magnetic resonance imaging (fMRI) could be used to determine whether perimetrically blind regions of the VF were still represented in VF maps reconstructed on the basis of visually evoked neural activity.

Functional magnetic resonance imaging (fMRI) has developed rapidly into a major non-invasive tool for studying the human brain. However, due to a variety of technical difficulties, it has yet to be widely adopted for use in alert, trained non-human primates. Our laboratory has been developing techniques for such fMRI studies. As background, we first consider basic principles of fMRI imaging, experimental design, and post-processing. We discuss appropriate MRI system hardware and components for conducting fMRI studies in alert macaques, and the animal preparation and behavior necessary for optimal experiments. Finally, we consider alternative fMRI techniques using exogenous contrast agents, arterial spin labeling, and more direct measures of neural activation.

Many neuroimaging applications deal with imbalanced imaging data. For example, in Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset, the mild cognitive impairment (MCI) cases eligible for the study are nearly two times the Alzheimer's disease (AD) patients for structural magnetic resonance imaging (MRI) modality and six times the control cases for proteomics modality. Constructing an accurate classifier from imbalanced data is a challenging task. Traditional classifiers that aim to maximize the overall prediction accuracy tend to classify all data into the majority class. In this paper, we study an ensemble system of feature selection and data sampling for the class imbalance problem. We systematically analyze various sampling techniques by examining the efficacy of different rates and types of undersampling, oversampling, and a combination of over and undersampling approaches. We thoroughly examine six widely used feature selection algorithms to identify significant biomarkers and thereby reduce the complexity of the data. The efficacy of the ensemble techniques is evaluated using two different classifiers including Random Forest and Support Vector Machines based on classification accuracy, area under the receiver operating characteristic curve (AUC), sensitivity, and specificity measures. Our extensive experimental results show that for various problem settings in ADNI, (1) a balanced training set obtained with K-Medoids technique based undersampling gives the best overall performance among different data sampling techniques and no sampling approach; and (2) sparse logistic regression with stability selection achieves competitive performance among various feature selection algorithms. Comprehensive experiments with various settings show that our proposed ensemble model of multiple undersampled datasets yields stable and promising results.

Subfield-specific measurements provide superior information in the early stages of neurodegenerative diseases compared to global hippocampal measurements. The overall goal was to systematically compare the performance of five representative manual and automated T1 and T2 based subfield labeling techniques in a sub-set of the ADNI2 population.

White matter hyperintensities (WMHs) are areas of abnormal signal on magnetic resonance images (MRIs) that characterize various types of histopathological lesions. The load and location of WMHs are important clinical measures that may indicate the presence of small vessel disease in aging and Alzheimer's disease (AD) patients. Manually segmenting WMHs is time consuming and prone to inter-rater and intra-rater variabilities. Automated tools that can accurately and robustly detect these lesions can be used to measure the vascular burden in individuals with AD or the elderly population in general. Many WMH segmentation techniques use a classifier in combination with a set of intensity and location features to segment WMHs, however, the optimal choice of classifier is unknown.

Arterial spin labeling (ASL) is the primary non-invasive MRI approach to measure baseline cerebral blood flow (CBF) in healthy subjects and patients. ASL also allows concurrent functional BOLD signal and CBF measurements, but the latter typically suffer from low contrast-to-noise (CNR) ratio. Ultra-high-field imaging significantly boosts BOLD signal CNR. However, it is contested whether also CBF CNR benefits from increasing magnetic field strength, especially given that technical challenges related to field inhomogeneities and power deposition constraints exist. Recently, we presented an optimized PASL technique that utilizes tr-FOCI inversion pulses and dielectric pads to overcome the temporal resolution limitations of previous 7T ASL implementations (Ivanov et al., in press; 2017). The primary goal of this study was to compare its performance to that of 3T ASL approaches - both pulsed ASL (PASL) and pseudo-continuous (pCASL) - concerning functional studies using simultaneous CBF and BOLD signal acquisition. To this aim, we investigated a wide range of parameters that can influence CBF and BOLD signal sensitivities: spatial resolution, labeling scheme, parallel imaging and echo time. We found that 7T ASL is superior in terms of CBF and BOLD temporal signal-to-noise ratio (SNR) and activation volume compared to all 3T ASL variants, in particular at high spatial resolution. Our results show that the advantages of 7T for ASL stem from increased image SNR, especially when parallel imaging is used. The gray matter baseline CBF was in good agreement for all 3T ASL variants, but a significantly lower value was obtained at 7T. The labeling scheme utilized was also found to significantly influence the measured perfusion territories CBF. In conclusion, a single-echo accelerated 7T PASL is recommended for high spatial and temporal resolution CBF and BOLD imaging, while a 3T dual-echo pCASL approach without parallel imaging may be preferred for low (i.e., 3mm isotropic and lower) resolution functional perfusion and BOLD applications.

As improvements in cortical surface modeling allowed accurate cortical topology in brain imaging studies, surface-based methods for the analysis of functional magnetic resonance imaging (fMRI) were introduced to overcome the topological deficiency of commonly used volume-based methods. The difference between the two methods is mainly due to the smoothing techniques applied. For practical applications, the surface-based methods need to quantitatively validate the accuracy of localizing activation. In this study, we evaluated the spatial accuracy of activation detected by the volume- and surface-based methods using simulated blood oxygenation level-dependent (BOLD) signals and MRI phantoms focusing on the influence of their smoothing techniques. T1- and T2-weighted phantoms were acquired from BrainWeb () and used to extract cortical surfaces and to generate echo planar imaging (EPI) data. Simulated BOLD signals as the gold standard of activation in our experiment were applied to the surfaces and projected to the volume space with random noise. Three-dimensional isotropic Gaussian kernel smoothing and two-dimensional heat kernel smoothing were applied to the volume- and surface-based methods. Sensitivity and 1-specificity, which are truly and falsely detected activations, and similarity measures, which are spatially and statistically similar for the gold standard and detected activations, were calculated. In the results, the surface-based method showed the sensitivity and similarity scores of about 12% higher than the volume-based method. In conclusion, the surface-based method guarantees better spatial accuracy for the localization of BOLD signal sources within the cortex than the volume-based method.

The development of MRI measures as biomarkers for neurodegenerative disease could prove extremely valuable for the assessment of neuroprotective therapies. Much current research is aimed at developing such biomarkers for use in people who are gene-positive for Huntington's disease yet exhibit few or no clinical symptoms of the disease (pre-HD). We acquired structural (T1), diffusion weighted and functional MRI (fMRI) data from 39 pre-HD volunteers and 25 age-matched controls. To determine whether it was possible to decode information about disease state from neuroimaging data, we applied multivariate pattern analysis techniques to several derived voxel-based and segmented region-based datasets. We found that different measures of structural, diffusion weighted, and functional MRI could successfully classify pre-HD and controls using support vector machines (SVM) and linear discriminant analysis (LDA) with up to 76% accuracy. The model producing the highest classification accuracy used LDA with a set of six volume measures from the basal ganglia. Furthermore, using support vector regression (SVR) and linear regression models, we were able to generate quantitative measures of disease progression that were significantly correlated with established measures of disease progression (estimated years to clinical onset, derived from age and genetic information) from several different neuroimaging measures. The best performing regression models used SVR with neuroimaging data from regions within the grey matter (caudate), white matter (corticospinal tract), and fMRI (insular cortex). These results highlight the utility of machine learning analyses in addition to conventional ones. We have shown that several neuroimaging measures contain multivariate patterns of information that are useful for the development of disease-state biomarkers for HD.