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High field MRI is an advanced technique for diagnostic and research purposes on animal models, such as the Beagle dog. In this context, studies on neuroscience applications, e.g. aging and neuro-pathologies, are currently increasing. This led to a need for reference values, in terms of volumetric assessment, for the structures typically involved. Nowadays, several canine brain MRI atlases have been provided. However, no reports are available regarding the measurements' reproducibility and little is known about the effect of formalin on MRI segmentation. Here, we assessed the segmentation variability of selected structures among operators (two operators segmented the same data) in a sample of 11 Beagle dogs. Then, we analyzed, for one Beagle dog, the longitudinal volumetric changes of these structures. We considered four conditions: in vivo, post mortem (after euthanasia), ex vivo (brain extracted and studied after 1 month in formalin, and after 12 months). The MRI data were collected with a 3 T scanner. Our findings suggest that the segmentation procedure was overall reproducible since only slight statistical differences were detected. In the post mortem/ ex vivo comparison, most structures showed a higher contrast, thereby leading to greater reproducibility between operators. We observed a net increase in the volume of the studied structures. This could be justified by the intrinsic relaxation time changes observed because of the formalin fixation. This led to an improvement in brain structure visualization and segmentation. To conclude, MRI-based segmentation seems to be a useful and accurate tool that allows longitudinal studies on formalin-fixed brains., Competing Interests: The authors have declared that no competing interests exist.

The aim of this work was to critically assess if functional near infrared spectroscopy (fNIRS) can be profitably used as a tool for noninvasive recording of brain functions and emotions in sheep. We considered an experimental design including advances in instrumentation (customized wireless multi-distance fNIRS system), more accurate physical modelling (two-layer model for photon diffusion and 3D Monte Carlo simulations), support from neuroanatomical tools (positioning of the fNIRS probe by MRI and DTI data of the very same animals), and rigorous protocols (motor task, startling test) for testing the behavioral response of freely moving sheep. Almost no hemodynamic response was found in the extra-cerebral region in both the motor task and the startling test. In the motor task, as expected we found a canonical hemodynamic response in the cerebral region when sheep were walking. In the startling test, the measured hemodynamic response in the cerebral region was mainly from movement. Overall, these results indicate that with the current setup and probe positioning we are primarily measuring the motor area of the sheep brain, and not probing the too deeply located cortical areas related to processing of emotions.

Magnetic Resonance (MR) is a non-invasive modality of choice for the evaluation of brain morphology, with superior performance as compared to other techniques. However, MR images are typically assessed qualitatively, thus relying on the experience of the involved radiologist. This may lead to errors of interpretation in the presence of subtle alterations and does not exploit the full potential of this technique as a quantitative diagnostic tool. To this end Magnetic Resonance Relaxometry (MRR), which is able to quantitively characterize the tissues under investigation through their relaxation rates, seems extremely promising. Many studies assessed the feasibility of relaxometry as a diagnostic tool in human brain disorders, with the most promising results obtained in the evaluation of neurodegenerative diseases and in the oncologic field. However, despite such extensive literature in human medicine, due to the lack of standardized protocols and the need of high-field MRI scanners, to date few studies have been performed on companion animals. In this work, first we describe relaxometry applications in human neuropathology and their possible extension to companion animals both in the experimental and clinical fields. Then, we present two experiments performed on a typical standard clinical scanner operating at 0.25 T to show that, despite the low field intensity, this technique may be promising even in the clinical setup. We tested the relaxometry protocol in a phantom study and then applied it to a real clinical case study. The results showed that this protocol used on a phantom led to a higher contrast, as compared to the standard approach. Furthermore, when applied to a real case study, this protocol revealed brain lesions undetected by the standard technique which were confirmed by a histopathological examination. These preliminary results are encouraging and support the development of this approach as an advanced diagnostic tool even in a clinical setting where low field MRI scanners are typically employed., (Copyright 2019 Biolife Sas. www.biolifesas.org.)

The aim of this preliminary study was to present a new approach for connectivity analysis in patients with severe acquired brain injury (ABI) that overcomes some of the difficulties created by anatomical abnormalities due to the brain injury. Using a data-driven approach, resting-state structural MRI (sMRI) and functional MRI (fMRI) data from three severe ABI patients - two with disorders of consciousness (DOC) and one who had recovered consciousness (non-DOC) - were integrated and analyzed. Parameters extracted from the distribution of the connectivity values, such as mean, standard deviation and skeweness, were considered. The distribution parameters estimated seem to provide an accurate multivariate classification of the considered cases that can be summarized as follows: connectivity in the severe ABI patients with DOC was on average lower than in the severe ABI non-DOC patient and healthy subjects. The dispersion of connectivity values of the severe ABI patients, non-DOC and DOC, was comparable, however the shape of the distribution was different in the non-DOC patient. Eventually, seed-based connectivity maps of the default mode Functional magnetic resonance imaging in disorders of consciousness: preliminary results of an innovative analysis of brain connectivity network show a pattern of increasing disruption of this network from the healthy subjects to non-DOC and DOC patients. Consistent results are obtained using an ICA-based approach..

The brain must dynamically integrate, coordinate, and respond to internal and external stimuli across multiple time scales. Non-invasive measurements of brain activity with fMRI have greatly advanced our understanding of the large-scale functional organization supporting these fundamental features of brain function. Conclusions from previous resting-state fMRI investigations were based upon static descriptions of functional connectivity (FC), and only recently studies have begun to capitalize on the wealth of information contained within the temporal features of spontaneous BOLD FC. Emerging evidence suggests that dynamic FC metrics may index changes in macroscopic neural activity patterns underlying critical aspects of cognition and behavior, though limitations with regard to analysis and interpretation remain. Here, we review recent findings, methodological considerations, neural and behavioral correlates, and future directions in the emerging field of dynamic FC investigations., (Copyright © 2013 Elsevier Inc. All rights reserved.)

Rationale: Adolescent rodents differ markedly from adults in several neuro-behavioural parameters. Moreover, 'paradoxical' responses to psychostimulants have been reported at this age., Objectives: Thus, we investigated the responses of adolescent (post-natal day, PND, 34 to 43) and adult (PND >60) Sprague-Dawley male rats to the psychostimulant drug methylphenidate (MPH). We used pharmacological magnetic resonance imaging (phMRI) performed at 4.7 T under isoflurane anaesthesia. Following anatomical MRI, axial gradient echo images were collected continuously. After baseline recording (32 min), animals received MPH (0 or 4 mg/kg i.p.) and were recorded for further 32 min., Results: Region-specific changes in the blood-oxygenation level dependent (BOLD) signal were evident as a function of age. As expected, among adults MPH induced an increase of BOLD signal in nucleus accumbens (NAcc) and prefrontal cortex (PFC), with no effects in the hippocampus (Hip). Notably, among adolescents, MPH induced a marked and generalised decrease of BOLD signal, which occurred earlier in NAcc and PFC whilst being delayed in the Hip. Any bias in BOLD responses was excluded by the measurement of physiological parameters., Conclusions: The present findings highlight the utility of phMRI in animal models. The peculiar negative BOLD effect found in adolescent rats may be suggestive of a reduced cerebro-vascular feedback and/or an increased MPH-induced neuronal activation. Data are relevant for a better understanding of brain/behavioural regulation during adolescent development. Moreover, a greater understanding of the differences between adult and adolescent drug responses will aid in the development of a more appropriate age-specific treatment strategy.

In this work an Empirical Markov Chain Monte Carlo Bayesian approach to analyse fMRI data is proposed. The Bayesian framework is appealing since complex models can be adopted in the analysis both for the image and noise model. Here, the noise autocorrelation is taken into account by adopting an AutoRegressive model of order one and a versatile non-linear model is assumed for the task-related activation. Model parameters include the noise variance and autocorrelation, activation amplitudes and the hemodynamic response function parameters. These are estimated at each voxel from samples of the Posterior Distribution. Prior information is included by means of a 4D spatio-temporal model for the interaction between neighbouring voxels in space and time. The results show that this model can provide smooth estimates from low SNR data while important spatial structures in the data can be preserved. A simulation study is presented in which the accuracy and bias of the estimates are addressed. Furthermore, some results on convergence diagnostic of the adopted algorithm are presented. To validate the proposed approach a comparison of the results with those from a standard GLM analysis, spatial filtering techniques and a Variational Bayes approach is provided. This comparison shows that our approach outperforms the classical analysis and is consistent with other Bayesian techniques. This is investigated further by means of the Bayes Factors and the analysis of the residuals. The proposed approach applied to Blocked Design and Event Related datasets produced reliable maps of activation.

Fricke-agarose gels have elicited much interest in the field of radiation dosimetry, as tissue-equivalent dosemeters. magnetic resonance (MR) relaxation rates are measured for dose reconstruction. A major problem of Fricke-agarose gels is the diffusion of the ferric ions formed after irradiation. Knowledge of the diffusion coefficient of ferric ions may be necessary. Xylene orange, a dye that specifically chelates ferric ions, was added to the Fricke gel system to reduce ion diffusion and, as the binding gives a coloured complex, to allow optical detection of ferric ions. Diffusion of ferric ions in two dimensions and time evolution of ion concentration were evaluated. MR images were obtained at different times after irradiation. Ferric ion distribution, the corresponding images and the doses at different times after irradiation were reconstructed taking into account the calculated diffusion coefficients. Diffusion was then estimated by means of two different optical methods. The agreement obtained supports the reliability of the MRI method and of the model.

The authors present a novel method for processing T(1)-weighted images acquired with Inversion-Recovery (IR) sequence. The method, developed within the Bayesian framework, takes into account a priori knowledge about the spatial regularity of the parameters to be estimated. Inference is drawn by means of Markov Chains Monte Carlo algorithms. The method has been applied to the processing of IR images from irradiated Fricke-agarose gels, proposed in the past as relative dosimeter to verify radiotherapeutic treatment planning systems. Comparison with results obtained from a standard approach shows that signal-to noise ratio (SNR) is strongly enhanced when the estimation of the longitudinal relaxation rate (R1) is performed with the newly proposed statistical approach. Furthermore, the method allows the use of more complex models of the signal. Finally, an appreciable reduction of total acquisition time can be obtained due to the possibility of using a reduced number of images. The method can also be applied to T(1) mapping of other systems.

In Fricke-agarose gels, an accurate determination of the spatial dose distribution is hindered by the diffusion of ferric ions. In this work, a model was developed to describe the diffusion process within gel samples of finite length and, thus, permit the reconstruction of the initial spatial distribution of the ferric ions. The temporal evolution of the ion concentration as a function of the initial concentration is derived by solving Fick's second law of diffusion in two dimensions with boundary reflections. The model was applied to magnetic resonance imaging data acquired at high spatial resolution (0.3 mm) and was found to describe accurately the observed diffusion effects. [ABSTRACT FROM AUTHOR]

Abstract: The Human Connectome Project (HCP) seeks to map the structural and functional connections between network elements in the human brain. Magnetoencephalography (MEG) provides a temporally rich source of information on brain network dynamics and represents one source of functional connectivity data to be provided by the HCP. High quality MEG data will be collected from 50 twin pairs both in the resting state and during performance of motor, working memory and language tasks. These data will be available to the general community. Additionally, using the cortical parcellation scheme common to all imaging modalities, the HCP will provide processing pipelines for calculating connection matrices as a function of time and frequency. Together with structural and functional data generated using magnetic resonance imaging methods, these data represent a unique opportunity to investigate brain network connectivity in a large cohort of normal adult human subjects. The analysis pipeline software and the dynamic connectivity matrices that it generates will all be made freely available to the research community. [Copyright &y& Elsevier]