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Recent decades have witnessed an increasing number of large to very large imaging studies, prominently in the field of neurodegenerative diseases. The datasets collected during these studies form essential resources for the research aiming at new biomarkers. Collecting, hosting, managing, processing, or reviewing those datasets is typically achieved through a local neuroinformatics infrastructure. In particular for organizations with their own imaging equipment, setting up such a system is still a hard task, and relying on cloud-based solutions, albeit promising, is not always possible. This paper proposes a practical model guided by core principles including user involvement, lightweight footprint, modularity, reusability, and facilitated data sharing. This model is based on the experience from an 8-year-old research center managing cohort research programs on Alzheimer’s disease. Such a model gave rise to an ecosystem of tools aiming at improved quality control through seamless automatic processes combined with a variety of code libraries, command line tools, graphical user interfaces, and instant messaging applets. The present ecosystem was shaped around XNAT and is composed of independently reusable modules that are freely available on GitLab/GitHub. This paradigm is scalable to the general community of researchers working with large neuroimaging datasets., The research leading to these results has received funding from “la Caixa” Foundation (ID 100010434), under agreement LCF/PR/GN17/50300004. Additional funding was obtained from the Universities and Research Secretariat, Ministry of Business and Knowledge of the Catalan In review 16 Government under grant no. 2017-SGR-892. JG is supported by the Spanish Ministry of Economy and Competitiveness (RYC-2013-13054). JG has received research support from the EU/EFPIA Innovative Medicines Initiative Joint Undertaking AMYPAD grant agreement no. 115952 and from Ministerio de Ciencia, Innovación y Universidades (grant agreement RTI2018-102261)., Peer Reviewed, Postprint (published version)

Research into hippocampal self-regulation abilities may help determine the clinical significance of hippocampal hyperactivity throughout the pathophysiological continuum of Alzheimer's disease. In this study, we aimed to identify the effects of amyloid-ii peptide 42 (amyloid-beta(42)) and phosphorylated tau on the patterns of functional connectomics involved in hippocampal downregulation. We identified 48 cognitively unimpaired participants (22 with elevated CSF amyloid-beta peptide 42 levels, 15 with elevated CSF phosphorylated tau levels, mean age of 62.705 +/- 4.628 years), from the population-based 'Alzheimer's and Families' study, with baseline MRI, CSF biomarkers, APOE genotyping and neuropsychological evaluation. We developed a closed-loop, real-time functional MRI neurofeedback task with virtual reality and tailored it for training downregulation of hippocampal subfield cornu ammonis 1 (CA1). Neurofeedback performance score, cognitive reserve score, hippocampal volume, number of apolipoprotein epsilon 4 alleles and sex were controlled for as confounds in all cross-sectional analyses. First, using voxel-wise multiple regression analysis and controlling for CSF biomarkers, we identified the effect of healthy ageing on eigenvector centrality, a measure of each voxel's overall influence based on iterative whole-brain connectomics, during hippocampal CAl downregulation. Then, controlling for age, we identified the effects of abnormal CSF amyloid-beta(42) and phosphorylated tau levels on eigenvector centrality during hippocampal CAl downregulation. Across subjects, our main findings during hippocampal downregulation were: (i) in the absence of abnormal biomarkers, age correlated with eigenvector centrality negatively in the insula and midcingulate cortex, and positively in the inferior temporal gyrus; (ii) abnormal CSF amyloid-beta(42) (<1098) correlated negatively with eigenvector centrality in the anterior cingulate cortex and primary motor cortex; and (iii)

This paper describes a new neuroimaging analysis toolbox that allows for the modeling of nonlinear effects at the voxel level, overcoming limitations of methods based on linear models like the GLM. We illustrate its features using a relevant example in which distinct nonlinear trajectories of Alzheimer's disease related brain atrophy patterns were found across the full biological spectrum of the disease. The open-source toolbox presented in this paper is available at https://github.com/imatge-upc/VNeAT., Comment: 4 pages + 1 page for acknowledgements and references. NIPS 2016 Workshop on Machine Learning for Health (NIPS ML4HC)

Subtraction of Ictal SPECT Co-registered to MRI (SISCOM) is an imaging technique used to localize the epileptogenic focus in patients with intractable partial epilepsy. The aim of this study was to determine the accuracy of registration algorithms involved in SISCOM analysis using FocusDET, a new user-friendly application. To this end, Monte Carlo simulation was employed to generate realistic SPECT studies. Simulated sinograms were reconstructed by using the Filtered BackProjection (FBP) algorithm and an Ordered Subsets Expectation Maximization (OSEM) reconstruction method that included compensation for all degradations. Registration errors in SPECT-SPECT and SPECT-MRI registration were evaluated by comparing the theoretical and actual transforms. Patient studies with well-localized epilepsy were also included in the registration assessment. Global registration errors including SPECT-SPECT and SPECT-MRI registration errors were less than 1.2 mm on average, exceeding the voxel size (3.32 mm) of SPECT studies in no case. Although images reconstructed using OSEM led to lower registration errors than images reconstructed with FBP, differences after using OSEM or FBP in reconstruction were less than 0.2 mm on average. This indicates that correction for degradations does not play a major role in the SISCOM process, thereby facilitating the application of the methodology in centers where OSEM is not implemented with correction of all degradations. These findings together with those obtained by clinicians from patients via MRI, interictal and ictal SPECT and video-EEG, show that FocusDET is a robust application for performing SISCOM analysis in clinical practice.

Subtraction of Ictal SPECT Co-registered to MRI (SISCOM) is an imaging technique used to localize the epileptogenic focus in patients with intractable partial epilepsy. The aim of this study was to determine the accuracy of registration algorithms involved in SISCOM analysis using FocusDET, a new user-friendly application. To this end, Monte Carlo simulation was employed to generate realistic SPECT studies. Simulated sinograms were reconstructed by using the Filtered BackProjection (FBP) algorithm and an Ordered Subsets Expectation Maximization (OSEM) reconstruction method that included compensation for all degradations. Registration errors in SPECT-SPECT and SPECT-MRI registration were evaluated by comparing the theoretical and actual transforms. Patient studies with well-localized epilepsy were also included in the registration assessment. Global registration errors including SPECT-SPECT and SPECT-MRI registration errors were less than 1.2 mm on average, exceeding the voxel size (3.32 mm) of SPECT studies in no case. Although images reconstructed using OSEM led to lower registration errors than images reconstructed with FBP, differences after using OSEM or FBP in reconstruction were less than 0.2 mm on average. This indicates that correction for degradations does not play a major role in the SISCOM process, thereby facilitating the application of the methodology in centers where OSEM is not implemented with correction of all degradations. These findings together with those obtained by clinicians from patients via MRI, interictal and ictal SPECT and video-EEG, show that FocusDET is a robust application for performing SISCOM analysis in clinical practice.

Schizophrenia is a disabling illness, characterized by a heterogeneous course including clinical deterioration and poor outcome. Accumulating findings in schizophrenia suggest that it might involve two pathophysiologic processes, one early in life (neurodevelopmental), and one after onset of the illness (neurodegenerative). Longitudinal imaging studies after onset of the illness may help to clarify these pathophysiological aspects of schizophrenia, but so far, probably due to methodological differences, there have been no conclusive results. The present study sets out to investigate longitudinal gray matter changes in patients with first-episode schizophrenia relative to healthy subjects over the first 4 years of the illness and the relation of gray matter changes in patients with functional outcome, using an objective automatic method not biased to one particular structure to analyze gray matter changes. Methods: We included 28 first-episode neuroleptic-naïve patients with DSM-IV diagnosis of schizophreniform disorder or schizophrenia, and 17 controls. 15 patients and 11 controls completed the longitudinal study and were reevaluated after four years. Gray matter changes over time were measured with voxel-based morphometry (VBM) using SPM5. Functional outcome was measured with the global assessment functioning scale (GAF). Results: Excessive decrease in gray matter was found in patients as compared to healthy individuals in the left superior temporal gyrus and right orbitofrontal gyrus, and excessive increase in the bilateral lingual gyrus and right cuneus. Additionally, gray matter changes in patients in the left lingual gyrus, right insula and right cerebellum, were inversely related to functional outcome (p < 0.001 uncorrected at voxel level, p < 0.05 family-wise-error corrected at cluster level). Conclusions: There are differing longitudinal gray matter changes in patients with schizophrenia during the first years of the illness as compared to healthy individual

Human amygdalar activation has been reported during facial emotion recognition (FER) studies, mostly using fast temporal resolution techniques (fMRI, H2 15O PET or MEG). The 18FDG PET technique has never been previously applied to FER studies. We decided to test whether amygdala response during FER tasks could be assessed with this technique. The study was conducted in 10 healthy right-handed volunteers who underwent two scans on different days in random order. Content of the tasks was either emotional (ET) or neutral (CT) and lasted for 17 1/2 min. Three SPM2 analyses were completed. The first, an ET-CT contrast, showed left amygdalar activation. The second ruled out order effect as a confounder factor. Finally, the whole brain contrast showed activation of the emotional recognition-related areas. Time responses and errors indicated high rates of accuracy in both tasks. We discuss the results and the role of habituation phenomena and the possibility of applying this technique to samples of patients with psychiatric disorders. In conclusion, our study reveals left amygdalar activation assessed with FDG PET, as well as other major emotion recognition-related brain areas during FER tasks. © 2008 Elsevier Ireland Ltd. All rights reserved.

BACKGROUND AND PURPOSE - Diffusion-weighted imaging (DWI) hyperintensities and apparent diffusion coefficient (ADC) hypointensities are MRI features of acute stroke. DWI alterations during ischemia recover with early reperfusion, but they can reappear later. Pronounced signal abnormalities early after stroke are associated with infarction, but the significance of subtle changes is unclear. Here we evaluated the degree and time course of regional signal intensity changes during the first 24 hours of reperfusion after transient ischemia, and we related them to the progression of the histopathological damage. METHODS - Rats (n=54) were subjected to 1-hour intraluminal middle cerebral artery occlusion to assess the dynamics of MRI signal intensity changes during the initial 24 hours and their correspondent histopathological features: 2,3,5-triphenyltetrazolium chloride (TTC) staining, and hematoxylin and eosin, and immunoreactivity to 70-kDa heat shock protein and to astroglial and microglial markers. RESULTS - This model of ischemia caused early striatal infarction but delayed necrosis in the cortex. The striatum showed marked MRI changes from 4 hours of reperfusion. By 12 hours, the striatal ADC signal intensity ratio to the homologous contralateral region was 30% reduced, and the TTC staining evidenced infarction. Contrarily, the cortical ADC ratio was only 15% reduced, and TTC staining was normal at 12 hours. After this time, the cortex showed sudden and pronounced (>30%) ADC signal intensity changes coincidentally with the manifestation of infarction, accompanied with severe vacuolation and unambiguous signs of neuronal and astroglial death. CONCLUSIONS - These findings suggest that minor changes in ADC signal intensity early after ischemia should not be underestimated because they may be harbingers of delayed infarction. © 2006 American Heart Association, Inc.

Background and Purpose - Hyperglycemia adversely affects the outcome of stroke. Global ischemia data support that the harmful effect of hyperglycemia is mediated by glucose-induced elevated plasma glucocorticoids. Here we sought to evaluate the negative effects of hyperglycemia on transient focal ischemia in the rat, and to test whether these could be prevented by inhibition of either corticosteroid production or neutrophil infiltration. Methods - Sprague-Dawley rats (n=217) were used. Ischemia was induced by 1 hour middle cerebral artery occlusion (n=196). Acute hyperglycemia was induced by IP injection of dextrose 30 minutes before ischemia. Neutrophil infiltration was blocked by neutropenia with vinblastine. Corticosterone synthesis was inhibited by chemical adrenalectomy with metyrapone. We measured MRI lesion and tissue infarct volumes, evaluated the neurological function, brain myeloperoxidase and matrix metalloproteinase-9 activities, and protein O-glycosylation. Results - Hyperglycemia significantly enhanced MRI diffusion-weighted imaging alterations, increased cortical, but not subcortical, infarct volume, worsened neurological score, and enhanced brain myeloperoxidase and matrix metalloproteinase-9 activities. Metyrapone did not prevent hyperglycemic brain damage despite successful reduction of plasma corticosterone. Yet, metyrapone tended to reduce cortical infarction and apparent diffusion coefficient lesion volume, indicating some negative contribution of corticosterone. Blocking neutrophil infiltration was also ineffective to prevent the harmful effect of hyperglycemia. A new finding was that O-linked glycosylation of cerebral proteins was increased under hyperglycemia. Conclusions - In transient middle cerebral artery occlusion, the hyperglycemia-exacerbated brain damage cannot be fully explained by the negative effects of plasma corticosteroids or neutrophil infiltration. The contribution of other intrinsic effects of high glucose, such as brain prot