Visual Explanation for Identification of the Brain Bases for Developmental Dyslexia on fMRI Data

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Predicting Brain Age at Slice Level : Convolutional Neural Networks and Consequences for Interpretability

Funding Information: NE was financed in part by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior— Brasil (CAPES)—Finance Code 001. MM was financed in part by the Conselho Nacional de Pesquisa—Brasil (CNPq). Funding Information: Conflict of Interest: BF had a research grant from Pfizer outside of this study.Peer reviewe

Increased Glucose Activity in Subgenual Anterior Cingulate and Hippocampus of High Performing Older Adults, Despite Amyloid Burden

BACKGROUND: Individuals at 80 years of age or above with exceptional memory are considered SuperAgers (SA), an operationalized definition of successful cognitive aging. SA showed increased thickness and altered functional connectivity in the anterior cingulate cortex as a neurobiological signature. However, their metabolic alterations are yet to be uncovered. OBJECTIVE: Herein, a metabolic (FDG-PET), amyloid (PIB-PET), and functional (fMRI) analysis of SA were conducted. METHODS: Ten SA, ten age-matched older adults (C80), and ten cognitively normal middle-aged (C50) adults underwent cognitive testing and multimodal neuroimaging examinations. Anterior and posterior regions of the cingulate cortex and hippocampal areas were primarily examined, then subregions of anterior cingulate were segregated. RESULTS: The SA group showed increased metabolic activity in the left and right subgenual anterior cingulate cortex (sACC, p   0.05). The SA group also presented decreased connectivity between right sACC and posterior cingulate (p <  0.005, corrected) as compared to that of the C80 group. CONCLUSION: These results support the key role of sACC and hippocampus in SA, even in the presence of amyloid deposition. It also suggests that sACC may be used as a potential biomarker in older adults for exceptional memory ability. Further longitudinal studies measuring metabolic biomarkers may help elucidate the interaction between these areas in the cognitive aging process

Enhancing collaborative neuroimaging research: introducing COINSTAC Vaults for federated analysis and reproducibility

Collaborative neuroimaging research is often hindered by technological, policy, administrative, and methodological barriers, despite the abundance of available data. COINSTAC (The Collaborative Informatics and Neuroimaging Suite Toolkit for Anonymous Computation) is a platform that successfully tackles these challenges through federated analysis, allowing researchers to analyze datasets without publicly sharing their data. This paper presents a significant enhancement to the COINSTAC platform: COINSTAC Vaults (CVs). CVs are designed to further reduce barriers by hosting standardized, persistent, and highly-available datasets, while seamlessly integrating with COINSTAC's federated analysis capabilities. CVs offer a user-friendly interface for self-service analysis, streamlining collaboration, and eliminating the need for manual coordination with data owners. Importantly, CVs can also be used in conjunction with open data as well, by simply creating a CV hosting the open data one would like to include in the analysis, thus filling an important gap in the data sharing ecosystem. We demonstrate the impact of CVs through several functional and structural neuroimaging studies utilizing federated analysis showcasing their potential to improve the reproducibility of research and increase sample sizes in neuroimaging studies

Utiliza??o de m?todos de decomposi??o emp?ricos no pr?-processamento de dados de resson?ncia magn?tica funcional

Submitted by Setor de Tratamento da Informa??o - BC/PUCRS ([email protected]) on 2016-09-22T11:11:06Z No. of bitstreams: 1 DIS_NATHALIA_BIANCHINI_ESPER_COMPLETO.pdf: 4985859 bytes, checksum: 25572c47a501b6fd792c5a3384b19891 (MD5)Made available in DSpace on 2016-09-22T11:11:06Z (GMT). No. of bitstreams: 1 DIS_NATHALIA_BIANCHINI_ESPER_COMPLETO.pdf: 4985859 bytes, checksum: 25572c47a501b6fd792c5a3384b19891 (MD5) Previous issue date: 2016-03-31Coordena??o de Aperfei?oamento de Pessoal de N?vel Superior - CAPESFunctional Magnetic Resonance Imaging is a noninvasive technique used to map and explore brain networks through the changes in the oxyhemoglobin concentration that is caused by neural activity. One of the techniques to evaluate and measure these brain funcions is resting-state fMRI, which is indicated to subjects with some degree of neurological impairment since no cognitive task is necessary. The main problem of this exam is that it is more sensitive to noise during scanning - from physiological sources, for example, such as heart beating and breathing. The most common and hardest to correct is noise caused by a subject?s head movement. Given this fact, the objective of this thesis is to study and evaluate the effectiveness of implement empirical decomposition methods in the preprocessing stage of fMRI data. Empirical Mode Decomposition and Empirical Mean Curve Decomposition were the chosen algorithms because of their use in non-stationary and nonlinear signals. Thirty-three children participating in the ACERTA Project were classified in two groups: good readers (14 subjects) and poor readers (19 subjects). These data were submitted to five different preprocessing strategies: two for the usual preprocessing steps using or not the movements censoring; one for the Empirical Mode Decomposition method; and two for the Empirical Mean Curve Decomposition, being that one strategy uses changes proposed in this work in original algorithm. According to statistical analysis, the Empirical Mean Curve Decomposition, both the original and the modified, proved to be a promissing method for noise reduction in real fMRI data.A t?cnica de imagem por resson?ncia magn?tica funcional ? um exame n?o invasivo que permite mapear e explorar diversas fun??es cerebrais por meio de varia??es na concentra??o de oxi-hemoglobina nas regi?es de atividade neural. Uma das t?cnicas para avaliar e mapear essas fun??es cerebrais ? o exame em estado de repouso, que ? mais indicado em pacientes/volunt?rios que tenham algum tipo de problema neurol?gico, pois n?o faz o uso de tarefas cognitivas para gerar as imagens de mapeamento cerebral. O principal problema desse exame ? ser muito sens?vel aos diferentes tipos de ru?do presentes ao longo do exame, como os de origem fisiol?gica, principalmente provenientes da respira??o e dos batimentos card?acos. O tipo de ru?do mais comum e que mais afeta os dados ? causado pela movimenta??o da cabe?a do paciente/volunt?rio. Pensando nisso, esta disserta??o tem como objetivo estudar e avaliar a efic?cia da utiliza??o de m?todos emp?ricos de decomposi??o durante a etapa de pr?-processamento para a redu??o de ru?do em dados oriundos de exames por resson?ncia magn?tica funcional. Os algoritmos escolhidos foram o de Decomposi??o em Modos Emp?ricos e o de Decomposi??o Emp?rica da Curva M?dia. Esses algoritmos foram escolhidos por serem utilizados em sinais n?o-estacion?rios e n?o-lineares. Este estudo foi realizado com 33 crian?as do Projeto ACERTA (Avalia??o de Crian?as do Risco de Transtornos de Aprendizagem) classificadas em dois grupos: bons leitores (14 crian?as) e maus leitores (19 crian?as). Estes dados foram submetidos a cinco diferentes estrat?gias de pr?-processamento: duas para as etapas usuais de pr?-processamento utilizando ou n?o a etapa de censura dos movimentos; uma para o m?todo de Decomposi??o em Modos Emp?ricos; e duas para o m?todo de Decomposi??o Emp?rica da Curva M?dia, sendo que uma estrat?gia utiliza altera??es no algoritmo original propostas por este trabalho. De acordo com as an?lises estat?sticas realizadas, o algoritmo de Decomposi??o Emp?rica da Curva M?dia, tanto o original quanto o modificado, mostrou ser um m?todo promissor para a redu??o de ru?do nos dados reais de fMRI

Guillain–Barré syndrome associated with COVID-19: A systematic review

With the outbreak of coronavirus disease 2019 (COVID-19), the whole world was impacted by a pandemic. With the passage of time and knowledge about the dynamics and viral propagation of this disease, the short-, medium- and long-term repercussions are still being discovered. During this period, it has been learned that various manifestations of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) can affect the nervous system. In recent months, a variety of studies and case reports have proposed an association between COVID-19 and Guillain–Barré syndrome (GBS). The present work aims to systematically review the publications available to date to verify the relationship between these two pathologies and the characteristics of post-COVID GBS. There were 156 studies included in this work, resulting in a total of 436 patients. The findings show a mean age of the patients of 61,38 years and a male majority. The GBS symptoms began on average 19 days after the onset of COVID-19 infection. Regarding GBS, the main manifestations found included generalized weakness, reflex reduction, facial paresis/paralysis and hypoesthesia. As expected, the most common result in cerebrospinal fluid (CSF) analysis was albuminocytological dissociation. A pattern of blood analysis findings common to all patients was not observed due to non-standardization of case reports. Regarding electrodiagnostic studies, acute inflammatory demyelinating polyneuropathy (AIDP) appeared as the most common subtype of GBS in this study. There have been reports, to a lesser extent, of acute motor axonal neuropathy (AMAN), acute sensorimotor axonal neuropathy (AMSAN), the pharyngeal-cervical-brachial variant (PCB), and Miller-Fisher syndrome (MFS). The GBS treatment used was mainly intravenous immunoglobulin (IVIG) and plasma exchange (PLEX). Therefore, the present study reports a high prevalence of hospitalization and intensive care units ICU admissions, conjecturing a relationship between the development of GBS and the severity of COVID-19. Despite the severity, most patients showed improvement in GBS symptoms after treatment, and their residual symptoms did not include motor involvement. Therefore, the development of GBS seems to be related to COVID-19 infection, as reported by the present systematic review

Moving beyond processing- and analysis-related variation in resting-state functional brain imaging

When fields lack consensus standard methods and accessible ground truths, reproducibility can be more of an ideal than a reality. Such has been the case for functional neuroimaging, where there exists a sprawling space of tools and processing pipelines. We provide a critical evaluation of the impact of differences across five independently developed minimal preprocessing pipelines for functional magnetic resonance imaging. We show that, even when handling identical data, interpipeline agreement was only moderate, critically shedding light on a factor that limits cross-study reproducibility. We show that low interpipeline agreement can go unrecognized until the reliability of the underlying data is high, which is increasingly the case as the field progresses. Crucially we show that, when interpipeline agreement is compromised, so too is the consistency of insights from brain-wide association studies. We highlight the importance of comparing analytic configurations, because both widely discussed and commonly overlooked decisions can lead to marked variation. Functional connectivity estimates vary significantly across different functional magnetic resonance imaging preprocessing pipelines. Due to these variations, using seemingly similar minimal preprocessing does not ensure consistency.</p

Neural correlates of exceptional memory ability in SuperAgers: A multimodal approach using FDG-PET, PIB-PET, and MRI

Individuals at 80 years of age or above with exceptional memory are considered SuperAgers (SA). A multimodal brain analysis of SA may provide biomarkers of successful cognitive aging. Herein, a molecular (PET-FDG, PET-PIB), functional (fMRI) and structural analysis (MRI) of SA was conducted. Ten SA, ten age-matched older adults (C80) and ten cognitively normal middle-aged adults underwent cognitive testing and neuroimaging examinations. The relationship between cognitive scores and cingulate areas and hippocampus were examined. The SA group showed increased FDG SUVr in the left subgenual Anterior Cingulate Cortex (sACC, p0.05). These results support the key role of ACC in SA, even in the presence of amyloid deposition. It also suggests that sACC can be used as a potential memory biomarker in older adults

Functional connectivity development along the sensorimotor-association axis enhances the cortical hierarchy

Abstract Human cortical maturation has been posited to be organized along the sensorimotor-association axis, a hierarchical axis of brain organization that spans from unimodal sensorimotor cortices to transmodal association cortices. Here, we investigate the hypothesis that the development of functional connectivity during childhood through adolescence conforms to the cortical hierarchy defined by the sensorimotor-association axis. We tested this pre-registered hypothesis in four large-scale, independent datasets (total n = 3355; ages 5–23 years): the Philadelphia Neurodevelopmental Cohort (n = 1207), Nathan Kline Institute-Rockland Sample (n = 397), Human Connectome Project: Development (n = 625), and Healthy Brain Network (n = 1126). Across datasets, the development of functional connectivity systematically varied along the sensorimotor-association axis. Connectivity in sensorimotor regions increased, whereas connectivity in association cortices declined, refining and reinforcing the cortical hierarchy. These consistent and generalizable results establish that the sensorimotor-association axis of cortical organization encodes the dominant pattern of functional connectivity development