JOAO RICARDO SATO
Projetos de Pesquisa
Unidades Organizacionais
LIM/44 - Laboratório de Ressonância Magnética em Neurorradiologia, Hospital das Clínicas, Faculdade de Medicina
13 resultados
Resultados de Busca
Agora exibindo 1 - 10 de 13
- Commentary: Functional connectome fingerprint: identifying individuals using patterns of brain connectivity(2017) BIAZOLI JR., Claudinei E.; SALUM, Giovanni A.; PAN, Pedro M.; ZUGMAN, Andre; AMARO JR., Edson; ROHDE, Luis A.; MIGUEL, Euripedes C.; JACKOWSKI, Andrea P.; BRESSAN, Rodrigo A.; SATO, Joao R.
- Stroke lesion in cortical neural circuits and post-stroke incidence of major depressive episode: A 4-month prospective study(2011) TERRONI, Luisa; AMARO JR., Edson; IOSIFESCU, Dan V.; TINONE, Gisela; SATO, Joao Ricardo; LEITE, Claudia Costa; SOBREIRO, Matildes F. M.; LUCIA, Mara Cristina Souza; SCAFF, Milberto; FRAGUAS, RenerioObjective. Little is known about the relevance of lesion in neural circuits reported to be associated with major depressive disorder. We investigated the association between lesion stroke size in the limbic-cortical-striatal-pallidal-thalamic (LCSPT) circuit and incidence of major depressive episode (MDE). Methods. We enrolled 68 patients with first-ever ischemic stroke and no history of major depressive disorder. Neurological and psychiatric examinations were performed at three time-points. We diagnosed major depressive episode, following DSM-IV criteria. Lesion location and volume were determined with magnetic resonance imaging, using a semi-automated method based on the Brodmann Cytoarchitectonic Atlas. Results. Twenty-one patients (31%) experienced major depressive episode. Larger lesions in the left cortical regions of the LCSPT circuit (3,760 vs. 660 mm(3); P = 0.004) were associated with higher incidence of MDE. Secondary analyses revealed that major depressive episode was associated with larger lesions in areas of the medial prefrontal cortex including the ventral (BA24) and dorsal anterior cingulate cortex (BA32) and subgenual cortex (BA25); and also the subiculum (BA28/36) and amygdala (BA34). Conclusions Our findings indicate that depression due to stroke is aetiologically related to the disruption of the left LCSPT circuit and support the relevance of the medial prefrontal cortex dysfunction in the pathophysiology of depression.
- Differences in Default Mode Network Connectivity in Meditators and Non-meditators During an Attention Task(2017) KOZASA, Elisa H.; SATO, Joao R.; RUSSELL, Tamara A.; BARREIROS, Maria A. M.; LACERDA, Shirley S.; RADVANY, Joao; MELLO, Luiz E. A. M.; AMARO JR., EdsonActivity in the default mode network (DMN) is reduced during non-self-referential goal-directed tasks in healthy individuals. In this study, we investigated differences in DMN functional connectivity between regular meditators and non-meditators during an attention paradigm. Non-meditators and regular meditators, matched by age, years of education, and gender were instructed to name the color of single words visually presented in a Stroop Word-Color Task (SWCT) adapted for functional magnetic resonance imaging (fMRI). The task was performed when the participants were not formally meditating. Logistic analysis based on imaging data indicated that the connectivity between the PCC (precuneus/posterior cingulate cortex) and the right and left parietal lobules helps differentiating regular meditators from non-meditators. Granger causality results showed that the activity in the PCC contains information to predict the activity in the right lateral parietal cortex and that the accuracy in this prediction is higher in regular meditators when compared to non-meditators. This suggests a stronger link between these two regions in regular meditators. In contrast to regular meditators, the PCC is more influenced by the left parietal region (related to the process of reading-which is the interference in the SWCT), and this region is more influenced by the PCC in non-meditators. These functional connectivity differences in the DMN between groups possibly reflect a higher degree of interference and probably more distraction during the SWCT in non-meditators compared with meditators.
- Wavelet correlation between subjects: A time-scale data driven analysis for brain mapping using fMRI(2011) LESSA, Patricia S.; SATO, Joao R.; CARDOSO, Elisson F.; NETO, Carlos G.; VALADARES, Ana Paula; AMARO JR., EdsonFunctional magnetic resonance imaging (fMRI) based on BOLD signal has been used to indirectly measure the local neural activity induced by cognitive tasks or stimulation. Most fMRI data analysis is carried out using the general linear model (GLM), a statistical approach which predicts the changes in the observed BOLD response based on an expected hemodynamic response function (HRF). In cases when the task is cognitively complex or in cases of diseases, variations in shape and/or delay may reduce the reliability of results. A novel exploratory method using fMRI data, which attempts to discriminate between neurophysiological signals induced by the stimulation protocol from artifacts or other confounding factors, is introduced in this paper. This new method is based on the fusion between correlation analysis and the discrete wavelet transform, to identify similarities in the time course of the BOLD signal in a group of volunteers. We illustrate the usefulness of this approach by analyzing fMRI data from normal subjects presented with standardized human face pictures expressing different degrees of sadness. The results show that the proposed wavelet correlation analysis has greater statistical power than conventional GLM or time domain intersubject correlation analysis.
- Temporal Stability of Network Centrality in Control and Default Mode Networks: Specific Associations with Externalizing Psychopathology in Children and Adolescents(2015) SATO, Joao Ricardo; BIAZOLI JR., Claudinei Eduardo; SALUM, Giovanni Abrahao; GADELHA, Ary; CROSSLEY, Nicolas; SATTERTHWAITE, Theodore D.; VIEIRA, Gilson; ZUGMAN, Andre; PICON, Felipe Almeida; PAN, Pedro Mario; HOEXTER, Marcelo Queiroz; ANES, Mauricio; MOURA, Luciana Monteiro; DEL'AQUILLA, Marco Antonio Gomes; AMARO JR., Edson; MCGUIRE, Philip; LACERDA, Acioly L. T.; ROHDE, Luis Augusto; MIGUEL, Euripedes Constantino; JACKOWSKI, Andrea Parolin; BRESSAN, Rodrigo AffonsecaAbnormal connectivity patterns have frequently been reported as involved in pathological mental states. However, most studies focus on ""static,"" stationary patterns of connectivity, which may miss crucial biological information. Recent methodological advances have allowed the investigation of dynamic functional connectivity patterns that describe non-stationary properties of brain networks. Here, we introduce a novel graphical measure of dynamic connectivity, called time-varying eigenvector centrality (tv-EVC). In a sample 655 children and adolescents (7-15 years old) from the Brazilian ""High Risk Cohort Study for Psychiatric Disorders"" who were imaged using resting-state fMRI, we used this measure to investigate age effects in the temporal in control and default-mode networks (CN/DMN). Using support vector regression, we propose a network maturation index based on the temporal stability of tv-EVC. Moreover, we investigated whether the network maturation is associated with the overall presence of behavioral and emotional problems with the Child Behavior Checklist. As hypothesized, we found that the tv-EVC at each node of CN/DMN become more stable with increasing age (P < 0.001 for all nodes). In addition, the maturity index for this particular network is indeed associated with general psychopathology in children assessed by the total score of Child Behavior Checklist (P = 0.027). Moreover, immaturity of the network was mainly correlated with externalizing behavior dimensions. Taken together, these results suggest that changes in functional network dynamics during neurodevelopment may provide unique insights regarding pathophysiology. (C) 2015 Wiley Periodicals, Inc.
- How Doctors Generate Diagnostic Hypotheses: A Study of Radiological Diagnosis with Functional Magnetic Resonance Imaging(2011) MELO, Marcio; SCARPIN, Daniel J.; AMARO JR., Edson; PASSOS, Rodrigo B. D.; SATO, Joao R.; FRISTON, Karl J.; PRICE, Cathy J.Background: In medical practice, diagnostic hypotheses are often made by physicians in the first moments of contact with patients; sometimes even before they report their symptoms. We propose that generation of diagnostic hypotheses in this context is the result of cognitive processes subserved by brain mechanisms that are similar to those involved in naming objects or concepts in everyday life. Methodology and Principal Findings: To test this proposal we developed an experimental paradigm with functional magnetic resonance imaging (fMRI) using radiological diagnosis as a model. Twenty-five radiologists diagnosed lesions in chest X-ray images and named non-medical targets (animals) embedded in chest X-ray images while being scanned in a fMRI session. Images were presented for 1.5 seconds; response times (RTs) and the ensuing cortical activations were assessed. The mean response time for diagnosing lesions was 1.33 (SD +/- 0.14) seconds and 1.23 (SD +/- 0.13) seconds for naming animals. 72% of the radiologists reported cogitating differential diagnoses during trials (3.5 seconds). The overall pattern of cortical activations was remarkably similar for both types of targets. However, within the neural systems shared by both stimuli, activation was significantly greater in left inferior frontal sulcus and posterior cingulate cortex for lesions relative to animals. Conclusions: Generation of diagnostic hypotheses and differential diagnoses made through the immediate visual recognition of clinical signs can be a fast and automatic process. The co-localization of significant brain activation for lesions and animals suggests that generating diagnostic hypotheses for lesions and naming animals are served by the same neuronal systems. Nevertheless, diagnosing lesions was cognitively more demanding and associated with more activation in higher order cortical areas. These results support the hypothesis that medical diagnoses based on prompt visual recognition of clinical signs and naming in everyday life are supported by similar brain systems.
- Meditation training increases brain efficiency in an attention task(2012) KOZASA, Elisa H.; SATO, Joao R.; LACERDA, Shirley S.; BARREIROS, Maria A. M.; RADVANY, Joao; RUSSELL, Tamara A.; SANCHES, Liana G.; MELLO, Luiz E. A. M.; AMARO JR., EdsonMeditation is a mental training, which involves attention and the ability to maintain focus on a particular object. In this study we have applied a specific attentional task to simply measure the performance of the participants with different levels of meditation experience, rather than evaluating meditation practice per se or task performance during meditation. Our objective was to evaluate the performance of regular meditators and non-meditators during an fMRI adapted Stroop Word-Colour Task (SWCT), which requires attention and impulse control, using a block design paradigm. We selected 20 right-handed regular meditators and 19 non-meditators matched for age, years of education and gender. Participants had to choose the colour (red, blue or green) of single words presented visually in three conditions: congruent, neutral and incongruent. Non-meditators showed greater activity than meditators in the right medial frontal, middle temporal, precentral and postcentral gyri and the lentiform nucleus during the incongruent conditions. No regions were more activated in meditators relative to non-meditators in the same comparison. Non-meditators showed an increased pattern of brain activation relative to regular meditators under the same behavioural performance level. This suggests that meditation training improves efficiency, possibly via improved sustained attention and impulse control.
- Identification of psychopathic individuals using pattern classification of MRI images(2011) SATO, Joao R.; OLIVEIRA-SOUZA, Ricardo de; THOMAZ, Carlos E.; BASILIO, Rodrigo; BRAMATI, Ivanei E.; AMARO JR., Edson; TOVAR-MOLL, Fernanda; HARE, Robert D.; MOLL, JorgeBackground: Psychopathy is a disorder of personality characterized by severe impairments of social conduct, emotional experience, and interpersonal behavior. Psychopaths consistently violate social norms and bring considerable financial, emotional, or physical harm to others and to society as a whole. Recent developments in analysis methods of magnetic resonance imaging (MRI), such as voxel-based-morphometry (VBM), have become major tools to understand the anatomical correlates of this disorder. Nevertheless, the identification of psychopathy by neuroimaging or other neurobiological tools (e. g., genetic testing) remains elusive. Methods/Principal findings: The main aim of this study was to develop an approach to distinguish psychopaths from healthy controls, based on the integration between pattern recognition methods and gray matter quantification. We employed support vector machines (SVM) and maximum uncertainty linear discrimination analysis (MLDA), with a feature-selection algorithm. Imaging data from 15 healthy controls and 15 psychopathic individuals (7 women in each group) were analyzed with SPM2 and the optimized VBM preprocessing routines. Participants were scanned with a 1.5 Tesla MRI system. Both SVM and MLDA achieved an overall leave-one-out accuracy of 80%, but SVM mapping was sparser than using MLDA. The superior temporal sulcus/gyrus (bilaterally) was identified as a region containing the most relevant information to separate the two groups. Conclusion/significance: These results indicate that gray matter quantitative measures contain robust information to predict high psychopathy scores in individual subjects. The methods employed herein might prove useful as an adjunct to the established clinical and neuropsychological measures in patient screening and diagnostic accuracy.
- Association between abnormal brain functional connectivity in children and psychopathology: A study based on graph theory and machine learning(2018) SATO, Joao Ricardo; BIAZOLI JR., Claudinei Eduardo; SALUM, Giovanni Abrahao; GADELHA, Ary; CROSSLEY, Nicolas; VIEIRA, Gilson; ZUGMAN, Andre; PICON, Felipe Almeida; PAN, Pedro Mario; HOEXTER, Marcelo Queiroz; AMARO JR., Edson; ANES, Mauricio; MOURA, Luciana Monteiro; DEL'AQUILLA, Marco Antonio Gomes; MCGUIRE, Philip; ROHDE, Luis Augusto; MIGUEL, Euripedes Constantino; JACKOWSKI, Andrea Parolin; BRESSAN, Rodrigo AffonsecaObjectives: One of the major challenges facing psychiatry is how to incorporate biological measures in the classification of mental health disorders. Many of these disorders affect brain development and its connectivity.In this study, we propose a novel method for assessing brain networks based on the combination of a graph theory measure (eigenvector centrality) and a one-class support vector machine (OC-SVM).Methods: We applied this approach to resting-state fMRI data from 622 children and adolescents. Eigenvector centrality (EVC) of nodes from positive- and negative-task networks were extracted from each subject and used as input to an OC-SVM to label individual brain networks as typical or atypical. We hypothesised that classification of these subjects regarding the pattern of brain connectivity would predict the level of psychopathology.Results: Subjects with atypical brain network organisation had higher levels of psychopathology (p<0.001). There was a greater EVC in the typical group at the bilateral posterior cingulate and bilateral posterior temporal cortices; and significant decreases in EVC at left temporal pole.Conclusions: The combination of graph theory methods and an OC-SVM is a promising method to characterise neurodevelopment, and may be useful to understand the deviations leading to mental disorders.
- Altered Functional Connectivity Between Precuneus and Motor Systems in Parkinson's Disease Patients(2017) THIBES, Raissa Benocci; NOVAES, Natalia P.; LUCATO, Leandro T.; CAMPANHOLO, Kenia R.; MELO, Luciano M.; LEITE, Claudia C.; AMARO JR., Edson; BARBOSA, Egberto Reis; BOR-SENG-SHU, Edson; CARDOSO, Ellison Fernando; SATO, Joao RicardoParkinson's disease (PD) is a neurodegenerative disorder that affects motor skills and cognition. As brain structure and function are compromised, functional magnetic resonance imaging (fMRI) can be a helpful tool to further investigate how intrinsic connectivity is impaired on the disease. The precuneus and medial prefrontal cortex (mPFC) are hub regions involved on the default mode network (DMN), a system that is active during rest and related to cognitive processes. We hypothesized that PD patients would present a decrease in functional connectivity among these two regions and the rest of the brain. Our goal was to identify regions in which functional connectivity to precuneus and mPFC was altered in PD. This study was based on resting-state fMRI data from 37 healthy subjects and 55 PD patients. Precuneus and mPFC were selected as seed regions in a whole brain functional connectivity mapping. As expected, we found abnormal connectivity from precuneus to motor system regions in PD patients, pointing toward a decreased connectivity in the disease. No significant group effects were found for the mPFC. Our findings suggest that internetwork connectivity from DMN to motor system is impaired in PD.