A5029606860- Functional Brain Connectivity Studies
- Neural dynamics and brain function
- EEG and Brain-Computer Interfaces
- Advanced Neuroimaging Techniques and Applications
- Mental Health Research Topics
- Obsessive-Compulsive Spectrum Disorders
- Optical Imaging and Spectroscopy Techniques
- Advanced MRI Techniques and Applications
- Autism Spectrum Disorder Research
- Attention Deficit Hyperactivity Disorder
- Neural and Behavioral Psychology Studies
- Bioinformatics and Genomic Networks
- Transcranial Magnetic Stimulation Studies
- Anxiety, Depression, Psychometrics, Treatment, Cognitive Processes
- Gene expression and cancer classification
- Gene Regulatory Network Analysis
- Heart Rate Variability and Autonomic Control
- Schizophrenia research and treatment
- Neurological disorders and treatments
- Neurobiology of Language and Bilingualism
- Neuroscience, Education and Cognitive Function
- Dementia and Cognitive Impairment Research
- Neural Networks and Applications
- Alzheimer's disease research and treatments
- Pain Management and Treatment
Universidade Federal do ABC
2016-2025
Hospital Israelita Albert Einstein
2020-2025
Universidade de São Paulo
2009-2023
National Council for Scientific and Technological Development
2014-2023
Universidade Federal de São Paulo
2014-2023
Insper
2023
Centro Universitário FEI
2023
Universidade Federal do Rio Grande do Sul
2015-2022
Hospital de Clínicas de Porto Alegre
2015-2022
Tufts University
2022
The employment of functional near-infrared spectroscopy (fNIRS) as a method brain imaging has increased over the last few years due to its portability, low-cost and robustness subject movement. Experiments with fNIRS are designed in face limited number sources detectors (optodes) be positioned on selected portion(s) scalp. optodes locations represent an expectation assessing cortical regions relevant experiment's hypothesis. However, this translation process remains challenge for...
The effect of persistent symptoms or compensatory processes related to cognitive dysfunction in obsessive-compulsive disorder may contribute brain structure alterations OCD, indicating that age is an important factor evaluating changes gray and white matter volumes.
Meditation is a mental training, which involves attention and the ability to maintain focus on particular object. In this study we have applied specific attentional task simply measure performance of participants with different levels meditation experience, rather than evaluating practice per se or during meditation. Our objective was evaluate regular meditators non-meditators an fMRI adapted Stroop Word-Colour Task (SWCT), requires impulse control, using block design paradigm. We selected...
This report is the second part of a comprehensive two-part series aimed at reviewing an extensive and diverse toolkit novel methods to explore brain health function. While first focused on neurophotonic tools mostly applicable animal studies, here, we highlight optical spectroscopy imaging relevant noninvasive human studies. We outline current state-of-the-art technologies software advances, most recent impact these neuroscience clinical applications, identify areas where innovation needed,...
Spatial cognition plays a crucial role in academic achievement, particularly science, technology, engineering, and mathematics (STEM) domains. Immersive virtual environments (VRs) have the growing potential to reduce cognitive load improve spatial reasoning. However, traditional methods struggle assess mental effort required for visuospatial processes due difficulty verbalizing actions other limitations self-reported evaluations. In this neuroergonomics study, we aimed capture neural...
With the development of DNA hybridization microarray technologies, nowadays it is possible to simultaneously assess expression levels thousands tens genes. Quantitative comparison microarrays uncovers distinct patterns gene expression, which define different cellular phenotypes or responses drugs. Due technical biases, normalization intensity a pre-requisite performing further statistical analyses. Therefore, choosing suitable approach for can be critical, deserving judicious...
The objective of this study is to present the rationale, methods, design and preliminary results from High Risk Cohort Study for Development Childhood Psychiatric Disorders. We describe sample selection components each phases study, its instruments, tasks procedures. Preliminary are limited baseline phase encompass: (i) efficacy oversampling procedure used increase frequency both child family psychopathology; (ii) interrater reliability (iii) role differential participation rate. A total...
Assessing the neural correlates of motor and cognitive processes under naturalistic experimentation is challenging due to movement constraints traditional brain imaging technologies. The recent advent portable technologies that are less sensitive motion artifacts such as Functional Near Infrared Spectroscopy (fNIRS) have been made possible study function in freely-moving participants. In this paper, we describe a series proof-of-concept experiments examining potential fNIRS assessing...
Abstract Background To understand the molecular mechanisms underlying important biological processes, a detailed description of gene products networks involved is required. In order to define and such networks, some statistical methods are proposed in literature estimate regulatory from time-series microarray data. However, several problems still need be overcome. Firstly, information flow inferred, addition correlation between genes. Secondly, we usually try identify large number genes...
Neuroimaging-based models contribute to increasing our understanding of schizophrenia pathophysiology and can reveal the underlying characteristics this other clinical conditions. However, considerable variability in reported neuroimaging results mirrors heterogeneity disorder. Machine learning methods capable representing invariant features could circumvent problem. In structural MRI study, we trained a deep model known as belief network (DBN) extract from brain morphometry data...
Previous studies have implicated aberrant reward processing in the pathogenesis of adolescent depression. However, no study has used functional connectivity within a distributed network, assessed using resting-state MRI (fMRI), to predict onset depression adolescents. This network-based at baseline depressive disorder follow-up community sample adolescents.A total 637 children 6-12 years old underwent fMRI. Discovery and replication analyses tested intrinsic (iFC) among nodes putative...
Machine learning is becoming an increasingly popular approach for investigating spatially distributed and subtle neuroanatomical alterations in brain-based disorders. However, some machine models have been criticized requiring a large number of cases each experimental group, resembling "black box" that provides little or no insight into the nature data. In this article, we propose alternative conceptual practical disorders which aim to overcome these limitations. We used artificial neural...
The framework of graph theory provides useful tools for investigating the neural substrates neuropsychiatric disorders. Graph description measures may be as predictor variables in classification procedures. Here, we consider several centrality features a algorithm to identify nodes resting-state networks containing predictive information that can discriminate between typical developing children and patients with attention-deficit/hyperactivity disorder (ADHD). prediction was based on support...
Ritual use of ayahuasca, an amazonian Amerindian medicine turned sacrament in syncretic religions Brazil, is rapidly growing around the world. Because this internationalization, a comprehensive understanding pharmacological mechanisms action brew and neural correlates modified states consciousness it induces important. Employing combination electroencephalogram (EEG) recordings quantification ayahuasca's compounds their metabolites systemic circulation we found ayahuasca to induce biphasic...
Objective: Brain imaging communities focusing on different diseases increasingly start collaborating and pooling data to perform well-powered meta- mega-analyses. Some methodologists claim that a one-stage individual-participant mega-analysis can be superior two-stage aggregated meta-analysis, since more detailed computations performed in mega-analysis. Before definitive conclusions regarding the performance of either method drawn, it is necessary critically evaluate methodology of, results...
Abstract Brain morphology varies across the ageing trajectory and prediction of a person's age using brain features can aid detection abnormalities in process. Existing studies on such “brain prediction” vary widely terms their methods type data, so at present most accurate generalisable methodological approach is unclear. Therefore, we used UK Biobank data set ( N = 10,824, range 47–73) to compare performance machine learning models support vector regression, relevance regression Gaussian...