A5068409000- Functional Brain Connectivity Studies
- Advanced Neuroimaging Techniques and Applications
- Advanced MRI Techniques and Applications
- Mental Health Research Topics
- Landslides and related hazards
- Neural dynamics and brain function
- EEG and Brain-Computer Interfaces
- Cryospheric studies and observations
- Complex Systems and Time Series Analysis
- earthquake and tectonic studies
- Theoretical and Computational Physics
- Multiple Sclerosis Research Studies
- Mental Health and Psychiatry
- Disaster Management and Resilience
- Fire effects on ecosystems
- Photoreceptor and optogenetics research
- Opinion Dynamics and Social Influence
- Fetal and Pediatric Neurological Disorders
- Sleep and Wakefulness Research
- Tryptophan and brain disorders
- Experimental and Theoretical Physics Studies
- Neonatal and fetal brain pathology
- Music Technology and Sound Studies
- Flood Risk Assessment and Management
- Complex Network Analysis Techniques
University of Lausanne
2024
École Polytechnique Fédérale de Lausanne
2017-2023
Wyss Center for Bio and Neuroengineering
2023
University of Geneva
2017-2022
École Polytechnique
2020-2021
University of the Philippines System
2018
University of the Philippines Diliman
2012-2017
Understanding how the anatomy of human brain constrains and influences formation large-scale functional networks remains a fundamental question in neuroscience. Here, given measured activity gray matter, we interpolate these signals into white matter on structurally-informed high-resolution voxel-level grid. The interpolated volumes reflect underlying anatomical information, revealing structures that mediate interaction between temporally coherent regions. Functional connectivity analyses...
Functional magnetic resonance imaging (fMRI) provides a window on the human brain at work. Spontaneous activity measured during resting-state has already provided many insights into function. In particular, recent interest in dynamic interactions between regions increased need for more advanced modeling tools. Here, we deploy fMRI deconvolution technique to express temporal fluctuations as combination of large-scale functional network profiles. Then, building upon novel sparse coupled hidden...
Functional dissociations in the brain observed during non-rapid eye movement (NREM) sleep have been associated with reduced information integration and impaired consciousness that accompany increasing depth. Here, we explored dynamical properties of large-scale functional networks derived from transient activity using magnetic resonance imaging. Spatial maps generally display significant modifications terms their tendency to occur across wakefulness NREM sleep. Unexpectedly, almost all...
Structural brain graphs are conventionally limited to defining nodes as gray matter regions from an atlas, with edges reflecting the density of axonal projections between pairs nodes. Here we explicitly model entire set voxels within a mask high-resolution, subject-specific graphs. We define strength local voxel-to-voxel connections using diffusion tensors and orientation distribution functions derived MRI data. study graphs’ Laplacian spectral properties on data Human Connectome Project....
Abstract. We propose a cellular automata model for earthquake occurrences patterned after the sandpile of self-organized criticality (SOC). By incorporating single parameter describing probability to target most susceptible site, successfully reproduces statistical signatures seismicity. The energy distributions closely follow power-law density functions (PDFs) with scaling exponent around −1. 6, consistent expectations Gutenberg–Richter (GR) law, wide range targeted triggering values....
Structural brain graphs are conventionally limited to defining nodes as gray matter regions from an atlas, with edges reflecting the density of axonal projections between pairs nodes. Here we explicitly model entire set voxels within a mask high-resolution, subject-specific graphs.
Abstract One way to increase the statistical power and generalizability of neuroimaging studies is collect data at multiple sites or merge cohorts. However, this usually comes with site-related biases due heterogeneity scanners acquisition parameters, negatively impacting sensitivity. Brain structural connectomes are not an exception: Being derived from T1-weighted diffusion-weighted magnetic resonance images, connectivity impacted by differences in imaging protocol. Beyond minimizing...
Understanding the organizational principles of human brain activity at systems level remains a major challenge in network neuroscience. Here, we introduce fully data-driven approach based on graph learning to extract meaningful repeating patterns from regionally-averaged timecourses. We use Graph Laplacian Mixture Model (GLMM), generative model that treats functional data as collection signals expressed multiple underlying graphs. By exploiting covariance between regions, these graphs can be...
Causal interactions between specific psychiatric symptoms could contribute to the heterogenous clinical trajectories observed in early psychopathology. Current diagnostic approaches merge manifestations that co-occur across subjects and significantly hinder our understanding of pathways connecting individual symptoms. Network analysis techniques have emerged as alternative help shed light on complex dynamics The present study attempts address two main limitations opinion hindered application...
Background: Modifications in brain function remain relatively unexplored progressive multiple sclerosis (PMS), despite their potential to provide new insights into the pathophysiology of disease at this stage. Objectives: To characterize dynamics functional networks rest patients with PMS, and relation clinical disability. Methods: Thirty-two PMS underwent cognitive assessment. The dynamic properties networks, retrieved from transient activity, were obtained 25 healthy controls (HCs)....
Non-invasive characterization of brain structure has been made possible by the introduction magnetic resonance imaging (MRI). Graph modeling structural connectivity useful, but is often limited to defining nodes as regions from a atlas. Here, we propose two methods for encoding in huge graph at voxel-level resolution (i.e., 850'000 voxels) based on diffusion tensor (DTI) and orientation density functions (ODF), respectively. The eigendecomposition graph's Laplacian operator then showing...
Abstract Background Modifications in brain function remain relatively unexplored progressive multiple sclerosis (PMS), despite their potential to provide new insights into the pathophysiology of this disease stage. Objectives To characterize dynamics functional networks at rest patients with PMS, and relation clinical disability. Methods Thirty-two PMS underwent cognitive assessment. The dynamic properties networks, retrieved from transient activity, were obtained 25 healthy controls (HC)....
In the human brain, corpus callosum is major white-matter commissural tract enabling transmission of sensory-motor, and higher level cognitive information between homotopic regions two cerebral hemispheres. Despite developmental absence (i.e., agenesis) (AgCC), functional connectivity preserved, including interhemispheric connectivity. Subcortical structures have been hypothesised to provide alternative pathways enable this preservation. To test hypothesis, we used Magnetic Resonance Imaging...
Abstract Functional dissociations in the brain observed during non-rapid eye movement (NREM) sleep have been mainly associated with reduced information integration and impaired consciousness that accompany increasing depth. Most of studies evaluated this relation mostly focused on spatial alterations networks across various vigilance states. Here, we explored dynamical properties large-scale functional derived from transients or moments activity changes fMRI using two complementary...
Abstract. We propose a cellular automata model for earthquake occurrences patterned after the sandpile of self-organized criticality (SOC). By incorporating single parameter describing probability to target most susceptible site, successfully reproduces statistical signatures seismicity. The energy (magnitude) distributions closely follow power-law density functions (PDFs) with scaling exponent −5/3, consistent expectations Gutenberg–Richter (GR) law, wide range targeted-triggering values;...
Anatomy of the human brain constrains formation large-scale functional networks. Here, given measured activity in gray matter, we interpolate these signals into white matter on a structurally-informed high-resolution voxel-level grid. The interpolated volumes reflect underlying anatomical information, revealing structures that mediate signal flow between temporally coherent regions. Functional connectivity analyses reveal an enriched picture default mode network (DMN) and its subcomponents,...
Abstract There is a growing recognition that psychiatric symptoms have the potential to causally interact with one another. Particularly in earliest stages of psychopathology dynamic interactions between could contribute heterogeneous and cross-diagnostic clinical evolutions. Current approaches attempt merge manifestations co-occur across subjects therefore significantly hinder our understanding pathways connecting individual symptoms. Network shed light on complex dynamics early...