Realistically Coupled Neural Mass Models Can Generate EEG Rhythms. - Roberto C. Sotero; Nelson J. Trujillo-Barreto; Yasser Iturria-Medina; Felix Carbonell; Juan C. Jiménez (Neural Comput., 2007)

Modelling the role of excitatory and inhibitory neuronal activity in the generation of the BOLD signal. - Roberto C. Sotero; Nelson J. Trujillo-Barreto (NeuroImage, 2007)

Studying the human brain anatomical network via diffusion-weighted MRI and Graph Theory. - Yasser Iturria-Medina; Roberto C. Sotero; Erick Jorge Canales-Rodríguez; Yasser Alemán-Gómez; Lester Melie-García (NeuroImage, 2008)

Biophysical model for integrating neuronal activity, EEG, fMRI and metabolism. - Roberto C. Sotero; Nelson J. Trujillo-Barreto (NeuroImage, 2008)

Identification and comparison of stochastic metabolic/hemodynamic models (sMHM) for the generation of the BOLD signal. - Roberto C. Sotero; Nelson J. Trujillo-Barreto; Juan C. Jiménez; Felix Carbonell; Rafael Rodriguez-Rojas (J. Comput. Neurosci., 2009)

Dynamical Mean Field Model of a Neural-Glial Mass. - Roberto C. Sotero; Ramón Martínez-Cancino (Neural Comput., 2010)

Energy-based stochastic control of neural mass models suggests time-varying effective connectivity in the resting state. - Roberto C. Sotero; Amir Shmuel (J. Comput. Neurosci., 2012)

Epidemic Spreading Model to Characterize Misfolded Proteins Propagation in Aging and Associated Neurodegenerative Disorders. - Yasser Iturria-Medina; Roberto C. Sotero; Paule-Joanne Toussaint; Alan C. Evans (PLoS Comput. Biol., 2014)

Multifocus image fusion via the Hartley transform. - Mehdy Dousty; Sabalan Daneshvar; Roberto C. Sotero (CCECE, 2016)

Topology, Cross-Frequency, and Same-Frequency Band Interactions Shape the Generation of Phase-Amplitude Coupling in a Neural Mass Model of a Cortical Column. - Roberto C. Sotero (PLoS Comput. Biol., 2016)

Multifactorial causal model of brain (dis)organization and therapeutic intervention: Application to Alzheimer's disease. - Yasser Iturria-Medina; Felix Carbonell; Roberto C. Sotero; François Chouinard-Decorte; Alan C. Evans (NeuroImage, 2017)

Design of optimal nonlinear network controllers for Alzheimer's disease. - Lazaro M. Sanchez-Rodriguez; Yasser Iturria-Medina; Erica A. Baines; Sabela C. Mallo; Mehdy Dousty; Roberto C. Sotero (PLoS Comput. Biol., 2018)

Measuring transient phase-amplitude coupling using local mutual information. - Ramón Martínez-Cancino; Joseph Heng; Arnaud Delorme; Kenneth Kreutz-Delgado; Roberto C. Sotero; Scott Makeig (NeuroImage, 2019)

What Can Local Transfer Entropy Tell Us about Phase-Amplitude Coupling in Electrophysiological Signals? - Ramón Martínez-Cancino; Arnaud Delorme; Johanna Wagner; Kenneth Kreutz-Delgado; Roberto C. Sotero; Scott Makeig (Entropy, 2020)

Detecting brain network communities: Considering the role of information flow and its different temporal scales. - Lazaro M. Sanchez-Rodriguez; Yasser Iturria-Medina; Pauline Mouches; Roberto C. Sotero (NeuroImage, 2021)

Solving large-scale MEG/EEG source localization and functional connectivity problems simultaneously using state-space models. - Jose Miguel Sanchez Bornot; Roberto C. Sotero; J. A. Scott Kelso; Damien Coyle (CoRR, 2022)

Exploring Correlation-Based Brain Networks with Adaptive Signed Random Walks. - Roberto C. Sotero; Jose Miguel Sanchez Bornot (CISP-BMEI, 2023)

Dynamic Source Localization and Functional Connectivity Estimation With State-Space Models: Preliminary Feasibility Analysis. - Jose Miguel Sanchez Bornot; Roberto C. Sotero; Damien Coyle (ICASSP Workshops, 2023)

Improving fMRI-based Autism Spectrum Disorder Classification with Random Walks-informed Feature Extraction and Selection. - Roberto Carlos Sotero; Jose Miguel Sanchez Bornot; Yasser Iturria-Medina (ICBRA, 2023)

Examining the Impact of fMRI Preprocessing Steps on Machine Learning-Based Classification of Autism Spectrum Disorder. - Roberto C. Sotero; Jose Miguel Sanchez Bornot; Iman Shaharabi-Farahani; Yasser Iturria-Medina (ICMHI, 2023)

Machine Learning for Time Series Forecasting Using State Space Models. - Jose Miguel Sanchez Bornot; Roberto C. Sotero (IDEAL, 2023)

Hebbian Learning-Guided Random Walks for Enhanced Community Detection in Correlation-Based Brain Networks. - Roberto C. Sotero; Jose Miguel Sanchez Bornot (IDEAL, 2023)

Parameter Estimation in Brain Dynamics Models from Resting-State fMRI Data using Physics-Informed Neural Networks. - Roberto C. Sotero; Jose Miguel Sanchez Bornot; Iman Shaharabi-Farahani (ICBEA, 2024)

Estimating the Excitatory-Inhibitory Balance from Electrocorticography Data using Physics-Informed Neural Networks. - Roberto Carlos Sotero; Jose Miguel Sanchez Bornot (ICBRA, 2024)

A Machine Learning Approach for Identifying Anatomical Biomarkers of Early Mild Cognitive Impairment. - Alwani Liyana Ahmad; Jose Miguel Sanchez Bornot; Roberto C. Sotero; Damien Coyle; Zamzuri Idris; Ibrahima Faye (CoRR, 2024)

Towards improving Alzheimer's intervention: a machine learning approach for biomarker detection through combining MEG and MRI pipelines. - Alwani Liyana Ahmad; Jose Miguel Sanchez Bornot; Roberto C. Sotero; Damien Coyle; Zamzuri Idris; Ibrahima Faye (CoRR, 2024)

Solving large-scale MEG/EEG source localisation and functional connectivity problems simultaneously using state-space models. - Jose Miguel Sanchez Bornot; Roberto C. Sotero; J. A. Scott Kelso; Özgür Simsek; Damien Coyle (NeuroImage, 2024)

Tunnelling Through Time Series: A Probabilistic Visibility Graph for Local and Global Pattern Discovery. - Roberto C. Sotero; Jose Miguel Sanchez Bornot (CoRR, 2025)