Intelligence is a very general mental capacity (g) that integrates and coordinates the functioning of over 80 mental abilities identified by scientific research. Perceiving, attending, memorizing, speaking, reasoning, or creating are mental activities that must be orchestrated by our intellect. Some individuals exhibit a greater capacity for orchestration (g) than others, and understanding the basis of these differences is an essential goal of the Briceño Zapata Institute of Neuroscience.
Understanding the biomolecular and brain mechanisms underlying human intelligence is fundamental. Based on this knowledge, we aim to develop neuro-computational models that guide neuro-modulation procedures to enhance that general mental capacity (g).
Neuroimaging studies, both functional and structural, based on magnetic resonance imaging (MRI) recordings, as well as Electroencephalography (EEG) and Magnetoencephalography (MEG), allow for the collection of neuro-data that will be complemented with information on the micro-structural organization of the brain (analysis of micro-circuitry using human tissues via microscopy), as well as proteomics and genomics.
These neuro-data will feed into two types of neuro-computational models: spiking networks and neural mass models. These in-silico models will serve as a framework for experimentally modifying parameters that will help understand the specific mechanisms governing the anatomical-functional organization of the networks of individuals with high capabilities compared to normative ones. These models will be personalized and will inspire specific neuromodulation treatments.
Neuromodulation allows for the modification of the organization of brain networks. Low-voltage electrical stimulation at certain nodes, at specific frequencies and intensities, could generate physiological states that enable optimized system functioning and, in some cases, improve the integrative capacity corresponding to intellect (g). This neuromodulation will be inspired by computational models and will help experimentally test different stimulation parameters.
The essential object of research will be the brain and its anatomical-functional organization, which entails considering biomolecular bases (genetics), cortical micro-organization, macro-scale studies (magnetic resonance imaging, electroencephalography, and magnetoencephalography), as well as in-silico research within computational neuroscience.
This knowledge about the anatomical-functional organization of the brain will lead to models that will inspire brain neuromodulation aimed at improving general cognitive capacity (g) in neurotypical individuals and those with cognitive difficulties.
PUBLICATIONS OF INTEREST ON HUMAN INTELLIGENCE.
Barbey, A. K., Karama, S., Haier, R. J. (2021). The Cambridge Handbook of Intelligence and Cognitive Neuroscience. Cambridge University Press.
Colom, R. (2024). Manual de psicología diferencial. Métodos, modelos y aplicaciones. Pirámide.
Colom, R. (2024). Inteligencia. Lo que de verdad sabemos sobre la inteligencia. Evidencias y mitos. Shackleton.
Haier, R. J., Colom, R., Hunt, E. B. (2023). The science of human intelligence. Cambridge University Press.
Haier, R. J. (2016). The neuroscience of intelligence. Cambridge University Press
At the Zapata-Briceño Institute of Neuroscience, we have a multidisciplinary team of highly qualified professionals dedicated to research and advancement in the field of neuroscience. Our expertise spans various specialties, from neurobiology to psychology, allowing us to address the challenges of human intelligence with a comprehensive and collaborative approach. Each member of the team contributes their passion, knowledge, and commitment, working together to improve the health and well-being of our community.
Senior Researcher
Alireza Valizadeh is a senior researcher and head of computational neuroscience studies at the Instituto Zapata-Briceño para la Investigación de la Inteligencia Humana in Madrid. With over 17 years of experience at the interface of physics, mathematics, and neuroscience, he leads a research group focused on the role of oscillatory dynamics, and network architecture/dynamics interaction in neural computation and brain disorders. His work has yielded ~50 peer-reviewed publications—most in Q1 journals—and bridges theoretical models with practical applications, from the mechanisms of information processing and signal transmission in the brain to stimulation-based therapies for neurological disorders
A passionate educator and mentor, he has supervised 50 PhD and master students, many of whom have gone on to publish in leading journals and pursue successful academic careers. He has been instrumental in designing and delivering over a dozen interdisciplinary graduate courses, integrating basic and computational neuroscience, dynamical systems, and physics. His curriculum development has helped shape a cross-disciplinary educational model, preparing students to conduct cutting-edge brain research. Through sustained teaching, mentorship, and curriculum innovation, he has played a central role in promoting theoretical and computational neuroscience in Iran and internationally. His election to the Iranian Academy of Sciences in 2019 recognizes his pioneering contributions to the field. He is a recognized leader in the field, formerly a full professor of theoretical neuroscience in Iran and now a research leader in Spain.
.
Senior Researcher
Maryam Pakpour is a researcher specialized in complex materials, soft condensed matter, and neuroscience. She is currently working at the Zapata-Briceño Institute of Neuroscience in Madrid, focusing on EEG signal analysis using statistical models and artificial intelligence methods.
During my Ph.D. at the University of Amsterdam under the supervision of Prof. Daniel Bonn, my research initially focused on the rheological behavior of complex materials. Given the broad industrial applications of this field, I continued my research as a postdoctoral fellow at the University of Liège. Later, my focus expanded to soft condensed matter and biological materials. From 2016 to 2018, I held a research position at the Institute for Advanced Studies in Basic Sciences (IASBS) in Iran, where I studied the rheological behavior of aggregated Amyloid Beta in the presence of different peptides. Subsequently, in 2018, I joined the Pasargad Institute for Advanced Innovative Solutions (PIAIS) in Tehran, where I investigated the viscoelastic properties of various materials based on my materials science background.
Throughout these projects, my expertise in materials science has been applied to study the behavior of different matter under specific conditions. In recent years, my research has shifted towards investigating the viscoelastic behavior of brain tissue to better understand its mechanical response and deformation under external forces.
Now, I integrate my background in physics, statistical modeling, into neuroscience, focus- ing on EEG signal analysis to explore brain activity and its underlying mechanisms. As part of a neuroscience research group that integrates both experimental and theoretical approaches, my work aims to uncover patterns in brain activity, contributing to a deeper understanding of neural dynamics and cognitive processes.
Senior Researcher
Federico Rámirez has been a Telecommunications Engineer since 2015 and obtained a Master’s degree in Biomedical Engineering in 2016 from the Technical University of Madrid. After several collaborations with hospitals as an external biostatistical analyst and, in particular, after meeting Fernando Maestú, he decided to pursue a PhD in Biomedical Engineering.
En 2020 tuvo el honor de realizar una estancia de investigación trabajando con el profesor Joaquín Goñi y su equipo en el CONNplexity Lab. Finalmente, en 2021 obtuvo el Doctorado en Ingeniería Biomédica con la calificación Cum Laude.
As a PhD in Biomedical Engineering, his area of expertise focuses on the processing and analysis of biomedical signals from EEG, MEG, and MRI. His research career is structured around two main axes: the characterization of Alzheimer’s disease, particularly in its early detection, and the development of algorithms for the automatic processing of biomedical signals.
Senior Researcher
Saeed Taghavi is a computational neuroscientist and physicist, and his work focuses on the modeling and simulation of neural networks. He investigates the dynamics of excitatory and inhibitory populations, with particular attention to oscillatory patterns, phase and amplitude responses, and the effects of external stimulation. His research combines biophysically inspired neuronal models and neural mass models with large-scale simulations to explore the mechanisms underlying collective neural activity.
Information link: https://saeedtaghavi.github.io/
Junior Researcher
Pablo Vizcaino is a young researcher, who studied physics in Zaragoza, and then obtained a master's degree in Computational Physics in Dublin. His interests have always lied among the computational and mathematical side of physics, with a keen drive to understand complex biological systems through the lenses of mathematics. Some of his work, among which the Python library itfit and the collaboration in phaseportrait (https://github.com/phaseportrait/phaseportraitis currently available on its GitHub page: https://github.com/Sir-Bip-Bop.
External Advisor
Roberto Colom is Professor of Differential Psychology at the Autonomous University of Madrid (UAM). Throughout his academic career, he has conducted extensive research focused on the study of human intelligence and the psychological factors associated with its functioning.
He is the author and editor of more than twenty books, both technical and popular science, and has published more than one hundred and fifty scientific articles. His work addresses the psychometric analysis of intelligence, as well as its cognitive foundations and biological basis, with a particular emphasis on the use of advanced neuroimaging methodologies.
In parallel, he has conducted applied research in fields such as intellectual disability, criminal behavior, and personnel selection. He is a member of the International Society for Intelligence Research (ISIR) and serves on the editorial boards of specialized journals such as Intelligence and the Journal of Intelligence.
Coordinating Researcher
Gianluca Susi holds a PhD in Sensor Engineering and Learning Systems from the University of Rome Tor Vergata (2012). After completing his doctorate, he served as an Assistant Professor in Electrical Circuits and Sound Engineering.
He is currently a Senior Researcher at the Center for Cognitive and Computational Neuroscience and an Assistant Professor at the Faculty of Physical Sciences of the Complutense University of Madrid.
He has carried out research stays at the Brain Simulation Section of Charité Hospital in Berlin and at the Institute for Cross-Disciplinary Physics and Complex Systems (IFISC, UIB–CSIC).
His work focuses on the simulation of neurophysiological activity using spiking neural networks and neural mass models to study brain connectivity in neurodegenerative diseases, as well as on the development of brain-inspired signal processing techniques applied to engineering.
