This book presents a new methodology to develop system-level brain models using ordinary differential equations (ODE), which are to be solved and analyzed through simple Python scripts. Computer simulations of this kind of models allow the study of healthy and damaged brain functions, the discovery of new neural pathways that may be crucial for the emergence of pathologies, and to simulate the effects of possible new therapies acting on brain actors which are difficult to investigate in traditional research.The methodology consists of four steps: (i) design the model architecture which represents the interactions between different brain areas; (ii) write the ODE system which are implied by the model; (iii) build a Python script that correctly solves the equations; (iv) optimize the free model parameters using genetic algorithms or other techniques to obtain one or more model instances that reproduce the target investigated behavior.This book is for all people who want to learn how to use Python and ODE to simulate brain functions regardless of their backgrounds. While rigorous mathematical proofs of many aspects of the arguments discussed are out of the scope of this work and are therefore omitted, the most important concepts necessary for the critical judgment and self-assessment of the practitioner's work are exposed in a simplified, readily applicable form, with extensive references for the adventurous reader to explore. The book is a self-consistent textbook containing all pieces necessary to learn from scratch: from the essential mathematical and computing tools to the knowledge necessary to design, simulate, visualize, and interpret brain models. These skills are acquired through several hands-on examples explained step-by-step. One important and distinctive aspect of the book is that, beside the theory, it provides the necessary contexts and practical examples which are key to the correct application of the proposed methodology.

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Daniele Caligiore is a Research Director at the Institute of Cognitive Sciences and Technologies (ISTC) of the Italian National Research Council (CNR), where he coordinates the Computational and Translational Neuroscience Laboratory (CTNLab). This interdisciplinary research group leverages artificial intelligence (AI) and computational neuroscience to study brain function and behavior. The CTNLab ultimate goal is to discover new clinical applications and therapies for neurodegenerative diseases. He is the director and co-founder of the Advanced School in Artificial Intelligence (AS-AI), a postgraduate institution supported by ISTC, dedicated to the interdisciplinary study and application of AI. Additionally, he teaches "Artificial Intelligence Systems in Social Contexts" at the Libera Università Maria Santissima Assunta (LUMSA) in Rome. Daniele earned his Master's Degree in Electronic Engineering from the University of Catania in 2003 and a PhD in Biomedical Engineering from the University Campus Bio-Medico of Rome in 2011. He has been a visiting scholar at the University of Plymouth, the University of Bologna, and the University of Southern California. With over 90 scientific articles published in international journals, conference proceedings, and book chapters, Daniele has also contributed to numerous international research projects in artificial intelligence and neuroscience. He serves on the Scientific Secretariat of the CNR Commission for Ethics and Integrity in Research and is an expert evaluator of research project proposals in AI and neuroscience for the Italian Ministry of University and Research (MUR) and the European Commission. Additionally, he is a founding member of AI2Life, a spin-off of ISTC-CNR, which aims to promote the use of AI to foster social development and individual well-being. Daniele is the author of interdisciplinary books, including "IA istruzioni per l'uso" and "Curarsi con l'Intelligenza Artificiale", both published by il Mulino, and "Healing with Artificial Intelligence", published by Routledge Taylor & Francis.

Samuele Carli is a seasoned Senior Developer and Entrepreneur with over 25 years of professional experience. Throughout his career, he has contributed to a diverse array of projects across scientific research, industry, and business domains, taking on roles ranging from developer to project manager and coordinator. He holds a Master of Science degree in Computer Science from Università degli Studi di Firenze, specializing in numerical analysis, computer simulation, and artificial intelligence. His expertise includes work on machine learning applications for data analysis at CERN (the European Organization for Nuclear Research). Currently, he collaborates as a researcher with CTNLab and ISTC-CNR, focusing on brain modeling and simulation in the context of neurodegenerative diseases. In addition to his research endeavors, Samuele teaches courses on numerical optimization at the Advanced School in Artificial Intelligence. He is also the co-founder and Chief Technology Officer of Entersys S.r.l., a company dedicated to small enterprise management and the development of AI-driven and data-centric solutions for enterprise resource planning and management.