Article
Physiology
Alys R. Clark, Kelly S. Burrowes, Merryn H. Tawhai
Summary: Anatomically based integrative models of the lung provide unique capabilities for studying normal and abnormal lung function, with substantial regional variability in structure and function. Computational models can mimic respiratory system structure, function, and response to intervention, without the technical and ethical issues of experimental studies and biomedical imaging. These models facilitate investigation of mechanisms determining respiratory function and dysfunction.
COMPREHENSIVE PHYSIOLOGY
(2021)
Article
Neurosciences
Andrew Y. Revell, Alexander B. Silva, T. Campbell Arnold, Joel M. Stein, Sandhitsu R. Das, Russell T. Shinohara, Dani S. Bassett, Brian Litt, Kathryn A. Davis
Summary: Brain maps are essential for studying brain function and organization. However, the choice of atlases can impact the prediction of brain's function from its structure. We demonstrate how atlas features can change network topology, structure-function correlation, and the ability to test specific hypotheses. We propose a framework and algorithm for atlas selection to maximize its validity.
Article
Neurosciences
Damien Depannemaecker, Aitakin Ezzati, Huifang E. Wang, Viktor Jirsa, Christophe Bernard
Summary: Epilepsy is a complex disease that can be studied using theoretical and computational models. Theoretical frameworks help classify seizures based on their dynamical properties, while computational models have potential for clinical applications. These models can provide insights into seizure mechanisms and aid in developing accurate diagnostic and personalized medicine tools. Considering glial cells is important in understanding epilepsy, and this type of approach provides valuable knowledge.
NEUROBIOLOGY OF DISEASE
(2023)
Article
Neurosciences
Robert J. Jirsaraie, Tobias Kaufmann, Vishnu Bashyam, Guray Erus, Joan L. Luby, Lars T. Westlye, Christos Davatzikos, Deanna M. Barch, Aristeidis Sotiras
Summary: Machine learning has shown promise in predicting age using neuroimaging data and deriving personalized biomarkers. In this study, the generalizability of two brain age models was evaluated in early-life samples. The models differed in their processing methods and predictive algorithms. The results revealed trade-offs and limitations impacting the generalizability, such as acquisition protocol differences and biased brain age estimates.
HUMAN BRAIN MAPPING
(2023)
Article
Public, Environmental & Occupational Health
Sarah Lucht, Lina Glaubitz, Susanne Moebus, Sara Schramm, Christiane Jockwitz, Svenja Caspers, Barbara Hoffmann
Summary: The study found that long-term exposure to air pollution and noise may not consistently affect the structural parameters of the brain's Default Mode Network (DMN). While some participants experienced outdoor noise levels above European recommendations, the exposure did not significantly alter the structure of DMN.
INTERNATIONAL JOURNAL OF HYGIENE AND ENVIRONMENTAL HEALTH
(2022)
Article
Audiology & Speech-Language Pathology
Elsa Lindboom, Aaron Nidiffer, Laurel H. Carney, Edmund C. Lalor
Summary: For decades, auditory neuroscience research has focused on describing how the human brain responds to complex acoustic stimuli. A systems-based approach has been taken, where neurophysiological responses are modeled based on features of the presented stimulus. However, the representation of sound is transformed as it passes through the auditory pathway, leading to fundamental differences between cortical inputs and the raw audio signal.
Review
Behavioral Sciences
Jose Manuel Perez-Garcia, Samuel Suarez-Suarez, Sonia Doallo, Fernando Cadaveira
Summary: This review comprehensively evaluates the impact of binge drinking on neurocognitive functions, and introduces the use of resting-state functional connectivity and neurite orientation dispersion and density imaging techniques. The study finds that binge drinking is associated with structural and functional anomalies in the brain.
NEUROSCIENCE AND BIOBEHAVIORAL REVIEWS
(2022)
Article
Engineering, Biomedical
Anne-Cecile Lesage, Alexis Simmons, Anando Sen, Simran Singh, Melissa Chen, Guillaume Cazoulat, Jeffrey S. Weinberg, Kristy K. Brock
Summary: This study evaluated the accuracy and efficiency of various FEM models in predicting inward brain-shift during neurosurgery. Including non-rigid modeling of the meninges was found to be statistically significant for patients with low-grade gliomas.
PHYSICS IN MEDICINE AND BIOLOGY
(2021)
Review
Biochemistry & Molecular Biology
Zeinab Breijyeh, Rafik Karaman
Summary: Enzymes are specific biological catalysts that accelerate chemical reactions in cells. Computational methods like molecular mechanics and quantum mechanics are used to study enzyme mechanisms and develop prodrugs for various medical purposes.
Review
Biology
Luiz Pessoa, Loreta Medina, Ester Desfilis
Summary: Mental terms are epistemically sterile as the brain's structure and function go beyond the boundaries of traditional psychology. Comparative neuroanatomy studies of the vertebrate brain have shown that it supports extensive signal communication and integration, enabling animals to adapt to complex and changing environments.
PHILOSOPHICAL TRANSACTIONS OF THE ROYAL SOCIETY B-BIOLOGICAL SCIENCES
(2022)
Article
Multidisciplinary Sciences
Bo-Yong Park, Casey Paquola, Richard A. Bethlehem, Oualid Benkarim, Bratislav Misic, Jonathan Smallwood, Edward T. Bullmore, Boris C. Bernhardt
Summary: This study analyzed the development of structural and functional brain networks in adolescents and found that multiple corticocortical structural networks continue to differentiate in youth. Regions with more similar structural wiring were more likely to be functionally coupled. Additionally, increased structural differentiation was associated with reduced functional interactions, illustrating the interaction between brain structure and function in adolescent development.
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
(2022)
Article
Clinical Neurology
Jun Gan, Wanting Liu, Jie Fan, Jinyao Yi, Changlian Tan, Xiongzhao Zhu
Summary: This study explores the effects of insight and disease diagnosis on clinical symptoms, neurocognition, and structural/functional alterations in the brain among patients with obsessive-compulsive disorder (OCD) and schizo-obsessive disorder (SOD). The study findings indicate that there is an interactive effect of insight and diagnosis on working memory and gray matter volume in the right superior and middle temporal gyrus. Furthermore, insight has significant effects on working memory, visual memory, compulsion, obsession, and spontaneous neural activity, while diagnosis has significant effects on the severity of compulsion, verbal IQ, executive function, memory, and neural activity in various brain regions.
JOURNAL OF AFFECTIVE DISORDERS
(2023)
Article
Chemistry, Multidisciplinary
Bexy Alfonso, Joaquin Taverner, Emilio Vivancos, Vicente Botti
Summary: This work explores the possibility of building generic computational approaches and languages to model affective phenomena. By conducting an analysis inspired by philosophical and psychological theories, a theoretical framework is proposed to support the development of a model of an affective agent with practical reasoning. The framework also allows for incremental research and evaluation of current computational approaches in integrating practical reasoning and affect-related issues.
APPLIED SCIENCES-BASEL
(2021)
Review
Biochemical Research Methods
Yan Zhao, Chun-Chun Wang, Xing Chen
Summary: Research has shown that the number of microbes in the human body is almost 10 times higher than the number of cells, and they play crucial roles in immune function, digestion, and metabolism. Recent studies have revealed close relationships between noncommunicable diseases and microbes, providing new insights into disease pathogenesis. Computational models have been developed to predict disease-related microbes, potentially revolutionizing disease diagnosis, treatment, and drug development.
BRIEFINGS IN BIOINFORMATICS
(2021)
Article
Biochemistry & Molecular Biology
Deborah Giordano, Cassiano Langini, Amedeo Caflisch, Anna Marabotti, Angelo Facchiano
Summary: The study compares the structures and flexibility of transglutaminase enzymes from Kutzneria albida (KalbTGase) and Streptomyces mobaraensis (MTGase). It is found that KalbTGase is more rigid and has a more closed catalytic site at room temperature, indicating higher selectivity compared to MTGase. Preliminary results at higher temperature suggest enhanced flexibility of KalbTGase, potentially allowing it to adapt to different substrates, while MTGase shows reduced adaptability and catalytic activity at higher temperatures.
COMPUTATIONAL AND STRUCTURAL BIOTECHNOLOGY JOURNAL
(2022)
Article
Mathematics, Applied
Claudio Runfola, Hiba Sheheitli, Fabrice Bartolomei, Huifang Wang, Viktor Jirsa
Summary: The success of resection surgery for drug-resistant epilepsy patients depends on accurately identifying the epileptogenic zone (EZ), a subnetwork of brain regions responsible for seizure genesis in focal epilepsy. The dynamical network biomarker (DNB) method, originally developed for complex disease onset, is adapted and implemented for EZ identification in Stereoelectroencephalography (SEEG) data analysis. The method is validated using simulated data and compared with expert clinicians' results. The high precision values obtained suggest that the DNB approach is a promising tool for EZ identification in focal epilepsy.
COMMUNICATIONS IN NONLINEAR SCIENCE AND NUMERICAL SIMULATION
(2023)
Article
Neurosciences
Mikhael Azilinon, Julia Makhalova, Wafaa Zaaraoui, Samuel Medina Villalon, Patrick Viout, Tangi Roussel, Mohamed M. El Mendili, Ben Ridley, Jean-Philippe Ranjeva, Fabrice Bartolomei, Viktor Jirsa, Maxime Guye
Summary: Whole brain ionic and metabolic imaging is a potential tool for brain disease characterization. This study used sodium MRI and H-1-MR spectroscopic imaging to evaluate changes in epileptogenic networks. The study found a significant increase in sodium signal and a decrease in NAA levels in the epileptogenic zone.
HUMAN BRAIN MAPPING
(2023)
Article
Cell Biology
Huifang E. Wang, Marmaduke Woodman, Paul Triebkorn, Jean-Didier Lemarechal, Jayant Jha, Borana Dollomaja, Anirudh Nihalani Vattikonda, Viktor Sip, Samuel Medina Villalon, Meysam Hashemi, Maxime Guye, Julia Makhalova, Fabrice Bartolomei, Viktor Jirsa
Summary: We propose a virtual epileptic patient (VEP) workflow that uses personalized brain models and machine learning methods to estimate epileptogenic zone networks (EZNs) and aid surgical strategies. By sampling and optimizing personalized model parameters using functional stereoelectroencephalography recordings, the VEP accurately determines a patient's EZN. Additionally, the VEP can predict surgical outcomes using virtual surgeries.
SCIENCE TRANSLATIONAL MEDICINE
(2023)
Article
Mathematical & Computational Biology
Jennifer S. S. Goldman, Lionel Kusch, David Aquilue, Bahar Hazal Yalcinkaya, Damien Depannemaecker, Kevin Ancourt, Trang-Anh E. Nghiem, Viktor Jirsa, Alain Destexhe
Summary: The study integrates neural dynamics across scales using mean-field modeling and finds that macroscopic dynamics resembling human brain activity emerge when AdEx mean-field neural populations are connected via structural tracts defined by the human connectome. The model can explain properties of empirically observed dynamics in space, time, phase, and frequency domains. It provides open access tools to investigate brain responsiveness and contributes to a more unified understanding of experimental data from conscious and unconscious states, as well as their associated pathologies.
FRONTIERS IN COMPUTATIONAL NEUROSCIENCE
(2023)
Article
Biochemical Research Methods
Giulio Ruffini, Giada Damiani, Diego Lozano-Soldevilla, Nikolas Deco, Fernando E. E. Rosas, Narsis A. A. Kiani, Adrian Ponce-Alvarez, Morten L. L. Kringelbach, Robin Carhart-Harris, Gustavo Deco
Summary: In this study, the authors characterized two brain states (psychedelics-induced and placebo) using functional magnetic resonance imaging (fMRI) data and features from the Ising model formalism and algorithmic complexity. They found that psychedelics increased BOLD signal complexity and Ising temperature, in agreement with previous findings and predictions. They also discovered that the placebo condition was already in a paramagnetic phase, while ingestion of psychedelics resulted in a shift towards a more disordered state. The study highlights the recovery of the structural connectome through fitting an Ising model and the role of reduced homotopic links in psychedelics-induced disorder.
PLOS COMPUTATIONAL BIOLOGY
(2023)
Article
Multidisciplinary Sciences
Morten L. Kringelbach, Yonatan Sanz Perl, Enzo Tagliazucchi, Gustavo Deco
Summary: Using a large-scale neuroimaging dataset, this study investigates the hierarchical reorganization of the brain's functional activity during naturalistic movie-watching compared to cognitive tasks and resting. The findings show that the hierarchy is flatter and the non-reversibility is smaller during movie-watching. The underlying mechanisms are revealed by a model-based generative effective connectivity (GEC). Overall, this study demonstrates the benefits of using naturalistic neuroscience in understanding brain function.
Review
Biochemistry & Molecular Biology
Jakub Vohryzek, Joana Cabral, Francesca Castaldo, Yonatan Sanz-Perl, Louis-David Lord, Henrique M. Fernandes, Vladimir Litvak, Morten L. Kringelbach, Gustavo Deco
Summary: Traditionally, model-free analyses are used in neuroimaging to detect significant differences between brain states. However, the challenge remains in assessing transitions between different brain states. This study introduces a Dynamic Sensitivity Analysis framework that quantifies these transitions and aims to rebalance brain activity towards a target state, such as healthy brain dynamics.
COMPUTATIONAL AND STRUCTURAL BIOTECHNOLOGY JOURNAL
(2023)
Article
Neurosciences
Gustavo Deco, Yonatan Sanz Perl, Laura de la Fuente, Jacobo D. Sitt, B. T. Thomas Yeo, Enzo Tagliazucchi, Morten L. Kringelbach
Summary: In this study, a thermodynamics-inspired, deep learning based Temporal Evolution NETwork (TENET) framework was used to assess the asymmetry in the flow of events, 'arrow of time', in human brain signals. The framework was applied to large-scale HCP neuroimaging data and revealed significant changes in the hierarchy of orchestration for resting state and cognitive tasks, as well as differences between health and neuropsychiatric disorders. This study provides new insights into brain dynamics in different brain states.
NETWORK NEUROSCIENCE
(2023)
Article
Clinical Neurology
Gian Marco Duma, Alberto Danieli, Giovanni Mento, Valerio Vitale, Raffaella Scotto Opipari, Viktor Jirsa, Paolo Bonanni, Pierpaolo Sorrentino
Summary: This study used neuronal avalanches to compare basal brain activity between patients with temporal lobe epilepsy (TLE) and controls. It was found that the propagation patterns of neuronal avalanches were altered in TLE during the resting state, suggesting a potential diagnostic application in epilepsy. Furthermore, the relationship between specific patterns of propagation and memory performance support the neurophysiological relevance of neuronal avalanches.
Article
Neurosciences
Roser Sanchez-Todo, Andre M. Bastos, Edmundo Lopez-Sola, Borja Mercadal, Emiliano Santarnecchi, Earl K. Miller, Gustavo Deco, Giulio Ruffini
Summary: In this study, a new framework called laminar neural mass models (LaNMM) is proposed to simulate electrophysiological measurements by combining conduction physics with NMMs. Using this framework, the location of oscillatory generators in the prefrontal cortex of the macaque monkey is inferred from laminar-resolved data. A minimal model capable of generating coupled slow and fast oscillations is defined, and LaNMM-specific parameters are optimized to fit the recorded data. The functional connectivity (FC) of the model and data are evaluated using an optimization function, and the family of best solutions reproduces the observed FC by selecting specific locations of pyramidal cells and their synapses.
Article
Neurosciences
Francesca Castaldo, Francisco Pascoa dos Santos, Ryan C. Timms, Joana Cabral, Jakub Vohryzek, Gustavo Deco, Mark Woolrich, Karl Friston, Paul Verschure, Vladimir Litvak
Summary: Existing whole-brain models are tailored to specific data modalities, but we propose that they originate from shared network dynamics. To link distinct features of brain activity across modalities, we consider two large-scale models and compare them against real data. Both models can represent functional connectivity and generate oscillatory modes, demonstrating the importance of balanced dynamics and delays.
Article
Neurosciences
Andrea I. Luppi, Joana Cabral, Rodrigo Cofre, Pedro A. M. Mediano, Fernando E. Rosas, Abid Y. Qureshi, Amy Kuceyeski, Enzo Tagliazucchi, Federico Raimondo, Gustavo Deco, James M. Shine, Morten L. Kringelbach, Patricio Orio, ShiNung Ching, Yonatan Sanz Perl, Michael N. Diringer, Robert D. Stevens, Jacobo Diego Sitt
Summary: Disorders of consciousness are challenging conditions characterized by persistent loss of responsiveness due to brain injury, requiring a better understanding of the neural mechanisms underlying human consciousness and improved treatment options. The increasing availability of multimodal neuroimaging data has led to various modeling efforts to stratify patients, identify causal mechanisms, and test potential treatment avenues in silico. This article provides a framework and vision for the field of modeling disorders of consciousness, addressing the gaps between current approaches and the desired outcomes, and offers recommendations for collaborative efforts to meet these challenges.
Article
Neurosciences
Prejaas K. B. Tewarie, Rikkert Hindriks, Yi Ming Lai, Stamatios N. Sotiropoulos, Morten Kringelbach, Gustavo Deco
Summary: Characterising brain states during tasks using electrophysiological modalities is common practice in neuroscience. Non-reversibility, or the temporal asymmetry in functional interactions, may be more sensitive to characterise task induced brain states than functional connectivity. Using whole brain computational models, we find that non-reversibility outperforms functional connectivity in the identification of task induced brain states, particularly in capturing bottom-up gamma induced brain states.
Article
Biology
Elvira G-Guzman, Yonatan Sanz Perl, Jakub Vohryzek, Anira Escrichs, Dragana Manasova, Basak Turker, Enzo Tagliazucchi, Morten Kringelbach, Jacobo D. Sitt, Gustavo Deco
Summary: Life is a constant battle against equilibrium, with living organisms requiring the violation of detailed balance to survive. Temporal asymmetry is used as a measure of non-equilibrium and can assess the reversibility in human brain time series. This study analyzes functional magnetic resonance imaging data in patients with disorder of consciousness and finds that a decrease in brain signal asymmetry and non-stationarity are key characteristics of impaired consciousness states.
Meeting Abstract
Pharmacology & Pharmacy
M. Breyton, S. Petkoski, P. Sorrentino, G. Rabuffo, J. Fousek, R. Guilhaumou, V. Jirsa
FUNDAMENTAL & CLINICAL PHARMACOLOGY
(2023)
