Role of connectivity anisotropies in the dynamics of cultured neuronal networks
An inherent challenge in designing laboratory-grown, engineered living neuronal networks lies in predicting the dynamic repertoire of the resulting network and its sensitivity to experimental variables. To fill this gap, and inspired by recent experimental studies, we present a numerical model desig...
| Autores: | ; ; |
|---|---|
| Tipo de documento: | Artículo |
| Estado: | Published version |
| Fecha de publicación: | 2025 |
| País: | España |
| Institución: | Universidad de Barcelona |
| Repositorio: | Dipòsit Digital de la UB |
| OAI Identifier: | oai:diposit.ub.edu:2445/225316 |
| Acceso en línea: | https://hdl.handle.net/2445/225316 |
| Nivel de acceso: | Acceso abierto |
| Palabra clave: | Anisotropia Neurociències Xarxes neuronals (Neurobiologia) Anisotropy Neurosciences Neural networks (Neurobiology) |
| _version_ | 1878738104700895232 |
|---|---|
| author | Houben, Akke Mats |
| author2 | García Ojalvo, Jordi Soriano i Fradera, Jordi |
| author2_role | author author |
| author_browse | García Ojalvo, Jordi Houben, Akke Mats Soriano i Fradera, Jordi |
| author_facet | Houben, Akke Mats García Ojalvo, Jordi Soriano i Fradera, Jordi |
| author_role | author |
| collection | Dipòsit Digital de la UB |
| description | An inherent challenge in designing laboratory-grown, engineered living neuronal networks lies in predicting the dynamic repertoire of the resulting network and its sensitivity to experimental variables. To fill this gap, and inspired by recent experimental studies, we present a numerical model designed to replicate the anisotropies in connectivity introduced through engineering, characterize the emergent collective behavior of the neuronal network, and make predictions. The numerical model is developed to replicate experimental data, and subsequently used to quantify network dynamics in relation to tunable structural and dynamical parameters. These include the strength of imprinted anisotropies, synaptic noise, and average axon lengths. We show that the model successfully captures the behavior of engineered neuronal cultures, revealing a rich repertoire of activity patterns that are highly sensitive to connectivity architecture and noise levels. Specifically, the imprinted anisotropies promote modularity and high clustering coefficients, substantially reducing the pathological-like bursting of standard neuronal cultures, whereas noise and axonal length influence the variability in dynamical states and activity propagation velocities. Moreover, connectivity anisotropies significantly enhance the ability to reconstruct structural connectivity from activity data, an aspect that is important to understand the structure–function relationship in neuronal networks. Our work provides a robust in silico framework to assist experimentalists in the design of in vitro neuronal systems and in anticipating their outcomes. This predictive capability is particularly valuable in developing reliable brain-on-a-chip platforms and in exploring fundamental aspects of neural computation, including input–output relationships and information coding. |
| eu_rights_str_mv | openAccess |
| format | article |
| id | ES_a9bb67e2dd2cef032cd3e45d2b6643cf |
| institution | Universidad de Barcelona |
| instname_str | Universidad de Barcelona |
| network_acronym_str | ES |
| network_name_str | España |
| oai_identifier_str | oai:diposit.ub.edu:2445/225316 |
| publishDate | 2025 |
| publishDateSort | 2025 |
| publisher | Public Library of Science (PLoS) |
| publisherStr | Public Library of Science (PLoS) |
| reponame_str | Dipòsit Digital de la UB |
| spelling | Role of connectivity anisotropies in the dynamics of cultured neuronal networks Houben, Akke Mats García Ojalvo, Jordi Soriano i Fradera, Jordi Anisotropia Neurociències Xarxes neuronals (Neurobiologia) Anisotropy Neurosciences Neural networks (Neurobiology) An inherent challenge in designing laboratory-grown, engineered living neuronal networks lies in predicting the dynamic repertoire of the resulting network and its sensitivity to experimental variables. To fill this gap, and inspired by recent experimental studies, we present a numerical model designed to replicate the anisotropies in connectivity introduced through engineering, characterize the emergent collective behavior of the neuronal network, and make predictions. The numerical model is developed to replicate experimental data, and subsequently used to quantify network dynamics in relation to tunable structural and dynamical parameters. These include the strength of imprinted anisotropies, synaptic noise, and average axon lengths. We show that the model successfully captures the behavior of engineered neuronal cultures, revealing a rich repertoire of activity patterns that are highly sensitive to connectivity architecture and noise levels. Specifically, the imprinted anisotropies promote modularity and high clustering coefficients, substantially reducing the pathological-like bursting of standard neuronal cultures, whereas noise and axonal length influence the variability in dynamical states and activity propagation velocities. Moreover, connectivity anisotropies significantly enhance the ability to reconstruct structural connectivity from activity data, an aspect that is important to understand the structure–function relationship in neuronal networks. Our work provides a robust in silico framework to assist experimentalists in the design of in vitro neuronal systems and in anticipating their outcomes. This predictive capability is particularly valuable in developing reliable brain-on-a-chip platforms and in exploring fundamental aspects of neural computation, including input–output relationships and information coding. Public Library of Science (PLoS) https://hdl.handle.net/2445/225316 |
| spellingShingle | Role of connectivity anisotropies in the dynamics of cultured neuronal networks Houben, Akke Mats Anisotropia Neurociències Xarxes neuronals (Neurobiologia) Anisotropy Neurosciences Neural networks (Neurobiology) |
| status_str | publishedVersion |
| title | Role of connectivity anisotropies in the dynamics of cultured neuronal networks |
| title_full | Role of connectivity anisotropies in the dynamics of cultured neuronal networks |
| title_fullStr | Role of connectivity anisotropies in the dynamics of cultured neuronal networks |
| title_full_unstemmed | Role of connectivity anisotropies in the dynamics of cultured neuronal networks |
| title_short | Role of connectivity anisotropies in the dynamics of cultured neuronal networks |
| title_sort | Role of connectivity anisotropies in the dynamics of cultured neuronal networks |
| topic | Anisotropia Neurociències Xarxes neuronals (Neurobiologia) Anisotropy Neurosciences Neural networks (Neurobiology) |
| topic_facet | Anisotropia Neurociències Xarxes neuronals (Neurobiologia) Anisotropy Neurosciences Neural networks (Neurobiology) |
| url | https://hdl.handle.net/2445/225316 |