Simulations Approaching Data: Cortical Slow Waves in Inferred Models of the Whole Hemisphere of Mouse

[2104.07445] Simulations Approaching Data: Cortical Slow Waves in Inferred Models of the Whole Hemisphere of Mouse Skip to main content Search Submit Donate Log in Search arXiv Press Enter to search · Advanced search Quantitative Biology > Neurons and Cognition arXiv:2104.07445 (q-bio) [Submitted on 15 Apr 2021 ( v1 ), last revised 29 Nov 2022 (this version, v3)] Title: Simulations Approaching Data: Cortical Slow Waves in Inferred Models of the Whole Hemisphere of Mouse Authors: Cristiano Capone , Chiara De Luca , Giulia De Bonis , Robin Gutzen , Irene Bernava , Elena Pastorelli , Francesco Simula , Cosimo Lupo , Leonardo Tonielli , Anna Letizia Allegra Mascaro , Francesco Resta , Francesco Pavone , Micheal Denker , Pier Stanislao Paolucci View a PDF of the paper titled Simulations Approaching Data: Cortical Slow Waves in Inferred Models of the Whole Hemisphere of Mouse, by Cristiano Capone and 13 other authors View PDF HTML (experimental) Abstract: Thanks to novel, powerful brain activity recording techniques, we can create data-driven models from thousands of recording channels and large portions of the cortex, which can improve our understanding of brain-states neuromodulation and the related richness of traveling waves dynamics. We investigate the inference of data-driven models and the comparison among experiments and simulations, through the characterization of the spatio-temporal features of cortical waves in experimental recordings and simulations. Inference is built in two steps: the inner loop that optimizes by likelihood maximization a mean-field model, and the outer loop that optimizes a periodic neuro-modulation by relying on direct comparison of observables apt for the characterization of cortical slow waves. The model is capable to reproduce most of the features of the non-stationary and non-linear dynamics displayed by the high-resolution recording of the in-vivo mouse brain obtained by wide-field calcium imaging techniques. The proposed approach is of interest for both experimental and computational neuroscientists. Subjects: Neurons and Cognition (q-bio.NC) ; Dynamical Systems (math.DS) Cite as: arXiv:2104.07445 [q-bio.NC] (or arXiv:2104.07445v3 [q-bio.NC] for this version) https://doi.org/10.48550/arXiv.2104.07445 Focus to learn more arXiv-issued DOI via DataCite Journal reference: Communications Biology 6, 266 (2023) Related DOI : https://doi.org/10.1038/s42003-023-04580-0 Focus to learn more DOI(s) linking to related resources Submission history From: Cristiano Capone [ view email ] [v1] Thu, 15 Apr 2021 13:25:17 UTC (6,765 KB) [v2] Wed, 25 May 2022 16:26:35 UTC (23,870 KB) [v3] Tue, 29 Nov 2022 14:08:23 UTC (10,315 KB) Full-text links: Access Paper: View a PDF of the paper titled Simulations Approaching Data: Cortical Slow Waves in Inferred Models of the Whole Hemisphere of Mouse, by Cristiano Capone and 13 other authors View PDF HTML (experimental) TeX Source view license Current browse context: q-bio.NC < prev | next > new | recent | 2021-04 Change to browse by: math math.DS q-bio References & Citations NASA ADS Google Scholar Semantic Scholar export BibTeX citation Loading... BibTeX formatted citation × loading... Data provided by: Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer ( What is the Explorer? ) Connected Papers Toggle Connected Papers ( What is Connected Papers? ) Litmaps Toggle Litmaps ( What is Litmaps? ) scite.ai Toggle scite Smart Citations ( What are Smart Citations? ) Code, Data, Media Code, Data and Media Associated with this Article alphaXiv Toggle alphaXiv ( What is alphaXiv? ) Links to Code Toggle CatalyzeX Code Finder for Papers ( What is CatalyzeX? ) DagsHub Toggle DagsHub ( What is DagsHub? ) GotitPub Toggle Gotit.pub ( What is GotitPub? ) Huggingface Toggle Hugging Face ( What is Huggingface? ) ScienceCast Toggle ScienceCast ( What is ScienceCast? ) Demos Demos Replicate Toggle Replicate ( What is Replicate? ) Spaces Toggle Hugging Face Spaces ( What is Spaces? ) Spaces Toggle TXYZ.AI ( What is TXYZ.AI? ) Related Papers Recommenders and Search Tools Link to Influence Flower Influence Flower ( What are Influence Flowers? ) Core recommender toggle CORE Recommender ( What is CORE? ) Author Venue Institution Topic About arXivLabs arXivLabs: experimental projects with community collaborators arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs . Which authors of this paper are endorsers? | Disable MathJax ( What is MathJax? ) We gratefully acknowledge support from our major funders , member institutions , , and all contributors. About · Help · Contact · Subscribe · Copyright · Privacy · Accessibility · Operational Status (opens in new tab) Major funding support from

Related documents

• Scaling up polarization-sensitive optical coherence tomography to image the whole macaque brain#366440
• Pyramidal-cell-specific hemispheric asymmetry shapes dorsoventral CA1 dynamics during rest and exploratory behavior#271964
• FB-GDM: Fully-Bayesian Guided Diffusion Models for High-Dimensional Linear Inverse Problems via Unsupervised Variational Inference#1077145
• Cross-organ MRI to assess the relationship between cardiac traits and cerebral white matter hyperintensity volumes.#320642
• Shadow Reduction in Ultrasound Imaging Using Differentiable Simulation and Radiance Field Decomposition#1077302