Lattice physics approaches for neural networks
Summary: Modern neuroscience has evolved into a frontier field that draws on numerous disciplines, resulting in the flourishing of novel conceptual frames primarily inspired by physics and complex systems science. Contributing in this direction, we recently introduced a mathematical framework to des...
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| Format: | Article |
| Language: | English |
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Elsevier
2024-12-01
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| Series: | iScience |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2589004224026154 |
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| author | Giampiero Bardella Simone Franchini Pierpaolo Pani Stefano Ferraina |
| author_facet | Giampiero Bardella Simone Franchini Pierpaolo Pani Stefano Ferraina |
| author_sort | Giampiero Bardella |
| collection | DOAJ |
| description | Summary: Modern neuroscience has evolved into a frontier field that draws on numerous disciplines, resulting in the flourishing of novel conceptual frames primarily inspired by physics and complex systems science. Contributing in this direction, we recently introduced a mathematical framework to describe the spatiotemporal interactions of systems of neurons using lattice field theory, the reference paradigm for theoretical particle physics. In this note, we provide a concise summary of the basics of the theory, aiming to be intuitive to the interdisciplinary neuroscience community. We contextualize our methods, illustrating how to readily connect the parameters of our formulation to experimental variables using well-known renormalization procedures. This synopsis yields the key concepts needed to describe neural networks using lattice physics. Such classes of methods are attention-worthy in an era of blistering improvements in numerical computations, as they can facilitate relating the observation of neural activity to generative models underpinned by physical principles. |
| format | Article |
| id | doaj-art-fd87efbe4a0a4e259d67fcb053919fcd |
| institution | OA Journals |
| issn | 2589-0042 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | Elsevier |
| record_format | Article |
| series | iScience |
| spelling | doaj-art-fd87efbe4a0a4e259d67fcb053919fcd2025-08-20T02:35:03ZengElsevieriScience2589-00422024-12-01271211139010.1016/j.isci.2024.111390Lattice physics approaches for neural networksGiampiero Bardella0Simone Franchini1Pierpaolo Pani2Stefano Ferraina3Department of Physiology and Pharmacology, Sapienza University of Rome, Rome, Italy; Corresponding authorDepartment of Physiology and Pharmacology, Sapienza University of Rome, Rome, Italy; Corresponding authorDepartment of Physiology and Pharmacology, Sapienza University of Rome, Rome, ItalyDepartment of Physiology and Pharmacology, Sapienza University of Rome, Rome, ItalySummary: Modern neuroscience has evolved into a frontier field that draws on numerous disciplines, resulting in the flourishing of novel conceptual frames primarily inspired by physics and complex systems science. Contributing in this direction, we recently introduced a mathematical framework to describe the spatiotemporal interactions of systems of neurons using lattice field theory, the reference paradigm for theoretical particle physics. In this note, we provide a concise summary of the basics of the theory, aiming to be intuitive to the interdisciplinary neuroscience community. We contextualize our methods, illustrating how to readily connect the parameters of our formulation to experimental variables using well-known renormalization procedures. This synopsis yields the key concepts needed to describe neural networks using lattice physics. Such classes of methods are attention-worthy in an era of blistering improvements in numerical computations, as they can facilitate relating the observation of neural activity to generative models underpinned by physical principles.http://www.sciencedirect.com/science/article/pii/S2589004224026154Mathematical method in physicsNeuroscienceComputing methodology |
| spellingShingle | Giampiero Bardella Simone Franchini Pierpaolo Pani Stefano Ferraina Lattice physics approaches for neural networks iScience Mathematical method in physics Neuroscience Computing methodology |
| title | Lattice physics approaches for neural networks |
| title_full | Lattice physics approaches for neural networks |
| title_fullStr | Lattice physics approaches for neural networks |
| title_full_unstemmed | Lattice physics approaches for neural networks |
| title_short | Lattice physics approaches for neural networks |
| title_sort | lattice physics approaches for neural networks |
| topic | Mathematical method in physics Neuroscience Computing methodology |
| url | http://www.sciencedirect.com/science/article/pii/S2589004224026154 |
| work_keys_str_mv | AT giampierobardella latticephysicsapproachesforneuralnetworks AT simonefranchini latticephysicsapproachesforneuralnetworks AT pierpaolopani latticephysicsapproachesforneuralnetworks AT stefanoferraina latticephysicsapproachesforneuralnetworks |