Academic Journal
The impact of sparsity in low-rank recurrent neural networks.
| العنوان: | The impact of sparsity in low-rank recurrent neural networks. |
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| المؤلفون: | Elizabeth Herbert, Srdjan Ostojic |
| المصدر: | PLoS Computational Biology, Vol 18, Iss 8, p e1010426 (2022) |
| بيانات النشر: | Public Library of Science (PLoS), 2022. |
| سنة النشر: | 2022 |
| المجموعة: | LCC:Biology (General) |
| مصطلحات موضوعية: | Biology (General), QH301-705.5 |
| الوصف: | Neural population dynamics are often highly coordinated, allowing task-related computations to be understood as neural trajectories through low-dimensional subspaces. How the network connectivity and input structure give rise to such activity can be investigated with the aid of low-rank recurrent neural networks, a recently-developed class of computational models which offer a rich theoretical framework linking the underlying connectivity structure to emergent low-dimensional dynamics. This framework has so far relied on the assumption of all-to-all connectivity, yet cortical networks are known to be highly sparse. Here we investigate the dynamics of low-rank recurrent networks in which the connections are randomly sparsified, which makes the network connectivity formally full-rank. We first analyse the impact of sparsity on the eigenvalue spectrum of low-rank connectivity matrices, and use this to examine the implications for the dynamics. We find that in the presence of sparsity, the eigenspectra in the complex plane consist of a continuous bulk and isolated outliers, a form analogous to the eigenspectra of connectivity matrices composed of a low-rank and a full-rank random component. This analogy allows us to characterise distinct dynamical regimes of the sparsified low-rank network as a function of key network parameters. Altogether, we find that the low-dimensional dynamics induced by low-rank connectivity structure are preserved even at high levels of sparsity, and can therefore support rich and robust computations even in networks sparsified to a biologically-realistic extent. |
| نوع الوثيقة: | article |
| وصف الملف: | electronic resource |
| اللغة: | English |
| تدمد: | 1553-734X 1553-7358 |
| Relation: | https://doaj.org/toc/1553-734X; https://doaj.org/toc/1553-7358 |
| DOI: | 10.1371/journal.pcbi.1010426 |
| URL الوصول: | https://doaj.org/article/164ccb67d3194cf7a8c188e78ef6ff75 |
| رقم الانضمام: | edsdoj.164ccb67d3194cf7a8c188e78ef6ff75 |
| قاعدة البيانات: | Directory of Open Access Journals |
Full Text Finder | تدمد: | 1553734X 15537358 |
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| DOI: | 10.1371/journal.pcbi.1010426 |