ArticleCognitive neurodynamics2023
Different eigenvalue distributions encode the same temporal tasks in recurrent neural networks.
Article in Cognitive neurodynamics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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5 citing papers in PubMed, 3 citations in OpenAlex.
- Task-Parametrized dynamics: Representation of time and decisions in recurrent neural networks.Journal of computational neuroscience · 2026Article
- Analyzing rescaling, discretization, and linearization in RNNs for neural system modeling.Frontiers in computational neuroscience · 2026Article
- Task-Parametrized Dynamics: Representation of Time and Decisions in Recurrent Neural Networks.bioRxiv : the preprint server for biology · 2025Article
- Effect in the spectra of eigenvalues and dynamics of RNNs trained with excitatory-inhibitory constraint.Cognitive neurodynamics · 2024Article
- Exploring Flip Flop memories and beyond: training Recurrent Neural Networks with key insights.Frontiers in systems neuroscience · 2024Article
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1 author at 1 institution in 1 country.
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Abstract
Different brain areas, such as the cortex and, more specifically, the prefrontal cortex, show great recurrence in their connections, even in early sensory areas. Several approaches and methods based on trained networks have been proposed to model and describe these regions. It is essential to understand the dynamics behind the models because they are used to build different hypotheses about the functioning of brain areas and to explain experimental results. The main contribution here is the description of the dynamics through the classification and interpretation carried out with a set of numerical simulations. This study sheds light on the multiplicity of solutions obtained for the same tasks and shows the link between the spectra of linearized trained networks and the dynamics of the counterparts. The patterns in the distribution of the eigenvalues of the recurrent weight matrix were studied and properly related to the dynamics in each task. Supplementary Information: The online version contains supplementary material available at 10.1007/s11571-022-09802-5.
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