ArticlePLoS computational biology2020
Achieving stable dynamics in neural circuits.
Article in PLoS computational biology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
11 citing papers in PubMed.
- Embedding of low-dimensional sensory dynamics in recurrent networks: Implications for the geometry of neural representation.Journal of computational neuroscience · 2026Article
- From Chaos to Coherence: Effects of High-Order Synaptic Correlations on Neural Dynamics.ArXiv · 2025Article
- A transient high-dimensional geometry affords stable conjunctive subspaces for efficient action selection.Nature communications · 2024Article
- A Transient High-dimensional Geometry Affords Stable Conjunctive Subspaces for Efficient Action Selection.bioRxiv : the preprint server for biology · 2024Article
- Article
- Brain-like hardware, do we need it?Frontiers in neuroscience · 2024Review
- Architecture of the brain's visual system enhances network stability and performance through layers, delays, and feedback.PLoS computational biology · 2023Article
- Adaptive control of synaptic plasticity integrates micro- and macroscopic network function.Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology · 2023Review
- Unraveling the mysteries of dendritic spine dynamics: Five key principles shaping memory and cognition.Proceedings of the Japan Academy. Series B, Physical and biological sciences · 2023Article
- Robust and brain-like working memory through short-term synaptic plasticity.PLoS computational biology · 2022Article
- The Continuity of Context: A Role for the Hippocampus.Trends in cognitive sciences · 2021Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
The brain consists of many interconnected networks with time-varying, partially autonomous activity. There are multiple sources of noise and variation yet activity has to eventually converge to a stable, reproducible state (or sequence of states) for its computations to make sense. We approached this problem from a control-theory perspective by applying contraction analysis to recurrent neural networks. This allowed us to find mechanisms for achieving stability in multiple connected networks with biologically realistic dynamics, including synaptic plasticity and time-varying inputs. These mechanisms included inhibitory Hebbian plasticity, excitatory anti-Hebbian plasticity, synaptic sparsity and excitatory-inhibitory balance. Our findings shed light on how stable computations might be achieved despite biological complexity. Crucially, our analysis is not limited to analyzing the stability of fixed geometric objects in state space (e.g points, lines, planes), but rather the stability of state trajectories which may be complex and time-varying.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.