ArticleIEEE transactions on control of network systems2018
Control Analysis and Design for Statistical Models of Spiking Networks.
Article in IEEE transactions on control of network systems, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 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
5 citing papers in PubMed.
- Developing control-theoretic objectives for large-scale brain dynamics and cognitive enhancement.Annual reviews in control · 2022Article
- Control of neural systems at multiple scales using model-free, deep reinforcement learning.Scientific reports · 2018Article
- Learning-based Approaches for Controlling Neural Spiking.Proceedings of the ... American Control Conference. American Control Conference · 2018Article
- State Estimation for General Complex Dynamical Networks with Incompletely Measured Information.Entropy (Basel, Switzerland) · 2017Article
- Fundamental Limits of Forced Asynchronous Spiking with Integrate and Fire Dynamics.Journal of mathematical neuroscience · 2017Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
A popular approach to characterizing activity in neuronal networks is the use of statistical models that describe neurons in terms of their firing rates (i.e., the number of spikes produced per unit time). The output realization of a statistical model is, in essence, an
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.