Paradoxical self-sustained dynamics emerge from orchestrated excitatory and inhibitory homeostatic plasticity rules is a research paper published in Proceedings of the National Academy of Sciences (2022). On theSindex it has a DataRank of 0. It has been cited 24 times.
Scored on demand from live citation data
DataRank reads this dataset's downstream impact straight off the citation graph — no black box, no proprietary weighting. How is this computed?
FAIR checklist signals are shown for context only and do not affect DataRank scoring.
We only score data papers we can read in full — never from an abstract alone.
HHS | National Institutes of Health
Grant: NS116589
Universidad Nacional de Quilmes
Grant: -
Pew Charitable Trusts
Grant: #2009-000360-006
Swiss National Science Foundation
Grant: P2ZHP3-187943
Swiss National Science Foundation
Grant: P500PB-203133
NINDS NIH HHS
Grant: R01 NS116589
Swiss National Science Foundation
Grant: 203133
Unraveling the Excitatory and Inhibitory Learning Rules Driving the Unsupervised Emergence of Self-sustained Regimes and Balanced Network Dynamics
Swiss National Science Foundation
Grant: 187943
Self-organization of Recurrent Neural Dynamics by Unsupervised Tuning of the Balance of Excitation and Inhibition
National Institutes of Health
Grant: 4R01NS116589-02
Multiplexing working memory and timing: Encoding retrospective and prospective information in transient neural trajectories.
FWCI
1.86
Citation Percentile
0.9%
Citation Trend
Fields of Study
MeSH Terms
Keywords
Sustainable Development Goals