Literature DB >> 20235825

Hebbian plasticity and homeostasis in a model of hypercolumn of the visual cortex.

R Rossi Pool1, G Mato.   

Abstract

Neurons in the nervous system display a wide variety of plasticity processes. Among them are covariance-based rules and homeostatic plasticity. By themselves, the first ones tend to generate instabilities because of the unbounded potentiation of synapses. The second ones tend to stabilize the system by setting a target for the postsynaptic firing rate. In this work, we analyze the combined effect of these two mechanisms in a simple model of hypercolumn of the visual cortex. We find that the presence of homeostatic plasticity together with nonplastic uniform inhibition stabilizes the effect of Hebbian plasticity. The system can reach nontrivial solutions, where the recurrent intracortical connections are strongly modulated. The modulation is strong enough to generate contrast invariance. Moreover, this state can be reached even beginning from a weakly modulated initial condition.

Entities:  

Mesh:

Year:  2010        PMID: 20235825     DOI: 10.1162/neco.2010.07-09-1056

Source DB:  PubMed          Journal:  Neural Comput        ISSN: 0899-7667            Impact factor:   2.026


  4 in total

1.  Combined effects of LTP/LTD and synaptic scaling in formation of discrete and line attractors with persistent activity from non-trivial baseline.

Authors:  Timothee Leleu; Kazuyuki Aihara
Journal:  Cogn Neurodyn       Date:  2012-07-14       Impact factor: 5.082

2.  Modeling the dynamic interaction of Hebbian and homeostatic plasticity.

Authors:  Taro Toyoizumi; Megumi Kaneko; Michael P Stryker; Kenneth D Miller
Journal:  Neuron       Date:  2014-10-22       Impact factor: 17.173

3.  Synaptic scaling in combination with many generic plasticity mechanisms stabilizes circuit connectivity.

Authors:  Christian Tetzlaff; Christoph Kolodziejski; Marc Timme; Florentin Wörgötter
Journal:  Front Comput Neurosci       Date:  2011-11-10       Impact factor: 2.380

4.  Unsupervised learning for robust working memory.

Authors:  Jintao Gu; Sukbin Lim
Journal:  PLoS Comput Biol       Date:  2022-05-02       Impact factor: 4.779

  4 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.