Neuromodulation by surprise: a biologically plausible model of the learning rate dynamics
- Standort
-
Deutsche Nationalbibliothek Frankfurt am Main
- ISSN
-
1471-2202
- Umfang
-
Online-Ressource
- Sprache
-
Englisch
- Anmerkungen
-
online resource.
- Erschienen in
-
Neuromodulation by surprise: a biologically plausible model of the learning rate dynamics ; volume:15 ; number:1 ; day:21 ; month:7 ; year:2014 ; pages:1-2 ; date:7.2014
BMC neuroscience ; 15, Heft 1 (21.7.2014), 1-2, 7.2014
- Urheber
-
Faraji, Mohammad Javad
- Beteiligte Personen und Organisationen
-
Preuschoff, Kerstin
Gerstner, Wulfram
SpringerLink (Online service)
- DOI
-
10.1186/1471-2202-15-S1-P159
- URN
-
urn:nbn:de:1111-2016032124595
- Rechteinformation
-
Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Letzte Aktualisierung
-
2025-08-14T10:51:34+0200
Datenpartner
Dieses Objekt wird bereitgestellt von:
Deutsche Nationalbibliothek. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Deutsche Nationalbibliothek. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Beteiligte
- Faraji, Mohammad Javad
- Preuschoff, Kerstin
- Gerstner, Wulfram
- SpringerLink (Online service)
Ähnliche Objekte (12)
Biologically plausible Reinforcement Learning
Stabilizing working memory in spiking networks with biologically plausible synaptic dynamics
Biologically plausible reinforcement learning of continuous actions
Degeneracy measures in biologically plausible random Boolean networks
NeuroCAD – the modular simulation environment for effective biologically plausible neuromodeling
Biologically plausible statistics from a Markov model of spiking cortical networks
Temporal sequence learning via adaptation in biologically plausible spiking neural networks
Efficient Realization of Large-Area E-Skin based on Biologically Plausible Principles
Adaptive structure evolution and biologically plausible synaptic plasticity for recurrent spiking neural networks
Object-based biasing for attentional control of gaze: a comparison of biologically plausible mechanisms
The influence of structure on the response properties of biologically plausible neural network models
The hypothesis that Helicobacter pylori predisposes to Alzheimer’s disease is biologically plausible
Biologically plausible Reinforcement Learning
Stabilizing working memory in spiking networks with biologically plausible synaptic dynamics
Biologically plausible reinforcement learning of continuous actions
Degeneracy measures in biologically plausible random Boolean networks
NeuroCAD – the modular simulation environment for effective biologically plausible neuromodeling
Biologically plausible statistics from a Markov model of spiking cortical networks
Temporal sequence learning via adaptation in biologically plausible spiking neural networks
Efficient Realization of Large-Area E-Skin based on Biologically Plausible Principles
Adaptive structure evolution and biologically plausible synaptic plasticity for recurrent spiking neural networks
Object-based biasing for attentional control of gaze: a comparison of biologically plausible mechanisms
The influence of structure on the response properties of biologically plausible neural network models
The hypothesis that Helicobacter pylori predisposes to Alzheimer’s disease is biologically plausible
Biologically plausible Reinforcement Learning
Stabilizing working memory in spiking networks with biologically plausible synaptic dynamics
Biologically plausible reinforcement learning of continuous actions
Degeneracy measures in biologically plausible random Boolean networks
NeuroCAD – the modular simulation environment for effective biologically plausible neuromodeling
Biologically plausible statistics from a Markov model of spiking cortical networks
Temporal sequence learning via adaptation in biologically plausible spiking neural networks
Efficient Realization of Large-Area E-Skin based on Biologically Plausible Principles
Adaptive structure evolution and biologically plausible synaptic plasticity for recurrent spiking neural networks
Object-based biasing for attentional control of gaze: a comparison of biologically plausible mechanisms
The influence of structure on the response properties of biologically plausible neural network models