Neuromodulation of Reactive Sensorimotor Mappings as a Short-Term Memory Mechanism in Delayed Response Tasks

By Tom Ziemke, Mikael Thieme. 2002

66 citations recorded by the source corpus.

Subfields: Cognitive Neuroscience, Electrical and Electronic Engineering

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Citations in the corpus

Born to Learn: the Inspiration, Progress, and Future of Evolved Plastic Artificial Neural Networks (2017, methodology): “Such a modulation of signals, or gated learning (Abbott, 1990), allows for the regulation and learning of behaviors as shown in numerous computational models (Baxter et al., 1999; Suri et al., 2001; Birmingham, 2001; Alexander and Sporns, 2002; Doya, 2002; Fujii et al., 2002; Suri, 2002; Ziemke and ”
Rare Neural Correlations Implement Robotic Conditioning with Delayed Rewards and Disturbances (2013, background): “…of models of modulated plasticity with rate-based neurons (e.g., Montague et al., 1996; Alexander and Sporns, 2002; Sporns and Alexander, 2002; Ziemke and Thieme, 2002; Soltoggio et al., 2008; Soltoggio and Stanley, 2012), and with spiking neurons and modulated…”
Rule Extraction from Recurrent Neural Networks: ATaxonomy and Review (2005, background): “…Wiles & Elman 1999, Rodriguez 1999, Tabor & Tanenhaus 1999), activation values plotted over time (e.g. Husbands, Harvey & Cliﬀ 1995, Meeden 1996, Ziemke & Thieme 2002), iterated maps (e.g. Wiles & Elman 1995), vector ﬂow ﬁelds (e.g. Rodriguez et al. 1999, Rodriguez 1999), external behaviour…”
Exploring the T-Maze: Evolving Learning-Like Robot Behaviors Using CTRNNs (2003, background): “Previous work on TMaze navigation in evolutionary robotics includes delayed response tasks where the robots had to perform one or several turns in a maze on the basis of light source cues given to the robot [5][13].”
Evolutionary Advantages of Neuromodulated Plasticity in Dynamic, Reward-based Scenarios (2008, background): “Short term memory by means of neuromodulation was investigated in ( Ziemke and Thieme, 2002 ) where a robot navigated in a T-maze and remembered turning directions according to visual clues in the maze.”
Evolutionary and Computational Advantages of Neuromodulated Plasticity (2008, background): “Short-term memory with modulated plasticity was investigated in (Ziemke and Thieme, 2002) where a robot navigated in a T-maze and remembered turning directions according to visual clues in the maze.”
Neuromodulation Improves the Evolution of Forward Models (2016, background): “Inspired by this natural phenomenon, researchers have added an abstraction of neuromodulation to NNs to improve short-term memory [34], evolvability [23], learning and adaptability [26], and finegrained plasticity control [24].”
Overcoming deception in evolution of cognitive behaviors (2014, methodology): “Such approaches include applying incremental evolution [21], refined fitness functions [18], more complicated neural models [28] or additional helper objectives [12, 13].”