Increasing Sensor Flexibility Through Neuromodulation

By J. Birmingham. 2001

16 citations recorded by the source corpus.

Both biological and man-made motor control networks require input from sensors to allow for modification of the motor program. Real sensory neurons are more flexible than typical robotic sensors because they are dynamic rather than static. The membrane properties of neurons and hence their excitability can be modified by the presence of neuromodulatory substances. In the case of a sensory neuron, this can change, in a functionally significant way, the code used to describe a stimulus. For instance, extension of the neuron’s dynamic range or modification of its filtering characteristics can result. This flexibility has an apparent cost. The code used may be situation-dependent and hence difficult to interpret. To address this issue and to understand how neuromodulation is used effectively in a motor control network, I am studying the GPR2 stretch receptor in the crustacean stomatogastric nervous system. Several different neuromodulatory substances can modify its encoding properties. Comparisons of physiological and anatomical evidence suggest that neuromodulation can be effected both by GPR2 itself and by other neurons in the network. These results suggest that the analog of neuromodulation might be useful for improving sensor performance in an artificial motor control system.

Subfields: Cellular and Molecular Neuroscience, Electrical and Electronic Engineering, Molecular Biology

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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 ”
Cellular, synaptic and network effects of neuromodulation (2002, background): “For example, crustacean muscle stretch receptors are sensitive to a number of amines and neuropeptides that alter both the spike rate and adaptation properties of the neuron (Birmingham, 2001; Pasztor & Bush, 1989).”
Evolutionary and Computational Advantages of Neuromodulated Plasticity (2008, background): “Modulatory dynamics of this kind in biological networks was suggested to increase sensory flexibility (Birmingham, 2001).”