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Closed-loop neuro-robotic experiments to test computational properties of neuronal networks.

Tessadori J, Chiappalone M - J Vis Exp (2015)

Bottom Line: There is mounting evidence that, even at a very low level, the representation of a given stimulus might be dependent on context and history.If this is actually the case, bi-directional interactions between the brain (or if need be a reduced model of it) and sensory-motor system can shed a light on how encoding and decoding of information is performed.This architecture allows a quick selection of diverse encoding, decoding, and learning algorithms to test different hypotheses on the computational properties of neuronal networks.

View Article: PubMed Central - PubMed

Affiliation: Neuroscience and Brain Technologies, Istituto Italiano di Tecnologia.

ABSTRACT
Information coding in the Central Nervous System (CNS) remains unexplored. There is mounting evidence that, even at a very low level, the representation of a given stimulus might be dependent on context and history. If this is actually the case, bi-directional interactions between the brain (or if need be a reduced model of it) and sensory-motor system can shed a light on how encoding and decoding of information is performed. Here an experimental system is introduced and described in which the activity of a neuronal element (i.e., a network of neurons extracted from embryonic mammalian hippocampi) is given context and used to control the movement of an artificial agent, while environmental information is fed back to the culture as a sequence of electrical stimuli. This architecture allows a quick selection of diverse encoding, decoding, and learning algorithms to test different hypotheses on the computational properties of neuronal networks.

No MeSH data available.


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Closed-loop neuro-robotic experiments to test computational properties of neuronal networks.

Tessadori J, Chiappalone M - J Vis Exp (2015)

© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4401171&req=5

Bottom Line: There is mounting evidence that, even at a very low level, the representation of a given stimulus might be dependent on context and history.If this is actually the case, bi-directional interactions between the brain (or if need be a reduced model of it) and sensory-motor system can shed a light on how encoding and decoding of information is performed.This architecture allows a quick selection of diverse encoding, decoding, and learning algorithms to test different hypotheses on the computational properties of neuronal networks.

View Article: PubMed Central - PubMed

Affiliation: Neuroscience and Brain Technologies, Istituto Italiano di Tecnologia.

ABSTRACT
Information coding in the Central Nervous System (CNS) remains unexplored. There is mounting evidence that, even at a very low level, the representation of a given stimulus might be dependent on context and history. If this is actually the case, bi-directional interactions between the brain (or if need be a reduced model of it) and sensory-motor system can shed a light on how encoding and decoding of information is performed. Here an experimental system is introduced and described in which the activity of a neuronal element (i.e., a network of neurons extracted from embryonic mammalian hippocampi) is given context and used to control the movement of an artificial agent, while environmental information is fed back to the culture as a sequence of electrical stimuli. This architecture allows a quick selection of diverse encoding, decoding, and learning algorithms to test different hypotheses on the computational properties of neuronal networks.

No MeSH data available.