Delayed mutual information infers patterns of synaptic connectivity in a proprioceptive neural network
Delayed mutual information infers patterns of synaptic connectivity in a proprioceptive neural network
Understanding the patterns of interconnections between neurons in complex networks is an enormous challenge using traditional physiological approaches. Here we combine the use of an information theoretic approach with intracellular recording to establish patterns of connections between layers of interneurons in a neural network responsible for mediating reflex movements of the hind limb of an insect. By analysing delayed mutual information of the synaptic and spiking responses of sensory neurons, spiking and nonspiking interneurons in response to movement of a joint receptor that monitors the position of the tibia relative to the femur, we are able to predict the patterns of interconnections between the layers of sensory neurons and interneurons in the network, with results matching closely those known from the literature. In addition, we use cross-correlation methods to establish the sign of those interconnections and show that they also show a high degree of similarity with those established for these networks over the last 30 years. The method proposed in this paper has great potential to elucidate functional connectivity at the neuronal level in many different neuronal networks
427-438
Endo, Wagner
1fa17fe8-0b11-4c18-ad1f-e809c65f8544
Santos, Fernando P.
f6e06f62-38ce-48bf-8d7e-5dd13791fa00
Simpson, David
53674880-f381-4cc9-8505-6a97eeac3c2a
Maciel, Carlos D.
0b9d2f77-4d09-49f8-a8f6-8ceb2254d14b
Newland, Philip L.
7a018c0e-37ba-40f5-bbf6-49ab0f299dbb
April 2015
Endo, Wagner
1fa17fe8-0b11-4c18-ad1f-e809c65f8544
Santos, Fernando P.
f6e06f62-38ce-48bf-8d7e-5dd13791fa00
Simpson, David
53674880-f381-4cc9-8505-6a97eeac3c2a
Maciel, Carlos D.
0b9d2f77-4d09-49f8-a8f6-8ceb2254d14b
Newland, Philip L.
7a018c0e-37ba-40f5-bbf6-49ab0f299dbb
Endo, Wagner, Santos, Fernando P., Simpson, David, Maciel, Carlos D. and Newland, Philip L.
(2015)
Delayed mutual information infers patterns of synaptic connectivity in a proprioceptive neural network.
Journal of Computational Neuroscience, 38 (2), .
(doi:10.1007/s10827-015-0548-6).
(PMID:25643986)
Abstract
Understanding the patterns of interconnections between neurons in complex networks is an enormous challenge using traditional physiological approaches. Here we combine the use of an information theoretic approach with intracellular recording to establish patterns of connections between layers of interneurons in a neural network responsible for mediating reflex movements of the hind limb of an insect. By analysing delayed mutual information of the synaptic and spiking responses of sensory neurons, spiking and nonspiking interneurons in response to movement of a joint receptor that monitors the position of the tibia relative to the femur, we are able to predict the patterns of interconnections between the layers of sensory neurons and interneurons in the network, with results matching closely those known from the literature. In addition, we use cross-correlation methods to establish the sign of those interconnections and show that they also show a high degree of similarity with those established for these networks over the last 30 years. The method proposed in this paper has great potential to elucidate functional connectivity at the neuronal level in many different neuronal networks
Text
art%3A10.1007%2Fs10827-015-0548-6.pdf
- Other
More information
Accepted/In Press date: 21 January 2015
Published date: April 2015
Organisations:
Centre for Biological Sciences
Identifiers
Local EPrints ID: 377484
URI: http://eprints.soton.ac.uk/id/eprint/377484
ISSN: 0929-5313
PURE UUID: 99973c55-8a35-4243-8bf0-67be31b2d770
Catalogue record
Date deposited: 08 Jun 2015 13:05
Last modified: 15 Mar 2024 03:14
Export record
Altmetrics
Contributors
Author:
Wagner Endo
Author:
Fernando P. Santos
Author:
Carlos D. Maciel
Download statistics
Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.
View more statistics