Limits...
A statistical method of identifying interactions in neuron-glia systems based on functional multicell Ca2+ imaging.

Nakae K, Ikegaya Y, Ishikawa T, Oba S, Urakubo H, Koyama M, Ishii S - PLoS Comput. Biol. (2014)

Bottom Line: The interactions in our interest included functional connectivity and response functions.We evaluated the cross-validated likelihood of GLMs that resulted from the addition or removal of connections to confirm the existence of specific neuron-to-glia or glia-to-neuron connections.We only accepted addition or removal when the modification improved the cross-validated likelihood.

View Article: PubMed Central - PubMed

Affiliation: Integrated Systems Biology Laboratory, Graduate School of Informatics, Kyoto University, Sakyo-ku, Kyoto, Japan.

ABSTRACT
Crosstalk between neurons and glia may constitute a significant part of information processing in the brain. We present a novel method of statistically identifying interactions in a neuron-glia network. We attempted to identify neuron-glia interactions from neuronal and glial activities via maximum-a-posteriori (MAP)-based parameter estimation by developing a generalized linear model (GLM) of a neuron-glia network. The interactions in our interest included functional connectivity and response functions. We evaluated the cross-validated likelihood of GLMs that resulted from the addition or removal of connections to confirm the existence of specific neuron-to-glia or glia-to-neuron connections. We only accepted addition or removal when the modification improved the cross-validated likelihood. We applied the method to a high-throughput, multicellular in vitro Ca2+ imaging dataset obtained from the CA3 region of a rat hippocampus, and then evaluated the reliability of connectivity estimates using a statistical test based on a surrogate method. Our findings based on the estimated connectivity were in good agreement with currently available physiological knowledge, suggesting our method can elucidate undiscovered functions of neuron-glia systems.

Show MeSH

Related in: MedlinePlus

Response functions from neurons to glial cells and from glial cells to neurons.(Left) The estimated response functions of the identified connections from glial cells to neurons; the average and the 95% confidence intervals of the response functions, , are plotted by the red curve and blue intervals, respectively. (Right) The estimated response functions of the identified connections from neurons to glia; the average and the 95% confidence intervals of the response functions, , are plotted by the red curve and blue intervals, respectively.
© Copyright Policy
Related In: Results  -  Collection

License
getmorefigures.php?uid=PMC4230777&req=5

pcbi-1003949-g006: Response functions from neurons to glial cells and from glial cells to neurons.(Left) The estimated response functions of the identified connections from glial cells to neurons; the average and the 95% confidence intervals of the response functions, , are plotted by the red curve and blue intervals, respectively. (Right) The estimated response functions of the identified connections from neurons to glia; the average and the 95% confidence intervals of the response functions, , are plotted by the red curve and blue intervals, respectively.

Mentions: We found from visual inspections that each neuron had some tendency to be under the functional projection of a unique glial cell. This tendency was particularly strong for neurons under the functional projection of glial cells 1, 2, 3, and 4 (Fig. 4B). These findings are consistent with the anatomy of astrocytes, where they are known to occupy nonoverlapping local territories whose diameter is about 30. The findings are also in agreement with the hypothesis of functional islands of neurons modulated by individual astrocytes [44], [45]. Fig. 6 (left) suggests that the excitatory glia-to-neuron connections have a mean peak latency of around 500 ms. The t-test () determined the temporal average of the response functions to be significantly positive.


A statistical method of identifying interactions in neuron-glia systems based on functional multicell Ca2+ imaging.

Nakae K, Ikegaya Y, Ishikawa T, Oba S, Urakubo H, Koyama M, Ishii S - PLoS Comput. Biol. (2014)

Response functions from neurons to glial cells and from glial cells to neurons.(Left) The estimated response functions of the identified connections from glial cells to neurons; the average and the 95% confidence intervals of the response functions, , are plotted by the red curve and blue intervals, respectively. (Right) The estimated response functions of the identified connections from neurons to glia; the average and the 95% confidence intervals of the response functions, , are plotted by the red curve and blue intervals, respectively.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4230777&req=5

pcbi-1003949-g006: Response functions from neurons to glial cells and from glial cells to neurons.(Left) The estimated response functions of the identified connections from glial cells to neurons; the average and the 95% confidence intervals of the response functions, , are plotted by the red curve and blue intervals, respectively. (Right) The estimated response functions of the identified connections from neurons to glia; the average and the 95% confidence intervals of the response functions, , are plotted by the red curve and blue intervals, respectively.
Mentions: We found from visual inspections that each neuron had some tendency to be under the functional projection of a unique glial cell. This tendency was particularly strong for neurons under the functional projection of glial cells 1, 2, 3, and 4 (Fig. 4B). These findings are consistent with the anatomy of astrocytes, where they are known to occupy nonoverlapping local territories whose diameter is about 30. The findings are also in agreement with the hypothesis of functional islands of neurons modulated by individual astrocytes [44], [45]. Fig. 6 (left) suggests that the excitatory glia-to-neuron connections have a mean peak latency of around 500 ms. The t-test () determined the temporal average of the response functions to be significantly positive.

Bottom Line: The interactions in our interest included functional connectivity and response functions.We evaluated the cross-validated likelihood of GLMs that resulted from the addition or removal of connections to confirm the existence of specific neuron-to-glia or glia-to-neuron connections.We only accepted addition or removal when the modification improved the cross-validated likelihood.

View Article: PubMed Central - PubMed

Affiliation: Integrated Systems Biology Laboratory, Graduate School of Informatics, Kyoto University, Sakyo-ku, Kyoto, Japan.

ABSTRACT
Crosstalk between neurons and glia may constitute a significant part of information processing in the brain. We present a novel method of statistically identifying interactions in a neuron-glia network. We attempted to identify neuron-glia interactions from neuronal and glial activities via maximum-a-posteriori (MAP)-based parameter estimation by developing a generalized linear model (GLM) of a neuron-glia network. The interactions in our interest included functional connectivity and response functions. We evaluated the cross-validated likelihood of GLMs that resulted from the addition or removal of connections to confirm the existence of specific neuron-to-glia or glia-to-neuron connections. We only accepted addition or removal when the modification improved the cross-validated likelihood. We applied the method to a high-throughput, multicellular in vitro Ca2+ imaging dataset obtained from the CA3 region of a rat hippocampus, and then evaluated the reliability of connectivity estimates using a statistical test based on a surrogate method. Our findings based on the estimated connectivity were in good agreement with currently available physiological knowledge, suggesting our method can elucidate undiscovered functions of neuron-glia systems.

Show MeSH
Related in: MedlinePlus