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Quantifying barcodes of dendritic spines using entropy-based metrics.

Viggiano D, Srivastava DP, Speranza L, Perrone-Capano C, Bellenchi GC, di Porzio U, Buckley NJ - Sci Rep (2015)

Bottom Line: Spine motility analysis has become the mainstay for investigating synaptic plasticity but is limited in its versatility requiring complex, non automatized instrumentations.We describe an entropy-based method for determining the spatial distribution of dendritic spines that allows successful estimation of spine motility from still images.This method has the potential to extend the applicability of spine motility analysis to ex vivo preparations.

View Article: PubMed Central - PubMed

Affiliation: Institute of Genetics and Biophysics "Adriano Buzzati Traverso", CNR, Naples, 80131, Italy.

ABSTRACT
Spine motility analysis has become the mainstay for investigating synaptic plasticity but is limited in its versatility requiring complex, non automatized instrumentations. We describe an entropy-based method for determining the spatial distribution of dendritic spines that allows successful estimation of spine motility from still images. This method has the potential to extend the applicability of spine motility analysis to ex vivo preparations.

No MeSH data available.


The Sample entropy of the position of dendritic spines is an estimate of the spine motility.(A) the sample entropy of spine position shows a linear relationship with the percentage of motile spines in a dendrite (Pearson correlation = 0.728, n = 25 dendrites, p ≪ 0.01). Sample entropy is not correlated with the density of dendritic spines (Pearson correlation −0.298, p = 0.092) nor with the length of the measured dendrites (Pearson correlation = 0.062, p = 0.730). (B) It is possible to characterize the difference in percentage of motile spines among different transgenic animals using sample entropy of spine distribution on still images (no requirement of time-lapse data). Epac 2 ko mice have a lower number of motile spines (F(2.33) = 10.7, p ≪ 0.01) and, correspondingly, lower sample entropy (F(2,23) = 3.73, p = 0.04); data represent mean ± SEM; n = 8 dendrites from 3 wt animals, 13 dendrites from 3 het animals and 15 dendrites from 3 ko animals. To compare sample entropy and number of motile spines data have been represented as per cent of wild type animals.
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f3: The Sample entropy of the position of dendritic spines is an estimate of the spine motility.(A) the sample entropy of spine position shows a linear relationship with the percentage of motile spines in a dendrite (Pearson correlation = 0.728, n = 25 dendrites, p ≪ 0.01). Sample entropy is not correlated with the density of dendritic spines (Pearson correlation −0.298, p = 0.092) nor with the length of the measured dendrites (Pearson correlation = 0.062, p = 0.730). (B) It is possible to characterize the difference in percentage of motile spines among different transgenic animals using sample entropy of spine distribution on still images (no requirement of time-lapse data). Epac 2 ko mice have a lower number of motile spines (F(2.33) = 10.7, p ≪ 0.01) and, correspondingly, lower sample entropy (F(2,23) = 3.73, p = 0.04); data represent mean ± SEM; n = 8 dendrites from 3 wt animals, 13 dendrites from 3 het animals and 15 dendrites from 3 ko animals. To compare sample entropy and number of motile spines data have been represented as per cent of wild type animals.

Mentions: The results from Epac2 ko mice are shown in Fig. 3: the sample entropy of the spines is not related to the number of spines, but shows significant correlation with the number of motile spines. Importantly, pooling the data of dendritic spines from Epac2+/+, +/− or −/− mice, the sample entropy replicated the trend of the number of motile spines i.e. the decrease of spine motility seen in Epac2 −/− mice previously reproted8 was mirriored by a reduction of the entropy in Epac2 −/− animals.


Quantifying barcodes of dendritic spines using entropy-based metrics.

Viggiano D, Srivastava DP, Speranza L, Perrone-Capano C, Bellenchi GC, di Porzio U, Buckley NJ - Sci Rep (2015)

The Sample entropy of the position of dendritic spines is an estimate of the spine motility.(A) the sample entropy of spine position shows a linear relationship with the percentage of motile spines in a dendrite (Pearson correlation = 0.728, n = 25 dendrites, p ≪ 0.01). Sample entropy is not correlated with the density of dendritic spines (Pearson correlation −0.298, p = 0.092) nor with the length of the measured dendrites (Pearson correlation = 0.062, p = 0.730). (B) It is possible to characterize the difference in percentage of motile spines among different transgenic animals using sample entropy of spine distribution on still images (no requirement of time-lapse data). Epac 2 ko mice have a lower number of motile spines (F(2.33) = 10.7, p ≪ 0.01) and, correspondingly, lower sample entropy (F(2,23) = 3.73, p = 0.04); data represent mean ± SEM; n = 8 dendrites from 3 wt animals, 13 dendrites from 3 het animals and 15 dendrites from 3 ko animals. To compare sample entropy and number of motile spines data have been represented as per cent of wild type animals.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4588562&req=5

f3: The Sample entropy of the position of dendritic spines is an estimate of the spine motility.(A) the sample entropy of spine position shows a linear relationship with the percentage of motile spines in a dendrite (Pearson correlation = 0.728, n = 25 dendrites, p ≪ 0.01). Sample entropy is not correlated with the density of dendritic spines (Pearson correlation −0.298, p = 0.092) nor with the length of the measured dendrites (Pearson correlation = 0.062, p = 0.730). (B) It is possible to characterize the difference in percentage of motile spines among different transgenic animals using sample entropy of spine distribution on still images (no requirement of time-lapse data). Epac 2 ko mice have a lower number of motile spines (F(2.33) = 10.7, p ≪ 0.01) and, correspondingly, lower sample entropy (F(2,23) = 3.73, p = 0.04); data represent mean ± SEM; n = 8 dendrites from 3 wt animals, 13 dendrites from 3 het animals and 15 dendrites from 3 ko animals. To compare sample entropy and number of motile spines data have been represented as per cent of wild type animals.
Mentions: The results from Epac2 ko mice are shown in Fig. 3: the sample entropy of the spines is not related to the number of spines, but shows significant correlation with the number of motile spines. Importantly, pooling the data of dendritic spines from Epac2+/+, +/− or −/− mice, the sample entropy replicated the trend of the number of motile spines i.e. the decrease of spine motility seen in Epac2 −/− mice previously reproted8 was mirriored by a reduction of the entropy in Epac2 −/− animals.

Bottom Line: Spine motility analysis has become the mainstay for investigating synaptic plasticity but is limited in its versatility requiring complex, non automatized instrumentations.We describe an entropy-based method for determining the spatial distribution of dendritic spines that allows successful estimation of spine motility from still images.This method has the potential to extend the applicability of spine motility analysis to ex vivo preparations.

View Article: PubMed Central - PubMed

Affiliation: Institute of Genetics and Biophysics "Adriano Buzzati Traverso", CNR, Naples, 80131, Italy.

ABSTRACT
Spine motility analysis has become the mainstay for investigating synaptic plasticity but is limited in its versatility requiring complex, non automatized instrumentations. We describe an entropy-based method for determining the spatial distribution of dendritic spines that allows successful estimation of spine motility from still images. This method has the potential to extend the applicability of spine motility analysis to ex vivo preparations.

No MeSH data available.