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Time-Dependent Increase in Network Response to Stimulation.

Hamilton F, Graham R, Luu L, Peixoto N - PLoS ONE (2015)

Bottom Line: Here we demonstrate the effects of a high frequency electrical stimulation signal in training cultured networks of cortical neurons.This increase was found to be statistically significant as compared to control networks that did not receive training.The timing of this increase suggests potentiation of synaptic mechanisms.

View Article: PubMed Central - PubMed

Affiliation: Department of Electrical and Computer Engineering, George Mason University, Fairfax, VA, United States of America.

ABSTRACT
In vitro neuronal cultures have become a popular method with which to probe network-level neuronal dynamics and phenomena in controlled laboratory settings. One of the key dynamics of interest in these in vitro studies has been the extent to which cultured networks display properties indicative of learning. Here we demonstrate the effects of a high frequency electrical stimulation signal in training cultured networks of cortical neurons. Networks receiving this training signal displayed a time-dependent increase in the response to a low frequency probing stimulation, particularly in the time window of 20-50 ms after stimulation. This increase was found to be statistically significant as compared to control networks that did not receive training. The timing of this increase suggests potentiation of synaptic mechanisms. To further investigate this possibility, we leveraged the powerful Cox statistical connectivity method as previously investigated by our group. This method was used to identify and track changes in network connectivity strength.

No MeSH data available.


Effect of training is time-dependent.A statistically significant interaction between time after stimulus and training was found for both (a) spike reliability and (b) spike frequency (p < 0.05). A Tukey post-hoc analysis was run to determine the points of statistical significance. (**) denotes p < 0.01 significance and (*) denotes p < 0.05 significance. Post-hoc analysis showed that there was a statistically significant difference in normalized spike frequency and normalized spike reliability at time bins 20–30 ms, 30–40 ms and 40–50 ms after stimulus between trained and control networks.
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pone.0142399.g005: Effect of training is time-dependent.A statistically significant interaction between time after stimulus and training was found for both (a) spike reliability and (b) spike frequency (p < 0.05). A Tukey post-hoc analysis was run to determine the points of statistical significance. (**) denotes p < 0.01 significance and (*) denotes p < 0.05 significance. Post-hoc analysis showed that there was a statistically significant difference in normalized spike frequency and normalized spike reliability at time bins 20–30 ms, 30–40 ms and 40–50 ms after stimulus between trained and control networks.

Mentions: Further analysis indicated a statistically significant interaction between spike frequency and time after stimulus(F(1, 1.838) = 4.290, p < 0.05) and between spike reliability and time after stimulus (F(1, 1.768) = 3.611, p < 0.05). Fig 5 shows the normalized frequency and reliability of control and trained networks as a function of time after stimulus. A Tukey post-hoc analysis was run to determine the points of statistical significance. This post-hoc analysis indicated a statistically significant difference between spike frequency of control and trained networks at time bins 20–30 ms (p < 0.01), 30–40 ms (p < 0.01) and 40–50 ms (p < 0.01) after stimulus. Reliability between control and trained networks was also statistically different at time bins 20–30 ms (p < 0.05), 30–40 ms (p < 0.01) and 40–50 ms (p < 0.01).


Time-Dependent Increase in Network Response to Stimulation.

Hamilton F, Graham R, Luu L, Peixoto N - PLoS ONE (2015)

Effect of training is time-dependent.A statistically significant interaction between time after stimulus and training was found for both (a) spike reliability and (b) spike frequency (p < 0.05). A Tukey post-hoc analysis was run to determine the points of statistical significance. (**) denotes p < 0.01 significance and (*) denotes p < 0.05 significance. Post-hoc analysis showed that there was a statistically significant difference in normalized spike frequency and normalized spike reliability at time bins 20–30 ms, 30–40 ms and 40–50 ms after stimulus between trained and control networks.
© Copyright Policy
Related In: Results  -  Collection

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getmorefigures.php?uid=PMC4636320&req=5

pone.0142399.g005: Effect of training is time-dependent.A statistically significant interaction between time after stimulus and training was found for both (a) spike reliability and (b) spike frequency (p < 0.05). A Tukey post-hoc analysis was run to determine the points of statistical significance. (**) denotes p < 0.01 significance and (*) denotes p < 0.05 significance. Post-hoc analysis showed that there was a statistically significant difference in normalized spike frequency and normalized spike reliability at time bins 20–30 ms, 30–40 ms and 40–50 ms after stimulus between trained and control networks.
Mentions: Further analysis indicated a statistically significant interaction between spike frequency and time after stimulus(F(1, 1.838) = 4.290, p < 0.05) and between spike reliability and time after stimulus (F(1, 1.768) = 3.611, p < 0.05). Fig 5 shows the normalized frequency and reliability of control and trained networks as a function of time after stimulus. A Tukey post-hoc analysis was run to determine the points of statistical significance. This post-hoc analysis indicated a statistically significant difference between spike frequency of control and trained networks at time bins 20–30 ms (p < 0.01), 30–40 ms (p < 0.01) and 40–50 ms (p < 0.01) after stimulus. Reliability between control and trained networks was also statistically different at time bins 20–30 ms (p < 0.05), 30–40 ms (p < 0.01) and 40–50 ms (p < 0.01).

Bottom Line: Here we demonstrate the effects of a high frequency electrical stimulation signal in training cultured networks of cortical neurons.This increase was found to be statistically significant as compared to control networks that did not receive training.The timing of this increase suggests potentiation of synaptic mechanisms.

View Article: PubMed Central - PubMed

Affiliation: Department of Electrical and Computer Engineering, George Mason University, Fairfax, VA, United States of America.

ABSTRACT
In vitro neuronal cultures have become a popular method with which to probe network-level neuronal dynamics and phenomena in controlled laboratory settings. One of the key dynamics of interest in these in vitro studies has been the extent to which cultured networks display properties indicative of learning. Here we demonstrate the effects of a high frequency electrical stimulation signal in training cultured networks of cortical neurons. Networks receiving this training signal displayed a time-dependent increase in the response to a low frequency probing stimulation, particularly in the time window of 20-50 ms after stimulation. This increase was found to be statistically significant as compared to control networks that did not receive training. The timing of this increase suggests potentiation of synaptic mechanisms. To further investigate this possibility, we leveraged the powerful Cox statistical connectivity method as previously investigated by our group. This method was used to identify and track changes in network connectivity strength.

No MeSH data available.