↓ Skip to main content

Opposing Effects of Intrinsic Conductance and Correlated Synaptic Input on Vm-Fluctuations during Network Activity

Overview of attention for article published in Frontiers in Computational Neuroscience, January 2012
Altmetric Badge

Mentioned by

twitter
2 X users

Citations

dimensions_citation
15 Dimensions

Readers on

mendeley
33 Mendeley
citeulike
3 CiteULike
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Opposing Effects of Intrinsic Conductance and Correlated Synaptic Input on Vm-Fluctuations during Network Activity
Published in
Frontiers in Computational Neuroscience, January 2012
DOI 10.3389/fncom.2012.00040
Pubmed ID
Authors

Jens Kolind, Jørn Hounsgaard, Rune W. Berg

Abstract

Neurons often receive massive concurrent bombardment of synaptic inhibition and excitation during functional network activity. This increases membrane conductance and causes fluctuations in membrane potential (V(m)) and spike timing. The conductance increase is commonly attributed to synaptic conductance, but also includes the intrinsic conductances recruited during network activity. These two sources of conductance have contrasting dynamic properties at sub-threshold membrane potentials. Synaptic transmitter gated conductance changes abruptly and briefly with each presynaptic action potential. If the spikes arrive at random times the changes in synaptic conductance are therefore stochastic and rapid during intense network activity. In comparison, sub-threshold intrinsic conductances vary smoothly in time. In the present study this discrepancy is investigated using two conductance-based models: a (1) compartment model and a (2) compartment with realistic slow intrinsic conductances. We examine the effects of varying the relative contributions of non-fluctuating intrinsic conductance with fluctuating concurrent inhibitory and excitatory synaptic conductance. For given levels of correlation in the synaptic input we find that the magnitude of the membrane fluctuations uniquely determines the relative contribution of synaptic and intrinsic conductance. We also quantify how V(m)-fluctuations vary with synaptic correlations for fixed ratios of synaptic and intrinsic conductance. Interestingly, the levels of V(m) -fluctuations and conductance observed experimentally during functional network activity leave little room for intrinsic conductance to contribute. Even without intrinsic conductances the variance in V(m) -fluctuations can only be explained by a high degree of correlated firing among presynaptic neurons.

X Demographics

X Demographics

The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 33 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Denmark 2 6%
United States 2 6%
Israel 1 3%
Unknown 28 85%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 12 36%
Student > Master 6 18%
Professor 5 15%
Researcher 3 9%
Student > Bachelor 2 6%
Other 3 9%
Unknown 2 6%
Readers by discipline Count As %
Agricultural and Biological Sciences 16 48%
Neuroscience 6 18%
Computer Science 2 6%
Engineering 2 6%
Physics and Astronomy 2 6%
Other 4 12%
Unknown 1 3%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 30 September 2013.
All research outputs
#17,664,478
of 22,675,759 outputs
Outputs from Frontiers in Computational Neuroscience
#956
of 1,336 outputs
Outputs of similar age
#191,318
of 244,088 outputs
Outputs of similar age from Frontiers in Computational Neuroscience
#46
of 69 outputs
Altmetric has tracked 22,675,759 research outputs across all sources so far. This one is in the 19th percentile – i.e., 19% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,336 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.2. This one is in the 21st percentile – i.e., 21% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 244,088 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 19th percentile – i.e., 19% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 69 others from the same source and published within six weeks on either side of this one. This one is in the 21st percentile – i.e., 21% of its contemporaries scored the same or lower than it.