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Methods for predicting cortical UP and DOWN states from the phase of deep layer local field potentials

Overview of attention for article published in Journal of Computational Neuroscience, March 2010
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Title
Methods for predicting cortical UP and DOWN states from the phase of deep layer local field potentials
Published in
Journal of Computational Neuroscience, March 2010
DOI 10.1007/s10827-010-0228-5
Pubmed ID
Authors

Aman B. Saleem, Paul Chadderton, John Apergis-Schoute, Kenneth D. Harris, Simon R. Schultz

Abstract

During anesthesia, slow-wave sleep and quiet wakefulness, neuronal membrane potentials collectively switch between de- and hyperpolarized levels, the cortical UP and DOWN states. Previous studies have shown that these cortical UP/DOWN states affect the excitability of individual neurons in response to sensory stimuli, indicating that a significant amount of the trial-to-trial variability in neuronal responses can be attributed to ongoing fluctuations in network activity. However, as intracellular recordings are frequently not available, it is important to be able to estimate their occurrence purely from extracellular data. Here, we combine in vivo whole cell recordings from single neurons with multi-site extracellular microelectrode recordings, to quantify the performance of various approaches to predicting UP/DOWN states from the deep-layer local field potential (LFP). We find that UP/DOWN states in deep cortical layers of rat primary auditory cortex (A1) are predictable from the phase of LFP at low frequencies (< 4 Hz), and that the likelihood of a given state varies sinusoidally with the phase of LFP at these frequencies. We introduce a novel method of detecting cortical state by combining information concerning the phase of the LFP and ongoing multi-unit activity.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 191 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 5 3%
France 2 1%
Hungary 1 <1%
Germany 1 <1%
Italy 1 <1%
Colombia 1 <1%
India 1 <1%
Finland 1 <1%
Malta 1 <1%
Other 1 <1%
Unknown 176 92%

Demographic breakdown

Readers by professional status Count As %
Researcher 51 27%
Student > Ph. D. Student 40 21%
Student > Master 15 8%
Professor > Associate Professor 14 7%
Student > Bachelor 12 6%
Other 38 20%
Unknown 21 11%
Readers by discipline Count As %
Agricultural and Biological Sciences 64 34%
Neuroscience 55 29%
Engineering 13 7%
Medicine and Dentistry 9 5%
Physics and Astronomy 8 4%
Other 20 10%
Unknown 22 12%
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 12 May 2010.
All research outputs
#15,240,835
of 22,660,862 outputs
Outputs from Journal of Computational Neuroscience
#168
of 306 outputs
Outputs of similar age
#76,565
of 93,739 outputs
Outputs of similar age from Journal of Computational Neuroscience
#3
of 3 outputs
Altmetric has tracked 22,660,862 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 306 research outputs from this source. They receive a mean Attention Score of 3.4. This one is in the 30th percentile – i.e., 30% 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 93,739 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 10th percentile – i.e., 10% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 3 others from the same source and published within six weeks on either side of this one.