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Local field potentials reflect multiple spatial scales in V4

Overview of attention for article published in Frontiers in Computational Neuroscience, January 2013
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Title
Local field potentials reflect multiple spatial scales in V4
Published in
Frontiers in Computational Neuroscience, January 2013
DOI 10.3389/fncom.2013.00021
Pubmed ID
Authors

Patrick J. Mineault, Theodoros P. Zanos, Christopher C. Pack

Abstract

Local field potentials (LFP) reflect the properties of neuronal circuits or columns recorded in a volume around a microelectrode (Buzsáki et al., 2012). The extent of this integration volume has been a subject of some debate, with estimates ranging from a few hundred microns (Katzner et al., 2009; Xing et al., 2009) to several millimeters (Kreiman et al., 2006). We estimated receptive fields (RFs) of multi-unit activity (MUA) and LFPs at an intermediate level of visual processing, in area V4 of two macaques. The spatial structure of LFP receptive fields varied greatly as a function of time lag following stimulus onset, with the retinotopy of LFPs matching that of MUAs at a restricted set of time lags. A model-based analysis of the LFPs allowed us to recover two distinct stimulus-triggered components: an MUA-like retinotopic component that originated in a small volume around the microelectrodes (~350 μm), and a second component that was shared across the entire V4 region; this second component had tuning properties unrelated to those of the MUAs. Our results suggest that the LFP reflects neural activity across multiple spatial scales, which both complicates its interpretation and offers new opportunities for investigating the large-scale structure of network processing.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 104 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 3 3%
Germany 1 <1%
India 1 <1%
Brazil 1 <1%
Belarus 1 <1%
Canada 1 <1%
Unknown 96 92%

Demographic breakdown

Readers by professional status Count As %
Researcher 29 28%
Student > Ph. D. Student 19 18%
Professor > Associate Professor 13 13%
Student > Master 8 8%
Student > Doctoral Student 7 7%
Other 19 18%
Unknown 9 9%
Readers by discipline Count As %
Neuroscience 34 33%
Agricultural and Biological Sciences 20 19%
Engineering 14 13%
Psychology 6 6%
Medicine and Dentistry 6 6%
Other 10 10%
Unknown 14 13%
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 17 April 2013.
All research outputs
#18,336,865
of 22,707,247 outputs
Outputs from Frontiers in Computational Neuroscience
#1,050
of 1,336 outputs
Outputs of similar age
#218,008
of 280,717 outputs
Outputs of similar age from Frontiers in Computational Neuroscience
#92
of 131 outputs
Altmetric has tracked 22,707,247 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% 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 13th percentile – i.e., 13% 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 280,717 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 11th percentile – i.e., 11% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 131 others from the same source and published within six weeks on either side of this one. This one is in the 20th percentile – i.e., 20% of its contemporaries scored the same or lower than it.