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Particle Tracking Facilitates Real Time Capable Motion Correction in 2D or 3D Two-Photon Imaging of Neuronal Activity

Overview of attention for article published in Frontiers in Neural Circuits, August 2017
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Title
Particle Tracking Facilitates Real Time Capable Motion Correction in 2D or 3D Two-Photon Imaging of Neuronal Activity
Published in
Frontiers in Neural Circuits, August 2017
DOI 10.3389/fncir.2017.00056
Pubmed ID
Authors

Samira Aghayee, Daniel E. Winkowski, Zachary Bowen, Erin E. Marshall, Matt J. Harrington, Patrick O. Kanold, Wolfgang Losert

Abstract

The application of 2-photon laser scanning microscopy (TPLSM) techniques to measure the dynamics of cellular calcium signals in populations of neurons is an extremely powerful technique for characterizing neural activity within the central nervous system. The use of TPLSM on awake and behaving subjects promises new insights into how neural circuit elements cooperatively interact to form sensory perceptions and generate behavior. A major challenge in imaging such preparations is unavoidable animal and tissue movement, which leads to shifts in the imaging location (jitter). The presence of image motion can lead to artifacts, especially since quantification of TPLSM images involves analysis of fluctuations in fluorescence intensities for each neuron, determined from small regions of interest (ROIs). Here, we validate a new motion correction approach to compensate for motion of TPLSM images in the superficial layers of auditory cortex of awake mice. We use a nominally uniform fluorescent signal as a secondary signal to complement the dynamic signals from genetically encoded calcium indicators. We tested motion correction for single plane time lapse imaging as well as multiplane (i.e., volume) time lapse imaging of cortical tissue. Our procedure of motion correction relies on locating the brightest neurons and tracking their positions over time using established techniques of particle finding and tracking. We show that our tracking based approach provides subpixel resolution without compromising speed. Unlike most established methods, our algorithm also captures deformations of the field of view and thus can compensate e.g., for rotations. Object tracking based motion correction thus offers an alternative approach for motion correction, one that is well suited for real time spike inference analysis and feedback control, and for correcting for tissue distortions.

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The data shown below were collected from the profiles of 4 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 47 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 47 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 11 23%
Researcher 9 19%
Student > Master 5 11%
Student > Doctoral Student 4 9%
Student > Bachelor 4 9%
Other 4 9%
Unknown 10 21%
Readers by discipline Count As %
Neuroscience 9 19%
Agricultural and Biological Sciences 7 15%
Engineering 6 13%
Physics and Astronomy 6 13%
Computer Science 4 9%
Other 5 11%
Unknown 10 21%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 27 October 2017.
All research outputs
#14,951,544
of 22,997,544 outputs
Outputs from Frontiers in Neural Circuits
#700
of 1,222 outputs
Outputs of similar age
#187,665
of 316,580 outputs
Outputs of similar age from Frontiers in Neural Circuits
#17
of 21 outputs
Altmetric has tracked 22,997,544 research outputs across all sources so far. This one is in the 32nd percentile – i.e., 32% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,222 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.8. This one is in the 36th percentile – i.e., 36% 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 316,580 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 37th percentile – i.e., 37% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 21 others from the same source and published within six weeks on either side of this one. This one is in the 14th percentile – i.e., 14% of its contemporaries scored the same or lower than it.