↓ Skip to main content

Measuring behavior across scales

Overview of attention for article published in BMC Biology, February 2018
Altmetric Badge

Mentioned by

blogs
1 blog
twitter
47 X users

Citations

dimensions_citation
158 Dimensions

Readers on

mendeley
290 Mendeley
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
Measuring behavior across scales
Published in
BMC Biology, February 2018
DOI 10.1186/s12915-018-0494-7
Pubmed ID
Authors

Gordon J. Berman

Abstract

The need for high-throughput, precise, and meaningful methods for measuring behavior has been amplified by our recent successes in measuring and manipulating neural circuitry. The largest challenges associated with moving in this direction, however, are not technical but are instead conceptual: what numbers should one put on the movements an animal is performing (or not performing)? In this review, I will describe how theoretical and data analytical ideas are interfacing with recently-developed computational and experimental methodologies to answer these questions across a variety of contexts, length scales, and time scales. I will attempt to highlight commonalities between approaches and areas where further advances are necessary to place behavior on the same quantitative footing as other scientific fields.

X Demographics

X Demographics

The data shown below were collected from the profiles of 47 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 290 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 290 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 83 29%
Researcher 50 17%
Student > Master 36 12%
Student > Bachelor 24 8%
Student > Doctoral Student 11 4%
Other 43 15%
Unknown 43 15%
Readers by discipline Count As %
Neuroscience 86 30%
Agricultural and Biological Sciences 72 25%
Engineering 18 6%
Computer Science 15 5%
Physics and Astronomy 10 3%
Other 37 13%
Unknown 52 18%