  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.
