iLAM : Imaging Locomotor Activity Monitor for circadian phenotyping of large‐bodied flying insects
Year: 2024
Type: article
Abstract: Historically, most insect chronoecological research has used direct observations, cameras or infrared beam‐based monitors to quantify movement across timed intervals. Although some alternative DIY systems are cheaper than the current standard locomotor activity monitor, these options remain complicated to build and/or computationally intensive. We developed the i maging L ocomotor A ctivity M onitor ( iLAM ), an affordable (~$75 USD/unit) system for activity quantification. The iLAM utilizes a Raspberry Pi Zero W computer and night‐vision camera inside a flight cage to photograph a population of insects at user‐defined intervals. Open‐source, modular R‐scripts process the images and output a file containing the number, size, coordinate location and timestamp of all movements (blobs) identified between consecutive images. Output can be analysed directly or converted into the standard TriKinetics DAM format. We demonstrated the flexibility and power of the iLAM system by comparing diel and circadian activity of different insect species (fireflies: Photinus marginellus , P. greeni , P. obscurellus ), ecotypes (moths: Ostrinia nubilalis ) and sexes (moths: O. nubilalis ). Data captured by only six iLAMs ($450) identified that peak activity of O. nubilalis females (AZT: 19.2 h) occurs significantly earlier than males (22.0 h). Additionally, male moths from a univoltine population exhibited a significantly shorter endogenous period length (AZT: 21.3 h) than males from a bivoltine genetic background (22.7 h). The iLAM will serve as a valuable tool for researchers seeking to measure locomotor activity across diverse species, sexes and populations in constant and changing environments.
Source: Methods in Ecology and Evolution
Authors: Jacob N. Dayton, Avalon C.S. Owens
Institutions: Tufts University, Harvard University, Rowland Institute at Harvard
Language: English
Subfield: Endocrine and Autonomic Systems
Field: Neuroscience
Domain: Life Sciences
Open Access status: gold
Estimated APC paid: $3,500
OpenAlex ID: W4401686469