Benjamin de Bivort

 

Assistant Professor
Organismic & Evolutionary Biology

Harvard University
52 Oxford Street
Room 248
Cambridge, MA 02138
Tel: 617-230-3769
Email: debivort@rowland.harvard.edu
Visit my lab page here.








The goal of our lab is to understand the neurobiological mechanisms of ecologically and evolutionarily relevant behaviors using techniques drawn from circuit neuroscience, comparative genomics and ethology, as they are manifested in fruit flies from the genus Drosophila.

Here are some of the questions we are working on:

What underlies the behavioral differences between genetically identical individuals? Individual flies display idiosyncratic behavioral tendencies in every paradigm we've examined. These idiosyncratic behaviors persist for the animals' lifetimes and thus constitute a form of fly personality. We have identified genes and neural circuits that regulate the extent of inter individual variability, implying that this behavioral variability is under active control. We are currently pursuing deeper understanding of the molecular and ecological underpinnings of behavioral idiosyncrasy.

What genetic changes underly the evolved differences in behavior between related strains and species? After individual-to-individual variability in behavior, species-to-species variation is the next largest source of variance in behavior. It is a long-term goal of the lab to determine how small genetic differences between species alter the physiology and information processing of neural circuits to determine the behavioral differences between them.

Is there a basic behavioral vocabulary? Careful characterization of both individual and species-level behavioral differences requires high-throughput quantitative characterizations of behavior. We have developed a number of instruments and methodologies to do this, including an imaging rig that allows us to automatically record the position of a single fly's legs as it runs on a floating ball. From this data we can automatically characterize its behavior using both supervised and unsupervised classification algorithms. The latter approach gives us the list of motor primitives being implemented by the animal, and a target list for identifying the central pattern generators responsible for behavior at the lowest level.


For a complete listing of publications click here.



Last Update: 11/7/2013