ACTIVE SNIFFINGProject reference: 622943
Funded under :
The Algorithmic and Neuronal Basis of Active Sensing in the Case of Odor-Trail Tracking
Total cost:EUR 252 290,4
EU contribution:EUR 252 290,4
Topic(s):FP7-PEOPLE-2013-IOF - Marie Curie Action: "International Outgoing Fellowships for Career Development"
Call for proposal:FP7-PEOPLE-2013-IOFSee other projects for this call
Funding scheme:MC-IOF - International Outgoing Fellowships (IOF)
In its natural environment, any behaving animal is constantly bombarded with sensory information that must be parsed quickly by the animal to act appropriately. Yet, the nervous system is limited in the amount of information it can handle. Thus, to avoid sensory overload, specific aspects of these information streams have to be actively attended to by the animal. Such focusing is called active sensing and is a fundamental operational mode of many sensory systems. One ethologically important model for active sensing that has received increasing attention is odor-guided navigation in rodents. During odor-trail tracking, sniffing rates rise up to four times above the normal respiration frequency and each sniff selectively determines which part of the external world is sampled. Yet, an algorithmic understanding of their search strategy as well as its neuronal basis is lacking. My aims are to understand the neural representation of odors during this natural behavior and to reveal the neuronal basis of odor tracking behavior by following a multidisciplinary research program. I will develop an experimental setup that can flexibly deliver tightly controlled odor trails on a custom-build treadmill. By generating specifically tailored odor stimuli, I will be able to probe odor-guided navigation in real time and thus uncover the tracking algorithm. Moreover, I will record neuronal population activity from the early olfactory areas in mice that are following the trail. Such population activity in behaving animals can now be measured because of recent developments in miniature microscopes and genetically encoded calcium probes. I will show which aspects of the stimulus and behavioral variables are encoded by applying feature selection methods. Furthermore, by linking the behavioral decisions an animal takes during tracking to the recorded population response I will reveal which aspects of neuronal activity contribute to the tracking behavior in a mechanistic way.
EU contribution: EUR 252 290,4
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