@article {6911,
	title = {Discovery of brainwide neural-behavioral maps via multiscale unsupervised structure learning},
	journal = {Science},
	volume = {344},
	year = {2014},
	month = {2014 Mar 27},
	pages = {386-92},
	chapter = {386},
	abstract = {<p>A single nervous system can generate many distinct motor patterns. Identifying which neurons and circuits control which behaviors has been a laborious piecemeal process, usually for one observer-defined behavior at a time. We present a fundamentally different approach to neuron-behavior mapping. We optogenetically activated 1,054 identified neuron lines in Drosophila larva and tracked the behavioral responses from 37,780 animals. Applying multiscale unsupervised structure learning methods to the behavioral data identified 29 discrete statistically distinguishable and observer-unbiased behavioral phenotypes. Mapping the neural lines to the behavior(s) they evoke provides a behavioral reference atlas for neuron subsets covering a large fraction of larval neurons. This atlas is a starting point for connectivity- and activity-mapping studies to further investigate the mechanisms by which neurons mediate diverse behaviors.</p>
},
	issn = {1095-9203},
	doi = {10.1126/science.1250298},
	author = {Vogelstein, Joshua T and Park, Youngser and Ohyama, Tomoko and Kerr, Rex and Truman, James W and Priebe, Carey E. and Zlatic, Marta}
}
