@article {69721,
	title = {A split-GAL4 driver line resource for Drosophila neuron types},
	year = {2025},
	month = {01/2025},
	doi = {10.7554/elife.98405.3},
	url = {http://dx.doi.org/10.7554/eLife.98405.3},
	author = {Meissner, Geoffrey W and Vannan, Allison and Jeter, Jennifer and Close, Kari and Depasquale, Gina M and Dorman, Zachary and Forster, Kaitlyn and Beringer, Jaye Anne and Gibney, Theresa V and Hausenfluck, Joanna H and He, Yisheng and Henderson, Kristin and Johnson, Lauren and Johnston, Rebecca M and Ihrke, Gudrun and Iyer, Nirmala and Lazarus, Rachel and Lee, Kelley and Li, Hsing-Hsi and Liaw, Hua-Peng and Melton, Brian and Miller, Scott and Motaher, Reeham and Novak, Alexandra and Ogundeyi, Omotara and Petruncio, Alyson and Price, Jacquelyn and Protopapas, Sophia and Tae, Susana and Taylor, Jennifer and Vorimo, Rebecca and Yarbrough, Brianna and Zeng, Kevin Xiankun and Zugates, Christopher T and Dionne, Heather and Angstadt, Claire and Ashley, Kelly and Cavallaro, Amanda and Dang, Tam and Gonzalez, Guillermo A and Hibbard, Karen L and Huang, Cuizhen and Kao, Jui-Chun and Laverty, Todd and Mercer, Monti and Perez, Brenda and Pitts, Scarlett and Ruiz, Danielle and Vallanadu, Viruthika and Zheng, Grace Zhiyu and Goina, Cristian and Otsuna, Hideo and Rokicki, Konrad and Svirskas, Robert R and Cheong, Han Sj and Dolan, Michael-John and Ehrhardt, Erica and Feng, Kai and El Galfi, Basel and Goldammer, Jens and Huston, Stephen J and Hu, Nan and Ito, Masayoshi and McKellar, Claire and minegishi, ryo and Namiki, Shigehiro and Nern, Aljoscha and Schretter, Catherine E and Sterne, Gabriella R and Venkatasubramanian, Lalanti and Wang, Kaiyu and Wolff, Tanya and Wu, Ming and George, Reed and Malkesman, Oz and Aso, Yoshinori and Card, Gwyneth M and Dickson, Barry J and Korff, Wyatt and Ito, Kei and Truman, James W and Zlatic, Marta and Rubin, Gerald M}
}
@article {68414,
	title = {High-throughput automated methods for classical and operant conditioning of larvae.},
	journal = {eLife},
	volume = {11},
	year = {2022},
	month = {2022 Oct 28},
	abstract = {<p>Learning which stimuli (classical conditioning) or which actions (operant conditioning) predict rewards or punishments can improve chances of survival. However, the circuit mechanisms that underlie distinct types of associative learning are still not fully understood. Automated, high-throughput paradigms for studying different types of associative learning, combined with manipulation of specific neurons in freely behaving animals, can help advance this field. The Drosophila melanogaster larva is a tractable model system for studying the circuit basis of behaviour, but many forms of associative learning have not yet been demonstrated in this animal. Here, we developed a high-throughput (i. e. multi-larva) training system that combines real-time behaviour detection of freely moving larvae with targeted opto- and thermogenetic stimulation of tracked animals. Both stimuli are controlled in either open- or closed-loop, and delivered with high temporal and spatial precision. Using this tracker, we show for the first time that Drosophila larvae can perform classical conditioning with no overlap between sensory stimuli (i. e. trace conditioning). We also demonstrate that larvae are capable of operant conditioning by inducing a bend direction preference through optogenetic activation of reward-encoding serotonergic neurons. Our results extend the known associative learning capacities of Drosophila larvae. Our automated training rig will facilitate the study of many different forms of associative learning and the identification of the neural circuits that underpin them.</p>
},
	issn = {2050-084X},
	doi = {10.7554/eLife.70015},
	author = {Croteau-Chonka, Elise C and Clayton, Michael S and Venkatasubramanian, Lalanti and Harris, Samuel N and Jones, Benjamin M W and Narayan, Lakshmi and Winding, Michael and Masson, Jean-Baptiste and Zlatic, Marta and Klein, Kristina T}
}
@article {65810,
	title = {Comparative Connectomics Reveals How Partner Identity, Location, and Activity Specify Synaptic Connectivity in Drosophila.},
	journal = {Neuron},
	volume = {109},
	year = {2021},
	month = {2021 Jan 06},
	pages = {105-22},
	abstract = {<p>The mechanisms by which synaptic partners recognize each other and establish appropriate numbers of connections during embryonic development to form functional neural circuits are poorly understood. We combined electron microscopy reconstruction, functional imaging of neural activity, and behavioral experiments to elucidate the roles of (1) partner identity, (2) location, and (3) activity in circuit assembly in the embryonic nerve cord of Drosophila. We found that postsynaptic partners are able to find and connect to their presynaptic partners even when these have been shifted to ectopic locations or silenced. However, orderly positioning of axon terminals by positional cues and synaptic activity is required for appropriate numbers of connections between specific partners, for appropriate balance between excitatory and inhibitory connections, and for appropriate functional connectivity and behavior. Our study reveals with unprecedented resolution the fine connectivity effects of multiple factors that work together to control the assembly of neural circuits.</p>
},
	issn = {1097-4199},
	doi = {10.1016/j.neuron.2020.10.004},
	author = {Valdes-Aleman, Javier and Fetter, Richard D and Sales, Emily C and Heckman, Emily L and Venkatasubramanian, Lalanti and Doe, Chris Q and Landgraf, Matthias and Cardona, Albert and Zlatic, Marta}
}
