@article {65723, title = {A systematic nomenclature for the Drosophila ventral nerve cord.}, journal = {Neuron}, volume = {107}, year = {2020}, month = {2020 Sep 14}, pages = {1071-79}, abstract = {

Drosophila melanogaster is an established model for neuroscience research with relevance in biology and medicine. Until recently, research on the Drosophila brain was hindered by the lack of a complete and uniform nomenclature. Recognizing this, Ito et\ al. (2014) produced an authoritative nomenclature for the adult insect brain, using Drosophila as the reference. Here, we extend this nomenclature to the adult thoracic and abdominal neuromeres, the ventral nerve cord (VNC), to provide an anatomical description of this major component of the Drosophila nervous system. The VNC is the locus for the reception and integration of sensory information and involved in generating most of the locomotor actions that underlie fly behaviors. The aim is to create a nomenclature, definitions, and spatial boundaries for the Drosophila VNC that are consistent with other insects. The work establishes an anatomical framework that provides a powerful tool for analyzing the functional organization of the VNC.

}, issn = {1097-4199}, doi = {10.1016/j.neuron.2020.08.005}, author = {Court, Robert and Namiki, Shigehiro and Armstrong, J Douglas and Borner, Jana and Card, Gwyneth and Costa, Marta and Dickinson, Michael and Duch, Carsten and Korff, Wyatt and Mann, Richard and Merritt, David and Murphey, Rod K and Seeds, Andrew M and Shirangi, Troy and Simpson, Julie H and Truman, James W and Tuthill, John C and Williams, Darren W and Shepherd, David} } @article {48788, title = {Simultaneous activation of parallel sensory pathways promotes a grooming sequence in Drosophila.}, journal = {eLife}, volume = {6}, year = {2017}, month = {2017 Sep 09}, abstract = {

A central model that describes how behavioral sequences are produced features a neural architecture that readies different movements simultaneously, and a mechanism where prioritized suppression between the movements determines their sequential performance. We previously described a model whereby suppression drives a Drosophila grooming sequence that is induced by simultaneous activation of different sensory pathways that each elicit a distinct movement (Seeds et al. 2014). Here, we confirm this model using transgenic expression to identify and optogenetically activate sensory neurons that elicit specific grooming movements. Simultaneous activation of different sensory pathways elicits a grooming sequence that resembles the naturally induced sequence. Moreover, the sequence proceeds after the sensory excitation is terminated, indicating that a persistent trace of this excitation induces the next grooming movement once the previous one is performed. This reveals a mechanism whereby parallel sensory inputs can be integrated and stored to elicit a delayed and sequential grooming response.

}, issn = {2050-084X}, doi = {10.7554/eLife.28804}, author = {Hampel, Stefanie and McKellar, Claire E and Simpson, Julie H and Seeds, Andrew M} } @article {48657, title = {A systematic nomenclature for the Drosophila ventral nervous system.}, journal = {bioRxiv}, year = {2017}, month = {2017 Apr 26}, abstract = {

Insect nervous systems are proven and powerful model systems for neuroscience research with wide relevance in biology and medicine. However, descriptions of insect brains have suffered from a lack of a complete and uniform nomenclature. Recognising this problem the Insect Brain Name Working Group produced the first agreed hierarchical nomenclature system for the adult insect brain, using Drosophila melanogaster as the reference framework, with other insect taxa considered to ensure greater consistency and expandability (Ito et al., 2014). Ito et al. (2014) purposely focused on the gnathal regions that account for approximately 50\% of the adult CNS. We extend this nomenclature system to the sub-gnathal regions of the adult Drosophila nervous system to provide a nomenclature of the so-called ventral nervous system (VNS), which includes the thoracic and abdominal neuromeres that was not included in the original work and contains the neurons that play critical roles underpinning most fly behaviours.

}, doi = {10.1101/122952}, author = {Court, Robert Christopher and Armstrong, James Douglas and Borner, Jana and Card, Gwyneth M and Costa, Marta and Dickinson, Michael H and Duch, Carsten and Korff, Wyatt and Mann, Richard S and Merritt, David and Murphey, Rodney K and Namiki, Shigehiro and Seeds, Andrew M and Shepherd, David and Shirangi, Troy R and Simpson, Julie H and Truman, James W and Tuthill, John C and Williams, Darren W} } @inbook {47793, title = {Targeted manipulation of neuronal activity in behaving adult flies.}, booktitle = {Decoding Neural Circuit Structure and Function}, year = {2017}, month = {2016 Aug 15}, pages = {191-222}, abstract = {

The ability to control the activity of specific neurons in freely behaving animals provides an effective way to probe the contributions of neural circuits to behavior. Wide interest in studying principles of neural circuit function using the fruit fly\ Drosophila melanogaster\ has fueled the construction of an extensive transgenic toolkit for performing such neural manipulations. Here we describe approaches for using these tools to manipulate the activity of specific neurons and assess how those manipulations impact the behavior of flies. We also describe methods for examining connectivity among multiple neurons that together form a neural circuit controlling a specific behavior. This work provides a resource for researchers interested in examining how neurons and neural circuits contribute to the rich repertoire of behaviors performed by flies.

}, doi = {10.1007/978-3-319-57363-2_7}, author = {Hampel, Stefanie and Seeds, Andrew M} } @article {47038, title = {A neural command circuit for grooming movement control.}, journal = {eLife}, volume = {4}, year = {2015}, month = {2015 Sep 7}, abstract = {

Animals perform many stereotyped movements, but how nervous systems are organized for controlling specific movements remains unclear. Here we use anatomical, optogenetic, behavioral, and physiological techniques to identify a circuit in Drosophila melanogaster that can elicit stereotyped leg movements that groom the antennae. Mechanosensory chordotonal neurons detect displacements of the antennae and excite three different classes of functionally connected interneurons, which include two classes of brain interneurons and different parallel descending neurons. This multilayered circuit is organized such that neurons within each layer are sufficient to specifically elicit antennal grooming. However, we find differences in the durations of antennal grooming elicited by neurons in the different layers, suggesting that the circuit is organized to both command antennal grooming and control its duration. As similar features underlie stimulus-induced movements in other animals, we infer the possibility of a common circuit organization for movement control that can be dissected in Drosophila.

}, issn = {2050-084X}, doi = {10.7554/eLife.08758}, author = {Hampel, Stefanie and Franconville, Romain and Simpson, Julie H and Seeds, Andrew M} } @article {45417, title = {A suppression hierarchy among competing motor programs drives sequential grooming in Drosophila.}, journal = {eLife}, volume = {3}, year = {2014}, month = {2014 Aug 19}, pages = {e02951}, abstract = {

Motor sequences are formed through the serial execution of different movements, but how nervous systems implement this process remains largely unknown. We determined the organizational principles governing how dirty fruit flies groom their bodies with sequential movements. Using genetically targeted activation of neural subsets, we drove distinct motor programs that clean individual body parts. This enabled competition experiments revealing that the motor programs are organized into a suppression hierarchy; motor programs that occur first suppress those that occur later. Cleaning one body part reduces the sensory drive to its motor program, which relieves suppression of the next movement, allowing the grooming sequence to progress down the hierarchy. A model featuring independently evoked cleaning movements activated in parallel, but selected serially through hierarchical suppression, was successful in reproducing the grooming sequence. This provides the first example of an innate motor sequence implemented by the prevailing model for generating human action sequences.

}, issn = {2050-084X}, doi = {10.7554/eLife.02951}, author = {Seeds, Andrew M and Ravbar, Primoz and Chung, Phuong and Hampel, Stefanie and Midgley, Frank M and Mensh, Brett D and Simpson, Julie H} } @article {4157, title = {BrainAligner: 3D registration atlases of Drosophila brains.}, journal = {Nature Methods}, volume = {8}, year = {2011}, month = {2011 Jun}, pages = {493-500}, abstract = {

Analyzing Drosophila melanogaster neural expression patterns in thousands of three-dimensional image stacks of individual brains requires registering them into a canonical framework based on a fiducial reference of neuropil morphology. Given a target brain labeled with predefined landmarks, the BrainAligner program automatically finds the corresponding landmarks in a subject brain and maps it to the coordinate system of the target brain via a deformable warp. Using a neuropil marker (the antibody nc82) as a reference of the brain morphology and a target brain that is itself a statistical average of data for 295 brains, we achieved a registration accuracy of 2 μm on average, permitting assessment of stereotypy, potential connectivity and functional mapping of the adult fruit fly brain. We used BrainAligner to generate an image pattern atlas of 2954 registered brains containing 470 different expression patterns that cover all the major compartments of the fly brain.

}, keywords = {Algorithms, Animals, Brain, Computer-Assisted, Drosophila melanogaster, Drosophila Proteins, Gene Expression, Genetically Modified, Green Fluorescent Proteins, Image Processing, Neuropil, Recombinant Proteins, Software, Transcription Factors}, issn = {1548-7105}, doi = {10.1038/nmeth.1602}, author = {Peng, Hanchuan and Chung, Phuong and Long, Fuhui and Qu, Lei and Jenett, Arnim and Seeds, Andrew M and Myers, Eugene W and Simpson, Julie H} }