@article {67262, title = {A developmental framework linking neurogenesis and circuit formation in the Drosophila CNS.}, journal = {eLife}, volume = {10}, year = {2021}, month = {2021 May 11}, abstract = {

The mechanisms specifying neuronal diversity are well-characterized, yet it remains unclear how or if these mechanisms regulate neural circuit assembly. To address this, we mapped the developmental origin of 160 interneurons from seven bilateral neural progenitors (neuroblasts), and identify them in a synapse-scale TEM reconstruction of the larval CNS. We find that lineages concurrently build the sensory and motor neuropils by generating sensory and motor hemilineages in a Notch-dependent manner. Neurons in a hemilineage share common synaptic targeting within the neuropil, which is further refined based on neuronal temporal identity. Connectome analysis shows that hemilineage-temporal cohorts share common connectivity. Finally, we show that proximity alone cannot explain the observed connectivity structure, suggesting hemilineage/temporal identity confers an added layer of specificity. Thus, we demonstrate that the mechanisms specifying neuronal diversity also govern circuit formation and function, and that these principles are broadly applicable throughout the nervous system.

}, issn = {2050-084X}, doi = {10.7554/eLife.67510}, author = {Mark, Brandon and Lai, Sen-Lin and Zarin, Aref Arzan and Manning, Laurina and Pollington, Heather Q and Litwin-Kumar, Ashok and Cardona, Albert and Truman, James W and Doe, Chris Q} } @article {65899, title = {The connectome of the adult mushroom body provides insights into function.}, journal = {eLife}, volume = {9}, year = {2020}, month = {2020 Dec 14}, abstract = {

Making inferences about the computations performed by neuronal circuits from synapse-level connectivity maps is an emerging opportunity in neuroscience. The mushroom body (MB) is well positioned for developing and testing such an approach due to its conserved neuronal architecture, recently completed dense connectome, and extensive prior experimental studies of its roles in learning, memory and activity regulation. Here we identify new components of the MB circuit in , including extensive visual input and MB output neurons (MBONs) with direct connections to descending neurons. We find unexpected structure in sensory inputs, in the transfer of information about different sensory modalities to MBONs, and in the modulation of that transfer by dopaminergic neurons (DANs). We provide insights into the circuitry used to integrate MB outputs, connectivity between the MB and the central complex and inputs to DANs, including feedback from MBONs. Our results provide a foundation for further theoretical and experimental work.

}, issn = {2050-084X}, doi = {10.7554/eLife.62576}, author = {Li, Feng and Lindsey, Jack W and Marin, Elizabeth C and Otto, Nils and Dreher, Marisa and Dempsey, Georgia and Stark, Ildiko and Bates, Alexander S and Pleijzier, Markus William and Schlegel, Philipp and Nern, Aljoscha and Takemura, Shin-ya and Eckstein, Nils and Yang, Tansy and Francis, Audrey and Braun, Amalia and Parekh, Ruchi and Costa, Marta and Scheffer, Louis K and Aso, Yoshi and Jefferis, Gregory Sxe and Abbott, Larry F and Litwin-Kumar, Ashok and Waddell, Scott and Rubin, Gerald M} } @article {65373, title = {Recurrent architecture for adaptive regulation of learning in the insect brain.}, journal = {Nature Neuroscience}, volume = {23}, year = {2020}, month = {2020 Mar 23}, pages = {544-55}, abstract = {

Dopaminergic neurons (DANs) drive learning across the animal kingdom, but the upstream circuits that regulate their activity and thereby learning remain poorly understood. We provide a synaptic-resolution connectome of the circuitry upstream of all DANs in a learning center, the mushroom body of Drosophila larva. We discover afferent sensory pathways and a large population of neurons that provide feedback from mushroom body output neurons and link distinct memory systems (aversive and appetitive). We combine this with functional studies of DANs and their presynaptic partners and with comprehensive circuit modeling. We find that DANs compare convergent feedback from aversive and appetitive systems, which enables the computation of integrated predictions that may improve future learning. Computational modeling reveals that the discovered feedback motifs increase model flexibility and performance on learning tasks. Our study provides the most detailed view to date of biological circuit motifs that support associative learning.

}, issn = {1546-1726}, doi = {10.1038/s41593-020-0607-9}, author = {Eschbach, Claire and Fushiki, Akira and Winding, Michael and Schneider-Mizell, Casey M and Shao, Mei and Arruda, Rebecca and Eichler, Katharina and Valdes-Aleman, Javier and Ohyama, Tomoko and Thum, Andreas S and Gerber, Bertram and Fetter, Richard D and Truman, James W and Litwin-Kumar, Ashok and Cardona, Albert and Zlatic, Marta and Cardona, Albert and Zlatic, Marta} } @article {65128, title = {Constraining computational models using electron microscopy wiring diagrams.}, journal = {Current Opinion in Neurobiology}, volume = {58}, year = {2019}, month = {2019 Aug 27}, pages = {94-100}, abstract = {

Numerous efforts to generate "connectomes," or synaptic wiring diagrams, of large neural circuits or entire nervous systems are currently underway. These efforts promise an abundance of data to guide theoretical models of neural computation and test their predictions. However, there is not yet a standard set of tools for incorporating the connectivity constraints that these datasets provide into the models typically studied in theoretical neuroscience. This article surveys recent approaches to building models with constrained wiring diagrams and the insights they have provided. It also describes challenges and the need for new techniques to scale these approaches to ever more complex datasets.

}, issn = {1873-6882}, doi = {10.1016/j.conb.2019.07.007}, author = {Litwin-Kumar, Ashok and Turaga, Srinivas C} } @article {65258, title = {A multilayer circuit architecture for the generation of distinct locomotor behaviors in .}, journal = {eLlife}, volume = {8}, year = {2019}, month = {2019 Dec 23}, abstract = {

Animals generate diverse motor behaviors, yet how the same motor neurons (MNs) generate two distinct or antagonistic behaviors remains an open question. Here we characterize larval muscle activity patterns and premotor/motor circuits to understand how they generate forward and backward locomotion. We show that all body wall MNs are activated during both behaviors, but a subset of MNs change recruitment timing for each behavior. We used TEM to reconstruct a full segment of all 60 MNs and 236 premotor neurons (PMNs), including differentially-recruited MNs. Analysis of this comprehensive connectome identified PMN-MN {\textquoteright}labeled line{\textquoteright} connectivity; PMN-MN combinatorial connectivity; asymmetric neuronal morphology; and PMN-MN circuit motifs that could all contribute to generating distinct behaviors. We generated a recurrent network model that reproduced the observed behaviors, and used functional optogenetics to validate selected model predictions. This PMN-MN connectome will provide a foundation for analyzing the full suite of larval behaviors.

}, issn = {2050-084X}, doi = {10.7554/eLife.51781}, author = {Zarin, Aref Arzan and Mark, Brandon and Cardona, Albert and Litwin-Kumar, Ashok and Doe, Chris Q} } @article {65227, title = {Nitric oxide acts as a cotransmitter in a subset of dopaminergic neurons to diversify memory dynamics.}, journal = {eLife}, volume = {8}, year = {2019}, month = {2019 Nov 14}, abstract = {

Animals employ diverse learning rules and synaptic plasticity dynamics to record temporal and statistical information about the world. However, the molecular mechanisms underlying this diversity are poorly understood. The anatomically defined compartments of the insect mushroom body function as parallel units of associative learning, with different learning rates, memory decay dynamics and flexibility (Aso \& Rubin 2016). Here we show that nitric oxide (NO) acts as a neurotransmitter in a subset of dopaminergic neurons in . NO{\textquoteright}s effects develop more slowly than those of dopamine and depend on soluble guanylate cyclase in postsynaptic Kenyon cells. NO acts antagonistically to dopamine; it shortens memory retention and facilitates the rapid updating of memories. The interplay of NO and dopamine enables memories stored in local domains along Kenyon cell axons to be specialized for predicting the value of odors based only on recent events. Our results provide key mechanistic insights into how diverse memory dynamics are established in parallel memory systems.

}, issn = {2050-084X}, doi = {10.7554/eLife.49257}, author = {Aso, Yoshinori and Ray, Robert P and Long, Xi and Bushey, Daniel and Cichewicz, Karol and Ngo, Teri-Tb and Sharp, Brandi and Christoforou, Christina and Hu, Amy and Lemire, Andrew L and Tillberg, Paul and Hirsh, Jay and Litwin-Kumar, Ashok and Rubin, Gerald M} } @article {48720, title = {The complete connectome of a learning and memory centre in an insect brain.}, journal = {Nature}, volume = {548}, year = {2017}, month = {2017 Aug 09}, pages = {175-182}, abstract = {

Associating stimuli with positive or negative reinforcement is essential for survival, but a complete wiring diagram of a higher-order circuit supporting associative memory has not been previously available. Here we reconstruct one such circuit at synaptic resolution, the Drosophila larval mushroom body. We find that most Kenyon cells integrate random combinations of inputs but that a subset receives stereotyped inputs from single projection neurons. This organization maximizes performance of a model output neuron on a stimulus discrimination task. We also report a novel canonical circuit in each mushroom body compartment with previously unidentified connections: reciprocal Kenyon cell to modulatory neuron connections, modulatory neuron to output neuron connections, and a surprisingly high number of recurrent connections between Kenyon cells. Stereotyped connections found between output neurons could enhance the selection of learned behaviours. The complete circuit map of the mushroom body should guide future functional studies of this learning and memory centre.

}, issn = {1476-4687}, doi = {10.1038/nature23455}, author = {Eichler, Katharina and Li, Feng and Litwin-Kumar, Ashok and Park, Youngser and Andrade, Ingrid and Schneider-Mizell, Casey M and Saumweber, Timo and Huser, Annina and Eschbach, Claire and Gerber, Bertram and Fetter, Richard D and Truman, James W and Priebe, Carey E and Abbott, L F and Thum, Andreas S and Zlatic, Marta and Cardona, Albert} }