@article {67793, title = {Circuits for integrating learned and innate valences in the insect brain.}, journal = {eLife}, volume = {10}, year = {2021}, month = {2021 Nov 10}, abstract = {

Animal behavior is shaped both by evolution and by individual experience. Parallel brain pathways encode innate and learned valences of cues, but the way in which they are integrated during action-selection is not well understood. We used electron microscopy to comprehensively map with synaptic resolution all neurons downstream of all Mushroom Body output neurons (encoding learned valences) and characterized their patterns of interaction with Lateral Horn neurons (encoding innate valences) in larva. The connectome revealed multiple types that receive convergent Mushroom Body and Lateral Horn inputs. A subset of these receives excitatory input from positive-valence MB and LH pathways and inhibitory input from negative-valence MB pathways. We confirmed functional connectivity from LH and MB pathways and behavioral roles of two of these neurons. These neurons encode integrated odor value and bidirectionally regulate turning. Based on this we speculate that learning could potentially skew the balance of excitation and inhibition onto these neurons and thereby modulate turning. Together, our study provides insights into the circuits that integrate learned and innate valences to modify behavior.

}, issn = {2050-084X}, doi = {10.7554/eLife.62567}, author = {Eschbach, Claire and Fushiki, Akira and Winding, Michael and Afonso, Bruno and Andrade, Ingrid V and Cocanougher, Benjamin T and Eichler, Katharina and Gepner, Ruben and Si, Guangwei and Valdes-Aleman, Javier and Fetter, Richard D and Gershow, Marc and Jefferis, Gregory Sxe and Samuel, Aravinthan Dt and Truman, James W and Cardona, Albert and Zlatic, Marta} } @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 = {

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.

}, 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} } @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} }