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@ARTICLE{Chan:270187,
author = {Chan, Chi Wai and Chen, Nannan and Hernandez, John and
Meltzer, Hagar and Park, Annie and Stahl, Aaron},
title = {{F}uture avenues in {D}rosophila mushroom body research.},
journal = {Learning $\&$ memory},
volume = {31},
number = {5},
issn = {1072-0502},
address = {Plainview, NY},
publisher = {Cold Spring Harbor Laboratory Press},
reportid = {DZNE-2024-00758},
pages = {a053863},
year = {2024},
abstract = {How does the brain translate sensory information into
complex behaviors? With relatively small neuronal numbers,
readable behavioral outputs, and an unparalleled genetic
toolkit, the Drosophila mushroom body (MB) offers an
excellent model to address this question in the context of
associative learning and memory. Recent technological
breakthroughs, such as the freshly completed full-brain
connectome, multiomics approaches, CRISPR-mediated gene
editing, and machine learning techniques, led to major
advancements in our understanding of the MB circuit at the
molecular, structural, physiological, and functional levels.
Despite significant progress in individual MB areas, the
field still faces the fundamental challenge of resolving how
these different levels combine and interact to ultimately
control the behavior of an individual fly. In this review,
we discuss various aspects of MB research, with a focus on
the current knowledge gaps, and an outlook on the future
methodological developments required to reach an overall
view of the neurobiological basis of learning and memory.},
subtyp = {Review Article},
keywords = {Mushroom Bodies: physiology / Animals / Drosophila:
physiology / Memory: physiology / Association Learning:
physiology},
cin = {AG Gründemann},
ddc = {150},
cid = {I:(DE-2719)5000069},
pnm = {351 - Brain Function (POF4-351)},
pid = {G:(DE-HGF)POF4-351},
typ = {PUB:(DE-HGF)16},
pmc = {pmc:PMC11199946},
pubmed = {pmid:38862172},
doi = {10.1101/lm.053863.123},
url = {https://pub.dzne.de/record/270187},
}