% IMPORTANT: The following is UTF-8 encoded. This means that in the presence
% of non-ASCII characters, it will not work with BibTeX 0.99 or older.
% Instead, you should use an up-to-date BibTeX implementation like “bibtex8” or
% “biber”.
@ARTICLE{Letzkus:285919,
author = {Letzkus, Johannes J and Sprekeler, Henning and Binder,
Harald and Bödecker, Joschka and Diester, Ilka and Elgueta,
Claudio and Grosser, Sabine and Haberl, Matthias and Kulik,
Akos and Larkum, Matthew and Leibold, Christian and Madry,
Christian and Monyer, Hannah and Poulet, James F A and
Sauer, Jonas-Frederic and Schmoranzer, Jan and Schreiber,
Susanne and Veit, Julia and Viana da Silva, Silvia and
Vlachos, Andreas and Vida, Imre and Geiger, Jörg R P and
Bartos, Marlene},
title = {{A} population approach to cortical {GABA}ergic interneuron
function.},
journal = {Neuron},
volume = {114},
number = {7},
issn = {0896-6273},
address = {[Cambridge, Mass.]},
publisher = {Cell Press},
reportid = {DZNE-2026-00365},
pages = {1176 - 1180},
year = {2026},
abstract = {Inhibitory interneuron diversity is a central feature of
cortical circuits. The IN-CODE consortium seeks to combine
large-scale recordings of interneuron types with
machine-learning tools to identify the role of their
physiological features, connectivity motifs, and
cooperativity in cognitive functions.},
keywords = {Interneurons: physiology / GABAergic Neurons: physiology /
Animals / Cerebral Cortex: physiology / Cerebral Cortex:
cytology / Humans / Machine Learning},
cin = {AG Viana-da-Silva},
ddc = {610},
cid = {I:(DE-2719)5000068},
pnm = {351 - Brain Function (POF4-351)},
pid = {G:(DE-HGF)POF4-351},
typ = {PUB:(DE-HGF)16},
pubmed = {pmid:41844157},
doi = {10.1016/j.neuron.2026.01.028},
url = {https://pub.dzne.de/record/285919},
}