- Home
- Search Results
- Page 1 of 1
Search for: All records
-
Total Resources3
- Resource Type
-
0002000001000000
- More
- Availability
-
21
- Author / Contributor
- Filter by Author / Creator
-
-
Turkcan, Mehmet Kerem (3)
-
Ghaderi, Javad (2)
-
Ghasemi, Mahshid (2)
-
Kostic, Zoran (2)
-
Zussman, Gil (2)
-
Ehsan, Taqiya (1)
-
Hindi, Basel (1)
-
Jain, Gaurav (1)
-
Lazar, Aurel A. (1)
-
Malcolm, Michael (1)
-
Ortiz, Jorge (1)
-
Pargoo, Navid Salami (1)
-
Paris, Sophie Ana (1)
-
Smith, Brian A (1)
-
Srinivasula, Koushik (1)
-
Sun, Yuan (1)
-
Weiner, Daniel (1)
-
Xia, Shuren (1)
-
Xie, Mingyu (1)
-
Xu, Xin_Yi Therese (1)
-
- Filter by Editor
-
-
& Spizer, S. M. (0)
-
& . Spizer, S. (0)
-
& Ahn, J. (0)
-
& Bateiha, S. (0)
-
& Bosch, N. (0)
-
& Brennan K. (0)
-
& Brennan, K. (0)
-
& Chen, B. (0)
-
& Chen, Bodong (0)
-
& Drown, S. (0)
-
& Ferretti, F. (0)
-
& Higgins, A. (0)
-
& J. Peters (0)
-
& Kali, Y. (0)
-
& Ruiz-Arias, P.M. (0)
-
& S. Spitzer (0)
-
& Sahin. I. (0)
-
& Spitzer, S. (0)
-
& Spitzer, S.M. (0)
-
(submitted - in Review for IEEE ICASSP-2024) (0)
-
-
Have feedback or suggestions for a way to improve these results?
!
Note: When clicking on a Digital Object Identifier (DOI) number, you will be taken to an external site maintained by the publisher.
Some full text articles may not yet be available without a charge during the embargo (administrative interval).
What is a DOI Number?
Some links on this page may take you to non-federal websites. Their policies may differ from this site.
-
Free, publicly-accessible full text available May 6, 2026
-
Jain, Gaurav; Hindi, Basel; Zhang, Zihao; Srinivasula, Koushik; Xie, Mingyu; Ghasemi, Mahshid; Weiner, Daniel; Paris, Sophie Ana; Xu, Xin_Yi Therese; Malcolm, Michael; et al (, ACM)
-
Lazar, Aurel A.; Turkcan, Mehmet Kerem; Zhou, Yiyin (, Frontiers in Neuroinformatics)The Drosophila brain has only a fraction of the number of neurons of higher organisms such as mice and humans. Yet the sheer complexity of its neural circuits recently revealed by large connectomics datasets suggests that computationally modeling the function of fruit fly brain circuits at this scale poses significant challenges. To address these challenges, we present here a programmable ontology that expands the scope of the current Drosophila brain anatomy ontologies to encompass the functional logic of the fly brain. The programmable ontology provides a language not only for modeling circuit motifs but also for programmatically exploring their functional logic. To achieve this goal, we tightly integrated the programmable ontology with the workflow of the interactive FlyBrainLab computing platform. As part of the programmable ontology, we developed NeuroNLP++, a web application that supports free-form English queries for constructing functional brain circuits fully anchored on the available connectome/synaptome datasets, and the published worldwide literature. In addition, we present a methodology for including a model of the space of odorants into the programmable ontology, and for modeling olfactory sensory circuits of the antenna of the fruit fly brain that detect odorant sources. Furthermore, we describe a methodology for modeling the functional logic of the antennal lobe circuit consisting of a massive number of local feedback loops, a characteristic feature observed across Drosophila brain regions. Finally, using a circuit library, we demonstrate the power of our methodology for interactively exploring the functional logic of the massive number of feedback loops in the antennal lobe.more » « less
An official website of the United States government
