A computational model of urinary bladder smooth muscle syncytium: Validation and investigation of electrical properties S Appukuttan, KL Brain, R Manchanda Journal of computational neuroscience 38, 167-187, 2015 | 27 | 2015 |
NEST 2.14. 0 A Peyser, R Deepu, J Mitchell, S Appukuttan, T Schumann, JM Eppler, ... Jülich Supercomputing Center, 2017 | 26 | 2017 |
Electrophysiology of syncytial smooth muscle R Manchanda, S Appukuttan, M Padmakumar Journal of Experimental Neuroscience 13, 1179069518821917, 2019 | 16 | 2019 |
HippoUnit: A software tool for the automated testing and systematic comparison of detailed models of hippocampal neurons based on electrophysiological data S Sáray, CA Rössert, S Appukuttan, R Migliore, P Vitale, CA Lupascu, ... PLoS computational biology 17 (1), e1008114, 2021 | 14 | 2021 |
EBRAINS live papers-interactive resource sheets for computational studies in neuroscience S Appukuttan, LL Bologna, F Schürmann, M Migliore, AP Davison Neuroinformatics 21 (1), 101-113, 2023 | 12 | 2023 |
Modeling extracellular fields for a three-dimensional network of cells using neuron S Appukuttan, KL Brain, R Manchanda Journal of neuroscience methods 290, 27-38, 2017 | 11 | 2017 |
Syncytial basis for diversity in spike shapes and their propagation in detrusor smooth muscle S Appukuttan, K Brain, R Manchanda Procedia Computer Science 51, 785-794, 2015 | 10 | 2015 |
Difference in axon diameter and myelin thickness between excitatory and inhibitory callosally projecting axons in mice K Basu, S Appukuttan, R Manchanda, A Sik Cerebral Cortex 33 (7), 4101-4115, 2023 | 6 | 2023 |
Investigation of the syncytial nature of detrusor smooth muscle as a determinant of action potential shape S Appukuttan, M Padmakumar, JS Young, KL Brain, R Manchanda Frontiers in Physiology 9, 401810, 2018 | 6 | 2018 |
SynapseUnit S Appukuttan, J Dainauskas, AP Davison Zenodo, 2020 | 5 | 2020 |
MorphoUnit S Appukuttan, PE Garcia, AP Davison Zenodo, 2020 | 5 | 2020 |
Investigation of action potential propagation in a syncytium S Appukuttan, K Brain, R Manchanda Biomed. Res. J 4 (1), 102-115, 2017 | 4 | 2017 |
Influence of gap junction subtypes on passive and active electrical properties of syncytial tissues S Appukuttan, R Sathe, R Manchanda 2016 International Conference on Systems in Medicine and Biology (ICSMB …, 2016 | 4 | 2016 |
The EBRAINS Hodgkin-Huxley Neuron Builder: An online resource for building data-driven neuron models LL Bologna, R Smiriglia, CA Lupascu, S Appukuttan, AP Davison, ... Frontiers in Neuroinformatics 16, 991609, 2022 | 3 | 2022 |
Systematic comparison and automated validation of detailed models of hippocampal neurons S Sáray, CA Rössert, S Appukuttan, R Migliore, P Vitale, CA Lupascu, ... bioRxiv, 2020 | 3 | 2020 |
Modular approach to modeling homotypic and heterotypic gap junctions S Appukuttan, R Sathe, R Manchanda 2015 IEEE 5th International Conference on Computational Advances in Bio and …, 2015 | 3 | 2015 |
A software framework for validating neuroscience models S Appukuttan, L Sharma, P Garcia-Rodriguez, A Davison | 2 | 2022 |
Independence of AP propagation velocity to transjunctional voltage dependence of gap junctional coupling S Appukuttan, R Manchanda 2015 International Conference on Biomedical Engineering and Computational …, 2015 | 2 | 2015 |
A faster way to model neuronal circuitry AP Davison, S Appukuttan Elife 11, e84463, 2022 | 1 | 2022 |
A method for the analysis of ap foot convexity: insights into smooth muscle biophysics S Appukuttan, M Padmakumar, KL Brain, R Manchanda Frontiers in Bioengineering and Biotechnology 5, 64, 2017 | 1 | 2017 |