Year |
Citation |
Score |
2023 |
Trofimova AM, Amakhin DV, Postnikova TY, Tiselko VS, Alekseev A, Podoliak E, Gordeliy VI, Chizhov AV, Zaitsev AV. Light-Driven Sodium Pump as a Potential Tool for the Control of Seizures in Epilepsy. Molecular Neurobiology. PMID 38114761 DOI: 10.1007/s12035-023-03865-z |
0.344 |
|
2023 |
Chizhov AV, Amakhin DV, Sagtekin AE, Desroches M. Single-compartment model of a pyramidal neuron, fitted to recordings with current and conductance injection. Biological Cybernetics. 117: 433-451. PMID 37755465 DOI: 10.1007/s00422-023-00976-7 |
0.379 |
|
2022 |
Proskurina EY, Chizhov AV, Zaitsev AV. Optogenetic Low-Frequency Stimulation of Principal Neurons, but Not Parvalbumin-Positive Interneurons, Prevents Generation of Ictal Discharges in Rodent Entorhinal Cortex in an In Vitro 4-Aminopyridine Model. International Journal of Molecular Sciences. 24. PMID 36613660 DOI: 10.3390/ijms24010195 |
0.385 |
|
2021 |
Amakhin DV, Soboleva EB, Chizhov AV, Zaitsev AV. Insertion of Calcium-Permeable AMPA Receptors during Epileptiform Activity In Vitro Modulates Excitability of Principal Neurons in the Rat Entorhinal Cortex. International Journal of Molecular Sciences. 22. PMID 34830051 DOI: 10.3390/ijms222212174 |
0.305 |
|
2021 |
Chizhov AV, Graham LJ. A strategy for mapping biophysical to abstract neuronal network models applied to primary visual cortex. Plos Computational Biology. 17: e1009007. PMID 34398895 DOI: 10.1371/journal.pcbi.1009007 |
0.312 |
|
2020 |
Chizhov AV, Sanin AE. A simple model of epileptic seizure propagation: Potassium diffusion versus axo-dendritic spread. Plos One. 15: e0230787. PMID 32275724 DOI: 10.1371/journal.pone.0230787 |
0.362 |
|
2019 |
Schwalger T, Chizhov AV. Mind the last spike - firing rate models for mesoscopic populations of spiking neurons. Current Opinion in Neurobiology. 58: 155-166. PMID 31590003 DOI: 10.1016/J.Conb.2019.08.003 |
0.387 |
|
2019 |
Chizhov A, Campillo F, Desroches M, Guillamon A, Rodrigues S. Conductance-Based Refractory Density Approach for a Population of Bursting Neurons. Bulletin of Mathematical Biology. PMID 31313084 DOI: 10.1007/S11538-019-00643-8 |
0.473 |
|
2019 |
Chizhov AV, Amakhin DV, Zaitsev AV. Mathematical model of Na-K-Cl homeostasis in ictal and interictal discharges. Plos One. 14: e0213904. PMID 30875397 DOI: 10.1371/journal.pone.0213904 |
0.376 |
|
2019 |
Chizhov AV, Amakhin DV, Zaitsev AV. Spatial propagation of interictal discharges along the cortex. Biochemical and Biophysical Research Communications. 508: 1245-1251. PMID 30563766 DOI: 10.1016/j.bbrc.2018.12.070 |
0.373 |
|
2018 |
Chizhov AV, Zefirov AV, Amakhin DV, Smirnova EY, Zaitsev AV. Minimal model of interictal and ictal discharges "Epileptor-2". Plos Computational Biology. 14: e1006186. PMID 29851959 DOI: 10.1371/journal.pcbi.1006186 |
0.379 |
|
2018 |
Smirnova EY, Amakhin DV, Malkin SL, Chizhov AV, Zaitsev AV. Acute changes in electrophysiological properties of cortical regular-spiking cells following seizures in a rat lithium-pilocarpine model. Neuroscience. PMID 29580962 DOI: 10.1016/j.neuroscience.2018.03.020 |
0.345 |
|
2018 |
Mysin I, Chizhov A. The Role of Geterogeneity in Synchronization of Spiking Neural Networks Mathematical Biology and Bioinformatics. 13: 490-506. DOI: 10.17537/2018.13.490 |
0.344 |
|
2017 |
Chizhov AV, Amakhin DV, Zaitsev AV. Computational model of interictal discharges triggered by interneurons. Plos One. 12: e0185752. PMID 28977038 DOI: 10.1371/journal.pone.0185752 |
0.406 |
|
2017 |
Chizhov AV. Conductance-based refractory density approach: comparison with experimental data and generalization to lognormal distribution of input current. Biological Cybernetics. PMID 28819690 DOI: 10.1007/s00422-017-0727-9 |
0.324 |
|
2017 |
Rubchinsky LL, Ahn S, Klijn W, Cumming B, Yates S, Karakasis V, Peyser A, Woodman M, Diaz-Pier S, Deraeve J, Vassena E, Alexander W, Beeman D, Kudela P, Boatman-Reich D, ... ... Chizhov A, ... ... Chizhov AV, et al. 26th Annual Computational Neuroscience Meeting (CNS*2017): Part 2 Bmc Neuroscience. 18. DOI: 10.1186/S12868-017-0371-2 |
0.505 |
|
2016 |
Buchin A, Chizhov A, Huberfeld G, Miles R, Gutkin BS. Reduced Efficacy of the KCC2 Cotransporter Promotes Epileptic Oscillations in a Subiculum Network Model. The Journal of Neuroscience : the Official Journal of the Society For Neuroscience. 36: 11619-11633. PMID 27852771 DOI: 10.1523/Jneurosci.4228-15.2016 |
0.6 |
|
2016 |
Amakhin DV, Ergina JL, Chizhov AV, Zaitsev AV. Synaptic Conductances during Interictal Discharges in Pyramidal Neurons of Rat Entorhinal Cortex. Frontiers in Cellular Neuroscience. 10: 233. PMID 27790093 DOI: 10.3389/fncel.2016.00233 |
0.369 |
|
2015 |
Chizhov AV, Sanchez-Aguilera A, Rodrigues S, de la Prida LM. Simplest relationship between local field potential and intracellular signals in layered neural tissue. Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics. 92: 062704. PMID 26764724 DOI: 10.1103/PhysRevE.92.062704 |
0.31 |
|
2015 |
Buchin A, Huberfeld G, Miles R, Chizhov A, Gutkin B. Effects of a reduced efficacy of the KCC2 co-transporter in temporal lobe epilepsy: single neuron and network study Bmc Neuroscience. 16. DOI: 10.1186/1471-2202-16-S1-P5 |
0.598 |
|
2014 |
Chizhov AV. Conductance-based refractory density model of primary visual cortex. Journal of Computational Neuroscience. 36: 297-319. PMID 23888313 DOI: 10.1007/s10827-013-0473-5 |
0.34 |
|
2010 |
Buchin AJ, Chizhov AV. Modified firing-rate model reproduces synchronization of a neuronal population receiving complex input Optical Memory and Neural Networks. 19: 166-171. DOI: 10.3103/S1060992X10020074 |
0.358 |
|
2010 |
Buchin AY, Chizhov AV. Firing-rate model of a population of adaptive neurons Biophysics. 55: 592-599. DOI: 10.1134/S0006350910040135 |
0.564 |
|
2009 |
Chizhov AV, Smirnova EY, Graham LJ. Mapping between V1 models of orientation selectivity: From a distributed multi-population conductance-based refractory density model to a firing-rate ring model Bmc Neuroscience. 10. DOI: 10.1186/1471-2202-10-S1-P181 |
0.324 |
|
2007 |
Chizhov AV, Graham LJ. Population model of hippocampal pyramidal neurons, linking a refractory density approach to conductance-based neurons. Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics. 75: 011924. PMID 17358201 DOI: 10.1103/Physreve.75.011924 |
0.348 |
|
2006 |
Chizhov AV, Graham LJ, Turbin AA. Simulation of neural population dynamics with a refractory density approach and a conductance-based threshold neuron model Neurocomputing. 70: 252-262. DOI: 10.1016/J.Neucom.2006.02.004 |
0.335 |
|
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