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Oleg Vinogradov
Oleg Vinogradov
Adresse e-mail validée de uni-tuebingen.de - Page d'accueil
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Neuronal circuits overcome imbalance in excitation and inhibition by adjusting connection numbers
N Sukenik, O Vinogradov, E Weinreb, M Segal, A Levina, E Moses
Proceedings of the National Academy of Sciences 118 (12), e2018459118, 2021
872021
Recurrent connectivity structure controls the emergence of co-tuned excitation and inhibition
E Giannakakis, O Vinogradov, V Buendía, A Levina
bioRxiv, 2023.02. 27.530253, 2023
52023
Effective excitability captures network dynamics across development and phenotypes
O Vinogradov, E Giannakakis, V Buendia, B Uysal, S Ron, E Weinreb, ...
bioRxiv, 2024.08. 21.608974, 2024
22024
Modeling population dynamics of neural circuits: from in vitro neural systems to structured cortical networks
O Vinogradov
Universität Tübingen, 2026
2026
Unsupervised clustering of burst shapes reveals the increasing complexity of developing networks in vitro
TJ Schäfer, E Giannakakis, P Schmidt-Barbo, A Levina, O Vinogradov
Bernstein Conference 2024, 2024
2024
Effective excitability: a determinant of the network bursting dynamics revealed by parameter invariance
O Vinogradov, E Giannakakis, B Uysal, S Ron, E Weinreb, H Lerche, ...
Bernstein Conference 2024, 2024
2024
Local excitation and lateral inhibition enable the simultaneous processing of multiple signals in recurrent neural networks
E Giannakakis, O Vinogradov, V Buendía, S Khajehabdollahi, A Levina
Kluwer Academic Publishers, 2024
2024
Overlapping E/I neuronal assemblies generate rich network dynamics and enable complex computations
E Giannakakis, V Buendia, O Vinogradov, S Khajehabdollahi, A Levina
Research in Encoding and Decoding of Neural Ensembles (AREADNE 2024), 73, 2024
2024
Distinct excitatory and inhibitory connectivity structures control the dynamics and computational capabilities of recurrent networks
E Giannakakis, V Buendia, O Vinogradov, S Khajehabdollahi, A Levina
Computational and Systems Neuroscience Meeting (COSYNE 2024), 58-59, 2024
2024
Inhomogeneous connectivity structures in E/I networks enable the processing of multiple chaotic time series
E Giannakakis, V Buendía, O Vinogradov, S Khajehabdollahi, A Levina
Bernstein Conference 2023, 2023
2023
Network excitability determines collective bursting dynamics of neuronal networks in vitro
O Vinogradov, E Giannakakis, V Buendia, B Uysal, E Weinreb, S Ron, ...
Bernstein Conference 2023, 2023
2023
Distinct anterior cingulate neurons drive changes-of-mind and monitor past performance
D Vasilev, O Vinogradov, R Iwai, A Levina, NK Totah
51st Annual Meeting of the Society for Neuroscience (Neuroscience 2022), 2022
2022
Dynamical regimes of network bursting in vitro
O Vinogradov, S Ron, E Weinreb, V Buendia, E Moses, A Levina
Bernstein Conference 2022, 2022
2022
Dynamical principles of network bursting in vitro
O Vinogradov
Bernstein 2022 Satellite Workshop: Advances in Network Dynamics of In Vitro …, 2022
2022
ACC Neurons Respond both during and after Response Conflict
D Vasilev, O Vinogradov, A Levina, NK Totah
Research in Encoding and Decoding of Neural Ensembles (AREADNE 2022), 115, 2022
2022
Balance and adaptation in neuronal systems
A Levina, O Vinogradov, N Sukenik, E Moses
NEST Conference 2022, 13, 2022
2022
Clustered recurrent connectivity promotes the development of E/I co-tuning via synaptic plasticity
E Giannakakis, O Vinogradov, A Levina
Computational and Systems Neuroscience Meeting (COSYNE 2022), 133-134, 2022
2022
Recurrent connectivity regulates the ability of inhibitory STDP to produce E/I co-tuning in a spiking network
E Giannakakis, O Vinogradov, A Levina
Bernstein Conference 2021, 2021
2021
Minimal model of cultured neuronal networks population dynamics
O Vinogradov, V Buendia, A Levina
Bernstein Conference 2021, 2021
2021
Examining network dynamics under inhibitory rewiring
N Patzlaff, O Vinogradov, E Giannakakis, A Levina
Bernstein Conference 2021, 2021
2021
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