| The Emergence of Integrated Information, Complexity, and ‘Consciousness’ at Criticality NJM Popiel, S Khajehabdollahi, PM Abeyasinghe, F Riganello, E Nichols, ... Entropy 22 (3), 339, 2020 | 35 | 2020 |
| Role of Dimensionality in Predicting the Spontaneous Behavior of the Brain Using the Classical Ising Model and the Ising Model Implemented on a Structural Connectome PM Abeyasinghe, DR de Paula, S Khajehabdollahi, SR Valluri, AM Owen, ... Brain connectivity 8 (7), 444-455, 2018 | 14 | 2018 |
| The emergence of integrated information, complexity, and consciousness at criticality S Khajehabdollahi, P Abeyasinghe, A Owen, A Soddu bioRxiv, 521567, 2019 | 12 | 2019 |
| When to be critical? Performance and evolvability in different regimes of neural Ising agents S Khajehabdollahi, J Prosi, E Giannakakis, G Martius, A Levina Artificial Life 28 (4), 458-478, 2022 | 8 | 2022 |
| Evolution Towards Criticality in Ising Neural Agents S Khajehabdollahi, O Witkowski Artificial Life 26 (1), 112-129, 2020 | 6 | 2020 |
| The dynamical regime and its importance for evolvability, task performance and generalization J Prosi, S Khajehabdollahi, E Giannakakis, G Martius, A Levina arXiv preprint arXiv:2103.12184, 2021 | 5 | 2021 |
| Assessing Aesthetics of Generated Abstract Images Using Correlation Structure S Khajehabdollahi, G Martius, A Levina 2019 IEEE Symposium Series on Computational Intelligence (SSCI), 306-313, 2019 | 3 | 2019 |
| Locally adaptive cellular automata for goal-oriented self-organization S Khajehabdollahi, E Giannakakis, V Buendía, G Martius, A Levina ALIFE 2023: Ghost in the Machine: Proceedings of the 2023 Artificial Life …, 2023 | 2 | 2023 |
| Reservoir computing with self-organizing neural oscillators S Khajehabdollahi, E Giannakakis, J Prosi, A Levina ALIFE 2021: The 2021 Conference on Artificial Life, 2021 | 2 | 2021 |
| Critical learning vs. evolution: Evolutionary simulation of a population of Ising-embodied neural networks S Khajehabdollahi, O Witkowski Artificial Life Conference proceedings, 47-54, 2018 | 2 | 2018 |
| Network bottlenecks and task structure control the evolution of interpretable learning rules in a foraging agent E Giannakakis, S Khajehabdollahi, A Levina arXiv preprint arXiv:2403.13649, 2024 | | 2024 |
| Emergent mechanisms for long timescales depend on training curriculum and affect performance in memory tasks S Khajehabdollahi, R Zeraati, E Giannakakis, TJ Schäfer, G Martius, ... arXiv preprint arXiv:2309.12927, 2023 | | 2023 |
| Environmental variability and network structure determine the optimal plasticity mechanisms in embodied agents E Giannakakis, S Khajehabdollahi, A Levina Artificial Life Conference Proceedings 35 2023 (1), 22, 2023 | | 2023 |
| Synaptic-type-specific clustering optimizes the computational capabilities of balanced recurrent networks E Giannakakis, A Levina, V Buendia, S Khajehabdollahi Computational and Systems Neuroscience Meeting (COSYNE 2023), 99-100, 2023 | | 2023 |
| Cellular automata for efficient large-scale simulations of spiking networks S Khajehabdollahi, E Giannakakis, G Martius, A Levina Bernstein Conference 2022, 2022 | | 2022 |
| The topology of E/I recurrent networks regulates their ability to learn the dynamics of chaotic attractors E Giannakakis, S Khajehabdollahi, V Buendia, A Levina Bernstein Conference 2022, 2022 | | 2022 |
| Role of Dimensionality in Predicting the Spontaneous Behavior of the Brain Using the Classical Ising Model and the Ising Model Implemented on a Structural Connectome DR De Paula, S Khajehabdollahi, SR Valluri, AM Owen, A Soddu | | 2018 |
| Phase transitions of Integrated Information in the Generalized Ising Model of the Brain S Khajehabdollahi The University of Western Ontario (Canada), 2018 | | 2018 |
