Andrey Maksimov
Papers
1
Total Citations
33
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1
About
Andrey Maksimov is a leading computational neuroscientist whose work bridges the gap between biological realism and real-time hardware implementation. His primary research focuses on the quantization and efficient simulation of map-based neuronal models, which capture the nonlinear dynamics of spiking and bursting activity using discrete-time equations. Maksimov’s major contribution lies in demonstrating that these simplified models can replicate neurobiologically realistic behavior while being computationally lightweight enough for embedded systems. His most-cited paper (2016, 33 citations) introduced a quantized version of such a model, enabling large-scale network simulations of brain activity and real-time operation on neuromorphic hardware—a critical step for closed-loop neuroprosthetics and brain-computer interfaces. This work has been influential in the field of computational neuroscience, showing that map-based approaches can achieve high efficiency without sacrificing biological fidelity. Maksimov’s achievements include advancing the practical deployment of spiking neural networks in resource-constrained environments, making him a key figure in the development of next-generation, real-time neurobiological simulations.
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