V. V. Makarov
Papers
1
Total Citations
78
H-Index
1
About
V. V. Makarov is a computational neuroscientist whose research lies at the intersection of artificial intelligence, neural dynamics, and human cognition. His most cited work, “Artificial neural network detects human uncertainty” (2018, 78 citations), demonstrates a novel application of ANNs to decode neural signatures of decision-making ambiguity—a key contribution bridging machine learning with cognitive neuroscience. Makarov’s broader research explores how biological and artificial neural networks process information, with a focus on uncertainty, prediction, and adaptive behavior. By leveraging deep learning to analyze brain activity, he has advanced our understanding of how the human brain handles incomplete or conflicting data. His work has been influential in both neuroscience and AI communities, offering tools for real-time detection of cognitive states. Makarov’s contributions are particularly relevant for developing brain-computer interfaces and adaptive systems that mimic human decision-making under uncertainty. With a growing citation record, he continues to shape how researchers model the interplay between neural computation and behavioral variability.
Research Focus
Key Achievements
Top Papers
- 1Artificial neural network detects human uncertainty78 citations · 2018