Bayesian sense of time in biological and artificial brains

التفاصيل البيبلوغرافية
العنوان: Bayesian sense of time in biological and artificial brains
المؤلفون: Fountas, Zafeirios, Zakharov, Alexey
سنة النشر: 2022
المجموعة: Computer Science
Quantitative Biology
Statistics
مصطلحات موضوعية: Quantitative Biology - Neurons and Cognition, Computer Science - Artificial Intelligence, Statistics - Machine Learning
الوصف: Enquiries concerning the underlying mechanisms and the emergent properties of a biological brain have a long history of theoretical postulates and experimental findings. Today, the scientific community tends to converge to a single interpretation of the brain's cognitive underpinnings -- that it is a Bayesian inference machine. This contemporary view has naturally been a strong driving force in recent developments around computational and cognitive neurosciences. Of particular interest is the brain's ability to process the passage of time -- one of the fundamental dimensions of our experience. How can we explain empirical data on human time perception using the Bayesian brain hypothesis? Can we replicate human estimation biases using Bayesian models? What insights can the agent-based machine learning models provide for the study of this subject? In this chapter, we review some of the recent advancements in the field of time perception and discuss the role of Bayesian processing in the construction of temporal models.
Comment: 27 pages, 3 figures, to appear in: Time and Science (ed. R. Lestienne & P. Harris)
نوع الوثيقة: Working Paper
URL الوصول: http://arxiv.org/abs/2201.05464
رقم الأكسشن: edsarx.2201.05464
قاعدة البيانات: arXiv