Summary

Orbitofrontal Cortex Uses Distinct Codes for Different Choice Attributes in Decisions Motivated by Curiosity

14 May 2021 - Pinjie Li

Curiosity influences many cognitive functions including decision making, learning, memory and attention. Besides, machine learning algorithms containing artificial curiosity outstand in exploration tasks. It also has the potential to inspire completely new and creative learning techniques. However, its biological function and the underlying neural mechanisms remain poorly understood. Experimental results may boost biologically inspired algorithms that would have much more power than artificial curiosity.

I gave a presentation referring to several review papers and some influential research papers, aiming to know the cutting-edge researches in exploring the neural and computational mechanisms of curiosity. The definition of curiosity nowadays is vague and more and more researchers tend to equal it as a drive state for information, information seeking on the other words. Studies focus on its relationship with rewards in human and non-human primates. Please see Kang et al., 2009, Gruber et al., 2014, Bromberg-Martin and Hikosaka, 2009, Blanchard et al., 2015 for more details. However, where the domain-general curiosity signal comes from and the neural circuitry of curiosity modulation on cognitive functions remain to be solved, not to speak of the underlying principles. As for the computational part, surprise and novelty in stimulus, reward and uncertainty, learning progress and metacognition are thought to motivate curiosity. Please see Gottlieb et al., 2013, Gottlieb et al., 2016, Daddaoua et al., 2016 for more details. Educationalists and psychologists also pay close attention to the development of curiosity in a lifetime, from infants through children to adults.

Original author： Pinjie Li
Link： https://CNeuroUSTC.github.io/2021/05/14/PinJieLi.html
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