Generalization is the ability to apply past experience to similar but non-identical situations. It not only affects stimulus-outcome relationships, as observed in conditioning experiments, but may also be essential for adaptive behaviors, which involve the interaction between individuals and their environment. Computational modeling could potentially clarify the effect of generalization on adaptive behaviors and how this effect emerges from the underlying computation. Recent neurobiological observation indicated that the striatal dopamine system achieves generalization and subsequent discrimination by updating the corticostriatal synaptic connections in differential response to reward and punishment. In this study, we analyzed how computational characteristics in this neurobiological system affects adaptive behaviors. We proposed a novel reinforcement learning model with multilayer neural networks in which the synaptic weights of only the last layer are updated according to the prediction error. We set fixed connections between the input and hidden layers to maintain the similarity of inputs in the hidden-layer representation. This network enabled fast generalization of reward and punishment learning, and thereby facilitated safe and efficient exploration of spatial navigation tasks. Notably, it demonstrated a quick reward approach and efficient punishment aversion in the early learning phase, compared to algorithms that do not show generalization. However, disturbance of the network that causes noisy generalization and impaired discrimination induced maladaptive valuation. These results suggested the advantage and potential drawback of computation by the striatal dopamine system with regard to adaptive behaviors.
Read Full Article (External Site)
Dr. David Lowemann, M.Sc, Ph.D., is a co-founder of the Institute for the Future of Human Potential, where he leads the charge in pioneering Self-Enhancement Science for the Success of Society. With a keen interest in exploring the untapped potential of the human mind, Dr. Lowemann has dedicated his career to pushing the boundaries of human capabilities and understanding.
Armed with a Master of Science degree and a Ph.D. in his field, Dr. Lowemann has consistently been at the forefront of research and innovation, delving into ways to optimize human performance, cognition, and overall well-being. His work at the Institute revolves around a profound commitment to harnessing cutting-edge science and technology to help individuals lead more fulfilling and intelligent lives.
Dr. Lowemann’s influence extends to the educational platform BetterSmarter.me, where he shares his insights, findings, and personal development strategies with a broader audience. His ongoing mission is shaping the way we perceive and leverage the vast capacities of the human mind, offering invaluable contributions to society’s overall success and collective well-being.