# The Brain Learns Like a Temporal Difference Algorithm by Terrence J. Sejnowski > “Neuroscientists have discovered that dopamine neurons, found in the brains of all vertebrates, are central to reward learning. The transient responses of dopamine neurons signal to the brain predictions for future reward, which are used to guide behavior and regulate synaptic plasticity. The dopamine responses have the same properties as the temporal difference learning algorithm used in TD-Gammon. Reinforcement learning was dismissed years ago as too weak a learner to handle the complexity of cognition. This belief needs to be re-evaluated in the light of the successes of TD-Gammon and learning algorithms in other areas of AI.” > **— Terrence J. Sejnowski**, *2007, Edge Annual Question, “What Are You Optimistic About?”* ## Sources and Context - **Direct Edge response and surrounding essay:** [Computational Neuroscientist, Salk Institute, Coauthor, The Computational Brain](https://www.edge.org/response-detail/10577) — Edge published this exact passage in its 2007 Annual Question collection, *WHAT ARE YOU OPTIMISTIC ABOUT?*. The response page preserves the surrounding argument and qualifications. - **Complete local collection index:** [[research/Edge 2007 Full Quotation Curation|Edge 2007 Full Quotation Curation]] — retained source-first record for the complete response cohort and this passage's promotion status. ## Related Articles and Collections - **Collection:** [[collections/Edge|Edge]] - **Collection:** [[collections/Machine Succession|Machine Succession]] - **Article:** [[articles/Modern Artificial Intelligence in the 1970s|AI in the 1970s]] - **Article:** [[articles/Christopher Nolan's Odyssey at the Threshold of Machine Succession|Nolan's Odyssey]] - **Article:** [[articles/Cyber-Physical Lessons from Imperial Beekeeping|Cyber-Physical Beekeeping]] - **Wiki map:** [[wiki/Artificial Intelligence|Artificial Intelligence]] ## Related Topics - [[wiki/Artificial Intelligence|Artificial Intelligence]] - [[wiki/Machine Learning|Machine Learning]] - [[wiki/Infrastructural Superintelligence|Infrastructural Superintelligence]] - [[wiki/Machine Succession|Machine Succession]] ## Share on Social Media ``` “Neuroscientists have discovered that dopamine neurons, found in the brains of all vertebrates, are central to reward learning. The transient responses of dopamine neurons signal to the brain predictions for future reward, which are used to guide behavior and regulate synaptic plasticity. The dopamine responses have the same properties as the temporal difference learning algorithm used in TD-Gammon. Reinforcement learning was dismissed years ago as too weak a learner to handle the complexity of cognition. This belief needs to be re-evaluated in the light of the successes of TD-Gammon and learning algorithms in other areas of AI.” — Terrence J. Sejnowski, 2007, Edge Annual Question, “What Are You Optimistic About?” https://bryantmcgill.com/simple-reminders-terrence-sejnowski-brain-learns-like-temporal-difference ```