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Summary | 10 Annotations
When we move between different contexts like this, our brain holds multiple sets of rules in mind so that it can switch to the appropriate one when necessary.
2018/11/23 08:14
These neural representations of task rules are maintained in the prefrontal cortex
2018/11/23 08:14
This region, called the mediodorsal thalamus, suppresses representations that are not currently needed.
2018/11/23 08:14
In a 2017 study published in Nature, Halassa and his colleagues showed that the mediodorsal thalamus helps the prefrontal cortex to keep a thought in mind by temporarily strengthening the neuronal connections in the prefrontal cortex that encode that particular thought.
2018/11/23 08:15
In the new study, Halassa wanted to further investigate the relationship between the mediodorsal thalamus and the prefrontal cortex.
2018/11/23 08:15
a professor of psychology at the Princeton Neuroscience Institute, described the study as a major leap forward in the field of cognitive neuroscience.
2018/11/23 08:16
The findings could help guide the development of better artificial intelligence algorithms, Halassa says. The human brain is very good at learning many different kinds of tasks — singing, walking, talking, etc. However, neural networks (a type of artificial intelligence based on interconnected nodes similar to neurons) usually are good at learning only one thing. These networks are subject to a phenomenon called “catastrophic forgetting” — when they try to learn a new task, previous tasks become overwritten. Halassa and his colleagues now hope to apply their findings to improve neural networks’ ability to store previously learned tasks while learning to perform new ones. The research was funded by the National Institutes of Health, the Brain and Behavior Foundation, the Klingenstein Foundation, the Pew Foundation, the Simons Foundation, the Human Frontiers Science Program, and the German Ministry of Education. Topics: Research, Memory, Brain and cognitive sciences, Artificial intelligence, Neuroscience, McGovern Institute, School of Science, National Institutes of Health (NIH) Related Halassa LabMcGovern InstituteDepartment of Brain and Cognitive SciencesSchool of Science Archives Study reveals a basis for attention deficits How the brain controls sleep New study reveals how brain waves control working
2018/11/23 08:10
he findings could help guide the development of better artificial intelligence algorithms, Halassa says. The human brain is very good at learning many different kinds of tasks — singing, walking, talking, etc. However, neural networks (a type of artificial intelligence based on interconnected nodes similar to neurons) usually are good at learning only one thing. These networks are subject to a phenomenon called “catastrophic forgetting” — when they try to learn a new task, previous tasks become overwritten. Halassa and his colleagues now hope to apply their findings to improve neural networks’ ability to store previously learned tasks while learning to perform new ones. The research was funded by the National Institutes of Health, the Brain and Behavior Foundation, the Klingenstein Foundation, the Pew Foundation, the Simons Foundation, the Human Frontiers Science Program, and the German Ministry of Education. Topics: Research, Memory, Brain and cognitive sciences, Artificial intelligence, Neuroscience, McGovern Institute, School of Science, National Institutes of Health (NIH) Related Halassa LabMcGovern InstituteDepartment of Brain and Cognitive SciencesSchool of Science Archives Study reveals a basis for attention deficits How the brain controls sleep
2018/11/23 08:11
The findings could help guide the development of better artificial intelligence algorithms,
2018/11/23 08:16
The findings could help guide the development of better artificial intelligence algorithms,
2018/11/23 08:16