In recent years, there has been rapid progress in designing artificial intelligence technology using neural networks that imitate brain circuits. One goal of this field of research is understanding the evolution of metamemory to use it to create artificial intelligence with a human-like mind. Metamemory is the process by which we ask ourselves whether we remember what we had for dinner yesterday and then use that memory to decide whether to eat something different tonight. While this may seem like a simple question, answering it involves a complex process. Metamemory is important because it involves a person having knowledge of their own memory capabilities and adjusting their behavior accordingly.

A team of researchers at the Graduate School of Informatics, Nagoya University, have brought us one step closer to the development of a neural network with metamemory through a computer-based evolution experiment. This type of neural network could help experts understand the evolution of metamemory, which could help develop artificial intelligence (AI) with a human-like mind. "In order to elucidate the evolutionary basis of the human mind and consciousness, it is important to understand metamemory," says Professor Arita. The team of researchers, which included Professor Takaya Arita, Yusuke Yamato, and Reiji Suzuki of the Graduate School of Informatics developed an artificial neural network model that performed the delayed matching-to-sample task and analyzed its behavior. The neural network was able to examine its memories, keep them, and separate outputs all without requiring assistance or human intervention.

In recent years, rapid progress has been made in the design of artificial intelligence technology using neural networks that mimic brain circuits. One of the goals of this area of research is to understand the evolution of metamemory in order to use it to create an artificial intelligence with a human-like mind. Metamemory is the process by which we ask ourselves if we remember what we ate for dinner yesterday, and then use that memory to decide whether to eat something different tonight. Although this may seem like a simple question, answering it involves a complex process. Metamemory is important because it involves a person knowing their own memory abilities and adjusting their behavior accordingly.

A team of researchers at the Graduate School of Informatics, Nagoya University, have brought us one step closer to the development of a neural network with metamemory through a computer-based evolution experiment. This type of neural network could help experts understand the evolution of metamemory, which could help develop artificial intelligence (AI) with a human-like mind.

A research group from the Graduate School of Informatics, Nagoya University, has taken a big step towards creating a neural network with metamemory through a computer-based evolution experiment. Their paper appears in Scientific Reports. In recent years, there has been rapid progress in designing artificial intelligence technology using neural networks that imitate brain circuits. One goal of this field of research is understanding the evolution of metamemory to use it to create artificial intelligence with a human-like mind. Metamemory is the process by which we ask ourselves whether we remember what we had for dinner yesterday and then use that memory to decide whether to eat something different tonight.

A research group from the Graduate School of Informatics, Nagoya University, has taken a big step towards creating a neural network with metamemory through a computer-based evolution experiment. In recent years, there has been rapid progress in designing artificial intelligence technology using neural networks that imitate brain circuits. One goal of this field of research is understanding the evolution of metamemory to use it to create artificial intelligence with a human-like mind. Metamemory is the process by which we ask ourselves whether we remember what we had for dinner yesterday and then use that memory to decide whether to eat something different tonight. While this may seem like a simple question, answering it involves a complex process.

We know how confidently we know: Metacognitive self-monitoring of memory states, so-called "metamemory," enables strategic and efficient information collection based on past experiences. However, it is unknown how metamemory is implemented in the brain. By whole-brain searches via functional magnetic resonance imaging, we discovered a neural correlate of metamemory for temporally remote events in prefrontal area 9 (or 9/46d), along with that for recent events within area 6. Reversible inactivation of each of these identified loci induced doubly dissociated selective impairments in metacognitive judgment performance on remote or recent memory, without impairing recognition performance itself. The findings reveal that parallel metamemory streams supervise recognition networks for remote and recent memory, without contributing to recognition itself.