AI and fMRI Show How Brain Connects Memories to Solve Problems

A team of German neuroscientists and Artificial Intelligence (AI) researchers have published results from their study that provided insights into the way the human brain connects individual episodic memories, or memories of specific events, to solve problems.

While humans are known to have the ability to creatively combine their memories to solve problems, it still remains unclear how people use their episodic memories to arrive at novel insights. According to the team of researchers, a novel brain mechanism allows the retrieved memories to trigger the retrieval of further related memories, thus allowing for the retrieval of multiple linked memories, which enable the brain to create insights.

They have suggested that the individual memories are stored as separate memory traces in a region of the brain called the hippocampus. Their new theory explores a neglected anatomical connection that loops out of the hippocampus to the neighboring entorhinal cortex, but then immediately passes back in. The researchers believe that it is this recurrent connection that allows memories to be retrieved from the hippocampus to trigger the retrieval of further related memories. The researchers tested this theory by taking high-resolution 7-Tesla functional MRI scans from 26 young men and women as they were performing a task requiring them to draw insights across separate events. The researchers showed the volunteers pairs of photographs: one of a face and one of an object or a place. Each individual object and place appeared in two separate photo pairs, each of which included a different face. This meant that every photo pair was linked with another pair through the shared object or place image.

In the second phase of the study, the participants were tested whether they could infer the indirect connection between these linked pairs of photos by showing one face and asking the participants to choose between two other faces. One of the choices—the correct one—was paired with the same object or place image, and one was not. The researchers expected the presented face to trigger the retrieval of the paired object or place and thus, spark brain activity that would pass out of the hippocampus into the entorhinal cortex. The researchers also expected evidence of this activity passing back into the hippocampus to trigger the retrieval of the correct linked face. The researchers trained a computer algorithm to distinguish between activation for scenes and objects within these input and output regions. The algorithm was then applied when only faces were displayed on the screen. If the algorithm indicated the presence of scene or object information on these trials, it could only be driven by retrieved memories of the linked scene or object photos.

"Our data showed that when the hippocampus retrieves a memory, it doesn't just pass it to the rest of the brain," said Dharshan Kumaran, a researcher who was part of the study. "Instead, it recirculates the activation back into the hippocampus, triggering the retrieval of other related memories."

The researchers believe that their results could help AI learn faster in the future. "While there are many domains where AI is superior, humans still have an advantage when tasks depend on the flexible use of episodic memory," said Martin Chadwick, another researcher who was part of the study. "If we can understand the mechanisms that allow people to do this, the hope is that we can replicate them within our AI systems, providing them with a much greater capacity for rapidly solving novel problems."