Nearly 50 years ago, neuroscientists discovered cells within the brain’s hippocampus that store memories of specific locations. These cells also play an important role in storing memories of events, known as episodic memories. While the mechanism of how place cells encode spatial memory has been well-characterized, it has remained a puzzle how they encode episodic memories.

A new model developed by MIT researchers explains how those place cells can be recruited to form episodic memories, even when there’s no spatial component. According to this model, place cells, along with grid cells found in the entorhinal cortex, act as a scaffold that can be used to anchor memories as a linked series.

“This model is a first-draft model of the entorhinal-hippocampal episodic memory circuit. It’s a foundation to build on to understand the nature of episodic memory. That’s the thing I’m really excited about,” says Ila Fiete, a professor of brain and cognitive sciences at MIT, a member of MIT’s McGovern Institute for Brain Research, and the senior author of the new study.

The model accurately replicates several features of biological memory systems, including the large storage capacity, gradual degradation of older memories, and the ability of people who compete in memory competitions to store enormous amounts of information in “memory palaces.”

MIT Research Scientist Sarthak Chandra and Sugandha Sharma PhD ’24 are the lead authors of the study, which appears today in Nature. Rishidev Chaudhuri, an assistant professor at the University of California at Davis, is also an author of the paper.

An index of memories

To encode spatial memory, place cells in the hippocampus work closely with grid cells — a special type of neuron that fires at many different locations, arranged geometrically in a regular pattern of repeating triangles. Together, a population of grid cells forms a lattice of triangles representing a physical space.

In addition to helping us recall places where we’ve been, these hippocampal-entorhinal circuits also help us navigate new locations. From human patients, it’s known that these circuits are also critical for forming episodic memories, which might have a spatial component but mainly consist of events, such as how you celebrated your last birthday or what you had for lunch yesterday.

“The same hippocampal and entorhinal circuits are used not just for spatial memory, but also for general episodic memory,” Fiete says. “The question you can ask is what is the connection between spatial and episodic memory that makes them live in the same circuit?”

Two hypotheses have been proposed to account for this overlap in function. One is that the circuit is specialized to store spatial memories because those types of memories — remembering where food was located or where predators were seen — are important to survival. Under this hypothesis, this circuit encodes episodic memories as a byproduct of spatial memory.

An alternative hypothesis suggests that the circuit is specialized to store episodic memories, but also encodes spatial memory because location is one aspect of many episodic memories.

In this work, Fiete and her colleagues proposed a third option: that the peculiar tiling structure of grid cells and their interactions with hippocampus are equally important for both types of memory — episodic and spatial. To develop their new model, they built on computational models that her lab has been developing over the past decade, which mimic how grid cells encode spatial information.

“We reached the point where I felt like we understood on some level the mechanisms of the grid cell circuit, so it felt like the time to try to understand the interactions between the grid cells and the larger circuit that includes the hippocampus,” Fiete says.

In the new model, the researchers hypothesized that grid cells interacting with hippocampal cells can act as a scaffold for storing either spatial or episodic memory. Each activation pattern within the grid defines a “well,” and these wells are spaced out at regular intervals. The wells don’t store the content of a specific memory, but each one acts as a pointer to a specific memory, which is stored in the synapses between the hippocampus and the sensory cortex.

When the memory is triggered later from fragmentary pieces, grid and hippocampal cell interactions drive the circuit state into the nearest well, and the state at the bottom of the well connects to the appropriate part of the sensory cortex to fill in the details of the memory. The sensory cortex is much larger than the hippocampus and can store vast amounts of memory.

“Conceptually, we can think about the hippocampus as a pointer network. It’s like an index that can be pattern-completed from a partial input, and that index then points toward sensory cortex, where those inputs were experienced in the first place,” Fiete says. “The scaffold doesn’t contain the content, it only contains this index of abstract scaffold states.”

Furthermore, events that occur in sequence can be linked together: Each well in the grid cell-hippocampal network efficiently stores the information that is needed to activate the next well, allowing memories to be recalled in the right order.

Modeling memory cliffs and palaces

The researchers’ new model replicates several memory-related phenomena much more accurately than existing models that are based on Hopfield networks — a type of neural network that can store and recall patterns.

While Hopfield networks offer insight into how memories can be formed by strengthening connections between neurons, they don’t perfectly model how biological memory works. In Hopfield models, every memory is recalled in perfect detail until capacity is reached. At that point, no new memories can form, and worse, attempting to add more memories erases all prior ones. This “memory cliff” doesn’t accurately mimic what happens in the biological brain, which tends to gradually forget the details of older memories while new ones are continually added.

The new MIT model captures findings from decades of recordings of grid and hippocampal cells in rodents made as the animals explore and forage in various environments. It also helps to explain the underlying mechanisms for a memorization strategy known as a memory palace. One of the tasks in memory competitions is to memorize the shuffled sequence of cards in one or several card decks. They usually do this by assigning each card to a particular spot in a memory palace — a memory of a childhood home or other environment they know well. When they need to recall the cards, they mentally stroll through the house, visualizing each card in its spot as they go along. Counterintuitively, adding the memory burden of associating cards with locations makes recall stronger and more reliable.

The MIT team’s computational model was able to perform such tasks very well, suggesting that memory palaces take advantage of the memory circuit’s own strategy of associating inputs with a scaffold in the hippocampus, but one level down: Long-acquired memories reconstructed in the larger sensory cortex can now be pressed into service as a scaffold for new memories. This allows for the storage and recall of many more items in a sequence than would otherwise be possible.

The researchers now plan to build on their model to explore how episodic memories could become converted to cortical “semantic” memory, or the memory of facts dissociated from the specific context in which they were acquired (for example, Paris is the capital of France), how episodes are defined, and how brain-like memory models could be integrated into modern machine learning.

The research was funded by the U.S. Office of Naval Research, the National Science Foundation under the Robust Intelligence program, the ARO-MURI award, the Simons Foundation, and the K. Lisa Yang ICoN Center.