Each of the five panels shows a memory snapshot created by hundreds of place cells while the rat was physically stationary at the top of the 1.8 m track (black). The time difference between the first and last snapshot is a mere one-fifth of a second; the positions represented by the neurons are shown in bright colors. (credit: Reprinted with permission from Pfeiffer and Foster, Science, 349:180)(2015)
How do you visualize your memory? As a continuous video recording, or as a series of snapshots strung together?
According to Johns Hopkins scientists, who actually watched nerve cells firing in the brains of rats as they planned where to go next, it’s a series of snapshots — more like jumping across stepping stones than walking across a bridge.
“Our data from rats suggest that our memories are actually organized that way, with one network of neurons responsible for the snapshots and another responsible for the string that connects them,” says David Foster, Ph.D., an assistant professor of neuroscience at the Johns Hopkins University School of Medicine.
A summary of their experiments, published in the journal Science on July 10, sheds light on what memories are and how they form,and how the system could fail.
The 2014 Nobel Prize in Physiology or Medicine was awarded for the discovery of a positioning system in the brain. Grid cells, together with other cells in the entorhinal cortex of the brain that recognize the direction of the head and the border of the room, form networks with the place cells in the hippocampus. This circuitry constitutes a comprehensive positioning system in the brain that appears to have components similar to those of the rat brain. (Credit: Mattias Karlén/The Nobel Committee for Physiology or Medicine)
Foster and his team focused their experiments on a group of nerve cells in the hippocampus of the brain known — in animals and people — for creating a mental “map” of experiences, or memories. The cells are called place cells because they each develop a preferred place in an environment and mainly fire only when the animal is in that place.
In previous experiments, Foster’s group learned that when a rat wants to get from point A to point D, it maps out its route mentally before starting on its journey. They could “see” this happen by implanting many tiny wires in the brains of the rats so that they could monitor the activity of more than 200 place cells at a time. By doing so, they found that the place cells representing point A would fire first, followed by those for point B, then C and D.
Maps of gaps
Their latest work, says Foster, is essentially a higher resolution “map” of the same process, which revealed gaps in between points A, B, C and D, corresponding to actual “gaps” between discrete “memories” in the rats’ brains.
“The trajectories that the rats reconstructed weren’t smooth,” says Foster. “We were able to see that neural activity ‘hovers’ in one place for about 20 milliseconds before ‘jumping’ to another place, where it hovers again before moving on to the next point.”
He says that what seems to be happening during the hovering phase is an individual memory is being strengthened or focused. “At first, you get a ‘blurry’ representation of point A because a bunch of place cells all around point A fire, but, as time passes, the activity becomes more focused on A,” he explains. Then the activity jumps to a “blurry” version of B, which then gets focused.
“We think that there is a whole network of cells dedicated to this process of fine-tuning and jumping,” says Foster. “Without it, memory retrieval would be even messier than it is.”
In the future, the group plans to see what happens when certain memories within a path go missing, hoping to learn more about what memories are and how we can preserve them in those suffering from Alzheimer’s disease and other cognitive disorders.
Abstract of Autoassociative dynamics in the generation of sequences of hippocampal place cells
Neuronal circuits produce self-sustaining sequences of activity patterns, but the precise mechanisms remain unknown. Here we provide evidence for autoassociative dynamics in sequence generation. During sharp-wave ripple (SWR) events, hippocampal neurons express sequenced reactivations, which we show are composed of discrete attractors. Each attractor corresponds to a single location, the representation of which sharpens over the course of several milliseconds, as the reactivation focuses at that location. Subsequently, the reactivation transitions rapidly to a spatially discontiguous location. This alternation between sharpening and transition occurs repeatedly within individual SWRs and is locked to the slow-gamma (25 to 50 hertz) rhythm. These findings support theoretical notions of neural network function and reveal a fundamental discretization in the retrieval of memory in the hippocampus, together with a function for gamma oscillations in the control of attractor dynamics.