University of Michigan anesthesiologist Kamran Diba and colleagues have found that during sleep, some neurons not only replay the recent past but also anticipate future experience.
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| To track the spatial tuning of neurons dynamically during offline states, Maboudi et al. used a new Bayesian learning approach based on the spike-triggered average decoded position in ensemble recordings from freely moving rats. |
“Certain neurons fire in response to specific stimuli,” Dr. Diba said.
“Neurons in the visual cortex fire when presented with the appropriate visual stimulus. The neurons we’re studying show place preferences.”
In their research, Dr. Diba and co-authors aimed to study the process by which these specialized neurons produce a representation of the world after a new experience.
Specifically, they tracked sharp wave ripples, a pattern of neuronal activation known to play a role in consolidating new memories and, more recently, also shown to tag which parts of a new experience are to be stored as memories.
“For the first time in this paper, we observed how these individual neurons stabilize spatial representations during rest periods,” said Dr. Caleb Kemere, a neuroscientist at Rice University.
“We imagined that some neurons might change their representations — reflecting the experience we’ve all had of waking up with a new understanding of a problem.”
“Showing this, however, required that we track how individual neurons achieve spatial tuning, i.e., the process by which the brain learns to navigate a new route or environment.”
The researchers trained rats to run back and forth on a raised track with liquid reward at either end and observed how individual neurons in the animals’ hippocampus would ‘spike’ in the process.
By calculating an average spiking rate over many laps back and forth, the researchers were able to estimate the neurons’ place field — or the area in the environment that a given neuron ‘cared’ about most.
“The critical point here is that place fields are estimated using the behavior of the animal,” Dr. Kemere said.
“I’ve been thinking for a long time about how we can evaluate the preferences of neurons outside of the maze, such as during sleep,” Dr. Diba added.
“We addressed this challenge by relating the activity of each individual neuron to the activity of all the other neurons.”
The scientists also developed a statistical machine learning approach that used the other neurons surveyed to map out an estimate of where the animal was dreaming of being.
They next used those dreamed positions to estimate the spatial tuning process for each neuron in their data sets.
“The ability to track the preferences of neurons even without a stimulus was an important breakthrough for us,” Dr. Diba said.
The method confirmed that the spatial representations that form during the experience of a new environment are, for most neurons, stable across several hours of postexperience sleep.
But as the authors had anticipated, there was more to the story.
“The thing that I loved the most about this research and the reason that I was so excited about it is finding that it’s not necessarily the case that during sleep the only thing these neurons do is to stabilize a memory of the experience. It turns out some neurons end up doing something else,” Dr. Kemere said.
“We can see these other changes occurring during sleep, and when we put the animals back in the environment a second time, we can validate that these changes really do reflect something that was learned while the animals were asleep.”
“It’s as if the second exposure to the space actually happens while the animal is sleeping.”
This is significant because it constitutes direct observation of neuroplasticity as it is happening during sleep.
“It seems like plasticity or rewiring in the brain requires really fast timescales,” Dr. Diba said.
This research is described in a paper in the journal Nature.
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K. Maboudi et al. 2024. Retuning of hippocampal representations during sleep. Nature 629, 630-638; doi: 10.1038/s41586-024-07397-x
