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In the brain at rest, neurons rehearse future experience
Some dreams may, in fact, predict the future: New research has found that during sleep, some neurons not only replay the recent past but also anticipate future experience.
“Certain neurons fire in response to specific stimuli,” said Kamran Diba, an associate professor of anesthesiology at Michigan and corresponding author on the study. “Neurons in the visual cortex fire when presented with the appropriate visual stimulus. The neurons we’re studying show place preferences.”
Together with collaborators in Michigan’s Neural Circuits and Memory Lab led by Diba, Rice neuroscientist Caleb Kemere has been studying the process by which these specialized neurons produce a representation of the world after a new experience. Specifically, the researchers 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 Kemere, associate professor of electrical and computer engineering and bioengineering at Rice.
Sleep is critical for memory and learning — science has quantified this age-old intuition by measuring performance on memory tests after a nap as opposed to after a period of waking or even sleep deprivation.
A couple of decades ago, scientists also discovered that neurons in the brains of sleeping animals that had been allowed to explore a new setting just before resting were firing in ways that replayed the animals’ trajectories during exploration. This finding aligned with the knowledge that sleep helps new experiences crystallize into stable memories, thus suggesting that the spatial representations of many of these specialized neurons in the hippocampus are stable during sleep. However, the researchers wanted to see if there was more to the story.
“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,” Kemere said. “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,” Kemere said, highlighting the challenge of assessing what happens to place fields during rest periods when the animal is not physically moving through the maze.
“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,” Diba said. “We addressed this challenge by relating the activity of each individual neuron to the activity of all the other neurons.”
This was the study’s key innovation: The researchers 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,” Diba said.
Both Diba and Kemere commended Kourosh Maboudi, a postdoctoral researcher at Michigan and the lead author on the study, for his role in the development of the learned tuning approach.
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 researchers 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,” Kemere said. “It turns out some neurons end up doing something else.
“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. Kemere underscored that almost all plasticity research — which examines the mechanisms that allow neurons to rewire and form new representations — looks at what happens during waking periods as stimuli are being presented rather than during sleep when the relevant stimuli are absent.
“It seems like plasticity or rewiring in the brain requires really fast timescales,” Diba said, pointing to the fascinating relationship between the duration of actual experience, “which can take up the span of seconds, minutes but also hours or days,” and actual memories, “which are super compressed.”
“If you remember anything, the memory — it’s instant,” Diba said, referencing a famous literary passage by French modernist writer Marcel Proust in which a childhood memory unspools a whole lost world of past experience at barely a moment’s notice.
The study is an example of advancements in neuroscience enabled in the past few decades by technological progress in the design of stable, high-resolution neural probes as well as by machine learning-backed computation power.
In light of these advancements, Kemere said brain science stands poised to make significant progress in the future, while at the same time expressing concern for the impact of recent budget cuts on continued research.
“It’s quite possible that if we were starting this work today, we might not have been able to do these experiments and get these results,” Kemere said. “We’re definitely grateful that the opportunity was there.”
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Early dark energy could resolve cosmology’s two biggest puzzles
A new study by MIT physicists proposes that a mysterious force known as early dark energy could solve two of the biggest puzzles in cosmology and fill in some major gaps in our understanding of how the early universe evolved.
Now, the MIT team has found that both puzzles could be resolved if the early universe had one extra, fleeting ingredient: early dark energy. Dark energy is an unknown form of energy that physicists suspect is driving the expansion of the universe today. Early dark energy is a similar, hypothetical phenomenon that may have made only a brief appearance, influencing the expansion of the universe in its first moments before disappearing entirely.
Some physicists have suspected that early dark energy could be the key to solving the Hubble tension, as the mysterious force could accelerate the early expansion of the universe by an amount that would resolve the measurement mismatch.
The MIT researchers have now found that early dark energy could also explain the baffling number of bright galaxies that astronomers have observed in the early universe. In their new study, reported in the Monthly Notices of the Royal Astronomical Society, the team modeled the formation of galaxies in the universe’s first few hundred million years. When they incorporated a dark energy component only in that earliest sliver of time, they found the number of galaxies that arose from the primordial environment bloomed to fit astronomers’ observations.
“You have these two looming open-ended puzzles,” says study co-author Rohan Naidu, a postdoc in MIT’s Kavli Institute for Astrophysics and Space Research. “We find that in fact, early dark energy is a very elegant and sparse solution to two of the most pressing problems in cosmology.”
The study’s co-authors include lead author and Kavli postdoc Xuejian (Jacob) Shen, and MIT professor of physics Mark Vogelsberger, along with Michael Boylan-Kolchin at the University of Texas at Austin, and Sandro Tacchella at the University of Cambridge.
Big city lights
Based on standard cosmological and galaxy formation models, the universe should have taken its time spinning up the first galaxies. It would have taken billions of years for primordial gas to coalesce into galaxies as large and bright as the Milky Way.
But in 2023, NASA’s James Webb Space Telescope (JWST) made a startling observation. With an ability to peer farther back in time than any observatory to date, the telescope uncovered a surprising number of bright galaxies as large as the modern Milky Way within the first 500 million years, when the universe was just 3 percent of its current age.
“The bright galaxies that JWST saw would be like seeing a clustering of lights around big cities, whereas theory predicts something like the light around more rural settings like Yellowstone National Park,” Shen says. “And we don’t expect that clustering of light so early on.”
For physicists, the observations imply that there is either something fundamentally wrong with the physics underlying the models or a missing ingredient in the early universe that scientists have not accounted for. The MIT team explored the possibility of the latter, and whether the missing ingredient might be early dark energy.
Physicists have proposed that early dark energy is a sort of antigravitational force that is turned on only at very early times. This force would counteract gravity’s inward pull and accelerate the early expansion of the universe, in a way that would resolve the mismatch in measurements. Early dark energy, therefore, is considered the most likely solution to the Hubble tension.
Galaxy skeleton
The MIT team explored whether early dark energy could also be the key to explaining the unexpected population of large, bright galaxies detected by JWST. In their new study, the physicists considered how early dark energy might affect the early structure of the universe that gave rise to the first galaxies. They focused on the formation of dark matter halos — regions of space where gravity happens to be stronger, and where matter begins to accumulate.
“We believe that dark matter halos are the invisible skeleton of the universe,” Shen explains. “Dark matter structures form first, and then galaxies form within these structures. So, we expect the number of bright galaxies should be proportional to the number of big dark matter halos.”
The team developed an empirical framework for early galaxy formation, which predicts the number, luminosity, and size of galaxies that should form in the early universe, given some measures of “cosmological parameters.” Cosmological parameters are the basic ingredients, or mathematical terms, that describe the evolution of the universe.
Physicists have determined that there are at least six main cosmological parameters, one of which is the Hubble constant — a term that describes the universe’s rate of expansion. Other parameters describe density fluctuations in the primordial soup, immediately after the Big Bang, from which dark matter halos eventually form.
The MIT team reasoned that if early dark energy affects the universe’s early expansion rate, in a way that resolves the Hubble tension, then it could affect the balance of the other cosmological parameters, in a way that might increase the number of bright galaxies that appear at early times. To test their theory, they incorporated a model of early dark energy (the same one that happens to resolve the Hubble tension) into an empirical galaxy formation framework to see how the earliest dark matter structures evolve and give rise to the first galaxies.
“What we show is, the skeletal structure of the early universe is altered in a subtle way where the amplitude of fluctuations goes up, and you get bigger halos, and brighter galaxies that are in place at earlier times, more so than in our more vanilla models,” Naidu says. “It means things were more abundant, and more clustered in the early universe.”
“A priori, I would not have expected the abundance of JWST’s early bright galaxies to have anything to do with early dark energy, but their observation that EDE pushes cosmological parameters in a direction that boosts the early-galaxy abundance is interesting,” says Marc Kamionkowski, professor of theoretical physics at Johns Hopkins University, who was not involved with the study. “I think more work will need to be done to establish a link between early galaxies and EDE, but regardless of how things turn out, it’s a clever — and hopefully ultimately fruitful — thing to try.”
“We demonstrated the potential of early dark energy as a unified solution to the two major issues faced by cosmology. This might be an evidence for its existence if the observational findings of JWST get further consolidated,” Vogelsberger concludes. “In the future, we can incorporate this into large cosmological simulations to see what detailed predictions we get.”
This research was supported, in part, by NASA and the National Science Foundation.
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Plant-derived secondary organic aerosols can act as mediators of plant-plant interactions
A new study published in Science reveals that plant-derived secondary organic aerosols (SOAs) can act as mediators of plant-plant interactions. This research was conducted through the cooperation of chemical ecologists, plant ecophysiologists and atmospheric physicists at the University of Eastern Finland.
The study showed that Scots pine seedlings, when damaged by large pine weevils, release VOCs that activate defences in nearby plants of the same species. Interestingly, the biological activity persisted after VOCs were oxidized to form SOAs. The results indicated that the elemental composition and quantity of SOAs likely determines their biological functions.
“A key novelty of the study is the finding that plants adopt subtly different defence strategies when receiving signals as VOCs or as SOAs, yet they exhibit similar degrees of resistance to herbivore feeding,” said Professor James Blande, head of the Environmental Ecology Research Group. This observation opens up the possibility that plants have sophisticated sensing systems that enable them to tailor their defences to information derived from different types of chemical cue.
“Considering the formation rate of SOAs from their precursor VOCs, their longer lifetime compared to VOCs, and the atmospheric air mass transport, we expect that the ecologically effective distance for interactions mediated by SOAs is longer than that for plant interactions mediated by VOCs,” said Professor Annele Virtanen, head of the Aerosol Physics Research Group. This could be interpreted as plants being able to detect cues representing close versus distant threats from herbivores.
The study is expected to open up a whole new complex research area to environmental ecologists and their collaborators, which could lead to new insights on the chemical cues structuring interactions between plants.
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Folded or cut, this lithium-sulfur battery keeps going
Most rechargeable batteries that power portable devices, such as toys, handheld vacuums and e-bikes, use lithium-ion technology. But these batteries can have short lifetimes and may catch fire when damaged. To address stability and safety issues, researchers reporting in ACS Energy Letters have designed a lithium-sulfur (Li-S) battery that features an improved iron sulfide cathode. One prototype remains highly stable over 300 charge-discharge cycles, and another provides power even after being folded or cut.
The team coated iron sulfide cathodes in different polymers and found in initial electrochemical performance tests that polyacrylic acid (PAA) performed best, retaining the electrode’s discharge capacity after 300 charge-discharge cycles. Next, the researchers incorporated a PAA-coated iron sulfide cathode into a prototype battery design, which also included a carbonate-based electrolyte, a lithium metal foil as an ion source, and a graphite-based anode. They produced and then tested both pouch cell and coin cell battery prototypes.
After more than 100 charge-discharge cycles, Wang and colleagues observed no substantial capacity decay in the pouch cell. Additional experiments showed that the pouch cell still worked after being folded and cut in half. The coin cell retained 72% of its capacity after 300 charge-discharge cycles. They next applied the polymer coating to cathodes made from other metals, creating lithium-molybdenum and lithium-vanadium batteries. These cells also had stable capacity over 300 charge-discharge cycles. Overall, the results indicate that coated cathodes could produce not only safer Li-S batteries with long lifespans, but also efficient batteries with other metal sulfides, according to Wang’s team.
The authors acknowledge funding from the National Natural Science Foundation of China; the Natural Science Foundation of Sichuan, China; and the Beijing National Laboratory for Condensed Matter Physics.
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