Light Enables Long-Term Memory Maintenance in Fruit Flies

S. Inami et al., “Environmental light is required for maintenance of long-term memory in Drosophila,” J Neurosci, 40:1427–39, 2020.

by Diana Kwon

As Earth rotates around its axis, the organisms that inhabit its surface are exposed to daily cycles of darkness and light. In animals, light has a powerful influence on sleep, hormone release, and metabolism. Work by Takaomi Sakai, a neuroscientist at Tokyo Metropolitan University, and his team suggests that light may also be crucial for forming and maintaining long-term memories.

The puzzle of how memories persist in the brain has long been of interest to Sakai. Researchers had previously demonstrated, in both rodents and flies, that the production of new proteins is necessary for maintaining long-term memories, but Sakai wondered how this process persisted over several days given cells’ molecular turnover. Maybe, he thought, an environmental stimulus, such as the light-dark cycles, periodically triggered protein production to enable memory formation and storage.

Sakai and his colleagues conducted a series of experiments to see how constant darkness would affect the ability of Drosophila melanogaster to form long-term memories. Male flies exposed to light after interacting with an unreceptive female showed reduced courtship behaviors toward new female mates several days later, indicating they had remembered the initial rejection. Flies kept in constant darkness, however, continued their attempts to copulate.

The team then probed the molecular mechanisms of these behaviors and discovered a pathway by which light activates cAMP response element-binding protein (CREB)—a transcription factor previously identified as important for forming long-term memories—within certain neurons found in the mushroom bodies, the memory center in fly brains.

“The fact that light is essential for long-term memory maintenance is fundamentally interesting,” says Seth Tomchick, a neuroscientist at the Scripps Research Institute in Florida who wasn’t involved in the study. However, he adds, “more work will be necessary” to fully characterize the molecular mechanisms underlying these effects.

Genetic Risk for Alzheimer’s Disease Linked to Highly Active Brains

Young carriers of the APOE4 allele have brains that are more connected (left, red lines illustrate connections between brain areas) and active (right, yellow indicates activity) than the brains of those without the allele.
KRISHNA SINGH, ELIFE, 8:E36011, 2019.

A growing body of evidence supports the theory that neural hyperactivity and hyperconnectivity precede the pathological changes that lead to neurodegeneration.


There are approximately 5.6 million people over the age of 65 living with Alzheimer’s disease in the United States. With the population aging, that number is projected to grow to 7.1 million by 2025. Researchers know that age, a family history of the disease, and carrying a genetic variant known as APOE4 are all associated with a higher chance of developing the condition. But the biological mechanisms leading to Alzheimer’s are still largely a mystery.

Over the last decade, scientists have amassed evidence for a hypothesis that, prior to developing full-blown Alzheimer’s disease, patients experience a period of hyperactivity and hyperconnectivity in the brain. Several functional magnetic resonance imaging studies have reported that people with mild cognitive impairment (MCI), a condition that often precedes Alzheimer’s, appear to have higher brain activity levels than their age-matched counterparts. Researchers have also found signs of such changes in healthy people carrying the APOE4 allele, as well as in presymptomatic stages of Alzheimer’s in rodent models of the disease.

Krishna Singh, a physicist and imaging neuroscientist at the Cardiff University Brain Research Imaging Center (CUBRIC) in the UK, and his colleagues wanted to investigate this theory further. Previous studies of brain activity in young APOE4 carriers were mostly conducted using small sample sizes, according to Singh. But by the mid-2010s, his team had access to neuroimaging data from close to 200 participants studied at CUBRIC as part of an effort to build a massive dataset of healthy brains. So the researchers decided to use the data to search for signs of unusual brain activity and connectivity in people with the APOE4 allele.

Using magnetoencephalography (MEG), a neuroimaging technique that records the magnetic fields generated by electrical activity in the brain, Singh and his colleagues had measured resting-state brain activity in a group of 183 healthy adults, which included 51 individuals who carried at least one copy of APOE4. The average age of the participants was 24 years old, although ages ranged from 18 to 65 years old.

Analysis of the imaging data revealed that, compared with controls, young APOE4 carriers displayed greater activity in several regions in the right side of the brain, including parts of what’s known as the default mode network, which is active when a person is not focused on a specific task. A similar set of brain regions also showed an overall increase in connectivity.

The researchers next compared the results to brain activity and connectivity data from a previous neuro­imaging study they had conducted, which found that elderly people with early-stage Alzheimer’s disease had decreased neuronal activity and connectivity compared with that of age-matched controls. The network of brain areas that displayed increased connectivity in young APOE4 carriers, the team found, partially overlapped with the brain regions that exhibited a decrease in connectivity in people with early-stage Alzheimer’s. These findings are intriguing, Singh says, because they suggest that brain areas that end up getting impaired in Alzheimer’s may be highly active and connected early in life—long before symptoms of the disease appear.

“This study adds further evidence that hyperactivity and hyperconnectivity may play an influential role in Alzheimer’s disease,” says Tal Nuriel, a professor of pathology and cell biology at the Columbia University Medical Center who wasn’t involved in the work. Because this was an observational study, the findings can only establish a correlation between brain activity and Alzheimer’s, Nuriel adds, so it’s still unclear whether the hyperactivity and hyperconnectivity observed during the early stages of the disease are a cause or a consequence of pathological changes that lead to neurodegeneration.

Scientists used to think that increased activity was simply a compensatory effect—the brain trying to make up for a loss of neurons and synapses, says Willem de Haan, a neurologist at the Amsterdam University Medical Center who was not involved in the latest study. “But I think there’s overwhelming evidence that this may actually be pathological hyperactivity.”

Much of that evidence comes from animal experiments conducted over the last decade or so. In rodents, researchers have found that hyperactivity can increase the production and spread of amyloid-ß, the peptide that accumulates into plaques found in the brains of people with Alzheimer’s—and that amyloid-ß can in turn induce neuronal hyperactivity. These findings have led some scientists to speculate that there might be a self-amplifying loop, where a progressive hyperactivity and build-up of amyloid-ß drives pathological changes associated with the neurodegenerative disease.

Research in humans also supports the idea that hyperactivity could play a causal role in Alzheimer’s disease. In 2012, researchers at Johns Hopkins University treated individuals with MCI with the anti-epileptic drug levetiracetam and found that the therapy suppressed activity in the hippocampus and led to improved memory performance. The team is currently testing levetiracetam for MCI in clinical trials. “I think this is one of the most interesting results,” says de Haan. “It seems to show that by correcting hyperactivity we can actually find some improvements in patients that might point to a completely new type of therapy for [Alzheimer’s disease].”

For the current study, Singh’s team also trained a machine-learning algorithm to distinguish APOE4 carriers from non-carriers based on their MEG data and tested whether it would be able to predict cases of Alzheimer’s. They found that while the program was able to perform above chance, the effect was not significant. “In a way, that was kind of encouraging,” Singh says. “Because I don’t think anybody would predict that we could find a signature [for Alzheimer’s] in 20- and 30-year-olds.”

For now, Singh says, his team’s findings simply shed light on what might be going on in the brains of people with the APOE4 allele. There are still a number of unanswered questions—such as when the transition from hyper- to hypoconnectivity and activity happens, what changes occur in the largely understudied middle-aged cohort, and whether there are differences between APOE4 carriers who go on to develop Alzheimer’s and those who don’t. Ultimately, to understand how disruptions in neuronal activity lead to behavioral and cognitive deficits, scientists need to decipher what’s going on inside a healthy brain, Singh says. “[We] require a model of how the brain works—and those are still in their infancy.”

When artificial intelligence was allowed to learn how to move through a virtual environment, it spontaneously generated patterns of activity found in grid neurons of the human brain.

Futuristic cityscape maze.

By Diana Kwon

A computer program can learn to navigate through space and spontaneously mimics the electrical activity of grid cells, neurons that help animals navigate their environments, according to a study published May 9 in Nature.

“This paper came out of the blue, like a shot, and it’s very exciting,” Edvard Moser, a neuroscientist at the Kavli Institute for Systems Neuroscience in Norway who was not involved in the work, tells Nature in an accompanying news story. “It is striking that the computer model, coming from a totally different perspective, ended up with the grid pattern we know from biology.” Moser shared a Nobel Prize for the discovery of grid cells with neuroscientists May-Britt Moser and John O’Keefe in 2014.

When scientists trained an artificial neural network to navigate in the form of virtual rats through a simulated environment, they found that the algorithm produced patterns of activity similar to that found in the grid cells of the human brain. “We wanted to see whether we could set up an artificial network with an appropriate task so that it would actually develop grid cells,” study coauthor Caswell Barry of University College London, tells Quanta. “What was surprising was how well it worked.”

The team then tested the program in a more-complex, maze-like environment, and found that not only did the virtual rats make their way to the end, they were also able to outperform a human expert at the task.

“It is doing the kinds of things that animals do and that is to take direct routes wherever possible and shortcuts when they are available,” coauthor Dharshan Kumaran, a senior researcher at Google’s AI company DeepMind, tells The Guardian.

DeepMind researchers hope to use these types of artificial neural networks to study other parts of the brain, such as those involved in understanding sound and controlling limbs, according to Wired. “This has proven to be extremely hard with traditional neuroscience so, in the future, if we could improve these artificial models, we could potentially use them to understand other brain functionalities,” study coauthor Andrea Banino, a research scientist at DeepMind, tells Wired. “This would be a giant step toward the future of brain understanding.”

Caloric Restriction Slows Signs of Aging in Humans

by Diana Kwon

Findings from a randomized, controlled trial finds that reducing food intake decreases metabolism and reduces oxidative damage to tissues and cells.

Studies in various animals, including rodents and monkeys, have reported that caloric restriction can extend their lifespans. Findings from a two-year, randomized, controlled trial with human participants, published last week (March 22) in Cell Metabolism, suggest that cutting down on calories may also be able to prolong the lives of people.

To investigate the effects of reducing food intake, Leanne Redman, an endocrinologist at the Pennington Biomedical Research Center at Louisiana State University, and her colleagues enrolled 53 healthy men and women between the ages of 21 and 50 and split them into two groups—one group reduced their caloric intake by 15 percent over two years, and the other remained on a regular diet.

The team found that the people who ate a restricted diet lost an average of around 9 kilograms and experienced a 10-percent drop in their resting metabolic rates. When the researchers examined the participants’ blood, they also found a reduction in markers of oxidative stress in those who cut down on calories. “After two years, the lower rate of metabolism and level of calorie restriction was linked to a reduction in oxidative damage to cells and tissues,” Redman tells Wired.

“[I]f by-products of metabolism accelerate aging processes, calorie restriction sustained over several years may help to decrease risk for chronic disease and prolong life,” Redman says in a statement.

This study was part of a larger, multi-center investigation of caloric restriction in humans, the Comprehensive Assessment of Long-Term Effects of Reducing Intake of Energy (CALERIE) trial. Luigi Fontana, an internist who ran a CALERIE investigation at Washington University in St. Louis, says that a slower metabolism and reduced oxidative stress will not necessarily lead to a longer life. “You can have a low resting metabolic rate because you’re dying of starvation,” he tells Wired. “Does that make it a biomarker of longevity? No. You can be calorie restricted by eating half a hamburger and a few fries each day but will you live longer? No, you will die of malnutrition.”