Unlike a bicep or a quadricep, we can’t see or feel when our brain is turning into mush through either disuse or misuse. Instead, any atrophy will instead make itself known when we’re struggling to remember a very common word, getting hopelessly lost in a part of town we’re intimately familiar with, or being driven to tears trying to figure out how to set up a personal hotspot. That last one happened to me about 90 minutes ago.
While the brain isn’t literally a muscle, its function can be positively and negatively affected by the behaviors we engage in—and ones that we don’t—each and every day. Below is a litany of habits you can pick up that could help you stop fucking with your grey matter and help enhance its function instead. If you change your ways, your chances of regaining your sparkle are good.
As I’m sure you’ve noticed, sleep is extremely important to all aspects of our health. Unfortunately, we’re getting less of it than ever. As recently as the mid-1900s, people slept around nine hours per night. In 1970, that number had fallen to around 7.5 hours per night. According to the CDC, over a third of American adults getting less than seven hours shut-eye per night. “Sleep is essential for optimal neuropsychological ability,” says Virginia-based neurologist and sleep specialist W. Christopher Winter. He elaborates on this in his book, The Sleep Solution: Why Your Sleep is Broken and How to Fix It. “From interpreting nonverbal cues and emotional content to managing concentration and organizing information in our minds, sleep is vital—and restricted sleep can dramatically impact cognitive performance.”
Another sleep-related thing to consider: naps are not just for cranky toddlers. A small study from 2010 looked at the academic performance of two groups of young adults: nappers and non-nappers. In the experiment, every participant completed a rigorous learning task. After the first task, one group took a 90-minute nap while the other stayed awake until a second task was administered hours later. The participants who napped in between tasks did significantly better on the second task and also showed signs of improvement and learning.
The non-nappers, on the other hand, became worse at learning and their ability to retain information decreased. “Napping helps raise levels of alertness and can help with memory,” says clinical psychologist and sleep specialist Michael Breus. He explains that a 20 to 25 minute cat nap can help you to stay sharp when you just didn’t get enough sleep the night before, but that getting more nighttime sleep is the best solution.
Caffeinate (in moderation)
Many of us are well acquainted with coffee’s ability to get us moving in the morning, but it can also help you process things more quickly. Winter says that caffeine’s role as a performance-enhancing drug has long been known. “It helps with concentration, focus, and memory processing as well as recall,” he says. According to a study from 2012, 200 mg of caffeine (about as much as you’d find in a 12-ounce cup of coffee) can improve a person’s verbal processing speed. By providing a group of adults a 200 mg caffeine pill in the morning and then asking them to complete word-recognition tasks, researchers discovered improved speed and accuracy compared to when they completed these tasks without caffeine.
Put the bottle down once in a while
In a study in the British Medical Journal, researchers looked at the impact of moderate alcohol consumption on the brain through the cognitive ability of more than 500 adults over 30 years. It was demonstrated that people who drank between 15 and 20 standard drinks per week were three times more likely to suffer from hippocampal atrophy—damage to the area of the brain involved in memory and spatial navigation.
Overall, drinking doesn’t “kill your brain cells,” but drinking too much too often can damage the part of your brain responsible for remembering things, which is almost as bleak. That actually leads me to my next suggestion.
Give Google a break
If you’re older than say, 35, you can probably remember a time when you had at least a dozen phone numbers committed to memory. You may also recall certain mental tricks you may have employed to help you do so, such as associating certain number sequences with the location of their keys on the dial pad, or “clustering” the numbers into groups to help you retain them. Guess what? That’s called using your brain.
In today’s connected world, we’re storing information basically everywhere else. In a 2011 paper entitled Google Effects on Memory: Cognitive Consequences of Having Information at Our Fingertips, college students were shown to recall less information when they knew they could search for it instead. Winter says that stress can be helpful in memory formation. Knowing that you have access to all the information you’ll need “might reduce memory capacity,” he says.
Have more sex
Sometimes, after a long, hard day, the thought of energetic humping can seem so daunting that you and your partner agree to a half-assed snuggle instead. But if you’re not making sex a priority at all, it might be worth checking out some of the research that touts the benefits it might have on our brain function.
In a small 2017 study published in the Journals of Gerontology, researchers asked a group of older adults questions about their sex lives and then had them to take a standardized test. This revealed a link between sex frequency and intelligence: People who claimed to engage in sexual activity weekly wound up having higher test scores than people who did not. It’s important to note that we can’t be certain of the direction of this effect—people who feel sharper might be more likely to be having more sex.
Still, other recent research has demonstrated a strong link between getting wild and getting smart. In 2017, another study published in the Archives of Sexual Behavior looked at the effect of sex on the cognitive abilities of 78 women aged between 18 and 29. Controlled for other factors such as menstrual phase and relationship length, researchers found that women who had sex more often had better recall of abstract words on a memory test. In fact, the bulk of research done on the benefits of sex on the brain revolves around memory. People who are getting some on a regular basis may be less depressed and more emotionally satisfied too, Winter says. This, he adds, could line up with sex being cognitively beneficial and helpful with focus.
IT BEGAN ABOUT a decade ago at Syracuse University, with a set of equations scrawled on a blackboard. Marc Howard, a cognitive neuroscientist now at Boston University, and Karthik Shankar, who was then one of his postdoctoral students, wanted to figure out a mathematical model of time processing: a neurologically computable function for representing the past, like a mental canvas onto which the brain could paint memories and perceptions. “Think about how the retina acts as a display that provides all kinds of visual information,” Howard said. “That’s what time is, for memory. And we want our theory to explain how that display works.”
But it’s fairly straightforward to represent a tableau of visual information, like light intensity or brightness, as functions of certain variables, like wavelength, because dedicated receptors in our eyes directly measure those qualities in what we see. The brain has no such receptors for time. “Color or shape perception, that’s much more obvious,” said Masamichi Hayashi, a cognitive neuroscientist at Osaka University in Japan. “But time is such an elusive property.” To encode that, the brain has to do something less direct.
Original story reprinted with permission from Quanta Magazine, an editorially independent publication of the Simons Foundation whose mission is to enhance public understanding of science by covering research developments and trends in mathematics and the physical and life sciences.
Pinpointing what that looked like at the level of neurons became Howard and Shankar’s goal. Their only hunch going into the project, Howard said, was his “aesthetic sense that there should be a small number of simple, beautiful rules.”
They came up with equations to describe how the brain might in theory encode time indirectly. In their scheme, as sensory neurons fire in response to an unfolding event, the brain maps the temporal component of that activity to some intermediate representation of the experience—a Laplace transform, in mathematical terms. That representation allows the brain to preserve information about the event as a function of some variable it can encode rather than as a function of time (which it can’t). The brain can then map the intermediate representation back into other activity for a temporal experience—an inverse Laplace transform—to reconstruct a compressed record of what happened when.
Just a few months after Howard and Shankar started to flesh out their theory, other scientists independently uncovered neurons, dubbed “time cells,” that were “as close as we can possibly get to having that explicit record of the past,” Howard said. These cells were each tuned to certain points in a span of time, with some firing, say, one second after a stimulus and others after five seconds, essentially bridging time gaps between experiences. Scientists could look at the cells’ activity and determine when a stimulus had been presented, based on which cells had fired. This was the inverse-Laplace-transform part of the researchers’ framework, the approximation of the function of past time. “I thought, oh my god, this stuff on the blackboard, this could be the real thing,” Howard said.
“It was then I knew the brain was going to cooperate,” he added.
Invigorated by empirical support for their theory, he and his colleagues have been working on a broader framework, which they hope to use to unify the brain’s wildly different types of memory, and more: If their equations are implemented by neurons, they could be used to describe not just the encoding of time but also a slew of other properties—even thought itself.
But that’s a big if. Since the discovery of time cells in 2008, the researchers had seen detailed, confirming evidence of only half of the mathematics involved. The other half—the intermediate representation of time—remained entirely theoretical.
Until last summer.
Orderings and Timestamps
In 2007, a couple of years before Howard and Shankar started tossing around ideas for their framework, Albert Tsao (now a postdoctoral researcher at Stanford University) was an undergraduate student doing an internship at the Kavli Institute for Systems Neuroscience in Norway. He spent the summer in the lab of May-Britt Moser and Edvard Moser, who had recently discovered grid cells—the neurons responsible for spatial navigation—in a brain area called the medial entorhinal cortex. Tsao wondered what its sister structure, the lateral entorhinal cortex, might be doing. Both regions provide major input to the hippocampus, which generates our “episodic” memories of experiences that occur at a particular time in a particular place. If the medial entorhinal cortex was responsible for representing the latter, Tsao reasoned, then maybe the lateral entorhinal cortex harbored a signal of time.
The kind of memory-linked time Tsao wanted to think about is deeply rooted in psychology. For us, time is a sequence of events, a measure of gradually changing content. That explains why we remember recent events better than ones from long ago, and why when a certain memory comes to mind, we tend to recall events that occurred around the same time. But how did that add up to an ordered temporal history, and what neural mechanism enabled it?
Tsao didn’t find anything at first. Even pinning down how to approach the problem was tricky because, technically, everything has some temporal quality to it. He examined the neural activity in the lateral entorhinal cortex of rats as they foraged for food in an enclosure, but he couldn’t make heads or tails of what the data showed. No distinctive time signal seemed to emerge.
Tsao tabled the work, returned to school and for years left the data alone. Later, as a graduate student in the Moser lab, he decided to revisit it, this time trying a statistical analysis of cortical neurons at a population level. That’s when he saw it: a firing pattern that, to him, looked a lot like time.
He, the Mosers and their colleagues set up experiments to test this connection further. In one series of trials, a rat was placed in a box, where it was free to roam and forage for food. The researchers recorded neural activity from the lateral entorhinal cortex and nearby brain regions. After a few minutes, they took the rat out of the box and allowed it to rest, then put it back in. They did this 12 times over about an hour and a half, alternating the colors of the walls (which could be black or white) between trials.
What looked like time-related neural behavior arose mainly in the lateral entorhinal cortex. The firing rates of those neurons abruptly spiked when the rat entered the box. As the seconds and then minutes passed, the activity of the neurons decreased at varying rates. That activity ramped up again at the start of the next trial, when the rat reentered the box. Meanwhile, in some cells, activity declined not only during each trial but throughout the entire experiment; in other cells, it increased throughout.
Based on the combination of these patterns, the researchers—and presumably the rats—could tell the different trials apart (tracing the signals back to certain sessions in the box, as if they were timestamps) and arrange them in order. Hundreds of neurons seemed to be working together to keep track of the order of the trials, and the length of each one.
“You get activity patterns that are not simply bridging delays to hold on to information but are parsing the episodic structure of experiences,” said Matthew Shapiro, a neuroscientist at Albany Medical College in New York who was not involved in the study.
The rats seemed to be using these “events”—changes in context—to get a sense of how much time had gone by. The researchers suspected that the signal might therefore look very different when the experiences weren’t so clearly divided into separate episodes. So they had rats run around a figure-eight track in a series of trials, sometimes in one direction and sometimes the other. During this repetitive task, the lateral entorhinal cortex’s time signals overlapped, likely indicating that the rats couldn’t distinguish one trial from another: They blended together in time. The neurons did, however, seem to be tracking the passage of time within single laps, where enough change occurred from one moment to the next.
Tsao and his colleagues were excited because, they posited, they had begun to tease out a mechanism behind subjective time in the brain, one that allowed memories to be distinctly tagged. “It shows how our perception of time is so elastic,” Shapiro said. “A second can last forever. Days can vanish. It’s this coding by parsing episodes that, to me, makes a very neat explanation for the way we see time. We’re processing things that happen in sequences, and what happens in those sequences can determine the subjective estimate for how much time passes.” The researchers now want to learn just how that happens.
Howard’s mathematics could help with that. When he heard about Tsao’s results, which were presented at a conference in 2017 and published in Nature last August, he was ecstatic: The different rates of decay Tsao had observed in the neural activity were exactly what his theory had predicted should happen in the brain’s intermediate representation of experience. “It looked like a Laplace transform of time,” Howard said—the piece of his and Shankar’s model that had been missing from empirical work.
“It was sort of weird,” Howard said. “We had these equations up on the board for the Laplace transform and the inverse around the same time people were discovering time cells. So we spent the last 10 years seeing the inverse, but we hadn’t seen the actual transform. … Now we’ve got it. I’m pretty stoked.”
“It was exciting,” said Kareem Zaghloul, a neurosurgeon and researcher at the National Institutes of Health in Maryland, “because the data they showed was very consistent with [Howard’s] ideas.” (In work published last month, Zaghloul and his team showed how changes in neural states in the human temporal lobe linked directly to people’s performance on a memory task.)
“There was a nonzero probability that all the work my colleagues and students and I had done was just imaginary. That it was about some set of equations that didn’t exist anywhere in the brain or in the world,” Howard added. “Seeing it there, in the data from someone else’s lab — that was a good day.”
Building Timelines of Past and Future
If Howard’s model is true, then it tells us how we create and maintain a timeline of the past—what he describes as a “trailing comet’s tail” that extends behind us as we go about our lives, getting blurrier and more compressed as it recedes into the past. That timeline could be of use not just to episodic memory in the hippocampus, but to working memory in the prefrontal cortex and conditioning responses in the striatum. These “can be understood as different operations working on the same form of temporal history,” Howard said. Even though the neural mechanisms that allow us to remember an event like our first day of school are different than those that allow us to remember a fact like a phone number or a skill like how to ride a bike, they might rely on this common foundation.
The discovery of time cells in those brain regions (“When you go looking for them, you see them everywhere,” according to Howard) seems to support the idea. So have recent findings—soon to be published by Howard, Elizabeth Buffalo at the University of Washington and other collaborators—that monkeys viewing a series of images show the same kind of temporal activity in their entorhinal cortex that Tsao observed in rats. “It’s exactly what you’d expect: the time since the image was presented,” Howard said.
He suspects that record serves not just memory but cognition as a whole. The same mathematics, he proposes, can help us understand our sense of the future, too: It becomes a matter of translating the functions involved. And that might very well help us make sense of timekeeping as it’s involved in the prediction of events to come (something that itself is based on knowledge obtained from past experiences).
Howard has also started to show that the same equations that the brain could use to represent time could also be applied to space, numerosity (our sense of numbers) and decision-making based on collected evidence — really, to any variable that can be put into the language of these equations. “For me, what’s appealing is that you’ve sort of built a neural currency for thinking,” Howard said. “If you can write out the state of the brain … what tens of millions of neurons are doing … as equations and transformations of equations, that’s thinking.”
He and his colleagues have been working on extending the theory to other domains of cognition. One day, such cognitive models could even lead to a new kind of artificial intelligence built on a different mathematical foundation than that of today’s deep learning methods. Only last month, scientists built a novel neural network model of time perception, which was based solely on measuring and reacting to changes in a visual scene. (The approach, however, focused on the sensory input part of the picture: what was happening on the surface, and not deep down in the memory-related brain regions that Tsao and Howard study.)
But before any application to AI is possible, scientists need to ascertain how the brain itself is achieving this. Tsao acknowledges that there’s still a lot to figure out, including what drives the lateral entorhinal cortex to do what it’s doing and what specifically allows memories to get tagged. But Howard’s theories offer tangible predictions that could help researchers carve out new paths toward answers.
Of course, Howard’s model of how the brain represents time isn’t the only idea out there. Some researchers, for instance, posit chains of neurons, linked by synapses, that fire sequentially. Or it could turn out that a different kind of transform, and not the Laplace transform, is at play.
Those possibilities do not dampen Howard’s enthusiasm. “This could all still be wrong,” he said. “But we’re excited and working hard.”