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Water and the Brain: Neuroscience and Blue Mind

The brain and the ocean are profoundly complex and subtle realms for investigation. We struggle to identify the approaches that yield deeper understanding. We’re drawn to their mysteries—and the inherent rhythms that define both—and we strive to find a language to describe them.

—DR. DAVID POEPPEL, PROFESSOR OF PSYCHOLOGY AND NEURAL SCIENCE, NEW YORK UNIVERSITY

Surfer João De Macedo waits on his board, three hundred feet or so from the beach. He’s relaxed yet alert, scanning the water for indications of the next wave. As he spots a smooth swell pattern that indicates a potentially rideable wave, anticipation releases another wave—of neurochemicals cascading throughout his brain and body. The water rises up in front of him, and he’s instinctively standing on his board, using the brain that has been shaped by the experience of the thousands of waves he’s ridden before to look for the perfect entry point. Dopamine explodes over his neurons as he drops into the pocket. He’s enclosed in a watery tunnel of cool, blue-green light, surrounded by the smell and the sound of the wave, feeling the air rushing past him as he makes minute physical adjustments to keep the ride going for as long as possible. Feel-good neurotransmitters—adrenaline, dopamine, endorphins—rise in waves inside his brain and body. He shoots out of the pocket just as the wave crest crashes behind him. He smiles, maybe even laughs. Then he turns back over the top of the wave, drops down onto his board, and starts to paddle out as he looks for the next wave—and the next dopamine rush.

The smile on João’s face wordlessly declares the thrill and pleasure he’s just experienced. Via such facial expressions, and through poetry, literature, and testimonies of all sorts, we humans have been self-reporting the effects of water on our minds and bodies. But it’s only in the past two decades or so1 that scientists have been able to examine what’s going on in the human brain when we encounter different aspects of our world and ourselves. Today neuroscience is exploding with studies that track, in infinitesimal detail, what our brains are doing when we are eating, drinking, sleeping, working, texting, kissing, exercising, creating, problem solving, playing.… If humans do it, it would seem that someone is studying it, to find out exactly which circuits are firing and which neurotransmitters are cascading during that particular activity.

Some refer to this new era of the brain as the “Golden Age of Neuroscience.” But despite all the studies that make for great news copy (and the colorful brain scans that make us more likely to accept the conclusions they accompany),² any scientist worth his or her salt will admit that we are just dipping our collective toes into understanding the processes of the human brain. Back in 2011, eminent neuroscientist V. S. Ramachandran stated that our current understanding of the brain “approximates to what we knew about chemistry in the 19th century—in short, not much.”3 That remains the case.

However, even that “not much” is far more than we have understood for two thousand years about the way the mind works. Undoubtedly many of the conclusions and studies done today will be proven inaccurate ten, twenty, fifty years from now. That’s science: you carefully observe the world around you, state a hypothesis, develop experiments or studies to prove or disprove your premise, use the technology you have available to you at the moment, and then develop conclusions based on the results. What’s truly exciting about this latest round of investigation, however, is that it endeavors to discover the physiological, chemical, and structural processes that underlie humanity’s very subjective experience of the world. What happens in your brain when you see the face of a loved one or gaze out over the rail of a boat? Which circuits are active when you’re at your most creative, or when an addict is seeking a fix? Does the environment physically shape our brains just as our brain filters, configures, and interprets our moment-to-moment perceptions of that environment? And is there a way we can use this understanding of how our brains work to help us be happier, more creative, more loving, and less stressed?

As I mentioned earlier, while neuroscience is studying an incredibly broad range of human behaviors and emotions, in every setting possible, for some reason our interaction with water seems to be left out. (Try this: go to your nearest bookstore or library and scan the indexes of any of the popular books on neuroscience, psychology, or self-help for topics related to water.) So, in this chapter we are going to start the conversation at the beginning by examining several major aspects of your brain on water. But first, let’s talk about the fundamentals of just how we study the brain.

How We Study the Brain

Everything we do, every thought we’ve ever had, is produced by the human brain. But exactly how it operates remains one of the biggest unsolved mysteries, and it seems the more we probe its secrets, the more surprises we find.

—NEIL DEGRASSE TYSON, ASTROPHYSICIST

Humans have always been infinitely curious about what goes on inside our skulls. In the late nineteenth and early twentieth centuries, scientists and theorists such as Sigmund Freud and William James described how we think and feel based upon the subjective experiences reported by their patients, combined with their clinical observation of human behavior. (Even today, self-reporting of subjective experience is vital in studying the ways our brains work.) Medical doctors, too, were a rich source of information; in fact, prior to the twentieth century, our information on the brain mostly arose from studying what happened when it malfunctioned due to disease or injury. But it’s one thing to theorize about how brains function normally by seeing what happens when they don’t function properly, and another to actually observe the brain in action when it is thinking, sleeping, feeling, creating, or interacting with the outside world. How do we go about understanding the normal human brain?

Cue the development of noninvasive techniques and devices that allowed scientists to track the workings of the normal human brain. The earliest of these devices was the electroencephalography (EEG) machine. Based on the understanding that living tissue has electrical properties, the first use of EEG on human beings occurred in 1924. Over the course of the twentieth century EEG recordings were used as diagnostic tools as well as in research.

An EEG works because neurons in the brain generate small electrical charges when they become active, and when groups of neurons fire together, they create an electrical “wave” that can be detected and recorded. Data are gathered by placing the EEG’s electrodes (often embedded in a cap, net, or band) on the head and monitoring the peaks and valleys of electricity generated in the brain. (The signal is amplified for the purposes of analysis.) EEGs can track brain activity by location, showing which side of the brain is involved in a “cognitive event”; by type of brain wave (alpha, beta, theta, and delta, each corresponding to a distinct frequency range and corresponding level of brain activity, making EEGs vital in sleep studies); and by abnormal activity (as is seen in epilepsy, a disease that creates patterns of spikes in electrical activity in the brain). Sophisticated EEG devices can noninvasively sample sixty-eight channels of data every four milliseconds or less, and record electrical events as brief as one millisecond. 4

Cognitive neuroscientists have found that the EEG can be an extremely useful tool in tracking brain functions like attention, emotional responses, how we retain information, and so on.⁵ And in an exciting development for those of us who do research outside of a laboratory setting, EEG readers are becoming smaller and more portable—some even resembling the kind of headset a computer gamer might use. However, EEG readings indicate electrical activity only at a shallow depth, and many critical functions occur much deeper in the brain. To explore those, other tools were needed. In the last fifty years MRI (good old-fashioned magnetic resonance imaging), positron emission tomography (PET), and single-photon emission computed tomography (SPECT) have been used to produce images of activity deep in the brain by tracking changes in blood flow or metabolic activity.6 But whereas MRI machines rely solely on magnetic fields and radio waves, PET and SPECT scans use injected radioactive isotopes, which limits their usefulness. A new answer arrived in the 1990s with functional magnetic resonance imaging, or fMRI.

Different areas of the brain become active at different times, depending on the tasks required. More activity requires more oxygen, causing increased blood flow to those areas of the brain. Like their older siblings, fMRI machines use powerful magnetic fields to align the protons in the hydrogen atoms in the blood, and then knock them out of alignment with radio waves. An MRI looks for differences in signals from the hydrogen atoms to distinguish between different types of matter. As the protons realign, they send out different signals for oxygenated and deoxygenated blood—and those signals are what the fMRI reads. As a test subject undertakes an activity—squeezing a hand, for example, or looking at a particular picture—fMRI scans measure the ratio of oxygenated to deoxygenated blood, or blood-oxygen-level-dependent (BOLD) contrast, in different areas of the brain at that moment. The machine’s computer then uses a sophisticated algorithm to interpret the data received from the fMRI and represent the contrast ratios in the form of infinitesimal, three-dimensional units called voxels. Different colors are used to indicate the intensity of the energy in that particular area, red being the most intense, purple or black indicating low or no activity. The brighter the color on the scan, the greater the activity in that particular region of the brain, giving rise to the term “lights up” when referring to activated brain regions.

Over the past twenty years fMRI has become the preferred method for measuring brain function, utilized by cognitive scientists, neurologists, neurobiologists, psychologists, neuroeconomists, and others.7 But even though fMRI is one of the best tools we have currently for measuring the brain function (and one of the only tools we have for examining structures deep inside the cranium), it’s important also to acknowledge its limitations. First, fMRIs are based on an indirect indicator of brain function. The functioning of the brain is ultimately chemical and electrical in nature: neurons produce electrical messages that are conveyed from one to the other either through direct contact, synapse to synapse, or via chemical neurotransmitters. This activity requires oxygen, which is provided by blood flow to the active areas of the brain; fMRI scans measure that blood flow, not actual neuronal activity. Thus, while fMRIs can tell us which areas of the brain are active, they cannot reveal the specific activating factors. Second, while fMRIs have excellent spatial resolution, showing the location of brain activity within two to three millimeters, because blood flow is far slower than neuronal activity (with a delay of at least two to five seconds between activation of neurons and increased blood flow to the area), the temporal resolution of an fMRI scan is much longer than the amount of time needed for the majority of perception or other cognitive processes. (In contrast, EEGs have poorer spatial resolution but, as mentioned earlier, can track electrical charges as fast as one millisecond.) There are also issues with differences in fMRI machines and the complex algorithms required to process the data, as well as variation in the size of voxels (which while tiny are far larger than the neurons they represent).

The most important limitation currently for fMRI-based studies of the brain is that they can track responses of subjects only in a lab rather than in the environments where a particular cognitive activity would logically take place. Imagine you were one of those undergraduates who volunteered to be a subject in a study that used fMRI scans.8 You would be asked to report to a lab and told that you should leave anything metal at home because of the powerful magnets in the machine. A friend who has previously had an fMRI tells you to dress warmly, as the temperature in the facility is kept cold for the equipment. Once you enter the lab and check in, you’re ushered into the room with the scanner: a large, doughnut-shaped machine with a hole in the middle just big enough for a human body. (If you’re at all claustrophobic, you’re uncomfortable merely looking at the small size of the opening.) The technician instructs you to lie down on a plastic bedlike slab with your head pointing toward the opening in the doughnut. She tells you that the bed will move forward so your head and shoulders are inside the scanner. There will be a mirror above you that will allow you to see a computer screen with instructions for tasks to perform while the scanner takes pictures of the activity in your brain. She gives you earplugs and explains that the scanner is very noisy, and points out a buzzer you can push if at any point you become too uncomfortable to continue. She puts a pillow under your head and one on each side of it to keep it stationary. “Stay as still as you can while the scan is in progress,” she requests, and then she slides your head and shoulders into the scanner.

So far, the process is equivalent to an MRI. But instead of just lying in the tube, you look up at the mirror and, as the thump-thump-thump sound of the fMRI commences, you can see the computer screen above you come to life. You follow the instructions and push buttons on the pad in your hand in response to the pictures flashing in front of your eyes. (In the future your fingers may get a rest thanks to eye-tracking technology.) The tasks keep you busy enough that you notice the small size of the space you’re inhabiting only a couple of times (which is good, because you came very close to pressing the buzzer that would let the technician know you were ready to quit). At the end of the test the computer screen goes blank and the noise stops—finally. The tech rolls you out of the machine, thanks you for your time, and asks you to schedule another session for the following week. You’re cold, your bladder is full, and you have the beginnings of a headache from the noise of the scanner—but it’s all for science, right? So you agree to come back.

An fMRI can reveal a great deal about the functioning of the brain, but it can tell us far less about the ways the human brain interacts with the real world. It can scan us while we look at pictures of people who are happy or sad or fearful or angry, but it cannot track our actual interactions with people on the street. It can reveal brain activity when we are calculating mathematical problems or choosing between this food or that beverage, but it cannot yet scan us while we enjoy that crisp, red apple picked straight from the tree or that glass of chardonnay in front of a roaring fireplace—let alone snorkeling above a coral reef. As cognitive neuroscientist and expert on auditory cognition, speech perception, and language comprehension Dr. David Poeppel notes, “Most of the mapping of the brain since the 1990s has been done using fMRI, and the goal is to make some kind of cartography. That’s laudable, but having a map is not an explanation. Having a map is just the beginning of the problem.” So while EEG and fMRI may be our best current tools to study the brain, and their integrated use a true “best of both worlds” solution, scientists like me, whose interests lie with areas that can’t be tested by a static machine in a sterile lab, are looking ahead to new techniques: diffusion tensor imaging, or DTI, which uses the diffusion of water through the brain to track neuronal axon bundles (the “cables” that connect regions) throughout the brain’s white matter, thereby showing how information travels through the brain;9 optogenetics, in which light-sensitive genes can be inserted into neurons to activate or silence them in an instant, allowing researchers to determine a particular neuron’s function;¹⁰ even wearable fNIRS (functional near-infrared spectroscopy) headgear¹¹ that will allow scientists to take readings of people in actual situations and environments.

Still, when it comes to understanding the human brain on water today, we can look at several specific streams of valuable information. First, we start with self-reported experience: How do people feel when they are around water? What effects do they notice? Second, we can take studies that have been done about the cognitive effects of nature as a whole and ask whether the response to water is any different. Third, we can look at the wide range of discovery in cognitive neuroscience, neurobiology, environmental psychology, and neurochemistry, and ask, “Does this apply to the brain on water?”

But we’ll start with a very basic question that’s actually not so basic at all: what exactly does the brain do?

What Does the Brain Do?

It’s a metaphor for how the brain is organized.

—RAY KURZWEIL, AUTHOR, INVENTOR, FUTURIST, WHEN ASKED WHY HE LOVES THE OCEAN

The three-pound mass of fat and protein that sits at the top of the spinal cord is not only mostly water, but itself rests in a kind of “water”: clear, colorless cerebrospinal fluid—composed of living cells (including immune cells that eliminate infectious pathogens from the nervous system), glucose, protein, lactate, minerals, and water—that cushions the brain from injury, maintains pressure in the cranium at a constant level, and provides enough buoyancy to reduce the brain’s effective weight from 1,400 grams to between 25 and 50 grams (thus preventing it from putting too much pressure on its lower levels and cutting off its blood supply).12 By weight, the brain is the biggest consumer of the body’s energy, using approximately 20 to 25 percent of its oxygen and 60 percent of its glucose for communication between neurons and cell-health maintenance.¹³ It contains approximately 1.1 trillion cells, of which anywhere from 85 to 100 billion¹⁴ are neurons (what we call “gray matter”), and most of the rest are axons and glia (“white matter”). The glia perform metabolic support functions such as wrapping the conducting axons in myelin (a whitish protein and lipid sheath for nerves) and recycling neurotransmitters. But the anatomy doesn’t really tell us much about what the brain actually does.

When it comes to interpreting those vast complexities of the human brain, Howard Fields of the University of California, San Francisco, is an excellent guide. Gray-haired and grandfatherly, with an infectious smile, he’s not only a world-class researcher but also a brilliant explainer. While major new discoveries about neurons are made almost every year, Fields told me, the best description of their purpose is as encoders of perception and action. Neuronal cell bodies, he said, are electrochemical, digital on-off switches connected by their axonal “wires” in an intricate network inside your head. There are billions of neurons in the human brain and each one can connect with tens of thousands of others, making trillions of connections. By interconnecting, groups of neurons create neural networks that produce every conscious and unconscious impulse, response, or thought you may have: from your ability to sense an itch (and scratch your nose in response), to the “ordinary and exceptional mental activities of attending, perceiving, remembering, feeling, and reasoning.”15 They also trigger the cascades of neurochemicals that mediate our emotions and behaviors in response to stress. By tracking different neural networks in different individuals, neuroscientists can create topographic maps of the brain, although this mapping can be exceedingly difficult, as there are often multiple networks performing different parts of the same function—for instance, the network responsible for the hand bringing food to your mouth is different from the network that directs the more subtle and delicate finger movements used when you hold a pen and write.¹⁶ The complexity of these networks is hinted at in sheer quantity—our neuron count exceeds the closest primate’s by an order of magnitude—but in the end it’s the quality of cognition and dexterity that most amazes.¹⁷

How can the brain make sense of the vast “storm” of perceptions and other stimuli that are flooding our senses every moment? And ultimately, what was the brain slated to do, based upon evolution? According to John Medina, the primary purpose of the human brain is to “(1) solve problems (2) related to surviving (3) in an unstable outdoor environment, and (4) to do so in nearly constant motion.”18 This purpose required the brain to constantly grow and adapt to the challenges humanity encountered in an ever-changing and dangerous world. Through the millennia the human brain evolved in fits and starts, with cognitive functions added and pruned based upon their survival benefits. (Every brain still evolves in the same way, gaining certain cognitive functions from birth, and having others eliminated for efficiency through the years.)¹⁹ What resulted over countless centuries was a brain structure with a flexible architecture, neuroplasticity, and, ultimately, neural networks that were able to acquire the basic building blocks of sight, hearing, smell, and sound, which in turn evolved into such higher-level functions as writing, speech, art, and music.²⁰

Actually, my using “ultimately” above isn’t quite accurate, since in theory while there are physical limits, there are no final endpoints to evolutionary adaptation. If we’re around a million years from now, who knows what we’ll look like and be able to do? But undoubtedly for most of us the factors that create evolutionary advantages or disadvantages differ from what they were a few hundred thousand years ago. It doesn’t take a Ph.D. to recognize that in addition to the environments in which we find ourselves, we are molded by the mental processes going on inside us and our interactions with other people. Indeed, at every moment we are being inundated with input from several sources: the thoughts streaming through our heads; the bodily sensations that rarely attract our attention (unless they demand it due to pain or pleasure); the specific perceptual and neurochemical torrent produced when another human being enters our focus; and the seemingly overwhelming, never-ending streams of stimuli that arrive from every aspect of the world around us.

How in the world can the brain make sense of all this input? How does it separate the signals that are necessary for survival from all of the other perceptual “noise”? It does so by becoming expert in pattern recognition and prediction. “The human brain is an amazing pattern-detecting machine,” writes psychologist David Pizarro. “We possess a variety of mechanisms that allow us to uncover hidden relationships between objects, events, and people. Without these, the sea of data hitting our senses would surely appear random and chaotic.”21 Consciously—but primarily unconsciously—we scan all of the incoming perceptual data and match it with what we have experienced in the past.²² The brain focuses on what it deems important (either because it matches previous patterns, or, more often, because it does not match what is expected and could possibly be dangerous). It interprets what that information means based on prior experience, and then predicts the consequences of what the information means. The processes of the unconscious mind, unlike the conscious “free decisions,” occur automatically and are not available to introspection, discussion, approval, or real-time modification.

These predictions often happen below the level of, and much faster than, conscious thought.²³ As David Eagleman, a neuroscientist at Baylor University’s College of Medicine, writes in Incognito: The Secret Lives of the Brain, “billions of specialized mechanisms operate below the radar—some collecting sensory data, some sending out motor programs, and the majority doing the main tasks of the neural workforce: combining information, making predictions about what is coming next, making decisions about what to do now.”24 It takes 450 milliseconds for a baseball to reach home plate once it’s released from the pitcher’s hand. As it zips through those sixty feet of airspace, a tremendous amount of data must get crunched by the batter. Foremost, the swing/no-swing decision must be made, not to mention decisions about bat speed and angle, real-time adjustments related to microclimates, and contemplations of the movement of the rest of the players on the field. Considering that it takes about 200 milliseconds to conclude whether a player should swing his bat, there’s precious little time to consciously bring one’s full knowledge and experience to bear on a proper analysis of the situation. To even consider those 200 milliseconds “time” at all is generous. Yet since 1901 Major League Baseball’s batters have made favorable decisions better than one out of four times they’ve taken an at bat. Those faring better often take their teams to the playoffs and on to the World Series championship game.

Given the challenge of hitting a 95-mile-per-hour fastball, there’s effectively no possibility that sort of average is the result of chance, so clearly some sort of cognition is going on. But how? Once the brain has taken in and analyzed data, it then must decide what to do—whether some kind of action is required. Yet how much data can one receive in a matter of milliseconds? To a great extent, this entire process is based upon trial and error. Our brains make a kind of high-speed cost-benefit computation before we take any action, and then revise that computation based on the outcome. Familiar situations reinforce current neural pathways; but every new bit of data, every new circumstance, every mistake and new action, forces the brain to remodel itself, if only slightly. If you’ve swung a bat tens of thousands of times, you’ve had moments when you are conscious about adjustments you’re making, such as when the team batting coach offers instruction, and are unconscious about the tens of thousands of times your deeper neural networks have absorbed those millisecond experiences. At a certain point, reliance on your conscious mind can become a disadvantage: think too much, and suddenly you’ve lost your rhythm and the ball misses the hole, the shot clanks off the rim, you play the wrong note—and you strike out.

Throughout our lives, the brain is literally changing itself, creating networks of neurons that accomplish needed functions efficiently.25 As Michael Merzenich, the “father” of neuroplasticity, states, “The cerebral cortex… is actually selectively refining its processing capacities to fit each task at hand.” This is an incredibly dynamic process, where gray matter volume increases in regions where more neuronal activity occurs.²⁶ It is also a competitive process in which existing networks that are no longer being used become weaker (as anyone who has learned another language and then attempted to take it up again years later knows).

According to Merzenich, neuroplasticity is essentially bimodal: it strengthens neural networks for the things we pay attention to, and weakens the areas we use the least. More complex skills, such as playing a musical instrument or driving a stick-shift car, bring together different neural networks throughout the brain. And even more intriguingly, abilities lost through injury, as in a stroke, can be regained as the brain rewires itself and redirects neural function to new pathways.27

While there are specific types of neural networks that most brains have in common, each person’s brain maps are unique.²⁸ (Tracing these neural networks is the next frontier of the Connectome Project, an effort funded by NIH and spearheaded by a consortium including Washington University, University of Minnesota, Oxford University, and others to map the connections in the human brain in a manner similar to that of the successful Human Genome Project of the 1990s, which mapped human DNA. In this case scientists use brain imaging and a new technique called optogenetics, involving the insertion of special molecules into the neurons of the brain that allow their function to be switched on and off by light.) Importantly, when it comes to Blue Mind, there are neural networks that are shaped by your interaction with your environment—from the time your brain starts to form in the environment of the womb, until you close your eyes on your deathbed. And because of neuroplasticity, we have the opportunity to reshape our brains throughout our lifetimes by changing the input and the environment we choose.

Understanding the power of Blue Mind requires taking a journey from a swimming pool to a cancer ward, from the Australian coast to the inner city, from the corner of a five-million-dollar laboratory to the corner office of a five-billion-dollar company. But, like all journeys, it makes sense to start at home—the home in our head and the home with our bed.