Your Brain at Work

When Apple fanatics lined up to get the new iPhone in 2011, the New York Times published an op-ed titled “You Love Your iPhone. Literally.” It described an unpublished experiment in which the author scanned the brains of 16 people as they heard and watched audio and video of ringing or vibrating iPhones. The scans showed activity in the insular cortex—an area that activates when someone experiences love. “Subjects’ brains responded...as they would respond to the presence or proximity of a girlfriend, boyfriend, or family member,” the author wrote. “They loved their iPhones.”

Dozens of neuroscientists cosigned a letter to the Times condemning the article, noting that one-third of all neuroimaging studies reveal activity in the insular cortex. It’s active when people sense temperature changes or even just breathe. In fact, in 2007 the Times itself had published an op-ed showing that the same area of the brain was engaged when subjects felt the opposite of love. Titled “This Is Your Brain on Politics,” the article linked activity in the insular cortex to disgust and asserted that it was particularly strong in men who saw the term “Republican.” Scientists wrote a letter protesting that article, too.

The two op-eds are examples of something scientists call “brain porn”: mainstream media reports that vastly oversimplify neuroscience research—and fuel a burgeoning industry of neuroconsultants who suggest that they can unlock the secrets of leadership and marketing from the brain. Though these articles’ conclusions are dubious, most of them are based on data from functional magnetic resonance imaging (fMRI) scans, a primary tool of neuroscience. The technology allows us to peer into brains as they work, to see thinking as regions of the brain become more or less active.

These powerful images offer temptingly simple explanations for complex phenomena. But the problem is, fMRI doesn’t necessarily show causation. What’s more, thinking and behavior don’t map onto brain regions one-to-one. You can’t scan someone’s brain while he watches commercials and tell if he prefers Coke or Pepsi. You can’t scan two CEOs’ brains and tell which person is the better leader. Insula activity alone doesn’t prove that you feel about your phone the way you feel about your mother.

To truly understand how neurological processes affect management, leadership, and marketing, we must separate fact from fiction, resist facile narratives, and establish a more sophisticated view of brain science.

And that’s exactly what’s beginning to happen. Because of a confluence of factors—technological advances in fMRI, newly applied statistical techniques, and even President Obama’s announcement of a brain-mapping initiative—neuroscientists are adopting a new and better framework for their discipline. It shifts the focus from studying the activation of brain regions to learning how networks of brain regions activate in concurrent patterns. It’s like going from using video from a single surveillance camera at a crime scene to do detective work to using footage from multiple cameras positioned in different locations.

The new tools and approaches have already produced new insights into the biology of our minds and deepened our understanding of concepts crucial to managers, including:

• how to enable creative thinking

• how to structure rewards

• the role of emotion in decision making

• the opportunities and pitfalls of multitasking

The network-based view isn’t nearly as sexy as the current popular view of neuroscience. Good neuroscience based on the network view is more complex. Messier. But good science is messy.

We fully expect other neuroscientists to contest the claims we make here; the science is so nascent that much is still under debate, and new research is updating what we know about the brain almost every second. Nevertheless, we feel confident about giving an “interim report” on the neuroscientific findings of the past 15 years that now have considerable empirical support.

As a former colleague of ours says, “Neuroscience has taught us surprisingly little about how the mind works, but it’s taught us a few things extremely well.” Those few things are what this article is about. Brain scientists have now identified as many as 15 brain networks and subnetworks. We’ll present the four that have the most consistent backing of neuroscientists: the default, reward, affect,and control networks. They’re widely accepted as core neural networks, and their roles are starting to be well understood—along with their implications for managers.

Neuroscientists have discovered as many as 15 neural networks and subnetworks. The four described below, along with their implications for knowledge work, are considered core and are the best understood.

The Default Network

Activates: When people are awake but not focused on external stimuli or any specific goal.

What it controls: Introspective thought and the ability to envision the past, the future, or alternative realities.

Crucial for understanding: Creative thinking and breakthrough innovation.

The Reward Network

Activates: In response to stimuli that induce enjoyment—such as food and water, money, and praise.

What it controls: Perceptions of pleasure and displeasure.

Crucial for understanding: Motivation and incentives.

The Affect Network

Activates: When people experience emotions.

What it controls: Autonomic and endocrine responses (alterations in blood pressure, heart rate, body temperature) that the brain interprets as feelings.

Crucial for understanding: Hunches and gut instincts, and the role that emotions play in decision making.

The Control Network

Activates: When people weigh long-term consequences, check their impulses, and selectively focus their attention.

What it controls: People’s ability to align their behavior with their goals.

Crucial for understanding: The benefits and risks of multitasking and how to set and manage priorities.

The Default Network: How to Unlock Breakthrough Innovation

One of the most exciting discoveries in neuroscience in the past decade is that the brain is never truly at rest. During wakeful periods when your brain is not focused on any particular thought (when your mind is wandering or you’re just plain “zoning out”), a distinct network of brain regions still fires up. We call it the “default” network. It’s also sometimes referred to as the “task negative” network because it’s engaged when people aren’t concentrating on a task. The mere discovery of this network has been groundbreaking: We now know that the brain spends considerable time processing internalized existing knowledge, not just new information from the five senses.

The default network is also responsible for one of our most prized abilities: transcendence. The capacity to envision what it’s like to be in a different place, a different time, a different person’s head, or a different world altogether is unique to humans and most potent when the default network is highly engaged. During transcendence, people’s brains “detach” themselves from the external environment, meaning they stop processing external stimuli.

This discovery leads us to believe that having unfocused free time is an important (and underutilized) factor in breakthrough innovations. That notion obviously calls to mind the “20% time” policy at Google, under which the company’s engineers get a day a week to work on whatever they want. Other companies have followed suit: Maddock Douglas, a marketing firm, gives employees 100 to 200 hours a year to work on anything that interests them. BrightHouse, a consulting firm, offers its staff five “Your Days” a year to reflect and simply free-associate. Intuit has launched a 10% program much like Google’s. Twitter holds Hack Week, during which employees experiment and develop ideas away from their day-to-day duties. And at the software firm Atlassian, developers get “ShipIt Days,” in which they have 24 hours to work on projects that intrigue them but, like an express shipper, have to deliver something overnight.

No doubt such programs have their benefits; unassigned time for creativity has long been known to enhance workers’ sense of self-sufficiency, happiness, and motivation. But discoveries about the default network make us think these programs probably don’t go far enough. For one thing, employees’ time in many of the programs is still not exactly “free.” They’re designed so that people will seek solutions to problems, which means that their default networks don’t detach from external stimuli. They are still rooted in immediate reality.

Most of these programs also focus on the quantity of time workers get. A better approach would be to focus on the quality of detachment created. Companies could turn off employees’ e-mail and calendars; take away their phones; send them on a trip, away from all offices and other staff members; and take all other job duties off their plates. Meditation is also an effective tool for detaching. The idea is to allow someone’s default network to engage in processes like simulating another person’s thoughts, envisioning another time and place, or free-associating without interruption from other networks that are processing input from the external world.

You may have experienced the power of the default network in a “Eureka!” moment or when you’ve thought of a solution after you walked away from a problem. But embracing detachment as a work policy is difficult, because it’s extremely hard to quantify the results of practicing it (which also may explain why the free-time programs that do exist are bound by parameters like time frame, percentage of time, and delivery deadline). Nevertheless, you should experiment with total detachment, because it’s a better way to generate breakthrough ideas.

The Reward Network: How to Structure Incentives

As early as the turn of the 20th century, scientists were speculating that we could create a “hedonometer” that would measure the amount of pleasure or displeasure we feel in response to any stimulus. Neuroscience now shows that the reward network is, in some ways, that hedonometer. It reliably activates in response to things that evoke enjoyment and deactivates in response to things that reduce enjoyment.

In case you’re thinking that we can scan people’s brains and see if Bud Light or Miller Lite produces a higher reading on the hedonometer, it’s not that simple. Pleasure and rewards are contextual and can be altered for any given stimulus by the presence of other stimuli. You may register higher for Bud Light because you think you’ll get free beer if you choose that. Or maybe Miller Lite scores lower because you don’t like it from a can, but you would have a different response to a bottle. Or maybe you weren’t in the mood for beer when the test was done. Also, we’ll see when we get to the control network later why this hedonometer is not the final arbiter of rewards in our minds.

Using electrodes and other invasive techniques, scientists identified what appeared to be neural reward networks in animals decades ago. Their reward systems activated when they were given food, drink, or other items with clear survival value. But it wasn’t until the late 20th and early 21st centuries that neuroscientists and neuroeconomists demonstrated that in humans this network is sensitive to secondary rewards not necessary for physical survival. Most notably, to money.

We’ve also documented how this hedonometer responds to immaterial rewards. We know, for example, that those can be as pleasurable as money to people. That idea is consistent with a 2009 McKinsey survey of executives and managers who reported nonfinancial incentives to be as effective as financial ones in motivating employees—and at times more effective.

What’s more, we can now identify the nonmonetary rewards that are likely to inspire individuals. Some aren’t surprising, like status and social approval. But others are not as predictable. For example, fairness. The researchers Jamil Zaki of Stanford and Jason Mitchell of Harvard have shown that when people are allowed to divide up small amounts of money between themselves and others, the reward network responds much more when they make generous, equitable choices. People are demotivated—their hedonometers go lower, if you will—by environments that promote inequity. Even people who are part of the privileged few are demotivated by inequitable systems. A fair environment is a reward to people regardless of their standing.

This finding suggests that companies that maintain a reasonable level of internal pay equity would do well to publicize that information among employees. Conversely, widespread knowledge of skyrocketing executive pay is sure to turn off the reward network. But it’s not just fair pay that matters. When people feel left out of strategy sessions despite being qualified to participate, for example, they become demotivated. The withholding of information also creates an inequitable environment between those in the know and those not in the know—which is why transparency is so important.

Another unexpected trigger of the reward network is the anticipation of learning. Curiosity is literally its own reward. In one study by Colin Camerer and his colleagues at the California Institute of Technology, participants read trivia questions and rated how curious they were about the answers. The stronger their desire to find out, the greater the activation in the reward network before they received an answer.

Goals are good, of course, but it’s important to note that the reward network seems to respond more positively to less stringent ones. Highly specific, challenging goals can actually be harmful because they curb curiosity and inhibit flexible thinking.

Look at what happened at General Motors in the early 2000s, when the company set the exceedingly specific objective of capturing 29% of the American car market. Just to reach that number, GM poured inordinate amounts of money into advertising and marketing, rather than funding innovation. Overly precise goals often engender myopic responses like that, which endanger companies’ long-term health. Indeed, this target led GM to the brink of bankruptcy. A more flexible goal—such as obtaining top ratings on measures of innovation—would have helped GM realize multiple aims.

Additionally, neuroscience indicates that goals may not always be necessary in motivation. It shows, for instance, that the intrinsically interesting work of solving novel problems turns up the brain’s hedonometer, even before solutions are found or rewards (financial or otherwise) are given out. The work can be as satisfying as the reward. GM could have fired up workers’ hedonometers just by giving the staff challenging problems to address rather than dictating what the outcome had to be.

In fact, the reward network’s strong response to immaterial rewards suggests that money is often a more expensive and less efficient incentive. One study by Kou Murayama of UCLA and his former colleagues at the University of Munich actually found that paying people for their performance on a rote task—trying to halt a stopwatch at exactly five seconds—undermined their motivation to perform the task for free, consequently reducing activation in the reward network. Any number of things employers can do “on the cheap”—fostering a culture of fairness and cooperation, offering opportunities for people to engage their curiosity, and providing plenty of social approval—will motivate employees as much if not more.

The Affect Network: How to Use Gut Instinct

In decision making, does intuition outperform careful deliberation? The debate is ongoing. Gauging how much trust to place in hunches is much easier, however, once you have a basic understanding of where they originate, why the brain generates them, and what function “feelings” serve.

Scholars have converged on an explanation of how the brain produces the emotional responses that we call feelings: Events in the environment trigger physiological changes (alterations in blood pressure, heart rate, body temperature), which the brain then interprets in context. Some events may have intrinsically affective properties (an electric shock is inherently unpleasant) or may have acquired emotional value through repeated association (over time the sound of a favorite colleague’s voice might engender excitement). The affect network produces these feelings and, through its interactions with other brain systems, controls their intensity and identifies their plausible source.

Feelings can be a by-product of thoughts—remembering an impending deadline can produce unease; imagining a good financial report can produce happiness. But feelings can also be activated unconsciously, without your knowing where they originated. A hunch is not some mystical sixth sense. It’s a real neurological response that manifests itself physically.

Here’s how it works: As the brain encounters events, choices, and people, it tags them with emotional significance. When people later have similar experiences, the brain accesses the tags as a shortcut to producing the appropriate feelings—doubt, anxiety, happiness, excitement. Say you tried habanero peppers once, and their heat was painful and ruined your night. Later the sight, smell, or even mention of habanero peppers (or the restaurant where you ate them) will cause the affect network to produce unpleasant feelings that make you avoid them. The important point is that you don’t have to do any rational analysis to decide whether to eat habaneros the next time they’re presented to you.

Physical changes attend these feelings, including increased heart rate, beads of sweat, the production of cortisol and other hormones, flushing of the skin, and gooseflesh. Often these changes occur preconsciously, before we detect them ourselves.

Suppose you see a spider. We used to think you would identify the spider as scary and then feel fear.

What we know now from studying the affect network is that the idea that the spider poses a threatfollows the fear evoked by the sight of the wriggling creature. Feelings inform thoughts, not the other way around.

The brain’s affect network seems to know what’s going on before we consciously recognize it. In one study, healthy subjects and subjects with damage to the brain regions in the affect network were given the Iowa Gambling Task. In it, subjects choose cards from four decks; as each card is drawn, they either win or lose some money. The “bad” decks have cards with high penalties and rewards and lead to a net loss. The “good” decks have cards with low penalties and rewards and lead to a net gain. Healthy individuals sampled cards from each deck 40 to 50 times before realizing that it was more profitable to consistently choose the decks with small rewards and penalties.

However, after only 10 cards had been pulled from each deck, the healthy subjects’ affect networks transmitted a subconscious stress response when the subjects hovered over “bad” decks—long before people consciously identified the decks as problematic. Subjects with damage to the affect network, on the other hand, never had this stress response and continued making poor choices.

But how is it possible that the brain knows things before we do? We’ve discovered that it’s because incoming sensory information is transmitted to the affect network via two routes: the “low road” and the “high road.” The low road is an expressway that bypasses brain areas that support conscious reasoning. The high road is the local road that runs through other brain regions to the affect network.

So, when our feelings about an event don’t match our conscious understanding of it—say we experience pangs of worry about our company’s inability to capture new markets or guilt over a looming ethical crisis while we’re discussing the firm’s current stability with potential investors—the issue could be nothing more than timing. Information traveling via the low road evokes a visceral response before the high road has time to finish processing the information.

At other times, the mismatch reflects a failure of high-road brain regions to identify the cause of the feeling generated by the speedy low road.

Breakthroughs in research on the affect network are teaching us how to deal with dissonant feelings. The Iowa Gambling Task, for example, speaks to the importance of doubt. The stress response the brain produced before players realized it was doubt—a powerful momentary emotion that we tend to shoo away the second it produces a chill or a bead of sweat on the skin. But this emotion can inform our thought process in high-stakes business decisions. When we successfully rationalize away our doubts, overconfidence is all that is left, and it often contributes to poor judgment. We now know, however, that we should try to incorporate these transient feelings into our decision-making process, not push them away.

The more we understand the affect network, the more we recognize the importance of relying on the fleeting intuitions—a flash of discomfort about a risky investment, a positive hunch about a new product in development, or a twinge of fear that one’s company will become outmoded and in need of new strategies—that we experience before our reasoning faculties have caught up.

Leaders tend to push away feelings in making decisions because they think it’s best to be dispassionate. But a mounting body of neurological evidence suggests that emotional impulses should not be ignored. The affect network fast-tracks decision making and helps us process information that may include too many variables.

We’ve learned some of this, incidentally, by examining the behavior of people with damage to their affect networks. Deprived of the biasing function of feelings, they’re forced to decide on all matters, no matter how mundane, by employing a long and involved cost-benefit analysis.

So hunches are extremely useful in helping us bypass complex and laborious analysis. Should we always trust them? Absolutely not. A strategy that promotes blindly following one’s gut discounts the value of reason. And it overlooks important limitations of the affect network. For one, the feelings produced by it are inexact and somewhat blunt. They can be wrongly overpowering, especially negative feelings like fear and anger. It’s easy for people to misidentify the cause of a hunch and to misunderstand its significance. Context is complicated. The brain may ascribe a feeling to a situation that is similar to a previous event but in fact not the same. The embarrassment felt after a poor presentation may lead us to dread the next one, even though we have practiced and are better prepared. A moment’s reflection on how much practice we’ve put in can help us overcome that feeling.

Nonetheless, the neuroscience of emotion shows us that although hunches are fallible, it’s worth exploring them more than we do. Particularly in situations involving risk, negative gut feelings can prevent leaders from making overconfident or overly optimistic decisions. In a world of markets and numbers and data, leaders have so much information that instinct seems immaterial and abstract and therefore hard to use. But hunches are indispensable.

While we could improve, we’re still reasonably adept at following positive hunches. We may sense that a market is a good one to enter even if we don’t have a full suite of data to back it up, and go with our gut. On the other hand, we tend to grossly undervalue negative hunches, especially doubt and anxiety. Leaders naturally try to eliminate both in themselves and in their organizations. These emotions make us look weak and create uncertainty, which markets and workers don’t like. Our inclination is to keep everyone motivated and focused and feeling in control, moving forward.

But such negative feelings are rooted in the same affect network as any other feelings and therefore stem from valuable past experiences. Leaders should pay attention to them and try to understand where they’re coming from. We don’t suggest leaders be guided by doubt and anxiety, but listening to them, evaluating them instead of avoiding them, can generate better outcomes.

The Control Network: How to Create Achievable Goals

Although we can execute many everyday activities on autopilot, we also have a remarkable capacity to override our habits and impulses. We can decide to sit in a different spot at the 1,001st staff meeting even after sitting in the same place for 1,000 meetings prior. If we believe it will help us get a promotion, we can choose to work in a remote and dreary corner of the world away from loved ones. Whereas other animals react to only immediate needs, we can pursue loftier goals—like capturing a larger share of the Latin American market and flying to the moon—even when they conflict with our immediate needs or contradict our past behavior patterns.

The control network is responsible for this flexibility. It aligns our brain activity and our behavior with our goals. Much as a CEO might reallocate a firm’s resources from a failing market to a growth market, the control network shifts blood flow away from brain regions emitting competing or inappropriate signals and toward regions that help us achieve our objectives. CEOs may review and reshuffle resources each budget cycle; the control network does this constantly as our circumstances change and our needs and aspirations evolve.

We’ve purposely arranged this article with the default network first and the control network last, as bookends. Research has shown that they’re essentially countervailing forces: The more engaged the control network is in distributing resources to achieve goals rooted in the real world, the less engaged the default network is in detaching from the real world and imagining alternative realities, and vice versa.

In a sense the control network is tasked with policing all the brain’s other networks. By suppressing the default network, the control network ensures that our minds can anchor themselves in the present moment and won’t wander all the time. By restraining the reward network, it helps us resist the lure of costly indulgences and check the impulse to act on immediate needs ($5 today) at the expense of more-important, long-term objectives ($10 a week from now). By regulating the affect network, it reins in our emotional reactions and ensures that our actions are not dictated solely by fleeting feelings or hunches.

The control network also helps us deal with our many competing goals. In a world of pinging e-mail, buzzing phones, and people bidding for our time, we need the ability to prioritize the most important tasks and shut out all the other distractions.

Of course, it’s not quite that simple. Complete absorption in a current task is as fraught a state of mind as complete daydreaming or impulsiveness. It can prevent us from detecting environmental changes that could help us. The soccer player so intent on getting off a winning shot may not notice a wide-open teammate who could score more easily if he were passed the ball. The player may also fail to realize that time is running out—ignoring an entirely separate and more critical priority because he’s so focused on shooting. It’s a tricky attention-management challenge the control network deals with. On one hand, it needs to prevent distractions from every shiny object thrown in front of us. On the other hand, it needs to let us respond when one of those shiny objects is an opportunity or an important demand.

To pursue these twin objectives concurrently, the control network hedges. It biases the brain to notice and respond to information related to both our current task and other outstanding goals. (Not just any stimuli, only those related to goals.) To keep us agile, the control network aims for the sweet spot: It tilts the scales in favor of actions compatible with our goals but not to such an extent that our resources are overcommitted. This safeguards our flexibility in unpredictable environments, but it also predisposes us to distraction. Not every player sprinting across the field is open for a pass and better positioned for a shot, and we shouldn’t have to look at the clock every few seconds to make sure we have time to shoot.

Recent discoveries about the control network reinforce what the best leaders say about outexecuting the competition through focus: Companies should limit the number of strategic initiatives they undertake to a manageable few. Asking people to pursue numerous goals fragments their attention and makes engaging in any mindful work difficult. With too many objectives to maintain and monitor, the control network spreads its limited resources thin, and we struggle to give enough attention to any of our responsibilities.

Some people believe that juggling multiple projects improves their mental agility, but emerging evidence casts doubt on such assumptions. One recent study by Eyal Ophir, Clifford Nass, and Anthony Wagner revealed that the control networks of individuals who chronically multitasked failed to allocate resources in a way that matched their priorities and showed that these people struggled to filter out irrelevant information. They struggled to not think about the tasks they were not doing. What good is thinking about the call you owe a client or the e-mails and tweets pinging on your phone while you’re discussing corporate strategy with the CFO? Not only are those goals unconnected to your conversation, but the current moment is completely void of opportunities to further their pursuit.

Attesting to the ease with which tasks that we’re not doing hijack our attention, an overwhelming majority of 40 senior executives we recently queried reported that their “off task” moments almost always involve thoughts of unfinished business. We’re blessed with brains that can prioritize unfulfilled goals. But we’re also cursed with them.

E-mails, meetings, texts, tweets, phone calls, news—the unstructured, continuous, fractured nature of modern work is a tremendous burden on the control network and consumes a huge amount of the brain’s energy. The resulting mental fatigue takes its toll in the form of mistakes, shallow thinking, and impaired self-regulation. When overwhelmed, the control network loses the proverbial reins, and our behavior is driven by immediate, situational cues instead of shaped with our priorities in mind. We go on autopilot, and our brains fall back to simply responding to whatever is in front of us, regardless of its importance.

Success as a leader requires, first and foremost, creating just a few clear priorities and gathering the courage to eliminate or outsource less important tasks and goals. Executives must also reset their expectations for what constitutes a viable workload, basing them on a realistic understanding of what their brains can handle. It’s less than what most of us try to accomplish.

An understanding of the control network also should guide our thinking about lean operations. Taking a “lean” approach should not mean saddling too few employees with too many tasks. The more leaders ask their workers to focus on, the worse those employees will perform. Though in the short term it’s cost-effective to keep staffs thin, brain science suggests many modern workers have already been pushed far beyond the point where their goals and tasks are manageable. Their work is already suffering.

After an explosion of articles on neuroimaging research in top journals in the early 2000s (what some scholars have termed neuroscience’s “Wild West”), critics were quick to dub the field “the new phrenology,” a reference to Franz Joseph Gall’s 18th-century pseudoscience, which mapped psychological faculties onto different brain regions. As neuroscience becomes more sophisticated, however, it promises to become a scientifically valid version of phrenology, albeit one with far more complexity and nuance.

Caution in interpretation is required if we’re to overcome the sins of the past decade. Still, there has never been a more exciting time for neuroscience, and many insights for business are forthcoming. For instance, a new method called hyperscanning—which allows scientists to see the brains of two people who are interacting—is shedding light on the keys to effective collaboration and communication. Innovative research on “brain genomics” is linking brain function to genetics, illuminating people’s predisposition to traits ranging from intelligence to impulsivity. Finally, neuroscientists are trying to understand how functions such as decision making, social skill, cognitive control, and emotion change across a life span. These advances set the stage for a hugely productive dialogue between science and business, which an informed population of consumers will make even more effective.

Harvard Business Review