How do people make sense of the epiphanies when they experience them? Pexels

It might be just the right word from your boss. It might be a phone call with a trusted friend. Or it might be waking up one morning and just knowing. There's no way to predict what will spark an epiphany that changes the way you see the world. But their power can be so far-reaching, they often leave us wondering where on earth that brilliant idea came from — and how we can find more.

Studying the mental processes behind epiphanies is especially hard because these flashes of insight are usually linked with unconscious mental processing and incubation, often during time periods when one may not seem to be thinking about a problem at all. In this way, epiphanies seem to arrive effortlessly.

So how do people make sense of the epiphanies when they experience them? In a set of unprecedented studies, Rice Business professor Erik Dane set out to find answers, first examining people who'd experienced general epiphanies, then analyzing a set of accounts of work- and career-related epiphanies themselves.

The research

In his first study, Dane surveyed more than 500 randomly selected people to ask them about their experiences with epiphanies, which he defined as a sudden and abrupt insight and/or change in perspective that transforms the individual.

Subjects who said they'd experienced epiphanies reported what they'd been doing beforehand, the feelings and insight associated with the epiphany and how they thought they'd changed afterward. Interestingly, though this survey wasn't limited to career- or work-related epiphanies, 20 percent of the responses related directly to these topics.

In the second study, Dane interviewed 22 professionals, asking them about distinct work- or career-related epiphanies, most of which resolved a nagging problem. After analyzing the transcripts of these interviews, Dane developed a set of theoretical categories describing the varieties of reactions an epiphany might spark.

People generally perceive and analyze their epiphanies in similar ways, Dane found. He categorized these into four dimensions: a person's emotional reaction to the experience of the epiphany, the question of how the epiphany arose, the circumstances that preceded the insight and a person's observations about how ready they were to experience change through an epiphany.

The findings

The typical first reaction to an epiphany, Dane says, is a sudden and emotionally charged release from a problem or tension. We've all been there: a stressful work situation that seems to offer no way out, followed by a dazzling solution that appears from the clouds. It's that suddenness that leads to the second typical reaction: a sense of astonishment due to the nonconscious nature of the insight's arrival. Feeling dumbfounded for a prolonged time isn't useful, though, so we usually start examining the factors surrounding the epiphany, including our own readiness to change.

What does this imply for workplace? After all, not every problem can or even ought to be solved by epiphany. At the same time, Dane notes, epiphanies can provide critical impetus to move forward.

Interestingly, his findings hint that one can increase the chances of having an epiphany. Though further research is required, Dane concludes that epiphanies most commonly arrive when people are open to the prospect of experiencing a major change. When something is mentally constraining us, on the other hand, eureka moments keep their distance.

The conclusion

As a worker, Dane suggests, you can open space for epiphanies by being actively aware of your surroundings. Look closely at your workplace, your constellation of coworkers and your place within the system. Perceived mindfully, these details may set the stage for problem-solving in a less focused moment.

If you're a mentor or a supervisor hoping to spark epiphanies in your work team, try applying this principle at work: Rather than laying out specific targets and attacking them head-on, aim for an environment that allows for mindful engagement, one that includes the problems that feature in your long-term goals and resonate with your workers' concerns and interests. Cultivating this environment and granting workers time and space to wander through it may lead, like a divining rod, to fresh sources of wisdom.

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This article originally appeared on Rice Business Wisdom.

Erik Dane is a distinguished associate professor of management (organizational behavior) at Jones Graduate School of Business at Rice University.

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Houston doctor wins NIH grant to test virtual reality for ICU delirium

Virtual healing

Think of it like a reverse version of The Matrix. A person wakes up in a hospital bed and gets plugged into a virtual reality game world in order to heal.

While it may sound far-fetched, Dr. Hina Faisal, a Houston Methodist critical care specialist in the Department of Surgery, was recently awarded a $242,000 grant from the National Institute of Health to test the effects of VR games on patients coming out of major surgery in the intensive care unit (ICU).

The five-year study will focus on older patients using mental stimulation techniques to reduce incidences of delirium. The award comes courtesy of the National Institute on Aging K76 Paul B. Beeson Emerging Leaders Career Development Award in Aging.

“As the population of older adults continues to grow, the need for effective, scalable interventions to prevent postoperative complications like delirium is more important than ever,” Faisal said in a news release.

ICU delirium is a serious condition that can lead to major complications and even death. Roughly 87 percent of patients who undergo major surgery involving intubation will experience some form of delirium coming out of anesthesia. Causes can range from infection to drug reactions. While many cases are mild, prolonged ICU delirium may prevent a patient from following medical advice or even cause them to hurt themselves.

Using VR games to treat delirium is a rapidly emerging and exciting branch of medicine. Studies show that VR games can help promote mental activity, memory and cognitive function. However, the full benefits are currently unknown as studies have been hampered by small patient populations.

Faisal believes that half of all ICU delirium cases are preventable through VR treatment. Currently, a general lack of knowledge and resources has been holding back the advancement of the treatment.

Hopefully, the work of Faisal in one of the busiest medical cities in the world can alleviate that problem as she spends the next half-decade plugging patients into games to aid in their healing.

Houston scientists develop breakthrough AI-driven process to design, decode genetic circuits

biotech breakthrough

Researchers at Rice University have developed an innovative process that uses artificial intelligence to better understand complex genetic circuits.

A study, published in the journal Nature, shows how the new technique, known as “Combining Long- and Short-range Sequencing to Investigate Genetic Complexity,” or CLASSIC, can generate and test millions of DNA designs at the same time, which, according to Rice.

The work was led by Rice’s Caleb Bashor, deputy director for the Rice Synthetic Biology Institute and member of the Ken Kennedy Institute. Bashor has been working with Kshitij Rai and Ronan O’Connell, co-first authors on the study, on the CLASSIC for over four years, according to a news release.

“Our work is the first demonstration that you can use AI for designing these circuits,” Bashor said in the release.

Genetic circuits program cells to perform specific functions. Finding the circuit that matches a desired function or performance "can be like looking for a needle in a haystack," Bashor explained. This work looked to find a solution to this long-standing challenge in synthetic biology.

First, the team developed a library of proof-of-concept genetic circuits. It then pooled the circuits and inserted them into human cells. Next, they used long-read and short-read DNA sequencing to create "a master map" that linked each circuit to how it performed.

The data was then used to train AI and machine learning models to analyze circuits and make accurate predictions for how untested circuits might perform.

“We end up with measurements for a lot of the possible designs but not all of them, and that is where building the (machine learning) model comes in,” O’Connell explained in the release. “We use the data to train a model that can understand this landscape and predict things we were not able to generate data on.”

Ultimately, the researchers believe the circuit characterization and AI-driven understanding can speed up synthetic biology, lead to faster development of biotechnology and potentially support more cell-based therapy breakthroughs by shedding new light on how gene circuits behave, according to Rice.

“We think AI/ML-driven design is the future of synthetic biology,” Bashor added in the release. “As we collect more data using CLASSIC, we can train more complex models to make predictions for how to design even more sophisticated and useful cellular biotechnology.”

The team at Rice also worked with Pankaj Mehta’s group in the department of physics at Boston University and Todd Treangen’s group in Rice’s computer science department. Research was supported by the National Institutes of Health, Office of Naval Research, the Robert J. Kleberg Jr. and Helen C. Kleberg Foundation, the American Heart Association, National Library of Medicine, the National Science Foundation, Rice’s Ken Kennedy Institute and the Rice Institute of Synthetic Biology.

James Collins, a biomedical engineer at MIT who helped establish synthetic biology as a field, added that CLASSIC is a new, defining milestone.

“Twenty-five years ago, those early circuits showed that we could program living cells, but they were built one at a time, each requiring months of tuning,” said Collins, who was one of the inventors of the toggle switch. “Bashor and colleagues have now delivered a transformative leap: CLASSIC brings high-throughput engineering to gene circuit design, allowing exploration of combinatorial spaces that were previously out of reach. Their platform doesn’t just accelerate the design-build-test-learn cycle; it redefines its scale, marking a new era of data-driven synthetic biology.”