What Counts as Evidence

This is the third post of three in a series leading up to the 16th annual International Forum on Consciousness, taking place in Madison this May. Hosted by the BTC Institute, Promega and Usona Institute, the forum gathers scientists, philosophers, and practitioners from dozens of different fields to investigate the nature of the mind. This year’s theme, “Unspoken Intelligence,” explores forms of perception and knowing that fall outside conventional cognition.

In 1845, mathematician Urbain Le Verrier calculated where an unseen planet had to be based on irregularities in Uranus’s orbit, wrote a letter to an observatory telling them where to point their telescope, and Neptune was there. He found a planet without ever looking up.

This is what third-person inquiry looks like at its best: observe from the outside, measure what anyone with the right instruments can measure, build a model precise enough to predict what no one has seen yet. Then look. The history of science is full of such moments, equations pointing to phenomena that hadn’t been detected, particles that hadn’t been observed, forces that hadn’t been measured. The method works because it is ruthlessly disciplined about what counts as evidence. The observer is removed, the conditions controlled, and the measurement trusted.

That discipline is not a limitation. It is the engine of over four centuries of extraordinary results. It gave us germ theory, the structure of DNA, and the sequenced human genome. Every time something seemed to resist physical explanation, the method eventually found the mechanism and the method held. The winning streak was long enough that the assumption underneath it stopped looking like an assumption. Outside-in, third-person, measurable evidence stopped looking like one way of knowing. It started looking like the definition of knowing itself.

The assumption felt safe because it had earned its confidence. Digestion, heredity, mental illness, each had seemed to resist physical explanation until it didn’t. The pattern was consistent enough that the method felt inevitable rather than chosen.

Then science turned toward consciousness, and the winning streak entered dangerous territory.


Here is the problem, what philosopher David Chalmers named the “hard problem” of consciousness in 1995.

To understand what Chalmers meant, it helps to start with his own illustration. When you see red, something measurable happens. Light hits the retina. Signals travel along the optic nerve. Specific regions of the visual cortex activate in patterns that neuroscientists can map with increasing precision. All of that is, in principle, fully describable by the third-person, outside-in approach. Given enough time and instruments, you can trace the whole sequence.

What you cannot describe from the outside is what red looks like. The redness of red, that specific quality of experience that exists only in the moment of seeing it, is not in the neural map. No better scanner will find it there, because the felt quality of the experience isn’t a physical thing hiding in the data. It exists only from the inside. The outside measurement, however precise, cannot reach it.

Chalmers used “hard” deliberately, in contrast to what he called the “easy problems” of consciousness: how the brain integrates information, focuses attention, produces behavior. Those are genuinely difficult, but the outside-in approach knows how to go after them. The hard problem is different in kind. It’s the question that remains even after you’ve solved all of the “easy” ones: why does any of it feel like anything at all?

Think of it this way: everything the brain does could, in principle, happen without any felt experience attached. Processing, responding, behaving, all of it could run like a machine in the dark, with no one home. The question Chalmers is asking is why it doesn’t. Philosophers ask it this way: why is there something it’s like to be you, right now, reading this?

No amount of outside-in evidence, however precise, touches that question, not because the science is insufficient but because the method was specifically designed to exclude first-person data. That exclusion was the whole point. It’s what made the outside-in approach so powerful everywhere else.

With consciousness, the method’s central design decision runs into a question it wasn’t built to answer: how do you study first-person experience when your method was built to exclude first-person data?

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The Filter You Didn’t Choose

This is the second post in a series leading up to the 16th annual International Forum on Consciousness, taking place in Madison this May, hosted by the BTC Institute, Promega and Usona Institute. The Forum gathers scientists, philosophers, and practitioners from dozens of different fields to investigate the nature of the mind. This year’s theme, “Unspoken Intelligence,” explores forms of perception and knowing that fall outside conventional cognition.

When she thought about a dog, she saw a dog, more specifically, every dog she had ever encountered, cycling through her mind like a card catalog with pictures attached. She assumed everyone did this. When she discovered they didn’t, that most people access something more like an abstract concept hovering somewhere between language and image, she was genuinely surprised. Temple Grandin had always known her mind didn’t work the way people expected. What she didn’t know, until she was an adult, was the specific shape of the difference.

Most of us know this story, or one like it. We understand that some minds filter experience differently, but the science on this doesn’t stop where the conversation usually does.


For most of its history, the field that mapped minds like Grandin’s looked at those that didn’t fit the available systems and concluded the minds were broken. (It didn’t ask whether the systems were.) More recently, the conversation has been reframing those minds not as deficient but as different.

For many people, that reframing has been transformative, changing how educators teach, how clinicians diagnose, and how workplaces are designed. We are now more familiar with alternative cognitive profiles such as autistic pattern recognition (like that experienced by Grandin), ADHD-associated divergent thinking, and the hyper-focused depth of what researchers call monotropic attention. These are not broken versions of normal cognition. They are different architectures, each with genuine capabilities that other minds aren’t built to produce.

The terms most commonly used to describe these differences, neurotypical and neurdivergent, are useful shorthand but they describe a binary the underlying biology doesn’t support. Cognitive traits distribute across a population the way most biological traits do. “Neurotypical” minds are simply closer to the statistical center. What we call “neurodivergent” can be better understood as the part of that population that differs visibly enough from the statistical center to make the variation impossible to ignore.


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The Body Already Knows

This is the first post in a series leading up to the 16th annual International Forum on Consciousness, taking place in Madison this May, hosted by the BTC Institute, Promega and Usona Institute. The Forum gathers scientists, philosophers, and practitioners from dozens of different fields to investigate the nature of the mind. This year’s theme, “Unspoken Intelligence,” explores forms of perception and knowing that fall outside conventional cognition.

There’s a quote that travels well in some intellectual circles:

You don’t have a soul. You are a soul. You have a body.

There’s something genuinely relieving about that idea. It locates the real you somewhere above the fray, untouched by the body’s demands and indignities, the consciousness that thinks and persists while the body handles the inconvenient work of being hungry and tired and sick. The thinking part is what counts.

Plato thought something similar. So did Augustine. As did Descartes. Kant, too. The idea that the thinking self is separate from and superior to the body is Western civilization’s default setting.

It sounds like wisdom. It is also, I’ve come to think, exactly the wrong way to understand what we are.

Here’s a different text, one most millennials can recite from memory. In the opening verse of “Lose Yourself,” Eminem rattles off a visceral catalog of physical symptoms: sweaty palms, weak knees, heavy arms, vomiting. The body staging a complete revolt while the mind tries to execute a plan, until the moment on stage when the mouth opens and nothing comes out. The mind wanted to perform, but the body said no.

Nobody who has memorized those lyrics thinks of them as a description of embodied cognition. They file it under music, or nostalgia, or just a song they played too loud in a car they didn’t own. But the nervous system doesn’t care what you call it, because the body doesn’t catalogue in words.

This is the thing the soul-body quote gets wrong: the body isn’t a vehicle the self rides around in. It’s already thinking, already keeping score, already running a process the mind is only partially aware of. The question is what to do about that.

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From Content Creators to Communication Partners: The Role of Motion in Scientific Storytelling

Image generated by DALL-E.

Moving Science Forward — Literally

I’ve always believed that the best science stories don’t just inform — they move us. And in many cases, that’s quite literal.

Whether I’m designing a figure for a new assay or animating a step-by-step protocol, I see motion as a bridge that turns complexity into clarity. When used well, that bridge transforms scientific communication from dense and static into something dynamic, visual and memorable.

And it’s not just me — a graphic designer — saying this. Scholars like Daniel Liddle describe motion as a form of visual rhetoric: a way to persuade, clarify and build trust through movement. Motion isn’t just decoration — it’s meaning made visible.

In this post, I’ll explore why motion matters in scientific communication and how animation makes complex ideas easier to grasp. From turning a protocol into a story that sticks to making technical jargon something you can remember, motion design helps science feel more approachable and a lot more memorable.

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Non-Pharmacological Approaches to ADHD: Exploring Inflammation and Omega-3s

Attention-Deficit/Hyperactivity Disorder (ADHD) is a complex neurodevelopmental disorder that affects millions worldwide. Current therapeutic treatment relies on pharmaceutical approaches, but emerging research suggests that dietary supplements, such as omega-3 fatty acids, may offer complementary therapeutic options. A recent study published in the Journal of Psychiatric Research explores the relationship between inflammation and dietary supplements to determine how they might influence ADHD pathology. This work was conducted in Dr. Edna Grünblatt’s lab at the University of Zurich and was supported through Promega’s Academic Access Program. I had the chance to interview Dr. Natalie Walter, the lead author, to learn more about how her work offers potential opportunities for non-pharmacological interventions.

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Exploring Career Options for PhD Students: Planning for Success

Earning a PhD opens doors to a wide range of career opportunities across academia, industry, government, and beyond. While many students begin their PhD programs with specific career goals, research shows that career interests often evolve during their training (Brown et al., 2023). Therefore, exploring career options and remaining flexible to opportunities is important. By embracing career exploration and self-assessment, students can identify their best career options and make informed decisions about their next steps after graduation.

The Many Career Options for PhD Graduates

PhD graduates today find themselves in diverse roles, with opportunities extending beyond traditional academia. Career paths include:

  • Academia: Research-intensive faculty positions, teaching-focused roles, or administrative leadership.
  • Industry: Roles in biotechnology, data science, or consulting, often in research or management positions.
  • Government and Nonprofit Organizations: Research or policy roles in agencies such as the NIH (National Institutes of Health) and FDA (Food and Drug Administration), and others.
  • Additional Careers: Science communication, medical writing, marketing, patent law, or entrepreneurship.

During their training, PhD students develop highly transferable skills—critical thinking, project management, data analysis, communication, and problem-solving—that are highly valued across sectors (Sinche et al., 2017). Recognizing the value of these skills can expand career options for graduates.

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Third Annual Targeted Protein Degradation Symposium: Embracing the Excitement of Discovery

The third annual Targeted Protein Degradation (TPD) Symposium just wrapped up last month. It was kicked off with Poncho Meisenheimer, VP of Research and Development at Promega, likening the gathering of researchers to “kids in a biology candy store.” This playful analogy captured the vibrant energy and sense of exploration among the attendees, who convened to delve into the future possibilities of proximity-induced degradation. Poncho left attendees with three key questions to consider throughout the symposium:

  1. How can we focus on quantitative measures of cellular events in relevant models?
  2. How do we generate results that serve both human and AI models?
  3. How do we best embrace the excitement of discovery?

Nearly 150 participants from both industry and academia attended the two-day symposium. It was held on September 11th and 12th at Promega’s R&D hub, the Kornberg Center, in Madison, Wisconsin. The event, now in its third year, provided a familiar environment where collaborations flourished, and many attendees rekindled connections forged through previous interactions or partnerships in the field.

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iGEM Grant Winners Tackle Tough Problems in Synthetic Biology

Conceptual image depicting dna strands intertwined with robotic parts.

In June, Promega proudly announced the ten winners of the 2024 Promega iGEM Grant. These extraordinary teams have been hard at work preparing for the iGEM Grand Jamboree, which will take place from October 23-26, 2024, in Paris, France. We interviewed a handful of this year’s grant recipients to learn more about their projects and journeys they’ve taken to reach this exciting milestone. Below are stories from four of the winning teams.

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The Casual Catalyst: Science Conversations and Cafes

There is no shortage of stories about great scientific collaborations that have taken root as the result of an excited conversation between two scientists over sandwiches and beer at a bar or a deli. One of the most famous examples of such a conversation was that between Herbert Boyer and Stanley Cohen when they attended a conference on bacterial plasmids in 1972—that very conversation led to the formation of the biotechnology field as the two scientists worked together to clone specific regions of DNA (1).  

“Over hot pastrami and corned beef sandwiches, Herbert Boyer and Stanley Cohen opened the door to genetic engineering and laid the foundations for gene therapy and the biotechnology industry.”  

Steven Johnson, author of Where Do Good Ideas Come From, credits the English coffee house as being crucial to the spread of the enlightenment movement in the 17th and 18th centuries (2). He argues that coffee houses provide a space where ideas can come together and form networks. In fact, he defines the concept of “idea” not as a single entity—a grand thought that poofs into existence upon hard work—but at its simplest level, a new idea is a new network of neurons firing in sync with each other.  

Johnson further argues that the development of great new ideas not only requires a space for ideas to bump into each other, connect and form a network, but also that great ideas are rarely the product of a single “Eureka” moment. Rather, they are slowly developing, churning hunches that have very long incubation periods (2).  

Science is Ripe with “Coffee House” Discoveries

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Expert Insights: A Look Forward at Multiplexing for in vivo Bioluminescence Imaging

Bioluminescent in vivo imaging tools

NanoLuc, NLuc

With advancements made over the past few decades, the future of in vivo bioluminescence imaging (BLI) continues to gain momentum. In vivo BLI provides a non-invasive way to image endogenous biological processes in whole animals. This provides an easier method to assess relevant systems and functions. Unlike fluorescent imaging, BLI relies on a combination of enzymes and substrates to produce light, greatly reducing background signal (Refaat et al., 2022). Traditional fluorescent tags are also quite large and may interfere with normal biological function. In vivo BLI research has been around for quite some time, primarily utilizing Firefly luciferase (Luc2/luciferin). A recent advancement was the creation of the small and bright NanoLuc® luciferase (NLuc). Promega offers an wide portfolio of NLuc products that provide ways to study genes, protein dynamics, and protein:protein interactions. To fully grasp the power of these tools, I interviewed several key investigators to determine their perspectives on the future of in vivo BLI. I was specifically interested in their thoughts on NLuc multiplexing potential with Firefly (FLuc), and future research areas. These two investigators are Dr. Thomas Kirkland, Sr. Scientific Investigator at Promega, and Dr. Laura Mezzanotte, Associate Professor at Erasmus MC.

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