Let’s introduce Dr. Bas Rokers to our audience! Who are you? If you had to describe yourself in 1 sentence, what would you say?

I am a visual neuroscientist and professor at NYU Abu Dhabi, where I lead a team dedicated to understanding how our brain constructs our rich three-dimensional visual world from the flat images that fall on our eyes.

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What are the most

A- Fascinating research

B- Impactful research

C- Fun and whimsical research

You are leading these days?

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Fascinating research: One of the most profound and fascinating projects I'm involved with is Project Prakash. This is a remarkable initiative based in India that has a dual mission: it provides sight-restoring surgery to children who were born blind due to congenital cataracts significantly improving quality of life. It also offers a unique scientific window into how the brain learns to see.

My role is to help understand the neural basis of this incredible transformation. We get to ask a question that philosophers and scientists have wondered about for centuries: What happens when a person who has been blind up to that point suddenly gains the gift of sight? We use fMRI to scan the children's brains both before and after their surgery. This allows us to witness the brain's remarkable plasticity firsthand. The most exciting part is seeing if—and how—those brain regions process visual information once sight is restored. It’s a beautiful and deeply moving fusion of humanitarian work and fundamental neuroscience, giving us unprecedented insight into how experience shapes the developing brain.

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Impactful research: I believe our most impactful research is tied to understanding neurodegenerative conditions like multiple sclerosis (MS). Vision problems are often one of the very first symptoms of MS, sometimes occurring years before a formal diagnosis. My lab is running studies to understand precisely how MS affects the visual system, from the optic nerve all the way to the visual processing centers in the brain.

We use a combination of advanced neuroimaging and highly sensitive visual tests to detect the subtle changes that MS causes, even in patients who feel their vision is normal. The goal is to identify clear and early biomarkers of the disease's progression. By tracking these visual changes, we hope to provide a more sensitive way to monitor the effectiveness of treatments and, ultimately, to contribute to earlier diagnosis, which is crucial for managing the disease and improving long-term health outcomes for patients.

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Fun and whimsical research: That would have to be our work with virtual reality. We've been exploring why VR can sometimes make people feel dizzy or nauseous—a phenomenon often called "cybersickness." We've been able to isolate specific visual cues that contribute to this feeling. It's fun because we get to design these immersive, sometimes perception-bending, virtual worlds and observe how people react. It feels a bit like being a digital magician, manipulating perception to understand its underlying rules, with the added benefit of helping make future VR experiences better for everyone.

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So we only get flat images... but we live in 3D? Is it true that our brain fuses two 2D pictures into one deep world, and you traced where that happens?

That's absolutely correct. Each of your eyes captures a slightly different flat, 2D image of the world, much like two cameras positioned a few centimeters apart. The real magic happens in the brain. It takes these two disparate images and, by computing the subtle differences between them (a cue called binocular disparity), it generates our vivid perception of depth.

And yes, my colleagues and I have been instrumental in tracing where this happens. Using fMRI, we've identified a network of visual areas in the brain that are specialized for this task. We've shown that early on in the visual pathway, in an area called the primary visual cortex (V1), information from the two eyes is still largely separate. But as that information is passed along to subsequent areas (like V2, V3, and the middle temporal area, MT), we see the signals being combined and transformed into a unified 3D representation of the world. We were able to pinpoint the specific neural populations that compute depth and motion through depth, essentially mapping the assembly line for 3D vision.

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A single visual cue… makes us dizzy in VR? What is motion parallax and how does it mess with our sense of balance?

The cue you're referring to is motion parallax. It’s one of the most powerful depth cues we have. When you move your head, objects closer to you appear to move more quickly across your field of view than objects farther away. Think about when you're in a car: nearby lampposts zip by, while distant mountains barely seem to move at all. Your brain is exquisitely tuned to this relationship between your own motion and the relative motion of objects to calculate depth and maintain your sense of balance.

In many VR experiences, this cue gets distorted. If you move your head but the visual world on the screen doesn't update with the perfectly corresponding parallax shifts, a conflict arises. Your visual system is getting signals that don't match the signals from your vestibular system—the balance sensors in your inner ear. Your brain receives contradictory information: your inner ear says you're moving, but the visual parallax cue says you're not, or that you're moving differently. This sensory conflict is a primary driver of the dizziness and nausea associated with cybersickness. It’s your brain's alarm bell saying, "Something isn't right here."

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AI…AI…AI…is AI doing anything useful in your field of visual neuroscience?

That’s a great question. My focus is on understanding the brain and how it creates our sense of sight.

And in that context, AI is proving to be an incredibly powerful tool, especially for clinical applications. One of the most exciting frontiers is using AI for the early diagnosis of neurodegenerative disorders. We feed machine learning algorithms massive datasets containing everything from high-resolution brain scans and eye-tracking data to clinical histories. The AI then learns to detect incredibly subtle patterns that are invisible to the human eye—patterns that can be predictive of conditions like multiple sclerosis or dementia long before clear symptoms arise.

Furthermore, we're using AI to uncover markers of resilience. We all know people who remain sharp as a tack well into old age, while others decline. Why? AI can help us answer that by sifting through all our data to identify the specific neural and even lifestyle factors that enable some brains to better resist the effects of aging or disease. The ultimate goal is to move from a one-size-fits-all approach to truly personalized neurology, using AI to predict individual risk and identify who might benefit most from early intervention.

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If you could design an experiment without any limitations of time or money…what would it be?

Without a doubt, I would launch a massive, longitudinal study that follows thousands of individuals from birth to old age. We would use a combination of advanced neuroimaging, genetic sequencing, and detailed perceptual and cognitive testing at regular intervals throughout their lives. The goal would be to create a complete developmental map of the human visual system. We could finally answer fundamental questions like: How does the brain learn to see in 3D? How do early life experiences shape our perceptual abilities? How does the brain adapt to injury or disease over time, and what makes some individuals more resilient than others? It would be the ultimate dataset for understanding brain development, plasticity, and aging.

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If you could have a superhero power. What would it be?

It would have to be the power to see the world through the eyes of others. Not just to see what they see, but to experience their unique perception of it. Imagine being able to perceive the world as a person with color blindness does, or as an infant just beginning to make sense of shapes and faces, or even to experience the visual world of another animal, like a hawk with its incredible acuity. It would be the ultimate tool for empathy and for understanding the beautiful diversity of perception.

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Mystery dinner party…Dead or Alive, who would be 3 guests you would invite to your dinner party?

That is a wonderful question. My three guests would be:

1. Santiago Ramón y Cajal: The father of modern neuroscience. His intricate drawings of neural circuits were revolutionary and are still breathtakingly beautiful. I would love to hear his thoughts on the tools we have today and ask him about the intuition that guided his groundbreaking discoveries.

2. Hermann von Helmholtz: A true polymath—a physician, physicist, and philosopher who made foundational contributions to our understanding of vision and perception. His work on color vision and unconscious inference is still central to my field. Discussing the link between the physical world and our subjective perception with him would be extraordinary.

3. Béla Julesz: A pioneering visual neuroscientist who used computer-generated random-dot stereograms to prove that depth perception could arise purely from binocular disparity, without any other cues. He was a creative and playful scientist, and I’d love to brainstorm wild visual experiments with him.

The conversation about the nature of perception, art, and the brain would be unforgettable.

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Question to you from our previous guest Dr. Stéphane Boissinot (Professor of Biology, NYUAD): “Will AI be able to produce philosophy?"

That is a deep and fascinating question from my colleague. I believe that in one sense, AI already is. AI models can synthesize vast amounts of philosophical text and generate coherent, novel-sounding arguments and essays in the style of famous philosophers. They can identify patterns and draw connections that a human might miss.

However, if we define "philosophy" not just as the logical arrangement of ideas but as a process rooted in subjective experience, consciousness, and a genuine curiosity about one's own existence and purpose, then the answer becomes much more complex. True philosophical inquiry often stems from awe, suffering, wonder, or the confrontation with mortality—states that are, as far as we know, tied to biological embodiment and consciousness.

An AI can write about the nature of good and evil, but can it feel the weight of a moral dilemma? It can describe phenomenology, but does it have phenomenal experience? Until an AI has a genuine, subjective, first-person perspective on the world, I think its "philosophy" will remain a sophisticated mimicry of ours—a brilliant reflection, but not the thing itself. So, my answer is a qualified yes: it can produce the text of philosophy, but whether it can partake in the human act of philosophizing remains the great unanswered question at the heart of both AI and neuroscience.

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