With every step we take, our brains are already thinking about the next one. If a bump in the terrain or a minor misstep has thrown us off balance, our stride may need to be altered to prevent a fall. Our two-legged posture makes maintaining stability particularly complex, which our brains solve in part by continually monitoring our bodies and adjusting where we place our feet.

Now, scientists at MIT have determined that animals with very different bodies likely use a shared strategy to balance themselves when they walk.

Nidhi Seethapathi, the Frederick A. and Carole J. Middleton Career Development Assistant Professor in Brain and Cognitive Sciences and Electrical Engineering and Computer Science at MIT, and K. Lisa Yang ICoN Center Fellow Antoine De Comite found that humans, mice, and fruit flies all use an error-correction process to guide foot placement and maintain stability while walking. Their findings, published in the journal PNAS, could inform future studies exploring how the brain achieves stability during locomotion — bridging the gap between animal models and human balance.

Humans know they exist, but how does “knowing” work? Despite all that’s been learned about brain function and the bodily processes it governs, we still don't understand where the subjective experiences associated with brain functions originate.

A new interdisciplinary project seeks to find answers to these kinds of big questions around consciousness, a fundamental yet elusive phenomenon.

The MIT Consciousness Club is co-led by philosopher Matthias Michel, the Old Dominion Career Development Professor in the Department of Linguistics and Philosophy, and Earl Miller, the Picower Professor of Neuroscience in the Department of Brain and Cognitive Sciences.

Funded by a grant from the MIT Human Insight Collaborative’s (MITHIC) SHASS+ Connectivity Fund, the MIT Consciousness Club aims to build a bridge between philosophy and cognitive (neuro)science, while also engaging the Boston area’s academic community to advance consciousness research.

“It’s possible to study this scientifically,” says Michel. “MIT positioning itself as a leader in the field would change everything.”

“Matthias takes a science-based approach to the work” Miller adds. “A coherent, fact-based, research-supported understanding of and approach to consciousness can have a massive impact on our approach to public health.”
 

Why did humans evolve the eyes we have today?

While scientists can’t go back in time to study the environmental pressures that shaped the evolution of the diverse vision systems that exist in nature, a new computational framework developed by MIT researchers allows them to explore this evolution in artificial intelligence agents.

The framework they developed, in which embodied AI agents evolve eyes and learn to see over many generations, is like a “scientific sandbox” that allows researchers to recreate different evolutionary trees. The user does this by changing the structure of the world and the tasks AI agents complete, such as finding food or telling objects apart.

This allows them to study why one animal may have evolved simple, light-sensitive patches as eyes, while another has complex, camera-type eyes.

The researchers’ experiments with this framework showcase how tasks drove eye evolution in the agents. For instance, they found that navigation tasks often led to the evolution of compound eyes with many individual units, like the eyes of insects and crustaceans. On the other hand, if agents focused on object discrimination, they were more likely to evolve camera-type eyes with irises and retinas. This framework could enable scientists to probe “what-if” questions about vision systems that are difficult to study experimentally. It could also guide the design of novel sensors and cameras for robots, drones, and wearable devices that balance performance with real-world constraints like energy efficiency and manufacturability.

Tomaso Poggio, the Eugene McDermott Professor in the Department of Brain and Cognitive Sciences, an investigator in the McGovern Institute, and co-director of the Center for Brains, Minds, and Machines, is a co-author of the research, published in Science Advances.