The Interesting Interplay Between Biological Intelligence & Artificial Intelligence

Women Leading Visual Tech: Interview with Dr. Mackenzie Mathis

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It’s been a year since we started our monthly Women Leading Visual Tech interview series to showcase the leading women whose work in visual tech is reshaping business and society!

Mackenzie Mathis is a neuroscientist, a tenure-track professor at the Swiss Federal Institute of Technology, working within the Brain Mind Institute & Center for Neuroprosthetics. The lab is hosted at the Campus Biotech in Geneva, Switzerland, where she holds the Bertarelli Foundation Chair of Integrative Neuroscience.

Dr. Mathis founded the Adaptive Motor Control Lab to investigate the neural basis of adaptive motor behaviors in mice to inform future translational research in neurological diseases. Her team’s goal is to reverse engineer the neural circuits that drive adaptive motor behavior by studying artificial and natural intelligence. The researchers are using the latest techniques in 2-photon and deep brain imaging. They also develop computer vision tools, like DeepLabCut.

Before that, Mackenzie completed her doctoral studies and was a faculty member at Harvard University. Her work has been featured in Nature, Bloomberg BusinessWeek, and The Atlantic.

Interview Excerpts

Abby: How do you describe what you do in simple terms?

Mackenzie: Humans can do remarkable things in terms of how we express ourselves. Our speaking, walking, writing, and other activities depend on the motor system. I’m interested in understanding how the motor system across different brain areas is orchestrating adaptability and this ease with which we carry ourselves around the world.

Abby: How did your fascination with it start?

Mackenzie: When I was an undergraduate, I was planning to go to medical school and I worked for a doctor all through college. I saw patients with Lou Gehrig's disease. In a few words: your motor neurons are dying in the periphery and you lose the ability to move and eventually the ability to breathe.

Abby: How did your initial research transition into computational neuroscience? When did you start using deep learning and why?

Mackenzie: Deep learning burst onto the scene around six years ago, when it became clear that this was going to be usable and have a massive impact and on all facets of society.

The Interplay Between Biological and Artificial Intelligence

Deep neural networks were built with inspiration from the brain, in terms of the units or the nodes. These networks model what we think our neurons might do. Now instead of doing stem cell-derived neurons, we're trying to build models of the system.

Abby: With some of the machine learning tools that you've developed, you're leveraging a lot of imaging to understand how the brain is functioning. Can you tell me about that?

Mackenzie: We can have a window into the brain. With mice, we can genetically engineer them such that any time a neuron fires, it glows green (calcium imaging). We can record that and then look at these populations of green-glowing neurons and try to make sense of the dynamics.

Measuring Neural Activity

We can also go back in and perturb those neural circuits with light-gated activation or inhibition, which is called optogenetics. This allows us to causally probe how the brain relates to behavior.

Abby: How does your research of neurological workings of mice correlate to doing something like fighting Lou Gehrig's disease?

Mackenzie: Mice can be an incredible platform for these technologies – anything from optogenetics to pose estimation. Historically, in biomedical research, we care about curing diseases but also the quality of life.

Abby: In five to ten years, how are we going to treat neurodegenerative disorders?

Mackenzie: We’ll probably have a holistic viewpoint and deeper metrics that are meaningful. I hope diagnosis would be transformed if the disease is not eradicated.

Conclusion

Mackenzie: I believe machine intelligence will help us in multiple different ways. We can provide tools and start thinking about the problems in new ways, which has driven innovation in science and the healthcare industry.