Mackenzie Mathis

Biography

My long term research goal is to understand the neural circuits and computations underlying adaptive behavior in intelligence systems through the lens of motor learning and control. To achieve this, I have embarked on studying motor circuits at a multitude of levels--from the molecular developmental programs of motor neurons, to the systems level of skilled motor behaviors in mice, to deep neural networks.

I have a multi-disciplinary background in neuroscience (from molecules to circuits to deep learning approaches). As a technician in the co-directed laboratory of Dr. Christopher Henderson and Dr. Hynek Wichterle and advised by Dr. Thomas Jessell, I contributed to multiple teams that aimed to understand the developmental regulation of spinal motor neurons, and used this knowledge to build one of the first in vitro models of ALS from stem cells for high throughput drug screening [1, 2]. During my graduate training in Dr. Naoshige Uchida’s laboratory at Harvard University, I developed the first behavioral mouse model of motor adaptation [3],  and I contributed to the first single unit recordings and optogenetic "tagging" of serotonin neurons in vivo (alongside dopamine neurons). I received the Harvard Rowland Fellowship in the fall of 2016, and after my PhD defense I was a postdoctoral fellow with Prof. Matthias Bethge at the University of Tübingen where I lead the development of deep learning-based methods to track poses of animals, which I completed and extended in my independent lab [4].

I started my independent laboratory in 2017 as a PI & Rowland Fellow at Harvard University, and in the fall of 2020 moved to EPFL for the opportunity to be the Bertarelli Foundation Chair of Integrative Neuroscience at the Brain Mind Institute of EPFL. My lab develops mouse models of motor adaptation, develop new quantitative approaches to behavior and neural circuits [4,5].

I am an ELLIS Scholar, a Vallee Scholar, a former NSF Graduate Fellow, and my work has been featured in the news at Bloomberg BusinessWeek, Nature, and The Atlantic, and in 2022 Nature Methods wrote a biographical piece. I was awarded the FENS EJN Young Investigator Prize 2022, the Eric Kandel Young Neuroscientist Prize in 2023, and the Swiss Science Latsis Prize in 2024.

Here are some key works spanning my career to date:

[1] G. Boulting*, E. Kiskinis*, G. Croft*, M.W. Amoroso*, D. Oakley* et al, A functionally characterized test set of human induced pluripotent stem cells. Nature Biotechnology (2011). 10.1038/nbt.1783 *co-first authors

[2] M.W. Amoroso*, G. Croft* et al, Accelerated high-yield generation of limb-innervating motor neurons from human stem cells. Journal of Neuroscience (2013) 10.1523/JNEUROSCI.0906-12 *co-first authors

[3] M.W. Mathis†, A. Mathis, N. Uchida†. Somatosensory cortex plays an essential role in forelimb motor adaptation in mice. Neuron (2017) 10.1016/j.neuron.2017.02.049 † corresponding author

[4] A. Mathis, P. Mamidanna, K.M. Cury, T. Abe, V.N. Murthy, M.W. Mathis*† & M. Bethge*. DeepLabCut: markerless pose estimation of user-defined body parts with deep learning. Nature Neuroscience (2018) 10.1038/s41593-018-0209-y *co-senior; † corresponding author

[5] S. Schneider, J. Lee, M.W. Mathis†. Learnable latent embeddings for joint behavioral and neural analysis. Nature (2023) https://doi.org/10.1038/s41586-023-06031-6 † corresponding author

(please note, M.W. Mathis was previously M.W. Amoroso)