Welcome to sinthlab - the Sensorimotor Integration and NeuroTheory Laboratory at the Université de Montréal and Mila.


We fuse AI and computational neuroscience with experimental neurophysiology and neural engineering to study how biological brains coordinate motor behaviors.

By linking fundamental neuroscientific insights with innovations in AI, we aim to guide the development of next-generation neuroprosthetic devices for rehabilitation.

We are hiring! Postdocs, students, or techs/RAs.
Contact us if you're interested!


Neural population dynamics underlying behavior

The lab aims to understand how the concerted activity of large populations of neurons control the intricate behaviors we produce. We combine neurophysiology experiments with computational models to identify and characterize low-dimensional dynamics that constrain the neural activity observed throughout the brain. We ultimately seek to uncover principles of the neural control of movement that are conserved over time, across individuals, and even across species in order to provide robust, interpretable view of brain activity to apply to neuroprosthetic devices.

More reading: Nature Neuroscience 2020, Neuron 2018, Neuron 2017

Computational methods to parse multi-region interactions

The neural control of behavior is distributed across many functionally and anatomically distinct brain regions. The lab aims to develop computational tools that can uncover, in an unsupervised manner, the distributed, multi-region interactions that guide behavior. Our approaches unveil how disparate sensory, cognitive, and motor systems of the brain coordinate to produce flexible and adaptable behavior. We employ data-driven Recurrent Neural Network (RNN) models to create in silico models of neural recordings that we can reverse engineer.

More reading: bioRxiv 2020a, CONB 2020

Development of closed-loop interfaces between artificial and biological circuits

The lab is working to understand how disparate source of inputs (both internal to the brain and from the external environment) shape the neural dynamics that we record from the brain. We draw on cutting-edge machine learning and AI to develop new classes of neural "decoders" that integrate naturally in closed-loop with ongoing dynamics in the brain. These innovations will be critical for the widespread clinical adoption of technologies such as brain-controlled spinal stimulation that promise to restore movement lost due to paralysis or movement disorders such as Parkinson's.

More reading: bioRxiv 2020b, Nature Neuroscience 2022

Team


Matthew G. Perich is an Assistant Professor in the Department of Neuroscience at the Université de Montréal and an Associate Member of the Montréal Institute for Learning Algorithms (Mila). His research program fuses AI and computational neuroscience with experimental neurophysiology and neural engineering to study how biological brains coordinate motor behaviors and ultimately guide the development of next-generation neuroprosthetic devices for rehabilitation.


Google Scholar | Code

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Join our team!
We are always looking for new colleagues to join our team!
Contact us if you're interested.


Collaborators

Paper Highlights


For a complete publication list, see Google Scholar

Info





For information about research and job opportunities:

matthew dot perich at umontreal dot ca.

Follow us on twitter: @mattperich

We are hiring at multiple levels!

Join us to help explore the interface between neuroscience, AI, and neuroprosthetics. Montréal has a thriving and vibrant neuroscience and AI community. All lab members enjoy access to numerous institutes including Mila and the Institut TransMedTech.

We are committed to supporting scientists from diverse backgrounds, including under-represented groups, and take great effort to ensure the lab is an inclusive and supportive environment for professional growth.


Our lab is part of the Départment de neurosciences in the Faculté de médecine at the Université de Montréal.

We are located at:
Pavillon Paul G. Desmerais
2960 Chemin de la Tour
Montréal QC H3T 1T9




Funding