Samir Menon
Motor Control

Personal Background

I grew up in Dehradun, a small town (of a million people) in northern India, and pursued an undergraduate degree in Information Technology at the Indian Institute of Information Technology, Allahabad. My research there focused on robotic pathfinding algorithms, and biologically inspired algorithms for multi-robot cooperation.

I was exposed to neuroscience research when I came to Stanford as a computer science graduate student, and started working with Kwabena Boahen's Brains in Silicon group. Being interested in robotic control, I started studying biological motor control and learning. I was amazed at the complexity, capabilities and, in my opinion, elegance, of biology, and before I realized it, I was hooked on neuroscience. Now, co-advised by Oussama Khatib, a roboticist, I spend my days trying to understand how the brain's different motor regions coordinate musculoskeletal motion.

Research Goals

I want to understand how humans seamlessly perform motor tasks in parallel, for instance, carrying a cup of coffee, talking on a cell phone, and looking around while maintaining an upright posture. Such tasks require the brain to coordinate hundreds of muscles simultaneously and to resolve any potential conflicts on the fly. To resolve conflicts, the brain prioritizes tasks, determines how each task’s required muscular coordination influences the others, and inhibits any destructive interference. Attempts to unravel how the brain represents such motor skills, however, have been confounded by the inability of traditional single-task based motor studies to delineate a generalizable motor representation from task-specific parameters like positions, trajectories and forces.

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Mapping Motion on to the Brain
A musculoskeletal model scaled to a subject's biomechanics reconstructs his skeletal motions and muscular activation as he draws a square. Correlating this muscular activation and skeletal motion with fMRI data collected while the subject performs the same motion in the scanner reveals the brain regions involved.

To elucidate the brain’s muscular coordination strategy, I am using insights from humanoid robotics and human biomechanics to construct subject-specific motor tasks that delineate task-specific confounds and systematically probe the muscular coordination substrate. I am also working to identify the underlying neural representation by measuring brain activity with functional magnetic resonance imaging (fMRI). Eventually, I hope to completely characterize and reverse engineer how the brain's motor regions control muscles.

Project Status

I am presently designing novel fMRI experiments to try and determine what motor controller components best explain neural activity in the brain's main motor regions, the motor cortex, basal ganglia and cerebellum. I recently developed a human biomechanical control simulation environment and am implementing different control strategies on human models. In the near future, I will use my human model simulations to help improve my fMRI experiment designs.


ID Article Full Text
S1 Demircan E, Besier T, Menon S, Khatib O, Human motion reconstruction and synthesis of human skill, Advances in Robot Kinematics. 2010 Jun 11(1):283-292.
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