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Photographed by Dr. Chakravarthy Gopalan

Madhusudhan Venkadesan

Postdoctoral Fellow
Harvard University
School of Engineering & Applied Sciences
29 Oxford Street
409 Pierce Hall
Cambridge, MA 02138

Phone: +1(607)339-6653
Fax: +1(617)495-9837
Email: madhu AT seas DOT harvard DOT edu

Curriculum Vitae (PDF)

Research

My research interest is to understand "how" animals coordinate their body using muscles to stably and robustly interact with the world. To this end, I combine experimental, numerical and theoretical approaches as appropriate to the natural phenomenon under investigation.

How do the "brain" and "body" interact with the world to yield the quintessential robustness and versatility of animal behavior? This question dates back at least 2300 years as seen from Aristotle's arguments in De partibus animalium (ca. 340 BCE). Attempts to answer this question have resulted in remarkably detailed knowledge of the constituent sensorimotor elements in animals ranging from relatively simple nematodes to extraordinarily complex humans. However, we remain unable to predict or mimic the overall behavioral dynamics of most animals under most circumstances. Added difficulties arise from "noise" and "time-delays" that are ubiquitous at almost every level in biological systems.

Past research

  • For my doctoral dissertation, I developed an experiment and used mathematical modelling to quantify the dynamics of dexterous manipulation in humans. I developed a data-driven model and used it to explain a very common observation: we normally handle objects without looking at our hands, but if the sensation from our fingerpads is degraded (due to coldness, anaesthesia, disease, etc), we rely heavily on our vision rather than other sensors (e.g., mechanoreceptors in our hand muscles) to compensate for this loss. I found that this contextual use of vision arises as a natural consequence of combining multiple redundant sensations in a task-optimal fashion, i.e., in a manner that maximizes their functional utility.
    Refs: Valero-Cuevas et al. 2003, Venkadesan et al. 2007a, 2007b.
  • I later used this experimental setup to develop a clinical outcome measure of sensorimotor integration during dynamic manipulation. This outcome measure could quantify hand disability and the effect of treatment more sensitively than existing measures of hand function. This work is part of an ongoing study at the Hospital for Special Surgery in New York, NY.
    Refs: Venkadesan et al. 2005.
  • Our experiment, that involved compressing slender springs between your thumb and fingers, was adapted to decouple strength requirements from control. In other words, we decoupled the control of magnitude of force production from the control of force direction at our fingertips by asking people to compress springs of equal stiffness, but different slenderness. By measuring blood flow in the brain using fMRI techniques, we were able to pinpoint areas of the brain involved in the control of 'dexterity', i.e. ability to control how the direction of our fingertip forces.
    Refs: Mosier et al. In review.

Currently ongoing projects

I have broken up some of my current work into three categories and listed them in decreasing order of how long I have been working on those problems. Each in itself involves, experiments, numerical modelling and some amount of analytical (paper & pen) calculations.

  • Hand: Two basic requirements when handling objects are (i) to switch between moving our fingers and pressing them against surfaces, (ii) produce motion while pressing down at the same time. These apparently commonplace activities are surprisingly challenging in terms of its control. How does biology solve these problems? What of it is because of clever control, and what is because of clever design of our hands, muscles, etc.? I seek to translate our initial results into design principles for robotic fingers and to better understand why minor neuromuscular ailments can severely affect our manual dexterity.
    Refs: Venkadesan and Valero-Cuevas 2008, 2009.

    Force production in our muscles is noisy even for producing a constant force. Is this noise structured in some special way? We found that this noise is structured so that there is less variability in those combinations of muscles that affect the task we are trying to do when compared with those combinations that do not affect our task. Although this conjecture has been around for a long time now, there had been no direct evidence at the level of muscles until now.
    Refs: Valero-Cuevas, Venkadesan and Todorov 2009.

  • Arm: What governs our choice of throwing style and strategy when trying to throw accurately? Why do we throw overarm sometimes and underarm at others? I am working on biomechanical modelling and experiments that address this question. This is clinically important to understand because the ability to throw is a key indicator of healthy development in children. Moreover, our ability to throw accurately *and* fast is important for hunting, with obvious ramifications to human evolution. I am now using our preliminary results to design experiments to parse the source of errors in throwing between sensory, planning and motor. By parsing the source of errors in throwing, I will be able to use it in clinical settings for measuring, tracking and rehabilitating patients with neuromuscular disorders.
    Refs: Venkadesan and Mahadevan 2009, In review.

  • Leg: There is much evidence that running might have played a role in the evolution of bipedalism in humans. While, the relative importance of running over walking is debated, there is little doubt that humans are very capable locomotors over rough terrain, or over long distances. My interest is to find out how much of human performance can be explained by how we tune our bodies to meet the stability demands of running on unpredictable terrain.

Professional areas of interest

  • Dexterous manipulation using the hand: Neuromuscular control and sensorimotor integration for dynamic (time-varying) manipulation of objects.
  • Optimality in sensorimotor control, sensory feedback, multisensory integration, and optimality in biological systems in general.
  • Nonlinear dynamical systems, bifurcation theory and bifurcation detection in noisy dynamical systems. Also, applications of stochastic dynamical systems and delay differential equations in life sciences.
  • Multi-body dynamics and hybrid dynamical systems (such as your finger when tapping on a table).
  • Multiscale computer modeling of skeletal muscle (from cross-bridges to whole muscle) and parameter estimation in musculoskeletal mechanisms.
  • Cortical control of the musculoskeletal systems: Experimental measurements using electromyography (EMG) and functional magnetic resonance imaging (fMRI).
  • Clinical measurement and evaluation of hand function.
  • Using mechanics, physics and mathematics to understand the functioning of any biological system.

Selected Publications

For a complete list of publications, look here (PDF of Curriculum Vitae).

Doctoral dissertation

  • Dynamic dexterous manipulation: Benefits of the edge of instability in exploring complex dynamical behavior. Madhusudhan Venkadesan, 2007. Cornell University, Ithaca, NY, U.S.A. PDF (1.92 MB)

Journal articles

  • Valero-Cuevas FJ§, Venkadesan M§, Todorov E§. Structured variability of muscle activations supports the minimal intervention principle of motor control. Journal of Neurophysiology, In Press. doi:10.1152/jn.90324.2008. PDF (1.27MB). §Equal contribution.
  • Venkadesan M, Valero-Cuevas FJ. Effects of neuromuscular lags on controlling contact transitions. Philosophical Transactions of the Royal Society A, 2009:367(1891):p. 1163-1179. doi:10.1098/rsta.2008.0261. PDF (1.01 MB)
  • Venkadesan M, Valero-Cuevas FJ. Neural control of motion-to-force transitions with the fingertip. Journal of Neuroscience, 2008:28(6):p. 1366-1373. doi:10.1523/jneurosci.4993-07.2008. PDF (827 KB)
  • Venkadesan M, Guckenheimer J, Valero-Cuevas FJ. Manipulating the edge of instability. Journal of Biomechanics, 2007:40(8):p. 1653-1661. doi:10.1016/j.jbiomech.2007.01.022. PDF (1.27 MB)
    • This manuscript was an invited submission as part of the 2006 Journal of Biomechanics Award awarded for an abstract presented at the 30th Annual Meeting of the American Society of Biomechanics.
  • Valero-Cuevas FJ, Smaby N, Venkadesan M, Peterson M, Wright T. The Strength-Dexterity test as a measure of dynamic pinch performance. Journal of Biomechanics, 2003:36(2): p. 265-270. PDF (224 KB)

Manuscripts in review

  • Venkadesan M, Mahadevan L. How to throw accurately.
  • Keenan KG, Santos VJ, Venkadesan M, Valero-Cuevas FJ. Maximal voluntary fingertip force production is not limited by movement speed in combined motion and force tasks.
  • Mosier K, Lau C, Wang Y, Venkadesan M, Valero-Cuevas FJ. Cortical networks for the control of hand dexterity.

Invited symposia

  • Venkadesan M, Valero-Cuevas FJ, Guckenheimer JM. The boundary of instability as a powerful experimental paradigm for understanding complex dynamical sensorimotor behavior: Dexterous manipulation as an example. In Advances in Computational Motor Control II Symposium at the 33rd Annual Meeting of the Society for Neuroscience. New Orleans, LA, 2003.

Invited seminars

  • Venkadesan M. Physical and biological limits of human motor performance. Special Seminar, Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, MA. 2009.

Select peer reviewed conference abstracts

  • Venkadesan M, Mahadevan L. How to throw accurately. Proceedings of the 2009 Annual Meeting of the Society for Integrative and Comparative Biology, Boston, MA: Abstract no. P3.70. 2009. Abstract PDF (54 KB), Poster PDF (2.19 MB).
  • Venkadesan M, Mosier K, Lau C, Wang Y, Valero-Cuevas FJ. Cortical networks for controlling instabilities in dexterous manipulation. Proceedings of the 31st Annual Meeting of the American Society of Biomechanics, Palo Alto, CA. Abstract no. 459. 2007.
  • Backus SL, Keenan K, McNamara III RV, Medina FA, Song S, Price C, Valero-Cuevas FJ, Venkadesan M. The transition between muscle coordination patterns is context dependent. Proceedings of the 31st Annual Meeting of the American Society of Biomechanics, Palo Alto, CA. Abstract no. 457. 2007.
  • Venkadesan M, Guckenheimer J, Valero-Cuevas FJ. Dynamic multisensory integration at the edge of instability is explained by a simple data-based model. Proceedings of the 30th Annual Meeting of the American Society of Biomechanics, Blacksburg, VA: Abstract no. 189. 2006.
  • Valero-Cuevas FJ, McNamara III RV, Santos VJ, Venkadesan M, Song S, Grace-Martin K. The nervous system transitions rapidly between incompatible control strategies by predictively exploiting the margins of error of the task. Proceedings of the World Congress of Biomechanics, Munich, Germany. 2006.
  • Venkadesan M, Srinivasan M, Guckenheimer J, Valero-Cuevas FJ. Computational time-delays due to sensory processing affect multisensory integration strategies. Proceedings of the Neural Control of Movement Annual Meeting, Key Biscayne, FL. 2006.
  • Venkadesan M, Backus S, Mandl LA, Swigart A, Peterson M, Lyman S, Ariola L, Hotchkiss RN, Valero-Cuevas FJ. The strength-dexterity test is a novel and clinically informative measure of treatment outcome in thumb osteoarthritis. Arthritis and Rheumatism, 2005:52(9):S516, 1362 Suppl. S. Abstract PDF (74 KB), Poster PDF (254 KB).

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