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People

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  • Abstracts: abstracts.md
  • Book Chapters: bookchpt.md
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usc-bbdl.github.io's Issues

Adding my ASB abstract

@inproceedings{jalaleddini2017ASB,
title={Evidence That Tuning of Muscle Spindles Can Be Decoupled from Muscle Activation},
author={Jalaleddini, Kian and Kutch, and Nagamori, Akira, and Laine Christopher, and Golkar, Mahsa A., and Kearney, Robert E., and Valero-Cuevas Francisco J}.
booktitle={Proceedings of the 41st Annual Meeting of the American Society of Biomechanics, Long Beach, CA},
volume={},
year={2017}
}

Title: Evidence That Tuning of Muscle Spindles Can Be Decoupled from Muscle Activation
Link:
Author: Kian Jalaleddini, Akira Nagamori, Christopher M. Laine, Mahsa A. Golkar, Robert E. Kearney, Francisco J Valero-Cuevas
BibTex: see above
Year: 2017
Journal: Proceedings of the 41st Annual Meeting of the American Society of Biomechanics, Boulder, CO
SupplementalLink
ASB2017_Poster_Kian.pdf

Get picture/figure for each project

  • Meng-Fen Tsai
  • Brian Cohn Statistical Control & ML
  • Ali Marjaninejad Brain-Machine-Interface
  • Chris Laine Tremor
  • Chris Laine Cortical Coherence
  • Chris Laine Ecog
  • Ko TMS/ ParkinsonsDisease
  • Emily SD test
  • Akira SD - Eccentric
  • Kian Neuromorphic + Neuromechanics
  • Suraj Neuromorphic Computing
  • Jun Data Capture
  • Daniel Neural Control of Movement
  • Victor Neuromorphic pet

interns to add

Vishweshwar Shastri (BME Masters student) - summer 2017.
Young Jin Kim (CS Undergrad) - summer 2017.
Chintalapudi Sarath (EE Masters student) - Summer, Fall 2017.

Publication which needs to be added to the website

Delete all nonrelevant information from this template when submitting your issue request:

#Publication

Should anthropomorphic systems be "redundant"?
Link (Just add "(Accepted)" at the end. Link is not available yet since it is not published yet)
I sent you the pdf file using email.
Abstract
Author: Ali Marjaninejad and Francisco J. Valero-Cuevas
BibTex: Not out there yet but this is the most accurate that I can give you right now:
Should anthropomorphic systems be "redundant"?, Ali Marjaninejad and Francisco J. Valero-Cuevas, Biomechanics of Anthropomorphic Systems, Eds Gentiane Venture, Jean-Paul Laumond & Bruno Watier, STAR series, Springer, 2018. (in press)
Year: 2018
Journal: It is a book chapter: Biomechanics of Anthropomorphic Systems
SupplementalLink						
Get BibTex Via Google Scholar’s Cite. (not available yet)
``
 ## NOTE:
The format of the Author section is very important to the design of the site. If there’s no supplemental material, just leave it blank.


## Example

Unilateral Eccentric Contraction of the Plantarflexors Leads to Bilateral Alterations in Leg Dexterity.

Papers/2016NagamoriFrontPhysiol.pdf

Eccentric contractions can affect musculotendon mechanical properties and disrupt muscle proprioception, but their behavioral consequences are poorly understood. We tested whether repeated eccentric contractions of plantarflexor muscles of one leg affected the dexterity of either leg. Twenty healthy male subjects (27.3 ± 4.0 yrs) compressed a compliant and slender spring prone to buckling with each isolated leg. The maximal instability they could control (i.e., the maximal average sustained compression force, or lower extremity dexterity force, LEDforce) quantified the dexterity of each leg. We found that eccentric contractions did not affect LEDforce, but reduced force variability (LEDSD). Surprisingly, LEDforce increased in the non-exposed, contralateral leg. These effects were specific to exposure to eccentric contractions because an effort-matched exposure to walking did not affect leg dexterity. In the exposed leg, eccentric contractions (i) reduced voluntary error corrections during spring compressions (i.e., reduced 0.5–4 Hz power of LEDforce); (ii) did not change spinal excitability (i.e., unaffected H-reflexes); and (iii) changed the structure of the neural drive to the α-motoneuron pool (i.e., reduced EMG power within the 4–8 Hz physiological tremor band). These results suggest that repeated eccentric contractions alter the feedback control for dexterity in the exposed leg by reducing muscle spindle sensitivity. Moreover, the unexpected improvement in LEDforce in the non-exposed contralateral leg was likely a consequence of crossed-effects on its spinal and supraspinal feedback control. We discuss the implications of these bilateral effects of unilateral eccentric contractions, their effect on spinal and supraspinal control of dynamic foot-ground interactions, and their potential to facilitate rehabilitation from musculoskeletal and neuromotor impairments.

Nagamori A, Valero-Cuevas FJ, Finley JM.

"@Article{nagamori2016unilateral,
title={Unilateral Eccentric Contraction of the Plantarflexors Leads to Bilateral Alterations in Leg Dexterity},
author={Nagamori, Akira and Valero-Cuevas, Francisco J and Finley, James M},
journal={Frontiers in Physiology},
volume={7},
year={2016},
publisher={Frontiers Media SA}
}
"

2016

Frontiers in Physiology



# Have an issue with website? (change/removal/addition)
Include:
 - Link to the file where the change needs to happen, exact text, images, etc to include/remove
 - Paste any available quick screenshots
 - Link to the files that will be affected by the change, which you can find via https://github.com/usc-bbdl/usc-bbdl.github.io
 - Urgency = immediately (text me too), within 2 days, or within 5 days)


update: new papers for the website

Task: add the following two papers as accepted (no link to PDF yet)

"Neuromorphic meets Neuromechanics PART I: The Methodology and Implementation" by Niu, Chuanxin; Jalaleddini, Kian; Sohn, Won Joon; Rocamora, John; Sanger, Terence; Valero-Cuevas, Francisco

"Neuromorphic Meets Neuromechanics, Part II: The Role of Fusimotor Drive" by Jalaleddini, Kian; Niu, Chuanxin; Chakravarthi Raja, Suraj; Sohn, Won Joon; Loeb, Gerald; Sanger, Terence; Valero-Cuevas, Francisco

under categories - Neuroscience | Computation & Modeling | Robotics |
Clinical Research | Biomechanics |

fco addns

1- when clicking on a paper, it should open in a new window

2- we need to work on the labels. One if them athletics, which I don't think is good
3- when you select a label, some years come out empty... we should only show the years that have papers
4- we need to have a picture of the book in the hime page, as in bbdl.usc.edu

add lab member bios to the about page

missing abstracts for two papers

  • The Potential of Virtual Reality and Gaming to Assist Successful Aging with Disability.
  • Morphological Communication: Exploiting Coupled Dynamics in a Complex Mechanical Structure to Achieve Locomotion

Design homepage

  • conduct interviews (who are our audience segments?)
    researchers
    current lab members
    prospective lab members
    prospective collaborators
    people who are looking to employ BBDL members
  • identify all pages in order of preferences
  • write user flow diagram
  • draw low fidelity mockup
  • conduct interviews
  • draw high fidelity mockup

ASB abstract

Title: Interactions between Tendon Stiffness and Spindle Afferent Feedback Determine the Magnitude of Involuntary Force Variability

Link: ASB_abstracrt.pdf

Abstract:
INTRODUCTION
Tendons influence the transmission of muscle contractions [1]. Moreover, the relative mechanical properties of tendon and muscle determine the changes of muscle and tendon lengths. Therefore, tendon stiffness plays a critical role in the neural control of limb motions and forces [3,4], and is a major factor influencing proprioceptive feedback [2,3].
A basic and popular metric of ‘precision’ in motor control is the ability to produce a constant isometric force. During such tasks, involuntary force variability is an informative and fundamental component of current theories of motor control [5]. We have shown that a closed-loop simulation of peripheral neuromuscular elements can replicate cardinal features of force variability, and can be used to test mechanistic hypotheses about its healthy and pathologic generation/modulation [6]. Thus, we hypothesized that alterations in tendon stiffness would have a distinct influence on the nature of involuntary force variability, and its relationship with proprioceptive feedback.
METHODS
We used a published physiologically-grounded closed-loop simulation of afferented muscle model [6]. The model includes a musculotendon unit, muscle spindle, Golgi tendon organ, and a force- tracking controller, which enables this system to perform force-tracking tasks. In this study, we modeled gastrocnemius muscle, and decreased and increased its tendon stiffness by 50% from a default value. We simulated 20 isometric force trials lasting 100s at 20% of maximal voluntary contraction (MVC) for each level of tendon stiffness. We repeated these trials at different levels of spindle feedback gain. The generated force during the last 90s was analyzed in the time and frequency domains.
RESULTS AND DISCUSSION
As expected, lower tendon stiffness reduced MVC (208 N, 202 N, and 185 N for high, default, and low tendon stiffness) [1].
Figure 1 shows that the overall amplitude of involuntary force variability depended on spindle feedback gain and tendon stiffness in a non-linear manner. In addition, low tendon stiffness resulted in larger reduction in involuntary force variability amplitude at increased spindle feedback gains. Importantly, tendon stiffness had no effect on force variability at lower spindle feedback gains.
These results demonstrate that tendon stiffness, via changes in spindle feedback gain, affect the regulation of involuntary force variability, and agree with suggestions that compliant tendons improve the control of isometric forces [2-4]. This further suggests that decreased or increased stiffness due to musculoskeletal injuries [7] or aging may require adaptation in neural control and coordination among muscles [8].
We also found frequency-specific effects of interactions between tendon stiffness and spindle feedback gain. Decreases in tendon stiffness led to lower high-frequency (5-12 Hz) force variability across spindle feedback gains (Figure 2).
This result implies that high-frequency involuntary force variability, often called physiological tremor, might provide insight into peripheral neuromecahnical interactions. Importantly, pathological tremor, such as occurs in Parkinson’s disease (4-6 Hz), may be exacerbated by the stiffening of tendons which both accompanies aging and is characteristic of the pathology [9].
CONCLUSIONS
Our work emphasizes that, as previously suggested [1-4], the mechanical properties of tendons could be an important—yet overlooked—aspect of force control. Moreover, our physiologically-grounded simulations begin to explain this in a mechanistic way that extends our understanding of healthy and pathologic involuntary force variability. These findings suggest that tendon properties may contribute to the mechanisms of disrupted motor control within certain pathologies, and may therefore represent promising targets for treatment/intervention.

Author: Nagamori A, Laine CM, Jalaleddini K, and Valero-Cuevas FJ

BibTex:
"@Article{nagamori2017interactions,
title={Interactions between Tendon Stiffness and Spindle Afferent Feedback Determine the Magnitude of Involuntary Force Variability},
author={Nagamori, Akira Laine, Christopher M, Jalaleddini, Kian, and Valero-Cuevas, Francisco J},
journal={41st Annual Meeting of the American Society of Biomechanics},
year={2017},
}
"

Year:
2017
Journal:
41st Annual Meeting of the American Society of Biomechanics, Boulder, CO, USA, August 8th – 11th, 2017

Current Projects

make this similar to the about page, where the photos of people are. Sample text:

example text content, with example of the related publications.

You also need to add a small section of 'Team' with links to the anchor points on the about page.
image

example image

image

Find some tasks for interns

Intern Tasks:

  • Flock of Birds repurposing
  • Proofreaders for papers
  • Dexterity testing with NMD devices
  • Phantom Robot
  • Figure design and schematic illustration

Add publication

Title: Intermuscular coherence reflects functional coordination
Link: http://jn.physiology.org/content/early/2017/06/26/jn.00204.2017
Abstract:
Coherence analysis has the ability to identify the presence of common descending drive shared by motor unit pools, and reveals its spectral properties. However, the link between spectral properties of shared neural drive and functional interactions among muscles remains unclear. We assessed shared neural drive between muscles of the thumb and index finger while participants executed two mechanically distinct precision pinch tasks, each requiring distinct functional coordination among muscles. We found that shared neural drive was systematically reduced or enhanced at specific frequencies of interest (~10 and ~40 Hz). While amplitude correlations between surface EMG signals also exhibited changes across tasks, only their coherence has strong physiological underpinnings indicative of neural binding. Our results support the use of intermuscular coherence as a tool to detect when co-activated muscles are members of a functional group or synergy of neural origin. Further, our results demonstrate the advantages of considering neural binding at 10, ~20, and >30 Hz, as indicators of task dependent neural coordination strategies.

Author: Laine, Christopher M. and Valero-Cuevas, Francisco J
BibTex:
@Article{laine2017intermuscular,
title={Intermuscular coherence reflects functional coordination},
author={Laine, Christopher M and Valero-Cuevas, Francisco J},
journal={Journal of Neurophysiology},
volume={118},
number={3},
pages={1775--1783},
year={2017},
publisher={Am Physiological Soc}
}
Year: 2017
Journal: Journal of Neurophysiology

Laine and Valero-Cuevas - 2017 - Intermuscular coherence reflects functional coordi.pdf

Brian ASB Abstract

Title: Neuromechanical implications of postural changes to motor learning and performance
Link: cohn_jalaleddini_valerocuevas_asb_2017.pdf
cohn_jalaleddini_valerocuevas_asb_2017.pdf

Abstract

METHODS
We firmly connected the index fingertip of a Utah/M.I.T hand [2] to a 6-DOF load cell to produce static forces (Fig 1). The load cell was affixed to the endpoint of an AdeptSix300 robot that was moved to change finger posture. Seven index finger tendons were actuated by DC brushless motors [3], routed through pulleys.
The robot moved the limb endpoint to 100 randomly selected endpoint postures on an arc (Fig 2). At each posture, the motors applied 100 force combinations across tendons uniformly at random (spanning 3 to 12N range). The duration of each trial was 0.8s— sufficient for forces to settle. We sampled fingertip and tendon forces at 1kHz.
were recorded as motors produced known tendon forces, at different postures. The resulting endpoint force vectors (red) were described in spherical coordinates (rho, theta, phi) in the common frame of reference of the fingertip and sensor.
We calculated the force steady-state of each trial by averaging the last 0.2s. For each posture, we identified the linear static 3x7 model ( Ai  ) that transforms tendon tensions to endpoint forces using linear regression:
Note this mapping does not consider torques at the endpoint of the finger [1] and serves as a worst-case scenario for model performance.
RESULTS AND DISCUSSION
For all individual postures, a linear model  Ai, accurately predicted endpoint force as a function of tendon forces, (i.e., a high percentage of variance-accounted-for, %VAF, Fig 2). In addition, the negligible residual error did not have a structure
Forces at the tip of the mechanical finger across posture (Fig 2a). As could be expected given the nonlinear changes in the finger’s Jacobian [1], posture had a profound effect on the  Ai  matrices that map tension to endpoint force. Interestingly, the effect of posture in fingertip force strength (rho, in N) and direction differed widely across muscles. While m 2 had a consistent rho across all postures, m 3 had higher variability(Fig3, left).As for direction,m 2’ s direction in the zy plane (phi) was consistent across postures—m 3  was more variable (Fig 3, right). We conclude that linear models (i.e.,  Ai matrices) do not perform uniformly well across postures. Yet
effective neural control of tendon driven limbs should work well across the workspace [4]. Interestingly, our results suggest small changes in posture can lead to large changes in the mechanical actions of muscles—therefore  Ai  matrices likely do not generalize well across regions of the workspace. We speculate that the full mechanical output of the limb should be considered (i.e., endpoint torque output),and that exploration of the full workspace is preferable as interpolation will likely not work. Thus, the mechanical structure of the tendinous apparatus can influence motor learning. Moreover, disruption of learning or recall of these mappings can easily lead to motor pathologies.```
Author
`Cohn BA, Jalaleddini K, Valero-Cuevas FJ`
BibTex
```@inproceedings
"@article{cohn2017-asb-neuromechanical-posture,
  title={Neuromechanical implications of postural changes to motor learning and performance},
  author={Cohn BA, Jalaleddini K, Valero-Cuevas FJ},
booktitle={Proceedings of the 41st Annual Meeting of the American Society of Biomechanics, Denver, CO},
  volume={},
  year={2017}
}

Year: 2017
Journal: American Society of Biomechanics
SupplementalLink:

Create postdoc advertisement

Who we are:

The Brain-Body Dynamics Lab, led by Prof. Francisco Valero-Cuevas, is dedicated to understanding neuromuscular control and the interaction between neural systems and biomechanical/robotic systems.

Our laboratory consists of an interdisciplinary group of graduate and undergraduate students, post-doctoral fellows, clinicians, and faculty in engineering, computer science, mathematics and bioengineering.
Further information about our laboratory can be found at: bbdl.usc.edu

Who we are looking for:

Our laboratory is accepting applications for an NIH funded post-doctoral fellowship to understand the neuromuscular control of complex tendon-driven systems, and reverse-engineer brain function in collaboration with Profs. Terry Sanger, and Jerry Loeb.

We are looking for candidates to implement models of neural circuitry and muscle function for simulation purposes or in real-time to control hardware-in-the loop systems. Successful applicants will have strong backgrounds in control and estimation of nonlinear systems, computational neuroscience, mechatronics, computational methods, robotics, and/or biomechanical modeling. Expertise in computer languages is necessary.

The successful candidate must have a Ph.D. in engineering, bioengineering or neuroscience; and a strong interest in neuromuscular control. She/he must have experience in at least two of the following: control & estimation of nonlinear or biological systems; computational modeling; and experimental design of electromechanical systems. Preference will be given to applicants with experience in neuroscience.

Nice to have:

Understanding of physiology/pathophysiology of the neuromuscular system, spinal reflex circuitry, muscle afferentation, and biomechanics of musculotendinous complex.
Experience in time and frequency-domain analysis of biomedical signals and systems, digital signal processing and system identification.
Experience in programming in MATLAB, Python or R for model simulation and data analysis purposes.
Familiarity with continuous-time, discrete-time, FIR/IIR, transfer-function, state-space representations of dynamic systems.
Experience in object oriented programming.
Knowledge of C/C++.
Knowledge of Verilog and experience working with FPGA.
Hands on experience in real-time control system design.
Hands on experience in biomedical instrumentation and signal conditioning.
Hands on experience with data acquisition system.
How to Apply:

For consideration, please submit your application (preferably in one single PDF document) including cover letter, a full CV, a statement of research interests and career goals and the names and email addresses of three references to Prof. Valero-Cuevas. Please write “Postdoctoral/Research Associate Position� in the subject line.

The position is available immediately, and applications will be received until the position is filled. The University of Southern California offers competitive salary and benefits.

v2 post-launch fixes

about/

  • reduce bio lengths in about
  • fix spacing for Fco bio
  • get links to lab alumni (make them underlined)
  • create 3 columns for lab alumni, flex to 2 column on mobile
  • too spaced out on Fundamentals. group the elements together.
  • request new picture from taegyum, theo, priyanka, dan, séb
  • pictures for Melissa and Maral and Allison
  • reduce font size of publications so you can fit each year on a page
  • put year indicators on the page; visual breaks by year
  • bibtex copied to clipboard tooltip

Search Function

The Search Function does not work in the "Publication" pages. The search box is just a box without any action. @briancohn

Hi: Please add my paper to the website. Thanks

Hi: Please add my paper to the website. Thanks

Title:
Finger movements are mainly represented by a linear transformation of energy in band-specific ECoG signals

Link:http://ieeexplore.ieee.org/abstract/document/8036991/

Abstract:
Electrocardiogram (ECoG) recordings are very attractive for Brain Machine Interface (BMI) applications due to their balance between good signal to noise ratio and minimal invasiveness. The design of ECoG signal decoders is an open research area to date which requires a better understanding of the nature of these signals and how information is encoded in them. In this study, a linear and a non-linear method, Linear Regression Model (LRM) and Artificial Neural Network (ANN) respectively, were used to decode finger movements from energy in band-specific ECoG signals. It is shown that the ANN only slightly outperformed the LRM, which suggests that finger movements are mainly represented by a linear transformation of energy in band-specific ECoG signals. In addition, comparing our results to similar Electroencephalogram (EEG) studies illustrated that the spatio-temporal summation of multiple neural signals is itself linearly correlated with movement, and is not an artifact introduced by the scalp or cranium. Furthermore, a new algorithm was employed to reduce the number of spectral features of the input signals required for either of the decoding methods.

Authors:

Ali Marjaninejad, Babak Taherian, Francisco J. Valero-Cuevas
BibTex:

@inproceedings{marjaninejad2017finger,
title={Finger movements are mainly represented by a linear transformation of energy in band-specific ECoG signals},
author={Marjaninejad, Ali and Taherian, Babak and Valero-Cuevas, Francisco J},
booktitle={Engineering in Medicine and Biology Society (EMBC), 2017 39th Annual International Conference of the IEEE},
pages={986--989},
year={2017},
organization={IEEE}
}

Year:
2017

Journal:
Published in: Engineering in Medicine and Biology Society (EMBC), 2017 39th Annual International Conference of the IEEE

SupplementalLink:
The code is shared on github at:
https://github.com/marjanin/Ali-Marjaninejad-et.-al.-2017-code

Add Dan's paper to the website

Similar movements are associated with drastically different muscle contraction velocities

Paper/Hagen2017Similar.pdf

We investigated how kinematic redundancy interacts with the neurophysiological control mechanisms required for smooth and accurate, rapid limb movements. Biomechanically speaking, tendon excursions are over-determined because the rotation of few joints determines the lengths and velocities of many muscles. But how different are the muscle velocity profiles induced by various, equally valid hand trajectories? We used an 18-muscle sagittal-plane arm model to calculate 100,000 feasible shoulder, elbow, and wrist joint rotations that produced valid basketball free throws with different hand trajectories, but identical initial and final hand positions and velocities. We found large differences in the eccentric and concentric muscle velocity profiles across many trajectories; even among similar trajectories. These differences have important consequences to their neural control because each trajectory will require unique, time-sensitive reflex modulation strategies. As Sherrington mentioned a century ago, failure to appropriately silence the stretch reflex of any one eccentrically contracting muscle will disrupt movement. Thus, trajectories that produce faster or more variable eccentric contractions will require more precise timing of reflex modulation across motoneuron pools; resulting in higher sensitivity to time delays, muscle mechanics, excitation/contraction dynamics, noise, errors and perturbations. By combining fundamental concepts of biomechanics and neuroscience, we propose that kinematic and muscle redundancy are, in fact, severely limited by the need to regulate reflex mechanisms in a task-specific and time-critical way. This in turn has important consequences to the learning and execution of accurate, smooth and repeatable movements—and to the rehabilitation of everyday limb movements in developmental and neurological conditions, and stroke.

Hagen DA, Valero-Cuevas FJ

"@Article{hagen2017similar,
title={Similar movements are associated with drastically different muscle contraction velocities},
author={Hagen, Daniel A and Valero-Cuevas, Francisco J},
journal={Journal of Biomechanics},
year={2017},
publisher={Elsevier}
}
"

2017

Journal of Biomechanics

anton update bio

Grenoble Alpes University, Gipsa-Lab Laboratory

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sign up for iStart

  • Hannah
  • Kian
  • Victor
  • Brian
  • Jun
  • Brian
  • Dan
  • Meng-fen
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  • Ali

Tremor II paper

Title: Physiological tremor increases when skeletal muscle is shortened: implications for fusimotor control.

Jalaleddini_et_al-2017-The_Journal_of_Physiology.pdf

Abstract: The involuntary force fluctuations associated with physiological (as distinct from
pathological) tremor are an unavoidable component of human motor control.While the origins
of physiological tremor are known to depend on muscle afferentation, it is possible that
the mechanical properties of muscle–tendon systems also affect its generation, amplification
and maintenance. In this paper, we investigated the dependence of physiological tremor on
muscle length in healthy individuals. We measured physiological tremor during tonic, isometric
plantarflexion torque at 30% of maximum at three ankle angles. The amplitude of
physiological tremor increased as calf muscles shortened in contrast to the stretch reflex whose
amplitude decreases as muscle shortens. We used a published closed-loop simulation model of
afferentedmuscle to explore the mechanisms responsible for this behaviour.We demonstrate that
changingmuscle lengths does not suffice to explain our experimental findings. Rather, the model
consistently required the modulation of γ-static fusimotor drive to produce increases in physiological
tremor withmuscle shortening – while successfully replicating the concomitant reduction
in stretch reflex amplitude. This need to control γ-static fusimotor drive explicitly as a function of
muscle length has important implications. First, it permits the amplitudes of physiological tremor
and stretch reflex to be decoupled. Second, it postulates neuromechanical interactions that require
length-dependent γ drivemodulation to be independent fromα drive to the parentmuscle. Lastly,
it suggests that physiological tremor can be used as a simple, non-invasivemeasure of the afferent
mechanisms underlying healthy motor function, and their disruption in neurological conditions.

Authors: Jalaleddini K, Nagamori A, Laine CM, Golkar MA, Kearney RE, Valero‐Cuevas FJ.

@Article{jalaleddini2017physiological,
title={Physiological tremor increases when skeletal muscle is shortened: implications for fusimotor control},
author={Jalaleddini, Kian and Nagamori, Akira and Laine, Christopher M and Golkar, Mahsa A and Kearney, Robert E and Valero-Cuevas, Francisco J},
journal={The Journal of physiology},
volume={595},
number={24},
pages={7331--7346},
year={2017},
publisher={Wiley Online Library}
}

Year: 2017
Journal: Journal of physiology.

New Publication

Title:
Cardinal features of involuntary force variability can arise from the closed-loop control of viscoelastic afferented muscles

journal.pcbi.1005884.pdf

Abstract:
Author summary Involuntary fluctuations in muscle force are an unavoidable consequence of human motor control and underlie movement execution errors. Amplification and distortion of involuntary force variability are common phenomena found in various neurological conditions and in fatigue. However, the underlying mechanisms for this are often unclear. We investigated the generation and modulation of involuntary force variability arising from different sources, as well as their interactions. We used a closed-loop simulation which included a physiologically-grounded model of an afferented musculotendon and an error-controller. We show that interactions among neural noise, musculotendon mechanics, proprioceptive feedback, and error correction are critical components of force control, and by taking these into account, our model was able to both replicate and explain many cardinal features of involuntary force variability previously reported experimentally. Also, our results suggest previously unrecognized pathways through which force variability may be altered in fatigue and in certain neurological diseases. Finally, we emphasize the potential for important clinical and scientific information to be extracted from relatively simple, non-invasive measurements of force.

Author:
Nagamori A, Laine CM, Valero-Cuevas FJ.

"@Article{nagamori2018cardinal,
title={Cardinal features of involuntary force variability can arise from the closed-loop control of viscoelastic afferented muscles},
author={Nagamori, Akira and Laine, Christopher M and Valero-Cuevas, Francisco J},
journal={PLOS Computational Biology},
volume={14},
issue = {1},
year={2018}
}"

Year:
2018

Journal:
PLOS Computational Biology

Conference Paper

The neural control of movement must contend with trajectory-specific and nonlinearly distorted manifolds of afferent muscle spindle activity

Papers/BerryIJCNN17.pdf

We introduce the concept of trajectory-specific sensory manifolds. They are the unique multidimensional and time-varying combinations of afferent signals that obligatorily emerge during a limb movement. We use the example of muscle spindles (i.e., the muscle's proprioceptors for length and velocity) that arise during movements of an arm (a planar 2-DOF 6-muscle model) during the production of straight, curved and oscillatory hand movements. Through the use of parallel coordinates, we visualize the high-dimensional evolution of the afferent signaling across muscles and tasks. We demonstrate that a given movement gives rise to a distinct sensory manifold embedded in the 12-D space of spindle information that is largely independent of the choice of muscle coordination strategy. Given that muscle lengths and velocities are fully determined by joint kinematics, such manifolds provide a rich set of information to use in its control.

Berry JA, Ritter R, Nagamori A, Valero-Cuevas, FJ.

"@inproceedings{berry2017neural,
title={The neural control of movement must contend with trajectory-specific and nonlinearly distorted manifolds of afferent muscle spindle activity},
author={Berry, Jasmine A and Ritter, Robert and Nagamori, Akira and Valero-Cuevas, Francisco J},
booktitle={Neural Networks (IJCNN), 2017 International Joint Conference on},
pages={1188--1194},
year={2017},
organization={IEEE}
}
"

2017

IEEE International Joint Conference on Neural Networks (IJCNN) 2017

BBDL Lab meeting updates - Prep for bbdl->valerolabport

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Here is my ASB information

title:Simple and Two-Element Hill-Type Muscle Models
Cannot Replicate Realistic Muscle Stiffness
link:
http://valerolab.org/marjani/Papers_and_Abstracts/Ali_ASB_2017_Abstract_website.pdf

Full Abstract:

INTRODUCTION
An important functional property of muscle is to
provide stiffness for the limbs [1]. Joint and limb
endpoint stiffnesses are critical to control limb
posture, movement and interaction with the
environment [1,2]. In general, stiffness produces
instantaneous resistance to change in muscle length.
Stiffness is known to be modulated muscle length
(i.e., by joint angles) and muscle activation levels
(i.e. α drive) [3], but the mechanisms that produce
them remain unclear.
Hill-type models are a class of normalized lumpedparameter models of muscle of varying complexities
that can be scaled to approximate specific muscles.
They estimate muscle force as functions of muscle
architecture (physiological cross sectional area and
pennation angle), kinematic state of muscle (length,
and velocity) and the muscle activation level (α
drive) [4,5]. The goal of this project is to assess the
ability of Hill-type models to produce muscle
stiffness [6].

METHODS
In this project, we studied versions of two popular
Hill-type muscle models. The first model is a simple
linear model consisting of series and parallel springs,
a viscous element and a contractile element referred
herein as the simple Hill-type model without forcelength properties (or the Hill-type w/o fl) [4]. The
contractile element converts the α drive to active
muscle force. This model, as presented, did not have
force-length properties. Thus, we modified it by
adding force-length properties to it (i.e., Hill-type w
fl). The two-element Hill-type model incorporates two
parallel active contractile elements for slow and fast
muscle fibers (i.e., Two-Element model) [5]. Note
that the active force-length
Figure 1: Stiffness as a function of muscle length.
properties of muscle (included in the contractile
element) are not equivalent to the Hook’s law stressstrain relationship. Rather, they represent the active
force the muscle can produce at each length for a
given activation level [7].
We estimated muscle stiffness in quasi-static
condition by applying ten small displacements (of
2.5% L0, where L0 is the optimal muscle length) with
the muscle lengths set between 0.5 L0 and 1.8 L0
while the muscle was fully activated. We also
calculated values of stiffness at two lengths (0.8 and
1.2 L0) for α drive ranging between 0 to 100 percent
in steps of 1%.

RESULTS AND DISCUSSION
Figure 1 shows stiffness for all models as a function
of normalized muscle length. To make figures easier
to compare, all figures are normalized to their
maximum absolute value. Stiffness for the simple
Hill-type model without force-length properties does
not depend on muscle length (red). Stiffness varies as
a function of muscle length for the other two models
(blue and green). However, it becomes negative at
some lengths. It is clear that the negative stiffness is
not physically possible since it results in instability.
Both of the two-Element and modified Hill-type41st Annual Meeting of the American Society of Biomechanics, Boulder, CO, USA, August 8th – 11th, 2017
Figure 2: Stiffness as a function of muscle lengths
equal to 0.8 L0 (solid lines) and 1.2 L0 (dashed lines).
models, however, show patterns similar to that
reported in experiments in their non-negative regions
[8]. Figure 2 shows the stiffness for all models as a
function of muscle activation level at two
representative muscle lengths (0.8, 1.2 L0). Once
again, stiffness is not a function of muscle activation
in the absence of force-length properties (red).
Stiffness for the two-Element model does vary with
the muscle activation level for the other two models
in a length-dependent manner (blue and green).
Interestingly, this change in the stiffness was
consistent with the relative proportions of the
derivatives of the active and passive parts of the
force-length curve. i.e. the more the activation, the
larger the weight of the active part. This result is
expected considering that activation applies only to
the active part of the force-length curve of muscle.
As can be seen on the figures, the stiffness can be
negative for both length dependent models (blue and
green) when the muscle length is longer than L0,
which demonstrates that the models fail to replicate
realistic muscle stiffness.

CONCLUSIONS
Our results show the simplest Hill-type model fails
to reproduce both muscle length and activation
dependence of stiffness. The modified and twoelement Hill-type muscle models produced stiffness
dependence on muscle length and activation, but
invariably produce negative stiffness at some muscle
lengths, which is not physically realistic. Although
force-length properties are very important in
explaining stiffness [1,2], Hill-type models cannot
replicate realistic muscle stiffness even when
including presence of force-length properties.
Future work will explore if dynamic simulations (as
opposed to this quasi-static version) and other
extensions, such as the inclusion of force-velocity
properties, can produce realistic muscle stiffness. If
those efforts are unsuccessful, other models such as
population-, fiber- and sarcomere-based—although
more computationally complex—would need to be
preferred.

REFERENCES

  1. Inouye J. M, and Valero-Cuevas F. J. PLoS
    Comput Biol, 12, p. e1004737, 2016.
  2. Babikian S, et al. J. Nonlinear Sci., 26, 1293–
    1309, 2016.
  3. Mirbagheri M. M. Exp. Brain Res.et al. 135, 423–
    436, 2000.
  4. Shadmehr R, and Wise S. P, MIT press, 2005.
  5. Lee S. S. M, et al. J. Biomech., 46, 2288–2295,
  6. Valero-Cuevas F. J, et al. IEEE Rev. Biomed.
    Eng, 12, 110-135, 2009
  7. Valero-Cuevas F. J. Fundamentals of
    neuromechanics, Springer, 2015
  8. Weiss P.L, et al. J. Biomech., 19, 727-735,1986.

ACKNOWLEDGMENTS
This study was supported by NIH-NIAMS under
award numbers R01AR050520 and R01AR052345
grants to FVC. This project is also supported by USC
graduate school’s provost fellowship to A.

Authors: Ali Marjaninejad, Babak Taherian, Kian Jalaleddini, and Francisco J Valero-Cuevas

Bibtex:
"
@inproceedings{,
address = {Boulder, Colorado, USA},

booktitle = {American Society for Biomechanics},

pages = {2},
title = {{Simple and Two-Element Hill-Type Muscle Models Cannot Replicate Realistic Muscle Stiffness}},

year = {2017}
}

"

Year:
2017

Conf:
ASB

SupplementalLink (Link to the poster):
http://valerolab.org/marjani/Papers_and_Abstracts/Ali_ASB_2017_Poster_website.pdf

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