Publications
2024
Millard M, Franklin DW, and Herzog W (2024) A three filament mechanistic model of musculotendon force and impedance. eLife (12), pp RP88344. https://doi.org/10.7554/eLife.88344.4
Schmidt A, Forano M, Sachtler A, Calzolari D, Weber BM, Franklin DW, and Albu-Schaffer (2024) Finding the rhythm: Humans exploit nonlinear intrinsic dynamics of compliant systems in periodic interaction tasks. PLoS Computational Biology 20(9), pp. e1011478. https://doi.org/10.1371/journal.pcbi.1011478
Forano M, and Franklin DW (2024) Reward actively engages both implicit and explicit components in dual force field adaptation. Journal of Neurophysiology, 132(1), pp 1-22. https://doi.org/10.1152/jn.00307.2023
Leib R, Howard IS, Millard M, and Franklin DW (2024) Behavioral Motor Performance. Comprehensive Physiology, 14(1), pp 5179-5224. https://doi.org/10.1002/cphy.c220032
2023
Franklin S, and Franklin DW (2023) Visuomotor feedback tuning in the absence of visual error information. Neurons, Behavior, Data Analysis and Theory, pp1-31, https://doi.org/10.51628/001c.91252.
Orschiedt J, and Franklin DW (2023) Learning context shapes bimanual control strategy and generalization of novel dynamics. PLoS Computational Biology, https://doi.org/10.1371/journal.pcbi.1011189
Kunavar T, Cheng X, Franklin DW, Burdet E and Babič, Jan (2023) Explicit learning based on reward prediction error facilitates agile motor adaptations. PLoS one, e0295274, https://doi.org/10.1371/journal.pone.0295274
Torell F, Franklin S, Franklin DW, Dimitriou M (2023) Goal-directed modulation of stretch reflex gains is reduced in the non-dominant upper limb. European Journal of Neuroscience, vol 58 pp.3981-4001. https://doi.org/10.1111/ejn.16148
Liu Y, Leib R and Franklin DW (2023) Follow the Force: Haptic Communication Enhances Coordination in Physical Human-Robot Interaction When Humans are Followers, IEEE Robotics and Automation Letters, vol. 8, no. 10, pp. 6459-6466, doi: 10.1109/LRA.2023.3307006.
Franklin S, Leib R, Dimitriou M, and Franklin DW (2023) Congruent visual cues speed dynamic motor adaptation. Journal of Neurophysiology 130 (2), 319-331. https://doi.org/10.1152/jn.00060.2023
Chen, Z., Franklin, D.W. (2023) Musculotendon Parameters in Lower Limb Models: Simplifications, Uncertainties, and Muscle Force Estimation Sensitivity. Ann Biomed Eng 51, 1147–1164. https://doi.org/10.1007/s10439-023-03166-5
2022
Česonis J, and Franklin DW (2022), Contextual cues are not unique for motor learning: Task-dependant switching of feedback controllers, PLoS Computational Biology, 18, e1010192
Newrzella SR, Franklin DW, and Haider S (2022), Three-Dimension Digital Twin Reference Architecture Model for Functionality, Dependability, and Life Cycle Development Across Industries, IEEE Access 10, 95390-95410
Leib R, Franklin S, Česonis J, and Franklin DW (2022), Stability of inverted pendulum reveals transition between predictive control and impedance control in grip force modulation, 2022 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC). 1481-1484.
Günter C, Liu Y, Leib R, and Franklin DW (2022), Force Control During the Precision Grip Translates to Virtual Reality, 2022 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC). 4171-4174.
Liu Y, Günter C, Leib R, and Franklin DW (2022), Learning of Dexterous Object Manipulation in a Virtual Reality Environment, 2022 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC). 4175-4178.
Liu Y, Günter C, Leib R, and Franklin DW (2022), Bimanual Manipulation of a Complex Object with Internal Dynamics, 2022 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC). 4119-4122.
Newrzella SR, Franklin DW, and Haider S (2022), Methodology for Digital Twin Use Cases: Definition, Prioritization, and Implementation, IEEE Access 10, 75444-75457
Izadi M, Franklin S, Bellafiore M, and Franklin DW (2022). Motor Learning in Response to Different Experimental Pain Models among Healthy Individuals: A Systematic Review, Frontiers in Human Neuroscience, 16
2021
Forano M, Schween R, Taylor JA, Hegele M, and Franklin DW (2021). Direct and indirect cues can enable dual adaptation, but through different learning processes. Journal of Neurophysiology 126: 1490-1506.
Česonis J and Franklin DW (2021) Mixed-horizon optimal feedback control as a model of human movement. Neurons, Behavior, Data Analysis and Theory. https://doi.org/10.51628/001c.29674
Lanillos P, Franklin S, Maselli A, and Franklin DW (2021) Active strategies for multisensory conflict suppression in the virtual hand illusion. Scientific Reports. https://doi.org/10.1038/s41598-021-02200-7
Newrzella, SR, Franklin DW, and Haider S (2021) 5-Dimension Cross-Industry Digital Twin Applications Model and Analysis of Digital Twin Classification Terms and Models. IEEE Access 9, 131306-131321
Franklin S, and Franklin DW (2021) Feedback Gains modulate with motor memory uncertainty. Neurons, Behavior, Data Analysis and Theory. https://doi:10.51628/001c.22336
2020
Lee S, Franklin S, Hassani FA, Yokota T, Nayeem MOG, Wang Y, Leib R, Cheng G, Franklin DW, Someya T (2020) Nanomesh pressure sensor for monitoring finger manipulation without sensory interference. Science 370: 966-970.
Forano M and Franklin DW (2020) Timescales of motor memory formation in dual-adaptation. PLoS Computational Biology 16(10): e1008373. https://doi.org/10.1371/journal.pcbi.1008373
Česonis J and Franklin DW (2020) Time-to-target explains task-dependent modulation of temporal feedback gain evolution. eNeuro 7(2): ENEURO.0514-19.2020
Howard IS, Franklin S and Franklin DW (2020) Asymmetry in kinematic generalization between visual and passive lead-in movements are consistent with a forward model in the sensorimotor system. PloS one 15 (1), e0228083
2019
Leib R, Česonis J, Franklin S, and Franklin DW (2019) LQG framework explains performance of balancing inverted pendulum with incongruent visual feedback. Engineering in Medicine and Biology Society (Proceedings of EMBC), 1940-1943
Česonis J, Leib R, Franklin S and Franklin DW (2019) Controller Gains of an Inverted Pendulum are Influenced by the Visual Feedback Position. Engineering in Medicine and Biology Society (Proceedings of EMBC), 5068-5071
Franklin S, Česonis J, Leib R, and Franklin DW (2019) Feedback Delay Changes the Control of an Inverted Pendulum. Engineering in Medicine and Biology Society (Proceedings of EMBC), 1517-1520
Franklin DW, Česonis J, Franklin S and Leib R (2019) A Technique for Measuring Visuomotor Feedback Contributions to the Control of an Inverted Pendulum. Engineering in Medicine and Biology Society (Proceedings of EMBC), 1513-1516
2018
Heald JB, Franklin DW and Wolpert DM (2018) Increasing muscle co-contraction speeds up internal model acquisition during dynamic motor learning. Scientific Reports 8(1): 16355
Millard M, Franklin DW and Herzog W (2018) A Continuous and Differentiable Mechanical Model of Muscle Force and Impedance. International Symposium on Wearable Robotics, 262-266
Howard IS, Franklin S Franklin DW (2018) Characterization of Neural Tuning: Visual Lead-in Movements Generalize in Speed and Distance. International Conference on NeuroRehabilitation, 1030-1033
Franklin S, Česonis J and Franklin DW (2018) Influence of Visual Feedback on the Sensorimotor Control of an Inverted Pendulum. Engineering in Medicine and Biology Society (Proceedings of EMBC), 5170-5173
Česonis J, Franklin S and Franklin DW (2018) A Simulated Inverted Pendulum to Investigate Human Sensorimotor Control. Engineering in Medicine and Biology Society (Proceedings of EMBC), 5166-5169
2017
Franklin S, Wolpert DM and Franklin DW (2017)
Rapid visuomotor feedback gains are tuned to the task dynamics
Journal of Neurophysiology 118(5), 2711-2726
Howard IS, Ford C, Cangelosi A and Franklin DW (2017)
Active lead-in variability affects motor memory formation and slows motor learning
Scientific Reports DOI:10.1038/s41598-017-05697-z
2016
Yeo S-H, Franklin DW and Wolpert DM (2016)
When optimal feedback control is not enough: feedforward strategies are required for optimal control with active sensing
PLoS Comp Biol 12(12): e1005190. doi:10.1371/journal. pcbi.1005190
Supplementary Materials available here.
Sheahan HR, Franklin DW and Wolpert DM (2016)
Motor planning, not execution, separates motor memories
Neuron 92, 773-779
See the Preview in Neuron by O'Shea and Shenoy
Franklin DW, Batchelor AV and Wolpert DM (2016)
The sensorimotor system can sculpt behaviorally relevant representations for motor learning.
eNeuro 3(4) DOI:http://dx.doi.org/10.1523/ENEURO.0070-16.2016
Howard IS and Franklin DW (2016)
Adaptive tuning functions arise from visual observation of past movement.
Scientific Reports DOI: 10.1038/srep28416
Franklin DW, Reichenbach A, Franklin S and Diedrichsen J (2016)
Temporal evolution of spatial computations for visuomotor control.
Journal of Neuroscience 36, 2329-2341
Franklin DW (2016)
Rapid feedback responses arise from pre-computed gains.
Motor Control 20, 171-176
2015
Howard IS and Franklin DW (2015)
Neural tuning functions underlie both generalization and interference.
PLoS ONE 10(6): e0131268. doi:10.1371/journal.pone.0131268
Yeo S-H, Wolpert DM and Franklin DW (2015)
Coordinate representations for interference reduction in motor learning.
PLoS ONE 10(6): e0129388. doi:10.1371/journal.pone.0129388
Franklin DW (2015)
Impedance control: Learning stability in human sensorimotor control.
Engineering in Medicine and Biology Society (Proceedings of EMBC), 1421-1424
Howard IS, Wolpert DM and Franklin DW (2015)
The value of the follow-through derives from motor learning depending on future actions.
Current Biology 25: 397-401
2014
Franklin DW, Franklin S and Wolpert DM (2014)
Fractionation of the visuomotor feedback response to directions of movement and perturbation.
Journal of Neurophysiology 112: 2218-2233
Reichenbach A, Franklin DW, Zatka-Haas P, Diedrichsen J (2014)
A dedicated binding mechanism for the visual control of movement.
Current Biology 24: 780-785
Burk D, Ingram JN, Franklin DW, Shadlen MN and Wolpert DM (2014)
Motor effort alters changes of mind in sensorimotor decision making.
PLoS ONE 9(3): e92681. doi:10.1371/journal.pone.0092681
Berniker M, Franklin DW, Flanagan JR, Wolpert DM and Kording K (2014)
Motor learning of novel dynamics is not represented in a single global coordinate system: evaluation of mixed coordinate representations and local learning
Journal of Neurophysiology 111: 1165-1182
2013
Dimitriou M, Wolpert DM and Franklin DW (2013)
The temporal evolution of feedback gains rapidly update to task demands
Journal of Neuroscience 33(26):10898-10909
Howard IS, Wolpert DM and Franklin DW (2013)
The effect of contextual cues on the encoding of motor memories
Journal of Neurophysiology 109: 2632-2644
2012
Howard IS, Ingram JN, Franklin DW and Wolpert DM (2012)
Gone in 0.6 seconds: The encoding of motor memories depends on recent sensorimotor states
Journal of Neuroscience 32(37):12756-12768
Franklin S, Wolpert DM and Franklin DW (2012)
Visuomotor feedback gains up-regulate during the learning of novel dynamics
Journal of Neurophysiology 108: 467-478
Dimitriou M, Franklin DW and Wolpert DM (2012)
Task-dependent coordination of rapid bimanual motor responses
Journal of Neurophysiology 107: 890-901
Kadiallah A, Franklin DW and Burdet E (2012)
Generalization in adaptation to stable and unstable dynamics
PLoS ONE, 7(10): e45075. doi:10.1371/journal.pone.004507
2011
Franklin DW and Wolpert DM (2011)
Computational mechanisms of sensorimotor control
Neuron, 72: 425-442
Franklin DW, and Wolpert DM (2011)
Reflex modulation: a window into cortical function
Current Biology, 21: R924-R926
Kadiallah A, Liaw G, Kawato M, Franklin DW and Burdet E (2011)
Impedance control is selectively tuned to multiple directions of movement
Journal of Neurophysiology, 106:2737-2748
2010
Tee KP, Franklin DW, Milner TE, Kawato M, and Burdet E (2010)
Concurrent adaptation of force and impedance in the redundant muscle system
Biological Cybernetics, 102, 31-44
2009
Selen LPJ, Franklin DW, and Wolpert DM (2009)
Impedance control reduces instability that arises from motor noise
Journal of Neuroscience, 29, 12606-12616
2008
Franklin DW, and Wolpert DM (2008)
Specificity of reflex adaptation for task-relevant variability
Journal of Neuroscience, 28, 14165-14175
Franklin DW, Burdet E, Tee KP, Osu R, Chew CM, Milner TE, and Kawato M (2008)
CNS learns stable, accurate, and efficient movements using a simple algorithm
Journal of Neuroscience, 28, 11165-11173
2007
Franklin DW, So U., Burdet E, and Kawato M (2007)
Visual feedback is not necessary for the learning of novel dynamics
PLoS ONE. 2(12): e1336. doi:10.1371/journal.pone.0001336
Franklin DW, Liaw G, Milner TE, Osu, R, Burdet E, and Kawato M (2007)
Endpoint stiffness of the arm is directionally tuned to instability in the environment
Journal of Neuroscience, 27, 7705-7716
Milner TE, Hinder MR, and Franklin DW (2007)
How is somatosensory information used to adapt to changes in the mechanical environment?
Progress in Brain Research, 165, 363-372
Milner T, Franklin DW, Imamizu H, and Kawato M (2007)
Central control of grasp: manipulation of objects with simple and complex dynamics
NeuroImage, 36: 388-95
Ganesh G, Franklin DW, Gassert R, Imamizu H, and Kawato M (2007)
Accurate Real-time Feedback of Surface EMG during fMRI
Journal of Neurophysiology, 97: 912-20
2006
Milner TE, Franklin DW, Imamizu H, and Kawato M (2006)
Central representation of stability during performance of motor tasks
Journal of Neurophysiology, 95, 893-901
Burdet E, Tee KP, Mareels I, Milner TE, Chew CM, Franklin DW, Osu R, and Kawato M(2006)
Stability and motor adaptation in human arm movements
Biological Cybernetics, 94, 20-32
2005
Oztop E, Franklin DW, Chaminade T, and Cheng, G (2005)
Human-humanoid Interaction: Is a humanoid robot perceived as a human?
International Journal of Humanoid Robotics, 2: 537-559
Milner T, and Franklin DW (2005)
Impedance control and internal model formation during the initial stage of adaptation to novel dynamics
Journal of Physiology, 567, 651-664
2004
Franklin DW, So U, Kawato M, and Milner TE (2004)
Impedance control balances stability with metabolically costly muscle activation
Journal of Neurophysiology. 92, 3097-3105
2003
Franklin DW, Osu R, Burdet E, Kawato M, and Milner TE (2003)
Adaptation to stable and unstable dynamics achieved by combined impedance control and inverse dynamics model
Journal of Neurophysiology. 90, 3270-3282
Franklin DW, Burdet E, Osu R, Kawato M, and Milner TE (2003)
Functional significance of stiffness in adaptation of multijoint arm movements to stable and unstable environments
Experimental Brain Research. 151, 145-157
Franklin DW, and Milner TE (2003)
Adaptive control of stiffness to stabilize hand position with large loads
Experimental Brain Research. 152, 211-220
Osu R, Burdet E, Franklin DW, Milner TE, and Kawato M (2003)
Different mechanisms involved in adaptation to stable and unstable dynamics
Journal of Neurophysiology. 90, 3255-3269
2002
Osu R, Franklin DW, Kato H, Gomi H, Domen K, Yoshioka T, and Kawato M (2002)
Short- and long-term changes in joint co-contraction associated with motor learning as revealed from surface EMG
Journal of Neurophysiology, 88, 991-1004
2001
Burdet E, Osu R, Franklin DW, Milner TE, and Kawato M (2001)
The central nervous system stabilizes unstable dynamics by learning optimal impedance
Nature 414, 446-449
2000 and prior
Burdet E, Osu R, Franklin DW, Yoshioka T, Milner TE, and Kawato M (2000)
A method for measuring hand stiffness during voluntary arm movements
Journal of Biomechanics 33, 1705-1709
Milner TE, and Franklin DW (1998)
Characterization of human fingertip stiffness in two dimensions: Dependence on finger posture and force direction
IEEE Transactions on Biomedical Engineering 45(11), 1363-1375
Milner TE, Cloutier CC, Leger AB, and Franklin DW (1995)
Inability to activate muscles maximally during cocontraction and the effects on joint stiffness
Experimental Brain Research 107, 293-305