Cortical model with reinforcement learning drives realistic virtual arm (Dura-Bernal et al 2015)


Dura-Bernal S et al. (2015). Cortical Spiking Network Interfaced with Virtual Musculoskeletal Arm and Robotic Arm. Frontiers in neurorobotics. 9 [PubMed]

See more from authors: Dura-Bernal S · Zhou X · Neymotin SA · Przekwas A · Francis JT · Lytton WW

References and models cited by this paper

Almássy N, Edelman GM, Sporns O. (1998). Behavioral constraints in the development of neuronal properties: a cortical model embedded in a real-world device. Cerebral cortex (New York, N.Y. : 1991). 8 [PubMed]

Alstermark B, Isa T. (2012). Circuits for skilled reaching and grasping. Annual review of neuroscience. 35 [PubMed]

Barrett Tech. (2012). WAM Training Documentation.

Bergenheim M, Ribot-Ciscar E, Roll JP. (2000). Proprioceptive population coding of two-dimensional limb movements in humans: I. Muscle spindle feedback during spatially oriented movements. Experimental brain research. 134 [PubMed]

Berger DJ, d'Avella A. (2014). Effective force control by muscle synergies. Frontiers in computational neuroscience. 8 [PubMed]

Carmena JM. (2013). Advances in neuroprosthetic learning and control. PLoS biology. 11 [PubMed]

Carrillo RR, Ros E, Boucheny C, Coenen OJ. (2008). A real-time spiking cerebellum model for learning robot control. Bio Systems. 94 [PubMed]

Chadderdon GL, Neymotin SA, Kerr CC, Lytton WW. (2012). Reinforcement learning of targeted movement in a spiking neuronal model of motor cortex. PloS one. 7 [PubMed]

Choi J, Sanchez J, Tarigoppula A, Marsh B, Chhatbar P. (2011). Control of a center-out reaching task using a reinforcement learning brain-machine interface Neural Engineering (NER), 2011 5th International IEEE-EMBS Conference on. IEEE.

DeWolf T, Eliasmith C. (2011). The neural optimal control hierarchy for motor control. Journal of neural engineering. 8 [PubMed]

Demandt E et al. (2012). Reaching movement onset- and end-related characteristics of EEG spectral power modulations. Frontiers in neuroscience. 6 [PubMed]

Dura-Bernal S, Chadderdon GL, Neymotin SA, Francis JT, Lytton WW. (2014). Towards a real-time interface between a biomimetic model of sensorimotor cortex and a robotic arm. Pattern recognition letters. 36 [PubMed]

Edelman GM. (1987). Neural Darwinism: The Theory of Neuronal Group Selection.

Et AL et al. (1887). Evaluating hebbian reinforcement learning bmi using an in silico brain model and a virtual musculoskeletal arm Neural Control of Movement.

Fagg AH et al. (2007). Biomimetic brain machine interfaces for the control of movement. The Journal of neuroscience : the official journal of the Society for Neuroscience. 27 [PubMed]

Flint RD, Lindberg EW, Jordan LR, Miller LE, Slutzky MW. (2012). Accurate decoding of reaching movements from field potentials in the absence of spikes. Journal of neural engineering. 9 [PubMed]

Francis JT. (2009). The neural representation of kinematics and dynamics in multiple brain regions: the use of force field reaching paradigms in the primate and rat Mechanosensitivity of the Nervous System, Mechanosensitivity in Cells and Tissues. 2

Hatsopoulos N, Joshi J, O'Leary JG. (2004). Decoding continuous and discrete motor behaviors using motor and premotor cortical ensembles. Journal of neurophysiology. 92 [PubMed]

Hines ML, Carnevale NT. (2001). NEURON: a tool for neuroscientists. The Neuroscientist : a review journal bringing neurobiology, neurology and psychiatry. 7 [PubMed]

Hines ML, Carnevale NT. (2006). The NEURON Book.

Hogan N, Sternad D. (2009). Sensitivity of smoothness measures to movement duration, amplitude, and arrests. Journal of motor behavior. 41 [PubMed]

Holzbaur KR, Murray WM, Delp SL. (2005). A model of the upper extremity for simulating musculoskeletal surgery and analyzing neuromuscular control. Annals of biomedical engineering. 33 [PubMed]

Izhikevich EM. (2007). Solving the distal reward problem through linkage of STDP and dopamine signaling. Cerebral cortex (New York, N.Y. : 1991). 17 [PubMed]

Kerr CC et al. (2012). Electrostimulation as a prosthesis for repair of information flow in a computer model of neocortex. IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society. 20 [PubMed]

Luque NR, Garrido JA, Carrillo RR, Coenen OJ, Ros E. (2011). Cerebellar input configuration toward object model abstraction in manipulation tasks. IEEE transactions on neural networks. 22 [PubMed]

Lytton W, Li K, Principe J, Francis J, Dura-Bernal S. (2015). Repairing lesions via kernel adaptive inverse control in a biomimetic model of sensorimotor cortex Neural Engineering (NER), 2015 7th International IEEE/EMBS Conference. (Montpellier).

Lytton WW, Neymotin SA, Hines ML. (2008). The virtual slice setup. Journal of neuroscience methods. 171 [PubMed]

Lytton WW, Omurtag A. (2007). Tonic-clonic transitions in computer simulation. Journal of clinical neurophysiology : official publication of the American Electroencephalographic Society. 24 [PubMed]

Lytton WW, Omurtag A, Neymotin SA, Hines ML. (2008). Just-in-time connectivity for large spiking networks. Neural computation. 20 [PubMed]

Lytton WW, Stewart M. (2005). A rule-based firing model for neural networks Int J Bioelectromagn. 7

Lytton WW, Stewart M. (2006). Rule-based firing for network simulations. Neurocomputing. 69

Mahmoudi B, Pohlmeyer EA, Prins NW, Geng S, Sanchez JC. (2013). Towards autonomous neuroprosthetic control using Hebbian reinforcement learning. Journal of neural engineering. 10 [PubMed]

Marsh BT, Tarigoppula VS, Chen C, Francis JT. (2015). Toward an autonomous brain machine interface: integrating sensorimotor reward modulation and reinforcement learning. The Journal of neuroscience : the official journal of the Society for Neuroscience. 35 [PubMed]

Neymotin SA, Chadderdon GL, Kerr CC, Francis JT, Lytton WW. (2013). Reinforcement learning of two-joint virtual arm reaching in a computer model of sensorimotor cortex. Neural computation. 25 [PubMed]

Neymotin SA, Lee H, Park E, Fenton AA, Lytton WW. (2011). Emergence of physiological oscillation frequencies in a computer model of neocortex. Frontiers in computational neuroscience. 5 [PubMed]

Orin D, Featherstone R. (2000). Robot dynamics: Equations and algorithms In ICRA (International Conference Robotics and Automation).

Prins NW, Sanchez JC, Prasad A. (2014). A confidence metric for using neurobiological feedback in actor-critic reinforcement learning based brain-machine interfaces. Frontiers in neuroscience. 8 [PubMed]

Roll JP, Albert F, Ribot-Ciscar E, Bergenheim M. (2004). "Proprioceptive signature" of cursive writing in humans: a multi-population coding. Experimental brain research. 157 [PubMed]

Sanchez J et al. (2012). Dynamically repairing and replacing neural networks: using hybrid computational and biological tools. IEEE pulse. 3 [PubMed]

Sartori M, Gizzi L, Lloyd DG, Farina D. (2013). A musculoskeletal model of human locomotion driven by a low dimensional set of impulsive excitation primitives. Frontiers in computational neuroscience. 7 [PubMed]

Schutte LM, Rodgers MM, Zajac F, Glaser RM. (1993). Improving the efficacy of electrical stimulation-induced leg cycle ergometry: an analysis based on a dynamic musculoskeletal model Rehabil. Eng. IEEE Trans.. 1

Shadmehr R, Mussa-Ivaldi FA. (1994). Adaptive representation of dynamics during learning of a motor task. The Journal of neuroscience : the official journal of the Society for Neuroscience. 14 [PubMed]

Song W, Kerr CC, Lytton WW, Francis JT. (2013). Cortical plasticity induced by spike-triggered microstimulation in primate somatosensory cortex. PloS one. 8 [PubMed]

Sussillo D, Churchland MM, Kaufman MT, Shenoy KV. (2015). A neural network that finds a naturalistic solution for the production of muscle activity. Nature neuroscience. 18 [PubMed]

Teulings HL, Contreras-Vidal JL, Stelmach GE, Adler CH. (1997). Parkinsonism reduces coordination of fingers, wrist, and arm in fine motor control. Experimental neurology. 146 [PubMed]

Thelen DG, Anderson FC, Delp SL. (2003). Generating dynamic simulations of movement using computed muscle control. Journal of biomechanics. 36 [PubMed]

Wolpert DM, Diedrichsen J, Flanagan JR. (2011). Principles of sensorimotor learning. Nature reviews. Neuroscience. 12 [PubMed]

Zajac FE. (1989). Muscle and tendon: properties, models, scaling, and application to biomechanics and motor control. Critical reviews in biomedical engineering. 17 [PubMed]

Zhang W et al. (2014). Towards real-time communication between in vivo neurophysiological data sources and simulator-based brain biomimetic models. J Comput Surg.

References and models that cite this paper

Dura-Bernal S et al. (2016). Restoring Behavior via Inverse Neurocontroller in a Lesioned Cortical Spiking Model Driving a Virtual Arm. Frontiers in neuroscience. 10 [PubMed]

Lytton WW et al. (2017). Evolutionary algorithm optimization of biological learning parameters in a biomimetic neuroprosthesis. IBM Journal of Research and Development (Computational Neuroscience special issue). 61(2/3)

Medlock L et al. (2022). Multiscale computer model of the spinal dorsal horn reveals changes in network processing associated with chronic pain The Journal of neuroscience : the official journal of the Society for Neuroscience. 42 [PubMed]

Dura-Bernal S et al. (2016). Restoring Behavior via Inverse Neurocontroller in a Lesioned Cortical Spiking Model Driving a Virtual Arm. Frontiers in neuroscience. 10 [PubMed]

See more from authors: Dura-Bernal S · Li K · Neymotin SA · Francis JT · Principe JC · Lytton WW

References and models cited by this paper

Alstermark B, Isa T. (2012). Circuits for skilled reaching and grasping. Annual review of neuroscience. 35 [PubMed]

Arle JE, Shils JL. (2008). Motor cortex stimulation for pain and movement disorders. Neurotherapeutics : the journal of the American Society for Experimental NeuroTherapeutics. 5 [PubMed]

Bensmaia SJ, Miller LE. (2014). Restoring sensorimotor function through intracortical interfaces: progress and looming challenges. Nature reviews. Neuroscience. 15 [PubMed]

Calvin WH. (1988). Neural Darwinism. The Theory of Neuronal Group Selection. Gerald M. Edelman. Basic Books, New York, 1987. xxii, 371 pp., illus. $29.95. Science (New York, N.Y.). 240 [PubMed]

Carandini M. (2012). From circuits to behavior: a bridge too far? Nature neuroscience. 15 [PubMed]

Chadderdon GL et al. (2014). Motor cortex microcircuit simulation based on brain activity mapping. Neural computation. 26 [PubMed]

Chen B, Zhao S, Zhu P, Príncipe JC. (2012). Quantized kernel least mean square algorithm. IEEE transactions on neural networks and learning systems. 23 [PubMed]

Ching S, Ritt JT. (2013). Control strategies for underactuated neural ensembles driven by optogenetic stimulation. Frontiers in neural circuits. 7 [PubMed]

Choi J, Sanchez J, Tarigoppula A, Marsh B, Chhatbar P. (2011). Control of a center-out reaching task using a reinforcement learning brain-machine interface Neural Engineering (NER), 2011 5th International IEEE-EMBS Conference on. IEEE.

Choi JS, DiStasio MM, Brockmeier AJ, Francis JT. (2012). An electric field model for prediction of somatosensory (S1) cortical field potentials induced by ventral posterior lateral (VPL) thalamic microstimulation. IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society. 20 [PubMed]

Clark KL, Armstrong KM, Moore T. (2011). Probing neural circuitry and function with electrical microstimulation. Proceedings. Biological sciences. 278 [PubMed]

Douglas RJ, Martin KA. (2012). Behavioral architecture of the cortical sheet. Current biology : CB. 22 [PubMed]

Dura-Bernal S, Chadderdon GL, Neymotin SA, Francis JT, Lytton WW. (2014). Towards a real-time interface between a biomimetic model of sensorimotor cortex and a robotic arm. Pattern recognition letters. 36 [PubMed]

Dura-Bernal S et al. (2015). Cortical Spiking Network Interfaced with Virtual Musculoskeletal Arm and Robotic Arm. Frontiers in neurorobotics. 9 [PubMed]

Grahn PJ et al. (2014). Restoration of motor function following spinal cord injury via optimal control of intraspinal microstimulation: toward a next generation closed-loop neural prosthesis. Frontiers in neuroscience. 8 [PubMed]

Grammont F, Riehle A. (1999). Precise spike synchronization in monkey motor cortex involved in preparation for movement. Experimental brain research. 128 [PubMed]

Gupta RK, Przekwas A. (2013). Mathematical Models of Blast-Induced TBI: Current Status, Challenges, and Prospects. Frontiers in neurology. 4 [PubMed]

Hampson RE et al. (2012). Facilitation and restoration of cognitive function in primate prefrontal cortex by a neuroprosthesis that utilizes minicolumn-specific neural firing. Journal of neural engineering. 9 [PubMed]

Hampson RE et al. (2013). Facilitation of memory encoding in primate hippocampus by a neuroprosthesis that promotes task-specific neural firing. Journal of neural engineering. 10 [PubMed]

Harris KD, Shepherd GM. (2015). The neocortical circuit: themes and variations. Nature neuroscience. 18 [PubMed]

Hartmann CJ, Chaturvedi A, Lujan JL. (2015). Quantitative analysis of axonal fiber activation evoked by deep brain stimulation via activation density heat maps. Frontiers in neuroscience. 9 [PubMed]

Hatsopoulos N, Joshi J, O'Leary JG. (2004). Decoding continuous and discrete motor behaviors using motor and premotor cortical ensembles. Journal of neurophysiology. 92 [PubMed]

Haykin S, Liu W, Principe JC. (2010). Kernel Adaptive Filtering: A Comprehensive Introduction.

Hiscott R. (2014). Darpa: On the hunt for neuroprosthetics to enhance memory Neurology Today.

Holzbaur KR, Murray WM, Delp SL. (2005). A model of the upper extremity for simulating musculoskeletal surgery and analyzing neuromuscular control. Annals of biomedical engineering. 33 [PubMed]

Hwang EJ, Shadmehr R. (2005). Internal models of limb dynamics and the encoding of limb state. Journal of neural engineering. 2 [PubMed]

Jackson A, Mavoori J, Fetz EE. (2006). Long-term motor cortex plasticity induced by an electronic neural implant. Nature. 444 [PubMed]

Jefferson SC et al. (2016). Cortical Stimulation Concurrent With Skilled Motor Training Improves Forelimb Function and Enhances Motor Cortical Reorganization Following Controlled Cortical Impact. Neurorehabilitation and neural repair. 30 [PubMed]

Kasthuri N et al. (2015). Saturated Reconstruction of a Volume of Neocortex. Cell. 162 [PubMed]

Kerr CC et al. (2012). Electrostimulation as a prosthesis for repair of information flow in a computer model of neocortex. IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society. 20 [PubMed]

Klaes C et al. (2014). A cognitive neuroprosthetic that uses cortical stimulation for somatosensory feedback. Journal of neural engineering. 11 [PubMed]

Kleim JA et al. (2003). Motor cortex stimulation enhances motor recovery and reduces peri-infarct dysfunction following ischemic insult. Neurological research. 25 [PubMed]

Kocaturk M, Gulcur HO, Canbeyli R. (2015). Toward Building Hybrid Biological/in silico Neural Networks for Motor Neuroprosthetic Control. Frontiers in neurorobotics. 9 [PubMed]

Koch C, Buice MA. (2015). A Biological Imitation Game. Cell. 163 [PubMed]

Koralek AC, Jin X, Long JD, Costa RM, Carmena JM. (2012). Corticostriatal plasticity is necessary for learning intentional neuroprosthetic skills. Nature. 483 [PubMed]

Kreuz T, Chicharro D, Greschner M, Andrzejak RG. (2011). Time-resolved and time-scale adaptive measures of spike train synchrony. Journal of neuroscience methods. 195 [PubMed]

Kreuz T, Mulansky M, Bozanic N. (2015). SPIKY: a graphical user interface for monitoring spike train synchrony. Journal of neurophysiology. 113 [PubMed]

Lee G et al. (2014). Towards real-time communication between in vivo neurophysiological data sources and simulator-based brain biomimetic models. Journal of computational surgery. 3 [PubMed]

Li L et al. (2013). Adaptive inverse control of neural spatiotemporal spike patterns with a reproducing kernel Hilbert space (RKHS) framework. IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society. 21 [PubMed]

Ling G. (2013). Newsmaker interview: Geoffrey Ling. DARPA aims to rebuild brains. Interview by Emily Underwood. Science (New York, N.Y.). 342 [PubMed]

Liu W, Pokharel P, Principe JC . (2008). The kernel least mean square algorithm. 56

Loeb GE, Tsianos GA. (2015). Major remaining gaps in models of sensorimotor systems. Frontiers in computational neuroscience. 9 [PubMed]

Lytton W, Li K, Principe J, Francis J, Dura-Bernal S. (2015). Repairing lesions via kernel adaptive inverse control in a biomimetic model of sensorimotor cortex Neural Engineering (NER), 2015 7th International IEEE/EMBS Conference. (Montpellier).

Lytton W et al. (2015). Large-scale m1 microcircuit model with plastic input connections from biological pmd neurons used for prosthetic arm control 24th Annual Computational Neuroscience Meeting (CNS15) BMC Neuroscience.

Lytton W, Stark J, Yamasaki D, Sober S. (1999). Computer models of stroke recovery: Implications for neurorehabilitation. The Neuroscientist . 5

Lytton WW et al. (2014). Network-level effects of optogenetic stimulation in a computer model of macaque primary motor cortex BMC Neuroscience. 15

Lytton WW, Fenton AA, Neymotin SA. (2015). Tracking recurrence of correlation structure in neuronal ensembles.

Lytton WW, Neymotin SA, Hines ML. (2008). The virtual slice setup. Journal of neuroscience methods. 171 [PubMed]

Lytton WW, Omurtag A, Neymotin SA, Hines ML. (2008). Just-in-time connectivity for large spiking networks. Neural computation. 20 [PubMed]

Lytton WW, Stewart M. (2006). Rule-based firing for network simulations. Neurocomputing. 69

Mante V, Sussillo D, Shenoy KV, Newsome WT. (2013). Context-dependent computation by recurrent dynamics in prefrontal cortex. Nature. 503 [PubMed]

Marcus G, Marblestone A, Dean T. (2014). Neuroscience. The atoms of neural computation. Science (New York, N.Y.). 346 [PubMed]

Markram H et al. (2015). Reconstruction and Simulation of Neocortical Microcircuitry. Cell. 163 [PubMed]

McIntyre CC, Mori S, Sherman DL, Thakor NV, Vitek JL. (2004). Electric field and stimulating influence generated by deep brain stimulation of the subthalamic nucleus. Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology. 115 [PubMed]

Miranda RA et al. (2015). DARPA-funded efforts in the development of novel brain-computer interface technologies. Journal of neuroscience methods. 244 [PubMed]

Nelson JT, Tepe V. (2015). Neuromodulation research and application in the U.S. Department of Defense. Brain stimulation. 8 [PubMed]

Neymotin SA, Chadderdon GL, Kerr CC, Francis JT, Lytton WW. (2013). Reinforcement learning of two-joint virtual arm reaching in a computer model of sensorimotor cortex. Neural computation. 25 [PubMed]

Neymotin SA, Lee H, Park E, Fenton AA, Lytton WW. (2011). Emergence of physiological oscillation frequencies in a computer model of neocortex. Frontiers in computational neuroscience. 5 [PubMed]

Nirenberg S, Pandarinath C. (2012). Retinal prosthetic strategy with the capacity to restore normal vision. Proceedings of the National Academy of Sciences of the United States of America. 109 [PubMed]

Nishimura Y, Perlmutter SI, Fetz EE. (2013). Restoration of upper limb movement via artificial corticospinal and musculospinal connections in a monkey with spinal cord injury. Frontiers in neural circuits. 7 [PubMed]

O'Doherty JE et al. (2011). Active tactile exploration using a brain-machine-brain interface. Nature. 479 [PubMed]

Orin D, Featherstone R. (2000). Robot dynamics: Equations and algorithms In ICRA (International Conference Robotics and Automation).

Overduin SA, d'Avella A, Carmena JM, Bizzi E. (2012). Microstimulation activates a handful of muscle synergies. Neuron. 76 [PubMed]

Overstreet CK, Klein JD, Helms Tillery SI. (2013). Computational modeling of direct neuronal recruitment during intracortical microstimulation in somatosensory cortex. Journal of neural engineering. 10 [PubMed]

Paiva AR, Park I, Príncipe JC. (2009). A reproducing kernel Hilbert space framework for spike train signal processing. Neural computation. 21 [PubMed]

Palop JJ, Mucke L. (2010). Amyloid-beta-induced neuronal dysfunction in Alzheimer's disease: from synapses toward neural networks. Nature neuroscience. 13 [PubMed]

Potjans TC, Diesmann M. (2014). The cell-type specific cortical microcircuit: relating structure and activity in a full-scale spiking network model. Cerebral cortex (New York, N.Y. : 1991). 24 [PubMed]

Ramanathan D, Conner JM, Tuszynski MH. (2006). A form of motor cortical plasticity that correlates with recovery of function after brain injury. Proceedings of the National Academy of Sciences of the United States of America. 103 [PubMed]

Rickgauer JP, Deisseroth K, Tank DW. (2014). Simultaneous cellular-resolution optical perturbation and imaging of place cell firing fields. Nature neuroscience. 17 [PubMed]

Riehle A, Grün S, Diesmann M, Aertsen A. (1997). Spike synchronization and rate modulation differentially involved in motor cortical function. Science (New York, N.Y.). 278 [PubMed]

Rowan MS, Neymotin SA, Lytton WW. (2014). Electrostimulation to reduce synaptic scaling driven progression of Alzheimer's disease. Frontiers in computational neuroscience. 8 [PubMed]

Rubino D, Robbins KA, Hatsopoulos NG. (2006). Propagating waves mediate information transfer in the motor cortex. Nature neuroscience. 9 [PubMed]

Sanchez J et al. (2012). Dynamically repairing and replacing neural networks: using hybrid computational and biological tools. IEEE pulse. 3 [PubMed]

Scholkopf B, Herbrich R, Smola AJ. (2001). A generalized representer theorem Proc. 14th Annual Conf. on Comput. Learn. Theory. 2111

Scholkopf B, Smola AJ. (2001). Learning with kernels: Support vector machines, regularization, optimization, and beyond.

Schutte LM, Rodgers MM, Zajac F, Glaser RM. (1993). Improving the efficacy of electrical stimulation-induced leg cycle ergometry: an analysis based on a dynamic musculoskeletal model Rehabil. Eng. IEEE Trans.. 1

Song W, Kerr CC, Lytton WW, Francis JT. (2013). Cortical plasticity induced by spike-triggered microstimulation in primate somatosensory cortex. PloS one. 8 [PubMed]

Spuler M, Nagel S, Rosenstiel W. (). A Spiking Neuronal Model Learning a Motor Control Task by Reinforcement Learning and Structural Synaptic Plasticity.

Stanley GB. (2013). Reading and writing the neural code. Nature neuroscience. 16 [PubMed]

Sussillo D, Churchland MM, Kaufman MT, Shenoy KV. (2015). A neural network that finds a naturalistic solution for the production of muscle activity. Nature neuroscience. 18 [PubMed]

Suter BA, Migliore M, Shepherd GM. (2013). Intrinsic electrophysiology of mouse corticospinal neurons: a class-specific triad of spike-related properties. Cerebral cortex (New York, N.Y. : 1991). 23 [PubMed]

Suter BA et al. (2014). Neurophotonics applications to motor cortex research. Neurophotonics. 1 [PubMed]

Tessadori J, Bisio M, Martinoia S, Chiappalone M. (2012). Modular neuronal assemblies embodied in a closed-loop environment: toward future integration of brains and machines. Frontiers in neural circuits. 6 [PubMed]

Thelen DG, Anderson FC, Delp SL. (2003). Generating dynamic simulations of movement using computed muscle control. Journal of biomechanics. 36 [PubMed]

Van Acker GM et al. (2013). Effective intracortical microstimulation parameters applied to primary motor cortex for evoking forelimb movements to stable spatial end points. Journal of neurophysiology. 110 [PubMed]

Warden MR, Cardin JA, Deisseroth K. (2014). Optical neural interfaces. Annual review of biomedical engineering. 16 [PubMed]

Wolpert DM, Diedrichsen J, Flanagan JR. (2011). Principles of sensorimotor learning. Nature reviews. Neuroscience. 12 [PubMed]

Zajac FE. (1989). Muscle and tendon: properties, models, scaling, and application to biomechanics and motor control. Critical reviews in biomedical engineering. 17 [PubMed]

References and models that cite this paper

Lytton WW et al. (2017). Evolutionary algorithm optimization of biological learning parameters in a biomimetic neuroprosthesis. IBM Journal of Research and Development (Computational Neuroscience special issue). 61(2/3)

Neymotin SA, Dura-Bernal S, Lakatos P, Sanger TD, Lytton WW. (2016). Multitarget Multiscale Simulation for Pharmacological Treatment of Dystonia in Motor Cortex. Frontiers in pharmacology. 7 [PubMed]

This website requires cookies and limited processing of your personal data in order to function. By continuing to browse or otherwise use this site, you are agreeing to this use. See our Privacy policy and how to cite and terms of use.