Loeb GE. Neural prosthetics: A review of empirical vs. systems engineering strategies. Appl Bionics Biomech. 2018;2018.
Valero-Cuevas FJ, Hoffmann H, Kurse MU, Kutch JJ, Theodorou EA. Computational models for neuromuscular function. IEEE Rev Biomed Eng. 2009;2:110–35.
Article PubMed PubMed Central Google Scholar
Reinkensmeyer DJ, Burdet E, Casadio M, Krakauer JW, Kwakkel G, Lang CE, Swinnen SP, Ward NS, Schweighofer N. Computational neurorehabilitation: modeling plasticity and learning to predict recovery. J Neuroeng Rehabil. 2016;13(1):1–25.
Goodall S, Reggia JA, Chen Y, Ruppin E, Whitney C. A computational model of acute focal cortical lesions. Stroke. 1997;28(1):101–9.
Article CAS PubMed Google Scholar
Reggia JA. Neurocomputational models of the remote effects of focal brain damage. Med Eng Phys. 2004;26(9):711–22.
Takiyama K, Okada M. Recovery in stroke rehabilitation through the rotation of preferred directions induced by bimanual movements: a computational study. PLoS ONE. 2012;7(5):37594.
Han CE, Arbib MA, Schweighofer N. Stroke rehabilitation reaches a threshold. PLoS Comput Biol. 2008;4(8):1000133.
Hidaka Y, Han CE, Wolf SL, Winstein CJ, Schweighofer N. Use it and improve it or lose it: interactions between arm function and use in humans post-stroke. PLoS Comput Biol. 2012;8(2):1002343.
Scheidt RA, Stoeckmann T. Reach adaptation and final position control amid environmental uncertainty after stroke. J Neurophysiol. 2007;97(4):2824–36.
Reinkensmeyer DJ, Guigon E, Maier MA. A computational model of use-dependent motor recovery following a stroke: optimizing corticospinal activations via reinforcement learning can explain residual capacity and other strength recovery dynamics. Neural Netw. 2012;29:60–9.
Bains AS, Schweighofer N. Time-sensitive reorganization of the somatosensory cortex poststroke depends on interaction between hebbian and homeoplasticity: a simulation study. J Neurophysiol. 2014;112(12):3240–50.
Article PubMed PubMed Central Google Scholar
Reinkensmeyer DJ, Aoyagi D, Emken JL, Galvez JA, Ichinose W, Kerdanyan G, Maneekobkunwong S, Minakata K, Nessler JA, Weber R, et al. Tools for understanding and optimizing robotic gait training. J Rehabil Res Dev. 2014;43(5):657–70.
Ballester BR, Nirme J, Duarte E, Cuxart A, Rodriguez S, Verschure P, Duff A. The visual amplification of goal-oriented movements counteracts acquired non-use in hemiparetic stroke patients. J Neuroeng Rehabil. 2015;12:1–11.
Burdet E, Li Y, Kager S, Chua KS-G, Hussain A, Campolo D. Interactive robot assistance for upper-limb training. In: Rehabilitation robotics, Elsevier; 2018; pp. 137–148.
Reinkensmeyer DJ. How to retrain movement after neurologic injury: a computational rationale for incorporating robot (or therapist) assistance. In: Proceedings of the 25th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (IEEE Cat. No. 03CH37439), vol. 2, IEEE; 2003; p. 1479–1482.
Casadio M, Sanguineti V. Learning, retention, and slacking: a model of the dynamics of recovery in robot therapy. IEEE Trans Neural Syst Rehabil Eng. 2012;20(3):286–96.
Crouch DL, Huang H. Lumped-parameter electromyogram-driven musculoskeletal hand model: a potential platform for real-time prosthesis control. J Biomech. 2016;49(16):3901–7.
Sartori M, Durandau G, Došen S, Farina D. Robust simultaneous myoelectric control of multiple degrees of freedom in wrist-hand prostheses by real-time neuromusculoskeletal modeling. J Neural Eng. 2018;15(6):066026.
Krakauer JW, Hadjiosif AM, Xu J, Wong AL, Haith AM. Motor learning Compr Physiol. 2019;9(2):613–63.
Dayan E, Cohen LG. Neuroplasticity subserving motor skill learning. Neuron. 2011;72(3):443–54.
Article CAS PubMed PubMed Central Google Scholar
Nudo R. Adaptive plasticity in motor cortex: implications for rehabilitation after brain injury. J Rehab Med-Suppl. 2003;41:7–10.
Torres-Oviedo G, Vasudevan E, Malone L, Bastian AJ. Locomotor adaptation. Prog Brain Res. 2011;191:65–74.
Article PubMed PubMed Central Google Scholar
Murphy TH, Corbett D. Plasticity during stroke recovery: from synapse to behaviour. Nat Rev Neurosci. 2009;10(12):861–72.
Article CAS PubMed Google Scholar
Bundy DT, Nudo RJ. Preclinical studies of neuroplasticity following experimental brain injury: an update. Stroke. 2019;50(9):2626–33.
Article PubMed PubMed Central Google Scholar
Krakauer JW. Motor learning: its relevance to stroke recovery and neurorehabilitation. Curr Opin Neurol. 2006;19(1):84–90.
Silasi G, Murphy TH. Stroke and the connectome: how connectivity guides therapeutic intervention. Neuron. 2014;83(6):1354–68.
Article CAS PubMed Google Scholar
Grefkes C, Fink GR. Connectivity-based approaches in stroke and recovery of function. Lancet Neurol. 2014;13(2):206–16.
Grefkes C, Fink GR. Recovery from stroke: current concepts and future perspectives. Neurol Res Pract. 2020;2(1):1–10.
Jang SH. Motor function-related maladaptive plasticity in stroke: a review. NeuroRehabilitation. 2013;32(2):311–6.
Takeuchi N, Izumi S-I, et al. Rehabilitation with poststroke motor recovery: a review with a focus on neural plasticity. Stroke Res Treat. 2013;2013.
Jinnah H, Berardelli A, Comella C, DeFazio G, DeLong MR, Factor S, Galpern WR, Hallett M, Ludlow CL, Perlmutter JS, et al. The focal dystonias: current views and challenges for future research. Mov Disord. 2013;28(7):926–43.
Article CAS PubMed PubMed Central Google Scholar
Stahl CM, Frucht SJ. Focal task specific dystonia: a review and update. J Neurol. 2017;264:1536–41.
Huang VS, Krakauer JW. Robotic neurorehabilitation: a computational motor learning perspective. J Neuroeng Rehabil. 2009;6:1–3.
Hermann DM, Chopp M. Promoting brain remodelling and plasticity for stroke recovery: therapeutic promise and potential pitfalls of clinical translation. 11(4): 369–380. https://doi.org/10.1016/S1474-4422(12)70039-X
Krakauer JW. Motor learning: its relevance to stroke recovery and neurorehabilitation. 19(1): 84–90 https://doi.org/10.1097/01.wco.0000200544.29915.cc
Kudithipudi D, Aguilar-Simon M, Babb J, Bazhenov M, Blackiston D, Bongard J, Brna AP, Chakravarthi Raja S, Cheney N, Clune J, Daram A, Fusi S, Helfer P, Kay L, Ketz N, Kira Z, Kolouri S, Krichmar JL, Kriegman S, Levin M, Madireddy S, Manicka S, Marjaninejad A, McNaughton B, Miikkulainen R, Navratilova Z, Pandit T, Parker A, Pilly PK, Risi S, Sejnowski TJ, Soltoggio A, Soures N, Tolias AS, Urbina-Meléndez D, Valero-Cuevas FJ, Ven GM, Vogelstein JT, Wang F, Weiss R, Yanguas-Gil A, Zou X, Siegelmann H. Biological underpinnings for lifelong learning machines. Nat Mach Intell. 2022;4(3):196–210. https://doi.org/10.1038/s42256-022-00452-0.
Hebb DO. The organization of behavior: A neuropsychological theory. Psychology press; 2005.
Feldman DE. The spike-timing dependence of plasticity. 75(4):556–571. https://doi.org/10.1016/j.neuron.2012.08.001
Bloch J, Greaves-Tunnell A, Shea-Brown E, Harchaoui Z, Shojaie A, Yazdan-Shahmorad A. Network structure mediates functional reorganization induced by optogenetic stimulation of non-human primate sensorimotor cortex. Iscience. 2022;25(5).
Schweighofer N. Computational neurorehabilitation. In: Neurorehabilitation Technology, Springer; 2022; p. 345–355.
Reisman DS, Wityk R, Silver K, Bastian AJ. Locomotor adaptation on a split-belt treadmill can improve walking symmetry post-stroke. Brain. 2007;130(7):1861–72.
Yazdan-Shahmorad A, Silversmith DB, Kharazia V, Sabes PN. Targeted cortical reorganization using optogenetics in non-human primates. Elife. 2018;7:31034.
Zanos S, Rembado I, Chen D, Fetz EE. Phase-locked stimulation during cortical beta oscillations produces bidirectional synaptic plasticity in awake monkeys. Curr Biol. 2018;28(16):2515–26.
Article CAS PubMed PubMed Central Google Scholar
Jackson A, Mavoori J, Fetz EE. Long-term motor cortex plasticity induced by an electronic neural implant. Nature. 2006;444(7115):56–60.
Article CAS PubMed Google Scholar
McPherson JG, Miller RR, Perlmutter SI. Targeted, activity-dependent spinal stimulation produces long-lasting motor recovery in chronic cervical spinal cord injury. Proc Natl Acad Sci. 2015;112(39):12193–8.
Article CAS PubMed PubMed Central Google Scholar
Capogrosso M, Milekovic T, Borton D, Wagner F, Moraud EM, Mignardot J-B, Buse N, Gandar J, Barraud Q, Xing D, et al. A brain-spine interface alleviating gait deficits after spinal cord injury in primates. Nature. 2016;539(7628):284–8.
Article PubMed PubMed Central Google Scholar
Lorach H, Galvez A, Spagnolo V, Martel F, Karakas S, Intering N, Vat M, Faivre O, Harte C, Komi S, Ravier J. Walking naturally after spinal cord injury using a brain–spine interface. Nature. 2023:1–8.
Liew S-L, Zavaliangos-Petropulu A, Jahanshad N, Lang CE, Hayward KS, Lohse KR, Juliano JM, Assogna F, Baugh LA, Bhattacharya AK, et al. The enigma stroke recovery working group: big data neuroimaging to study brain–behavior relationships after stroke. Hum Brain Mapp. 2022;43(1):129–48.
Hammer EM, Halder S, Blankertz B, Sannelli C, Dickhaus T, Kleih S, Müller K-R, Kübler A. Psychological predictors of smr-bci performance. Biol Psychol. 2012;89(1):80–6.
留言 (0)