Brain–computer interface boosts motor imagery practice during stroke recovery
暂无分享,去创建一个
M. Molinari | F. Cincotti | I. Pisotta | L. Astolfi | D. Mattia | F. Pichiorri | G. Morone | M. Petti | J. Toppi | S. Paolucci | M. Inghilleri | Maurizio Inghilleri
[1] P. Welch. The use of fast Fourier transform for the estimation of power spectra: A method based on time averaging over short, modified periodograms , 1967 .
[2] A. Fugl-Meyer,et al. The post-stroke hemiplegic patient. 1. a method for evaluation of physical performance. , 1975, Scandinavian journal of rehabilitation medicine.
[3] Richard W. Bohannon,et al. Interrater reliability of a modified Ashworth scale of muscle spasticity. , 1987, Physical therapy.
[4] J. Marler,et al. Measurements of acute cerebral infarction: a clinical examination scale. , 1989, Stroke.
[5] B Cooper,et al. Efficiency, effectiveness, and duration of stroke rehabilitation. , 1990, Stroke.
[6] P. Rossini,et al. Non-invasive electrical and magnetic stimulation of the brain, spinal cord and roots: basic principles and procedures for routine clinical application. Report of an IFCN committee. , 1994, Electroencephalography and clinical neurophysiology.
[7] Pierre Comon,et al. Independent component analysis, A new concept? , 1994, Signal Process..
[8] M. Jeannerod,et al. Mental motor imagery: a window into the representational stages of action , 1995, Current Opinion in Neurobiology.
[9] F. L. D. Silva,et al. Event-related EEG/MEG synchronization and desynchronization: basic principles , 1999, Clinical Neurophysiology.
[10] W. Klimesch. EEG alpha and theta oscillations reflect cognitive and memory performance: a review and analysis , 1999, Brain Research Reviews.
[11] Erkki Oja,et al. Independent component analysis: algorithms and applications , 2000, Neural Networks.
[12] Y. Benjamini,et al. THE CONTROL OF THE FALSE DISCOVERY RATE IN MULTIPLE TESTING UNDER DEPENDENCY , 2001 .
[13] Luiz A. Baccalá,et al. Partial directed coherence: a new concept in neural structure determination , 2001, Biological Cybernetics.
[14] B. Tilley,et al. Use of odds ratio or relative risk to measure a treatment effect in clinical trials with multiple correlated binary outcomes: data from the NINDS t‐PA stroke trial , 2001, Statistics in medicine.
[15] S. Black,et al. The Fugl-Meyer Assessment of Motor Recovery after Stroke: A Critical Review of Its Measurement Properties , 2002, Neurorehabilitation and neural repair.
[16] Andreas R. Luft,et al. Lesion location alters brain activation in chronically impaired stroke survivors , 2004, NeuroImage.
[17] Alan J Thompson,et al. The influence of time after stroke on brain activations during a motor task , 2004, Annals of neurology.
[18] L. Craighero,et al. The influence of hand posture on corticospinal excitability during motor imagery: a transcranial magnetic stimulation study. , 2004, Cerebral cortex.
[19] Magdalena Sabaté,et al. Brain lateralization of motor imagery: motor planning asymmetry as a cause of movement lateralization , 2004, Neuropsychologia.
[20] Katarzyna J. Blinowska,et al. Determination of EEG activity propagation: pair-wise versus multichannel estimate , 2004, IEEE Transactions on Biomedical Engineering.
[21] M. Johnston,et al. Functional limitations and survival following stroke: Psychological and clinical predictors of 3-year outcome , 2004, International journal of behavioral medicine.
[22] T. Tombaugh. Test-retest reliable coefficients and 5-year change scores for the MMSE and 3MS. , 2005, Archives of clinical neuropsychology : the official journal of the National Academy of Neuropsychologists.
[23] A. Guillot,et al. Contribution from neurophysiological and psychological methods to the study of motor imagery , 2005, Brain Research Reviews.
[24] S. Swinnen,et al. Kinesthetic, but not visual, motor imagery modulates corticomotor excitability , 2005, Experimental Brain Research.
[25] Michael Eichler,et al. Abstract Journal of Neuroscience Methods xxx (2005) xxx–xxx Testing for directed influences among neural signals using partial directed coherence , 2005 .
[26] Paolo Maria Rossini,et al. Imagery-induced cortical excitability changes in stroke: a transcranial magnetic stimulation study. , 2006, Cerebral cortex.
[27] G. Riva,et al. A Strategy for Computer-Assisted Mental Practice in Stroke Rehabilitation , 2006, Neurorehabilitation and neural repair.
[28] Gary F. Egan,et al. Evolution of Brain Activation with Good and Poor Motor Recovery after Stroke , 2006, Neurorehabilitation and neural repair.
[29] Laura Astolfi,et al. Assessing cortical functional connectivity by partial directed coherence: simulations and application to real data , 2006, IEEE Transactions on Biomedical Engineering.
[30] Sandra G. Hart,et al. Nasa-Task Load Index (NASA-TLX); 20 Years Later , 2006 .
[31] S. Page,et al. Mental Practice in Chronic Stroke: Results of a Randomized, Placebo-Controlled Trial , 2007, Stroke.
[32] E. Fetz. Volitional control of neural activity: implications for brain–computer interfaces , 2007, The Journal of physiology.
[33] Winston D. Byblow,et al. Lateralization of motor imagery following stroke , 2007, Clinical Neurophysiology.
[34] G. A. Miller,et al. Comparison of different cortical connectivity estimators for high‐resolution EEG recordings , 2007, Human brain mapping.
[35] K. Sameshima,et al. Connectivity Inference between Neural Structures via Partial Directed Coherence , 2007 .
[36] M. Hallett,et al. Motor planning, imagery, and execution in the distributed motor network: a time-course study with functional MRI. , 2008, Cerebral cortex.
[37] J. Wolpaw,et al. Brain–computer interfaces in neurological rehabilitation , 2008, The Lancet Neurology.
[38] Febo Cincotti,et al. High-resolution EEG techniques for brain–computer interface applications , 2008, Journal of Neuroscience Methods.
[39] Ethan R. Buch,et al. Think to Move: a Neuromagnetic Brain-Computer Interface (BCI) System for Chronic Stroke , 2008, Stroke.
[40] G. Fink,et al. Cortical connectivity after subcortical stroke assessed with functional magnetic resonance imaging , 2008, Annals of neurology.
[41] Susumu Urakawa,et al. Global synchronization in the theta band during mental imagery of navigation in humans , 2009, Neuroscience Research.
[42] Bruce H Dobkin,et al. Progressive Staging of Pilot Studies to Improve Phase III Trials for Motor Interventions , 2009, Neurorehabilitation and neural repair.
[43] Mark E. Dohring,et al. Feasibility of a New Application of Noninvasive Brain Computer Interface (BCI): A Case Study of Training for Recovery of Volitional Motor Control After Stroke , 2009, Journal of neurologic physical therapy : JNPT.
[44] K. Zentgraf,et al. Cognitive motor processes: The role of motor imagery in the study of motor representations , 2009, Brain Research Reviews.
[45] Le Li,et al. A Randomized Controlled Trial of Mental Imagery Augment Generalization of Learning in Acute Poststroke Patients , 2009, Stroke.
[46] J. Baron,et al. Motor imagery after stroke: Relating outcome to motor network connectivity , 2009, Annals of neurology.
[47] O. Sporns,et al. Complex brain networks: graph theoretical analysis of structural and functional systems , 2009, Nature Reviews Neuroscience.
[48] G. Prasad,et al. Applying a brain-computer interface to support motor imagery practice in people with stroke for upper limb recovery: a feasibility study , 2010, Journal of NeuroEngineering and Rehabilitation.
[49] Michael B. Miller,et al. The principled control of false positives in neuroimaging. , 2009, Social cognitive and affective neuroscience.
[50] J. Rothwell,et al. Standardizing the intensity of upper limb treatment in rehabilitation medicine , 2010, Clinical rehabilitation.
[51] M. Viergever,et al. Recovery of Sensorimotor Function after Experimental Stroke Correlates with Restoration of Resting-State Interhemispheric Functional Connectivity , 2010, The Journal of Neuroscience.
[52] G. Vecchiato,et al. The issue of multiple univariate comparisons in the context of neuroelectric brain mapping: An application in a neuromarketing experiment , 2010, Journal of Neuroscience Methods.
[53] M. Levin,et al. Systematic Review of the Evidence Does Provision of Extrinsic Feedback Result in Improved Motor Learning in the Upper Limb Poststroke ? , 2009 .
[54] Olaf Sporns,et al. Complex network measures of brain connectivity: Uses and interpretations , 2010, NeuroImage.
[55] Tomohiro Ishizu,et al. Effects of motor imagery on intermanual transfer: A near-infrared spectroscopy and behavioural study , 2010, Brain Research.
[56] C. Braun,et al. Combination of Brain-Computer Interface Training and Goal-Directed Physical Therapy in Chronic Stroke: A Case Report , 2010, Neurorehabilitation and neural repair.
[57] C. Richards,et al. Mental Practice for Relearning Locomotor Skills , 2010, Physical Therapy.
[58] Andreas Daffertshofer,et al. Comparing Brain Networks of Different Size and Connectivity Density Using Graph Theory , 2010, PloS one.
[59] M. Levesley,et al. Systematic review of outcome measures used in the evaluation of robot-assisted upper limb exercise in stroke. , 2011, Journal of rehabilitation medicine.
[60] M G Bleichner,et al. Functional MRI-based identification of brain areas involved in motor imagery for implantable brain–computer interfaces , 2011, Journal of neural engineering.
[61] Heidi M. Schambra,et al. Reward Improves Long-Term Retention of a Motor Memory through Induction of Offline Memory Gains , 2011, Current Biology.
[62] L. Cohen,et al. Neuroplasticity in the context of motor rehabilitation after stroke , 2011, Nature Reviews Neurology.
[63] Karl J. Friston. Functional and Effective Connectivity: A Review , 2011, Brain Connect..
[64] Laura Astolfi,et al. Testing the asymptotic statistic for the assessment of the significance of partial directed coherence connectivity patterns , 2011, 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.
[65] Moritz Grosse-Wentrup,et al. Using brain–computer interfaces to induce neural plasticity and restore function , 2011, Journal of neural engineering.
[66] Marie Johnston,et al. Mental practice with motor imagery in stroke recovery: randomized controlled trial of efficacy , 2011, Brain : a journal of neurology.
[67] Dennis J. McFarland,et al. Brain–computer interfaces for communication and control , 2002, Clinical Neurophysiology.
[68] C. Braun,et al. Chronic stroke recovery after combined BCI training and physiotherapy: a case report. , 2011, Psychophysiology.
[69] C. Neuper,et al. Sensorimotor rhythm-based brain–computer interface training: the impact on motor cortical responsiveness , 2011, Journal of neural engineering.
[70] F Cincotti,et al. Workload measurement in a communication application operated through a P300-based brain–computer interface , 2011, Journal of neural engineering.
[71] S. Silvoni,et al. Brain-Computer Interface in Stroke: A Review of Progress , 2011, Clinical EEG and neuroscience.
[72] Joachim Gross,et al. Reliability of multivariate causality measures for neural data , 2011, Journal of Neuroscience Methods.
[73] T. Sanger,et al. Harnessing neuroplasticity for clinical applications , 2011, Brain : a journal of neurology.
[74] P. Holmes,et al. The relationship between corticospinal excitability during motor imagery and motor imagery ability , 2012, Behavioural Brain Research.
[75] P M Rossini,et al. Cortical plasticity and brain computer interface. , 2012, European journal of physical and rehabilitation medicine.
[76] Dean J Krusienski,et al. Brain-computer interfaces in medicine. , 2012, Mayo Clinic proceedings.
[77] André J. Szameitat,et al. Cortical activation during executed, imagined, observed, and passive wrist movements in healthy volunteers and stroke patients , 2012, NeuroImage.
[78] Laura Astolfi,et al. How the Statistical Validation of Functional Connectivity Patterns Can Prevent Erroneous Definition of Small-World Properties of a Brain Connectivity Network , 2012, Comput. Math. Methods Medicine.
[79] Mark Hallett,et al. Self-modulation of primary motor cortex activity with motor and motor imagery tasks using real-time fMRI-based neurofeedback , 2012, NeuroImage.
[80] Ethan R. Buch,et al. Parietofrontal integrity determines neural modulation associated with grasping imagery after stroke. , 2012, Brain : a journal of neurology.
[81] C. Neuper,et al. Relationship Between Electrical Brain Responses to Motor Imagery and Motor Impairment in Stroke , 2012, Stroke.
[82] S. Paolucci,et al. Impact of participation on rehabilitation results: a multivariate study. , 2012, European journal of physical and rehabilitation medicine.
[83] Febo Cincotti,et al. Multiscale topological properties of functional brain networks during motor imagery after stroke , 2013, NeuroImage.
[84] L. Cohen,et al. Brain–machine interface in chronic stroke rehabilitation: A controlled study , 2013, Annals of neurology.
[85] J. Baron,et al. Does motor imagery share neural networks with executed movement: a multivariate fMRI analysis , 2013, Front. Hum. Neurosci..
[86] N. Birbaumer,et al. Resting State Changes in Functional Connectivity Correlate With Movement Recovery for BCI and Robot-Assisted Upper-Extremity Training After Stroke , 2013, Neurorehabilitation and neural repair.
[87] L. R. Quitadamo,et al. Investigating the effects of a sensorimotor rhythm-based BCI training on the cortical activity elicited by mental imagery , 2014, Journal of neural engineering.
[88] S. Cramer,et al. Motor imagery during movement activates the brain more than movement alone after stroke: a pilot study. , 2014, Journal of rehabilitation medicine.
[89] R. Rosenfeld. Patients , 2012, Otolaryngology--head and neck surgery : official journal of American Academy of Otolaryngology-Head and Neck Surgery.
[90] I. Toni,et al. Distinct roles for alpha- and beta-band oscillations during mental simulation of goal-directed actions. , 2014, The Journal of neuroscience : the official journal of the Society for Neuroscience.
[91] Chetwyn C H Chan,et al. Pilot randomized controlled trial of self-regulation in promoting function in acute poststroke patients. , 2014, Archives of physical medicine and rehabilitation.
[92] Vera Kaiser,et al. Cortical effects of user training in a motor imagery based brain–computer interface measured by fNIRS and EEG , 2014, NeuroImage.
[93] Timothy Bardouille,et al. Laterality of brain activity during motor imagery is modulated by the provision of source level neurofeedback , 2014, NeuroImage.
[94] M. Molinari,et al. Proof of principle of a brain-computer interface approach to support poststroke arm rehabilitation in hospitalized patients: design, acceptability, and usability. , 2015, Archives of physical medicine and rehabilitation.
[95] Ian Wellwood,et al. The Effect of Combined Somatosensory Stimulation and Task-Specific Training on Upper Limb Function in Chronic Stroke , 2015, Neurorehabilitation and neural repair.
[96] L. Cohen,et al. Brain–machine interfaces in neurorehabilitation of stroke , 2015, Neurobiology of Disease.