Format
Sort by
Items per page

Send to

Choose Destination

Links from PubMed

Items: 1 to 20 of 196

1.

Multimodal sensory feedback associated with motor attempts alters BOLD responses to paralyzed hand movement in chronic stroke patients.

Ono T, Tomita Y, Inose M, Ota T, Kimura A, Liu M, Ushiba J.

Brain Topogr. 2015 Mar;28(2):340-51. doi: 10.1007/s10548-014-0382-6. Epub 2014 Jul 23.

PMID:
25053224
2.

Feasibility of a new application of noninvasive Brain Computer Interface (BCI): a case study of training for recovery of volitional motor control after stroke.

Daly JJ, Cheng R, Rogers J, Litinas K, Hrovat K, Dohring M.

J Neurol Phys Ther. 2009 Dec;33(4):203-11. doi: 10.1097/NPT.0b013e3181c1fc0b.

PMID:
20208465
3.

Think to move: a neuromagnetic brain-computer interface (BCI) system for chronic stroke.

Buch E, Weber C, Cohen LG, Braun C, Dimyan MA, Ard T, Mellinger J, Caria A, Soekadar S, Fourkas A, Birbaumer N.

Stroke. 2008 Mar;39(3):910-7. doi: 10.1161/STROKEAHA.107.505313. Epub 2008 Feb 7.

4.

Brain oscillatory signatures of motor tasks.

Ramos-Murguialday A, Birbaumer N.

J Neurophysiol. 2015 Jun 1;113(10):3663-82. doi: 10.1152/jn.00467.2013. Epub 2015 Mar 25.

5.

Event-related desynchronization reflects downregulation of intracortical inhibition in human primary motor cortex.

Takemi M, Masakado Y, Liu M, Ushiba J.

J Neurophysiol. 2013 Sep;110(5):1158-66. doi: 10.1152/jn.01092.2012. Epub 2013 Jun 12.

PMID:
23761697
6.

Using ipsilateral motor signals in the unaffected cerebral hemisphere as a signal platform for brain-computer interfaces in hemiplegic stroke survivors.

Bundy DT, Wronkiewicz M, Sharma M, Moran DW, Corbetta M, Leuthardt EC.

J Neural Eng. 2012 Jun;9(3):036011. doi: 10.1088/1741-2560/9/3/036011. Epub 2012 May 22.

7.

Brain-computer interface with somatosensory feedback improves functional recovery from severe hemiplegia due to chronic stroke.

Ono T, Shindo K, Kawashima K, Ota N, Ito M, Ota T, Mukaino M, Fujiwara T, Kimura A, Liu M, Ushiba J.

Front Neuroeng. 2014 Jul 7;7:19. doi: 10.3389/fneng.2014.00019. eCollection 2014.

8.

Ipsilateral EEG mu rhythm reflects the excitability of uncrossed pathways projecting to shoulder muscles.

Hasegawa K, Kasuga S, Takasaki K, Mizuno K, Liu M, Ushiba J.

J Neuroeng Rehabil. 2017 Aug 25;14(1):85. doi: 10.1186/s12984-017-0294-2.

9.

Daily training with realistic visual feedback improves reproducibility of event-related desynchronisation following hand motor imagery.

Ono T, Kimura A, Ushiba J.

Clin Neurophysiol. 2013 Sep;124(9):1779-86. doi: 10.1016/j.clinph.2013.03.006. Epub 2013 May 3.

PMID:
23643578
10.

The role of the unaffected hemisphere in motor recovery after stroke.

Riecker A, Gröschel K, Ackermann H, Schnaudigel S, Kassubek J, Kastrup A.

Hum Brain Mapp. 2010 Jul;31(7):1017-29. doi: 10.1002/hbm.20914.

PMID:
20091792
11.

Functional recovery in upper limb function in stroke survivors by using brain-computer interface A single case A-B-A-B design.

Ono T, Mukaino M, Ushiba J.

Conf Proc IEEE Eng Med Biol Soc. 2013;2013:265-8. doi: 10.1109/EMBC.2013.6609488.

PMID:
24109675
12.

Proprioceptive feedback and brain computer interface (BCI) based neuroprostheses.

Ramos-Murguialday A, Schürholz M, Caggiano V, Wildgruber M, Caria A, Hammer EM, Halder S, Birbaumer N.

PLoS One. 2012;7(10):e47048. doi: 10.1371/journal.pone.0047048. Epub 2012 Oct 5.

13.

Effect of real-time cortical feedback in motor imagery-based mental practice training.

Bai O, Huang D, Fei DY, Kunz R.

NeuroRehabilitation. 2014;34(2):355-63. doi: 10.3233/NRE-131039.

PMID:
24401829
14.

Applying a brain-computer interface to support motor imagery practice in people with stroke for upper limb recovery: a feasibility study.

Prasad G, Herman P, Coyle D, McDonough S, Crosbie J.

J Neuroeng Rehabil. 2010 Dec 14;7:60. doi: 10.1186/1743-0003-7-60.

15.

Effects of neurofeedback training with an electroencephalogram-based brain-computer interface for hand paralysis in patients with chronic stroke: a preliminary case series study.

Shindo K, Kawashima K, Ushiba J, Ota N, Ito M, Ota T, Kimura A, Liu M.

J Rehabil Med. 2011 Oct;43(10):951-7. doi: 10.2340/16501977-0859.

16.

Lesion location alters brain activation in chronically impaired stroke survivors.

Luft AR, Waller S, Forrester L, Smith GV, Whitall J, Macko RF, Schulz JB, Hanley DF.

Neuroimage. 2004 Mar;21(3):924-35.

PMID:
15006659
17.

Network interactions underlying mirror feedback in stroke: A dynamic causal modeling study.

Saleh S, Yarossi M, Manuweera T, Adamovich S, Tunik E.

Neuroimage Clin. 2016 Nov 21;13:46-54. eCollection 2017.

18.

Neurophysiological substrates of stroke patients with motor imagery-based Brain-Computer Interface training.

Li M, Liu Y, Wu Y, Liu S, Jia J, Zhang L.

Int J Neurosci. 2014 Jun;124(6):403-15. doi: 10.3109/00207454.2013.850082. Epub 2013 Oct 31.

PMID:
24079396
19.

Comparison of blood-oxygen-level-dependent functional magnetic resonance imaging and near-infrared spectroscopy recording during functional brain activation in patients with stroke and brain tumors.

Sakatani K, Murata Y, Fujiwara N, Hoshino T, Nakamura S, Kano T, Katayama Y.

J Biomed Opt. 2007 Nov-Dec;12(6):062110. doi: 10.1117/1.2823036. Review.

PMID:
18163813
20.

Acquired control of ventral premotor cortex activity by feedback training: an exploratory real-time FMRI and TMS study.

Sitaram R, Veit R, Stevens B, Caria A, Gerloff C, Birbaumer N, Hummel F.

Neurorehabil Neural Repair. 2012 Mar-Apr;26(3):256-65. doi: 10.1177/1545968311418345. Epub 2011 Sep 8.

PMID:
21903976

Supplemental Content

Support Center