Posts Tagged chronic

[Abstract] Comparison of Task Oriented Approach and Mirror Therapy for Poststroke Hand Function Rehabilitation

Abstract

Objective: The purpose of this study was to compare the effectiveness of task-oriented therapy and mirror therapy on improving hand function in post-stroke patients.
Methods: Total subjects 30 were randomly divided into two groups: the task-oriented group (15 patients) and the mirror therapy group (15 patients). The task-oriented group underwent task-oriented training for 45 mins a day for 5 days a week for 4 weeks. The mirror therapy group underwent a mirror therapy program under the same schedule as
task-oriented therapy. The manual dexterity and motor functioning of the hand were evaluated before the intervention and 4 weeks after the intervention by using FMA (Fugl-Meyer assessment) and BBT (Box & Block test).
Results: Hand function of all patients increased significantly after the 4-week intervention program on the evaluation of motor function and manual dexterity by FMA and BBT in both the groups of Task-Oriented approach and Mirror therapy, but Group A Task-oriented approach improved more significantly when compared to Group B Mirror therapy.
Conclusion: The treatment effect was more in patients who received a Task-Oriented approach compared to Mirror therapy. These findings suggest that the Task-Oriented approach was more effective in post stoke hand function rehabilitation.

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[ARTICLE] Relationship Between Motor Capacity of the Contralesional and Ipsilesional Hand Depends on the Side of Stroke in Chronic Stroke Survivors With Mild-to-Moderate Impairment – Full Text

There is growing evidence that after a stroke, sensorimotor deficits in the ipsilesional hand are related to the degree of impairment in the contralesional upper extremity. Here, we asked if the relationship between the motor capacities of the two hands differs based on the side of stroke. Forty-two pre-morbidly right-handed chronic stroke survivors (left hemisphere damage, LHD = 21) with mild-to-moderate paresis performed distal items of the Wolf Motor Function Test (dWMFT). We found that compared to RHD, the relationship between contralesional arm impairment (Upper Extremity Fugl-Meyer, UEFM) and ipsilesional hand motor capacity was stronger (R2LHD=RLHD2= 0.42; R2RHDRRHD2 < 0.01; z = 2.12; p = 0.03) and the slope was steeper (t = −2.03; p = 0.04) in LHD. Similarly, the relationship between contralesional dWMFT and ipsilesional hand motor capacity was stronger (R2LHD=RLHD2= 0.65; R2RHDRRHD2 = 0.09; z = 2.45; p = 0.01) and the slope was steeper (t = 2.03; p = 0.04) in LHD compared to RHD. Multiple regression analysis confirmed the presence of an interaction between contralesional UEFM and side of stroke (β3 = 0.66 ± 0.30; p = 0.024) and between contralesional dWMFT and side of stroke (β3 = −0.51 ± 0.34; p = 0.05). Our findings suggest that the relationship between contra- and ipsi-lesional motor capacity depends on the side of stroke in chronic stroke survivors with mild-to-moderate impairment. When contralesional impairment is more severe, the ipsilesional hand is proportionally slower in those with LHD compared to those with RHD.

Introduction

It is now well-known that unilateral stroke not only results in weakness of the opposite half of the body, i.e., contralateral to the lesion or contralesional limb, but also significant motor deficits in the same half of the body, i.e., ipsilateral to the lesion or ipsilesional limb (14). Previous work suggests that deficits in the ipsilesional arm and hand varies with the severity of contralesional deficits, especially in the sub-acute and chronic phase after stroke (58). More interestingly, the unilateral motor deficits observed for contralesional and ipsilesional limbs seem to be hemisphere-specific and thus depend on side of stroke lesion (915). For predominantly right-handed cohorts, contralesional deficits appear to be more severe in those with right hemisphere damage (RHD), in whom the contralesional limb is non-dominant. For example, using clinical motor assessments of grip strength and hand dexterity, Harris and Eng (11) showed that contralesional motor impairments were less severe in chronic stroke survivors who suffered damage in the dominant (i.e., left) hemisphere (LHD) compared to those who suffered damage in the non-dominant (right) hemisphere (1115).

In contrast, considering ipsilesional motor deficits, the evidence is mixed concerning hemisphere-specific effects. For instance, some studies reported that individuals with LHD exhibited more severe ipsilesional arm and hand deficits compared to those with RHD (41517) while others have reported no difference in ipsilesional hand motor capacity between LHD and RHD (2). In acute stroke survivors, Nowak et al. demonstrated that deficits in grip force of the ipsilesional hand were significantly associated with clinical measures of function of the contralesional hand only in LHD (12). Contrary to this, de Paiva Silva et al. (14) found that compared to controls and LHD, the ipsilesional hand in chronic stroke survivors was significantly slower and less smooth in RHD especially when contralesional impairment was relatively more severe (UEFM < 34).

Taken together, there is converging evidence regarding the relationship between motor deficits of the contralesional and ipsilesional upper extremity, such that ipsilesional deficits are worse when contralesional impairment is greater (Figure 1A); however, it is uncertain whether the relationship between the two limbs depends on which hemisphere is damaged. In particular, motor deficits of the two limbs are most prominent for tasks that require dexterous motor control (e.g., grip force, tapping, tracking). For predominantly right-handed cohorts (as is the case in most studies), contralesional deficits appear to be more severe in those with RHD, in whom the contralesional limb is non-dominant; whereas ipsilesional deficits are more severe in those with LHD. An exception to this observation for those with RHD seems to be in the case when contralesional impairment is most severe (i.e., UEFM < 34) (14). Thus, one might predict that as contralesional impairment worsens, individuals with LHD would have proportionally worse ipsilesional deficits, but individuals with RHD (especially if say UEFM > 34) would not; see Figures 1B,C for two alternative hypotheses. To our knowledge, this prediction has not before been explicitly tested.

Figure 1. Hypothesized effects represented in schematic figure. (A) The null hypothesis, wherein the relationship between contralesional (CL) impairment and ipsilesional (IL) motor capacity is not modified by the side of stroke lesion, i.e., β1 ≠ 0 but β3 = 0. (B) Alternative hypothesis 1, wherein ipsilesional deficits are related to contralesional impairment but only in LHD (blue) and not in RHD (red). (C) Alternate hypothesis 2, wherein ipsilesional deficits are related to contralesional impairment but only in LHD and in RHD with severe impairment (represented in the shaded dark-gray area). For both alternate hypotheses, β1 and β3 ≠ 0.

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via Frontiers | Relationship Between Motor Capacity of the Contralesional and Ipsilesional Hand Depends on the Side of Stroke in Chronic Stroke Survivors With Mild-to-Moderate Impairment | Neurology

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[Abstract] Pushing the limits of recovery in chronic stroke survivors: User perceptions of the Queen Square Upper Limb Neurorehabilitation Programme – Full Text PDF

Abstract

Introduction: The Queen Square Upper Limb (QSUL) Neurorehabilitation Programme is a clinical service within the National Health Service in the United Kingdom that provides 90 hours of therapy over three weeks to stroke survivors with persistent upper limb impairment. This study aimed to explore the perceptions of participants of this programme, including clinicians, stroke survivors and carers.

Design: Descriptive qualitative.

Setting: Clinical outpatient neurorehabilitation service.

Participants: Clinicians (physiotherapists, occupational therapists, rehabilitation assistants) involved in the delivery of the QSUL Programme, as well as stroke survivors and carers who had participated in the programme were purposively sampled. Each focus group followed a series of semi-structured, open questions that were tailored to the clinical or stroke group. One independent researcher facilitated all focus groups, which were audio-recorded, transcribed verbatim and analysed by four researchers using a thematic approach to identify main themes.

Results: Four focus groups were completed: three including stroke survivors (n = 16) and carers (n = 2), and one including clinicians (n = 11). The main stroke survivor themes related to psychosocial aspects of the programme (″ you feel valued as an individual ″), as well as the behavioural training provided (″ gruelling, yet rewarding& [Prime]). The main clinician themes also included psychosocial aspects of the programme (″ patient driven ethos − no barriers, no rules ″), and knowledge, skills and resources of clinicians (″ it is more than intensity, it is complex ″).

Conclusions: As an intervention, the QSUL Programme is both comprehensive and complex. The impact of participation in the programme spans psychosocial and behavioural domains from the perspectives of both the stroke survivor and clinician.

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via Pushing the limits of recovery in chronic stroke survivors: User perceptions of the Queen Square Upper Limb Neurorehabilitation Programme. | medRxiv

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[Abstract] Timing-dependent interaction effects of tDCS with mirror therapy on upper extremity motor recovery in patients with chronic stroke: A randomized controlled pilot study

Highlights

  • The priming effect of dual tDCS was important to facilitate motor recovery in combination with mirror therapy in stroke.

Abstract

This study was a randomized, controlled pilot trial to investigate the timing-dependent interaction effects of dual transcranial direct current stimulation (tDCS) in mirror therapy (MT) for hemiplegic upper extremity in patients with chronic stroke. Thirty patients with chronic stroke were randomly assigned to three groups: tDCS applied before MT (prior-tDCS group), tDCS applied during MT (concurrent-tDCS group), and sham tDCS applied randomly prior to or concurrent with MT (sham-tDCS group). Dual tDCS at 1 mA was applied bilaterally over the ipsilesional M1 (anodal electrode) and the contralesional M1 (cathodal electrode) for 30 min. The intervention was delivered five days per week for two weeks. Upper extremity motor performance was measured using the Fugl-Meyer Assessment-Upper Extremity (FMA-UE), the Action Research Arm Test (ARAT), and the Box and Block Test (BBT). Assessments were administered at baseline, post-intervention, and two weeks follow-up. The results indicated that concurrent-tDCS group showed significant improvements in the ARAT in relation to the prior-tDCS group and sham-tDCS group at post-intervention. Besides, a trend toward greater improvement was also found in the FMA-UE for the concurrent-tDCS group. However, no statistically significant difference in the FMA-UE and BBT was identified among the three groups at either post-intervention or follow-up. The concurrent-tDCS seems to be more advantageous and time-efficient in the context of clinical trials combining with MT. The timing-dependent interaction factor of tDCS to facilitate motor recovery should be considered in future clinical application.

via Timing-dependent interaction effects of tDCS with mirror therapy on upper extremity motor recovery in patients with chronic stroke: A randomized controlled pilot study – Journal of the Neurological Sciences

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[Abstract] Motor Imagery Based Brain-Computer Interface Control of Continuous Passive Motion for Wrist Extension Recovery in Chronic Stroke Patients

Highlights

  • Twenty-one patients successfully recovered active wrist extension.
  • Motor imagery based BCI control of wrist CPM training was applied.
  • Typical spatial and spectrum patterns of ERD/ERS formed after training.

Abstract

Motor recovery of wrist and fingers is still a great challenge for chronic stroke survivors. The present study aimed to verify the efficiency of motor imagery based brain-computer interface (BCI) control of continuous passive motion (CPM) in the recovery of wrist extension due to stroke. An observational study was conducted in 26 chronic stroke patients, aged 49.0 ± 15.4 years, with upper extremity motor impairment. All patients showed no wrist extension recovery. A 24-channel highresolution electroencephalogram (EEG) system was used to acquire cortical signal while they were imagining extension of the affected wrist. Then, 20 sessions of BCI-driven CPM training were carried out for 6 weeks. Primary outcome was the increase of active range of motion (ROM) of the affected wrist from the baseline to final evaluation. Improvement of modified Barthel Index, EEG classification and motor imagery pattern of wrist extension were recorded as secondary outcomes. Twenty-one patients finally passed the EEG screening and completed all the BCI-driven CPM trainings. From baseline to the final evaluation, the increase of active ROM of the affected wrists was (24.05 ± 14.46)˚. The increase of modified Barthel Index was 3.10 ± 4.02 points. But no statistical difference was detected between the baseline and final evaluations (P > 0.05). Both EEG classification and motor imagery pattern improved. The present study demonstrated beneficial outcomes of MI-based BCI control of CPM training in motor recovery of wrist extension using motor imagery signal of brain in chronic stroke patients.

 

Graphical abstract

via Motor Imagery Based Brain-Computer Interface Control of Continuous Passive Motion for Wrist Extension Recovery in Chronic Stroke Patients – ScienceDirect

 

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[Abstract + References] Perspectives: Hemianopia—Toward Novel Treatment Options Based on Oscillatory Activity?

Stroke has become one of the main causes of visual impairment, with more than 15 million incidences of first-time strokes, per year, worldwide. One-third of stroke survivors exhibit visual impairment, and most of them will not fully recover. Some recovery is possible, but this usually happens in the first few weeks after a stroke.

Most of the rehabilitation options that are offered to patients are compensatory, such as optical aids or eye training. However, these techniques do not seem to provide a sufficient amount of improvement transferable to everyday life.

Based on the relatively recent idea that the visual system can actually recover from a chronic lesion, visual retraining protocols have emerged, sometimes even in combination with noninvasive brain stimulation (NIBS), to further boost plastic changes in the residual visual tracts and network.

The present article reviews the underlying mechanisms supporting visual retraining and describes the first clinical trials that applied NIBS combined with visual retraining. As a further perspective, it gathers the scientific evidence demonstrating the relevance of interregional functional synchronization of brain networks for visual field recovery, especially the causal role of α and γ oscillations in parieto-occipital regions.

Because transcranial alternating current stimulation (tACS) can induce frequency-specific entrainment and modulate spike timing–dependent plasticity, we present a new promising interventional approach, consisting of applying physiologically motivated tACS protocols based on multifocal cross-frequency brain stimulation of the visuoattentional network for visual field recovery.

1. Dagnelie, G. Age-related psychophysical changes and low vision. Invest Opthalmol Vis Sci. 2013;54:ORSF88ORSF93.
Google Scholar | Crossref | Medline


2. Court, H, McLean, G, Guthrie, B, Mercer, SW, Smith, DJ. Visual impairment is associated with physical and mental comorbidities in older adults: a cross-sectional study. BMC Med. 2014;12:181.
Google Scholar | Crossref | Medline | ISI


3. World Health Organization . Action Plan for the Prevention of Avoidable Blindness and Visual Impairment 2009-2013. Geneva, SwitzerlandWorld Health Organization2010.
Google Scholar


4. Allen, CM, Marshell, MJG, Wade, DT. The Management of Acute Stroke. Kent, EnglandCastle House Publications1988.
Google Scholar


5. Zhang, X, Kedar, S, Lynn, MJ, Newman, NJ, Biousse, V. Natural history of homonymous hemianopia. Neurology. 2006;66:901905.
Google Scholar | Crossref | Medline | ISI


6. Naeem, Z. The prevalence of visual problems in stroke patients and the effectiveness of the current screening tool used. Br Ir Orthopt J. 2015;9:5558.
Google Scholar | Crossref


7. Rowe, FJ, Wright, D, Brand, D, et alA prospective profile of visual field loss following stroke: prevalence, type, rehabilitation, and outcome. Biomed Res Int. 2013;2013:719096.
Google Scholar | Crossref | Medline | ISI


8. Liu, GT, Volpe, NJ, Galetta, SL. Retrochiasmal disorders. In: Neuro-Ophthalmology: Diagnosis and Management. Philadelphia, PAWB Saunders2001:296.
Google Scholar


9. Peli, E, Apfelbaum, H, Berson, EL, Goldstein, RB. The risk of pedestrian collisions with peripheral visual field loss. J Vis. 2016;16:5.
Google Scholar | Crossref | Medline


10. Ungewiss, J, Kübler, T, Sippel, K, et al; Simulator/On-Road Study Group . Agreement of driving simulator and on-road driving performance in patients with binocular visual field loss. Graefes Arch Clin Exp Ophthalmol. 2018;256:24292435.
Google Scholar | Crossref | Medline


11. Chen, CS, Lee, AW, Clarke, G, et alVision-related quality of life in patients with complete homonymous hemianopia post stroke. Top Stroke Rehabil. 2009;16:445453.
Google Scholar | Crossref | Medline


12. Papageorgiou, E, Hardiess, G, Schaeffel, F, et alAssessment of vision-related quality of life in patients with homonymous visual field defects. Graefes Arch Clin Exp Ophthalmol. 2007;245:17491758.
Google Scholar | Crossref | Medline | ISI


13. Kaplan, J, Hier, DB. Visuospatial deficits after right hemisphere stroke. Am J Occup Ther. 1982;36:314321.
Google Scholar | Crossref | Medline | ISI


14. Pambakian, AL, Kennard, C. Can visual function be restored in patients with homonymous hemianopia? Br J Ophthalmol. 1997;81:324328.
Google Scholar | Crossref | Medline | ISI


15. Bowers, AR, Keeney, K, Peli, E. Randomized crossover clinical trial of real and sham peripheral prism glasses for hemianopia. JAMA Ophthalmol. 2014;132:214222.
Google Scholar | Crossref | Medline | ISI


16. Rowe, FJ, Conroy, EJ, Bedson, E, et alA pilot randomized controlled trial comparing effectiveness of prism glasses, visual search training and standard care in hemianopia. Acta Neurol Scand. 2017;136:310321.
Google Scholar | Crossref | Medline


17. Gottlieb, DD, Fuhr, A, Hatch, WV, Wright, KD. Neuro-optometric facilitation of vision recovery after acquired brain injury. NeuroRehabilitation. 1998;11:175199.
Google Scholar | Crossref | Medline


18. Lee, AG, Perez, AM. Improving awareness of peripheral visual field using sectorial prism. J Am Optom Assoc. 1999;70:624628.
Google Scholar | Medline


19. Szlyk, JP, Seiple, W, Stelmack, J, McMahon, T. Use of prisms for navigation and driving in hemianopic patients. Ophthalmic Physiol Opt. 2005;25:128135.
Google Scholar | Crossref | Medline


20. Peli, E. Field expansion for homonymous hemianopia by optically induced peripheral exotropia. Optom Vis Sci. 2000;77:453464.
Google Scholar | Crossref | Medline | ISI


21. Hayes, A, Chen, CS, Clarke, G, Thompson, A. Functional improvements following the use of the NVT Vision Rehabilitation program for patients with hemianopia following stroke. NeuroRehabilitation. 2012;31:1930.
Google Scholar | Crossref | Medline


22. Nelles, G, Pscherer, A, de Greiff, A, et alEye-movement training-induced plasticity in patients with post-stroke hemianopia. J Neurol. 2009;256:726733.
Google Scholar | Crossref | Medline | ISI


23. Mannan, SK, Pambakian, ALM, Kennard, C. Compensatory strategies following visual search training in patients with homonymous hemianopia: an eye movement study. J Neurol. 2010;257:18121821.
Google Scholar | Crossref | Medline | ISI


24. Lane, AR, Smith, DT, Ellison, A, Schenk, T. Visual exploration training is no better than attention training for treating hemianopia. Brain. 2010;133(pt 6):17171728.
Google Scholar | Crossref | Medline


25. Spitzyna, GA, Wise, RJS, McDonald, SA, et alOptokinetic therapy improves text reading in patients with hemianopic alexia: a controlled trial. Neurology. 2007;68:19221930.
Google Scholar | Crossref | Medline | ISI


26. Cowey, A, Stoerig, P, Perry, VH. Transneuronal retrograde degeneration of retinal ganglion cells after damage to striate cortex in macaque monkeys: selective loss of P beta cells. Neuroscience. 1989;29:6580.
Google Scholar | Crossref | Medline | ISI


27. Weller, RE, Kaas, JH. Parameters affecting the loss of ganglion cells of the retina following ablations of striate cortex in primates. Vis Neurosci. 1989;3:327349.
Google Scholar | Crossref | Medline | ISI


28. Stoerig, P. Blindsight, conscious vision, and the role of primary visual cortex. Prog Brain Res. 2006;155:217234.
Google Scholar | Crossref | Medline | ISI


29. Weiskrantz, L. Is blindsight just degraded normal vision? Exp Brain Res. 2009;192:413416.
Google Scholar | Crossref | Medline


30. Merrill, EG, Wall, PD. Factors forming the edge of a receptive field: the presence of relatively ineffective afferent terminals. J Physiol. 1972;226:825846.
Google Scholar | Crossref | Medline


31. Alloway, KD, Burton, H. Differential effects of GABA and bicuculline on rapidly- and slowly-adapting neurons in primary somatosensory cortex of primates. Exp Brain Res. 1991;85:598610.
Google Scholar | Crossref | Medline


32. Garraghty, PE, LaChica, EA, Kaas, JH. Injury-induced reorganization of somatosensory cortex is accompanied by reductions in GABA staining. Somatosens Mot Res. 1991;8:347354.
Google Scholar | Crossref | Medline | ISI


33. Chen, R, Corwell, B, Yaseen, Z, Hallett, M, Cohen, LG. Mechanisms of cortical reorganization in lower-limb amputees. J Neurosci. 1998;18:34433450.
Google Scholar | Crossref | Medline | ISI


34. Eysel, UT. Perilesional cortical dysfunction and reorganization. Adv Neurol. 1997;73:195206.
Google Scholar | Medline


35. Poggel, DA, Kasten, E, Müller-Oehring, EM, Sabel, BA, Brandt, SA. Unusual spontaneous and training induced visual field recovery in a patient with a gunshot lesion. J Neurol Neurosurg Psychiatry. 2001;70:236239.
Google Scholar | Crossref | Medline


36. Sabel, BA, Kasten, E, Kreutz, MR. Recovery of vision after partial visual system injury as a model of postlesion neuroplasticity. Adv Neurol. 1997;73:251276.
Google Scholar | Medline


37. Eysel, UT, Schweigart, G, Mittmann, T, et alReorganization in the visual cortex after retinal and cortical damage. Restor Neurol Neurosci. 1999;15:153164.
Google Scholar | Medline


38. Kaas, JH, Krubitzer, LA, Chino, YM, Langston, AL, Polley, EH, Blair, N. Reorganization of retinotopic cortical maps in adult mammals after lesions of the retina. Science. 1990;248:229231.
Google Scholar | Crossref | Medline | ISI


39. Heinen, SJ, Skavenski, AA. Recovery of visual responses in foveal V1 neurons following bilateral foveal lesions in adult monkey. Exp Brain Res. 1991;83:670674.
Google Scholar | Crossref | Medline | ISI


40. Horton, JC, Hocking, DR. Monocular core zones and binocular border strips in primate striate cortex revealed by the contrasting effects of enucleation, eyelid suture, and retinal laser lesions on cytochrome oxidase activity. J Neurosci. 1998;18:54335455.
Google Scholar | Crossref | Medline


41. Smirnakis, SM, Brewer, AA, Schmid, MC, et alLack of long-term cortical reorganization after macaque retinal lesions. Nature. 2005;435:300307.
Google Scholar | Crossref | Medline | ISI


42. Raninen, A, Vanni, S, Hyvärinen, L, Näsänen, R. Temporal sensitivity in a hemianopic visual field can be improved by long-term training using flicker stimulation. J Neurol Neurosurg Psychiatry. 2007;78:6673.
Google Scholar | Crossref | Medline | ISI


43. Casco, C, Barollo, M, Contemori, G, Battaglini, L. Neural restoration training improves visual functions and expands visual field of patients with homonymous visual field defects. Restor Neurol Neurosci. 2018;36:275291.
Google Scholar | Crossref | Medline


44. Przekoracka-Krawczyk, A, Michalski, A, Wojtczak-KwaÅ›niewska, M. Visual therapy in open space rehabilitation of acquired visual field defect. Neuropsychiatry. 2018;8:15271532.
Google Scholar | Crossref


45. Sahraie, A, Trevethan, CT, MacLeod, MJ, Murray, AD, Olson, JA, Weiskrantz, L. Increased sensitivity after repeated stimulation of residual spatial channels in blindsight. Proc Natl Acad Sci U S A. 2006;103:1497114976.
Google Scholar | Crossref | Medline | ISI


46. Kentridge, RW, Heywood, CA, Weiskrantz, L. Attention without awareness in blindsight. Proc Biol Sci. 1999;266:18051811.
Google Scholar | Crossref | Medline | ISI


47. Chokron, S, Perez, C, Obadia, M, Gaudry, I, Laloum, L, Gout, O. From blindsight to sight: cognitive rehabilitation of visual field defects. Restor Neurol Neurosci. 2008;26:305320.
Google Scholar | Medline | ISI


48. Kasten, E, Wüst, S, Behrens-Baumann, W, Sabel, BA. Computer-based training for the treatment of partial blindness. Nat Med. 1998;4:10831087.
Google Scholar | Crossref | Medline | ISI


49. Marshall, RS, Chmayssani, M, O’Brien, KA, Handy, C, Greenstein, VC. Visual field expansion after visual restoration therapy. Clin Rehabil. 2010;24:10271035.
Google Scholar | SAGE Journals | ISI


50. Horton, JC. Disappointing results from Nova Vision’s visual restoration therapy. Br J Ophthalmol. 2005;89:12.
Google Scholar | Crossref | Medline | ISI


51. Horton, JC. Vision restoration therapy: confounded by eye movements. Br J Ophthalmol. 2005;89:792794.
Google Scholar | Crossref | Medline | ISI


52. Pelak, VS, Dubin, M, Whitney, E. Homonymous hemianopia: a critical analysis of optical devices, compensatory training, and NovaVision. Curr Treat Options Neurol. 2007;9:4147.
Google Scholar | Crossref | Medline


53. McFadzean, RM. NovaVision: vision restoration therapy. Curr Opin Ophthalmol. 2006;17:498503.
Google Scholar | Crossref | Medline


54. Kasten, E, Bunzenthal, U, Sabel, BA. Visual field recovery after vision restoration therapy (VRT) is independent of eye movements: an eye tracker study. Behav Brain Res. 2006;175:1826.
Google Scholar | Crossref | Medline


55. Mueller, I, Mast, H, Sabel, BA. Recovery of visual field defects: a large clinical observational study using vision restoration therapy. Restor Neurol Neurosci. 2007;25:563572.
Google Scholar | Medline


56. Huxlin, KR. Perceptual plasticity in damaged adult visual systems. Vision Res. 2008;48:21542166.
Google Scholar | Crossref | Medline


57. Hanna, KL, Hepworth, LR, Rowe, FJ. The treatment methods for post-stroke visual impairment: a systematic review. Brain Behav. 2017;7:e00682.
Google Scholar | Crossref | Medline


58. Lefaucheur, JP, Antal, A, Ayache, SS, et alEvidence-based guidelines on the therapeutic use of transcranial direct current stimulation (tDCS). Clin Neurophysiol. 2017;128:5692.
Google Scholar | Crossref | Medline | ISI


59. Raffin, E, Hummel, FC. Restoring motor functions after stroke: multiple approaches and opportunities. Neuroscientist. 2018;24:400416http://journals.sagepub.com.gate2.inist.fr/eprint/qtCDdEqIpZjMxiFjkwJi/full. Accessed November 7, 2017.
Google Scholar


60. Wessel, MJ, Zimerman, M, Hummel, FC. Non-invasive brain stimulation: an interventional tool for enhancing behavioral training after stroke. Front Hum Neurosci. 2015;9:265.
Google Scholar | Crossref | Medline | ISI


61. Hummel, FC, Cohen, LG. Non-invasive brain stimulation: a new strategy to improve neurorehabilitation after stroke? Lancet Neurol. 2006;5:708712.
Google Scholar | Crossref | Medline | ISI


62. Di Pino, G, Pellegrino, G, Assenza, G, et alModulation of brain plasticity in stroke: a novel model for neurorehabilitation. Nat Rev Neurol. 2014;10:597608.
Google Scholar | Crossref | Medline | ISI


63. Spiegel, DP, Byblow, WD, Hess, RF, Thompson, B. Anodal transcranial direct current stimulation transiently improves contrast sensitivity and normalizes visual cortex activation in individuals with amblyopia. Neurorehabil Neural Repair. 2013;27:760769.
Google Scholar | SAGE Journals | ISI


64. Ding, Z, Li, J, Spiegel, DP, et alThe effect of transcranial direct current stimulation on contrast sensitivity and visual evoked potential amplitude in adults with amblyopia. Sci Rep. 2016;6:19280.
Google Scholar | Crossref | Medline


65. Bocci, T, Nasini, F, Caleo, M, et alUnilateral application of cathodal tDCS reduces transcallosal inhibition and improves visual acuity in amblyopic patients. Front Behav Neurosci. 2018;12:109.
Google Scholar | Crossref | Medline


66. Clavagnier, S, Thompson, B, Hess, RF. Long lasting effects of daily theta burst rTMS sessions in the human amblyopic cortex. Brain Stimul. 2013;6:860867.
Google Scholar | Crossref | Medline


67. Camilleri, R, Pavan, A, Campana, G. The application of online transcranial random noise stimulation and perceptual learning in the improvement of visual functions in mild myopia. Neuropsychologia. 2016;89:225231.
Google Scholar | Crossref | Medline


68. Camilleri, R, Pavan, A, Ghin, F, Battaglini, L, Campana, G. Improvement of uncorrected visual acuity and contrast sensitivity with perceptual learning and transcranial random noise stimulation in individuals with mild myopia. Front Psychol. 2014;5:1234.
Google Scholar | Crossref


69. Plow, EB, Obretenova, SN, Halko, MA, et alCombining visual rehabilitative training and noninvasive brain stimulation to enhance visual function in patients with hemianopia: a comparative case study. PM R. 2011;3:825835.
Google Scholar | Crossref | Medline


70. Matteo, BM, Viganò, B, Cerri, CG, Meroni, R, Cornaggia, CM, Perin, C. Transcranial direct current stimulation (tDCS) combined with blindsight rehabilitation for the treatment of homonymous hemianopia: a report of two-cases. J Phys Ther Sci. 2017;29:17001705.
Google Scholar | Crossref | Medline


71. Alber, R, Moser, H, Gall, C, Sabel, BA. Combined transcranial direct current stimulation and vision restoration training in subacute stroke rehabilitation: a pilot study. PM R. 2017;9:787794.
Google Scholar | Crossref | Medline


72. Antal, A, Alekseichuk, I, Bikson, M, et alLow intensity transcranial electric stimulation: safety, ethical, legal regulatory and application guidelines. Clin Neurophysiol. 2017;128:17741809.
Google Scholar | Crossref | Medline


73. Halko, M, Datta, A, Plow, EB, Scaturro, J, Bikson, M, Merabet, LB. Neuroplastic changes following rehabilitative training correlate with regional electrical field induced with tDCS. Neuroimage. 2011;57:885891.
Google Scholar | Crossref | Medline | ISI


74. Antal, A, Kincses, TZ, Nitsche, MA, Bartfai, O, Paulus, W. Excitability changes induced in the human primary visual cortex by transcranial direct current stimulation: direct electrophysiological evidence. Invest Ophthalmol Vis Sci. 2004;45:702707.
Google Scholar | Crossref | Medline | ISI


75. Lang, N, Siebner, HR, Chadaide, Z, et alBidirectional modulation of primary visual cortex excitability: a combined tDCS and rTMS study. Invest Ophthalmol Vis Sci. 2007;48:57825787.
Google Scholar | Crossref | Medline


76. Accornero, N, Li Voti, P, La Riccia, M, Gregori, B. Visual evoked potentials modulation during direct current cortical polarization. Exp Brain Res. 2007;178:261266.
Google Scholar | Crossref | Medline | ISI


77. Olma, MC, Dargie, RA, Behrens, JR, et alLong-term effects of serial anodal tDCS on motion perception in subjects with occipital stroke measured in the unaffected visual hemifield. Front Hum Neurosci. 2013;7:314https://www.frontiersin.org/articles/10.3389/fnhum.2013.00314/full#B14. Accessed September 11, 2018.
Google Scholar


78. Antal, A, Nitsche, MA, Paulus, W. External modulation of visual perception in humans. Neuroreport. 2001;12:35533555.
Google Scholar | Crossref | Medline | ISI


79. Behrens, JR, Kraft, A, Irlbacher, K, Gerhardt, H, Olma, MC, Brandt, SA. Long-lasting enhancement of visual perception with repetitive noninvasive transcranial direct current stimulation. Front Cell Neurosci. 2017;11:238.
Google Scholar | Crossref | Medline


80. Kraft, A, Roehmel, J, Olma, MC, Schmidt, S, Irlbacher, K, Brandt, SA. Transcranial direct current stimulation affects visual perception measured by threshold perimetry. Exp Brain Res. 2010;207:283290.
Google Scholar | Crossref | Medline | ISI


81. Liebetanz, D, Nitsche, MA, Tergau, F, Paulus, W. Pharmacological approach to the mechanisms of transcranial DC-stimulation–induced after-effects of human motor cortex excitability. Brain. 2002;125:22382247.
Google Scholar | Crossref | Medline | ISI


82. Stagg, CJ, Nitsche, MA. Physiological basis of transcranial direct current stimulation. Neuroscientist. 2011;17:3753.
Google Scholar | SAGE Journals | ISI


83. Bindman, LJ, Lippold, OCJ, Redfearn, JWT. Long-lasting changes in the level of the electrical activity of the cerebral cortex produced by polarizing currents. Nature. 1962;196:584585.
Google Scholar | Crossref | Medline | ISI


84. Creutzfeldt, OD, Fromm, GH, Kapp, H. Influence of transcortical d-c currents on cortical neuronal activity. Exp Neurol. 1962;5:436452.
Google Scholar | Crossref | Medline | ISI


85. Hummel, FC, Celnik, P, Pascual-Leone, A, et alControversy: noninvasive and invasive cortical stimulation show efficacy in treating stroke patients. Brain Stimul. 2008;1:370382.
Google Scholar | Crossref | Medline | ISI


86. Morishita, T, Hummel, FC. Non-invasive brain stimulation (NIBS) in motor recovery after stroke: concepts to increase efficacy. Curr Behav Neurosci Rep. 2017;4:280289.
Google Scholar | Crossref


87. Plow, EB, Obretenova, SN, Jackson, ML, Merabet, LB. Temporal profile of functional visual rehabilitative outcomes modulated by transcranial direct current stimulation. Neuromodulation. 2012;15:367373.
Google Scholar | Crossref | Medline | ISI


88. Larcombe, SJ, Kulyomina, Y, Antonova, N, et alVisual training in hemianopia alters neural activity in the absence of behavioural improvement: a pilot study. Ophthalmic Physiol Opt. 2018;38:538549.
Google Scholar | Crossref | Medline


89. Plow, EB, Obretenova, SN, Fregni, F, Pascual-Leone, A, Merabet, LB. Comparison of visual field training for hemianopia with active versus sham transcranial direct cortical stimulation. Neurorehabil Neural Repair. 2012;26:616626.
Google Scholar | SAGE Journals | ISI


90. Goebel, R, Muckli, L, Zanella, FE, Singer, W, Stoerig, P. Sustained extrastriate cortical activation without visual awareness revealed by fMRI studies of hemianopic patients. Vision Res. 2001;41:14591474.
Google Scholar | Crossref | Medline | ISI


91. Herpich, F, Melnick, MD, Agosta, S, Huxlin, KR, Tadin, D, Battelli, L. Boosting learning efficacy with non-invasive brain stimulation in intact and brain-damaged humans. J Neurosci. 2019;39:55515561.
Google Scholar | Crossref | Medline


92. Moret, B, Camilleri, R, Pavan, A, et alDifferential effects of high-frequency transcranial random noise stimulation (hf-tRNS) on contrast sensitivity and visual acuity when combined with a short perceptual training in adults with amblyopia. Neuropsychologia. 2018;114:125133.
Google Scholar | Crossref | Medline


93. Gall, C, Sgorzaly, S, Schmidt, S, Brandt, S, Fedorov, A, Sabel, B. Noninvasive transorbital alternating current stimulation improves subjective visual functioning and vision-related quality of life in optic neuropathy. Brain Stimul. 2011;4:175188.
Google Scholar | Crossref | Medline | ISI


94. Gall, C, Schmidt, S, Schittkowski, MP, et alAlternating current stimulation for vision restoration after optic nerve damage: a randomized clinical trial. PLoS One. 2016;11:e0156134.
Google Scholar | Crossref | Medline


95. Fedorov, A, Chibisova, Y, Szymaszek, A, Alexandrov, M, Gall, C, Sabel, BA. Non-invasive alternating current stimulation induces recovery from stroke. Restor Neurol Neurosci. 2010;28:825833.
Google Scholar | Medline


96. Sabel, BA, Fedorov, AB, Naue, N, Borrmann, A, Herrmann, C, Gall, C. Non-invasive alternating current stimulation improves vision in optic neuropathy. Restor Neurol Neurosci. 2011;29:493505.
Google Scholar | Medline


97. Schmidt, S, Mante, A, Rönnefarth, M, Fleischmann, R, Gall, C, Brandt, SA. Progressive enhancement of alpha activity and visual function in patients with optic neuropathy: a two-week repeated session alternating current stimulation study. Brain Stimul. 2013;6:8793.
Google Scholar | Crossref | Medline


98. Bola, M, Gall, C, Moewes, C, Fedorov, A, Hinrichs, H, Sabel, BA. Brain functional connectivity network breakdown and restoration in blindness. Neurology. 2014;83:542551.
Google Scholar | Crossref | Medline | ISI


99. Sabel, BA, Hamid, AIA, Borrmann, C, Speck, O, Antal, A. Transorbital alternating current stimulation modifies BOLD activity in healthy subjects and in a stroke patient with hemianopia: a 7 Tesla fMRI feasibility study [published online April 9, 2019]. Int J Psychophysiol. doi:10.1016/j.ijpsycho.2019.04.0022019http://www.sciencedirect.com/science/article/pii/S0167876018310559. Accessed October 10, 2019.
Google Scholar


100. Miyake, K, Yoshida, M, Inoue, Y, Hata, Y. Neuroprotective effect of transcorneal electrical stimulation on the acute phase of optic nerve injury. Invest Ophthalmol Vis Sci. 2007;48:23562361.
Google Scholar | Crossref | Medline


101. Sergeeva, EG, Bola, M, Wagner, S, et alRepetitive transcorneal alternating current stimulation reduces brain idling state after long-term vision loss. Brain Stimul. 2015;8:10651073.
Google Scholar | Crossref | Medline


102. Sergeeva, EG, Fedorov, AB, Henrich-Noack, P, Sabel, BA. Transcorneal alternating current stimulation induces EEG “aftereffects” only in rats with an intact visual system but not after severe optic nerve damage. J Neurophysiol. 2012;108:24942500.
Google Scholar | Crossref | Medline


103. Lewis, PM, Ackland, HM, Lowery, AJ, Rosenfeld, JV. Restoration of vision in blind individuals using bionic devices: a review with a focus on cortical visual prostheses. Brain Res. 2015;1595:5173.
Google Scholar | Crossref | Medline | ISI


104. Rahmatnejad, K, Ahmed, OM, Waisbourd, M, Katz, LJ. Non-invasive electrical stimulation for vision restoration: dream or reality? Expert Rev Ophthalmol. 2016;11:325327.
Google Scholar | Crossref


105. Buzsáki, G. Rhythms of the Brain. Oxford, EnglandOxford University Press2006.
Google Scholar | Crossref


106. Klimesch, W, Fellinger, R, Freunberger, R. Alpha oscillations and early stages of visual encoding. Front Psychol. 2011;2:118http://journal.frontiersin.org.gate2.inist.fr/article/10.3389/fpsyg.2011.00118/full. Accessed September 25, 2017.
Google Scholar


107. Jensen, O, Mazaheri, A. Shaping functional architecture by oscillatory alpha activity: gating by inhibition. Front Hum Neurosci. 2010;4:186.
Google Scholar | Crossref | Medline | ISI


108. Cooper, NR, Croft, RJ, Dominey, SJJ, Burgess, AP, Gruzelier, JH. Paradox lost? Exploring the role of alpha oscillations during externally vs internally directed attention and the implications for idling and inhibition hypotheses. Int J Psychophysiol. 2003;47:6574.
Google Scholar | Crossref | Medline | ISI


109. Worden, MS, Foxe, JJ, Wang, N, Simpson, GV. Anticipatory biasing of visuospatial attention indexed by retinotopically specific alpha-band electroencephalography increases over occipital cortex. J Neurosci. 2000;20:RC63.
Google Scholar | Crossref | Medline | ISI


110. Sauseng, P, Klimesch, W, Stadler, W, et alA shift of visual spatial attention is selectively associated with human EEG alpha activity. Eur J Neurosci. 2005;22:29172926.
Google Scholar | Crossref | Medline


111. Rajagovindan, R, Ding, M. From prestimulus alpha oscillation to visual-evoked response: an inverted-U function and its attentional modulation. J Cogn Neurosci. 2011;23:13791394.
Google Scholar | Crossref | Medline


112. van Ede, F, de Lange, F, Jensen, O, Maris, E. Orienting attention to an upcoming tactile event involves a spatially and temporally specific modulation of sensorimotor alpha- and beta-band oscillations. J Neurosci. 2011;31:20162024.
Google Scholar | Crossref | Medline


113. Klimesch, W. α-Band oscillations, attention, and controlled access to stored information. Trends Cogn Sci. 2012;16:606617.
Google Scholar | Crossref | Medline | ISI


114. Magazzini, L, Singh, KD. Spatial attention modulates visual gamma oscillations across the human ventral stream. Neuroimage. 2018;166:219229.
Google Scholar | Crossref | Medline


115. Fries, P, Reynolds, JH, Rorie, AE, Desimone, R. Modulation of oscillatory neuronal synchronization by selective visual attention. Science. 2001;291:15601563.
Google Scholar | Crossref | Medline | ISI


116. Cabral-Calderin, Y, Wilke, M. Probing the link between perception and oscillations: lessons from transcranial alternating current stimulation [published online February 7, 2019]. Neuroscientist. doi:10.1177/1073858419828646
Google Scholar | SAGE Journals


117. Akam, T, Kullmann, DM. Oscillatory multiplexing of population codes for selective communication in the mammalian brain. Nat Rev Neurosci. 2014;15:111122.
Google Scholar | Crossref | Medline


118. Singer, W. Neuronal synchrony: a versatile code for the definition of relations? Neuron. 1999;24:4965, 111-125.
Google Scholar | Crossref | Medline | ISI


119. Fries, P. A mechanism for cognitive dynamics: neuronal communication through neuronal coherence. Trends Cogn Sci. 2005;9:474480.
Google Scholar | Crossref | Medline | ISI


120. Fries, P. Rhythms for cognition: communication through coherence. Neuron. 2015;88:220235.
Google Scholar | Crossref | Medline


121. Jensen, O, Bonnefond, M, VanRullen, R. An oscillatory mechanism for prioritizing salient unattended stimuli. Trends Cogn Sci. 2012;16:200206.
Google Scholar | Crossref | Medline | ISI


122. Foxe, JJ, Snyder, AC. The role of alpha-band brain oscillations as a sensory suppression mechanism during selective attention. Front Psychol. 2011;2:154.
Google Scholar | Crossref | Medline


123. Bonnefond, M, Kastner, S, Jensen, O. Communication between brain areas based on nested oscillations. eNeuro. 2017;4:ENEURO.0153-16.2017.
Google Scholar | Crossref | Medline


124. von Stein, A, Chiang, C, König, P. Top-down processing mediated by interareal synchronization. Proc Natl Acad Sci U S A. 2000;97:1474814753.
Google Scholar | Crossref | Medline | ISI


125. van Kerkoerle, T, Self, MW, Dagnino, B, et alAlpha and gamma oscillations characterize feedback and feedforward processing in monkey visual cortex. Proc Natl Acad Sci U S A. 2014;111:1433214341.
Google Scholar | Crossref | Medline


126. Bastos, AM, Vezoli, J, Bosman, CA, et alVisual areas exert feedforward and feedback influences through distinct frequency channels. Neuron. 2015;85:390401.
Google Scholar | Crossref | Medline


127. Jensen, O, Bonnefond, M, Marshall, TR, Tiesinga, P. Oscillatory mechanisms of feedforward and feedback visual processing. Trends Neurosci. 2015;38:192194.
Google Scholar | Crossref | Medline


128. Michalareas, G, Vezoli, J, van Pelt, S, Schoffelen, J-M, Kennedy, H, Fries, P. Alpha-beta and gamma rhythms subserve feedback and feedforward influences among human visual cortical areas. Neuron. 2016;89:384397.
Google Scholar | Crossref | Medline


129. Richter, CG, Coppola, R, Bressler, SL. Top-down beta oscillatory signaling conveys behavioral context in early visual cortex. Sci Rep. 2018;8:6991.
Google Scholar | Crossref | Medline


130. Antal, A, Paulus, W. Transcranial alternating current stimulation (tACS). Front Hum Neurosci. 2013;7:317.
Google Scholar | Crossref | Medline | ISI


131. Herrmann, CS, Rach, S, Neuling, T, Strüber, D. Transcranial alternating current stimulation: a review of the underlying mechanisms and modulation of cognitive processes. Front Hum Neurosci. 2013;7:279.
Google Scholar | Crossref | Medline | ISI


132. Zaehle, T, Rach, S, Herrmann, CS. Transcranial alternating current stimulation enhances individual alpha activity in human EEG. PLoS One. 2010;5:e13766.
Google Scholar | Crossref | Medline | ISI


133. Bola, M, Gall, C, Sabel, BA. Disturbed temporal dynamics of brain synchronization in vision loss. Cortex. 2015;67:134146.
Google Scholar | Crossref | Medline


134. Wang, L, Guo, X, Sun, J, Jin, Z, Tong, S. Cortical networks of hemianopia stroke patients: a graph theoretical analysis of EEG signals at resting state. Conf Proc IEEE Eng Med Biol Sci. 2012;2012:4952.
Google Scholar | Medline


135. Guggisberg, AG, Koch, PJ, Hummel, FC, Buetefisch, CM. Brain networks and their relevance for stroke rehabilitation. Clin Neurophysiol. 2019;130:10981124.
Google Scholar | Crossref | Medline


136. Aldrich, MS, Alessi, AG, Beck, RW, Gilman, S. Cortical blindness: etiology, diagnosis, and prognosis. Ann Neurol. 1987;21:149158.
Google Scholar | Crossref | Medline


137. Schurger, A, Cowey, A, Tallon-Baudry, C. Induced gamma-band oscillations correlate with awareness in hemianopic patient GY. Neuropsychologia. 2006;44:17961803.
Google Scholar | Crossref | Medline


138. Richter, CG, Thompson, WH, Bosman, CA, Fries, P. Top-down beta enhances bottom-up gamma. J Neurosci. 2017;37:66986711.
Google Scholar | Crossref | Medline


139. Quentin, R, Chanes, L, Vernet, M, Valero-Cabré, A. Fronto-parietal anatomical connections influence the modulation of conscious visual perception by high-beta frontal oscillatory activity. Cereb Cortex. 2015;25:20952101.
Google Scholar | Crossref | Medline


140. Saturnino, GB, Madsen, KH, Siebner, HR, Thielscher, A. How to target inter-regional phase synchronization with dual-site transcranial alternating current stimulation. Neuroimage. 2017;163:6880.
Google Scholar | Crossref | Medline


141. Kohli, S, Casson, AJ. Towards close-loop tES: workload monitoring during tACS stimulation. Brain Stimul. 2017;10:e28e29.
Google Scholar | Crossref | Medline


142. Thut, G, Bergmann, TO, Fröhlich, F, et alGuiding transcranial brain stimulation by EEG/MEG to interact with ongoing brain activity and associated functions: a position paper. Clin Neurophysiol. 2017;128:843857.
Google Scholar | Crossref | Medline


143. Bergmann, TO, Mölle, M, Schmidt, MA, et alEEG-guided transcranial magnetic stimulation reveals rapid shifts in motor cortical excitability during the human sleep slow oscillation. J Neurosci. 2012;32:243253.
Google Scholar | Crossref | Medline


144. Karabanov, A, Thielscher, A, Siebner, HR. Transcranial brain stimulation: closing the loop between brain and stimulation. Curr Opin Neurol. 2016;29:397404.
Google Scholar | Crossref | Medline


145. Bestmann, S. Computational neurostimulation in basic and translational research. Prog Brain Res. 2015;222:xv-xx.
Google Scholar


146. Noury, N, Siegel, M. Phase properties of transcranial electrical stimulation artifacts in electrophysiological recordings. Neuroimage. 2017;158:406416.
Google Scholar | Crossref | Medline


147. Lustenberger, C, Boyle, MR, Alagapan, S, Mellin, JM, Vaughn, BV, Fröhlich, F. Feedback-controlled transcranial alternating current stimulation reveals a functional role of sleep spindles in motor memory consolidation. Curr Biol. 2016;26:21272136.
Google Scholar | Crossref | Medline


148. Jones, AP, Choe, J, Bryant, NB, et alDose-dependent effects of closed-loop tACS delivered during slow-wave oscillations on memory consolidation. Front Neurosci. 2018;12:867.
Google Scholar | Crossref | Medline

via Perspectives: Hemianopia—Toward Novel Treatment Options Based on Oscillatory Activity? – Estelle Raffin, Roberto F. Salamanca-Giron, Friedhelm Christoph Hummel,

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[Abstract] Roles of Lesioned and Nonlesioned Hemispheres in Reaching Performance Poststroke

Background. Severe poststroke arm impairment is associated with greater activation of the nonlesioned hemisphere during movement of the affected arm. The circumstances under which this activation may be adaptive or maladaptive remain unclear.

Objective. To identify the functional relevance of key lesioned and nonlesioned hemisphere motor areas to reaching performance in patients with mild versus severe arm impairment.

Methods. A total of 20 participants with chronic stroke performed a reaching response time task with their affected arm. During the reaction time period, a transient magnetic stimulus was applied over the primary (M1) or dorsal premotor cortex (PMd) of either hemisphere, and the effect of the perturbation on movement time (MT) was calculated.

Results. For perturbation of the nonlesioned hemisphere, there was a significant interaction effect of Site of perturbation (PMd vs M1) by Group (mild vs severe; P < .001). Perturbation of PMd had a greater effect on MT in the severe versus the mild group. This effect was not observed with perturbation of M1. For perturbation of the lesioned hemisphere, there was a main effect of site of perturbation (P < .05), with perturbation of M1 having a greater effect on MT than PMd.

Conclusions. These results demonstrate that, in the context of reaching movements, the role of the nonlesioned hemisphere depends on both impairment severity and the specific site that is targeted. A deeper understanding of these individual-, task-, and site-specific factors is essential for advancing the potential usefulness of neuromodulation to enhance poststroke motor recovery.

  

via Roles of Lesioned and Nonlesioned Hemispheres in Reaching Performance Poststroke – Rachael M. Harrington, Evan Chan, Amanda K. Rounds, Clinton J. Wutzke, Alexander W. Dromerick, Peter E. Turkeltaub, Michelle L. Harris-Love,

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[Abstract] An investigation into the validity and reliability of mHealth devices for counting steps in chronic stroke survivors

To investigate the validity and test–retest reliability of mHealth devices (Google Fit, Health, STEPZ, Pacer, and Fitbit Ultra) to estimate the number of steps in individuals after chronic stroke and to compare whether the measurement of the number of steps is affected by their location on the body (paretic and non-paretic side).

Observational study with repeated measures.

University laboratory.

Fifty-five community-dwelling individuals with chronic stroke.

Not applicable.

The number of steps was measured using mHealth devices (Google Fit, Health, STEPZ, Pacer, and Fitbit Ultra), and compared against criterion-standard measure during the Two-Minute Walk Test using habitual speed.

Our sample was 54.5% men, mean age of 62.5 years (SD 14.9) with a chronicity after stroke of 66.8 months (SD 55.9). There was a statistically significant association between the actual number of steps and those estimated by the Google Fit, STEPZ Iphone and Android applications, Pacer iphone and Android, and Fitbit Ultra (0.30 ⩽ r ⩾ 0.80). The Pacer iphone application demonstrated the highest reliability coefficient (ICC(2,1) = 0.80; P < 0.001). There were no statistically significant differences in device measurements that depended on body location.

mHealth devices (Pacer–iphone, Fitbit Ultra, Google Fit, and Pacer–Android) are valid and reliable for step counting in chronic stroke survivors. Body location (paretic or non-paretic side) does not affect validity or reliability of the step count metric.

via An investigation into the validity and reliability of mHealth devices for counting steps in chronic stroke survivors – Pollyana Helena Vieira Costa, Thainá Paula Dias de Jesus, Carolee Winstein, Camila Torriani-Pasin, Janaine Cunha Polese,

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[Abstract] Enriching footsteps sounds in gait rehabilitation in chronic stroke patients: a pilot study

Abstract

In the context of neurorehabilitation, sound is being increasingly applied for facilitating sensorimotor learning. In this study, we aimed to test the potential value of auditory stimulation for improving gait in chronic stroke patients by inducing alterations of the frequency spectra of walking sounds via a sound system that selectively amplifies and equalizes the signal in order to produce distorted auditory feedback. Twenty‐two patients with lower extremity paresis were exposed to real‐time alterations of their footstep sounds while walking. Changes in body perception, emotion, and gait were quantified. Our results suggest that by altering footsteps sounds, several gait parameters can be modified in terms of left–right foot asymmetry. We observed that augmenting low‐frequency bands or amplifying the natural walking sounds led to a reduction in the asymmetry index of stance and stride times, whereas it inverted the asymmetry pattern in heel–ground exerted force. By contrast, augmenting high‐frequency bands led to opposite results. These gait changes might be related to updating of internal forward models, signaling the need for adjustment of the motor system to reduce the perceived discrepancies between predicted–actual sensory feedbacks. Our findings may have the potential to enhance gait awareness in stroke patients and other clinical conditions, supporting gait rehabilitation.

 

via Enriching footsteps sounds in gait rehabilitation in chronic stroke patients: a pilot study – Gomez‐Andres – – Annals of the New York Academy of Sciences – Wiley Online Library

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