Posts Tagged Cognitive Rehabilitation

[Abstract] Computer-Based Cognitive Rehabilitation in Patients with Visuospatial Neglect or Homonymous Hemianopia after Stroke

Abstract

Objectives: The purpose of this pilot study was to investigate the feasibility and effects of computer-based cognitive rehabilitation (CBCR) in patients with symptoms of visuospatial neglect or homonymous hemianopia in the subacute phase following stroke.

Method: A randomized, controlled, unblinded cross-over design was completed with early versus late CBCR including 7 patients in the early intervention group (EI) and 7 patients in the late intervention group (LI). EI received CBCR training immediately after inclusion (m = 19 days after stroke onset) for 3 weeks and LI waited for 3 weeks after inclusion before receiving CBCR training for 3 weeks (m = 44 days after stroke onset).

Results: CBCR improved visuospatial symptoms after stroke significantly when administered early in the subacute phase after stroke. The same significant effect was not found when CBCR was administered later in the rehabilitation. The difference in the development of the EI and LI groups during the first 3 weeks was not significant, which could be due to a lack of statistical power. CBCR did not impact mental well-being negatively in any of the groups. In the LI group, the anticipation of CBCR seemed to have a positive impact of mental well-being.

Conclusion: CBCR is feasible and has a positive effect on symptoms in patients with visuospatial symptoms in the subacute phase after stroke. The study was small and confirmation in larger samples with blinded outcome assessors is needed.

via Computer-Based Cognitive Rehabilitation in Patients with Visuospatial Neglect or Homonymous Hemianopia after Stroke – ScienceDirect

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[Abstract] Evidence-Based Cognitive Rehabilitation: Systematic Review of the Literature From 2009 Through 2014 – Archives of Physical Medicine and Rehabilitation

Η εικόνα ίσως περιέχει: κείμενο

Abstract

Objectives

To conduct an updated, systematic review of the clinical literature, classify studies based on the strength of research design, and derive consensual, evidence-based clinical recommendations for cognitive rehabilitation of people with traumatic brain injury (TBI) or stroke.

Data Sources

Online PubMed and print journal searches identified citations for 250 articles published from 2009 through 2014.

Study Selection

Selected for inclusion were 186 articles after initial screening. Fifty articles were initially excluded (24 focusing on patients without neurologic diagnoses, pediatric patients, or other patients with neurologic diagnoses, 10 noncognitive interventions, 13 descriptive protocols or studies, 3 nontreatment studies). Fifteen articles were excluded after complete review (1 other neurologic diagnosis, 2 nontreatment studies, 1 qualitative study, 4 descriptive articles, 7 secondary analyses). 121 studies were fully reviewed.

Data Extraction

Articles were reviewed by the Cognitive Rehabilitation Task Force (CRTF) members according to specific criteria for study design and quality, and classified as providing class I, class II, or class III evidence. Articles were assigned to 1 of 6 possible categories (based on interventions for attention, vision and neglect, language and communication skills, memory, executive function, or comprehensive-integrated interventions).

Data Synthesis

Of 121 studies, 41 were rated as class I, 3 as class Ia, 14 as class II, and 63 as class III. Recommendations were derived by CRTF consensus from the relative strengths of the evidence, based on the decision rules applied in prior reviews.

Conclusions

CRTF has now evaluated 491 articles (109 class I or Ia, 68 class II, and 314 class III) and makes 29 recommendations for evidence-based practice of cognitive rehabilitation (9 Practice Standards, 9 Practice Guidelines, 11 Practice Options). Evidence supports Practice Standards for (1) attention deficits after TBI or stroke; (2) visual scanning for neglect after right-hemisphere stroke; (3) compensatory strategies for mild memory deficits; (4) language deficits after left-hemisphere stroke; (5) social-communication deficits after TBI; (6) metacognitive strategy training for deficits in executive functioning; and (7) comprehensive-holistic neuropsychological rehabilitation to reduce cognitive and functional disability after TBI or stroke.

via Evidence-Based Cognitive Rehabilitation: Systematic Review of the Literature From 2009 Through 2014 – Archives of Physical Medicine and Rehabilitation

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[Abstract] Virtual Reality Environment for the Cognitive Rehabilitation of Stroke Patients

Abstract

We present ongoing work to develop a virtual reality environment for the cognitive rehabilitation of patients as a part of their recovery from a stroke. A stroke causes damage to the brain and problem solving, memory and task sequencing are commonly affected. The brain can recover to some extent, however, and stroke patients have to relearn to carry out activities of daily learning. We have created an application called VIRTUE to enable such activities to be practiced using immersive virtual reality. Gamification techniques enhance the motivation of patients such as by making the level of difficulty of a task increase over time. The design and implementation of VIRTUE is presented together with the results of a small acceptability study.

via Virtual Reality Environment for the Cognitive Rehabilitation of Stroke Patients

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[Abstract] Difficulty Factors for VR Cognitive Rehabilitation Training – Crossing a Virtual Road

Highlights

Immersive VR environment for the training of safe road crossing decisions.

Relevant Lanes and Traffic Speed have a clear influence on task difficulty.

No clear influence could be found for the Gap Size.

The Number of Vehicles had almost no effect on the perceived task difficulty.

Two neuropsychologists stated that the system is ready for a study on patients.

 

Abstract

Patients with cognitive or visual impairments have problems in dealing with complex situations. During the rehabilitation process, it is important to confront the patient with (everyday) tasks that have increasing degrees of difficulty to improve their performance. Immersive virtual reality training offers the potential to create a better transfer to daily life than non-immersive computer training. In cooperation with two neuropsychologists, an immersive virtual environment (VE) was developed in which cognitive training in the form of safe road crossing decisions can be performed. We present the experimental exploration and evaluation of difficulty factors within such a VR-based cognitive rehabilitation program. Four difficulty factors were identified and compared (number of relevant traffic lanes, speed of vehicles, distance between vehicles, and number of vehicles). The combination of these difficulty factors resulted in 36 training scenarios. The impact of the factors on participant performance and subjective perception of scenario difficulty were evaluated with 60 healthy participants to estimate the impact of the four factors to a situation’s difficulty level. For the factors Relevant Lanes and Traffic Speed a clear influence on the perceived task difficulty could be determined. No clear influence could be found for the Gap Size. The Number of Vehicles had almost no effect on the perceived task difficulty. Finally, we asked two experienced neuropsychologists about the applicability of our developed system to patients, and they stated that the system is ready for a study on patients.

via Difficulty Factors for VR Cognitive Rehabilitation Training – Crossing a Virtual Road – ScienceDirect

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[Abstract] The Effect of Noninvasive Brain Stimulation on Poststroke Cognitive Function: A Systematic Review

Abstract

Introduction. Cognitive impairment after stroke has been associated with lower quality of life and independence in the long run, stressing the need for methods that target impairment for cognitive rehabilitation. The use of noninvasive brain stimulation (NIBS) on recovery of language functions is well documented, yet the effects of NIBS on other cognitive domains remain largely unknown. Therefore, we conducted a systematic review that evaluates the effects of different stimulation techniques on domain-specific (long-term) cognitive recovery after stroke. 

Methods. Three databases (PubMed, EMBASE, and PsycINFO) were searched for articles (in English) on the effects of NIBS on cognitive domains, published up to January 2018. 

Results. A total of 40 articles were included: randomized controlled trials (n = 21), studies with a crossover design (n = 9), case studies (n = 6), and studies with a mixed design (n = 4). Most studies tested effects on neglect (n = 25). The majority of the studies revealed treatment effects on at least 1 time point poststroke, in at least 1 cognitive domain. Studies varied highly on the factors time poststroke, number of treatment sessions, and stimulation protocols. Outcome measures were generally limited to a few cognitive tests. 

Conclusion. Our review suggests that NIBS is able to alleviate neglect after stroke. However, the results are still inconclusive and preliminary for the effect of NIBS on other cognitive domains. A standardized core set of outcome measures of cognition, also at the level of daily life activities and participation, and international agreement on treatment protocols, could lead to better evaluation of the efficacy of NIBS and comparisons between studies.

https://journals.sagepub.com/doi/abs/10.1177/1545968319834900

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[ARTICLE] Technology-based cognitive training and rehabilitation interventions for individuals with mild cognitive impairment: a systematic review

Abstract

Background

Individuals with mild cognitive impairment (MCI) are at heightened risk of developing dementia. Rapid advances in computing technology have enabled researchers to conduct cognitive training and rehabilitation interventions with the assistance of technology. This systematic review aims to evaluate the effects of technology-based cognitive training or rehabilitation interventions to improve cognitive function among individuals with MCI.

Methods

We conducted a systematic review using the following criteria: individuals with MCI, empirical studies, and evaluated a technology-based cognitive training or rehabilitation intervention. Twenty-six articles met the criteria.

Results

Studies were characterized by considerable variation in study design, intervention content, and technologies applied. The major types of technologies applied included computerized software, tablets, gaming consoles, and virtual reality. Use of technology to adjust the difficulties of tasks based on participants’ performance was an important feature. Technology-based cognitive training and rehabilitation interventions had significant effect on global cognitive function in 8 out of 22 studies; 8 out of 18 studies found positive effects on attention, 9 out of 16 studies on executive function, and 16 out of 19 studies on memory. Some cognitive interventions improved non-cognitive symptoms such as anxiety, depression, and ADLs.

Conclusion

Technology-based cognitive training and rehabilitation interventions show promise, but the findings were inconsistent due to the variations in study design. Future studies should consider using more consistent methodologies. Appropriate control groups should be designed to understand the additional benefits of cognitive training and rehabilitation delivered with the assistance of technology.

Background

Due to the aging of the world’s population, the number of people who live with dementia is projected to triple to 131 million by the year 2050 []. Development of preventative strategies for individuals at higher risk of developing dementia is an international priority []. Mild cognitive impairment (MCI) is regarded as an intermediate stage between normal cognition and dementia []. Individuals with MCI usually suffer with significant cognitive complaints, yet do not exhibit the functional impairments required for a diagnosis of dementia. These people typically have a faster rate of progression to dementia than those without MCI [], but the cognitive decline among MCI subjects has the potential of being improved []. Previous systematic reviews of cognitive intervention studies, both cognitive training and cognitive rehabilitation, have demonstrated promising effects on improving cognitive function among subjects with MCI [].

Recently, rapid advances in computing technology have enabled researchers to conduct cognitive training and rehabilitation interventions with the assistance of technology. A variety of technologies, including virtual reality (VR), interactive video gaming, and mobile technology, have been used to implement cognitive training and rehabilitation programs. Potential advantages to using technology-based interventions include enhanced accessibility and cost-effectiveness, providing a user experience that is immersive and comprehensive, as well as providing adaptive responses based on individual performance. Many computerized cognitive intervention programs are easily accessed through a computer or tablet, and the technology can objectively collect data during the intervention to provide real-time feedback to participants or therapists. Importantly, interventions delivered using technology have shown better effects compared to traditional cognitive training and rehabilitation programs in improving cognitive function and quality of life []. The reasons for this superiority are not well-understood but could be related to the usability and motivational factors related to the real-time interaction and feedback received from the training system [].

Three recent reviews of cognitive training and rehabilitation for use with individuals with MCI and dementia suggest that technology holds promise to improve both cognitive and non-cognitive outcomes []. The reviews conducted by Coyle, et al. [] and Chandler, et al. [] were limited by accessing articles from only two databases, and did not comprehensively cover available technologies. Hill, et al. [] limited their review to papers published until July 2016 and included only older adults aged 60 and above. More technology-based intervention studies have been conducted since then, and only including studies with older adults 60 and above could limit the scope of the review given that adults can develop early-onset MCI in their 40s []. Therefore, the purpose of this review is to 1) capture more studies using technology-based cognitive interventions by conducting a more comprehensive search using additional databases 2) understand the effect of technology-based cognitive interventions on improving abilities among individuals with MCI; and 3) examine the effects of multimodal technology-based interventions and their potential superiority compared to single component interventions.[…]

 

Continue —-> Technology-based cognitive training and rehabilitation interventions for individuals with mild cognitive impairment: a systematic review

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[Abstract] Cognitive rehabilitation in patients with traumatic brain injury: A narrative review on the emerging use of virtual reality

Highlights

About 10% of TBI patients have a severe brain damage with severe motor and cognitive dysfunctions.

New cognitive interventions, including VR training, can be useful in TBI.

VR creates a positive, motivating and enjoyable learning experience for the TBI patients.

Abstract

Traumatic brain injury (TBI) is a clinical condition characterized by brain damage due to an external, rapid and violent force. TBI causes attention, memory, affectivity, behaviour, planning, and executive dysfunctions, with a significant impact on the quality of life of the patient and of his/her family. Cognitive and motor rehabilitation programs are essential for clinical recovery of TBI patients, improving functional outcomes and the quality of life. Various researches have underlined the possible effectiveness of innovative techniques, with regard to virtual reality (VR), during the different phases of rehabilitation after TBI. This review aims to evaluate the role of VR tools in cognitive assessment and rehabilitation in individuals affected by TBI. Studies performed between 2010 and 2017 and fulfilling the selected criteria were found on PubMed, Scopus, Cochrane and Web of Sciences databases. The search combined the terms VR, assessment, rehabilitation and TBI. Our review has shown that VR has the potential to provide an effective assessment and rehabilitation tool for the treatment of cognitive and behavioral impairment on TBI patients.

via Cognitive rehabilitation in patients with traumatic brain injury: A narrative review on the emerging use of virtual reality – Journal of Clinical Neuroscience

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[ARTICLE] Combined Cognitive-Motor Rehabilitation in Virtual Reality Improves Motor Outcomes in Chronic Stroke – A Pilot Study – Full Text

Stroke is one of the most common causes of acquired disability, leaving numerous adults with cognitive and motor impairments, and affecting patients’ capability to live independently. Virtual Reality (VR) based methods for stroke rehabilitation have mainly focused on motor rehabilitation but there is increasing interest toward the integration of cognitive training for providing more effective solutions. Here we investigate the feasibility for stroke recovery of a virtual cognitive-motor task, the Reh@Task, which combines adapted arm reaching, and attention and memory training. 24 participants in the chronic stage of stroke, with cognitive and motor deficits, were allocated to one of two groups (VR, Control). Both groups were enrolled in conventional occupational therapy, which mostly involves motor training. Additionally, the VR group underwent training with the Reh@Task and the control group performed time-matched conventional occupational therapy. Motor and cognitive competences were assessed at baseline, end of treatment (1 month) and at a 1-month follow-up through the Montreal Cognitive Assessment, Single Letter Cancelation, Digit Cancelation, Bells Test, Fugl-Meyer Assessment Test, Chedoke Arm and Hand Activity Inventory, Modified Ashworth Scale, and Barthel Index. Our results show that both groups improved in motor function over time, but the Reh@Task group displayed significantly higher between-group outcomes in the arm subpart of the Fugl-Meyer Assessment Test. Improvements in cognitive function were significant and similar in both groups. Overall, these results are supportive of the viability of VR tools that combine motor and cognitive training, such as the Reh@Task. Trial Registration:This trial was not registered because it is a small clinical study that addresses the feasibility of a prototype device.

Introduction

Stroke is one of the most common causes of adult disability and its prevalence is likely to increase with an aging population (WHO, 2015). It is estimated that 33–42% of stroke survivors require assistance for daily living activities 3–6 months post-stroke and 36% continue to be disabled 5 years later (Teasell et al., 2012). Loss of motor control and muscle strength of the upper extremity are the most prevalent deficits and are those that have a greater impact on functional capacity (Saposnik, 2016). Hence, its recovery is fundamental for minimizing long-term disability and improving quality of life. In fact, most rehabilitation interventions focus on facilitating recovery through motor learning principles (Kleim and Jones, 2008). However, learning engages also cognitive processes such as attention, memory and executive functioning, all of which may be affected by stroke (Cumming et al., 2013). Still, conventional rehabilitation methodologies are mostly motor focused, although 70% of patients experience some degree of cognitive decline (Gottesman and Hillis, 2010), which also affects their capability to live independently (Langhorne et al., 2011).[…]

 

Continue —> Frontiers | Combined Cognitive-Motor Rehabilitation in Virtual Reality Improves Motor Outcomes in Chronic Stroke – A Pilot Study | Psychology

FIGURE 1. Experimental setup and VR task. (A) The user works on a tabletop and arm movements are captured by augmented reality pattern tracking. These movements are mapped onto the movements of a virtual arm on the screen for the execution of the cancelation task. (B) The target stimuli can be letters, numbers, and symbols in black or different colors. The target stimuli in this picture are ordered by increasing complexity.

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[Abstract+References] Non-invasive Cerebellar Stimulation: a Promising Approach for Stroke Recovery?

Abstract

Non-invasive brain stimulation (NIBS) combined with behavioral training is a promising strategy to augment recovery after stroke. Current research efforts have been mainly focusing on primary motor cortex (M1) stimulation. However, the translation from proof-of-principle to clinical applications is not yet satisfactory. Possible reasons are the heterogeneous properties of stroke, generalization of the stimulation protocols, and hence the lack of patient stratification. One strategy to overcome these limitations could be the evaluation of alternative stimulation targets, like the cerebellum. In this regard, first studies provided evidence that non-invasive cerebellar stimulation can modulate cerebellar processing and linked behavior in healthy subjects. The cerebellum provides unique plasticity mechanisms and has vast connections to interact with neocortical areas. Moreover, the cerebellum could serve as a non-lesioned entry to the motor or cognitive system in supratentorial stroke. In the current article, we review mechanisms of plasticity in the cortico-cerebellar system after stroke, methods for non-invasive cerebellar stimulation, and possible target symptoms in stroke, like fine motor deficits, gait disturbance, or cognitive impairments, and discuss strategies for multi-focal stimulation.

 References

  1. 1.
    Mozaffarian D, Benjamin EJ, Go AS, Arnett DK, Blaha MJ, Cushman M, et al. Heart disease and stroke statistics—2016 update: a report from the American Heart Association. Circulation. 2016;133(4):e38–360. https://doi.org/10.1161/CIR.0000000000000350.PubMedCrossRefGoogle Scholar
  2. 2.
    Blackburn DJ, Bafadhel L, Randall M, Harkness KA. Cognitive screening in the acute stroke setting. Age Ageing. 2013;42(1):113–6. https://doi.org/10.1093/ageing/afs116.PubMedCrossRefGoogle Scholar
  3. 3.
    Kotila M, Waltimo O, Niemi ML, Laaksonen R, Lempinen M. The profile of recovery from stroke and factors influencing outcome. Stroke. 1984;15(6):1039–44. https://doi.org/10.1161/01.STR.15.6.1039.PubMedCrossRefGoogle Scholar
  4. 4.
    Ramsey LE, Siegel JS, Lang CE, Strube M, Shulman GL, Corbetta M. Behavioural clusters and predictors of performance during recovery from stroke. Nat Hum Behav. 2017;1(3):38. https://doi.org/10.1038/s41562-016-0038.CrossRefGoogle Scholar
  5. 5.
    Rathore SS, Hinn AR, Cooper LS, Tyroler HA, Rosamond WD. Characterization of incident stroke signs and symptoms: findings from the atherosclerosis risk in communities study. Stroke. 2002;33(11):2718–21. https://doi.org/10.1161/01.STR.0000035286.87503.31.PubMedCrossRefGoogle Scholar
  6. 6.
    Stinear CM, Barber PA, Petoe M, Anwar S, Byblow WD. The PREP algorithm predicts potential for upper limb recovery after stroke. Brain. 2012;135(8):2527–35. https://doi.org/10.1093/brain/aws146.PubMedCrossRefGoogle Scholar
  7. 7.
    Hummel FC, Cohen LG. Drivers of brain plasticity. Curr Opin Neurol. 2005;18(6):667–74. https://doi.org/10.1097/01.wco.0000189876.37475.42.PubMedCrossRefGoogle Scholar
  8. 8.
    Hummel F, Celnik P, Giraux P, Floel A, Wu WH, Gerloff C, et al. Effects of non-invasive cortical stimulation on skilled motor function in chronic stroke. Brain. 2005;128(3):490–9. https://doi.org/10.1093/brain/awh369.PubMedCrossRefGoogle Scholar
  9. 9.
    Lefaucheur JP, Antal A, Ayache SS, Benninger DH, Brunelin J, Cogiamanian F, et al. Evidence-based guidelines on the therapeutic use of transcranial direct current stimulation (tDCS). Clin Neurophysiol. 2017;128(1):56–92. https://doi.org/10.1016/j.clinph.2016.10.087.PubMedCrossRefGoogle Scholar
  10. 10.
    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. https://doi.org/10.3389/fnhum.2015.00265.
  11. 11.
    Tedesco Triccas L, Burridge JH, Hughes AM, Pickering RM, Desikan M, Rothwell JC, et al. Multiple sessions of transcranial direct current stimulation and upper extremity rehabilitation in stroke: a review and meta-analysis. Clin Neurophysiol. 2016;127(1):946–55. https://doi.org/10.1016/j.clinph.2015.04.067.PubMedCrossRefGoogle Scholar
  12. 12.
    Rossi C, Sallustio F, Di Legge S, Stanzione P, Koch G. Transcranial direct current stimulation of the affected hemisphere does not accelerate recovery of acute stroke patients. Eur J Neurol. 2013;20(1):202–4. https://doi.org/10.1111/j.1468-1331.2012.03703.x.PubMedCrossRefGoogle Scholar
  13. 13.
    Kapoor A, Lanctôt KL, Bayley M, Kiss A, Herrmann N, Murray BJ, et al. “Good outcome” isn’t good enough: cognitive impairment, depressive symptoms, and social restrictions in physically recovered stroke patients. Stroke. 2017;48(6):1688–90. https://doi.org/10.1161/STROKEAHA.117.016728.PubMedCrossRefGoogle Scholar
  14. 14.
    das Nair R, Cogger H, Worthington E, Lincoln NB. Cognitive rehabilitation for memory deficits after stroke: an updated review. Stroke. 2017;48(2):e28–9. https://doi.org/10.1161/STROKEAHA.116.015377.PubMedCrossRefGoogle Scholar
  15. 15.
    Miniussi C, Cappa SF, Cohen LG, Floel A, Fregni F, Nitsche MA, et al. Efficacy of repetitive transcranial magnetic stimulation/transcranial direct current stimulation in cognitive neurorehabilitation. Brain Stimulat. 2008;1(4):326–36. https://doi.org/10.1016/j.brs.2008.07.002.CrossRefGoogle Scholar
  16. 16.
    Elsner B, Kugler J, Pohl M, Mehrholz J. Transcranial direct current stimulation (tDCS) for improving activities of daily living, and physical and cognitive functioning, in people after stroke. Cochrane Database Syst Rev. 2016;3:CD009645. https://doi.org/10.1002/14651858.CD009645.pub3.
  17. 17.
    Ameli M, Grefkes C, Kemper F, Riegg FP, Rehme AK, Karbe H, et al. Differential effects of high-frequency repetitive transcranial magnetic stimulation over ipsilesional primary motor cortex in cortical and subcortical middle cerebral artery stroke. Ann Neurol. 2009;66(3):298–309. https://doi.org/10.1002/ana.21725.PubMedCrossRefGoogle Scholar
  18. 18.
    Carey JR, Deng H, Gillick BT, Cassidy JM, Anderson DC, Zhang L, et al. Serial treatments of primed low-frequency rTMS in stroke: characteristics of responders vs. nonresponders. Restor Neurol Neurosci. 2014;32(2):323–35. https://doi.org/10.3233/RNN-130358.PubMedPubMedCentralGoogle Scholar
  19. 19.
    Wagner T, Fregni F, Fecteau S, Grodzinsky A, Zahn M, Pascual-Leone A. Transcranial direct current stimulation: a computer-based human model study. NeuroImage. 2007;35(3):1113–24. https://doi.org/10.1016/j.neuroimage.2007.01.027.PubMedCrossRefGoogle Scholar
  20. 20.
    Lindenberg R, Zhu LL, Ruber T, Schlaug G. Predicting functional motor potential in chronic stroke patients using diffusion tensor imaging. Hum Brain Mapp. 2012;33(5):1040–51. https://doi.org/10.1002/hbm.21266.PubMedCrossRefGoogle Scholar
  21. 21.
    Demirtas-Tatlidede A, Alonso-Alonso M, Shetty RP, Ronen I, Pascual-Leone A, Fregni F. Long-term effects of contralesional rTMS in severe stroke: safety, cortical excitability, and relationship with transcallosal motor fibers. NeuroRehabilitation. 2015;36(1):51–9. https://doi.org/10.3233/NRE-141191.PubMedGoogle Scholar
  22. 22.
    O’Shea J, Boudrias MH, Stagg CJ, Bachtiar V, Kischka U, Blicher JU, et al. Predicting behavioural response to TDCS in chronic motor stroke. NeuroImage. 2014;85(Pt 3):924–33. https://doi.org/10.1016/j.neuroimage.2013.05.096.PubMedPubMedCentralCrossRefGoogle Scholar
  23. 23.
    Bradnam LV, Stinear CM, Barber PA, Byblow WD. Contralesional hemisphere control of the proximal paretic upper limb following stroke. Cereb Cortex. 2012;22(11):2662–71. https://doi.org/10.1093/cercor/bhr344.PubMedCrossRefGoogle Scholar
  24. 24.
    Wang CC, Wang CP, Tsai PY, Hsieh CY, Chan RC, Yeh SC. Inhibitory repetitive transcranial magnetic stimulation of the contralesional premotor and primary motor cortices facilitate poststroke motor recovery. Restor Neurol Neurosci. 2014;32(6):825–35. https://doi.org/10.3233/RNN-140410.PubMedGoogle Scholar
  25. 25.
    Fregni F, Boggio PS, Mansur CG, Wagner T, Ferreira MJ, Lima MC, et al. Transcranial direct current stimulation of the unaffected hemisphere in stroke patients. Neuroreport. 2005;16(14):1551–5. https://doi.org/10.1097/01.wnr.0000177010.44602.5e.PubMedCrossRefGoogle Scholar
  26. 26.
    Kwon TG, Kim YH, Chang WH, Bang OY, Shin YI. Effective method of combining rTMS and motor training in stroke patients. Restor Neurol Neurosci. 2014;32(2):223–32. https://doi.org/10.3233/RNN-130313.PubMedGoogle Scholar
  27. 27.
    Cho JY, Lee A, Kim MS, Park E, Chang WH, Shin YI, et al. Dual-mode noninvasive brain stimulation over the bilateral primary motor cortices in stroke patients. Restor Neurol Neurosci. 2017;35(1):105–14. https://doi.org/10.3233/RNN-160669.PubMedGoogle Scholar
  28. 28.
    Boggio PS, Nunes A, Rigonatti SP, Nitsche MA, Pascual-Leone A, Fregni F. Repeated sessions of noninvasive brain DC stimulation is associated with motor function improvement in stroke patients. Restor Neurol Neurosci. 2007;25(2):123–9.PubMedGoogle Scholar
  29. 29.
    Carey MR. Synaptic mechanisms of sensorimotor learning in the cerebellum. Curr Opin Neurobiol. 2011;21(4):609–15. https://doi.org/10.1016/j.conb.2011.06.011.PubMedCrossRefGoogle Scholar
  30. 30.
    Cheron G, Dan B, Marquez-Ruiz J. Translational approach to behavioral learning: lessons from cerebellar plasticity. Neural Plast. 2013;2013:853654. https://doi.org/10.1155/2013/853654.
  31. 31.
    Bostan AC, Dum RP, Strick PL. Cerebellar networks with the cerebral cortex and basal ganglia. Trends Cogn Sci. 2013;17(5):241–54. https://doi.org/10.1016/j.tics.2013.03.003.PubMedPubMedCentralCrossRefGoogle Scholar
  32. 32.
    Manto MU. On the cerebello-cerebral interactions. The Cerebellum. 2006;5:286–8. https://doi.org/10.1080/14734220601003955.
  33. 33.
    Galea JM, Vazquez A, Pasricha N, de Xivry JJ, Celnik P. Dissociating the roles of the cerebellum and motor cortex during adaptive learning: the motor cortex retains what the cerebellum learns. Cereb Cortex. 2011;21(8):1761–70. https://doi.org/10.1093/cercor/bhq246.PubMedCrossRefGoogle Scholar
  34. 34.
    Theoret H, Haque J, Pascual-Leone A. Increased variability of paced finger tapping accuracy following repetitive magnetic stimulation of the cerebellum in humans. Neurosci Lett. 2001;306(1-2):29–32. https://doi.org/10.1016/S0304-3940(01)01860-2.PubMedCrossRefGoogle Scholar
  35. 35.
    Baron JC, Bousser MG, Comar D, Castaigne P. “Crossed cerebellar diaschisis” in human supratentorial brain infarction. Trans Am Neurol Assoc. 1981;105:459–61.PubMedGoogle Scholar
  36. 36.
    Szilagyi G, Vas A, Kerenyi L, Nagy Z, Csiba L, Gulyas B. Correlation between crossed cerebellar diaschisis and clinical neurological scales. Acta Neurol Scand. 2012;125(6):373–81. https://doi.org/10.1111/j.1600-0404.2011.01576.x.PubMedCrossRefGoogle Scholar
  37. 37.
    Gold L, Lauritzen M. Neuronal deactivation explains decreased cerebellar blood flow in response to focal cerebral ischemia or suppressed neocortical function. Proc Natl Acad Sci U A. 2002;99(11):7699–704. https://doi.org/10.1073/pnas.112012499.CrossRefGoogle Scholar
  38. 38.
    Kamouchi M, Fujishima M, Saku Y, Ibayashi S, Iida M. Crossed cerebellar hypoperfusion in hyperacute ischemic stroke. J Neurol Sci. 2004;225(1-2):65–9. https://doi.org/10.1016/j.jns.2004.07.004.PubMedCrossRefGoogle Scholar
  39. 39.
    Miura H, Nagata K, Hirata Y, Satoh Y, Watahiki Y, Hatazawa J. Evolution of crossed cerebellar diaschisis in middle cerebral artery infarction. J Neuroimaging. 1994;4(2):91–6. https://doi.org/10.1111/jon19944291.PubMedCrossRefGoogle Scholar
  40. 40.
    Takasawa M, Watanabe M, Yamamoto S, Hoshi T, Sasaki T, Hashikawa K, et al. Prognostic value of subacute crossed cerebellar diaschisis: single-photon emission CT study in patients with middle cerebral artery territory infarct. AJNR Am J Neuroradiol. 2002;23(2):189–93.PubMedGoogle Scholar
  41. 41.
    Bindman LJ, Lippold OC, Redfearn JW. Long-lasting changes in the level of the electrical activity of the cerebral cortex produced by polarizing currents. Nature. 1962;196(4854):584–5. https://doi.org/10.1038/196584a0.PubMedCrossRefGoogle Scholar
  42. 42.
    Lang N, Siebner HR, Ward NS, Lee L, Nitsche MA, Paulus W, et al. How does transcranial DC stimulation of the primary motor cortex alter regional neuronal activity in the human brain? Eur J Neurosci. 2005;22(2):495–504. https://doi.org/10.1111/j.1460-9568.2005.04233.x.PubMedPubMedCentralCrossRefGoogle Scholar
  43. 43.
    Schulz R, Frey BM, Koch P, Zimerman M, Bönstrup M, Feldheim J, et al. Cortico-cerebellar structural connectivity is related to residual motor output in chronic stroke. Cereb Cortex. 2017;27:635–45. https://doi.org/10.1093/cercor/bhv251.
  44. 44.
    Ugawa Y, Uesaka Y, Terao Y, Hanajima R, Kanazawa I. Magnetic stimulation over the cerebellum in humans. Ann Neurol. 1995;37(6):703–13. https://doi.org/10.1002/ana.410370603.PubMedCrossRefGoogle Scholar
  45. 45.
    Rothwell JC. Using transcranial magnetic stimulation methods to probe connectivity between motor areas of the brain. Hum Mov Sci. 2011;30(5):906–15. https://doi.org/10.1016/j.humov.2010.07.007.PubMedCrossRefGoogle Scholar
  46. 46.
    Kikuchi S, Mochizuki H, Moriya A, Nakatani-Enomoto S, Nakamura K, Hanajima R, et al. Ataxic hemiparesis: neurophysiological analysis by cerebellar transcranial magnetic stimulation. Cerebellum. 2012;11(1):259–63. https://doi.org/10.1007/s12311-011-0303-0.PubMedCrossRefGoogle Scholar
  47. 47.
    Ugawa Y, Terao Y, Hanajima R, Sakai K, Furubayashi T, Machii K, et al. Magnetic stimulation over the cerebellum in patients with ataxia. Electroencephalogr Clin Neurophysiol. 1997;104(5):453–8. https://doi.org/10.1016/S0168-5597(97)00051-8.PubMedCrossRefGoogle Scholar
  48. 48.
    Galea JM, Jayaram G, Ajagbe L, Celnik P. Modulation of cerebellar excitability by polarity-specific noninvasive direct current stimulation. J Neurosci. 2009;29(28):9115–22. https://doi.org/10.1523/JNEUROSCI.2184-09.2009.PubMedPubMedCentralCrossRefGoogle Scholar
  49. 49.
    Krakauer JW. Motor learning: its relevance to stroke recovery and neurorehabilitation. Curr Opin Neurol. 2006;19(1):84–90. https://doi.org/10.1097/01.wco.0000200544.29915.cc.PubMedCrossRefGoogle Scholar
  50. 50.
    Nudo RJ, Wise BM, SiFuentes F, Milliken GW. Neural substrates for the effects of rehabilitative training on motor recovery after ischemic infarct. Science. 1996;272(5269):1791–4. https://doi.org/10.1126/science.272.5269.1791.PubMedCrossRefGoogle Scholar
  51. 51.
    Askim T, Indredavik B, Vangberg T, Haberg A. Motor network changes associated with successful motor skill relearning after acute ischemic stroke: a longitudinal functional magnetic resonance imaging study. Neurorehabil Neural Repair. 2009;23(3):295–304. https://doi.org/10.1177/1545968308322840.PubMedCrossRefGoogle Scholar
  52. 52.
    Doyon J, Benali H. Reorganization and plasticity in the adult brain during learning of motor skills. Curr Opin Neurobiol. 2005;15(2):161–7. https://doi.org/10.1016/j.conb.2005.03.004.PubMedCrossRefGoogle Scholar
  53. 53.
    Hardwick RM, Rottschy C, Miall RC, Eickhoff SB. A quantitative meta-analysis and review of motor learning in the human brain. NeuroImage. 2013;67:283–97. https://doi.org/10.1016/j.neuroimage.2012.11.020.PubMedPubMedCentralCrossRefGoogle Scholar
  54. 54.
    Cantarero G, Spampinato D, Reis J, Ajagbe L, Thompson T, Kulkarni K, et al. Cerebellar direct current stimulation enhances on-line motor skill acquisition through an effect on accuracy. J Neurosci. 2015;35(7):3285–90. https://doi.org/10.1523/JNEUROSCI.2885-14.2015.PubMedPubMedCentralCrossRefGoogle Scholar
  55. 55.
    Wessel MJ, Zimerman M, Timmermann JE, Heise KF, Gerloff C, Hummel FC. Enhancing consolidation of a new temporal motor skill by cerebellar noninvasive stimulation. Cereb Cortex. 2016;26(4):1660–7. https://doi.org/10.1093/cercor/bhu335.PubMedCrossRefGoogle Scholar
  56. 56.
    Di Lazzaro V, Restuccia D, Molinari M, Leggio MG, Nardone R, Fogli D, et al. Excitability of the motor cortex to magnetic stimulation in patients with cerebellar lesions. J Neurol Neurosurg Psychiatry. 1994;57(1):108–10. https://doi.org/10.1136/jnnp.57.1.108.PubMedPubMedCentralCrossRefGoogle Scholar
  57. 57.
    Liepert J, Kucinski T, Tuscher O, Pawlas F, Baumer T, Weiller C. Motor cortex excitability after cerebellar infarction. Stroke. 2004;35(11):2484–8. https://doi.org/10.1161/01.STR.0000143152.45801.ca.PubMedCrossRefGoogle Scholar
  58. 58.
    De Vico FF, Clausi S, Leggio M, Chavez M, Valencia M, Maglione AG, et al. Interhemispheric connectivity characterizes cortical reorganization in motor-related networks after cerebellar lesions. Cerebellum. 2017;16:358–75. https://doi.org/10.1007/s12311-016-0811-z.
  59. 59.
    Koziol LF, Budding D, Andreasen N, D’Arrigo S, Bulgheroni S, Imamizu H, et al. Consensus paper: the cerebellum’s role in movement and cognition. Cerebellum Lond Engl. 2014;13(1):151–77. https://doi.org/10.1007/s12311-013-0511-x.CrossRefGoogle Scholar
  60. 60.
    Sui R, Zhang L. Cerebellar dysfunction may play an important role in vascular dementia. Med Hypotheses. 2012;78:162–5. https://doi.org/10.1016/j.mehy.2011.10.017.
  61. 61.
    Chida K, Ogasawara K, Aso K, Suga Y, Kobayashi M, Yoshida K, et al. Postcarotid endarterectomy improvement in cognition is associated with resolution of crossed cerebellar hypoperfusion and increase in 123I-iomazenil uptake in the cerebral cortex: a SPECT study. Cerebrovasc Dis Basel Switz. 2010;29(4):343–51. https://doi.org/10.1159/000278930.CrossRefGoogle Scholar
  62. 62.
    Rastogi A, Cash R, Dunlop K, Vesia M, Kucyi A, Ghahremani A, et al. Modulation of cognitive cerebello-cerebral functional connectivity by lateral cerebellar continuous theta burst stimulation. NeuroImage. 2017;158:48–57. https://doi.org/10.1016/j.neuroimage.2017.06.048.PubMedCrossRefGoogle Scholar
  63. 63.
    Desmond JE, Chen SHA, Shieh PB. Cerebellar transcranial magnetic stimulation impairs verbal working memory. Ann Neurol. 2005;58(4):553–60. https://doi.org/10.1002/ana.20604.PubMedCrossRefGoogle Scholar
  64. 64.
    Balsters JH, Ramnani N. Cerebellar plasticity and the automation of first-order rules. J Neurosci. 2011;31(6):2305–12. https://doi.org/10.1523/JNEUROSCI.4358-10.2011.PubMedCrossRefGoogle Scholar
  65. 65.
    van Dun K, Bodranghien F, Manto M, Marien P. Targeting the cerebellum by noninvasive neurostimulation: a review. Cerebellum. 2017;16(3):695–741. https://doi.org/10.1007/s12311-016-0840-7.PubMedCrossRefGoogle Scholar
  66. 66.
    Fritsch B, Reis J, Martinowich K, Schambra HM, Ji Y, Cohen LG, et al. Direct current stimulation promotes BDNF-dependent synaptic plasticity: potential implications for motor learning. Neuron. 2010;66(2):198–204. https://doi.org/10.1016/j.neuron.2010.03.035.PubMedPubMedCentralCrossRefGoogle Scholar
  67. 67.
    Antal A, Paulus W. Transcranial alternating current stimulation (tACS). Front Hum Neurosci. 2013;7:317. https://doi.org/10.3389/fnhum.2013.00317.
  68. 68.
    Valero-Cabre A, Payne BR, Pascual-Leone A. Opposite impact on 14C-2-deoxyglucose brain metabolism following patterns of high and low frequency repetitive transcranial magnetic stimulation in the posterior parietal cortex. Exp Brain Res. 2007;176(4):603–15. https://doi.org/10.1007/s00221-006-0639-8.PubMedCrossRefGoogle Scholar
  69. 69.
    Huang YZ, Chen RS, Rothwell JC, Wen HY. The after-effect of human theta burst stimulation is NMDA receptor dependent. Clin Neurophysiol. 2007;118(5):1028–32. https://doi.org/10.1016/j.clinph.2007.01.021.PubMedCrossRefGoogle Scholar
  70. 70.
    Naro A, Bramanti A, Leo A, Manuli A, Sciarrone F, Russo M, et al. Effects of cerebellar transcranial alternating current stimulation on motor cortex excitability and motor function. Brain Struct Funct. 2017;222(6):2891–906. https://doi.org/10.1007/s00429-016-1355-1.PubMedCrossRefGoogle Scholar
  71. 71.
    Morellini N, Grehl S, Tang A, Rodger J, Mariani J, Lohof AM, et al. What does low-intensity rTMS do to the cerebellum? Cerebellum. 2015;14(1):23–6. https://doi.org/10.1007/s12311-014-0617-9.PubMedCrossRefGoogle Scholar
  72. 72.
    Koch G, Mori F, Marconi B, Codeca C, Pecchioli C, Salerno S, et al. Changes in intracortical circuits of the human motor cortex following theta burst stimulation of the lateral cerebellum. Clin Neurophysiol. 2008;119(11):2559–69. https://doi.org/10.1016/j.clinph.2008.08.008.PubMedCrossRefGoogle Scholar
  73. 73.
    Doeltgen SH, Young J, Bradnam LV. Anodal direct current stimulation of the cerebellum reduces cerebellar brain inhibition but does not influence afferent input from the hand or face in healthy adults. Cerebellum. 2016;15(4):466–74. https://doi.org/10.1007/s12311-015-0713-5.PubMedCrossRefGoogle Scholar
  74. 74.
    Naro A, Leo A, Russo M, Cannavo A, Milardi D, Bramanti P, et al. Does transcranial alternating current stimulation induce cerebellum plasticity? Feasibility, safety and efficacy of a novel electrophysiological approach. Brain Stimul. 2016;9(3):388–95. https://doi.org/10.1016/j.brs.2016.02.005.PubMedCrossRefGoogle Scholar
  75. 75.
    Popa T, Russo M, Meunier S. Long-lasting inhibition of cerebellar output. Brain Stimul. 2010;3(3):161–9. https://doi.org/10.1016/j.brs.2009.10.001.PubMedCrossRefGoogle Scholar
  76. 76.
    Oliveri M, Koch G, Torriero S, Caltagirone C. Increased facilitation of the primary motor cortex following 1 Hz repetitive transcranial magnetic stimulation of the contralateral cerebellum in normal humans. Neurosci Lett. 2005;376(3):188–93. https://doi.org/10.1016/j.neulet.2004.11.053.PubMedCrossRefGoogle Scholar
  77. 77.
    Fierro B, Giglia G, Palermo A, Pecoraro C, Scalia S, Brighina F. Modulatory effects of 1 Hz rTMS over the cerebellum on motor cortex excitability. Exp Brain Res. 2007;176(3):440–7. https://doi.org/10.1007/s00221-006-0628-y.PubMedCrossRefGoogle Scholar
  78. 78.
    Langguth B, Eichhammer P, Zowe M, Landgrebe M, Binder H, Sand P, et al. Modulating cerebello-thalamocortical pathways by neuronavigated cerebellar repetitive transcranial stimulation (rTMS). Neurophysiol Clin. 2008;38(5):289–95. https://doi.org/10.1016/j.neucli.2008.08.003.PubMedCrossRefGoogle Scholar
  79. 79.
    Torriero S, Oliveri M, Koch G, Caltagirone C, Petrosini L. Interference of left and right cerebellar rTMS with procedural learning. J Cogn Neurosci. 2004;16(9):1605–11. https://doi.org/10.1162/0898929042568488.PubMedCrossRefGoogle Scholar
  80. 80.
    Hoffland BS, Bologna M, Kassavetis P, Teo JT, Rothwell JC, Yeo CH, et al. Cerebellar theta burst stimulation impairs eyeblink classical conditioning. J Physiol. 2012;590(4):887–97. https://doi.org/10.1113/jphysiol.2011.218537.PubMedCrossRefGoogle Scholar
  81. 81.
    Li Voti P, Conte A, Rocchi L, Bologna M, Khan N, Leodori G, et al. Cerebellar continuous theta-burst stimulation affects motor learning of voluntary arm movements in humans. Eur J Neurosci. 2014;39(1):124–31. https://doi.org/10.1111/ejn.12391.PubMedCrossRefGoogle Scholar
  82. 82.
    Sebastian R, Saxena S, Tsapkini K, Faria AV, Long C, Wright A, et al. Cerebellar tDCS: a novel approach to augment language treatment post-stroke. Front Hum Neurosci. 2017;10:695. https://doi.org/10.3389/fnhum.2016.00695.
  83. 83.
    Kim WS, Jung SH, Oh MK, Min YS, Lim JY, Paik NJ. Effect of repetitive transcranial magnetic stimulation over the cerebellum on patients with ataxia after posterior circulation stroke: a pilot study. J Rehabil Med. 2014;46(5):418–23. https://doi.org/10.2340/16501977-1802.PubMedCrossRefGoogle Scholar
  84. 84.
    Bonni S, Ponzo V, Caltagirone C, Koch G. Cerebellar theta burst stimulation in stroke patients with ataxia. Funct Neurol. 2014;29(1):41–5. https://doi.org/10.11138/FNeur/2014.29.1.041.
  85. 85.
    Bikson M, Inoue M, Akiyama H, Deans JK, Fox JE, Miyakawa H, et al. Effects of uniform extracellular DC electric fields on excitability in rat hippocampal slices in vitro. J Physiol. 2004;557(1):175–90. https://doi.org/10.1113/jphysiol.2003.055772.PubMedPubMedCentralCrossRefGoogle Scholar
  86. 86.
    Creutzfeldt OD, Fromm GH, Kapp H. Influence of transcortical d-c currents on cortical neuronal activity. Exp Neurol. 1962;5(6):436–52. https://doi.org/10.1016/0014-4886(62)90056-0.PubMedCrossRefGoogle Scholar
  87. 87.
    Nitsche MA, Paulus W. Excitability changes induced in the human motor cortex by weak transcranial direct current stimulation. J Physiol. 2000;527(Pt 3):633–9. https://doi.org/10.1111/j.1469-7793.2000.t01-1-00633.x.PubMedPubMedCentralCrossRefGoogle Scholar
  88. 88.
    Ferrucci R, Brunoni AR, Parazzini M, Vergari M, Rossi E, Fumagalli M, et al. Modulating human procedural learning by cerebellar transcranial direct current stimulation. Cerebellum. 2013;12(4):485–92. https://doi.org/10.1007/s12311-012-0436-9.PubMedCrossRefGoogle Scholar
  89. 89.
    Pope PA, Miall RC. Task-specific facilitation of cognition by cathodal transcranial direct current stimulation of the cerebellum. Brain Stimul. 2012;5(2):84–94. https://doi.org/10.1016/j.brs.2012.03.006.PubMedPubMedCentralCrossRefGoogle Scholar
  90. 90.
    Oldrati V, Schutter DJLG. Targeting the human cerebellum with transcranial direct current stimulation to modulate behavior: a meta-analysis. Cerebellum. 2017. https://doi.org/10.1007/s12311-017-0877-2.
  91. 91.
    Block HJ, Celnik P. Can cerebellar transcranial direct current stimulation become a valuable neurorehabilitation intervention? Expert Rev Neurother. 2012;12(11):1275–7. https://doi.org/10.1586/ern.12.121.PubMedPubMedCentralCrossRefGoogle Scholar
  92. 92.
    Celnik P. Understanding and modulating motor learning with cerebellar stimulation. Cerebellum. 2015;14(2):171–4. https://doi.org/10.1007/s12311-014-0607-y.PubMedPubMedCentralCrossRefGoogle Scholar
  93. 93.
    Ferrucci R, Cortese F, Priori A. Cerebellar tDCS: how to do it. Cerebellum. 2015;14(1):27–30. https://doi.org/10.1007/s12311-014-0599-7.PubMedCrossRefGoogle Scholar
  94. 94.
    Grimaldi G, Argyropoulos GP, Bastian A, Cortes M, Davis NJ, Edwards DJ, et al. Cerebellar transcranial direct current stimulation (ctDCS): a novel approach to understanding cerebellar function in health and disease. Neuroscientist. 2016;22(1):83–97. https://doi.org/10.1177/1073858414559409.PubMedPubMedCentralCrossRefGoogle Scholar
  95. 95.
    van Dun K, Bodranghien FC, Marien P, Manto MU. tDCS of the cerebellum: where do we stand in 2016? Technical issues and critical review of the literature. Front Hum Neurosci. 2016;10:199. https://doi.org/10.3389/fnhum.2016.00199.
  96. 96.
    Antal A, Boros K, Poreisz C, Chaieb L, Terney D, Paulus W. Comparatively weak after-effects of transcranial alternating current stimulation (tACS) on cortical excitability in humans. Brain Stimul. 2008;1(2):97–105. https://doi.org/10.1016/j.brs.2007.10.001.PubMedCrossRefGoogle Scholar
  97. 97.
    Moliadze V, Antal A, Paulus W. Boosting brain excitability by transcranial high frequency stimulation in the ripple range. J Physiol. 2010;588(24):4891–904. https://doi.org/10.1113/jphysiol.2010.196998.PubMedPubMedCentralCrossRefGoogle Scholar
  98. 98.
    Helfrich RF, Schneider TR, Rach S, Trautmann-Lengsfeld SA, Engel AK, Herrmann CS. Entrainment of brain oscillations by transcranial alternating current stimulation. Curr Biol. 2014;24(3):333–9. https://doi.org/10.1016/j.cub.2013.12.041.PubMedCrossRefGoogle Scholar
  99. 99.
    Zaehle T, Rach S, Herrmann CS. Transcranial alternating current stimulation enhances individual alpha activity in human EEG. PLoS One. 2010;5(11):e13766. https://doi.org/10.1371/journal.pone.0013766.PubMedPubMedCentralCrossRefGoogle Scholar
  100. 100.
    Polania R, Nitsche MA, Korman C, Batsikadze G, Paulus W. The importance of timing in segregated theta phase-coupling for cognitive performance. Curr Biol. 2012;22(14):1314–8. https://doi.org/10.1016/j.cub.2012.05.021.PubMedCrossRefGoogle Scholar
  101. 101.
    Antal A, Herrmann CS. Transcranial alternating current and random noise stimulation: possible mechanisms. Neural Plast. 2016;2016:3616807. http://doi.org/10.1155/2016/3616807.
  102. 102.
    Hallett M. Transcranial magnetic stimulation: a primer. Neuron. 2007;55(2):187–99. https://doi.org/10.1016/j.neuron.2007.06.026.PubMedCrossRefGoogle Scholar
  103. 103.
    Rossi S, Hallett M, Rossini PM, Pascual-Leone A. Safety of TMSCG. Safety, ethical considerations, and application guidelines for the use of transcranial magnetic stimulation in clinical practice and research. Clin Neurophysiol. 2009;120(12):2008–39. https://doi.org/10.1016/j.clinph.2009.08.016.PubMedPubMedCentralCrossRefGoogle Scholar
  104. 104.
    Huang YZ, Edwards MJ, Rounis E, Bhatia KP, Rothwell JC. Theta burst stimulation of the human motor cortex. Neuron. 2005;45(2):201–6. https://doi.org/10.1016/j.neuron.2004.12.033.PubMedCrossRefGoogle Scholar
  105. 105.
    Miall RC, Christensen LO. The effect of rTMS over the cerebellum in normal human volunteers on peg-board movement performance. Neurosci Lett. 2004;371(2-3):185–9. https://doi.org/10.1016/j.neulet.2004.08.067.PubMedCrossRefGoogle Scholar
  106. 106.
    Koch G. Repetitive transcranial magnetic stimulation: a tool for human cerebellar plasticity. Funct Neurol. 2010;25(3):159–63.PubMedGoogle Scholar
  107. 107.
    Minks E, Kopickova M, Marecek R, Streitova H, Bares M. Transcranial magnetic stimulation of the cerebellum. Biomed Pap Med Fac Univ Palacky Olomouc Czech Repub. 2010;154(2):133–9. https://doi.org/10.5507/bp.2010.020.PubMedCrossRefGoogle Scholar
  108. 108.
    Ivry RB, Keele SW, Diener HC. Dissociation of the lateral and medial cerebellum in movement timing and movement execution. Exp Brain Res. 1988;73(1):167–80. https://doi.org/10.1007/BF00279670.PubMedCrossRefGoogle Scholar
  109. 109.
    Stoodley CJ, MacMore JP, Makris N, Sherman JC, Schmahmann JD. Location of lesion determines motor vs. cognitive consequences in patients with cerebellar stroke. NeuroImage Clin. 2016;12:765–75. https://doi.org/10.1016/j.nicl.2016.10.013.PubMedPubMedCentralCrossRefGoogle Scholar
  110. 110.
    Machado AG, Cooperrider J, Furmaga HT, Baker KB, Park HJ, Chen Z, et al. Chronic 30-Hz deep cerebellar stimulation coupled with training enhances post-ischemia motor recovery and peri-infarct synaptophysin expression in rodents. Neurosurgery. 2013;73(2):344–53. https://doi.org/10.1227/01.neu.0000430766.80102.ac.
  111. 111.
    Jorgensen HS. The Copenhagen Stroke Study experience. J Stroke Cerebrovasc Dis. 1996;6(1):5–16. https://doi.org/10.1016/S1052-3057(96)80020-6.PubMedCrossRefGoogle Scholar
  112. 112.
    Beyaert C, Vasa R, Frykberg GE. Gait post-stroke: pathophysiology and rehabilitation strategies. Neurophysiol Clin. 2015;45(4-5):335–55. https://doi.org/10.1016/j.neucli.2015.09.005.PubMedCrossRefGoogle Scholar
  113. 113.
    Chieffo R, Comi G, Leocani L. Noninvasive neuromodulation in poststroke gait disorders: rationale, feasibility, and state of the art. Neurorehabil Neural Repair. 2015;30:71–82. https://doi.org/10.1177/1545968315586464.
  114. 114.
    Jayaram G, Tang B, Pallegadda R, Vasudevan EV, Celnik P, Bastian A. Modulating locomotor adaptation with cerebellar stimulation. J Neurophysiol. 2012;107(11):2950–7. https://doi.org/10.1152/jn.00645.2011.PubMedPubMedCentralCrossRefGoogle Scholar
  115. 115.
    Fernandez L, Albein-Urios N, Kirkovski M, McGinley JL, Murphy AT, Hyde C, et al. Cathodal transcranial direct current stimulation (tDCS) to the right cerebellar hemisphere affects motor adaptation during gait. Cerebellum. 2017;16(1):168–77. https://doi.org/10.1007/s12311-016-0788-7.PubMedCrossRefGoogle Scholar
  116. 116.
    Naro A, Milardi D, Cacciola A, Russo M, Sciarrone F, La Rosa G, et al. What do we know about the influence of the cerebellum on walking ability? Promising findings from transcranial alternating current stimulation. Cerebellum. 2017;16(4):859–67. https://doi.org/10.1007/s12311-017-0859-4.PubMedCrossRefGoogle Scholar
  117. 117.
    Nijsse B, Visser-Meily JM, van Mierlo ML, Post MW, de Kort PL, van Heugten CM. Temporal evolution of Poststroke cognitive impairment using the Montreal Cognitive Assessment. Stroke. 2017;48(1):98–104. https://doi.org/10.1161/STROKEAHA.116.014168.PubMedCrossRefGoogle Scholar
  118. 118.
    Dichgans M, Leys D. Vascular cognitive impairment. Circ Res. 2017;120(3):573–91. https://doi.org/10.1161/CIRCRESAHA.116.308426.PubMedCrossRefGoogle Scholar
  119. 119.
    Brainin M, Tuomilehto J, Heiss WD, Bornstein NM, Bath PM, Teuschl Y, et al. Post-stroke cognitive decline: an update and perspectives for clinical research. Eur J Neurol. 2015;22(2):229–238, e13-6https://doi.org/10.1111/ene.12626.PubMedCrossRefGoogle Scholar
  120. 120.
    Bodranghien F, Bastian A, Casali C, Hallett M, Louis ED, Manto M, et al. Consensus paper: revisiting the symptoms and signs of cerebellar syndrome. Cerebellum. 2016;15(3):369–91. https://doi.org/10.1007/s12311-015-0687-3.PubMedPubMedCentralCrossRefGoogle Scholar
  121. 121.
    Schmahmann JD, Sherman JC. The cerebellar cognitive affective syndrome. Brain. 1998;121(Pt 4):561–79. https://doi.org/10.1093/brain/121.4.561.PubMedCrossRefGoogle Scholar
  122. 122.
    Ferrucci R, Giannicola G, Rosa M, Fumagalli M, Boggio PS, Hallett M, et al. Cerebellum and processing of negative facial emotions: cerebellar transcranial DC stimulation specifically enhances the emotional recognition of facial anger and sadness. Cogn Emot. 2012;26(5):786–99. https://doi.org/10.1080/02699931.2011.619520.PubMedCrossRefGoogle Scholar
  123. 123.
    Turkeltaub PE, Swears MK, D’Mello AM, Stoodley CJ. Cerebellar tDCS as a novel treatment for aphasia? Evidence from behavioral and resting-state functional connectivity data in healthy adults. Restor Neurol Neurosci. 2016;34(4):491–505. https://doi.org/10.3233/RNN-150633.PubMedPubMedCentralGoogle Scholar
  124. 124.
    Boehringer A, Macher K, Dukart J, Villringer A, Pleger B. Cerebellar transcranial direct current stimulation modulates verbal working memory. Brain Stimul. 2013;6(4):649–53. https://doi.org/10.1016/j.brs.2012.10.001.PubMedCrossRefGoogle Scholar
  125. 125.
    Ferrucci R, Marceglia S, Vergari M, Cogiamanian F, Mrakic-Sposta S, Mameli F, et al. Cerebellar transcranial direct current stimulation impairs the practice-dependent proficiency increase in working memory. J Cogn Neurosci. 2008;20(9):1687–97. https://doi.org/10.1162/jocn.2008.20112.PubMedCrossRefGoogle Scholar
  126. 126.
    Macher K, Bohringer A, Villringer A, Pleger B. Cerebellar-parietal connections underpin phonological storage. J Neurosci. 2014;34(14):5029–37. https://doi.org/10.1523/JNEUROSCI.0106-14.2014.PubMedCrossRefGoogle Scholar
  127. 127.
    Grimaldi G, Oulad Ben Taib N, Manto M, Bodranghien F. Marked reduction of cerebellar deficits in upper limbs following transcranial cerebello-cerebral DC stimulation: tremor reduction and re-programming of the timing of antagonist commands. Front Syst Neurosci. 2014;8:9. https://doi.org/10.3389/fnsys.2014.00009.
  128. 128.
    Ramnani N. The primate cortico-cerebellar system: anatomy and function. Nat Rev Neurosci. 2006;7(7):511–22. https://doi.org/10.1038/nrn1953.PubMedCrossRefGoogle Scholar
  129. 129.
    Manto M, Marien P. Schmahmann’s syndrome—identification of the third cornerstone of clinical ataxiology. Cerebellum Ataxias. 2015;2(1):2. https://doi.org/10.1186/s40673-015-0023-1.PubMedPubMedCentralCrossRefGoogle Scholar
  130. 130.
    Stoodley CJ, Schmahmann JD. Functional topography in the human cerebellum: a meta-analysis of neuroimaging studies. NeuroImage. 2009;44(2):489–501. https://doi.org/10.1016/j.neuroimage.2008.08.039.PubMedCrossRefGoogle Scholar
  131. 131.
    Schutter DJ, van Honk J. The cerebellum on the rise in human emotion. Cerebellum. 2005;4(4):290–4. https://doi.org/10.1080/14734220500348584.PubMedCrossRefGoogle Scholar
  132. 132.
    Kelly RM, Strick PL. Cerebellar loops with motor cortex and prefrontal cortex of a nonhuman primate. J Neurosci. 2003;23(23):8432–44.PubMedGoogle Scholar
  133. 133.
    Jurgens U. The efferent and afferent connections of the supplementary motor area. Brain Res. 1984;300(1):63–81. https://doi.org/10.1016/0006-8993(84)91341-6.PubMedCrossRefGoogle Scholar
  134. 134.
    Akkal D, Dum RP, Strick PL. Supplementary motor area and presupplementary motor area: targets of basal ganglia and cerebellar output. J Neurosci. 2007;27(40):10659–73. https://doi.org/10.1523/JNEUROSCI.3134-07.2007.PubMedCrossRefGoogle Scholar
  135. 135.
    Brodal P. The corticopontine projection in the rhesus monkey. Origin and principles of organization. Brain. 1978;101(2):251–83. https://doi.org/10.1093/brain/101.2.251.PubMedCrossRefGoogle Scholar
  136. 136.
    Hashimoto M, Takahara D, Hirata Y, Inoue K, Miyachi S, Nambu A, et al. Motor and non-motor projections from the cerebellum to rostrocaudally distinct sectors of the dorsal premotor cortex in macaques. Eur J Neurosci. 2010;31(8):1402–13. https://doi.org/10.1111/j.1460-9568.2010.07151.x.PubMedCrossRefGoogle Scholar
  137. 137.
    Middleton FA, Strick PL. Dentate output channels: motor and cognitive components. Prog Brain Res. 1997;114:553–66. https://doi.org/10.1016/S0079-6123(08)63386-5.PubMedCrossRefGoogle Scholar
  138. 138.
    Clower DM, Dum RP, Strick PL. Basal ganglia and cerebellar inputs to “AIP”. Cereb Cortex. 2005;15(7):913–20. https://doi.org/10.1093/cercor/bhh190.PubMedCrossRefGoogle Scholar
  139. 139.
    Prevosto V, Graf W, Ugolini G. Cerebellar inputs to intraparietal cortex areas LIP and MIP: functional frameworks for adaptive control of eye movements, reaching, and arm/eye/head movement coordination. Cereb Cortex. 2010;20(1):214–28. https://doi.org/10.1093/cercor/bhp091.PubMedCrossRefGoogle Scholar
  140. 140.
    Anand BK, Malhotra CL, Singh B, Dua S. Cerebellar projections to limbic system. J Neurophysiol. 1959;22(4):451–7.PubMedGoogle Scholar
  141. 141.
    Snider RS, Maiti A. Cerebellar contributions to the Papez circuit. J Neurosci Res. 1976;2(2):133–46. https://doi.org/10.1002/jnr.490020204.PubMedCrossRefGoogle Scholar
  142. 142.
    Zimerman M, Nitsch M, Giraux P, Gerloff C, Cohen LG, Hummel FC. Neuroenhancement of the aging brain: restoring skill acquisition in old subjects. Ann Neurol. 2013;73(1):10–5. https://doi.org/10.1002/ana.23761.PubMedCrossRefGoogle Scholar
  143. 143.
    Samaei A, Ehsani F, Zoghi M, Hafez Yosephi M, Jaberzadeh S. Online and offline effects of cerebellar transcranial direct current stimulation on motor learning in healthy older adults: a randomized double-blind sham-controlled study. Eur J Neurosci. 2017;45(9):1177–85. https://doi.org/10.1111/ejn.13559.PubMedCrossRefGoogle Scholar
  144. 144.
    Ehsani F, Bakhtiary AH, Jaberzadeh S, Talimkhani A, Hajihasani A. Differential effects of primary motor cortex and cerebellar transcranial direct current stimulation on motor learning in healthy individuals: a randomized double-blind sham-controlled study. Neurosci Res. 2016;112:10–9. https://doi.org/10.1016/j.neures.2016.06.003.PubMedCrossRefGoogle Scholar
  145. 145.
    Fregni F, Boggio PS, Nitsche M, Bermpohl F, Antal A, Feredoes E, et al. Anodal transcranial direct current stimulation of prefrontal cortex enhances working memory. Exp Brain Res. 2005;166(1):23–30. https://doi.org/10.1007/s00221-005-2334-6.PubMedCrossRefGoogle Scholar
  146. 146.
    Miler JA, Meron D, Baldwin DS, Garner M. The effect of prefrontal transcranial direct current stimulation on attention network function in healthy volunteers. Neuromodulation. 2017. https://doi.org/10.1111/ner.12629.
  147. 147.
    Hulst T, John L, Kuper M, van der Geest JN, Goricke SL, Donchin O, et al. Cerebellar patients do not benefit from cerebellar or M1 transcranial direct current stimulation during force field reaching adaptation. J Neurophysiol. 2017;118(2):732–48. https://doi.org/10.1152/jn.00808.2016.PubMedCrossRefGoogle Scholar
  148. 148.
    Jalali R, Miall RC, Galea JM. No consistent effect of cerebellar transcranial direct current stimulation (tDCS) on visuomotor adaptation. J Neurophysiol. 2017;118(2):655–65. https://doi.org/10.1152/jn.00896.2016.PubMedCrossRefGoogle Scholar
  149. 149.
    Spielmann K, van der Vliet R, van de Sandt-Koenderman WM, Frens MA, Ribbers GM, Selles RW, et al. Cerebellar cathodal transcranial direct stimulation and performance on a verb generation task: a replication study. Neural Plast. 2017;2017:1254615. https://doi.org/10.1155/2017/1254615.
  150. 150.
    Verhage MC, Avila EO, Frens MA, Donchin O, van der Geest JN. Cerebellar tDCS does not enhance performance in an implicit categorization learning task. Front Psychol. 2017;8:476. https://doi.org/10.3389/fpsyg.2017.00476.
  151. 151.
    Cooper IS. Twenty-five years of experience with physiological neurosurgery. Neurosurgery. 1981;9(2):190–200. https://doi.org/10.1227/00006123-198108000-00017.PubMedCrossRefGoogle Scholar
  152. 152.
    Oulad Ben Taib N, Manto M. Trains of epidural DC stimulation of the cerebellum tune corticomotor excitability. Neural Plast. 2013;2013:613197. https://doi.org/10.1155/2013/613197.
  153. 153.
    Teixeira MJ, Cury RG, Galhardoni R, Barboza VR, Brunoni AR, Alho E, et al. Deep brain stimulation of the dentate nucleus improves cerebellar ataxia after cerebellar stroke. Neurology. 2015;85(23):2075–6. https://doi.org/10.1212/WNL.0000000000002204.PubMedCrossRefGoogle Scholar

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[Abstract] Improving Cognitive Function in Patients with Stroke: Can Computerized Training Be the Future?

Background

Cognitive impairment after stroke is common and can cause disability with a high impact on quality of life and independence. Cognitive rehabilitation is a therapeutic approach designed to improve cognitive functioning after central nervous system’s injuries. Computerized cognitive rehabilitation (CCR) uses multimedia and informatics resources to optimize cognitive compromised performances. The aim of this study is to evaluate the effects of pc cognitive training with Erica software in patients with stroke.

Methods

We studied 35 subjects (randomly divided into 2 groups), affected by either ischemic or hemorrhagic stroke, having attended from January 2013 to May 2015 the Laboratory of Robotic and Cognitive Rehabilitation of Istituto di Ricerca e Cura a Carattere Scientifico Neurolesi in Messina. Cognitive dysfunctions were investigated through a complete neuropsychological battery, administered before (T0) and after (T1) each different training.

Results

At T0, all the patients showed language and cognitive deficits, especially in attention process and memory abilities, with mood alterations. After the rehabilitation program (T1), we noted a global cognitive improvement in both groups, but a more significant increase in the scores of the different clinical scales we administered was found after CCR.

Conclusions

Our data suggest that cognitive pc training by using the Erica software may be a useful methodology to increase the post-stroke cognitive recovery.

 

via Improving Cognitive Function in Patients with Stroke: Can Computerized Training Be the Future?

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