Posts Tagged motor imagery

[ARTICLE] Effect of tDCS stimulation of motor cortex and cerebellum on EEG classification of motor imagery and sensorimotor band power – Full Text

Abstract

Background

Transcranial direct current stimulation (tDCS) is a technique for brain modulation that has potential to be used in motor neurorehabilitation. Considering that the cerebellum and motor cortex exert influence on the motor network, their stimulation could enhance motor functions, such as motor imagery, and be utilized for brain-computer interfaces (BCIs) during motor neurorehabilitation.

Methods

A new tDCS montage that influences cerebellum and either right-hand or feet motor area is proposed and validated with a simulation of electric field. The effect of current density (0, 0.02, 0.04 or 0.06 mA/cm2) on electroencephalographic (EEG) classification into rest or right-hand/feet motor imagery was evaluated on 5 healthy volunteers for different stimulation modalities: 1) 10-minutes anodal tDCS before EEG acquisition over right-hand or 2) feet motor cortical area, and 3) 4-seconds anodal tDCS during EEG acquisition either on right-hand or feet cortical areas before each time right-hand or feet motor imagery is performed. For each subject and tDCS modality, analysis of variance and Tukey-Kramer multiple comparisons tests (p <0.001) are used to detect significant differences between classification accuracies that are obtained with different current densities. For tDCS modalities that improved accuracy, t-tests (p <0.05) are used to compare μ and βband power when a specific current density is provided against the case of supplying no stimulation.

Results

The proposed montage improved the classification of right-hand motor imagery for 4 out of 5 subjects when the highest current was applied for 10 minutes over the right-hand motor area. Although EEG band power changes could not be related directly to classification improvement, tDCS appears to affect variably different motor areas on μ and/or β band.

Conclusions

The proposed montage seems capable of enhancing right-hand motor imagery detection when the right-hand motor area is stimulated. Future research should be focused on applying higher currents over the feet motor cortex, which is deeper in the brain compared to the hand motor cortex, since it may allow observation of effects due to tDCS. Also, strategies for improving analysis of EEG respect to accuracy changes should be implemented.

Background

Transcranial direct current stimulation (tDCS) is a noninvasive technique for brain stimulation where direct current is supplied through two or more electrodes in order to modulate temporally brain excitability [12]. This technique has shown potential to improve motor performance and motor learning [345]. Hence, it could be applied in motor neurorehabilitacion [1]. However, tDCS effects vary depending on several factors, such as the size or position of the stimulation electrodes and the current intensity that is applied [6] or the mental state of the user [7]. Therefore, it should be considered that outcomes of tDCS studies are the result of different affected brain networks that may be involved in attention and movements, among other processes.

Volitional locomotion requires automatic control of movement while the cerebral cortex provides commands that are transmitted by neural projections toward the brainstem and the spinal cord. This control involves predictive motor operations that link activity from the cerebral cortex, cerebellum, basal ganglia and brainstem in order to modify actions at the spinal cord level [8]. In general, this set of structures can be considered to form a motor network that allow voluntary movement.

Different parts of the cerebral cortex participate in the performance of self-initiated movement, like the supplementary motor (SMA), the primary motor (M1) and premotor (PM) areas. It is known that M1 is activated during motor execution. Excitatory effects of M1 have been studied with anodal stimulation [6], finding that activation of this region is related to higher motor evoked potentials (MEPs) and an increment of force movement on its associated body part area [910]. Moreover, M1 seems to be critical in the early phase of consolidation of motor skills during procedural motor learning [11], i.e., the implicit skill acquisition through the repeated practice of a task [12].

In addition, the SMA and PM influence M1 in order to program opportune precise motor commands when movement pattern is modified intentionally, based on information from temporoparietal cortices regarding to the body’s state [8]. The SMA contributes in the generation of anticipatory postural adjustments [13]. Consequently, its facilitatory stimulation seems to increase anticipatory postural adjustments amplitudes, to reduce the time required to perform movements during the learning task of sequential movements, and to produce early initiation of motor responses [141516]. These studies suggest the possibility of using SMA excitation during treatments for motor disorders, since hemiparesis after stroke involves the impairment of anticipatory motor control at the affected limb [17]. In addition, some studies propose the participation of the SMA in motor memory and both implicit and explicit motor learning [18192021], i.e, when new information is acquired without intending to do so and when acquisition of skill is conscious [22], respectively. Complimentary to the role of SMA, the PM is crucial for sensory-guided movement initiation and the consolidation of motor sequence learning during sleep [823], while its facilitation with anodal tDCS seems to enhance the excitability from the ipsilateral M1 [24], which may be useful for treatment of PM disorders.

As previously mentioned, the cerebellum is also involved in locomotion through the regulation of motor processes by influencing the cerebral cortex, among other neural structures. During adaptive control of movement, as in the gait process, it seems that loops that interconnect reciprocally motor cortical areas to the basal ganglia and cerebellum allow predictive control of locomotion and they exhibit correlation with movement parameters [825]. Regarding to studies about cerebellar stimulation, there is still not enough knowledge about the effects of tDCS on different neuronal populations and the afferent pathways, so results are variable among studies and their interpretation is more complex than for cerebral tDCS [26]. Furthermore, the topographical motor organization of the cerebellum is not clear yet [27]. Nevertheless, most studies base their experimental procedure on the existence of decussating cerebello-cerebral connections, even if there are also ipsilateral cerebello-cerebral tracts or inter-hemispheric cerebellar connections [28]. Hence, a cerebellar hemisphere is stimulated to affect cerebellar brain inhibition (CBI), which refers to the inherent suppression of cerebellum over the contralateral M1 [29]. For example, the supply of anodal and cathodal stimulation over the right cerebellum in [30] resulted in incremental and decremental CBI on the left M1, respectively. In contrast, there are some studies that suggest this expectation may be not always appropriate. In [31] it was shown that inhibitory transcranial magnetic stimulation (a stimulation technique that provides magnetic field pulses on the brain [32]) over the lateral right cerebellum led to procedural learning decrement for tasks performed with either the right or left hand, whereas inhibition of lateral left cerebellar hemisphere decreased learning only with the left hand. In addition, results from [33] showed that cathodal cerebellar tDCS worsened locomotor adaptation ipsilaterally. These two studies may provide a reference for using cerebellar inhibition for avoiding undesired brain activity changes during motor rehabilitation, such as compensatory movement habits that might contribute to maladaptative plasticity and hamper the goal of achieving a normal movement pattern [34]. […]

Continue —> Effect of tDCS stimulation of motor cortex and cerebellum on EEG classification of motor imagery and sensorimotor band power | Journal of NeuroEngineering and Rehabilitation | Full Text

Fig. 1 tDCS montage. Scheme of tDCS electrodes position in reference to EEG electrodes and inion (left), and placement of tDCS electrodes on the EEG cap (right). Electrodes 1,2 and 3 are highlighted in red, green and blue, respectively

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[Abstract] Neural plasticity during motor learning with motor imagery practice: Review and perspectives

Highlights

• TMS reveals the neural aspects of motor learning with MI.

• Neural plasticity during MI practice may occur at the cortical and spinal level.

• MI training may strengthen synapse efficiency.

• Presynaptic inhibition may decrease after MI training.


Abstract

In the last decade, many studies confirmed the benefits of mental practice with motor imagery. In this review we first aimed to compile data issued from fundamental and clinical investigations and to provide the key-components for the optimization of motor imagery strategy. We focused on transcranial magnetic stimulation studies, supported by brain imaging research, that sustain the current hypothesis of a functional link between cortical reorganization and behavioral improvement. As perspectives, we suggest a model of neural adaptation following mental practice, in which synapse conductivity and inhibitory mechanisms at the spinal level may also play an important role.

Source: Neural plasticity during motor learning with motor imagery practice: Review and perspectives

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[Review] Motor Imagery-Based Rehabilitation: Potential Neural Correlates and Clinical Application for Functional Recovery of Motor Deficits after Stroke – Full Text PDF

ABSTRACT:

Motor imagery (MI), defined as the mental implementation of an action in the absence of movement or muscle activation, is a rehabilitation technique that offers a means to replace or restore lost motor function in stroke patients when used in conjunction with conventional physiotherapy procedures. This article briefly reviews the concepts and neural correlates of MI in order to promote improved understanding, as well as to enhance the clinical utility of MI-based rehabilitation regimens. We specifically highlight the role of the cerebellum and basal ganglia, premotor, supplementary motor, and prefrontal areas, primary motor cortex, and parietal cortex. Additionally, we examine the recent literature related to MI and its potential as a therapeutic technique in both upper and lower limb stroke rehabilitation.

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[ARTICLE] Motor priming in virtual reality can augment motor-imagery training efficacy in restorative brain-computer interaction: a within-subject analysis – Full Text

Abstract

Background

The use of Brain–Computer Interface (BCI) technology in neurorehabilitation provides new strategies to overcome stroke-related motor limitations. Recent studies demonstrated the brain’s capacity for functional and structural plasticity through BCI. However, it is not fully clear how we can take full advantage of the neurobiological mechanisms underlying recovery and how to maximize restoration through BCI. In this study we investigate the role of multimodal virtual reality (VR) simulations and motor priming (MP) in an upper limb motor-imagery BCI task in order to maximize the engagement of sensory-motor networks in a broad range of patients who can benefit from virtual rehabilitation training.

Methods

In order to investigate how different BCI paradigms impact brain activation, we designed 3 experimental conditions in a within-subject design, including an immersive Multimodal Virtual Reality with Motor Priming (VRMP) condition where users had to perform motor-execution before BCI training, an immersive Multimodal VR condition, and a control condition with standard 2D feedback. Further, these were also compared to overt motor-execution. Finally, a set of questionnaires were used to gather subjective data on Workload, Kinesthetic Imagery and Presence.

Results

Our findings show increased capacity to modulate and enhance brain activity patterns in all extracted EEG rhythms matching more closely those present during motor-execution and also a strong relationship between electrophysiological data and subjective experience.

Conclusions

Our data suggest that both VR and particularly MP can enhance the activation of brain patterns present during overt motor-execution. Further, we show changes in the interhemispheric EEG balance, which might play an important role in the promotion of neural activation and neuroplastic changes in stroke patients in a motor-imagery neurofeedback paradigm. In addition, electrophysiological correlates of psychophysiological responses provide us with valuable information about the motor and affective state of the user that has the potential to be used to predict MI-BCI training outcome based on user’s profile. Finally, we propose a BCI paradigm in VR, which gives the possibility of motor priming for patients with low level of motor control.

Continue —> Motor priming in virtual reality can augment motor-imagery training efficacy in restorative brain-computer interaction: a within-subject analysis | Journal of NeuroEngineering and Rehabilitation | Full Text

Fig. 2 MI-BCI training conditions. (a) VRMP: the user has to perform motor priming by mapping his/her hand movements into the virtual environment. (b) VR: the user has to perform training through simultaneous motor action observation and MI, before moving to the MI task were he/she has to control the virtual hands through MI. (c) Control: MI training with standard feedback through arrows-and-bars

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[Abstract] Review of functional near-infrared spectroscopy in neurorehabilitation – Neurophotonics – SPIE

Abstract

We provide a brief overview of the research and clinical applications of near-infrared spectroscopy (NIRS) in the neurorehabilitation field. NIRS has several potential advantages and shortcomings as a neuroimaging tool and is suitable for research application in the rehabilitation field.

As one of the main applications of NIRS, we discuss its application as a monitoring tool, including investigating the neural mechanism of functional recovery after brain damage and investigating the neural mechanisms for controlling bipedal locomotion and postural balance in humans. In addition to being a monitoring tool, advances in signal processing techniques allow us to use NIRS as a therapeutic tool in this field.

With a brief summary of recent studies investigating the clinical application of NIRS using motor imagery task, we discuss the possible clinical usage of NIRS in brain–computer interface and neurofeedback.

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Source: Review of functional near-infrared spectroscopy in neurorehabilitation | Neurophotonics | SPIE

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[Editorial] Principles underlying post-stroke recovery of upper extremity sensorimotor function – a neuroimaging perspective – frontiers

A substantial proportion of stroke survivors suffers from long-term sensorimotor deficits of the contralesional arm and hand (1). Neuroimaging, using a diversity of methods, has the potential to uncover underlying principles of functional disabilities and recovery characterizing patient groups as well as individual variability (2-6). The present issue aimed at: i. revealing the physiological mechanisms and the long term course of stroke recovery with respect to site and size of lesions, ii. correlating behavioral deficits and electrophysiological parameters with imaging patterns; iii. delineating neural networks involved; and iv. identifying sites where interventions enhance the recovery process.

Seitz and Donnan give an overview of mechanisms and disease-related limitations in post-stroke recovery (7). They address two informative subsections delineating time courses of the recovery process and state-of-the-art of neurorehabilitative training to improve the stroke-induced neurological deficit. Auriat et al. complete this clinical perspective with an overview on the use of transcranial magnetic stimulation and multimodal neuroimaging to estimate functional resources post-stroke (8). They provide a review of data from studies utilizing DTI, MRS, fMRI, EEG and brain stimulation techniques, focusing on TMS and its combination with uni- and multi-modal neuroimaging methods with respect to their benefits and limitations. Falcon et al. used “The Virtual Brain (TVB)”, an open source platform based on local biophysical models (9). Using this platform they simulated individuals’ brain activity linking structural data directly to a TVB model. Correlating TVB parameters with graph analysis metrics they obtained evidence for a shift of global to local dynamics in chronic stroke patients. Buetefisch (10) reviews the role of an intact contralesional motor cortex (M1) in post-stroke recovery of upper extremity motor function. The impact of the contralesional M1, on the lesioned motor cortex, seems to be promoting activity in the acute and inhibiting it in the chronic stage. Supportive evidence comes from animal studies including changes in neurotransmitter systems, dendritic growth and synapse formation. Thus, the contralesional M1 may represent a treatment target during rehabilitation. Sharma and Baron (11) report a fMRI study of a finger-thumb opposition sequence in chronic, well-recovered subcortical stroke patients. Using independent component analysis they could show that recovery of motor function involved pre-existing cortical networks contributing to recovery in a differentiated manner. The study of Abela et al. (12) complements these investigations of functional networks associated with recovery in the case of cortical sensorimotor stroke. The structural covariance network in patients recovering from hand paresis encompassed (i) a cortico-striato-thalamic loop involved in motor execution and (ii) higher order sensorimotor cortices affected by the stroke lesions. The network emerged in the early chronic stage post-stroke, was related to grey matter volume increases in the ipsilesional medio-dorsal thalamus, and its expression depended on an interaction of recovered hand function and the lesion size.Bannister et al. (13) report about neuroimaging evidence for the significance of the contralesional hemisphere in the recovery process after hemispheric supratentorial ischemic stroke, thus supplementing the review of Buetefisch (see above, 10). They followed the time course of touch sensation in the upper extremity using resting state – fMRI to explore functional connectivity. Improvement of touch sensation was related to changes in the contralesional hemisphere and cerebellum: 1. an increase in connectivity strength between the secondary somatosensory area seed and both inferior parietal cortex and middle temporal gyrus as well as the thalamus seed and cerebellum; and 2. a decrease in connectivity strength between SI seed and the cerebellum. Primassin et al. dealed with four exemplary cases in which motor and language domains were affected differently (14). They focused on dissociative outcomes after seven weeks of rehabilitative treatment following on the predominant failure at baseline. Primarily, precise location of the lesions in the corticospinal tract and/or fasciculus arcuatus, respectively, turned out to be critical for recovery. Motor and language improvement seemed to occur together, rather than to compete for recovery resources.

Ben-Shabat et al. investigated changes in human proprioception, its specific brain activation, laterality and changes following stroke (15). Brain activation involved the supramarginal gyrus (SMG) and dorsal premotor cortex (PMd) with a prominent lateralization in the former. Lateralization was diminished in three patients exhibiting proprioceptive deficits post-stroke and a common lesion within the thalamus. The findings underline the role of SMG and dPM in spatial processing and motor control.
Brugger et al. investigated the intriguing role of supplementary motor complex (SMC) and disturbed motor control, a retrospective clinical and lesion analysis of ten patients presenting anterior cerebral artery stroke (16). In the very acute phase alien hand syndrome (AHS) dominated accompanied by failed conscious awareness of motor intention and a missing sense of agency while performing externally triggered movements. In the follow-up motor signs specifically related to AHS, i.e. disturbed self-initiated movements, grasping and intermanual conflict, were mainly related to lesions of the pre-supplementary motor area and medial cingulate cortex.
Camilleri et al. (17) studied the neural substrate underlying the performance of the trail making test (TMT) that is often used in the follow-up of stroke. In healthy volunteers they found that performance in terms of motor speed to be related to the local brain volume of a region in the lower bank of the left inferior sulcus. Conjunction analysis of four connectivity approaches has shown this area to represent a constituent of the so-called multiple demand network, highlighting the TMT as related rather to executive than primary motor function.

In sum, the neurological deficits, recovery mechanisms and the prognosis for recovery after stroke are hot spots of clinical neurology and systems neuroscience research. Multimodal imaging, applied neurophysiology and careful neurobehavioral in-vivo correlations have opened new vistas on the pathophysiological mechanisms underlying post-stroke recovery of upper extremity sensorimotor deficits paving new avenues for future research.

Keywords: stroke recovery, multimodal neuroimaging, computational biophysical modeling, motor control, Motor Imagery, Somatosensory Disorders, perilesional plasticity, network reorganization, structural covariance, Neurorehabilitation

Source: Frontiers | Editorial: Principles underlying post-stroke recovery of upper extremity sensorimotor function – a neuroimaging perspective | Stroke

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[Article] Using a brain-machine interface to control a hybrid upper limb exoskeleton during rehabilitation of patients with neurological conditions – Full Text PDF/HTML/ePUB

Abstract

Background: As a consequence of the increase of cerebro-vascular accidents, the number of people suffering from motor disabilities is raising. Exoskeletons, Functional Electrical Stimulation (FES) devices and Brain-Machine Interfaces (BMIs) could be combined for rehabilitation purposes in order to improve therapy outcomes.

Methods: In this work, a system based on a hybrid upper limb exoskeleton is used for neurological rehabilitation. Reaching movements are supported by the passive exoskeleton ArmeoSpring and FES. The movement execution is triggered by an EEG-based BMI. The BMI uses two different methods to interact with the exoskeleton from the user’s brain activity. The first method relies on motor imagery tasks classification, whilst the second one is based on movement intention detection.

Results: Three healthy users and five patients with neurological conditions participated in the experiments to verify the usability of the system. Using the BMI based on motor imagery, healthy volunteers obtained an average accuracy of 82.9 ± 14.5 %, and patients obtained an accuracy of 65.3 ± 9.0 %, with a low False Positives rate (FP) (19.2 ± 10.4 % and 15.0 ± 8.4 %, respectively). On the other hand, by using the BMI based on detecting the arm movement intention, the average accuracy was 76.7 ± 13.2 % for healthy users and 71.6 ± 15.8 % for patients, with 28.7 ± 19.9 % and 21.2 ± 13.3 % of FP rate (healthy users and patients, respectively).

Conclusions: The accuracy of the results shows that the combined use of a hybrid upper limb exoskeleton and a BMI could be used for rehabilitation therapies. The advantage of this system is that the user is an active part of the rehabilitation procedure. The next step will be to verify what are the clinical benefits for the patients using this new rehabilitation procedure.

Full Text HTML —>  JNER | Full text | Using a brain-machine interface to control a hybrid upper limb exoskeleton during rehabilitation of patients with neurological conditions

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[ARTICLE] Motor Imagery based Brain-Computer Interfaces: An Emerging Technology to Rehabilitate Motor Deficits

Highlights

  • BCIs permit to reintegrate the sensory-motor loop by accessing to brain information.
  • Motor imagery based BCIs seem to be an effective system for an early rehabilitation.
  • This technology does not need remaining motor activity and promotes neuroplasticity.
  • BCI for rehabilitation tends towards implantable devices plus stimulation systems.

Abstract

When the sensory-motor integration system is malfunctioning provokes a wide variety of neurological disorders, which in many cases cannot be treated with conventional medication, or via existing therapeutic technology. A brain-computer interface (BCI) is a tool that permits to reintegrate the sensory-motor loop, accessing directly to brain information. A potential, promising and quite investigated application of BCI has been in the motor rehabilitation field. It is well-known that motor deficits are the major disability wherewith the worldwide population lives. Therefore, this paper aims to specify the foundation of motor rehabilitation BCIs, as well as to review the recent research conducted so far (specifically, from 2007 to date), in order to evaluate the suitability and reliability of this technology. Although BCI for post-stroke rehabilitation is still in its infancy, the tendency is towards the development of implantable devices that encompass a BCI module plus a stimulation system.

Source: Motor Imagery based Brain-Computer Interfaces: An Emerging Technology to Rehabilitate Motor Deficits

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[ARTICLE] Effect of Motor Imagery on the F-Wave Parameters in Hemiparetic Stroke Survivors – Full Text HTML

Abstract

Objective

To assess the effect of motor imagery, as a rehabilitation method in stroke, on F-wave parameters that undergo changes during upper motor neuron involvement.

Methods

Twenty-one fully conscious hemiparetic stroke survivors with a completely plegic hand (power 0/5) and a minimum interval of 72 hours since stroke were recruited into this study. The mean F-wave latency, amplitude, and persistence in the median and ulnar nerves were measured in both the affected and non-affected sides at rest and in the paretic hand during a mental task. Comparison was made between data from the affected hand and the non-affected hand as well as between data from the affected hand at baseline and during motor imagery.

Results

Patients had significantly different F-wave persistence between the affected and non-affected sides (paired t-test, p<0.001). Motor imagery could improve F-wave persistence in both the investigated nerves (paired t-test, p=0.01 for ulnar nerve and p<0.001 for median nerve) and F-response amplitude in the median nerve (paired t-test, p=0.01) of the affected limb.

Conclusion

The amplitude and persistence of F-wave were improved during motor imagery, representing F-wave facilitation. This result suggests that motor imagery can restore motor neuron excitability, which is depressed after stroke.

Continue —> KoreaMed Synapse.

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[ARTICLE] Multisensory Stimulation in Stroke Rehabilitation – Full Text

The brain has a large capacity for automatic simultaneous processing and integration of sensory information. Combining information from different sensory modalities facilitates our ability to detect, discriminate, and recognize sensory stimuli, and learning is often optimal in a multisensory environment. Currently used multisensory stimulation methods in stroke rehabilitation include motor imagery, action observation, training with a mirror or in a virtual environment, and various kinds of music therapy. Non-invasive brain stimulation has showed promising preliminary results in aphasia and neglect. Patient heterogeneity and the interaction of age, gender, genes, and environment are discussed. Randomized controlled longitudinal trials starting earlier post-stroke are needed. The advance in brain network science and neuroimaging enabling longitudinal studies of structural and functional networks are likely to have an important impact on patient selection for specific interventions in future stroke rehabilitation. It is proposed that we should pay more attention to age, gender, and laterality in clinical studies.

Introduction

We live in a multisensory environment and the interaction between our genes and the environment shapes our brains. The brain has a large capacity for automatic simultaneous processing and integration of sensory information, and multisensory influences are integral to primary as well as higher order cortical operations (Ghazanfar and Schroeder, 2006). Combining information from different sensory modalities facilitates our ability to detect, discriminate, and recognize sensory stimuli (Driver and Noesselt, 2008; Shams and Seitz, 2008; Gentile et al., 2011). Non-invasive brain stimulation does not only affect the targeted local regions but also activity in remote interconnected regions. Although repetitive transcranial magnetic stimulation (rTMS) cannot directly target subcortical structures, the activity in thalamus can be modulated by stimulation of parietal cortex, an observation that open up new possibilities for studies of cortical–subcortical interactions in multisensory processing (Blankenburg et al., 2008, 2010). Multisensory enhancement of detection sensitivity for low-contrast visual stimuli by sounds reflects a brain network involving not only established multisensory and sensory-specific cortex but also visual and auditory thalamus (Noesselt et al., 2010). Diffusion tensor imaging and tractography have enhanced the opportunity to study white matter tract networks and compare structural and functional connectivity in humans (Ciccarelli et al., 2008). Combining non-invasive brain stimulation with neuroimaging offers an opportunity to study causal relations between specific brain regions and individual cognitive and perceptual functions (Driver and Noesselt, 2008; Driver et al., 2009; Bolognini and Maravita, 2011; Zamora-López et al., 2011). Non-invasive brain stimulation techniques have the advantage that they can be used both as diagnostic tools and in treatment.

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Figure 1. Dendritic branching and spines in pyramidal neurons in parietal cortex in rats housed in standard laboratory cages (A) and rats in enriched environment with opportunity for various activities (B), Johansson and Belichenko (2002).

Continue —>  Frontiers | Multisensory Stimulation in Stroke Rehabilitation | Frontiers in Human Neuroscience.

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