Posts Tagged fNIRS

[JUST ACCEPTED] “Increased Sensorimotor Cortex Activation with Decreased Motor Performance during Functional Upper Extremity Tasks Post-Stroke” – Abstract

The following article has just been accepted for publication in Journal of Neurologic Physical Therapy.

“Increased Sensorimotor Cortex Activation with Decreased Motor Performance during Functional Upper Extremity Tasks Post-Stroke”

By Shannon B Lim, MSc, MPT; Janice J Eng

Provisional Abstract:

Background: Current literature has focused on identifying neuroplastic changes associated with stroke through tasks and in positions that are not representative of functional rehabilitation. Emerging technologies such as functional near-infrared spectroscopy (fNIRS) provide new methods of expanding the area of neuroplasticity within rehabilitation.
Purpose: This study determined the differences in sensorimotor cortex activation during unrestrained reaching and gripping after stroke.
Methods: 11 healthy and 11 chronic post-stroke individuals completed reaching and gripping tasks under three conditions using their 1) stronger, 2) weaker, and 3) both arms together. Performance and sensorimotor cortex activation using fNIRS were collected. Group and arm differences were calculated using mixed ANCOVA (covariate: age). Pairwise comparisons were used for post-hoc analyses. Partial Pearson’s correlations between performance and activation were assessed for each task, group, and hemisphere.
Results: Larger sensorimotor activations in the ipsilesional hemisphere were found for the stroke compared to healthy group for reaching and gripping conditions despite poorer performance. Significant correlations were observed between gripping performance (with the weaker arm and both arms simultaneously) and sensorimotor activation for the stroke group only.
Discussion: Stroke leads to significantly larger sensorimotor activation during functional reaching and gripping despite poorer performance. This may indicate an increased sense of effort, decreased efficiency, or increased difficulty after stroke.
Conclusion: fNIRS can be used for assessing differences in brain activation during movements in functional positions after stroke. This can be a promising tool for investigating possible neuroplastic changes associated with functional rehabilitation interventions in the stroke population.

Supplemental Digital Content 1. Video abstract .mp4

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[ARTICLE] fNIRS-based Neurorobotic Interface for gait rehabilitation – Full Text

Abstract

Background

In this paper, a novel functional near-infrared spectroscopy (fNIRS)-based brain-computer interface (BCI) framework for control of prosthetic legs and rehabilitation of patients suffering from locomotive disorders is presented.

Methods

fNIRS signals are used to initiate and stop the gait cycle, while a nonlinear proportional derivative computed torque controller (PD-CTC) with gravity compensation is used to control the torques of hip and knee joints for minimization of position error. In the present study, the brain signals of walking intention and rest tasks were acquired from the left hemisphere’s primary motor cortex for nine subjects. Thereafter, for removal of motion artifacts and physiological noises, the performances of six different filters (i.e. Kalman, Wiener, Gaussian, hemodynamic response filter (hrf), Band-pass, finite impulse response) were evaluated. Then, six different features were extracted from oxygenated hemoglobin signals, and their different combinations were used for classification. Also, the classification performances of five different classifiers (i.e. k-Nearest Neighbour, quadratic discriminant analysis, linear discriminant analysis (LDA), Naïve Bayes, support vector machine (SVM)) were tested.

Results

The classification accuracies obtained from SVM using the hrf were significantly higher (p < 0.01) than those of the other classifier/ filter combinations. Those accuracies were 77.5, 72.5, 68.3, 74.2, 73.3, 80.8, 65, 76.7, and 86.7% for the nine subjects, respectively.

Conclusion

The control commands generated using the classifiers initiated and stopped the gait cycle of the prosthetic leg, the knee and hip torques of which were controlled using the PD-CTC to minimize the position error. The proposed scheme can be effectively used for neurofeedback training and rehabilitation of lower-limb amputees and paralyzed patients.

Background

Neurological disability due specifically to stroke or spinal cord injury can profoundly affect the social life of paralyzed patients [123]. The resultant gait impairment is a large contributor to ambulatory dysfunction [4]. In order to regain complete functional independence, physical rehabilitation remains the mainstay option, owing to the significant expense of health care and the redundancy of therapy sessions. Such devices are developed as alternatives to traditional, expensive and time-consuming exercises in busy daily life. In the past, similar training sessions on treadmills performed using robotic mechanisms have shown better functional outcomes [12567]. However, these devices have limitations particular to given research and clinical settings. Therefore, wearable upper- and lower-limb robotic devices have been developed [78], which are used to assist users by actuating joints to partial or complete movement using brain intentions, according to individual-patient needs.

To date, various noninvasive modalities including functional magnetic resonance imaging (fMRI), electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) have been used to acquire brain signals. fNIRS is a relatively new modality that detects brain intention with reference to changes in hemodynamic response. Its fewer artifacts, better spatial resolution and acceptable temporal resolution make it the choice for comprehensive and promising results in, for example, rehabilitation and mental task applications [91011121314151617181920]. The main brain-computer interface (BCI) challenge in this regard is to extract useful information from raw brain signals for control-command generation [212223]. Acquired signals are processed in the following four stages: preprocessing, feature extraction, classification, and command generation. In preprocessing, physiological and instrumental artifacts and noises are removed [2425]. After this filtration stage, feature extraction proceeds in order to gather useful information. Then, the extracted features are classified using different classifiers. Finally, the trained classifier is used to generate control commands based on a trained model [23]. Figure 1 shows a schematic of a BCI.

Fig. 1 Schematic of BCI

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via fNIRS-based Neurorobotic Interface for gait rehabilitation | Journal of NeuroEngineering and Rehabilitation | Full Text

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[ARTICLE] Near-Infrared Spectroscopy in Gait Disorders – Is it Time to Begin? – Full Text

Walking is a complex motor behavior with a special relevance in clinical neurology. Many neurological diseases, such as Parkinson’s disease and stroke, are characterized by gait disorders whose neurofunctional correlates are poorly investigated. Indeed, the analysis of real walking with the standard neuroimaging techniques poses strong challenges, and only a few studies on motor imagery or walking observation have been performed so far. Functional near-infrared spectroscopy (fNIRS) is becoming an important research tool to assess functional activity in neurological populations or for special tasks, such as walking, because it allows investigating brain hemodynamic activity in an ecological setting, without strong immobility constraints. A systematic review following PRISMA guidelines was conducted on the fNIRS-based examination of gait disorders. Twelve of the initial yield of 489 articles have been included in this review. The lesson learnt from these studies suggest that oxy-hemoglobin levels within the prefrontal and premotor cortices are more sensitive to compensation strategies reflecting postural control and restoration of gait disorders. Although this field of study is in its relative infancy, the evidence provided encourages the translation of fNIRS in clinical practice, as it offers a unique opportunity to explore in depth the activity of the cortical motor system during real walking in neurological patients. We also discuss to what extent fNIRS may be applied for assessing the effectiveness of rehabilitation programs.

Walking is one of the most fundamental motor functions in humans,13 often impaired in some focal neurological conditions (ie, stroke), or neurodegenerative diseases, such as Parkinson’s disease (PD).4 Worldwide almost two thirds of people over 70 years old suffer from gait disorders, and because of the progressively ageing population, an increasing pressure on health care systems is expected in the coming years.5

Although the physiological basis of walking is well understood, pathophysiological mechanisms in neurological patients have been poorly described. This is caused by the difficulty to assess in vivo neuronal processes during overt movements.

During the past 20 years, functional magnetic resonance imaging (fMRI) has been the preferred instrument to investigate mechanisms underlying movement control6 as well as movement disorders.7 fMRI allows measuring the blood oxygenation level-dependent (BOLD) signal that, relying on variations in deoxy-hemoglobin (deoxyHb) concentrations, provides an indirect measure of functional activity of the human brain.8 Patterns of activation/deactivation and connectivity across brain regions can be detected with a very high spatial resolution for both cortical and subcortical structures. This technique, however, is characterized by severe limitations and constraints about motion artifacts and only small movements are allowed inside the scanner. This entails dramatic compromises on the experimental design and on the inclusion/exclusion criteria. Multiple solutions have been attempted to overcome such limitations. For instance, many neuroimaging studies have been performed on the motor imagery,9,10 but imaging can be different from subject to subject,11 and imagined walking and actual walking engage different brain networks.12 Other authors have suggested the application of virtual reality,13 and there have been a few attempts to allow an almost real-walking sequence while scanning with fMRI.14,15Additional opportunities to investigate the mechanisms sustaining walking control include the use of surrogate tasks in the scanner as proxy of walking tasks,16 or to “freeze” brain activations during walking using positron emission tomography (PET) radiotracers, which allow the retrospective identification of activation patterns, albeit with some uncertainties and low spatial and temporal resolution.12

Therefore, until now there has not been an ecological way to noninvasively assess neurophysiological correlates of walking processes in gait disorders.

Functional near-infrared spectroscopy (fNIRS) is becoming an important research tool to assess functional activity in special populations (neurological and psychiatric patients)17 or for special tasks.1821 fNIRS is a noninvasive optical imaging technique that, similarly to fMRI, measures the hemodynamic response to infer the underlying neural activity. Optical imaging is based on near-infrared (650-1000 nm) light propagation into scattering tissues and its absorption by 2 major chromophores in the brain, oxy-hemoglobin (oxyHb) and deoxyHb, which show specific absorption spectra depending on the wavelength of the photons.22 Typically, an fNIRS apparatus is composed of a light source that is coupled to the participant’s head via either light-emitting diodes (LEDs) or through fiber-optical bundles with a detector that receives the light after it has been scattered through the tissue. A variation of the optical density of the photons measured by detectors depends on the absorption of the biological tissues (Figure 1A). Using more than one wavelength and applying the modified Beer-Lambert law, it is possible to infer on the changes of oxyHb and deoxyHb concentrations.23 fNIRS has a number of definite advantages compared to fMRI, its major competitor: (a) it does not pose immobility constrains,25 (b) is portable,26 (c) allows recording during real walking,27 (d) allows long-lasting recordings, (e) it does not produce any noise, (f) it makes possible the investigation of brain activity during sleep,28 (f) it allows to obtain a richer picture of the neurovascular coupling as it measures changes in both oxyHb and deoxyHb concentration with high temporal resolution (up to milliseconds). High temporal resolution is usually not mandatory for the investigation of the hemodynamic response whose dynamic takes at least 3 to 5 seconds, but it can be useful for the study of transient hemodynamic activity like the initial dip29 or to detect subtle temporal variations in the latency of the hemodynamic response across different experimental conditions.19,21,30 The major drawback of fNIRS in comparison to fMRI is its lower spatial resolution (few centimeters under the skull) and its lack of sensitivity to subcortical regions.18,19 However, this might be considered a minor limitation, as there is a large body of evidence suggesting that (a) cortical mechanisms take place in walking,31 (b) the organization of the motor system is distributed along large brain regions,32and (c) the function of subcortical structures is mirrored in the cerebral cortex.33

figure

Figure 1. Illustration of penetration depth of near-infrared light into the tissue in a probe configuration used to investigate motor performances during walking task (upper row). The picture shows brain reconstruction from a high-resolution anatomical MRI. The spheres placed over the skull correspond to vitamin E capsules employed during the MRI to mark the positions of the optodes and to allow the coregistration of the individual anatomy together with the optode position. In this illustration, only the photons propagation from one source (S) to one detector (D) have been simulated. The yellow-red scale indicates the degree of sensitivity74 for the considered source-detector pair to the head/brain structures. (A, B, and C) Lower row: Examples of fNIRS experimental device used for assessing brain activity during real walking tasks. These fNIRS approaches included either commercial device, such as (A) wireless portable fNIRS system (NIRx; Germany) or support systems for treadmill walking activity with body weight support24 (B) or with free movement range (C).

Continue —> Near-Infrared Spectroscopy in Gait Disorders – Feb 14, 2017

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[ARTICLE] Transcranial Direct Current Stimulation Modulates Neuronal Activity and Learning in Pilot Training – Full Text HTML

Skill acquisition requires distributed learning both within (online) and across (offline) days to consolidate experiences into newly learned abilities. In particular, piloting an aircraft requires skills developed from extensive training and practice. Here, we tested the hypothesis that transcranial direct current stimulation (tDCS) can modulate neuronal function to improve skill learning and performance during flight simulator training of aircraft landing procedures.

Thirty-two right-handed participants consented to participate in four consecutive daily sessions of flight simulation training and received sham or anodal high-definition-tDCS to the right dorsolateral prefrontal cortex (DLPFC) or left motor cortex (M1) in a randomized, double-blind experiment. Continuous electroencephalography (EEG) and functional near infrared spectroscopy (fNIRS) were collected during flight simulation, n-back working memory, and resting-state assessments. tDCS of the right DLPFC increased midline-frontal theta-band activity in flight and n-back working memory training, confirming tDCS-related modulation of brain processes involved in executive function. This modulation corresponded to a significantly different online and offline learning rates for working memory accuracy and decreased inter-subject behavioral variability in flight and n-back tasks in the DLPFC stimulation group. Additionally, tDCS of left M1 increased parietal alpha power during flight tasks and tDCS to the right DLPFC increased midline frontal theta-band power during n-back and flight tasks.

These results demonstrate a modulation of group variance in skill acquisition through an increasing in learned skill consistency in cognitive and real-world tasks with tDCS. Further, tDCS performance improvements corresponded to changes in electrophysiological and blood-oxygenation activity of the DLPFC and motor cortices, providing a stronger link between modulated neuronal function and behavior.

Continue —> Frontiers | Transcranial Direct Current Stimulation Modulates Neuronal Activity and Learning in Pilot Training | Frontiers in Human Neuroscience

Figure 1. Experimental design. (A) Experiment timeline depicting the relative timing of each task (see Table 1 for descriptions of each task). The N-Back and Easy Landing tasks are highlighted, and the duration of tDCS is depicted in red. (B) An example of 6 trials of the N-Back task is shown. 1-back orientation and location match trials are highlighted in yellow. (C) The flight simulator, neuroimaging (EEG and FNIRS) and tDCS setup is shown with on a subject (1). Flight simulator equipment includes three-panel display, a radio panel (2), an instrument panel (3) with (from left to right) compass, altimeter, airspeed indicator, vertical speed indicator, and turn/slip indicator, a multi-panel (4) with (from left to right) autopilot settings, auto throttle switch, flaps switch, and elevator trim wheel, yoke (5), and throttle quadrant system (6). (D) Autopilot flight path for the Easy Landing task is shown in 3 dimensions, color-coded by vertical speed. Screenshots for initial descent, approach, and landing are also shown.

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[ARTICLE] Potential determinants of efficacy of mirror therapy in stroke patients. A pilot study – OPEN ACCESS

Abstract

Background: Mirror therapy (MT) was found to improve motor function after stroke. However, there is high variability between patients regarding motor recovery.

Objectives: The following pilot study was designed to identify potential factors determining this variability between patients with severe upper limb paresis, receiving MT.

Methods: Eleven sub-acute stroke patients with severe upper limb paresis participated, receiving in-patient rehabilitation. After a set of pre-assessments (including measurement of brain activity at the primary motor cortex and precuneus during the mirror illusion, using near-infrared spectroscopy as described previously), four weeks of MT were applied, followed by a set of post-assessments. Discriminant group analysis for MT responders and non-responders was performed.

Results: Six out of eleven patients were defined as responders and five as non-responders on the basis of their functional motor improvement. The initial motor function and the activity shift in both precunei (mirror index) were found to discriminate significantly between responders and non-responders.

Conclusions: In line with earlier results, initial motor function was confirmed as crucial determinant of motor recovery. Additionally, activity response to the mirror illusion in both precunei was found to be a candidate for determination of the efficacy of MT.

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[DISSERTATION] Cerebral activation during visual stimulation of mirrored hand movements in normal subjects and stroke patients – Full Text PDF

Introduction

Stroke is the second leading cause for death worldwide (after ischemic heart disease) as per WHO and one of the leading causes for disability at advanced age (Feigin et al., 2014). Stroke is not limited to industrial countries how recent analysis demonstrated, but is a global problem, indeed stroke mortality and stroke burden measured by the disability-adjusted life years (DALY) is highest in low-income countries (Johnston, Mendis, & Mathers, 2009). If the observed trend from 1990 to 2010 in incidence, mortality, and DALYs continues, by 2030 there will be almost “12 million stroke deaths, 70 million stroke survivors, and more than 200 million DALYs” burden worldwide (Feigin et al., 2014). About one third of all stroke patients suffer from severe hemiparesis (disability to move one body side) of the upper limb (Jorgensen et al., 1995). In one study about first-ever unilateral stroke patients in the area of the middle cerebral artery (MCA) with following severe hemiparesis, even after intensive rehabilitation procedure 62% remained without any function and only about 38% regained some dexterity of the affected arm (complete recovery: 11.6%) (Kwakkel, Kollen, van der Grond, & Prevo, 2003). With regard to the individual suffering as well as to the raising costs that are caused by these low recovery rates, it is socially relevant to promote research in the field of neurological rehabilitation of severe hemiparesis and to search for alternatives to the conventional rehabilitation procedures. The thesis at hand aims for a better understanding of the underlying neurophysiological mechanisms of one alternative therapy, the so-called mirror therapy (MT). Although a lot of research on MT has been done in the past years, many questions about the underlying cerebral mechanism and about potential determinants of the efficacy of MT remain open.

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[ARTICLE] Lower limb movement preparation in chronic stroke: A pilot study toward an fNIRS-BCI for gait rehabilitation.

Abstract

Background. Thus far, most of the brain–computer interfaces (BCIs) developed for motor rehabilitation used electroencephalographic signals to drive prostheses that support upper limb movement. Only few BCIs used hemodynamic signals or were designed to control lower extremity prostheses. Recent technological developments indicate that functional near-infrared spectroscopy (fNIRS)-BCI can be exploited in rehabilitation of lower limb movement due to its great usability and reduced sensitivity to head motion artifacts.

Objective. The aim of this proof of concept study was to assess whether hemodynamic signals underlying lower limb motor preparation in stroke patients can be reliably measured and classified.

Methods. fNIRS data were acquired during preparation of left and right hip movement in 7 chronic stroke patients.

Results. Single-trial analysis indicated that specific hemodynamic changes associated with left and right hip movement preparation can be measured with fNIRS. Linear discriminant analysis classification of totHB signal changes in the premotor cortex and/or posterior parietal cortex indicated above chance accuracy in discriminating paretic from nonparetic movement preparation trials in most of the tested patients.

Conclusion. The results provide first evidence that fNIRS can detect brain activity associated with single-trial lower limb motor preparation in stroke patients. These findings encourage further investigation of fNIRS suitability for BCI applications in rehabilitation of patients with lower limb motor impairment after stroke.

via Articles, Books, & Reports – Exploring the NARIC Collection | National Rehabilitation Information Center.

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