Posts Tagged functional near-infrared spectroscopy
[Abstract] FUNCTIONAL NEAR-INFRARED SPECTROSCOPY-BASED UPPER EXTREMITY FUNCTION REHABILITATION FOR STROKE SURVIVOR: A REVIEW
Recently, the functional near-infrared spectroscopy (600–900-NIRS)-based rehabilitation researches have been studied for understanding the human brain. Although -NIRS can successfully measure the relative blood concentration changes of oxy-hemoglobin (HbO) and deoxy-hemoglobin (HbR) as an assessment tool to identify significant clinical intervention during pre- and post-rehabilitation therapy for stroke survivors, there is insufficient information particularly on the use of -NIRS as a clinical translation in upper extremity function rehabilitation. In order to widely utilize the -NIRS for upper extremity rehabilitation, device information, experiment design, measurement procedure, and analyzing method are described for clinician aspect in this study. In addition, further research trend was introduced from previous studies for stroke survivor rehabilitation. The authors believed that the information provided in this study can be a useful guideline to encourage future researchers to focus on upper extremity function rehabilitation of stroke survivors.nm electromagnetic wave) (
[ARTICLE] Increased gait variability during robot-assisted walking is accompanied by increased sensorimotor brain activity in healthy people – Full Text
Gait disorders are major symptoms of neurological diseases affecting the quality of life. Interventions that restore walking and allow patients to maintain safe and independent mobility are essential. Robot-assisted gait training (RAGT) proved to be a promising treatment for restoring and improving the ability to walk. Due to heterogenuous study designs and fragmentary knowlegde about the neural correlates associated with RAGT and the relation to motor recovery, guidelines for an individually optimized therapy can hardly be derived. To optimize robotic rehabilitation, it is crucial to understand how robotic assistance affect locomotor control and its underlying brain activity. Thus, this study aimed to investigate the effects of robotic assistance (RA) during treadmill walking (TW) on cortical activity and the relationship between RA-related changes of cortical activity and biomechanical gait characteristics.
Twelve healthy, right-handed volunteers (9 females; M = 25 ± 4 years) performed unassisted walking (UAW) and robot-assisted walking (RAW) trials on a treadmill, at 2.8 km/h, in a randomized, within-subject design. Ground reaction forces (GRFs) provided information regarding the individual gait patterns, while brain activity was examined by measuring cerebral hemodynamic changes in brain regions associated with the cortical locomotor network, including the sensorimotor cortex (SMC), premotor cortex (PMC) and supplementary motor area (SMA), using functional near-infrared spectroscopy (fNIRS).
A statistically significant increase in brain activity was observed in the SMC compared with the PMC and SMA (p < 0.05), and a classical double bump in the vertical GRF was observed during both UAW and RAW throughout the stance phase. However, intraindividual gait variability increased significantly with RA and was correlated with increased brain activity in the SMC (p = 0.05; r = 0.57).
On the one hand, robotic guidance could generate sensory feedback that promotes active participation, leading to increased gait variability and somatosensory brain activity. On the other hand, changes in brain activity and biomechanical gait characteristics may also be due to the sensory feedback of the robot, which disrupts the cortical network of automated walking in healthy individuals. More comprehensive neurophysiological studies both in laboratory and in clinical settings are necessary to investigate the entire brain network associated with RAW.
Safe and independent locomotion represents a fundamental motor function for humans that is essential for self-contained living and good quality of life [1,2,3,4,5]. Locomotion requires the ability to coordinate a number of different muscles acting on different joints [6,7,8], which are guided by cortical and subcortical brain structures within the locomotor network . Structural and functional changes within the locomotor network are often accompanied by gait and balance impairments which are frequently considered to be the most significant concerns in individuals suffering from brain injuries or neurological diseases [5, 10, 11]. Reduced walking speeds and step lengths  as well as non-optimal amount of gait variability [13,14,15] are common symptoms associated with gait impairments that increase the risk of falling .
In addition to manual-assisted therapy, robotic neurorehabilitation has often been applied in recent years [17, 18] because it provides early, intensive, task-specific and multi-sensory training which is thought to be effective for balance and gait recovery [17, 19, 20]. Depending on the severity of the disease, movements can be completely guided or assisted, tailored to individual needs , using either stationary robotic systems or wearable powered exoskeletons.
Previous studies investigated the effectiveness of robot-assisted gait training (RAGT) in patients suffering from stroke [21, 22], multiple sclerosis [23,24,25,26], Parkinson’s disease [27, 28], traumatic brain injury  or spinal cord injury [30,31,32]. Positive effects of RAGT on walking speed [33, 34], leg muscle force  step length, and gait symmetry [29, 35] were reported. However, the results of different studies are difficult to summarize due to the lack of consistency in protocols and settings of robotic-assisted treatments (e.g., amount and frequency of training sessions, amount and type of provided robotic support) as well as fragmentary knowledge of the effects on functional brain reorganization, motor recovery and their relation [36, 37]. Therefore, it is currently a huge challenge to draw guidelines for robotic rehabilitation protocols [22, 36,37,38]. To design prologned personalized training protocols in robotic rehabilitation to maximize individual treatment effects , it is crucial to increase the understanding of changes in locomotor patterns  and brain signals  underlying RAGT and how they are related [36, 41].
A series of studies investigated the effects of robotic assistance (RA) on biomechanical gait patterns in healthy people [39, 42,43,44]. On one side, altered gait patterns were reported during robot-assisted walking (RAW) compared to unassisted walking (UAW), in particular, substantially higher muscle activity in the quadriceps, gluteus and adductor longus leg muscles and lower muscle activity in the gastrocnemius and tibialis anterior ankle muscles [39, 42] as well as reduced lower-body joint angles due to the little medial-lateral hip movements [45,46,47]. On the other side, similar muscle activation patterns were observed during RAW compared to UAW [44, 48, 49], indicating that robotic devices allow physiological muscle activation patterns during gait . However, it is hypothesized that the ability to execute a physiological gait pattern depends on how the training parameters such as body weight support (BWS), guidance force (GF) or kinematic restrictions in the robotic devices are set [44, 48, 50]. For example, Aurich-Schuler et al.  reported that the movements of the trunk and pelvis are more similar to UAW on a treadmill when the pelvis is not fixed during RAW, indicating that differences in musle activity and kinematic gait characteristics between RAW and UAW are due to the reduction in degrees of freedom that user’s experience while walking in the robotic device . In line with this, a clinical concern that is often raised with respect to RAW is the lack of gait variability [45, 48, 50]. It is assumed that since the robotic systems are often operated with 100% GF, which means that the devices attempt to force a particular gait pattern regardless of the user’s intentions, the user lacks the ability to vary and adapt his gait patterns . Contrary to this, Hidler et al.  observed differences in kinematic gait patterns between subsequent steps during RAW, as demonstrated by variability in relative knee and hip movements. Nevertheless, Gizzi et al.  showed that the muscular activity during RAW was clearly more stereotyped and similar among individuals compared to UAW. They concluded that RAW provides a therapeutic approach to restore and improve walking that is more repeatable and standardized than approaches based on exercising during UAW .
In addition to biomechanical gait changes, insights into brain activity and intervention-related changes in brain activity that relate to gait responses, will contribute to the optimization of therapy interventions [41, 51]. Whereas the application of functional magnetic resonance imaging (fMRI), considered as gold standard for the assessment of activity in cortical and subcortical structures, is restricted due to the vulnerability for movement artifacts and the range of motion in the scanner , functional near infrared spectroscopy (fNIRS) is affordable and easily implementable in a portable system, less susceptible to motion artifacts, thus facilitation a wider range of application with special cohorts (e.g., children, patients) and in everyday environments (e.g., during a therapeutic session of RAW or UAW) [53, 54]. Although with lower resolution compared to fMRI , fNIRS also relies on the principle of neurovascular coupling and allows the indirect evaluation of cortical activation [56, 57] based on hemodynamic changes which are analogous to the blood-oxygenation-level-dependent responses measured by fMRI . Despite limited depth sensitivity, which restricts the measurement of brain activity to cortical layers, it is a promising tool to investigate the contribution of cortical areas to the neuromotor control of gross motor skills, such as walking . Regarding the cortical correlates of walking, numerous studies identified either increaesed oxygenated hemoglobin (Hboxy) concentration changes in the sensorimotor cortex (SMC) by using fNIRS [53, 57,58,59] or suppressed alpha and beta power in sensorimotor areas by using electroencephalography (EEG) [60,61,62] demonstrating that motor cortex and corticospinal tract contribute directly to the muscle activity of locomotion . However, brain activity during RAW [36, 61, 64,65,66,67,68], especially in patients [69, 70] or by using fNIRS [68, 69], is rarely studied .
Analyzing the effects of RA on brain activity in healthy volunteers, Knaepen et al.  reported significantly suppressed alpha and beta rhythms in the right sensory cortex during UAW compared to RAW with 100% GF and 0% BWS. Thus, significantly larger involvement of the SMC during UAW compared to RAW were concluded . In contrast, increases of Hboxy were observed in motor areas during RAW compared UAW, leading to the conclusion that RA facilitated increased cortical activation within locomotor control systems . Furthermore, Simis et al.  demonstrated the feasibility of fNIRS to evaluate the real-time activation of the primary motor cortex (M1) in both hemispheres during RAW in patients suffering from spinal cord injury. Two out of three patients exhibited enhanced M1 activation during RAW compared with standing which indicate the enhanced involvement of motor cortical areas in walking with RA .
To summarize, previous studies mostly focused the effects of RA on either gait characteristics or brain activity. Combined measurements investigating the effects of RA on both biomechanical and hemodynamic patterns might help for a better understanding of the neurophysiological mechanisms underlying gait and gait disorders as well as the effectiveness of robotic rehabilitation on motor recovery [37, 71]. Up to now, no consensus exists regarding how robotic devices should be designed, controlled or adjusted (i.e., device settings, such as the level of support) for synergistic interactions with the human body to achieve optimal neurorehabilitation [37, 72]. Therefore, further research concerning behavioral and neurophysiological mechanisms underlying RAW as well as the modulatory effect of RAGT on neuroplasticy and gait recovery are required giving the fact that such knowledge is of clinical relevance for the development of gait rehabilitation strategies.
Consequently, the central purpose of this study was to investigate both gait characteristics and hemodynamic activity during RAW to identify RAW-related changes in brain activity and their relationship to gait responses. Assuming that sensorimotor areas play a pivotal role within the cortical network of automatic gait [9, 53] and that RA affects gait and brain patterns in young, healthy volunteers [39, 42, 45, 68], we hypothesized that RA result in both altered gait and brain activity patterns. Based on previous studies, more stereotypical gait characteristics with less inter- and intraindividual variability are expected during RAW due to 100% GF and the fixed pelvis compared to UAW [45, 48], wheares brain activity in SMC can be either decreased  or increased .
This study was performed in accordance with the Declaration of Helsinki. Experimental procedures were performed in accordance with the recommendations of the Deutsche Gesellschaft für Psychologie and were approved by the ethical committee of the Medical Association Hessen in Frankfurt (Germany). The participants were informed about all relevant study-related contents and gave their written consent prior to the initiation of the experiment.
Twelve healthy subjects (9 female, 3 male; aged 25 ± 4 years), without any gait pathologies and free of extremity injuries, were recruited to participate in this study. All participants were right-handed, according to the Edinburg handedness-scale , without any neurological or psychological disorders and with normal or corrected-to-normal vision. All participants were requested to disclose pre-existing neurological and psychological conditions, medical conditions, drug intake, and alcohol or caffeine intake during the preceding week.
The Lokomat (Hocoma AG, Volketswil, Switzerland) is a robotic gait-orthosis, consisting of a motorized treadmill and a BWS system. Two robotic actuators can guide the knee and hip joints of participants to match pre-programmed gait patterns, which were derived from average joint trajectories of healthy walkers, using a GF ranging from 0 to 100% [74, 75] (Fig. 1a). Kinematic trajectories can be adjusted to each individual’s size and step preferences . The BWS was adjusted to 30% body weight for each participant, and the control mode was set to provide 100% guidance .
Continue —-> Increased gait variability during robot-assisted walking is accompanied by increased sensorimotor brain activity in healthy people | Journal of NeuroEngineering and Rehabilitation | Full Text
[ARTICLE] Increased Sensorimotor Cortex Activation With Decreased Motor Performance During Functional Upper Extremity Tasks Poststroke – Full Text
Background and Purpose: 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. This study determined the differences in sensorimotor cortex activation during unrestrained reaching and gripping after stroke.
Methods: Eleven individuals with chronic stroke and 11 neurologically healthy individuals completed reaching and gripping tasks under 3 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 analysis of covariance (covariate: age). Pairwise comparisons were used for post hoc analyses. Partial Pearson 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 with 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 and Conclusions: 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. 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.
Video Abstract available for more insights from the authors (see Video Abstract, Supplemental Digital Content 1, available at: http://links.lww.com/JNPT/A269).
Stroke is the leading cause of long-term disability in Canada, with approximately 405 000 Canadians currently living with its long-lasting effects.1 While the site of injury and the specific presentation of symptoms are heterogeneous, up to 70% of these individuals experience upper extremity hemiparesis,2 and even after rehabilitation, greater than 65% of this population have difficulty utilizing their affected limb in activities of daily living.3 Decreased use of the paretic arm can lead to chronic pain and weakness, decreased bone density,4 cerebral cortex changes,5and an overall decrease in quality of life.6 In addition, stroke rehabilitation and continual care are costly for the health care system.7 Therefore, it is important to maximize patient recovery in an effective and efficient manner.
One area that has been highly debated for rehabilitation efficacy is the side of arm training. Numerous reviews have stated conflicting and inconclusive results pertaining to benefits of the paretic (affected) arm or bilateral arm training8–10 and a few studies have recently investigated the effects of the nonparetic (less-affected) arm training.11,12 Investigating how stroke itself affects neural activation during unilateral and bilateral upper extremity activities may help explain the mechanisms underlying such training.
In individuals living with the chronic effects of stroke, nonnormal brain activation is commonly seen with irregular activation in both the ipsi- and contralesional hemispheres during movement. A meta-analysis of 20 studies13 calculated increases in contralesional primary motor cortex, and bilateral premotor and supplementary motor areas with use of the paretic hand compared with healthy individuals. Systematically reviewing 22 functional magnetic resonance imaging (fMRI) and positron emission tomography studies, Buma et al14 reported general initial increases in contra-, ipsi-, and perilesional activation during paretic upper extremity movement in individuals with cortical and subcortical strokes when compared with healthy adults. In addition, as paretic arm performance increased with training, these authors also showed that in many, but not all participants, activation decreased in areas such as the contralesional motor cortex (ie, ipsilateral to the movement arm), which is not typically activated in healthy individuals. Previous reviews have also reported increases in cortical activation of motor supporting areas (bilateral premotor and supplementary motor areas) later in recovery that are associated with greater function,15 although the opposite has also been reported.16
The majority of previously mentioned evidence utilized neuroimaging techniques that require an individual to remain fairly still, especially at the head, and recorded in the supine position. While there are many advantages to these techniques, such as high spatial resolution and penetration depth using fMRI, the functional imaging data acquired from these studies may not be truly indicative of the neural correlates involved during rehabilitation tasks. Thus, assessment of brain activation during upright, unrestrained, functional tasks is needed. Functional near-infrared spectroscopy (fNIRS) is an emerging neuroimaging device that has the capabilities of determining cortical activation while the participant is mobile. Similar to fMRI, fNIRS is an indirect measure of cortical activation that utilizes the neurovascular coupling theory to estimate changes in brain activity.17 Near-infrared light emitted by this device is absorbed by areas high in oxyhemoglobin or deoxyhemoglobin content and is measured through detectors placed on the individual’s head. When an increase in brain activity occurs, a typical overall increase in oxyhemoglobin concentration and a slight decrease in deoxyhemoglobin are observed.17 Due to its portability, fNIRS has been used to investigate cortical activation during various mobile tasks after stroke.18,19 To our knowledge, no work has been done to compare sensorimotor cortex activation of paretic, nonparetic, and bilateral arm movements poststroke using fNIRS.
Therefore, the primary purpose of this study was to investigate differences in cortical brain activation during performance of upper extremity activities in an upright position after stroke and in neurologically healthy individuals. Based on the current evidence, we hypothesized that greater sensorimotor cortex activation would be observed in the stroke group compared with the neurologically healthy group, particularly when using the weaker arm. For our secondary measures, we hypothesize that (1) individuals in the stroke group will perform worse than the control group when using their weaker arm and (2) cortical activation in the contralateral hemisphere (eg, ipsilesional hemisphere during paretic arm movements) will positively correlate with task performance.[…]
[ARTICLE] Transcranial direct current stimulation for the treatment of motor impairment following traumatic brain injury – Full Text
After traumatic brain injury (TBI), motor impairment is less common than neurocognitive or behavioral problems. However, about 30% of TBI survivors have reported motor deficits limiting the activities of daily living or participation. After acute primary and secondary injuries, there are subsequent changes including increased GABA-mediated inhibition during the subacute stage and neuroplastic alterations that are adaptive or maladaptive during the chronic stage. Therefore, timely and appropriate neuromodulation by transcranial direct current stimulation (tDCS) may be beneficial to patients with TBI for neuroprotection or restoration of maladaptive changes.
Technologically, combination of imaging-based modelling or simultaneous brain signal monitoring with tDCS could result in greater individualized optimal targeting allowing a more favorable neuroplasticity after TBI. Moreover, a combination of task-oriented training using virtual reality with tDCS can be considered as a potent tele-rehabilitation tool in the home setting, increasing the dose of rehabilitation and neuromodulation, resulting in better motor recovery.
This review summarizes the pathophysiology and possible neuroplastic changes in TBI, as well as provides the general concepts and current evidence with respect to the applicability of tDCS in motor recovery. Through its endeavors, it aims to provide insights on further successful development and clinical application of tDCS in motor rehabilitation after TBI.
Traumatic brain injury (TBI) is defined as “an alteration in brain function (loss of consciousness, post-traumatic amnesia, and neurologic deficits) or other evidence of brain pathology (visual, neuroradiologic, or laboratory confirmation of damage to the brain) caused by external force” . The incidence and prevalence of TBI are substantial and increasing in both developing and developed countries. TBI in older age groups due to falling has been on the rise in recent years, becoming the prevalent condition in all age groups [2, 3]. TBI causes broad spectrum of impairments, including cognitive, psychological, sensory or motor impairments [4, 5], which may increase the socioeconomic burdens and reduce the quality of life [6, 7]. Although motor impairment, such as limb weakness, gait disturbance, balance problem, dystonia or spasticity, is less common than neurocognitive or behavioral problems after TBI, about 30% of TBI survivors have reported motor deficits that severely limited activities of daily living or participation .
Motor impairment after TBI is caused by both focal and diffuse damages, making it difficult to determine the precise anatomo-clinical correlations [9, 10]. According to previous clinical studies, recovery after TBI also seems worse than that after stroke, although the neuroplasticity after TBI may also play an important role for recovery . Therefore, a single unimodal approach for motor recovery, including conventional rehabilitation, may be limiting, and hence, requiring a novel therapeutic modality to improve the outcome after TBI.
Transcranial direct current stimulation (tDCS) – one of the noninvasive brain stimulation (NIBS) methods – can increase or decrease the cortical excitability according to polarity (anodal vs. cathodal) and be used to modulate the synaptic plasticity to promote long-term functional recovery via long-term depression or potentiation [12, 13]. Recent clinical trials evaluating patients with stroke have reported the potential benefits of tDCS for motor recovery . Neuroplastic changes after TBI and results from animal studies also suggest that tDCS could improve the motor deficit in TBI, although clinical trials using tDCS for motor recovery in TBI are currently lacking .
In this review, we will cover (1) the pathophysiology and possible neuroplastic changes in TBI; (2) physiology of tDCS; (3) current clinical evidence of tDCS in TBI for motor recovery; (4) general current concept of tDCS application for motor recovery; and (5) the future developments and perspectives of tDCS for motor recovery after TBI. Although the scope of motor recovery is wide, this review will focus primarily on the recovery of limb function, especially that of the upper limb. We expect that this review can provide insights on further successful development and clinical application of tDCS in motor rehabilitation after TBI.[…]
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.
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.
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.
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.
Neurological disability due specifically to stroke or spinal cord injury can profoundly affect the social life of paralyzed patients [1, 2, 3]. The resultant gait impairment is a large contributor to ambulatory dysfunction . 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 [1, 2, 5, 6, 7]. However, these devices have limitations particular to given research and clinical settings. Therefore, wearable upper- and lower-limb robotic devices have been developed [7, 8], which are used to assist users by actuating joints to partial or complete movement using brain intentions, according to individual-patient needs.
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,1–3 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.18–21 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
74 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).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 sensitivity
Photo by Evan Krape July 15, 2016
Functional near-infrared spectroscopy adds new research capability
New brain imaging equipment is now available to scientists at the University of Delaware’s Science, Technology and Advanced Research (STAR) Campus.
The technology is called functional near-infrared spectroscopy, or just fNIRS for short. It gathers brain activity, including cortical activation, during real-world tasks.
Most importantly for research participants, it is non-invasive, allowing them to be more at ease during studies.
The system was recently installed at UD’s STAR Health Sciences Complex.
The fNIRS system comes to the University via a National Institutes of Health shared instrumentation grant.
Anjana Bhat, associate professor in the Department of Physical Therapy, is the principal investigator on the grant and played a key role in acquiring the equipment.
The collaboration already includes 11 faculty members from three departments — Physical Therapy, Kinesiology and Applied Physiology, and Psychological and Brain Sciences. But, the equipment can help researchers in lots of areas, both inside and outside of the University.
In addition to Bhat, the UD advisory committee includes Tom Buchanan, George W. Laird Professor of Mechanical Engineering and director of the Delaware Rehabilitation Institute, and Stuart Binder-Macleod, Edward L. Ratledge Professor of Physical Therapy.
The group is offering open time for researchers around the University to explore possibilities for studies.
“We’d love anyone conducting research in, for example, neuroscience or behavioral research to come use the fNIRS system,” said Bhat.
Bhat has studied motor and social development in children along the autism spectrum. She saw the fNIRS system as a tool to dive deeper into brain mechanisms.
The fNIRS system provides distinct advantages over the traditional magnetic resonance imaging (MRI) to study cortical mechanisms of various human behaviors.
“Kids have a tough time laying still in an MRI scanner,” said Bhat. “MRI machines/rooms emit high sounds and lots of lights. It is an unusual environment and since children with autism can have aversion to lights and sounds, they may struggle following through on instructions during an MRI scan.”
In contrast, the fNIRS system only requires the participant to wear a cap. It allows a participant to engage in meaningful, everyday social interactions, computer-based interactions or various movements. They can play, reach or walk on a treadmill.
So how does it work? Well, the cap has several probes that emit near-infrared light. This light passes through the skull and brain. Depending on how much blood supply is in the brain tissue, the light is then absorbed. Each emitter has a corresponding detector, which picks up the reflected light.
“The difference in light emitted versus absorbed tells us how much blood supply reaches the underlying brain tissue. This gives us an indirect measure of how active the brain tissue is during a particular function or behavior,” Bhat said.
Samuel Lee, associate professor of physical therapy, uses neuromuscular electrical stimulation to enhance function in individuals with cerebral palsy. His lab might use stimulation to assist muscles in activities like walking or cycling.
Lee said, “fNIRS will allow us an objective and quantitative measure to substantiate the theories behind our investigations.”
Scheduling is managed through an fNIRS group calendar. To sign up for time with the fNIRS system, interested parties can contact Anjana Bhat. Training opportunities and operational assistance are also available through Delaware Rehabilitation Institute’s Kevin McGinnis.
Source: fNIRS brain imaging | UDaily
[ARTICLE] Lower limb movement preparation in chronic stroke: A pilot study toward an fNIRS-BCI for gait rehabilitation.
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.