Applications of functional near-infrared spectroscopy (fNIRS) to Neurorehabilitation of cognitive disabilities

Cortical effects of user training in a motor imagery based brain-computer interface measured by fNIRS and EEG

The present study aims to gain insights into the effects of training with a motor imagery (MI)-based brain-computer interface (BCI) on activation patterns of the sensorimotor cortex. We used functional near-infrared spectroscopy (fNIRS) and electroencephalography (EEG) to investigate long-term training effects across 10 sessions using a 2-class (right hand and feet) MI-based BCI in fifteen subjects. In the course of the training a significant enhancement of activation pattern emerges, represented by an [oxy-Hb] increase in fNIRS and a stronger event-related desynchronization in the upper β-frequency band in the EEG. These effects were only visible in participants with relatively low BCI performance (mean accuracy ≤ 70%). We found that training with an MI-based BCI affects cortical activation patterns especially in users with low BCI performance. Our results may serve as a valuable contribution to the field of BCI research and provide information about the effects that training with an MI-based BCI has on cortical activation patterns. This might be useful for clinical applications of BCI which aim at promoting and guiding neuroplasticity.

NIRS in clinical neurology - a 'promising' tool?

Near-infrared spectroscopy (NIRS) has become a relevant research tool in neuroscience. In special populations such as infants and for special tasks such as walking, NIRS has asserted itself as a low resolution functional imaging technique which profits from its ease of application, portability and the option to co-register other neurophysiological and behavioral data in a 'near natural' environment. For clinical use in neurology this translates into the option to provide a bed-side oximeter for the brain, broadly available at comparatively low costs. However, while some potential for routine brain monitoring during cardiac and vascular surgery and in neonatology has been established, NIRS is largely unknown to clinical neurologists. The article discusses some of the reasons for this lack of use in clinical neurology. Research using NIRS in three major neurologic diseases (cerebrovascular disease, epilepsy and headache) is reviewed. Additionally the potential to exploit the established position of NIRS as a functional imaging tool with regard to clinical questions such as preoperative functional assessment and neurorehabilitation is discussed.

The cortical control of cycling exercise in stroke patients: an fNIRS study

Stroke survivors suffering from deficits in motor control typically have limited functional abilities, which could result in poor quality of life. Cycling exercise is a common training paradigm for restoring locomotion rhythm in patients. The provision of speed feedback has been used to facilitate the learning of controlled cycling performance and the neuromuscular control of the affected leg. However, the central mechanism for motor relearning of active and passive pedaling motions in stroke patients has not been investigated as extensively. The aim of this study was to measure the cortical activation patterns during active cycling with and without speed feedback and during power-assisted (passive) cycling in stroke patients. A frequency-domain near-infrared spectroscopy (FD-NIRS) system was used to detect the hemodynamic changes resulting from neuronal activity during the pedaling exercise from the bilateral sensorimotor cortices (SMCs), supplementary motor areas (SMAs), and premotor cortices (PMCs). The variation in cycling speed and the level of symmetry of muscle activation of bilateral rectus femoris were used to evaluate cycling performance. The results showed that passive cycling had a similar cortical activation pattern to that observed during active cycling without feedback but with a smaller intensity of the SMC of the unaffected hemisphere. Enhanced PMC activation of the unaffected side with improved cycling performance was observed during active cycling with feedback, with respect to that observed without feedback. This suggests that the speed feedback enhanced the PMC activation and improved cycling performance in stroke patients.

Wavelet based motion artifact removal for Functional Near Infrared Spectroscopy

Functional Near Infrared Spectroscopy (fNIRS) enables researchers to conduct studies in situations where use of other functional imaging methods is impossible. An important shortcoming of fNIRS is the sensitivity to motion artifacts. We propose a new wavelet based algorithm for removing movement artifacts from fNIRS signals. We tested the method on simulated and experimental fNIRS data. The results show an average of 18.97 dB and 15.54 dB attenuation in motion artifacts power for our two test subjects without introducing significant distortion in the artifact-free regions of the signal.

Predictability of investment behavior from brain information measured by functional near-infrared spectroscopy: a bayesian neural network model

In line with previous studies using fMRI and as is apparent from experimental results, cerebral blood flow (oxygenated hemoglobin (oxyHb) concentration) in the medial prefrontal cortex (MPFC) and orbital cortex (OFC) as is observed with fNIRS (functional near-infrared spectroscopy) is presumed to be closely related to reward prediction and risk prediction as part of decision-making under risk. Results of analysis using a predictive model with a three-layer perceptron revealed that changes in the oxyHb concentration in cerebral blood as indicated by fNIRS observation include information to effectively predict investment behavior. This paper indicates that adding oxyHb concentration at the aforementioned sites in the brain as a predictive factor allows prediction of subjects' investment behavior with a considerable degree of precision. This fact indicates that information provided by fNIRS allows valid analysis of investment behavior and it also suggests a wide-ranging practical applicability for this information like investment assistance using fNIRS.

How to make a spaghetti sauce with a dozen small things I cannot name: a review of the impact of semantic-memory deficits on everyday actions

The purpose of this article is to present current evidence regarding the role of semantic memory in everyday actions. First we describe key models of everyday actions. We then discuss current evidence regarding the role of semantic memory in everyday actions. We reviewed articles reporting on the execution and representation of everyday actions in populations with semantic-memory deficits and single-object use in patients with semantic dementia. Although the evidence is sparse, the general conclusion of this review is that semantic memory seems necessary to support everyday actions. Finally, future challenges and research perspectives are discussed.

The impact of ablated cortex on the validity and interpretation of the fNIRS signal

Functional near infrared spectroscopy (fNIRS) is a safe and portable brain imaging modality that monitors changes in the hemodynamic activity at the cortical level. Although still in its emerging stage, fNIRS has recently gained increasing acknowledgements of its strengths and suitability for many clinical applications. The fast evolution and growth of fNIRS applications has been made possible mainly by studies that substantiate the general validity of the fNIRS measures. Such studies investigate both the fNIRS construct, by cross-validating it with fMRI, and the repeatability of fNIRS measures.Nonetheless, cases exist that would pose a challenge forfNIRS measures of cortical activation. In particular, violations of the assumptions made on the optical properties of the sampled tissue would affect some variables included in the modified Beer-Lambert law (mBBL), which allows conversion of the changes in measured light intensity into changes in the oxyhemoglobin and deoxyhemoglobin concentrations. These violations would therefore reflect on the fNIRS readings and on the way data are interpreted. The aim of this paper is to present an example of such challenging situations. The case presented is a subject whose left frontal lobe cortex has been partially ablated following a subdural hematoma. fNIRS measures were recorded during a verbal fluency task, known to be associated to functioning of the left frontal lobe. We examine the outcome of fNIRS, contextualizing it in the framework of the mBLL and its assumptions.