Enhanced performance by a hybrid NIRS–EEG brain computer interface

Noninvasive Brain Computer Interfaces (BCI) have been promoted to be used for neuroprosthetics. However, reports on applications with electroencephalography (EEG) show a demand for a better accuracy and stability. Here we investigate whether near-infrared spectroscopy (NIRS) can be used to enhance the EEG approach. In our study both methods were applied simultaneously in a real-time Sensory Motor Rhythm (SMR)-based BCI paradigm, involving executed movements as well as motor imagery. We tested how the classification of NIRS data can complement ongoing real-time EEG classification. Our results show that simultaneous measurements of NIRS and EEG can significantly improve the classification accuracy of motor imagery in over 90% of considered subjects and increases performance by 5% on average (p < 0:01). However, the long time delay of the hemodynamic response may hinder an overall increase of bit-rates. Furthermore we find that EEG and NIRS complement each other in terms of information content and are thus a viable multimodal imaging technique, suitable for BCI

A hybrid brain-computer interface combining the EEG and NIRS

Compared to the conventional brain-computer interface (BCI) system, the hybrid BCI provides a more efficient way for the communication between the brain and the external device. The Electroencephalography (EEG) signal and the change of oxygenation in the brain are two prevailing approaches used in the BCI. However, single physiological signal couldn't provide enough information for a satisfied BCI. This paper proposes a hybrid BCI system based on the combination of the EEG signal and the cerebral blood oxygen changes measured by the near-infrared spectroscopy system (NIRS) to detect the state of motor imagery (MI). The result shows that the average recognition rate can achieve above 75.04% and the highest rate 91.11%, which are higher than when only using EEG or NIRS. It suggests that the proposed hybrid BCI system has a good performance in the combination of these two different signals. Further investigation may help develop better BCIs with high accuracy and significant efficiency. © 2012 IEEE.published_or_final_versio

Reshaping cortical activity with subthalamic stimulation in Parkinson's disease during finger tapping and gait mapped by near infrared spectroscopy

Exploration of motor cortex activity is essential to understanding the pathophysiology in Parkinson's Disease (PD), but only simple motor tasks can be investigated using a fMRI or PET. We aim to investigate the cortical activity of PD patients during a complex motor task (gait) to verify the impact of deep brain stimulation in the subthalamic nucleus (DBS-STN) by using Near-Infrared-Spectroscopy (NIRS). NIRS is a neuroimaging method of brain cortical activity using low-energy optical radiation to detect local changes in (de)oxyhemoglobin concentration. We used a multichannel portable NIRS during finger tapping (FT) and gait. To determine the signal activity, our methodology consisted of a pre-processing phase for the raw signal, followed by statistical analysis based on a general linear model. Processed recordings from 9 patients were statistically compared between the on and off states of DBS-STN. DBS-STN led to an increased activity in the contralateral motor cortex areas during FT. During gait, we observed a concentration of activity towards the cortex central area in the "stimulation-on" state. Our study shows how NIRS can be used to detect functional changes in the cortex of patients with PD with DBS-STN and indicates its future use for applications unsuited for PET and a fMRI

Effects of aging on cerebral oxygenation during working-memory performance: A functional near-infrared spectroscopy study

Contains fulltext : 102484.pdf (publisher's version ) (Open Access)Working memory is sensitive to aging-related decline. Evidence exists that aging is accompanied by a reorganization of the working-memory circuitry, but the underlying neurocognitive mechanisms are unclear. In this study, we examined aging-related changes in prefrontal activation during working-memory performance using functional Near-Infrared Spectroscopy (fNIRS), a noninvasive neuroimaging technique. Seventeen healthy young (21–32 years) and 17 healthy older adults (64–81 years) performed a verbal working-memory task (n-back). Oxygenated and deoxygenated hemoglobin concentration changes were registered by two fNIRS channels located over the left and right prefrontal cortex. Increased working-memory load resulted in worse performance compared to the control condition in older adults, but not in young participants. In both young and older adults, prefrontal activation increased with rising working-memory load. Young adults showed slight right-hemispheric dominance at low levels of working-memory load, while no hemispheric differences were apparent in older adults. Analysis of the time-activation curve during the high working-memory load condition revealed a continuous increase of the hemodynamic response in the young. In contrast to that, a quadratic pattern of activation was found in the older participants. Based on these results it could be hypothesized that young adults were better able to keep the prefrontal cortex recruited over a prolonged period of time. To conclude, already at low levels of working-memory load do older adults recruit both hemispheres, possibly in an attempt to compensate for the observed aging-related decline in performance. Also, our study shows that aging effects on the time course of the hemodynamic response must be taken into account in the interpretation of the results of neuroimaging studies that rely on blood oxygen levels, such as fMRI.11 p