Functional near-infrared (fNIR) sensing is a relatively young brain imaging technique, yet one that holds great promise for brain-computer interfaces. Measuring essentially the same signals as functional magnetic resonance imaging (fMRI), fNIR acts as a single-point monitor of oxy- and deoxy-hemoglobin concentrations for localized sensing with greatly lowered costs and hardware requirements. As an optical sensing technique, fNIR is more robust to ambient electrical noise that affects the electroencephalogram (EEG) signal. The reduced hardware requirements and robustness in noisy environments make fNIR well-suited for brain-computer interface systems as it poses few physical restrictions on the operator and can be implemented in a wide range of applications and scenarios.

Near-infrared (NIR) sensing in flight applications can provide critical objective indicators of crew state. By monitoring oxy-hemoglobin concentrations, a NIR sensor can detect changes in flight crew physiology in response to both cognitive demands and extreme conditions related to flight applications, including gravity-induced loss of consciousness (G-LOC) and hypoxia. A custom NIR sensor was created for in-helmet monitoring of oxy-hemoglobin in flight. This wearable, wireless sensor addresses requirements for flight applications and was applied to a case study that examines the raw optical signal and oxy-hemoglobin response to Valsalva maneuvers performed at 1g.

The objective of this study was to identify a parsimonious set of physiological measures that could be used to best predict cognitive fatigue levels. A 37 hour sleep deprivation study was conducted to induce reduced levels of alertness and cognitive impairment as measured by a psychomotor vigilance test. Non-invasive, wearable and ambulatory sensors were used to acquire cardio-respiratory and motion data during the sleep deprivation. Subsequently 23 potential predictors were derived from the raw sensor data. The least absolute shrinkage and selection operator, along with a cross validation strategy was used to create a sparse model and identify a minimum predictor subset that provided the best prediction accuracy. Final predictor selection was found to vary with task and context. Depending on context selected predictors indicated elevated levels of sympathetic nervous system activity, increased restlessness during engaging tasks and increased cardio-respiratory synchronization with increasing cognitive fatigue.

Controlling computers and other electronic devices using only one's thoughts is an exciting yet unlikely and distant reality for most people. However, for people with locked-in syndrome, their disabilities are so severe that they have no other alternatives. Applications that are consciously controlled using signals from the brain (called brain-computer interfaces, or BCIs) have been shown to restore some communication and environmental control for these individuals. Unfortunately, BCIs can be slow and tedious to learn or operate, reducing their effectiveness. This demonstration presents engaging BCI applications, including a video game and a digital painting program, that enable users to have fun while they improve their control over the brain signals required to use BCIs.

This paper explores the validation of tactile mechanisms as an effective means of communications for integration into a physiologic system interface (PSI). Tactile communications can offer a channel that only minimally interferes with a primary or concurrent task. The PSI will use functional brain imaging techniques, specifically functional near-infrared imaging (fNIR), to determine cognitive workload in language and visual processing areas of the brain. The resulting closed-loop system will thus have the capability of providing the operator with necessary information by using the modality most available to the user, thus enabling effective multi-tasking and minimal task interference.

Functional near-infrared sensing (fNIR) enables real-time, noninvasive monitoring of cognitive activity by measuring the brain’s hemodynamic and metabolic responses. We have demonstrated the ability for non-vocal and non-physical communications through detecting directed changes in cognitive tasks. Building upon past research, this paper reports methods that allow the calibration of the fNIR oxygenation signal to better be used in more complex communicative and selection tasks. This work is then discussed in the context of a faster, continuous fNIR brain-computer interface framework.

Functional near-infrared (fNIR) technology exploits the known properties of the interaction between human tissue and near-infrared (NIR) light to monitor relative oxyand deoxy-hemoglobin concentrations. Infrared light, with wavelengths ranging from ∼2500 nm to 25 µm, is absorbed by the human body due to the high water content of tissue and the high absorption rate of infrared light by water. Visible light, with wavelengths ranging from 400 nm to ∼750 nm, is scattered by the human body and does not pass through it. Between visible and infrared light, NIR light is composed of light with wavelengths between 750 nm and 2,500 nm. This NIR light is relatively weakly absorbed and scattered by the human body [1]. The weak absorption and scattering property of NIR light allows the detection of this light after penetration through several centimeters of tissue, making these wave

This is the first MRI study to report differences in brain structure size between low and highly hypnotizable, healthy, right-handed young adults. Participants were stringently screened for hypnotic susceptibility with two standardized scales, and then exposed to hypnotic analgesia training to control cold pressor pain. Only the highly hypnotizable subjects (HHs) who eliminated pain perception were included in the present study. These HHs, who demonstrated more effective attentional and inhibitory capabilities, had a significantly (P<0.003) larger (31.8%) rostrum, a corpus callosum area involved in the allocation of attention and transfer of information between prefrontal cortices, than low hypnotizable subjects (LHs). These results provide support to the neuropsychophysiological model that HHs have more effective frontal attentional systems implementing control, monitoring performance and inhibiting unwanted stimuli from conscious awareness, than LHs.

In the present study, functional magnetic resonance imaging was used to examine the neural mechanisms involved in the imagined spatial transformation of one's body. The task required subjects to update the position of one of four external objects from memory after they had performed an imagined self-rotation to a new position. Activation in the rotation condition was compared with that in a control condition in which subjects located the positions of objects without imagining a change in self-position. The results indicated similar networks of activation to other egocentric transformation tasks involving decisions about body parts. The most significant area of activation was in the left posterior parietal cortex. Other regions of activation common among several of the subjects were secondary visual, premotor, and frontal lobe regions. These results are discussed relative to motor and visual imagery processes as well as to the distinctions between the present task and other imagined egocentric transformation tasks.

Vibratory stimuli on the skin are mediated by two major receptors: Meissner corpuscles and Pacinian corpuscles. These receptors differ in properties such as density distribution, receptive field size, frequency sensitivity and depth of location. The cortical response to stimulation of these corpuscles can be tested by taking advantage of the differences in frequency discrimination of the receptors. Meissner corpuscles are most sensitive to frequencies around 10-50 Hz (flutter), while Pacinian corpuscles are most sensitive to high frequency (100-300 Hz) vibration. This study compared the neuronal responses (hemodynamic response) generated from vibratory stimuli of 35 Hz and 150 Hz with functional MRI. Group functional activation maps showed differences in the activation pattern for the two stimulus frequencies.

Presenting various stimuli in an MRI scanner can be difficult due to the high magnetic field associated with the scanner. Mechanical vibration stimuli are difficult to deliver to subjects in the MRI environment because most vibration devices contain internal circuitry that can adversely interact with the high magnetic field. Piezoelectric ceramics can provide a solution to this problem since they do not require any internal circuitry to vibrate. Piezoceramics are nonmagnetic and they can be made to vibrate if supplied with an alternating current from a straight wire. We designed a piezoceramic vibrotactile stimulator that is safe and effective in functional MRI experiments. The stimulator was tested in an fMRI experiment at 35 and 150 Hz. The results yielded activation sites in the primary sensory cortex and Brodmann area 40 at both frequencies.