J. Hunter Downs

An fMRI study of imagined self-rotation

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 selfposition. 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.

FMRI mapping of the somatosensory cortex with vibratory stimuli: Is there a dependency on stimulus frequency?

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.

A new vibrotactile stimulator for functional MRI

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. Hum. Brain Mapping 10:140–145, 2000.

Surface-Based Spatial Normalization Using Convex Hulls

In this chapter, a new method for spatial normalization, the convex hull method, has been described that uses both affine and nonaffine transformations for normalizing individual brains sizes and shapes to that of a standard brain. It does so in an automated way and has been shown to exceed or match the ability of other methods to reduce anatomical variability. It has been demonstrated that the convex hull method can successfully spatially normalize magnetic resonance images to the 1988 Talairach atlas in a completely automated manner. The spatial normalization of positron emission tomography images using the convex hull method is also completely automated The convex hull also meets all the original design goals for a spatial normalization method—namely, it matches the surface of the brain being normalized to the Talairach atlas surface, it has no modalities specific steps in the process, it requires no additional images other than those being normalized, and requires no landmark selections. Additionally, it is capable of normalizing partially complete data and it is not specific to spatially normalizing to the 1988 Talairach atlas, allowing it to be used with future atlases. The studies of anatomical variability in the 1988 Talairach atlas space indicate that the sulci are of the order of two to three times more variable than point structures and deep gray matter nuclei. There is also some evidence to suggest that the variability of brain structures may be influenced by the rigidity of its neighborhood.

A new approach to functional near-infrared technology

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

Adaptive control of teleoperation systems

We develop suitable adaptive control schemes for control of a teleoperation system with unknown parameters of different types: those with constant values, those with jumping values, and those with smooth but large time-varying values. Associated with different situations of adaptive control systems, different new transparency concepts are introduced and verified by analysis and simulation results.

An integrated remote neurosurgical system

The Neurovisualization Lab at the University of Virginia is developing the Integrated Remote Neurosurgical System (IRNS) to allow mentoring of neurosurgical procedures in remote locations. The system allows a remote neurosurgeon to control a robotic microscope through the use of a 3-D input device, communicate with the operating room (0/R) team through live audio and video, and view presurgical imagery. The surgical team in the O/R will have access to the same images and communication facilities. The system will serve as a training tool through the use of a complete robotic simulation we have developed. We have also instituted safety precautions in the form of restriction of robot motion, monitoring, and protocols of system use. We have developed a registration system to assist in the implementation of these guidelines. A task analysis has led to the development of a prototype user interface, and the preliminary integration of available components has been completed. We report on the current state of the system and ongoing development with respect to the user interface and experimentation.

Exploring calibration techniques for functional near-infrared imaging (fNIR) controlled brain-computer interfaces

Functional near-infrared sensing (fNIR) enables real-time, non-invasive monitoring of cognitive activity by measuring the brains 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.

Engaging, Non-Invasive Brain-Computer Interfaces (BCIs) for Improving Training Effectiveness & Enabling Creative Expression:

Controlling computers and other electronic devices using only ones 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.

Parsimonious Identification of Physiological Indices for Monitoring Cognitive Fatigue

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.