Traci H. 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.

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

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.

Functional Near-Infrared Sensing (fNIR) and Environmental Control Applications

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.

Physiologic system interfaces using fNIR with tactile feedback for improving operator effectiveness

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 brain imaging for analysis of reading effort for computer-generated text

This paper discusses two functional brain imaging techniques, functional magnetic resonance imaging (fMRI) and functional near-infrared (fNIR) imaging, and their applications for quantitative usability analysis. This application is demonstrated through a two-phase study on reading effort required for varying degrees of font degradation. The first phase used fMRI to map cortical locations that were active while subjects read fonts of varying quality. The second phase used fNIR imaging, which showed higher levels of activity (and thus greater cognitive effort) in the visual processing area of the brain during a reading task with text presented in degraded fonts. The readability analysis techniques demonstrated in this study also generalize to applications requiring an objective analysis of interface usability.

Motor representations involved in perceiving tools and graspable non-tools: an fMRI study

•fMRI Acquisition »1.5 T Siemens Vision scanner »Gradient-echo EPI sequence »26 contiguous axial slices 4 mm thick with in-plane resolution of 2.6 x 2.6 mm »Whole brain acquisition »Maximum of 128 acquisitions •Activation Localization »Pearson’s correlation with Bonferroni correction (AFNI) »Registered to anatomical MRI and spatially normalized to Talairach atlas (AFNI) »ANOVA to compare Tools and Non-Tools •Task »Covertly name objects »Look at blurred images •Paradigm »Alternated epochs of Tools, Non-tools (NT) and Blurred Images (Control) »8 Pictures presented in each epoch (400 ms) followed by crosshair (1600 ms) Discussion Do we perceive objects relative to their potential for actions? A number of recent studies have found that observation and naming of common tools activates premotor areas in the absence of any motoric task (Chao & Martin, 2000; Grafton et al., 1997; Martin et al., 1996). Activity in this area has not been found in similar tasks involving other types of objects. A question exists as to whether premotor activity is associated with a tool’s semantic properties relating to action, or whether this activity is associated with automatic motor representations elicited by any objects that afford actions.