Stimulus and Optode Placement Effects on Functional Near-Infrared Spectroscopy of Visual Cortex

Functional near-infrared spectroscopy has yet to be implemented as a stand-alone technique within an ophthalmology clinical setting, despite its promising advantages. The present study aims to further investigate reliability of visual cortical signals. This was achieved by: (1) assessing the effects of optode placements using the 10–20 International System of Electrode Placement consisting of 28 channels, (2) determining effects of stimulus size on response, and (3) evaluating response variability as a result of cap placement across three sessions. Ten participants with mean age 23.8 4.8 years (five male) and varying types of hair color and thickness were recruited. Visual stimuli of black-and-white checkerboards, reversing at a frequency of 7.5 Hz were presented. Visual angles of individual checker squares included 1 deg, 2 deg, 5 deg, 9 deg, and 18 deg. The number of channels that showed response was analyzed for each participant, stimulus size, and session. 1-deg stimulus showed the greatest activation. One of three data collection sessions for each participant gave different results (p \u3c 0.05). Hair color and thickness each had an effect upon the overall HbO (p \u3c 0.05), while only color had a significant effect for HbD (p \u3c 0.05). A reliable level of robustness and consistency is still required for clinical implementation and assessment of visual dysfunction

Evaluation of Functional Near Infrared Spectroscopy (fNIRS) for Assessment of the Visual and Motor Cortices in Adults

Introduction: Functional near-infrared spectroscopy (fNIRS) is a relatively young technique in the field of medical imaging. As such, it has yet to be widely implemented for clinical use, despite its promising advantages. However, unlike fMRI-its much bulkier and costly counterpart-fNIRS has yet to be proven as a standalone imaging tool within a clinical setting, particularly that of ophthalmology or physical therapy. Methods: Ten healthy young adults (23.8 ± 4.8 years) participated in the study. Activation of the visual cortex was achieved utilizing various reversing checkerboard stimuli across three data collection sessions for each participant. Further, activation of the motor cortex was achieved using simple grasping and finger tapping tasks. Data was processed with MATLAB scripts and statistical analysis was performed using JMP. Results: Quantitatively, statistically significant differences in the level of activation were elicited by some stimuli, but not others. No differences were discovered between the levels of activation for the two motor tasks. However, as expected, differences were observed between the hair types of participants for both visual and motor activation. Additionally, one of the three data collection sessions for each participant tended to give statistically different results than the other two. Qualitatively, the number of stimulus events and data channels which showed activation were inconsistent. Conclusions: It has been shown, both previously (by others) and within this study, that fNIRS is indeed feasible for investigating the visual and motor cortices. However, a reliable level of robustness and sensitivity is required for clinical implementation. This research shows that fNIRS can in fact achieve an appropriate level of sensitivity for visual studies, but it still lacks an appropriate level of robustness in terms of repeatability and corporal differences for assessment of visual or motor dysfunction

Evaluation of Functional Near Infrared Spectroscopy (fNIRS) for Assessment of the Visual and Motor Cortices in Adults

Introduction: Functional near-infrared spectroscopy (fNIRS) is a relatively young technique in the field of medical imaging. As such, it has yet to be widely implemented for clinical use, despite its promising advantages. However, unlike fMRI-its much bulkier and costly counterpart-fNIRS has yet to be proven as a standalone imaging tool within a clinical setting, particularly that of ophthalmology or physical therapy.Methods: Ten healthy young adults (23.8 ± 4.8 years) participated in the study. Activation of the visual cortex was achieved utilizing various reversing checkerboard stimuli across three data collection sessions for each participant. Further, activation of the motor cortex was achieved using simple grasping and finger tapping tasks. Data was processed with MATLAB scripts and statistical analysis was performed using JMP.Results: Quantitatively, statistically significant differences in the level of activation were elicited by some stimuli, but not others. No differences were discovered between the levels of activation for the two motor tasks. However, as expected, differences were observed between the hair types of participants for both visual and motor activation. Additionally, one of the three data collection sessions for each participant tended to give statistically different results than the other two. Qualitatively, the number of stimulus events and data channels which showed activation were inconsistent.Conclusions: It has been shown, both previously (by others) and within this study, that fNIRS is indeed feasible for investigating the visual and motor cortices. However, a reliable level of robustness and sensitivity is required for clinical implementation. This research shows that fNIRS can in fact achieve an appropriate level of sensitivity for visual studies, but it still lacks an appropriate level of robustness in terms of repeatability and corporal differences for assessment of visual or motor dysfunction

Hand-Grasping and Finger Tapping Induced Similar Functional Near-Infrared Spectroscopy Cortical Responses

Despite promising advantages such as low cost and portability of functional near-infrared spectroscopy (fNIRS), it has yet to be widely implemented outside of basic research. Specifically, fNIRS has yet to be proven as a standalone tool within a clinical setting. The objective of this study was to assess hemodynamic concentration changes at the primary and premotor motor cortices as a result of simple whole-hand grasping and sequential finger-opposition (tapping) tasks. These tasks were repeated over 3 days in a randomized manner. Ten healthy young adults (23.8 4.8 years) participated in the study. Quantitatively, no statistically significant differences were discovered between the levels of activation for the two motor tasks (p \u3e 0.05). Overall, the signals were consistent across all 3 days. The findings show that both finger-opposition and hand grasping can be used interchangeably in fNIRS for assessment of motor function which would be useful in further advancing techniques for clinical implementation

Empowering Implementation Teams with a Learning Health System Approach: Leveraging Data to Improve Quality of Care for Transient Ischemic Attack

BACKGROUND: Questions persist about how learning healthcare systems should integrate audit and feedback (A&F) into quality improvement (QI) projects to support clinical teams' use of performance data to improve care quality. OBJECTIVE: To identify how a virtual "Hub" dashboard that provided performance data for patients with transient ischemic attack (TIA), a resource library, and a forum for sharing QI plans and tools supported QI activities among newly formed multidisciplinary clinical teams at six Department of Veterans Affairs (VA) medical centers. DESIGN: An observational, qualitative evaluation of how team members used a web-based Hub. PARTICIPANTS: External facilitators and multidisciplinary team members at VA facilities engaged in QI to improve the quality of TIA care. APPROACH: Qualitative implementation process and summative evaluation of observational Hub data (interviews with Hub users, structured field notes) to identify emergent, contextual themes and patterns of Hub usage. KEY RESULTS: The Hub supported newly formed multidisciplinary teams in implementing QI plans in three main ways: as an information interface for integrated monitoring of TIA performance; as a repository used by local teams and facility champions; and as a tool for team activation. The Hub enabled access to data that were previously inaccessible and unavailable and integrated that data with benchmark and scientific evidence to serve as a common data infrastructure. Led by champions, each implementation team used the Hub differently: local adoption of the staff and patient education materials; benchmarking facility performance against national rates and peer facilities; and positive reinforcement for QI plan development and monitoring. External facilitators used the Hub to help teams leverage data to target areas of improvement and disseminate local adaptations to promote resource sharing across teams. CONCLUSIONS: As a dynamic platform for A&F operating within learning health systems, hubs represent a promising strategy to support local implementation of QI programs by newly formed, multidisciplinary teams