INS NYC 2024 Program

Poster	Poster Session 06 Program Schedule 02/15/2024 04:00 pm - 05:15 pm Room: Shubert Complex (Posters 1-60) Poster Session 06: Aging \| MCI \| Neurodegenerative Disease - PART 2 Final Abstract #36 Concurrent functional Near-Infrared Spectroscopy and 6 Degree of Freedom Immersive Virtual Reality in Older Adults Victor Di Rita, Research Program on Cognition and Neuromodulation Based Interventions, Department of Psychiatry, University of Michigan, Ann Arbor, United States Allison Ploutz-Snyder, Research Program on Cognition and Neuromodulation Based Interventions, Department of Psychiatry, University of Michigan, Ann Arbor, United States Loryn Davidson, Research Program on Cognition and Neuromodulation Based Interventions, Department of Psychiatry, University of Michigan, Ann Arbor, United States Darby Eck, Research Program on Cognition and Neuromodulation Based Interventions, Department of Psychiatry, University of Michigan, Ann Arbor, United States Alexandru Iordan, Research Program on Cognition and Neuromodulation Based Interventions, Department of Psychiatry, University of Michigan, Ann Arbor, United States Benjamin Hampstead, Research Program on Cognition and Neuromodulation Based Interventions, Department of Psychiatry, University of Michigan, Ann Arbor, United States Category: Dementia (Alzheimer's Disease) Keyword 1: visuospatial functions Keyword 2: neuroimaging: functional Objective: Impairments in spatial navigation (SN) present in the earliest stages of dementia of the Alzheimer’s type (DAT) and may have greater specificity for Alzheimer's pathology than episodic memory deficits. Thus, developing techniques that allow for the precise characterization of SN capabilities in aging populations may enhance the detection of early cognitive change, a crucial step for intervening. Here we present a novel six-degree-of-freedom immersive virtual reality (iVR) SN paradigm with concurrent functional near-infrared spectroscopy (fNIRS). To our knowledge, this is the first study to investigate ecological spatial navigation using a fully wireless head-mounted iVR display with a portable continuous-wave fNIRS system in an older adult population. Participants and Methods: Six cognitively intact older adults completed standardized neuropsychological tests as well as a custom iVR environment that was created using the Unity video game engine. Participants freely explored the space and were instructed to remember distinct images in each room. We acquired fNIRS during the encoding phase using two NIRSport2 CW-fNIRS devices and a total of 50 channels (42 long and 8 short) arising from 14 sources, 16 detectors, and eight short channels. After encoding, we evaluated participants’ ability to navigate back to the images, beginning each trial from a different location in the environment. fNIRS data were pre-processed, analyzed, and visualized using the Brain AnalyzIR toolbox and EasyTopo. We defined blocks for a GLM analysis as the five seconds prior to entering a room and the first ten seconds inside the room. Given the small sample for this study, we present beta coefficients from all fNIRS channels as measures of effect size in lieu of setting statistical thresholds. We focused our iVR analysis on the encoding phase. We calculated the total distance traveled during encoding (path length) for each participant and used this as a measure of how efficiently they learned the environment. We then calculated the Spearman’s rank correlation coefficient (ρ) for the association between path length and neuropsychological test scores. Results: No participant reported motion sickness while in the iVR environment. Path length during encoding showed inverse correlations with visuospatial (ρ = -0.54) and attention (ρ = -0.60) index scores from RBANS and positive correlations with Trails A (ρ = 0.71) and B (ρ = 0.60) completion times. Based on the magnitude of beta coefficients at the group level, fNIRS data showed trends in activation in the left angular gyrus as well as the pre- and postcentral gyrus bilaterally. Conclusions: Our iVR paradigm provides a novel approach for understanding ecologically relevant cognitive changes that occur in older adults across the Alzheimer’s disease and related dementias spectrum. Future efforts will integrate machine-learning classification techniques using the several thousand movement data points acquired per participant to elucidate navigational “fingerprints” present within this population.

Poster

02/15/2024
04:00 pm - 05:15 pm
Room: Shubert Complex (Posters 1-60)

Poster Session 06: Aging | MCI | Neurodegenerative Disease - PART 2

Final Abstract #36

Concurrent functional Near-Infrared Spectroscopy and 6 Degree of Freedom Immersive Virtual Reality in Older Adults

Victor Di Rita, Research Program on Cognition and Neuromodulation Based Interventions, Department of Psychiatry, University of Michigan, Ann Arbor, United States
Allison Ploutz-Snyder, Research Program on Cognition and Neuromodulation Based Interventions, Department of Psychiatry, University of Michigan, Ann Arbor, United States
Loryn Davidson, Research Program on Cognition and Neuromodulation Based Interventions, Department of Psychiatry, University of Michigan, Ann Arbor, United States
Darby Eck, Research Program on Cognition and Neuromodulation Based Interventions, Department of Psychiatry, University of Michigan, Ann Arbor, United States
Alexandru Iordan, Research Program on Cognition and Neuromodulation Based Interventions, Department of Psychiatry, University of Michigan, Ann Arbor, United States
Benjamin Hampstead, Research Program on Cognition and Neuromodulation Based Interventions, Department of Psychiatry, University of Michigan, Ann Arbor, United States

Category: Dementia (Alzheimer's Disease)

Keyword 1: visuospatial functions
Keyword 2: neuroimaging: functional

Objective:

Impairments in spatial navigation (SN) present in the earliest stages of dementia of the Alzheimer’s type (DAT) and may have greater specificity for Alzheimer's pathology than episodic memory deficits. Thus, developing techniques that allow for the precise characterization of SN capabilities in aging populations may enhance the detection of early cognitive change, a crucial step for intervening. Here we present a novel six-degree-of-freedom immersive virtual reality (iVR) SN paradigm with concurrent functional near-infrared spectroscopy (fNIRS). To our knowledge, this is the first study to investigate ecological spatial navigation using a fully wireless head-mounted iVR display with a portable continuous-wave fNIRS system in an older adult population.

Participants and Methods:

Six cognitively intact older adults completed standardized neuropsychological tests as well as a custom iVR environment that was created using the Unity video game engine. Participants freely explored the space and were instructed to remember distinct images in each room. We acquired fNIRS during the encoding phase using two NIRSport2 CW-fNIRS devices and a total of 50 channels (42 long and 8 short) arising from 14 sources, 16 detectors, and eight short channels. After encoding, we evaluated participants’ ability to navigate back to the images, beginning each trial from a different location in the environment. fNIRS data were pre-processed, analyzed, and visualized using the Brain AnalyzIR toolbox and EasyTopo. We defined blocks for a GLM analysis as the five seconds prior to entering a room and the first ten seconds inside the room. Given the small sample for this study, we present beta coefficients from all fNIRS channels as measures of effect size in lieu of setting statistical thresholds. We focused our iVR analysis on the encoding phase. We calculated the total distance traveled during encoding (path length) for each participant and used this as a measure of how efficiently they learned the environment. We then calculated the Spearman’s rank correlation coefficient (ρ) for the association between path length and neuropsychological test scores.

Results:

No participant reported motion sickness while in the iVR environment. Path length during encoding showed inverse correlations with visuospatial (ρ = -0.54) and attention (ρ = -0.60) index scores from RBANS and positive correlations with Trails A (ρ = 0.71) and B (ρ = 0.60) completion times. Based on the magnitude of beta coefficients at the group level, fNIRS data showed trends in activation in the left angular gyrus as well as the pre- and postcentral gyrus bilaterally.

Conclusions:

Our iVR paradigm provides a novel approach for understanding ecologically relevant cognitive changes that occur in older adults across the Alzheimer’s disease and related dementias spectrum. Future efforts will integrate machine-learning classification techniques using the several thousand movement data points acquired per participant to elucidate navigational “fingerprints” present within this population.