Seminars in Hearing Research (03/06/25) - Victoria Sinfield
Seminars in Hearing Research (03/06/25) - Victoria Sinfield
| Author: | M. Heinz |
|---|---|
| Event Date: | March 6, 2025 |
| Hosted By: | Maureen Shader |
| Time: | 12:00 - 1:00 pm |
| Location: | Nelson 1215 |
| Contact Name: | Shader, Maureen J |
| Contact Email: | mshader@purdue.edu |
| Open To: | All |
| Priority: | No |
| School or Program: | Non-Engineering |
| College Calendar: | Show |
Seminars in Hearing Research
Date: Thursday, March 6, 2025
Location: Nelson 1215
Time: Noon - 1:00 pm
Speaker: Victoria Sinfield. Master's Student, BME
Title: Optimizing fNIRS for enhanced cognitive load analysis through multidimensional noise correction.
Abstract: Functional near-infrared spectroscopy (fNIRS) is a valuable tool for studying cognitive processes, offering a non-invasive way to measure hemodynamic responses during naturalistic tasks. However, systemic physiological noise presents a challenge for test-retest reliability, particularly in auditory research, making it critical to establish robust pre-processing strategies to ensure that observed neural signals accurately reflect cognitive activity. To address this, we conducted a multidimensional test-retest reliability analysis, comparing six noise correction approaches across ten sessions of a passive auditory task in a single participant, ultimately identifying key factors that influence both reliability and signal accuracy. While regression of systemic and extra-cerebral signals reduced reliability metrics, it provided a more accurate depiction of neural activity by mitigating confounding noise. Notably, certain correction methods may prove more appropriate and effective for active cognitive tasks, where systemic responses interact more dynamically with task demands. With these insights, we applied a suitable correction approach to an independent experiment focused on determining the effects of auditory cognitive load on sentence recognition, allowing us to examine task-related hemodynamic responses while ensuring signal consistency and accuracy. This work highlights the importance of optimizing fNIRS pre-processing strategies to enhance the validity of cognitive research, ultimately improving the interpretability and reproducibility of neural measures in complex tasks that reflect real-world scenarios.
---
The working schedule is available here: https://purdue.edu/TPAN/hearing/shrp_schedule
The titles and abstracts of the talks will be added here: https://purdue.edu/TPAN/hearing/shrp_abstracts