Highlighting the strengths of new wearable fNIRS, precision accuracy microgenetic research designs, and new NeuroDOT processing algorithm to measure change over time in clinical populations for Speech-Language and Hearing Researchers

Abstract

Fundamental to understanding the process of intervention among individuals with communication disorders is the ability to document behavioral changes over time. This technical report demonstrates the clinical applicability of wearable fNIRS systems and NeuroDOT processing pipelines for examining within-person cortical dynamics of learning. Using a microgenetic research design and a dense sampling approach, we examined changes in the prefrontal cortical hemodynamic response in an adult female participant who completed the same spoken sentence repetition and auditory fixation tasks across eight sessions. In addition to participant accuracy, hemodynamic data were collected with a continuous-wave, multi-channel fNIRS system (NIRSport2) using a prefrontal 20-channel optode montage. Data were processed using NeuroDOT (https://www.nitrc.org/projects/neurodot) (Eggebrecht & Culver, 2019) to: (i) standardize signal quality across the sessions to quantify motion levels and to ensure standardized brain map specificity, (ii) to examine both channel space fluctuations in the hemodynamic response and map changes in cortical activation patterns over the sessions. The signal quality met the predefined criteria for only the first five sessions. Participant's repetition accuracy did not improve over the five sessions. Channel-wise analysis revealed that HbO concentration differs significantly over right and left hemisphere channels over the course of the five sessions for the Sentence Repetition task, but not for the Auditory Fixation condition. Brain maps revealed qualitative differences in the pattern of prefrontal cortical activation across the five sessions. To fully document the mechanisms that drive changes in behavior, understanding the brain-behavior link is critical to identifying and discriminating between typical and atypical learning.