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Category Archives: sfNIRS2024-Session-2
Sa-093-Optimizing Short Distance Diffuse Correlation Spectroscopy
Diffuse correlation spectroscopy (DCS) is a promising method for non-invasively monitoring cerebral blood flow (CBF). Its accuracy requires accounting for signal contamination from scalp blood flow, typically performed by recording DCS signals at a short source-detector separation (SDS), in addition to a longer SDS that provides sensitivity to CBF. However, balancing the signal-to-noise ratio (SNR) at the two distances is challenging. Our study investigates the potential impact of emitter light intensity on short separation DCS measurements. Continue reading
Sa-094-Assessing the Reproducibility of a Hybrid Time-Resolved NIRS/DCS System for Daily Hemodynamic ICU Monitoring
Bedside cerebral oxygenation and blood flow monitoring in the intensive care unit (ICU) has the potential to improve early detection of cerebral ischemia. To assess the feasibility of daily optical monitoring, the reproducibility of oxygenation and blood flow measurements using an in-house built time-resolved NIRS/DCS system was assessed. Data were collected on three days (1,2, and 7); each consisted of three acquisition sessions where the probes were removed and re-secured between sessions. Oxygenation varied by <6% within and between sessions, while blood flow varied by 15% within sessions and 26% between sessions. Continue reading
Sa-090-A modular TD-fNIRS system for many applications
Kernel has developed a new and modular system for time-domain functional near-infrared spectroscopy (TD-fNIRS). We have previously demonstrated the ability of the system to accurately measure absolute optical properties and tissue oxygen saturation. Here, we will present a highly configurable form factor that we’ve made to enable additional applications using our core modular TD-NIRS technology. We will share results that demonstrate the ability of our system to resolve functional brain activation along with physiological signals. In summary, these technological innovations allow for the development of new applications of TD-fNIRS that use a modular, scalable system for measuring multimodal brain signals. Continue reading
Sa-098-Artefact detection and removal using ICA-ERBM in fNIRS
We introduce a blind source separation technique for the detection and removal of artefacts in fNIRS data. Synthetic HRFs are added to optical density timeseries recorded from three subjects with simultaneous accelerometer and gyroscope recordings. ICA-ERBM is used to identify and remove artefacts correlated with motion. We compare the recovery of the synthetic HRFs after motion correction across methods and observe strong performance from the ICA-ERBM algorithm indicating, that with further hyperparamter tuning, it has potential to effectively clean fNIRS signals. Continue reading
Sa-101-Novel fNIRS Digitization Methodology, Firefly: Innovative 3D Imaging and Software
Optode location variance due to cap placement and head topology, as well as scalp-cortex correlation, are essential aspects of fNIRS research. We present an innovative digitization methodology, Firefly (© pending), utilizing blue-light 3D imaging, color-depth mapping, and custom software applications to provide dynamic assessments of optode positioning during capping procedures, compatible with EasyCap and custom probe designs. Pilot data suggest our methodology enhances digitization localization and offers a robust solution to convert channel space locations to voxel space locations within the brain volume; ultimately providing researchers with an efficient, unified solution for creating scalp-cortex sensitivity profiles. Continue reading
Sa-105-Semantic memory for brand-name products: The view from tensor decomposition of the fNIRS signal
Tensor decomposition was used to examine the impact of semantic categorization of brand name products on blood flow in the left and right lateral prefrontal cortex (LPFC) and anterior temporal lobe (ATL) during a study phase and again in a test phase in which the previously categorized products were presented for a purchase decision. Results showed that categorization in the study phase resulted in relatively greater hemodynamic activity in all regions and relatively less hemodynamic activity during the test phase, but only in the left ATL. These findings suggest that tensor decomposition is a feasible approach to analyzing fNIRS signals. Continue reading
Sa-077-Investigating newborns’ representations of language prosody with NIRS-EEG
In this work, we employ concurrent NIRS and EEG to investigate newborns’ neural mechanisms underlying the processing of speech and animal vocalizations. Continue reading
Sa-078-Decoding Valence and Arousal in Music Using fNIRS
Music's impact on emotion regulation and reward has attracted plenty of attention in cognitive and affective neuroscience prompting interest in its neural correlates for potential neurorehabilitation interventions. We acquired fNIRS data from 7 participants while listening to 24 musical excerpts divided considering the valence-arousal model proposed by Russell. We decoded specific quadrants with 53.6% ± 33.1% accuracy. This work validates fNIRS as a viable interface for rehabilitative approaches using music. Continue reading
Sa-015-Uncontrolled False Positives in Filtered fNIRS: A Critical Examination
Filtering is a common preprocessing method in functional near infrared spectroscopy (fNIRS) but can lead to assumption violations in the statistical methods used in fNIRS research. Simulated data with a variety of noise conditions tested whether these assumption violations lead to uncontrolled false positive rate (FPR). Preprocessing with a filter led to a loss of false positive control for all tested statistical methods and measured an FPR much higher than the α-level. We conclude that filtering should be avoided in combination with many common statistical approaches in fNIRS. Continue reading
Sa-081-A naturalistic approach to investigate the neural correlates of a laundry cycle with and without fragrance
Advancements in brain imaging have facilitated the development of “real-world” experimental scenarios. In this study, participants engaged in a household chore – laundry – while their frontal lobe brain activity was monitored using fNIRS. Participants completed this twice using both fragranced and unfragranced detergent, to explore if fNIRS is able to identify any differences in brain activity in response to subtle changes in stimuli. Analysis was conducted using Automatic IDentification of functional Events (AIDE) software and fNIRS correlation-based signal improvement (CBSI). Results indicated that brain activity, particularly in the right frontopolar and occasionally the left dorsolateral prefrontal cortex, was more pronounced and frequent with the unfragranced detergent than the fragranced. Continue reading