Biology subjects

Yucel, M. A.

Publications and source records attributed to Yucel, M. A..

4 recordsLinked to original sources

bioRxiv2025

High-Density Multi-Distance fNIRS Enhances Detection of Brain Activity during a Word-Color Stroop Task

STRUCTURED ABSTRACTO_ST_ABSSignificanceC_ST_ABSFunctional Near-Infrared Spectroscopy (fNIRS) enables neuroimaging in scenarios where other modalities are less suitable, such as during motion tasks or in low-resource environments. Sparse fNIRS arrays with 30mm channel spacing are widely used but have limited spatial resolution. High-density (HD) arrays with overlapping, multi-distance channels improve sensitivity and localization but increase costs and setup times. A statistical comparison of HD and sparse arrays is needed for evaluating the benefits and trade-offs of HD arrays. AimThis study provides a statistical comparison of HD and sparse fNIRS performance to inform array selection in future research. ApproachWe measured prefrontal cortex (PFC) activation during congruent and incongruent Word-Color Stroop (WCS) tasks using both Sparse and HD arrays for 17 healthy adult participants, comparing dorsolateral PFC channel and image results at the group level. ResultsWhile both arrays detected activation in channel space during incongruent WCS, channel and image space results demonstrated superior localization and sensitivity with the HD array for all WCS. ConclusionsSparse channel data may suitably detect activation from cognitively demanding tasks, like incongruent WCS. However, the HD array outperformed Sparse in detecting and localizing brain activity in image space, particularly during lower cognitive load tasks, making them more suitable for neuroimaging applications.

bioengineering↗

bioRxiv2025

Mapping human cerebral blood flow with high-density, multi-channel speckle contrast optical spectroscopy

Recently, speckle contrast optical spectroscopy (SCOS) enabled non-invasive, high signal-to-noise-ratio (SNR) human cerebral blood flow (CBF) measurements, relevant for both neuroscience and clinical monitoring of diseases with CBF dysregulation. Single channel SCOS measurements limit the information obtained to only one location on the head. In this work, we develop a multi-channel SCOS system to map spatial heterogeneity in CBF changes during human brain activation. Using a galvanometer, we temporally multiplexed a free-space laser to 7 source fibers positioned at different locations on the head. Diffuse light collected from the tissue is captured by fiber bundles projecting to 17 complementary metal-oxide semiconductor (CMOS) cameras, resulting in 50 source-detector channels measuring optical density (OD) and relative CBF changes covering an area of 7.6 cm by 6.6 cm on the head. We validated the spatial specificity and stability of the system using a liquid flow phantom. We then measured brain activity during a word-color Stroop task in 15 subjects and obtained brain activation maps. The average signal changes in the channel showing the largest activation were 1.7 x 10-2 in {Delta}OD and 6.6% in CBF.

bioengineering↗

bioRxiv2024

ninjaCap: A fully customizable and 3D printable headgear for fNIRS and EEG brain imaging

SignificanceAccurate sensor placement is vital for non-invasive brain imaging, particularly for functional near infrared spectroscopy (fNIRS) and diffuse optical tomography (DOT), which lack standardized layouts like EEG. Custom, manually prepared probe layouts on textile caps are often imprecise and labor-intensive. AimWe introduce a method for creating personalized, 3D-printed headgear, enabling accurate translation of 3D brain coordinates to 2D printable panels for custom fNIRS and EEG sensor layouts, reducing costs and manual labor. ApproachOur approach uses atlas-based or subject-specific head models and a spring-relaxation algorithm for flattening 3D coordinates onto 2D panels, using 10-5 EEG coordinates for reference. This process ensures geometrical fidelity, crucial for accurate probe placement. Probe geometries and holder types are customizable and printed directly on the cap, making the approach agnostic to instrument manufacturers and probe types. ResultsOur ninjaCap method offers 2.2{+/-}1.5 mm probe placement accuracy. Over the last five years, we have developed and validated this approach with over 50 cap models and 500 participants. A cloud-based ninjaCap generation pipeline along with detailed instructions is now available at openfnirs.org. ConclusionsThe ninjaCap marks a significant advancement in creating individualized neuroimaging caps, reducing costs and labor while improving probe placement accuracy, thereby reducing variability in research.

neuroscience↗

bioRxiv2024

fNIRS Dataset During Complex Scene Analysis

When analyzing complex scenes, humans often focus their attention on an object at a particular spatial location. The ability to decode the attended spatial location would facilitate brain computer interfaces for complex scene analysis (CSA). Here, we investigated capability of functional near-infrared spectroscopy (fNIRS) to decode audio-visual spatial attention in the presence of competing stimuli from multiple locations. We targeted dorsal frontoparietal network including frontal eye field (FEF) and intra-parietal sulcus (IPS) as well as superior temporal gyrus/planum temporal (STG/PT). They all were shown in previous functional magnetic resonance imaging (fMRI) studies to be activated by auditory, visual, or audio-visual spatial tasks. To date, fNIRS has not been applied to decode auditory and visual-spatial attention during CSA, and thus, no such dataset exists yet. This report provides an open-access fNIRS dataset that can be used to develop, test, and compare machine learning algorithms for classifying attended locations based on the fNIRS signals on a single trial basis.

neuroscience↗