2432
Symposium
The growing emphasis on naturalistic imaging paradigms underscores the importance of exploring next-generation, wearable, high-resolution optical neuroimaging technologies, such as high-channel-count fNIRS (HCC-fNIRS) and High-Density Diffuse Optical Tomography (HD-DOT). These modalities offer a promising alternative to functional magnetic resonance imaging (fMRI), especially in scenarios where fMRI's logistical limitations hinder its application. This symposium aims to showcase the latest advancements in HCC-fNIRS and HD-DOT, particularly their application in wearable systems for real-time, real-world brain imaging.
As the field gravitates towards these innovative technologies, evidenced by the increasing number of fNIRS/DOT abstracts presented at recent OHBM conferences, it becomes crucial for the neuroscience community to deepen its understanding and application of these tools in everyday life studies. This symposium will provide critical insights into the operational use cases of HCC-fNIRS and HD-DOT and demonstrate how these technologies can be integrated into current fMRI research frameworks.
A highlight is a talk by Dr. Alexander Huth, who shows the utility of DOT in cutting-edge fMRI language decoding studies, leveraging extensive within-subject datasets to map and decode language processes. This symposium is designed not only to inform but also to inspire attendees, encouraging the adoption and advancement of HCC-fNIRS and HD-DOT in naturalistic neuroimaging applications. Participants will leave with a clearer understanding of how these technologies can transform the landscape of functional neuroimaging and enhance the fidelity of brain mapping in dynamic, everyday environments.
1. Demonstrate the Viability of Wearable Optical Imaging Technologies: Participants will learn how high-channel-count fNIRS (HCC-fNIRS) and High-Density Diffuse Optical Tomography (HD-DOT) serve as effective surrogates to traditional fMRI, specifically in conducting brain research within naturalistic settings.
2. Explore Unique Experimental Applications: The symposium will introduce attendees to the unique types of naturalistic experiments enabled by wearable optical imaging technologies, highlighting studies that are impractical with traditional fMRI due to its physical and environmental constraints.
3. Establish the Future Trajectory of Wearable Neuroimaging: Attendees will gain insights into the future directions of HCC-fNIRS and HD-DOT within naturalistic studies and the goals for the next decade of research.
This symposium targets researchers and clinicians specializing in naturalistic, pediatric, and clinical neuroimaging, bridging the gap between traditional fMRI and emerging wearable technologies. It is particularly designed for fMRI researchers interested in learning about the advantages, limitations, and applications of wearable optical neuroimaging research within the context of naturalistic imaging.
Presentations
Optical brain mapping techniques fill crucial gaps via enabling technologies for assessing health in patients contraindicated for fMRI, in naturalistic settings, and at the point of care. However, most previous fNIRS systems used sparse-imaging arrays, significantly corrupting image quality. High-Density DOT (HD-DOT), an advanced form of fNIRS, leverages high-density arrays of interdigitated sources and detectors to increase the SD-pair channel count dramatically and enable volumetric reconstruct images of the brain that leverage MRI anatomy, often subject-specific. Recent results with High-Density DOT (HD-DOT) demonstrate the feasibility of mapping sensory networks (visual, auditory, motor) and distributed cognitive networks, including the frontal-parietal and default mode networks. Despite these advances, the application of HD-DOT to naturalistic studies has been limited by large optoelectronic consoles and bulky fiber optics. Making HD-DOT wearable is the key to unlocking and disseminating HD-DOT for cognitive neuroscience research. A new generation of wearable high-channel-count fNIRS and HD-DOT systems are enabling this paradigm shift.
Presenter
Joseph Culver, PhD, Washington University in St. Louis
Radiology
St. Louis, MO
United States
Longitudinal inter-generational study designs allow evaluation of the relationship differences between the same or different generations. Pairs of participants (young adult + senior or two young adults) engaged in collaborative art and cognitive tasks across six weekly sessions. We measured brain activity using fNIRS, body movements using video-based motion capture, as well as behavioral and qualitative aspects of the real-world experience. This research sheds light on how budding relationships may be supported by the emergence of motor synchrony and inter-brain synchrony over time.
Advances in wearable functional near-infrared spectroscopy (fNIRS) and diffuse optical tomography (DOT) are rapidly expanding opportunities to complement fMRI by studying the brain in ecologically valid environments. Transitioning from well-controlled laboratory settings to the dynamic, complex, and multisensory environments of the everyday world presents a range of significant challenges, particularly in signal acquisition and processing. However, the increasing ease of acquiring larger data volumes also paves the way for new, powerful, data-driven approaches that can be used as a remedy. A typical goal is to improve the contrast of the hemodynamic response by better differentiating evoked from non-evoked and cerebral from non-cerebral physiological activity and behavior. This is particularly relevant for biomarker extraction and single-trial analysis, e.g., in brain-computer interfaces or neuroergonomics. In my talk, I will examine recent advances in mobile brain monitoring using fNIRS/DOT, discuss some of the current data science challenges, and demonstrate how we have begun to tackle them.
Presenter
Alexander von Lühmann, Intelligent Biomedical Sensing Lab - TU Berlin / BIFOLD Berlin, Berlin
Germany
Deep neural network language models enable us to model how the human brain responds to natural language with unprecedented accuracy. Applied to very large within-subject datasets, these models enable us to both map language representations with high fidelity and decode language that a person is hearing or thinking from non-invasive functional measurements. I will discuss recent advances in mapping and decoding language representations using BOLD fMRI in combination with modern AI tools and the integration of HD-DOT for these methods.