Pre-Congress Workshops
Monday, July 6

Full Day Workshop

This course will teach modeling and processing approaches for using diffuse optical methods for mapping brain function in humans. This includes temporal data processing and image reconstruction using the NeuroDOT software package. This course will use a combination of instructor lecturing and hands-on exercises using publicly available high-fidelity data to teach both conceptual and practical aspects of fNIRS imaging using the NeuroDOT software package and Optical-imaging XNAT-enabled Informatics (OXI).

Attendees will learn and develop skills using NeuroDOT pipelines including data pre-processing, anatomical light modeling, and image reconstruction. All the training will be centered upon providing knowledge, training and tools for volumetric imaging of functional brain activations based on contrasts of hemoglobin concentration as measured using fNIRS data. The class will review the basic physics and biology of the approach, step through how the software works locally and on the cloud, and train attendees to use the software through exercises. More information about NeuroDOT is available at https://www.nitrc.org/projects/neurodot. The goal of the workshop is for attendees to understand current fNIRS and HD-DOT methods and their applications, quantitatively assess and track data quality, and utilize the NeuroDOT toolbox to perform data pre-processing, image reconstruction, and anatomical light modeling in a reproducible manner.

Participants will be able to use OXI to test NeuroDOT pipelines on provided sample datasets, which they can then apply to their own data. Workshop attendees will learn about how to integrate data from different types of fNIRS systems, including custom and commercially available systems (GowerLabs LUMO, NIRx, Artinis, and more). The format of the workshop will be a combination of lecture-style presentations and hands-on activities. During the lectures, participants will also be encouraged to ask questions to facilitate discussion. In the hands-on component, attendees will perform data pre-processing, data quality assessment, image reconstruction, array alignment, and head modeling using NeuroDOT in Matlab. Jupyter notebooks in Python for NeuroDOT pre-processing and image reconstruction pipelines will also be available for the attendees to use. Participants who participate in the hands-on tutorials will be able to perform a range of modeling and analyses using open-source tools in Matlab and Python. Attendees of the workshop will be able to interact directly with the presenters who are the main developers of NeuroDOT and OXI. Proposed ideas and feedback from the attendees will be used to guide future development of the NeuroDOT and OXI tools.

Half Day Workshops – Morning

This workshop bridges the methodological gap between screen-based and head-mounted eye-tracking systems in infant research. Participants will develop a unified conceptual framework for understanding both approaches and gain practical implementation strategies for their own research.

Primary Learning Objectives: Participants will learn to make informed decisions about which eye-tracking system best addresses their research questions. We will examine how screen-based systems excel at measuring precise gaze patterns to controlled stimuli, while head-mounted systems enable investigation of natural exploratory behavior and real-world object interactions.

The workshop emphasizes that despite differences in data collection, both systems rely on shared analytical concepts. Participants will understand how Areas of Interest (AOIs) and Time Windows of Interest function across systems, though their implementation differs. This allows researchers to transfer analytical thinking from screen-based paradigms to mobile eye-tracking contexts.A core objective is understanding head-mounted eye-tracking data processing. Participants will learn how preprocessing challenges (absent stable reference points and dynamic scenes) can be addressed through methodological solutions that leverage shared analytical principles, illustrating how head-mounted data can be structured using familiar concepts.

Takeaway Skills: By workshop conclusion, participants will:

(1) evaluate which eye-tracking approach suits their research questions,
(2) identify shared analytical principles across both systems,
(3) understand preprocessing strategies for head-mounted eye-tracking, and (
4) adapt screen-based analytical frameworks to mobile eye-tracking data.

The workshop will combine presentations with interactive discussion and live demonstrations, providing participants with conceptual understanding and practical examples they can explore independently after the workshop.

Structure: The workshop will be organized around key themes comparing and contrasting screen-based and head-mounted eye-tracking approaches. Each session will include presentations explaining methodological principles, followed by discussion of how these principles apply to different research contexts in infant studies.

Demonstrations: We will present data examples from both screen-based and head-mounted eye-tracking studies, illustrating typical data structures and analytical challenges for each system. These real-world examples will help participants recognize the practical implications of methodological choices discussed in the theoretical sections.Coding examples will showcase processing pipelines for both eye-tracking approaches. Participants will follow along as we walk through example scripts. These demonstrations will emphasize the conceptual parallels in how both systems handle Areas of Interest definition, time window selection, and data aggregation, making the commonalities concrete and tangible.Discussion

Components: Throughout the workshop, we will facilitate group discussions where participants can share their research questions and receive guidance on which eye-tracking approach might be most suitable. These segments will allow attendees to contextualize the material within their specific research programs.

Take-Home Materials: Participants will receive presentation slides, example datasets from both screen-based and head-mounted studies, and fully commented analysis scripts to explore at their own pace after the workshop.

Implementing the NIH Baby Toolbox in Large-Scale and International Research

 This workshop will equip researchers with practical, evidence-based guidance for implementing the NIH Baby Toolbox in large-scale, multi-site, and international studies. The Baby Toolbox is a newly normed, standardized assessment battery available in English and Spanish for infants 1–42 months. As the only NIH-sponsored standardized assessment built specifically for infancy, it fills a longstanding gap in early developmental science, where measurement challenges have historically limited scalability. Although the battery has strong psychometric foundations, successful deployment in large-scale settings requires thoughtful planning to ensure high-quality administration, reliable scoring, and consistency across contexts. Drawing on lessons learned from large-scale, multi-site infant studies, this workshop will feature five presentations that illustrate challenges and opportunities inherent in administering developmental assessments at scale.

Together, these talks will highlight common issues faced in infant assessment, including training teams with varied experience levels, ensuring fidelity across sites, integrating technology reliably, and navigating data-sharing and open-science requirements. They will also showcase concrete strategies that have proven effective in combating these challenges. By using the Baby Toolbox as a case example, the workshop aims to equip attendees with a deeper understanding of how standardized infant assessments can be deployed successfully across complex research infrastructures and how these tools can unlock new scientific questions that require large, high-quality datasets.

Participants will leave with clear guidance for integrating developmental assessments into large-scale studies, as well as and understanding of how to access publicly available Baby Toolbox data from these large projects for their own research agendas.  Workshop Format: This workshop will follow a presentation-plus-discussion format.

The core of the workshop will feature five focused talks, each offering complementary perspectives on large-scale implementation of developmental assessments. 

Half Day Workshops – Afternoon

This workshop will provide an introduction to our open-source ERP data analysis package, ERPLAB Toolbox, and especially on our brand-new ERPLAB Studio graphical user interface. The workshop will focus on basic functionality, including: Importing EEG data, re-referencing, filtering, artifact correction and rejection, assigning events to bins, averaging, plotting, scoring amplitudes and latencies, and quantifying data quality. It will demonstrate how to perform these steps in the GUI and also how to automate them with scripts. The workshop will frame this presentation in terms of the specific constraints involved in infant EEG/ERP research.

Participants should already have a basic knowledge of EEG and ERPs (which you can obtain by taking our free online course, Introduction to ERPs, which takes 3-4 hours to complete).