MEG and source imaging
Conventional SQUID-MEG, preprocessing, and source-level interpretation.
Direct acquisition, head-position tracking, MEG-MRI coregistration, MaxFilter, temporal signal-space separation, and Fast-VESTAL source maps.
Clinical neuroscience and translational neurotechnology
I build measurement systems, analysis pipelines, and software that make neuroscience usable.
Robert J. Gougelet is a researcher and developer whose work spans conventional MEG acquisition and preprocessing, Fast-VESTAL source imaging, cerebellar fMRI, EEG analysis, fNIRS methods, and clinical systems development. The work focuses on rigorous tools people can actually use.
MEG
fMRI
EEG
fNIRS
Clinical systems
Teaching
What I bring
My background is strongest where technical rigor, experimental design, and real-world use cases meet.
Cerebellar fMRI
Ecological task design with full preprocessing and GLM workflows.
Naturalistic aviation paradigms, SPM8 preprocessing, and cerebellar interpretation grounded in the first-author 2020 paper.
fNIRS systems
fnirs-webpipe
Open-source, cross-platform, client-side fNIRS analysis that runs in any modern browser, including offline. Features include NIRx ingestion, rapid visualization, event-aware preprocessing, cleaning, filtering, and protocol export.
Clinical systems
Patient-resource and care-coordination software built for real use.
Clinical analytics and web applications shaped by population management, care coordination, and practice operations.
Applied sensing
EEG, EMG, neurofeedback, and human-systems measurement.
Applied sensing work across NASA Langley, JPL, USF, and NHRC established a practical foundation in physiological measurement.
Teaching
Laboratory development, statistics, data science, and human-computer interaction.
University teaching across neurophysiology, psychology, statistics, and technical lab formats with hands-on student support.
Principle
I care about systems that are technically strong, visually clear, and honest about what they measure. That means work that can survive scrutiny and still feel good to use.
Selected proof points
- Research Lead and Software Developer, Human Neurophysiology Methods Lab Hands-on fNIRS methods, reproducible workflows, and quantitative analysis teaching.
- Clinical Systems Developer, Xcelsior Health Clinical analytics and patient-resource web applications used for practice operations.
- NSF EAPSI / JSPS fellow and PI Direct funding for a multimodal neuroimaging project with Daniel E. Callan as co-PI.
- First-author cerebellar aviation fMRI paper Naturalistic task design, full SPM8 analysis, and a publication that bridges cognition, cerebellum, and performance.
Selected outputs
Representative projects across neuroimaging, fNIRS, and clinical systems.
Multimodal neuroimaging
MEG source work in autism and connectivity analysis
Acquired and preprocessed MEG on an Elekta/Neuromag Vectorview system, generated Fast-VESTAL source maps, and created MEG-derived ROIs for downstream fMRI interpretation.
fNIRS methods
Human Neurophysiology Methods Lab and browser-based fNIRS analysis
Built and taught around a local-first analysis workflow that supports NIRx ingestion, channel-wise visualization, preprocessing, and reloadable analysis protocols.
Clinical technology
Health-system software shaped by real operations
Clinical analytics and patient-resource applications developed in a stack that includes Node.js, Vue 3, Tailwind, Google Apps Script, and Google Cloud.
Cerebellar fMRI
Aviation pursuit study with full SPM8 preprocessing
Designed the X-Plane task, wrote control software, and led the full fMRI pipeline for the first-author study on cerebellum, basal ganglia, and cortex.