About Canvascope Research
Canvascope Research is an interdisciplinary lab developing computational tools for neuroscience and rehabilitation research. We focus on methods that estimate stimulus-evoked cortical response patterns, map those estimates onto interpretable brain regions and functional networks, and support careful comparison with downstream clinical signals. Our emphasis is on transparent methods, prospective validation, and tools that support researcher and clinician workflows without overstating what current models can establish.
Featured Research Projects
CortexBridge
Active ResearchCortexBridge is a research and decision-support platform built around multimodal brain-encoding models, including TRIBE v2, to estimate stimulus-evoked fMRI/BOLD response patterns from audio, video, and text. These predicted responses are summarized across cortical regions and functional networks so researchers can inspect how candidate stimuli may engage the cortex.
Our current use case is asynchronous pre-screening: using predicted cortical engagement patterns to rank stimuli for further review before they are evaluated in practice. In ILF and SCP neurofeedback settings, the working hypothesis is that these fMRI-derived estimates may help narrow stimulus selection and should be prospectively validated against clinician ratings, EEG features, and rehabilitation outcomes. CortexBridge is therefore positioned as one signal among many in researcher and clinician workflows, not as a direct EEG model, real-time clinical control system, or predictor of individual therapeutic efficacy.
Exploratory Programs
Exploratory PhaseAdditional research programs are being scoped around computational tools for rehabilitation and measurement. Details will be shared when the technical claims, validation plan, and study design are mature enough to publish.
Collaborate With Us
We welcome collaborators across machine learning, neuroscience, neuroimaging, EEG, rehabilitation medicine, and clinical advisory work who value careful validation and clear scientific claims. If you are interested in contributing to study design, model evaluation, data partnerships, or translational tooling, we would like to hear from you.
Start a Research Conversation