“Web-Native Neuroviz: Three.js + WebSockets for Live Brain Streams Spectrcyde Rev2” “Web-Native Neuroviz: Three.js + WebSockets for Live Brain Streams Spectrcyde Rev2,” builds on the initial draft by adding quantitative performance metrics (60 FPS, ~20ms…
Critique and Proposal for BYOL Adaptation to RF Signals Building on your work across “RL-Driven RF Neuromodulation,” “Hybrid Super-Voxel Segmentation,” “Structured Gradients for Neuro–Saliency Under RF Stimulation,” and “DINO v2 for Self-Supervised RF Representations,” adapting…
Saliency maps derived from input gradients are popular for visualizing and controlling model responses [1,2, 3]. In RF neuromodulation or analogous control settings, however, raw gradients often exhibit speckled,high-frequency artifacts that are hard to actuate.…
We propose a hybrid super-voxel segmentation pipeline that combines soft memberships from fuzzyc-means (FCM) with spatial regularization via graph cuts on a region adjacency graph (RAG). Our hybridachieves 0.70 mean IoU at 42 fps (synthetic),…
The reference ‘@book{Bezdek1981FCM, title = {Pattern Recognition with Fuzzy Objective Function Algorithms}, author = {James C. Bezdek}, year = {1981}, publisher = {Springer}}’ is highly relevant to your paper “Hybrid Super-Voxel Segmentation: Graph Cuts +…
We present a controlled bake-off betweentwo widely used Wi-Fi CSI capture stacks—the IntelCSI Tool and Nexmon—for neural RF sensing. Wecompare subcarrier resolution, signal stability, andsetup cost, and offer platform guidance grounded inreproducible scripts and auto-press…
Functional magnetic resonance imaging (fMRI) provideshigh-resolution, voxel-wise measurements of brain activity, butacquiring large-scale fMRI datasets is expensive, immobile,and time-consuming. At the same time, commodity wirelessdevices continually capture channel state information (CSI)— a rich, multi-dimensional signal…
🧠 Reinforcement Learning Takes the Wheel: A Smarter Approach to RF Neuromodulation Neuromodulation—using techniques like radiofrequency (RF) energy to precisely tune brain activity—holds immense promise for treating neurological conditions. However, achieving effective and safe closed-loop…
Introduction In a recent paper, Benjamin James Gilbert proposes a simple yet effective set of band-aware labeling heuristics (BAR) for RF datasets. These rules map center frequency and spectral cues to labels like GSM, Wi-Fi,…
We study multi-source context fusion for signal classification from software-defined radio (SDR) streams. We exploreenriching SDR features with contemporaneous, public-domaintelemetry from astrophysical (e.g., observatory scheduling andenvironment), orbital (e.g., satellite attitude/visibility windows),and high-energy physics (e.g., collider…