Data & Analytics

FedDOSE federated brain dFC with site decomposition.

Exploiting Symmetry in Quantum Reservoir Computing (QRC) methodology — observable-orbit completion aligns encoding, dynamics, measurement, and readout so symmetry-induced inductive bias is visible in the measured feature map; validated on spin-ring, real-weather cyclic forecasting, and IBM hardware.

Exclusion statistics as a thermodynamic resource in quantum heat engines — using particle statistics interpolation (fermion/boson/anyon) as a design parameter for quantum thermal machines. From arXiv:2606.19310.

Excitation-driven data generation and distributed control optimization for building thermal systems and district heating networks. Combines BuilDyn framework (arXiv:2605.29849) and distributed NMPC with ADMM (arXiv:2605.29841).

Energy-based dynamical systems framework for neurocomputation, learning, and optimization. Unifies Hopfield networks, Boltzmann machines, modern EBMs, and equilibrium propagation under a single energy landscape formulation. Covers gradient flow dynamics, attractor analysis, contrastive learning, and biologically-plausible learning rules. Activation: energy-based models, EBMs, neural dynamics, Hopfield networks, energy landscape, attractor dynamics, gradient flow, equilibrium propagation, cont...

Embodied Virtual Reality feedback reshapes neural representations to support continuous 3D motor imagery decoding in brain-computer interfaces. First systematic investigation of embodied VR feedback during real-time 3D virtual limb control. Use when: (1) Designing VR-based BCI systems, (2) Studying motor imagery neural representations, (3) Comparing VR vs screen feedback modalities, (4) Investigating longitudinal BCI training effects. Activation: embodied VR feedback, motor imagery BCI, 3D vi...

Theoretical analysis of effective target shift in online learning and methods to correct for it. Explains why online learning struggles under distributional shift and how to characterize the relationship between online and offline learning. Activation triggers: online learning, target shift, distributional shift, online vs offline learning, sequential learning theory

Effective rank methodology for predicting quantum data encoding performance. Uses feature map effective rank as a threshold criterion to accelerate the search for high-performing QML encodings. Activation: effective rank encoding, feature map rank QML, encoding performance prediction, quantum encoding predictor, QML encoding ranking.

Open-source platform cataloguing 791 public neurophysiological datasets (EEG, MEG, iEEG, EMG, fNIRS) with automatic format repair, BIDS compliance, and machine learning integration.

EEG-based tinnitus biomarker identification methodology with cross-dataset generalization. Uses microstate analysis and Koopman operator analysis via DMD to extract robust neural signatures. Focuses on Koopman eigenvalue magnitude for oscillation stability. Applications: clinical diagnostics, cross-platform tinnitus detection. Triggers: tinnitus biomarker, EEG microstate, Koopman EEG, cross-dataset generalization

Deep learning framework for objective consciousness level measurement using multi-dimensional transcranial electrical stimulation (TES) with EEG. Combines TES-evoked brain responses with CNN classification for bedside-awareness assessment. Activation triggers: eeg tes, consciousness measurement, transcranial stimulation, brain state classification, awareness assessment, disorder of consciousness.

Structure-Guided Diffusion Model (SGDM v3) for EEG-based visual cognition reconstruction with enhanced cross-subject generalization. Combines structurally supervised VAE, spatiotemporal EEG encoder with contrastive learning, and ControlNet-guided diffusion for high-fidelity image reconstruction from brain signals.

Skill for analyzing brain networks using noninvasive electrophysiological measurements (EEG/MEG) based on arXiv:2607.17602v1 'Exploring Brain Networks Using Noninvasive Electrophysiological Measurements: Methods and Applications'

EEG-based Hopfield energy landscape analysis for quantifying brain network stability during emotional processing (happy/sad face tasks). Activation: emotion energy landscape, brain stability, happy sad face EEG, Hopfield emotion.

EEG-conditioned framework for reconstructing dynamic fMRI as continuous neural sequences with high spatial fidelity and temporal coherence at cortical-vertex level. Incorporates null-space intermediate-frame reconstruction for handling sampling irregularities.

Eccentricity-Constrained CNN Training methodology for adaptive visual information coding around the visual field using egocentric data

Eccentricity-constrained CNN training on egocentric video reveals adaptive, task-aligned information coding across the visual field, with fovea-preferred models advantaged for face and object tasks and periphery-preferred models favored in scene-selective cortex.

Dynamical quantum optimal transport (QOT) methodology based on Benamou-Brenier formulation for computing geodesics between positive semidefinite matrices. Use when: computing quantum state transport distances, solving quantum chemistry problems via optimal transport, analyzing numerical convergence of QOT distances, or implementing interior-point methods for quantum density matrix geodesics. Activation: quantum optimal transport, dynamical QOT, Benamou-Brenier, quantum chemistry optimal trans...

Gaussian-equivalent process methodology for analyzing nonlinear noise in recurrent neural circuits using Ornstein-Uhlenbeck noise matching and lognormal moment closure. Activation: mean field, nonlinear noise, recurrent networks, OU process.

Dynamic Gated Neuron (DGN) - Biologically plausible gating mechanism for Spiking Neural Networks via dynamic membrane conductance modulation. Enables selective input filtering and adaptive noise suppression. Activation triggers: dynamic gated neuron, DGN, SNN gating, conductance-based SNN, robust spiking neural network, biological gating.

Statistical-mechanical theory of dreaming in memories.

Distribution-valued brain connectivity analysis using vector quantiles instead of scalar edge weights. Based on Mhanna, Achard, Petersen (2026, HAL). Use when building brain connectivity graphs from fMRI/EEG, improving connectome classification, or representing higher-order connectivity statistics. Activation: distribution-valued brain connectivity, graph brain representation, fMRI connectome classification, voxel clustering, brain network edges, vector quantile connectivity.

Discounted Model Predictive Control (MPC) and infinite-horizon optimal control under plant-model mismatch. Unified framework for stability and suboptimality analysis with robustness guarantees. Use for: robust MPC, plant-model mismatch handling, discounted optimal control, stability analysis, surrogate model control. Activation: discounted MPC, plant-model mismatch, robust MPC, infinite-horizon control, suboptimality analysis.

DINA (Dual-Tower Image-Neural Alignment) framework for interpretable contrastive analysis of V1 population activity. Aligns visual stimuli and V1 responses in shared latent space at intermediate feature map level. Activation: DINA, V1 population activity, image-neural alignment, contrastive framework, calcium imaging decoding, visual computation.