Cognitive Computing

BCI Signal Processing

Ingest raw EEG, ECoG, and other neural interface signals. VectorScaleDB converts multi-channel brain recordings into temporal vectors with per-channel feature extraction and automatic artifact rejection.

Signal Ingestion

EEG and ECoG to vectors

Multi-channel BCI signals are ingested as temporal vectors. Each channel contributes features — power spectral density, band power ratios, event-related potentials — to a unified observation vector that captures the cognitive state at each timestamp.

Configurable channel-to-dimension mapping
Automatic artifact rejection for eye blinks and movement
Support for high-density electrode arrays (256+ channels)
Session-based recording with start/stop lifecycle

Feature Extraction

Spectral and temporal features

Built-in feature extractors compute band power (delta, theta, alpha, beta, gamma), spectral entropy, coherence between channel pairs, and event-related synchronization. Features are computed in real time during ingestion.

Five standard EEG frequency bands
Cross-channel coherence matrices
Sliding window with configurable overlap
Compression ratios of 100x+ for resting-state recordings

Cognitive Regimes

Automatically detect transitions between cognitive states. VectorScaleDB's drift-based regime detection identifies focus, fatigue, learning onset, and cognitive load shifts from the temporal evolution of BCI feature vectors.

Fatigue Detection

Drowsiness and attention decay

Rising theta/alpha ratios and decreasing beta power trigger fatigue regime transitions. Alerts fire before performance degrades, enabling proactive intervention in safety-critical applications.

Learning Curves

Skill acquisition tracking

Track how neural patterns consolidate during learning. Change-point analysis on compressed BCI segments detects when a subject transitions from exploration to mastery — the moment a skill becomes automatic.

Cognitive Load

Task difficulty adaptation

Monitor cognitive load in real time through frontal theta power and parietal alpha suppression. Adaptive systems can scale task difficulty based on detected load, maintaining optimal engagement.

Consent Gate

Every modification to neural data requires explicit consent. The consent gate is not optional — it is a mandatory pipeline stage that validates authorization, checks safety bounds, and logs every decision before any write proceeds.

Safety-Critical

Mandatory authorization checks

The consent gate sits between the API layer and the storage engine. No BCI data modification bypasses it. Each operation requires a valid consent token that specifies the subject, the action scope, and the expiration window.

Per-subject consent tokens with cryptographic signatures
Action-scoped permissions (read, write, transfer, delete)
Automatic expiration with mandatory re-consent
Full audit trail of consent decisions

Bounds Checking

Safety parameter enforcement

Stimulation parameters, skill transfer amplitudes, and feedback loop gains are validated against configurable safety bounds before execution. Out-of-bounds operations are rejected with detailed explanations.

Configurable safety thresholds per operation type
Rate limiting on stimulation frequency
Cumulative exposure tracking per session
Emergency stop capability with immediate effect

Skill Distillation

Extract transferable skill patterns from expert neural recordings. The multi-stage distillation pipeline compresses hours of BCI data into compact skill templates that capture the essential neural signatures of expertise.

Pipeline

Multi-stage skill extraction

Raw BCI recordings are filtered, segmented by cognitive regime, clustered by behavioral similarity, and compressed into skill templates. Each stage reduces dimensionality while preserving the discriminative features that define the skill.

Artifact rejection and normalization
Regime-aware segmentation
Cross-session temporal alignment
Template compression to transferable format

Transfer

Cross-subject skill sharing

Distilled skill templates can be applied to new subjects through the consent-gated transfer pipeline. The system adapts templates to the target subject's baseline neural patterns, accounting for individual neuroanatomical differences.

Consent required from both source and target subjects
Baseline calibration before transfer
Gradual application with continuous monitoring
Rollback capability if adverse effects detected

Immersive Reality

Spatial computing support for VR/AR/XR applications. Frustum-aware queries return only the data visible to the user, while haptic feedback and spatial audio channels are synchronized with BCI-driven cognitive state.

Frustum Culling

View-dependent data streaming

Define a 3D viewing frustum and receive only the entities within it. Level-of-detail scaling reduces resolution with distance, minimizing bandwidth for immersive applications running at 90+ fps.

Haptics

Tactile feedback integration

Haptic feedback channels are stored as temporal vectors alongside visual and audio data. BCI-driven cognitive state modulates haptic intensity — reducing feedback during cognitive overload.

Spatial Audio

3D audio positioning

Spatial audio source positions are tracked as temporal vectors with head-related transfer function metadata. Audio rendering adapts to the user's position and orientation in real time.