Synthetic Cognitive Augmentation Network
A comprehensive AI framework that mirrors human cognition through modular agents, psychometric alignment, and neuromorphic computing—creating personalized, energy-efficient cognitive support systems.
Five foundational advances in cognitive AI architecture and personalization
SCAN is not just one technology—it's a complete ecosystem of interconnected AI systems designed to augment human cognition. Think of it as a neural network that thinks like you do, learns from you, and helps you make better decisions.
Traditional AI systems are monolithic—one giant model trying to do everything. The human brain doesn't work that way. Your prefrontal cortex has specialized regions: one for planning, one for emotional regulation, one for risk assessment. SCAN mirrors this biological reality.
The ecosystem consists of four integrated components, each solving a specific challenge in building truly intelligent, personalized AI systems.
The foundation—a modular cognitive architecture with specialized agents that work like different regions of your brain
The intelligent layer—adaptive agents that learn from your feedback and personalize to your needs
The alignment tool—a questionnaire that maps your cognitive style to agent behaviors
The efficient engine—neuromorphic computing that runs AI with brain-like energy efficiency
SCAN is the architectural foundation—a modular AI system where specialized agents work together like regions of the human prefrontal cortex. Instead of one model doing everything poorly, five focused agents excel at specific cognitive tasks.
SCANUE is the evolution—where SCAN agents become truly adaptive. Each agent is fine-tuned for its cognitive function, learns from human feedback, and continuously improves. It's SCAN with a memory and the ability to grow.
SCANAQ is the personalization engine—a 36-item psychometric assessment that profiles your cognitive style across 8 dimensions. It tells SCANUE how to adapt its agents to match the way you think and decide.
STAC is the efficiency breakthrough—a neuromorphic architecture that combines transformers with spiking neural networks. It delivers SCAN's cognitive power with 3-4× less energy, making edge deployment possible.
First, you take the questionnaire. SCANAQ assesses your cognitive style across 8 dimensions. Then, each dimension configures a specific PFC agent. For example, your Planning score tells the DLPFC agent how you prefer to organize tasks, so it can provide responses that match your natural planning style. This personalization happens for all 8 dimensions across all 5 agents.
Each component plays a specific role, and together they create a cognitive augmentation system that's both powerful and personal.
Follow the 8-step process from assessment to personalized AI guidance
See how SCAN transforms decision-making across different domains with personalized cognitive support
The SCAN ecosystem is backed by peer-reviewed research across three comprehensive publications.
Introduces the core SCAN framework—modular AI agents modeled after prefrontal cortex regions. Demonstrates biological plausibility and introduces SCANUE, SCANAQ, and STAC as future components.
Deep dive into SCANAQ—the 36-item psychometric questionnaire that aligns AI agents to individual cognitive styles. Includes comprehensive scoring rubrics, PFC mapping, and design-based research via CAUSE.
Technical implementation of STAC—hybrid spiking neural network architecture. Details two approaches: V1 fine-tuning and V2 conversion, with planned validation on Intel Loihi neuromorphic hardware.
STAC's hybrid spiking neural network architecture delivers significant improvements over traditional artificial neural networks in energy efficiency, processing speed, and accuracy.
From healthcare to finance, education to edge computing—SCAN's modular, personalized approach transforms how AI supports human decision-making.
SCAN is an active research project. Whether you're a researcher, developer, or just curious about cognitive AI, there are multiple ways to engage with this work.
Explore the SCAN ecosystem through our published research papers and work in progress.
All SCAN components are open-source. Fork, extend, and build upon the ecosystem for your own research or applications.