HBRAN-UIMS: Hierarchical Brain-like Recurrent Attention Networks and Unified Intelligence Metric Suite

HBRAN (Hierarchical Brain-like Recurrent Attention Network) is a novel cognitive neural architecture that mirrors hierarchical information processing in the human brain. The architecture includes: • Perception modules (BiLSTM-Attention layers)• Memory encoding (Variational Autoencoder)• Metacognitive decision making (Classification head)• Working memory (GRU layers)• Self-reflection (MLP)• Consciousness Extension Layer (CEL)• Unified Superfunction Layer (USFL) UIMS (Unified Intelligence Metric Suite) provides 37 evaluation metrics across 5 cognitive clusters:• A: Core Informational Competence• B: Adaptability & Generalization• C: Structural Cognition• D: Counterfactual & Predictive Reasoning• E: Metacognitive Intelligence This package includes:• Complete architecture implementations in Wolfram Language• 5 research notebooks with experimental results• Information neuroscience analysis (entropy, mutual information)• Clustering quality metrics (silhouette scores)• Full documentation and test suite