import Std namespace Semantics.NeurodivergentPatternLUT /-- Pattern type enumeration -/ inductive PatternType where | neurotypical -- Standard cognitive pattern | autism -- Autism spectrum pattern | adhd -- ADHD pattern | combined -- Comorbid autism + ADHD | adaptive -- Adaptive pattern for specific task deriving BEq /-- Excitation/Inhibition ratio for autism pattern -/ structure EIRatio where ratio : UInt16 -- E/I ratio (neurotypical ≈ 1.0 = 65536, autism > 1.2) threshold : UInt16 -- Activation threshold (lower for autism) sensitivity : UInt16 -- Pattern detection sensitivity /-- Local/Long-Range connectivity ratio for autism pattern -/ structure ConnectivityRatio where localDensity : UInt16 -- Local connectivity density longRangeDensity : UInt16 -- Long-range connectivity density ratio : UInt16 -- κ = f_local / f_long (autism > 1.3) /-- Dopamine transport parameters for ADHD pattern -/ structure DopamineTransport where clearanceTime : UInt16 -- Dopamine clearance time (τ_clear) deficitFactor : UInt16 -- δ_adhd (0.2-0.4) baselineClearance : UInt16 -- τ_normal (neurotypical baseline) /-- Sensory filter threshold for autism pattern -/ structure SensoryThreshold where threshold : UInt16 -- Sensory gating threshold (θ) hyperSensitivity : UInt16 -- σ_hyper (0.3-0.6) baselineThreshold : UInt16 -- θ_neurotypical /-- Compensatory routing weight for neurodivergent patterns -/ structure CompensatoryRouting where standardWeight : UInt16 -- w_standard compensatoryWeight : UInt16 -- w_comp compensationFactor : UInt16 -- λ_comp (0.2-0.8) /-- Complete neurodivergent pattern configuration -/ structure NeurodivergentPattern where eiRatio : EIRatio connectivity : ConnectivityRatio dopamine : DopamineTransport sensory : SensoryThreshold routing : CompensatoryRouting patternType : PatternType /-- Inhabited instance for NeurodivergentPattern -/ instance : Inhabited NeurodivergentPattern := ⟨ { eiRatio := { ratio := 65536, threshold := 32768, sensitivity := 16384 }, connectivity := { localDensity := 32768, longRangeDensity := 32768, ratio := 65536 }, dopamine := { clearanceTime := 32768, deficitFactor := 0, baselineClearance := 32768 }, sensory := { threshold := 32768, hyperSensitivity := 0, baselineThreshold := 32768 }, routing := { standardWeight := 65536, compensatoryWeight := 65536, compensationFactor := 0 }, patternType := .neurotypical } ⟩ /-- Warm LUT for neurodivergent patterns -/ structure NeurodivergentPatternLUT where entries : Array NeurodivergentPattern -- Pre-computed pattern entries currentIndex : Nat -- Current LUT index size : Nat -- LUT size /-- Task type for adaptive pattern selection -/ inductive TaskType where | securityScan -- Fast threat detection | codeReview -- Detail-oriented analysis | sustainedFocus -- Attention maintenance | signalDetection -- Weak signal detection | faultTolerance -- Redundant routing deriving Repr, BEq /-- Initialize neurotypical baseline pattern -/ def mkNeurotypicalPattern : NeurodivergentPattern := { eiRatio := { ratio := 65536, threshold := 32768, sensitivity := 16384 }, connectivity := { localDensity := 32768, longRangeDensity := 32768, ratio := 65536 }, dopamine := { clearanceTime := 32768, deficitFactor := 0, baselineClearance := 32768 }, sensory := { threshold := 32768, hyperSensitivity := 0, baselineThreshold := 32768 }, routing := { standardWeight := 65536, compensatoryWeight := 65536, compensationFactor := 0 }, patternType := .neurotypical } /-- Initialize autism pattern (enhanced pattern detection) -/ def mkAutismPattern : NeurodivergentPattern := { eiRatio := { ratio := 78643, threshold := 20480, sensitivity := 24576 }, -- EIRatio: ξ=1.2, lower threshold connectivity := { localDensity := 40960, longRangeDensity := 24576, ratio := 106496 }, -- ConnectivityRatio: κ=1.6 dopamine := { clearanceTime := 32768, deficitFactor := 0, baselineClearance := 32768 }, sensory := { threshold := 20480, hyperSensitivity := 12288, baselineThreshold := 32768 }, -- SensoryThreshold: 40% lower routing := { standardWeight := 65536, compensatoryWeight := 98304, compensationFactor := 32768 }, -- CompensatoryRouting: λ=0.5 patternType := .autism } /-- Initialize ADHD pattern (attentional flexibility) -/ def mkADHDPattern : NeurodivergentPattern := { eiRatio := { ratio := 65536, threshold := 32768, sensitivity := 16384 }, connectivity := { localDensity := 32768, longRangeDensity := 32768, ratio := 65536 }, dopamine := { clearanceTime := 40960, deficitFactor := 19661, baselineClearance := 32768 }, -- DopamineTransport: 30% deficit sensory := { threshold := 32768, hyperSensitivity := 0, baselineThreshold := 32768 }, routing := { standardWeight := 65536, compensatoryWeight := 81920, compensationFactor := 16384 }, -- CompensatoryRouting: λ=0.25 patternType := .adhd } /-- Initialize combined autism + ADHD pattern -/ def mkCombinedPattern : NeurodivergentPattern := { eiRatio := { ratio := 78643, threshold := 20480, sensitivity := 24576 }, connectivity := { localDensity := 40960, longRangeDensity := 24576, ratio := 106496 }, dopamine := { clearanceTime := 40960, deficitFactor := 19661, baselineClearance := 32768 }, sensory := { threshold := 20480, hyperSensitivity := 12288, baselineThreshold := 32768 }, routing := { standardWeight := 65536, compensatoryWeight := 114688, compensationFactor := 49152 }, -- CompensatoryRouting: λ=0.75 patternType := .combined } /-- Initialize adaptive pattern for specific task -/ def mkAdaptivePattern (taskType : TaskType) : NeurodivergentPattern := match taskType with | .securityScan => { eiRatio := { ratio := 81920, threshold := 16384, sensitivity := 28672 }, -- EIRatio: High sensitivity connectivity := { localDensity := 36864, longRangeDensity := 28672, ratio := 81920 }, dopamine := { clearanceTime := 36864, deficitFactor := 13107, baselineClearance := 32768 }, sensory := { threshold := 16384, hyperSensitivity := 16384, baselineThreshold := 32768 }, routing := { standardWeight := 65536, compensatoryWeight := 65536, compensationFactor := 0 }, patternType := .adaptive } | .codeReview => { eiRatio := { ratio := 73728, threshold := 24576, sensitivity := 20480 }, connectivity := { localDensity := 45056, longRangeDensity := 20480, ratio := 114688 }, -- ConnectivityRatio: High local dopamine := { clearanceTime := 32768, deficitFactor := 0, baselineClearance := 32768 }, sensory := { threshold := 24576, hyperSensitivity := 8192, baselineThreshold := 32768 }, routing := { standardWeight := 65536, compensatoryWeight := 73728, compensationFactor := 8192 }, patternType := .adaptive } | .sustainedFocus => { eiRatio := { ratio := 65536, threshold := 32768, sensitivity := 16384 }, connectivity := { localDensity := 32768, longRangeDensity := 32768, ratio := 65536 }, dopamine := { clearanceTime := 49152, deficitFactor := 26214, baselineClearance := 32768 }, -- DopamineTransport: High deficit sensory := { threshold := 32768, hyperSensitivity := 0, baselineThreshold := 32768 }, routing := { standardWeight := 65536, compensatoryWeight := 65536, compensationFactor := 0 }, patternType := .adaptive } | .signalDetection => { eiRatio := { ratio := 65536, threshold := 32768, sensitivity := 16384 }, connectivity := { localDensity := 32768, longRangeDensity := 32768, ratio := 65536 }, dopamine := { clearanceTime := 32768, deficitFactor := 0, baselineClearance := 32768 }, sensory := { threshold := 12288, hyperSensitivity := 20480, baselineThreshold := 32768 }, -- SensoryThreshold: Very low threshold routing := { standardWeight := 65536, compensatoryWeight := 65536, compensationFactor := 0 }, patternType := .adaptive } | .faultTolerance => { eiRatio := { ratio := 65536, threshold := 32768, sensitivity := 16384 }, connectivity := { localDensity := 32768, longRangeDensity := 32768, ratio := 65536 }, dopamine := { clearanceTime := 32768, deficitFactor := 0, baselineClearance := 32768 }, sensory := { threshold := 32768, hyperSensitivity := 0, baselineThreshold := 32768 }, routing := { standardWeight := 65536, compensatoryWeight := 122880, compensationFactor := 57344 }, -- CompensatoryRouting: High compensation patternType := .adaptive } /-- Initialize warm LUT with pre-computed patterns -/ def initWarmLUT : NeurodivergentPatternLUT := { entries := #[mkNeurotypicalPattern, mkAutismPattern, mkADHDPattern, mkCombinedPattern], currentIndex := 0, size := 4 } /-- Load pattern from LUT by index -/ def loadPattern (lut : NeurodivergentPatternLUT) (index : Nat) : Option NeurodivergentPattern := if index < lut.size then some lut.entries[index]! else none /-- Load pattern by type (search LUT) -/ def loadPatternByType (lut : NeurodivergentPatternLUT) (pType : PatternType) : Option NeurodivergentPattern := let rec loop (i : Nat) : Option NeurodivergentPattern := if i >= lut.size then none else let pattern := lut.entries[i]! if pattern.patternType == pType then some pattern else loop (i + 1) loop 0 /-- Load adaptive pattern for specific task (not in LUT, compute on demand) -/ def loadAdaptivePattern (taskType : TaskType) : NeurodivergentPattern := mkAdaptivePattern taskType end Semantics.NeurodivergentPatternLUT