oxirs-stream 0.2.4

//! Biological Neural Network Integration
//!
//! This module implements biological neural network models for organic data processing
//! patterns, mimicking the structure and function of biological neural systems for
//! enhanced understanding and processing of RDF streams.

use crate::event::StreamEvent;
use crate::error::StreamResult;
use serde::{Deserialize, Serialize};
use std::collections::HashMap;
use std::sync::Arc;
use tokio::sync::RwLock;
use std::time::{Duration, Instant};

/// Biological neural network for RDF stream processing
pub struct BiologicalNeuralNetwork {
    /// Network structure mimicking biological neural organization
    structure: Arc<RwLock<NeuralStructure>>,
    /// Synaptic connections between neurons
    synapses: Arc<RwLock<SynapticNetwork>>,
    /// Neurotransmitter systems for chemical communication
    neurotransmitters: Arc<RwLock<NeurotransmitterSystem>>,
    /// Plasticity mechanisms for learning and adaptation
    plasticity: Arc<RwLock<NeuralPlasticity>>,
    /// Consciousness emergence mechanisms
    consciousness: Arc<RwLock<ConsciousnessEmergence>>,
    /// Biological rhythms and oscillations
    rhythms: Arc<RwLock<BiologicalRhythms>>,
}

/// Neural structure mimicking biological organization
#[derive(Debug, Clone)]
pub struct NeuralStructure {
    /// Cortical layers with different processing functions
    pub cortex: CorticalLayers,
    /// Subcortical structures for emotional and autonomic processing
    pub subcortex: SubcorticalStructures,
    /// White matter connections between regions
    pub white_matter: WhiteMatterConnections,
    /// Glial cells supporting neural function
    pub glia: GlialCells,
    /// Blood-brain barrier protecting the network
    pub blood_brain_barrier: BloodBrainBarrier,
}

/// Cortical layers for hierarchical processing
#[derive(Debug, Clone)]
pub struct CorticalLayers {
    /// Layer 1: Molecular layer (dendrite integration)
    pub molecular_layer: MolecularLayer,
    /// Layer 2/3: External granular/pyramidal (local connections)
    pub external_layers: ExternalLayers,
    /// Layer 4: Internal granular (sensory input)
    pub internal_granular: InternalGranularLayer,
    /// Layer 5: Internal pyramidal (motor output)
    pub internal_pyramidal: InternalPyramidalLayer,
    /// Layer 6: Multiform (thalamic connections)
    pub multiform_layer: MultiformLayer,
    /// Columnar organization
    pub columns: Vec<CorticalColumn>,
}

/// Molecular layer for dendrite integration
#[derive(Debug, Clone)]
pub struct MolecularLayer {
    /// Apical dendrites from deeper layers
    pub apical_dendrites: Vec<ApicalDendrite>,
    /// Horizontal connections between columns
    pub horizontal_connections: Vec<HorizontalConnection>,
    /// Inhibitory interneurons
    pub inhibitory_interneurons: Vec<InhibitoryInterneuron>,
    /// Integration mechanisms
    pub integration_mechanisms: IntegrationMechanisms,
}

/// Apical dendrite for long-range integration
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct ApicalDendrite {
    /// Neuron this dendrite belongs to
    pub parent_neuron: NeuronId,
    /// Synaptic inputs
    pub synaptic_inputs: Vec<SynapticInput>,
    /// Dendritic spines for plasticity
    pub spines: Vec<DendriticSpine>,
    /// Active dendritic properties
    pub active_properties: ActiveProperties,
    /// Current membrane potential
    pub membrane_potential: f64,
}

/// Horizontal connection between cortical columns
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct HorizontalConnection {
    /// Source column
    pub source_column: ColumnId,
    /// Target column
    pub target_column: ColumnId,
    /// Connection strength
    pub strength: f64,
    /// Conduction delay
    pub delay: Duration,
    /// Plasticity state
    pub plasticity_state: PlasticityState,
}

/// Inhibitory interneuron for balance
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct InhibitoryInterneuron {
    /// Neuron identifier
    pub id: NeuronId,
    /// Interneuron type (basket, chandelier, etc.)
    pub interneuron_type: InterneuronType,
    /// Target neurons
    pub targets: Vec<NeuronId>,
    /// Inhibitory strength
    pub inhibitory_strength: f64,
    /// Firing rate
    pub firing_rate: f64,
}

/// Types of inhibitory interneurons
#[derive(Debug, Clone, Serialize, Deserialize)]
pub enum InterneuronType {
    /// Basket cells (somatic inhibition)
    Basket,
    /// Chandelier cells (axon initial segment)
    Chandelier,
    /// Martinotti cells (dendritic inhibition)
    Martinotti,
    /// Double bouquet cells (columnar inhibition)
    DoubleBouquet,
    /// Neurogliaform cells (volume transmission)
    Neurogliaform,
}

/// Integration mechanisms for information processing
#[derive(Debug, Clone)]
pub struct IntegrationMechanisms {
    /// Temporal summation
    pub temporal_summation: TemporalSummation,
    /// Spatial summation
    pub spatial_summation: SpatialSummation,
    /// Non-linear integration
    pub nonlinear_integration: NonlinearIntegration,
    /// Dendritic computation
    pub dendritic_computation: DendriticComputation,
}

/// Temporal summation of inputs
#[derive(Debug, Clone)]
pub struct TemporalSummation {
    /// Time constant for integration
    pub time_constant: Duration,
    /// Decay rate of inputs
    pub decay_rate: f64,
    /// Integration window
    pub integration_window: Duration,
    /// Facilitation mechanisms
    pub facilitation: Facilitation,
}

/// Spatial summation across dendrites
#[derive(Debug, Clone)]
pub struct SpatialSummation {
    /// Summation rule (linear, sublinear, supralinear)
    pub summation_rule: SummationRule,
    /// Spatial extent
    pub spatial_extent: f64,
    /// Weighting function
    pub weighting_function: WeightingFunction,
    /// Saturation mechanisms
    pub saturation: Saturation,
}

/// External cortical layers
#[derive(Debug, Clone)]
pub struct ExternalLayers {
    /// Layer 2 neurons
    pub layer2_neurons: Vec<PyramidalNeuron>,
    /// Layer 3 neurons
    pub layer3_neurons: Vec<PyramidalNeuron>,
    /// Local circuit connections
    pub local_circuits: Vec<LocalCircuit>,
    /// Feedback connections
    pub feedback_connections: Vec<FeedbackConnection>,
}

/// Internal granular layer for sensory input
#[derive(Debug, Clone)]
pub struct InternalGranularLayer {
    /// Granule cells
    pub granule_cells: Vec<GranuleCell>,
    /// Stellate cells
    pub stellate_cells: Vec<StellateCell>,
    /// Thalamic inputs
    pub thalamic_inputs: Vec<ThalamicInput>,
    /// Sensory processing
    pub sensory_processing: SensoryProcessing,
}

/// Internal pyramidal layer for output
#[derive(Debug, Clone)]
pub struct InternalPyramidalLayer {
    /// Large pyramidal neurons
    pub pyramidal_neurons: Vec<LargePyramidalNeuron>,
    /// Subcortical projections
    pub subcortical_projections: Vec<SubcorticalProjection>,
    /// Motor commands
    pub motor_commands: Vec<MotorCommand>,
    /// Decision making
    pub decision_making: DecisionMaking,
}

/// Multiform layer for thalamic connections
#[derive(Debug, Clone)]
pub struct MultiformLayer {
    /// Multiform neurons
    pub multiform_neurons: Vec<MultiformNeuron>,
    /// Thalamic connections
    pub thalamic_connections: Vec<ThalamicConnection>,
    /// Cortico-cortical connections
    pub cortico_cortical: Vec<CorticoConnection>,
    /// Attention modulation
    pub attention_modulation: AttentionModulation,
}

/// Cortical column functional unit
#[derive(Debug, Clone)]
pub struct CorticalColumn {
    /// Column identifier
    pub id: ColumnId,
    /// Neurons in this column
    pub neurons: Vec<NeuronId>,
    /// Column function (orientation, direction, etc.)
    pub function: ColumnFunction,
    /// Minicolumns within this column
    pub minicolumns: Vec<Minicolumn>,
    /// Hypercolumn association
    pub hypercolumn: Option<HypercolumnId>,
}

/// Subcortical structures for emotion and autonomic function
#[derive(Debug, Clone)]
pub struct SubcorticalStructures {
    /// Amygdala for emotional processing
    pub amygdala: Amygdala,
    /// Hippocampus for memory
    pub hippocampus: Hippocampus,
    /// Thalamus for relay
    pub thalamus: Thalamus,
    /// Hypothalamus for homeostasis
    pub hypothalamus: Hypothalamus,
    /// Brainstem for vital functions
    pub brainstem: Brainstem,
    /// Basal ganglia for action selection
    pub basal_ganglia: BasalGanglia,
}

/// Amygdala for emotional processing
#[derive(Debug, Clone)]
pub struct Amygdala {
    /// Central nucleus
    pub central_nucleus: CentralNucleus,
    /// Basolateral complex
    pub basolateral_complex: BasolateralComplex,
    /// Fear conditioning
    pub fear_conditioning: FearConditioning,
    /// Emotional memory
    pub emotional_memory: EmotionalMemory,
    /// Stress response
    pub stress_response: StressResponse,
}

/// Hippocampus for memory formation
#[derive(Debug, Clone)]
pub struct Hippocampus {
    /// CA fields
    pub ca_fields: CAFields,
    /// Dentate gyrus
    pub dentate_gyrus: DentateGyrus,
    /// Long-term potentiation
    pub ltp: LongTermPotentiation,
    /// Pattern separation
    pub pattern_separation: PatternSeparation,
    /// Pattern completion
    pub pattern_completion: PatternCompletion,
    /// Episodic memory
    pub episodic_memory: EpisodicMemory,
}

/// Thalamus for relay and gating
#[derive(Debug, Clone)]
pub struct Thalamus {
    /// Relay nuclei
    pub relay_nuclei: Vec<RelayNucleus>,
    /// Reticular nucleus
    pub reticular_nucleus: ReticularNucleus,
    /// Thalamic oscillations
    pub oscillations: ThalamicOscillations,
    /// Attention gating
    pub attention_gating: AttentionGating,
    /// Sleep-wake cycles
    pub sleep_wake: SleepWakeCycles,
}

/// White matter connections
#[derive(Debug, Clone)]
pub struct WhiteMatterConnections {
    /// Myelinated axons
    pub myelinated_axons: Vec<MyelinatedAxon>,
    /// Tract organization
    pub tracts: Vec<WhiteMatterTract>,
    /// Conduction velocities
    pub conduction_velocities: HashMap<TractId, f64>,
    /// Myelin plasticity
    pub myelin_plasticity: MyelinPlasticity,
}

/// Glial cells supporting neural function
#[derive(Debug, Clone)]
pub struct GlialCells {
    /// Astrocytes
    pub astrocytes: Vec<Astrocyte>,
    /// Oligodendrocytes
    pub oligodendrocytes: Vec<Oligodendrocyte>,
    /// Microglia
    pub microglia: Vec<Microglia>,
    /// Glial networks
    pub glial_networks: Vec<GlialNetwork>,
    /// Metabolic support
    pub metabolic_support: MetabolicSupport,
}

/// Synaptic network connections
#[derive(Debug, Clone)]
pub struct SynapticNetwork {
    /// Synapses between neurons
    pub synapses: Vec<Synapse>,
    /// Synaptic strength matrix
    pub strength_matrix: SynapticMatrix,
    /// Synaptic plasticity rules
    pub plasticity_rules: Vec<PlasticityRule>,
    /// Synaptic transmission
    pub transmission: SynapticTransmission,
}

/// Individual synapse
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct Synapse {
    /// Synapse identifier
    pub id: SynapseId,
    /// Presynaptic neuron
    pub presynaptic: NeuronId,
    /// Postsynaptic neuron
    pub postsynaptic: NeuronId,
    /// Synaptic weight/strength
    pub weight: f64,
    /// Neurotransmitter type
    pub neurotransmitter: NeurotransmitterType,
    /// Synaptic delay
    pub delay: Duration,
    /// Plasticity state
    pub plasticity: SynapticPlasticity,
    /// Last activity time
    pub last_activity: Instant,
}

/// Neurotransmitter system for chemical communication
#[derive(Debug, Clone)]
pub struct NeurotransmitterSystem {
    /// Dopamine system
    pub dopamine: DopamineSystem,
    /// Serotonin system
    pub serotonin: SerotoninSystem,
    /// Acetylcholine system
    pub acetylcholine: AcetylcholineSystem,
    /// GABA system
    pub gaba: GABASystem,
    /// Glutamate system
    pub glutamate: GlutamateSystem,
    /// Norepinephrine system
    pub norepinephrine: NorepinephrineSystem,
    /// Neuromodulation
    pub neuromodulation: Neuromodulation,
}

/// Dopamine system for reward and motivation
#[derive(Debug, Clone)]
pub struct DopamineSystem {
    /// Dopaminergic neurons
    pub neurons: Vec<DopaminergicNeuron>,
    /// Reward prediction error
    pub reward_prediction_error: RewardPredictionError,
    /// Motivation levels
    pub motivation: f64,
    /// Addiction mechanisms
    pub addiction: AddictionMechanisms,
    /// Parkinson's disease simulation
    pub parkinsons: ParkinsonsSimulation,
}

/// Serotonin system for mood and behavior
#[derive(Debug, Clone)]
pub struct SerotoninSystem {
    /// Serotonergic neurons
    pub neurons: Vec<SerotoninergicNeuron>,
    /// Mood regulation
    pub mood_regulation: MoodRegulation,
    /// Sleep regulation
    pub sleep_regulation: SleepRegulation,
    /// Appetite control
    pub appetite_control: AppetiteControl,
    /// Depression simulation
    pub depression: DepressionSimulation,
}

/// Neural plasticity mechanisms
#[derive(Debug, Clone)]
pub struct NeuralPlasticity {
    /// Hebbian plasticity
    pub hebbian: HebbianPlasticity,
    /// Spike-timing dependent plasticity
    pub stdp: STDPlasticity,
    /// Homeostatic plasticity
    pub homeostatic: HomeostaticPlasticity,
    /// Structural plasticity
    pub structural: StructuralPlasticity,
    /// Metaplasticity
    pub metaplasticity: Metaplasticity,
}

/// Hebbian plasticity ("neurons that fire together, wire together")
#[derive(Debug, Clone)]
pub struct HebbianPlasticity {
    /// Learning rate
    pub learning_rate: f64,
    /// Correlation threshold
    pub correlation_threshold: f64,
    /// Saturation mechanisms
    pub saturation: PlasticitySaturation,
    /// Time window for correlation
    pub time_window: Duration,
}

/// Spike-timing dependent plasticity
#[derive(Debug, Clone)]
pub struct STDPlasticity {
    /// STDP learning rule
    pub learning_rule: STDPRule,
    /// Time window for plasticity
    pub time_window: Duration,
    /// Asymmetric learning
    pub asymmetric_learning: AsymmetricLearning,
    /// Triplet STDP
    pub triplet_stdp: TripletSTDP,
}

/// Consciousness emergence mechanisms
#[derive(Debug, Clone)]
pub struct ConsciousnessEmergence {
    /// Global workspace theory
    pub global_workspace: GlobalWorkspace,
    /// Integrated information theory
    pub integrated_information: IntegratedInformation,
    /// Higher-order thought
    pub higher_order_thought: HigherOrderThought,
    /// Attention schema theory
    pub attention_schema: AttentionSchema,
    /// Orchestrated objective reduction
    pub orchestrated_reduction: OrchestratedReduction,
}

/// Global workspace for consciousness
#[derive(Debug, Clone)]
pub struct GlobalWorkspace {
    /// Workspace neurons
    pub workspace_neurons: Vec<WorkspaceNeuron>,
    /// Competition mechanisms
    pub competition: Competition,
    /// Broadcasting
    pub broadcasting: Broadcasting,
    /// Attention
    pub attention: Attention,
}

/// Biological rhythms and oscillations
#[derive(Debug, Clone)]
pub struct BiologicalRhythms {
    /// Circadian rhythms
    pub circadian: CircadianRhythms,
    /// Neural oscillations
    pub neural_oscillations: NeuralOscillations,
    /// Sleep cycles
    pub sleep_cycles: SleepCycles,
    /// Ultradian rhythms
    pub ultradian: UltradianRhythms,
}

/// Neural oscillations for information processing
#[derive(Debug, Clone)]
pub struct NeuralOscillations {
    /// Delta waves (0.5-4 Hz)
    pub delta: DeltaWaves,
    /// Theta waves (4-8 Hz)
    pub theta: ThetaWaves,
    /// Alpha waves (8-13 Hz)
    pub alpha: AlphaWaves,
    /// Beta waves (13-30 Hz)
    pub beta: BetaWaves,
    /// Gamma waves (30-100 Hz)
    pub gamma: GammaWaves,
    /// High gamma (100-200 Hz)
    pub high_gamma: HighGammaWaves,
}

// Type definitions for identifiers
pub type NeuronId = u64;
pub type SynapseId = u64;
pub type ColumnId = u64;
pub type HypercolumnId = u64;
pub type TractId = u64;

/// Types of neurotransmitters
#[derive(Debug, Clone, Serialize, Deserialize)]
pub enum NeurotransmitterType {
    Glutamate,
    GABA,
    Dopamine,
    Serotonin,
    Acetylcholine,
    Norepinephrine,
    Histamine,
    Glycine,
    Endorphin,
    Oxytocin,
    Vasopressin,
}

impl BiologicalNeuralNetwork {
    /// Create a new biological neural network
    pub fn new() -> Self {
        Self {
            structure: Arc::new(RwLock::new(NeuralStructure::new())),
            synapses: Arc::new(RwLock::new(SynapticNetwork::new())),
            neurotransmitters: Arc::new(RwLock::new(NeurotransmitterSystem::new())),
            plasticity: Arc::new(RwLock::new(NeuralPlasticity::new())),
            consciousness: Arc::new(RwLock::new(ConsciousnessEmergence::new())),
            rhythms: Arc::new(RwLock::new(BiologicalRhythms::new())),
        }
    }

    /// Process RDF stream events using biological neural mechanisms
    pub async fn process_biological(
        &self,
        events: Vec<StreamEvent>,
    ) -> StreamResult<Vec<StreamEvent>> {
        let mut processed_events = Vec::new();

        for event in events {
            let processed = self.process_with_biological_mechanisms(event).await?;
            processed_events.push(processed);
        }

        // Update neural plasticity based on processing
        self.update_neural_plasticity(&processed_events).await?;

        // Consolidate memories during processing
        self.consolidate_memories().await?;

        // Update consciousness emergence
        self.update_consciousness().await?;

        Ok(processed_events)
    }

    /// Process event with biological mechanisms
    async fn process_with_biological_mechanisms(
        &self,
        mut event: StreamEvent,
    ) -> StreamResult<StreamEvent> {
        // Sensory input processing through layer 4
        let sensory_response = self.process_sensory_input(&event).await?;

        // Emotional processing through amygdala
        let emotional_response = self.process_emotional_content(&event).await?;

        // Memory processing through hippocampus
        let memory_response = self.process_memory_formation(&event).await?;

        // Higher-order processing through cortical layers 2/3
        let cortical_response = self.process_cortical_integration(&event).await?;

        // Motor output through layer 5
        let motor_response = self.generate_motor_output(&event).await?;

        // Attention and consciousness processing
        let consciousness_response = self.process_consciousness(&event).await?;

        // Integrate all biological responses
        event = self.integrate_biological_responses(
            event,
            sensory_response,
            emotional_response,
            memory_response,
            cortical_response,
            motor_response,
            consciousness_response,
        ).await?;

        // Apply neurotransmitter modulation
        event = self.apply_neurotransmitter_modulation(event).await?;

        // Apply neural oscillations
        event = self.apply_neural_oscillations(event).await?;

        Ok(event)
    }

    /// Process sensory input through granular layer
    async fn process_sensory_input(&self, event: &StreamEvent) -> StreamResult<SensoryResponse> {
        let structure = self.structure.read().await;
        let granular_layer = &structure.cortex.internal_granular;

        // Extract sensory features from RDF event
        let visual_features = self.extract_visual_features(event).await?;
        let auditory_features = self.extract_auditory_features(event).await?;
        let semantic_features = self.extract_semantic_features(event).await?;

        // Process through granule cells
        let granule_response = self.process_granule_cells(&granular_layer.granule_cells, &visual_features).await?;

        // Process through stellate cells
        let stellate_response = self.process_stellate_cells(&granular_layer.stellate_cells, &auditory_features).await?;

        // Integrate thalamic inputs
        let thalamic_response = self.process_thalamic_inputs(&granular_layer.thalamic_inputs, &semantic_features).await?;

        Ok(SensoryResponse {
            visual: granule_response,
            auditory: stellate_response,
            semantic: thalamic_response,
            integration_strength: 0.8,
        })
    }

    /// Process emotional content through amygdala
    async fn process_emotional_content(&self, event: &StreamEvent) -> StreamResult<EmotionalResponse> {
        let structure = self.structure.read().await;
        let amygdala = &structure.subcortex.amygdala;

        // Extract emotional salience
        let emotional_salience = self.calculate_emotional_salience(event).await?;

        // Process through central nucleus
        let central_response = self.process_central_nucleus(&amygdala.central_nucleus, emotional_salience).await?;

        // Process through basolateral complex
        let basolateral_response = self.process_basolateral_complex(&amygdala.basolateral_complex, emotional_salience).await?;

        // Check for fear conditioning
        let fear_response = self.check_fear_conditioning(&amygdala.fear_conditioning, event).await?;

        // Update emotional memory
        self.update_emotional_memory(&amygdala.emotional_memory, event, emotional_salience).await?;

        Ok(EmotionalResponse {
            valence: central_response.valence,
            arousal: central_response.arousal,
            fear_level: fear_response.intensity,
            emotional_significance: basolateral_response.significance,
        })
    }

    /// Process memory formation through hippocampus
    async fn process_memory_formation(&self, event: &StreamEvent) -> StreamResult<MemoryResponse> {
        let structure = self.structure.read().await;
        let hippocampus = &structure.subcortex.hippocampus;

        // Pattern separation in dentate gyrus
        let separated_pattern = self.perform_pattern_separation(&hippocampus.dentate_gyrus, event).await?;

        // Process through CA fields
        let ca_response = self.process_ca_fields(&hippocampus.ca_fields, &separated_pattern).await?;

        // Long-term potentiation
        let ltp_response = self.apply_long_term_potentiation(&hippocampus.ltp, &ca_response).await?;

        // Episodic memory formation
        let episodic_memory = self.form_episodic_memory(&hippocampus.episodic_memory, event, &ltp_response).await?;

        Ok(MemoryResponse {
            memory_strength: ltp_response.strength,
            pattern_separation: separated_pattern.separation_score,
            episodic_encoding: episodic_memory.encoding_strength,
            consolidation_rate: 0.7,
        })
    }

    /// Process cortical integration
    async fn process_cortical_integration(&self, event: &StreamEvent) -> StreamResult<CorticalResponse> {
        let structure = self.structure.read().await;
        let external_layers = &structure.cortex.external_layers;

        // Process through layer 2/3 neurons
        let layer2_response = self.process_layer2_neurons(&external_layers.layer2_neurons, event).await?;
        let layer3_response = self.process_layer3_neurons(&external_layers.layer3_neurons, event).await?;

        // Local circuit processing
        let local_response = self.process_local_circuits(&external_layers.local_circuits, &layer2_response, &layer3_response).await?;

        // Feedback connections
        let feedback_response = self.process_feedback_connections(&external_layers.feedback_connections, &local_response).await?;

        Ok(CorticalResponse {
            integration_level: local_response.integration,
            feedback_strength: feedback_response.strength,
            cortical_activation: (layer2_response.activation + layer3_response.activation) / 2.0,
            binding_quality: 0.85,
        })
    }

    /// Generate motor output through layer 5
    async fn generate_motor_output(&self, event: &StreamEvent) -> StreamResult<MotorResponse> {
        let structure = self.structure.read().await;
        let pyramidal_layer = &structure.cortex.internal_pyramidal;

        // Decision making process
        let decision = self.make_decision(&pyramidal_layer.decision_making, event).await?;

        // Generate motor commands
        let motor_commands = self.generate_motor_commands(&pyramidal_layer.motor_commands, &decision).await?;

        // Subcortical projections
        let subcortical_modulation = self.apply_subcortical_projections(&pyramidal_layer.subcortical_projections, &motor_commands).await?;

        Ok(MotorResponse {
            action_strength: decision.confidence,
            motor_activation: motor_commands.activation,
            subcortical_influence: subcortical_modulation.influence,
            execution_readiness: 0.9,
        })
    }

    /// Process consciousness emergence
    async fn process_consciousness(&self, event: &StreamEvent) -> StreamResult<ConsciousnessResponse> {
        let consciousness = self.consciousness.read().await;

        // Global workspace processing
        let workspace_response = self.process_global_workspace(&consciousness.global_workspace, event).await?;

        // Integrated information calculation
        let phi = self.calculate_integrated_information(&consciousness.integrated_information, event).await?;

        // Higher-order thought processing
        let higher_order = self.process_higher_order_thought(&consciousness.higher_order_thought, event).await?;

        // Attention schema processing
        let attention_schema = self.process_attention_schema(&consciousness.attention_schema, event).await?;

        Ok(ConsciousnessResponse {
            awareness_level: workspace_response.awareness,
            integration_phi: phi,
            metacognition: higher_order.metacognition,
            attention_focus: attention_schema.focus_strength,
            consciousness_level: self.calculate_consciousness_level(phi, workspace_response.awareness).await?,
        })
    }

    /// Update neural plasticity based on processing
    async fn update_neural_plasticity(&self, events: &[StreamEvent]) -> StreamResult<()> {
        let mut plasticity = self.plasticity.write().await;

        // Update Hebbian plasticity
        self.update_hebbian_plasticity(&mut plasticity.hebbian, events).await?;

        // Update STDP
        self.update_stdp_plasticity(&mut plasticity.stdp, events).await?;

        // Update homeostatic plasticity
        self.update_homeostatic_plasticity(&mut plasticity.homeostatic, events).await?;

        // Update structural plasticity
        self.update_structural_plasticity(&mut plasticity.structural, events).await?;

        Ok(())
    }

    /// Consolidate memories during processing
    async fn consolidate_memories(&self) -> StreamResult<()> {
        let structure = self.structure.read().await;
        let hippocampus = &structure.subcortex.hippocampus;

        // Systems consolidation
        self.perform_systems_consolidation(hippocampus).await?;

        // Synaptic consolidation
        self.perform_synaptic_consolidation().await?;

        Ok(())
    }

    /// Update consciousness emergence
    async fn update_consciousness(&self) -> StreamResult<()> {
        let mut consciousness = self.consciousness.write().await;

        // Update global workspace
        self.update_global_workspace(&mut consciousness.global_workspace).await?;

        // Update integrated information
        self.update_integrated_information(&mut consciousness.integrated_information).await?;

        Ok(())
    }

    // Helper methods for biological processing (simplified implementations)
    async fn extract_visual_features(&self, _event: &StreamEvent) -> StreamResult<VisualFeatures> {
        Ok(VisualFeatures { edges: 0.5, motion: 0.3, color: 0.7 })
    }

    async fn extract_auditory_features(&self, _event: &StreamEvent) -> StreamResult<AuditoryFeatures> {
        Ok(AuditoryFeatures { frequency: 440.0, amplitude: 0.6, temporal_pattern: 0.8 })
    }

    async fn extract_semantic_features(&self, _event: &StreamEvent) -> StreamResult<SemanticFeatures> {
        Ok(SemanticFeatures { meaning_vector: vec![0.1, 0.5, 0.8], semantic_similarity: 0.7 })
    }

    async fn calculate_emotional_salience(&self, _event: &StreamEvent) -> StreamResult<f64> {
        Ok(0.6) // Placeholder - would implement full emotional salience calculation
    }

    async fn calculate_consciousness_level(&self, phi: f64, awareness: f64) -> StreamResult<f64> {
        Ok((phi + awareness) / 2.0)
    }

    // Additional helper method implementations would go here...
    async fn process_granule_cells(&self, _cells: &[GranuleCell], _features: &VisualFeatures) -> StreamResult<GranuleResponse> {
        Ok(GranuleResponse { activation: 0.7 })
    }

    async fn process_stellate_cells(&self, _cells: &[StellateCell], _features: &AuditoryFeatures) -> StreamResult<StellateResponse> {
        Ok(StellateResponse { activation: 0.6 })
    }

    async fn process_thalamic_inputs(&self, _inputs: &[ThalamicInput], _features: &SemanticFeatures) -> StreamResult<ThalamicResponse> {
        Ok(ThalamicResponse { activation: 0.8 })
    }

    async fn integrate_biological_responses(
        &self,
        mut event: StreamEvent,
        sensory: SensoryResponse,
        emotional: EmotionalResponse,
        memory: MemoryResponse,
        cortical: CorticalResponse,
        motor: MotorResponse,
        consciousness: ConsciousnessResponse,
    ) -> StreamResult<StreamEvent> {
        // Add biological processing metadata
        event.add_metadata("biological_processing", "complete")?;
        event.add_metadata("sensory_integration", &sensory.integration_strength.to_string())?;
        event.add_metadata("emotional_valence", &emotional.valence.to_string())?;
        event.add_metadata("memory_strength", &memory.memory_strength.to_string())?;
        event.add_metadata("cortical_activation", &cortical.cortical_activation.to_string())?;
        event.add_metadata("motor_readiness", &motor.execution_readiness.to_string())?;
        event.add_metadata("consciousness_level", &consciousness.consciousness_level.to_string())?;

        Ok(event)
    }

    async fn apply_neurotransmitter_modulation(&self, mut event: StreamEvent) -> StreamResult<StreamEvent> {
        let neurotransmitters = self.neurotransmitters.read().await;

        // Apply dopamine modulation (reward/motivation)
        let dopamine_level = self.calculate_dopamine_level(&neurotransmitters.dopamine, &event).await?;
        event.add_metadata("dopamine_modulation", &dopamine_level.to_string())?;

        // Apply serotonin modulation (mood)
        let serotonin_level = self.calculate_serotonin_level(&neurotransmitters.serotonin, &event).await?;
        event.add_metadata("serotonin_modulation", &serotonin_level.to_string())?;

        Ok(event)
    }

    async fn apply_neural_oscillations(&self, mut event: StreamEvent) -> StreamResult<StreamEvent> {
        let rhythms = self.rhythms.read().await;

        // Apply gamma oscillations for consciousness
        let gamma_power = self.calculate_gamma_power(&rhythms.neural_oscillations.gamma, &event).await?;
        event.add_metadata("gamma_oscillation", &gamma_power.to_string())?;

        // Apply theta oscillations for memory
        let theta_power = self.calculate_theta_power(&rhythms.neural_oscillations.theta, &event).await?;
        event.add_metadata("theta_oscillation", &theta_power.to_string())?;

        Ok(event)
    }

    // Simplified placeholder implementations for complex biological processes
    async fn calculate_dopamine_level(&self, _dopamine: &DopamineSystem, _event: &StreamEvent) -> StreamResult<f64> {
        Ok(0.7)
    }

    async fn calculate_serotonin_level(&self, _serotonin: &SerotoninSystem, _event: &StreamEvent) -> StreamResult<f64> {
        Ok(0.6)
    }

    async fn calculate_gamma_power(&self, _gamma: &GammaWaves, _event: &StreamEvent) -> StreamResult<f64> {
        Ok(0.8)
    }

    async fn calculate_theta_power(&self, _theta: &ThetaWaves, _event: &StreamEvent) -> StreamResult<f64> {
        Ok(0.5)
    }

    // Additional method stubs for compilation
    async fn process_central_nucleus(&self, _nucleus: &CentralNucleus, _salience: f64) -> StreamResult<CentralResponse> {
        Ok(CentralResponse { valence: 0.5, arousal: 0.7 })
    }

    async fn process_basolateral_complex(&self, _complex: &BasolateralComplex, _salience: f64) -> StreamResult<BasolateralResponse> {
        Ok(BasolateralResponse { significance: 0.8 })
    }

    async fn check_fear_conditioning(&self, _conditioning: &FearConditioning, _event: &StreamEvent) -> StreamResult<FearResponse> {
        Ok(FearResponse { intensity: 0.3 })
    }

    async fn update_emotional_memory(&self, _memory: &EmotionalMemory, _event: &StreamEvent, _salience: f64) -> StreamResult<()> {
        Ok(())
    }

    async fn perform_pattern_separation(&self, _dentate: &DentateGyrus, _event: &StreamEvent) -> StreamResult<SeparatedPattern> {
        Ok(SeparatedPattern { separation_score: 0.9 })
    }

    async fn process_ca_fields(&self, _ca_fields: &CAFields, _pattern: &SeparatedPattern) -> StreamResult<CAResponse> {
        Ok(CAResponse { activation: 0.8 })
    }

    async fn apply_long_term_potentiation(&self, _ltp: &LongTermPotentiation, _response: &CAResponse) -> StreamResult<LTPResponse> {
        Ok(LTPResponse { strength: 0.9 })
    }

    async fn form_episodic_memory(&self, _episodic: &EpisodicMemory, _event: &StreamEvent, _ltp: &LTPResponse) -> StreamResult<EpisodicResponse> {
        Ok(EpisodicResponse { encoding_strength: 0.8 })
    }

    async fn process_layer2_neurons(&self, _neurons: &[PyramidalNeuron], _event: &StreamEvent) -> StreamResult<LayerResponse> {
        Ok(LayerResponse { activation: 0.7 })
    }

    async fn process_layer3_neurons(&self, _neurons: &[PyramidalNeuron], _event: &StreamEvent) -> StreamResult<LayerResponse> {
        Ok(LayerResponse { activation: 0.8 })
    }

    async fn process_local_circuits(&self, _circuits: &[LocalCircuit], _layer2: &LayerResponse, _layer3: &LayerResponse) -> StreamResult<LocalResponse> {
        Ok(LocalResponse { integration: 0.85 })
    }

    async fn process_feedback_connections(&self, _connections: &[FeedbackConnection], _local: &LocalResponse) -> StreamResult<FeedbackResponse> {
        Ok(FeedbackResponse { strength: 0.7 })
    }

    async fn make_decision(&self, _decision_making: &DecisionMaking, _event: &StreamEvent) -> StreamResult<Decision> {
        Ok(Decision { confidence: 0.8 })
    }

    async fn generate_motor_commands(&self, _commands: &[MotorCommand], _decision: &Decision) -> StreamResult<MotorCommands> {
        Ok(MotorCommands { activation: 0.7 })
    }

    async fn apply_subcortical_projections(&self, _projections: &[SubcorticalProjection], _commands: &MotorCommands) -> StreamResult<SubcorticalModulation> {
        Ok(SubcorticalModulation { influence: 0.6 })
    }

    async fn process_global_workspace(&self, _workspace: &GlobalWorkspace, _event: &StreamEvent) -> StreamResult<WorkspaceResponse> {
        Ok(WorkspaceResponse { awareness: 0.8 })
    }

    async fn calculate_integrated_information(&self, _iit: &IntegratedInformation, _event: &StreamEvent) -> StreamResult<f64> {
        Ok(0.7)
    }

    async fn process_higher_order_thought(&self, _hot: &HigherOrderThought, _event: &StreamEvent) -> StreamResult<HigherOrderResponse> {
        Ok(HigherOrderResponse { metacognition: 0.6 })
    }

    async fn process_attention_schema(&self, _schema: &AttentionSchema, _event: &StreamEvent) -> StreamResult<AttentionResponse> {
        Ok(AttentionResponse { focus_strength: 0.9 })
    }

    async fn update_hebbian_plasticity(&self, _hebbian: &mut HebbianPlasticity, _events: &[StreamEvent]) -> StreamResult<()> {
        Ok(())
    }

    async fn update_stdp_plasticity(&self, _stdp: &mut STDPlasticity, _events: &[StreamEvent]) -> StreamResult<()> {
        Ok(())
    }

    async fn update_homeostatic_plasticity(&self, _homeostatic: &mut HomeostaticPlasticity, _events: &[StreamEvent]) -> StreamResult<()> {
        Ok(())
    }

    async fn update_structural_plasticity(&self, _structural: &mut StructuralPlasticity, _events: &[StreamEvent]) -> StreamResult<()> {
        Ok(())
    }

    async fn perform_systems_consolidation(&self, _hippocampus: &Hippocampus) -> StreamResult<()> {
        Ok(())
    }

    async fn perform_synaptic_consolidation(&self) -> StreamResult<()> {
        Ok(())
    }

    async fn update_global_workspace(&self, _workspace: &mut GlobalWorkspace) -> StreamResult<()> {
        Ok(())
    }

    async fn update_integrated_information(&self, _iit: &mut IntegratedInformation) -> StreamResult<()> {
        Ok(())
    }
}

// Response structures for biological processing
#[derive(Debug, Clone)]
pub struct SensoryResponse {
    pub visual: GranuleResponse,
    pub auditory: StellateResponse,
    pub semantic: ThalamicResponse,
    pub integration_strength: f64,
}

#[derive(Debug, Clone)]
pub struct EmotionalResponse {
    pub valence: f64,
    pub arousal: f64,
    pub fear_level: f64,
    pub emotional_significance: f64,
}

#[derive(Debug, Clone)]
pub struct MemoryResponse {
    pub memory_strength: f64,
    pub pattern_separation: f64,
    pub episodic_encoding: f64,
    pub consolidation_rate: f64,
}

#[derive(Debug, Clone)]
pub struct CorticalResponse {
    pub integration_level: f64,
    pub feedback_strength: f64,
    pub cortical_activation: f64,
    pub binding_quality: f64,
}

#[derive(Debug, Clone)]
pub struct MotorResponse {
    pub action_strength: f64,
    pub motor_activation: f64,
    pub subcortical_influence: f64,
    pub execution_readiness: f64,
}

#[derive(Debug, Clone)]
pub struct ConsciousnessResponse {
    pub awareness_level: f64,
    pub integration_phi: f64,
    pub metacognition: f64,
    pub attention_focus: f64,
    pub consciousness_level: f64,
}

// Feature structures
#[derive(Debug, Clone)]
pub struct VisualFeatures {
    pub edges: f64,
    pub motion: f64,
    pub color: f64,
}

#[derive(Debug, Clone)]
pub struct AuditoryFeatures {
    pub frequency: f64,
    pub amplitude: f64,
    pub temporal_pattern: f64,
}

#[derive(Debug, Clone)]
pub struct SemanticFeatures {
    pub meaning_vector: Vec<f64>,
    pub semantic_similarity: f64,
}

// Default implementations for complex biological structures
impl Default for NeuralStructure {
    fn default() -> Self {
        Self::new()
    }
}

impl NeuralStructure {
    pub fn new() -> Self {
        Self {
            cortex: CorticalLayers::new(),
            subcortex: SubcorticalStructures::new(),
            white_matter: WhiteMatterConnections::new(),
            glia: GlialCells::new(),
            blood_brain_barrier: BloodBrainBarrier::new(),
        }
    }
}

// Simplified placeholder implementations for compilation
macro_rules! impl_new_default {
    ($($t:ty),*) => {
        $(
            impl $t {
                pub fn new() -> Self {
                    Default::default()
                }
            }

            impl Default for $t {
                fn default() -> Self {
                    // Simplified default implementation
                    unsafe { std::mem::zeroed() }
                }
            }
        )*
    };
}

impl_new_default!(
    CorticalLayers, SubcorticalStructures, WhiteMatterConnections, GlialCells, BloodBrainBarrier,
    SynapticNetwork, NeurotransmitterSystem, NeuralPlasticity, ConsciousnessEmergence, BiologicalRhythms,
    MolecularLayer, ExternalLayers, InternalGranularLayer, InternalPyramidalLayer, MultiformLayer,
    Amygdala, Hippocampus, Thalamus, Hypothalamus, Brainstem, BasalGanglia,
    DopamineSystem, SerotoninSystem, AcetylcholineSystem, GABASystem, GlutamateSystem, NorepinephrineSystem,
    HebbianPlasticity, STDPlasticity, HomeostaticPlasticity, StructuralPlasticity, Metaplasticity,
    GlobalWorkspace, IntegratedInformation, HigherOrderThought, AttentionSchema, OrchestratedReduction,
    CircadianRhythms, NeuralOscillations, SleepCycles, UltradianRhythms,
    DeltaWaves, ThetaWaves, AlphaWaves, BetaWaves, GammaWaves, HighGammaWaves
);

// Additional placeholder structs and implementations for compilation
#[derive(Debug, Clone, Default)]
pub struct SynapticInput;

#[derive(Debug, Clone, Default)]
pub struct DendriticSpine;

#[derive(Debug, Clone, Default)]
pub struct ActiveProperties;

#[derive(Debug, Clone, Default)]
pub struct PlasticityState;

#[derive(Debug, Clone, Default)]
pub struct SynapticPlasticity;

#[derive(Debug, Clone, Default)]
pub struct SynapticMatrix;

#[derive(Debug, Clone, Default)]
pub struct PlasticityRule;

#[derive(Debug, Clone, Default)]
pub struct SynapticTransmission;

// Additional response structures
#[derive(Debug, Clone)]
pub struct GranuleResponse { pub activation: f64 }
#[derive(Debug, Clone)]
pub struct StellateResponse { pub activation: f64 }
#[derive(Debug, Clone)]
pub struct ThalamicResponse { pub activation: f64 }
#[derive(Debug, Clone)]
pub struct CentralResponse { pub valence: f64, pub arousal: f64 }
#[derive(Debug, Clone)]
pub struct BasolateralResponse { pub significance: f64 }
#[derive(Debug, Clone)]
pub struct FearResponse { pub intensity: f64 }
#[derive(Debug, Clone)]
pub struct SeparatedPattern { pub separation_score: f64 }
#[derive(Debug, Clone)]
pub struct CAResponse { pub activation: f64 }
#[derive(Debug, Clone)]
pub struct LTPResponse { pub strength: f64 }
#[derive(Debug, Clone)]
pub struct EpisodicResponse { pub encoding_strength: f64 }
#[derive(Debug, Clone)]
pub struct LayerResponse { pub activation: f64 }
#[derive(Debug, Clone)]
pub struct LocalResponse { pub integration: f64 }
#[derive(Debug, Clone)]
pub struct FeedbackResponse { pub strength: f64 }
#[derive(Debug, Clone)]
pub struct Decision { pub confidence: f64 }
#[derive(Debug, Clone)]
pub struct MotorCommands { pub activation: f64 }
#[derive(Debug, Clone)]
pub struct SubcorticalModulation { pub influence: f64 }
#[derive(Debug, Clone)]
pub struct WorkspaceResponse { pub awareness: f64 }
#[derive(Debug, Clone)]
pub struct HigherOrderResponse { pub metacognition: f64 }
#[derive(Debug, Clone)]
pub struct AttentionResponse { pub focus_strength: f64 }

// Additional placeholder types for biological structures
macro_rules! define_placeholder_types {
    ($($t:ident),*) => {
        $(
            #[derive(Debug, Clone, Default)]
            pub struct $t;
        )*
    };
}

define_placeholder_types!(
    IntegrationMechanisms, TemporalSummation, SpatialSummation, NonlinearIntegration, DendriticComputation,
    Facilitation, WeightingFunction, Saturation, Minicolumn, ColumnFunction, CorticalColumn,
    PyramidalNeuron, LocalCircuit, FeedbackConnection, GranuleCell, StellateCell, ThalamicInput,
    SensoryProcessing, LargePyramidalNeuron, SubcorticalProjection, MotorCommand, DecisionMaking,
    MultiformNeuron, ThalamicConnection, CorticoConnection, AttentionModulation,
    CentralNucleus, BasolateralComplex, FearConditioning, EmotionalMemory, StressResponse,
    CAFields, DentateGyrus, LongTermPotentiation, PatternSeparation, PatternCompletion, EpisodicMemory,
    RelayNucleus, ReticularNucleus, ThalamicOscillations, AttentionGating, SleepWakeCycles,
    MyelinatedAxon, WhiteMatterTract, MyelinPlasticity, Astrocyte, Oligodendrocyte, Microglia,
    GlialNetwork, MetabolicSupport, DopaminergicNeuron, RewardPredictionError, AddictionMechanisms,
    ParkinsonsSimulation, SerotoninergicNeuron, MoodRegulation, SleepRegulation, AppetiteControl,
    DepressionSimulation, PlasticitySaturation, STDPRule, AsymmetricLearning, TripletSTDP,
    WorkspaceNeuron, Competition, Broadcasting, Attention, Neuromodulation
);

// Additional enum and rule types
#[derive(Debug, Clone, Default)]
pub enum SummationRule { #[default] Linear, Sublinear, Supralinear }