Attention Management Architecture¶

This diagram provides a detailed view of the NeuroCognitive Architecture (NCA) attention management subsystem.

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graph TB
    classDef main fill:#1a1a1a,stroke:#555,color:#fff
    classDef component fill:#242424,stroke:#555,color:#fff
    classDef subcomponent fill:#2b2b2b,stroke:#555,color:#fff
    classDef attention fill:#203040,stroke:#555,color:#fff
    classDef sensory fill:#302030,stroke:#555,color:#fff
    classDef resource fill:#203020,stroke:#555,color:#fff
    classDef external fill:#302020,stroke:#555,color:#fff

    subgraph AttentionSystem["Attention Management System"]
        direction TB
        class AttentionSystem main

        subgraph CoreComponents["Core Attention Components"]
            direction TB
            class CoreComponents component

            subgraph FocusControl["Focus Control"]
                direction TB
                class FocusControl attention
                SpotlightManager[Attention<br>Spotlight] --- FocusShifting[Focus<br>Shifting]
                SustainedAttention[Sustained<br>Attention] --- DividedAttention[Divided<br>Attention]
                class SpotlightManager,FocusShifting,SustainedAttention,DividedAttention subcomponent
            end

            subgraph SensoryFiltering["Sensory Filtering"]
                direction TB
                class SensoryFiltering sensory
                BottomUpFiltering[Bottom-Up<br>Filtering] --- TopDownRegulation[Top-Down<br>Regulation]
                NoiseReduction[Noise<br>Reduction] --- SignalEnhancement[Signal<br>Enhancement]
                class BottomUpFiltering,TopDownRegulation,NoiseReduction,SignalEnhancement subcomponent
            end

            subgraph SalienceDetection["Salience Detection"]
                direction TB
                class SalienceDetection attention
                NoveltyDetector[Novelty<br>Detector] --- RelevanceEvaluator[Relevance<br>Evaluator]
                EmotionalSalience[Emotional<br>Salience] --- GoalSalience[Goal<br>Salience]
                class NoveltyDetector,RelevanceEvaluator,EmotionalSalience,GoalSalience subcomponent
            end

            subgraph AttentionAllocation["Attention Allocation"]
                direction TB
                class AttentionAllocation resource
                ResourceManager[Resource<br>Manager] --- PriorityQueue[Priority<br>Queue]
                DynamicAllocation[Dynamic<br>Allocation] --- CostBenefitAnalyzer[Cost-Benefit<br>Analyzer]
                class ResourceManager,PriorityQueue,DynamicAllocation,CostBenefitAnalyzer subcomponent
            end
        end

        subgraph SpecializedMechanisms["Specialized Mechanisms"]
            direction TB
            class SpecializedMechanisms component

            subgraph IntrusionControl["Intrusion Control"]
                direction TB
                class IntrusionControl attention
                DistractionBuffer[Distraction<br>Buffer] --- IntrusionDetector[Intrusion<br>Detector]
                ProtectionMechanisms[Protection<br>Mechanisms] --- IntrusionSuppression[Intrusion<br>Suppression]
                class DistractionBuffer,IntrusionDetector,ProtectionMechanisms,IntrusionSuppression subcomponent
            end

            subgraph ContextualModulation["Contextual Modulation"]
                direction TB
                class ContextualModulation attention
                ContextResolver[Context<br>Resolver] --- ContextualPriming[Contextual<br>Priming]
                ExpectationGenerator[Expectation<br>Generator] --- PredictiveAttention[Predictive<br>Attention]
                class ContextResolver,ContextualPriming,ExpectationGenerator,PredictiveAttention subcomponent
            end
        end

        subgraph AttentionalStates["Attentional States"]
            direction TB
            class AttentionalStates component
            VigilantState[Vigilant<br>State] --- FocusedState[Focused<br>State]
            DistractedState[Distracted<br>State] --- OverloadedState[Overloaded<br>State]
            DiffuseState[Diffuse<br>State] --- RestingState[Resting<br>State]
            class VigilantState,FocusedState,DistractedState,OverloadedState,DiffuseState,RestingState subcomponent
        end

        subgraph AttentionMonitoring["Attention Monitoring"]
            direction TB
            class AttentionMonitoring component
            PerformanceMonitor[Performance<br>Monitor] --- EfficiencyAnalyzer[Efficiency<br>Analyzer]
            FatigueDetector[Fatigue<br>Detector] --- AdaptiveRegulator[Adaptive<br>Regulator]
            class PerformanceMonitor,EfficiencyAnalyzer,FatigueDetector,AdaptiveRegulator subcomponent
        end
    end

    %% External connections
    ExecutiveControl[Executive<br>Control] --> FocusControl
    WorkingMemory[Working<br>Memory] --> ContextualModulation
    SensoryInput[Sensory<br>Input] --> SensoryFiltering
    HealthSystem[Health<br>System] --> AttentionMonitoring

    %% Internal connections
    SensoryFiltering --> SalienceDetection
    SalienceDetection --> FocusControl
    FocusControl --> AttentionAllocation
    AttentionMonitoring --> AttentionalStates
    AttentionalStates --> AttentionAllocation
    IntrusionControl --> SensoryFiltering
    IntrusionControl --> FocusControl
    ContextualModulation --> SalienceDetection
    ContextualModulation --> FocusControl

    %% Output connections
    AttentionAllocation --> ResourceOutput[Resource<br>Allocation]
    FocusControl --> AttentionOutput[Attention<br>Guidance]

    %% Node styling
    class ExecutiveControl,WorkingMemory,SensoryInput,HealthSystem,ResourceOutput,AttentionOutput external

Attention Management Architecture Components¶

The NCA attention management subsystem provides mechanisms for directing and controlling attention, allowing the system to focus on relevant information while filtering out distractions. It consists of the following key components:

Core Attention Components¶

Focus Control:
Attention Spotlight: Directs the focus of attention to specific information
Focus Shifting: Moves attention between different information sources
Sustained Attention: Maintains focus on a specific target over time
Divided Attention: Manages focus on multiple targets simultaneously
Sensory Filtering:
Bottom-Up Filtering: Automatic filtering based on sensory properties
Top-Down Regulation: Controlled filtering based on goals and expectations
Noise Reduction: Reduces irrelevant sensory information
Signal Enhancement: Enhances relevant sensory information
Salience Detection:
Novelty Detector: Identifies novel or unexpected information
Relevance Evaluator: Assesses information relevance to current goals
Emotional Salience: Detects emotionally significant information
Goal Salience: Detects information relevant to current goals
Attention Allocation:
Resource Manager: Manages the allocation of attention resources
Priority Queue: Prioritizes items for attention allocation
Dynamic Allocation: Adjusts allocation based on changing conditions
Cost-Benefit Analyzer: Evaluates the costs and benefits of attention allocation

Specialized Mechanisms¶

Intrusion Control:
Distraction Buffer: Temporarily holds potential distractions
Intrusion Detector: Detects unwanted information intrusions
Protection Mechanisms: Protects focused attention from disruption
Intrusion Suppression: Actively suppresses intrusive information
Contextual Modulation:
Context Resolver: Determines the current context for attention
Contextual Priming: Primes attention based on context
Expectation Generator: Generates expectations about upcoming information
Predictive Attention: Directs attention based on predictions

Attentional States¶

The system can be in various attentional states: - Vigilant State: Heightened awareness and alertness - Focused State: Concentrated attention on specific items - Distracted State: Attention disrupted by irrelevant information - Overloaded State: Excessive demands on attention resources - Diffuse State: Broadly distributed, unfocused attention - Resting State: Minimal attentional engagement

Attention Monitoring¶

Performance Monitor: Tracks the performance of the attention system
Efficiency Analyzer: Evaluates attention efficiency
Fatigue Detector: Detects attention fatigue
Adaptive Regulator: Regulates attention based on current conditions

External Connections¶

The attention management system connects with: - Executive Control: Provides top-down control of attention - Working Memory: Provides context for attention allocation - Sensory Input: Provides information for bottom-up attention - Health System: Provides health state for attention regulation

Output Connections¶

The attention management system produces: - Resource Allocation: Allocation of cognitive resources based on attention - Attention Guidance: Guidance for other systems based on attentional focus

The attention management system is designed to adaptively control information processing, enhancing relevant information and suppressing distractions in a way inspired by human attentional mechanisms.