ct_example_annotations.md
Human‑readable explanation of every field in ct_example.json#
This document explains the meaning of each field in the Conscious Transfer Substrate Map v1 example instance.
It is written for clarity, not for formal specification — the schema remains the authoritative source.
1. Behavioral Layer#
The behavioral layer captures observable, repeatable patterns in how an agent learns and performs tasks.
1.1 Conditioning Models#
classical.cs_us_mapping#
Pairs of stimuli showing which conditioned stimulus (CS) predicts which unconditioned stimulus (US).
Example: “tone → airpuff” means the tone reliably precedes an airpuff.
classical.acquisition_rate#
How quickly the agent learns the CS–US association.
classical.extinction_rate#
How quickly the association fades when the CS is no longer followed by the US.
operant.reinforcement_schedule#
The rule governing when rewards are delivered (e.g., variable interval 30 seconds).
operant.learning_rate#
How strongly new outcomes update behavior.
operant.discount_factor#
How much future rewards matter relative to immediate ones.
1.2 Performance Metrics#
reaction_time_distribution#
A sample of reaction times (in milliseconds) from a standard task.
accuracy#
Proportion of correct responses.
error_types#
Categories of mistakes the agent makes (e.g., omissions, commissions).
speed_accuracy_tradeoff.slope / intercept#
How the agent balances speed vs. accuracy — a stable behavioral signature.
2. Cognitive Layer#
The cognitive layer captures task‑bound computational operators that survive RTT filtering.
2.1 Working Memory#
capacity#
How many items can be actively maintained at once.
decay_rate#
How quickly information fades without rehearsal.
refresh_rate#
How quickly the agent can refresh or cycle items to keep them active.
2.2 Attention#
selective_filter_strength#
How effectively irrelevant information is filtered out.
sustained_attention_stability#
How consistently attention is maintained over time.
switching_cost#
Extra time required to switch between tasks or rules.
2.3 Decision Models#
drift_diffusion.drift_rate#
How quickly evidence accumulates toward a decision.
drift_diffusion.boundary_separation#
How cautious or bold the decision threshold is.
drift_diffusion.non_decision_time#
Time spent on perception and motor execution, not decision‑making.
signal_detection.sensitivity_d_prime#
How well the agent distinguishes signal from noise.
signal_detection.criterion_c#
Bias toward saying “yes” or “no” when uncertain.
2.4 Learning Models#
reinforcement_learning.learning_rate#
How strongly new outcomes update value estimates.
reinforcement_learning.exploration_rate#
How often the agent tries new actions instead of exploiting known ones.
reinforcement_learning.reward_sensitivity#
How strongly rewards influence behavior.
3. Measurement Layer#
The measurement layer defines how the substrate is validated, not the substrate itself.
3.1 Psychometrics#
reliability_alpha#
Internal consistency of measurement instruments.
test_retest_stability#
How stable scores are across repeated testing.
factor_structure#
Latent dimensions extracted from performance (e.g., working memory, attention).
3.2 Neuropsych Tests#
task_battery.task_name#
Name of a standardized cognitive test.
task_battery.score#
Raw performance score.
task_battery.normative_z#
How the score compares to population norms (in standard deviations).
4. Anchoring Constraints#
These are biological correlates that meet RTT criteria — stable, traceable, and functionally meaningful.
4.1 Circuit Mappings#
region#
Brain region with a known functional role.
associated_function#
What cognitive/behavioral process the region supports.
lesion_effect#
What happens when the region is damaged — a functional anchor.
4.2 Neurophysiological Signatures#
task#
The task during which the signature appears.
frequency_band#
EEG/MEG frequency or ERP component.
amplitude#
Strength of the signal.
latency#
Time delay between stimulus and neural response.
4.3 Pharmacological Profiles#
agent#
Drug or compound with a known effect profile.
receptor_target#
Primary biological target (e.g., dopamine transporter).
effect_profile#
How the agent modulates behavior or cognitive parameters.
How to Use This File#
This annotation file is meant to:
- help researchers understand the meaning of each field
- support onboarding into the Conscious Transfer substrate
- clarify how the example instance relates to the schema
- maintain conceptual cleanliness without narrative drift
It is not a substitute for the schema — it is a guide to interpreting instances.