fibertract

Peripheral nervous system substrate for neuromorphic systems.

Twin primitive to neuropool. Where neuropool provides spiking neural substrate (brain tissue), fibertract provides connective tissue (peripheral nerves).

Core Concepts

Fiber tracts are labeled lines. The tract kind defines what signals on that tract mean. A signal on a nociceptive tract IS pain. A signal on a proprioceptive tract IS body position. Same data format, different qualia -- determined by which tract carries it.

Asymmetric encoding. Motor tracts (efferent, brain -> body) carry Signal -- the brain's native ternary format {polarity: i8, magnitude: u8}. Sensory tracts (afferent, body -> brain) carry i32 -- wide dynamic range with Weber-law quantization for biologically realistic discrimination.

Use-dependent adaptation. Tracts don't learn (no plasticity). They adapt: conductivity improves with use, jitter decreases with practice, strength grows with sustained effort, endurance builds over time. Idle tracts atrophy. This is connective tissue, not neural substrate.

Architecture

FiberBundle ("left_hand", "gaze", "vocal_tract", ...)
  +-- Vec<FiberTract>
        |-- MotorSkeletal   [Signal]  brain -> body (amplify)
        |-- Proprioceptive  [i32]     body -> brain (position)
        |-- NociceptiveFast [i32]     body -> brain (sharp pain)
        |-- Interoceptive   [i32]     body -> brain (fatigue)
        +-- ...

Fiber Types

Kind	Direction	Speed	Biological Analog	Carries
Proprioceptive	Afferent	Ia/Ib (fastest)	Position, extension, force	i32
Mechanoreceptive	Afferent	A-beta (fast)	Touch, pressure, texture	i32
NociceptiveFast	Afferent	A-delta (medium)	Sharp pain, temperature	i32
NociceptiveSlow	Afferent	C-fiber (slow)	Burning, aching, itch	i32
Interoceptive	Afferent	C-visceral (slowest)	Fatigue, metabolic state	i32
MotorSkeletal	Efferent	A-alpha (fastest)	Voluntary movement	Signal
MotorSpindle	Efferent	A-gamma (fast)	Muscle tone, reflexes	Signal

Physical Properties (all u8, no floats)

Property	Range	Meaning
Conductivity	0=severed, 255=perfect	Myelination quality
Jitter	0=clean, 255=overwhelmed	Transmission noise
Gain	128=unity, >128=amplify	Signal amplification
Sensitivity	0=numb, 255=hypersensitive	Detection threshold
Fatigue	0=fresh, 255=spent	Current exhaustion
Endurance	0=fragile, 255=tireless	Fatigue resistance
Strength	0=atrophied, 255=peak	Max force / acuity
Elasticity	0=sluggish, 255=instant	Signal tracking speed

Weber-Law Quantization

Sensory signals are quantized using Weber's law -- just-noticeable difference is proportional to stimulus magnitude:

Magnitude	Step Size	Example
0-49	5	You notice 1g vs 6g
50-199	10	You notice 100g vs 110g
200-999	15	You barely notice 500g vs 515g
1000+	25	You can't tell 2000g from 2020g

Transmission Pipeline

Motor (brain -> body):

Signal -> Gain -> Conductivity loss -> Fatigue -> Jitter -> Recruitment -> Elasticity -> Output

Sensory (body -> brain):

Raw i32 -> Weber quantize -> Gain -> Conductivity -> Fatigue -> Jitter -> Sensitivity -> Elasticity -> Output

Body Profiles

Pre-configured LimbProfile presets for biologically appropriate fiber bundles:

Profile	Motor Dim	Key Traits
hand	32	High dexterity, dense touch (64ch), low jitter
arm	16	Good strength, balanced sensory
leg	12	High strength/endurance, coarse motor, high proprioception
vocal_tract	24	Extreme precision, near-instant elasticity, minimal pain
gaze	12	Fastest response, cleanest signals, no pain fibers
torso	8	Core stability, high visceral awareness

Usage

use fibertract::{FiberBundle, FiberTract, FiberTractKind, LimbProfile};

// Build a hand from preset profile
let profile = LimbProfile::hand("left");
let mut hand = profile.build();

// Chemical modulation (affects entire bundle)
hand.apply_adrenaline(200);  // fight-or-flight: boost motor, gate pain

// Adapt over time (call each tick)
use fibertract::adapt::{adapt_bundle, AdaptationConfig};
let config = AdaptationConfig::default();
adapt_bundle(&mut hand, &config);

Pain System

Pain events carry perceived intensity (after chemical gating), onset sharpness, duration, and habituation state. The brain uses salience scoring to allocate attention:

use fibertract::{PainEvent, PainSource};

let event = PainEvent {
    bundle_name: "left_hand".into(),
    source: PainSource::Sharp,
    intensity: 200,
    onset: 220,
    duration_ticks: 5,
    habituating: false,
};

assert!(event.is_urgent());      // high intensity + high urgency source
assert_eq!(event.salience(), _);  // weighted score for attention

Features

• serde (default) -- enables serialization for all types via serde + serde_json

Dependencies

• ternary-signal -- the Signal type ({polarity, magnitude})
• log -- structured logging
• rand -- jitter noise generation

License

MIT OR Apache-2.0