Struct NeuromodNeuron 

pub struct NeuromodNeuron {
    pub v: f32,
    pub v_rest: f32,
    pub v_reset: f32,
    pub leak: f32,
    pub threshold: f32,
    pub gain: f32,
    pub weights: Vec<f32>,
    pub last_spike: bool,
}

Neuromodulatory Integrative Fixed-threshold (NIF) neuron.

This is a router-internal integration primitive for ChannelRouter, not a general-purpose neuron model — canonical neuron models (LIF, Izhikevich, Hodgkin-Huxley, GIF, FitzHugh-Nagumo, Lapicque) live in the separate neuromod crate, which synaptic-wiring intentionally does not depend on. See the crate-level docs for the full boundary rationale.

$V_{t+1} = V_t + (G \cdot I_{syn}) - \lambda(V_t - V_{rest})$ where $G$ is the modulation gain and $\lambda$ is the leak rate.

Fields

v: f32

Current membrane potential.

v_rest: f32

Resting membrane potential.

v_reset: f32

Reset potential after a spike.

leak: f32

Passive leak rate per timestep.

threshold: f32

Firing threshold.

gain: f32

Neuromodulatory gain (scales incoming stimulus).

weights: Vec<f32>

Synaptic weights — one per input channel.

last_spike: bool

Whether the neuron fired in the last timestep.

Implementations

impl NeuromodNeuron

pub fn new() -> Self

pub fn integrate(&mut self, stimulus: f32)

Advance neuron dynamics by one timestep.

The stimulus is scaled by the neuron’s current gain.

pub fn check_fire(&mut self) -> Option<f32>

Check if the neuron spikes. Resets V on fire.

pub fn set_gain(&mut self, new_gain: f32)

Update the modulation gain.

Trait Implementations

impl Clone for NeuromodNeuron

fn clone(&self) -> NeuromodNeuron

Returns a duplicate of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl Debug for NeuromodNeuron

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Default for NeuromodNeuron

fn default() -> Self

Returns the “default value” for a type.

impl<'de> Deserialize<'de> for NeuromodNeuron

where NeuromodNeuron: Default,

fn deserialize<__D>(__deserializer: __D) -> Result<Self, __D::Error>

where __D: Deserializer<'de>,

Deserialize this value from the given Serde deserializer.

impl Serialize for NeuromodNeuron

fn serialize<__S>(&self, __serializer: __S) -> Result<__S::Ok, __S::Error>

where __S: Serializer,

Serialize this value into the given Serde serializer.