# norse.torch.functional¶

## Encoding¶

 constant_current_lif_encode Encodes input currents as fixed (constant) voltage currents, and simulates the spikes that occur during a number of timesteps/iterations (seq_length). gaussian_rbf A gaussian radial basis kernel that calculates the radial basis given a distance value (distance between $$x$$ and a data value $$x'$$, or $$\|\mathbf{x} - \mathbf{x'}\|^2$$ below). euclidean_distance Simple euclidean distance metric. population_encode Encodes a set of input values into population codes, such that each singular input value is represented by a list of numbers (typically calculated by a radial basis kernel), whose length is equal to the out_features. poisson_encode Encodes a tensor of input values, which are assumed to be in the range [0,1] into a tensor of one dimension higher of binary values, which represent input spikes. poisson_encode_step Encodes a tensor of input values, which are assumed to be in the range [0,1] into a tensor of binary values, which represent input spikes. signed_poisson_encode Encodes a tensor of input values, which are assumed to be in the range [-1,1] into a tensor of one dimension higher of binary values, which represent input spikes. signed_poisson_encode_step Creates a poisson distributed signed spike vector, when spike_latency_lif_encode Encodes an input value by the time the first spike occurs. spike_latency_encode For all neurons, remove all but the first spike. lif_current_encoder Computes a single euler-integration step of a leaky integrator. lif_adex_current_encoder Computes a single euler-integration step of an adaptive exponential LIF neuron-model adapted from http://www.scholarpedia.org/article/Adaptive_exponential_integrate-and-fire_model. lif_ex_current_encoder Computes a single euler-integration step of a leaky integrator adapted from https://neuronaldynamics.epfl.ch/online/Ch5.S2.html.

## Logical¶

 logical_and Computes a logical and provided x and y are bitvectors. logical_xor Computes a logical xor provided x and y are bitvectors. logical_or Computes a logical or provided x and y are bitvectors. muller_c Computes the muller-c element next state provided x_1 and x_2 are bitvectors and y_prev is the previous state. posedge_detector Determines whether a transition from 0 to 1 has occured providing that z and z_prev are bitvectors

## Regularization¶

 regularize_step Takes one step for a regularizer that aggregates some information (based on the spike_accumulator function), which is pushed forward and returned for future inclusion in an error term. spike_accumulator A spike accumulator that aggregates spikes and returns the total sum as an integer. voltage_accumulator A spike accumulator that aggregates membrane potentials over time.

## Threshold functions¶

 heaviside A heaviside step function that truncates numbers <= 0 to 0 and everything else to 1. heavi_erfc_fn heavi_tanh_fn logistic_fn heavi_circ_fn circ_dist_fn triangle_fn super_fn

## Temporal operations¶

 lift Creates a lifted version of the given activation function which applies the activation function in the temporal domain.

## Neuron models¶

### Integrate-and-fire (IAF)¶

 IAFParameters Parametrization of a LIF neuron IAFFeedForwardState State of a feed forward IAF neuron iaf_feed_forward_step

### Izhikevich¶

 IzhikevichParameters Parametrization of av Izhikevich neuron IzhikevichSpikingBehavior Spiking behavior of a Izhikevich neuron tonic_spiking Spiking behavior of a Izhikevich neuron tonic_bursting Spiking behavior of a Izhikevich neuron phasic_spiking Spiking behavior of a Izhikevich neuron phasic_bursting Spiking behavior of a Izhikevich neuron mixed_mode Spiking behavior of a Izhikevich neuron spike_frequency_adaptation Spiking behavior of a Izhikevich neuron class_1_exc Spiking behavior of a Izhikevich neuron class_2_exc Spiking behavior of a Izhikevich neuron spike_latency Spiking behavior of a Izhikevich neuron subthreshold_oscillation Spiking behavior of a Izhikevich neuron resonator Spiking behavior of a Izhikevich neuron izhikevich_feed_forward_step

### Leaky integrator¶

 LIParameters Parameters of a leaky integrator LIState State of a leaky-integrator li_feed_forward_step

### Leaky integrate-and-fire (LIF)¶

 LIFParameters Parametrization of a LIF neuron LIFFeedForwardState State of a feed forward LIF neuron lif_feed_forward_step Computes a single euler-integration step for a lif neuron-model. lif_feed_forward_adjoint_step Implementes a single euler forward and adjoint backward step of a leaky integrate and fire neuron with current based exponential synapses. lif_feed_forward_adjoint_step_sparse Implementes a single euler forward and adjoint backward step of a leaky integrate and fire neuron with current based exponential synapses.

### LIF, conductance based¶

 CobaLIFParameters Parameters of conductance based LIF neuron. CobaLIFFeedForwardState State of a conductance based feed forward LIF neuron. coba_lif_feed_forward_step Euler integration step for a conductance based LIF neuron.

 LIFAdExParameters Parametrization of an Adaptive Exponential Leaky Integrate and Fire neuron LIFAdExFeedForwardState State of a feed forward LIFAdEx neuron lif_adex_feed_forward_step Computes a single euler-integration step of an adaptive exponential LIF neuron-model adapted from http://www.scholarpedia.org/article/Adaptive_exponential_integrate-and-fire_model. lif_adex_current_encoder Computes a single euler-integration step of an adaptive exponential LIF neuron-model adapted from http://www.scholarpedia.org/article/Adaptive_exponential_integrate-and-fire_model.

### LIF, exponential¶

 LIFExParameters Parametrization of an Exponential Leaky Integrate and Fire neuron LIFExFeedForwardState State of a feed forward LIFEx neuron lif_ex_feed_forward_step Computes a single euler-integration step of an exponential LIF neuron-model adapted from https://neuronaldynamics.epfl.ch/online/Ch5.S2.html. lif_ex_current_encoder Computes a single euler-integration step of a leaky integrator adapted from https://neuronaldynamics.epfl.ch/online/Ch5.S2.html.

### LIF, multicompartmental (MC)¶

 lif_mc_feed_forward_step Computes a single euler-integration feed forward step of a LIF multi-compartment neuron-model. lif_mc_refrac_feed_forward_step

### LIF, refractory¶

 LIFRefracParameters Parameters of a LIF neuron with absolute refractory period. LIFRefracFeedForwardState State of a feed forward LIF neuron with absolute refractory period. lif_refrac_feed_forward_step Computes a single euler-integration step of a feed forward lif_refrac_feed_forward_adjoint_step Implementes a single euler forward and adjoint backward step of a leaky integrate and fire neuron with current based exponential synapses and a refractory period.

### Long short-term memory (LSNN)¶

 LSNNParameters Parameters of an LSNN neuron LSNNFeedForwardState Integration state kept for a lsnn module lsnn_feed_forward_step Euler integration step for LIF Neuron with threshold adaptation. lsnn_feed_forward_adjoint_step Implementes a single euler forward and adjoint backward step of a lif neuron with adaptive threshhold and current based exponential synapses.

## Plasticity models¶

### Spike-time dependent plasticity (STDP)¶

 STDPSensorParameters Parameters of an STDP sensor as it is used for event driven plasticity rules. STDPSensorState State of an event driven STDP sensor. stdp_sensor_step Event driven STDP rule.

### Tsodyks-Markram timing-dependent plasticity (TDP)¶

 TsodyksMakramParameters Parameters of the Tsodyks-Makram Model TsodyksMakramState State of the Tsodyks-Makram Model, note that we are tracking the input current state separately. stp_step Euler integration step for Tsodyks Makram model of STP.