Stochastic neuron implementation with exponential probability. More...

#include <neuron/implementations/neuron_impl.h>
#include <spin1_api.h>
#include <debug.h>
#include <random.h>
#include <stdfix-full-iso.h>
#include <common/maths-util.h>
#include <neuron/neuron_recording.h>
#include <neuron/current_sources/current_source_impl.h>
#include <neuron/current_sources/current_source.h>
#include "stoc_exp_common.h"

Data Structures
struct	neuron_params_t
	definition of neuron parameters More...

struct	neuron_impl_t
	definition of neuron state More...

Macros
#define	V_RECORDING_INDEX 0

#define	EX_INPUT_INDEX 1

#define	IN_INPUT_INDEX 2

#define	PROB_INDEX 3

#define	N_RECORDED_VARS 4

#define	SPIKE_RECORDING_BITFIELD 0

#define	N_BITFIELD_VARS 1

Functions
static bool	neuron_impl_initialise (uint32_t n_neurons)

static void	neuron_model_initialise (neuron_impl_t state, neuron_params_t params)

static void	neuron_model_save_state (neuron_impl_t state, neuron_params_t params)

static void	neuron_impl_load_neuron_parameters (address_t address, uint32_t next, uint32_t n_neurons, address_t save_initial_state)

static void	neuron_impl_store_neuron_parameters (address_t address, uint32_t next, uint32_t n_neurons)

static void	neuron_impl_add_inputs (index_t synapse_type_index, index_t neuron_index, input_t weights_this_timestep)

static void	do_refrac_update (uint32_t timer_count, uint32_t time, uint32_t neuron_index, neuron_impl_t *neuron)

static void	do_non_refrac_update (uint32_t timer_count, uint32_t time, uint32_t neuron_index, neuron_impl_t *neuron)

static void	neuron_impl_do_timestep_update (uint32_t timer_count, uint32_t time, uint32_t n_neurons)

static void	neuron_impl_print_inputs (uint32_t n_neurons)

static void	neuron_impl_print_synapse_parameters (uint32_t n_neurons)

static const char *	neuron_impl_get_synapse_type_char (uint32_t synapse_type)

Variables
static neuron_impl_t *	neuron_array
	Array of neuron states.

Detailed Description

Stochastic neuron implementation with exponential probability.

Definition in file neuron_impl_stoc_exp_stable.h.

Data Structure Documentation

◆ neuron_params_t

struct neuron_params_t

definition of neuron parameters

The state parameters of an Izhekevich model neuron.

definition for LIF neuron parameters

Definition at line 47 of file neuron_impl_stoc_exp.h.

Data Fields
UREAL	tau_ms	The tau value of the neuron.
UREAL	time_step	The timestep of the neuron being used. The time step in milliseconds. current timestep in ms
REAL	bias	The bias value.
uint32_t	refract_init	The initial refractory timer.
mars_kiss64_seed_t	random_seed	Random seed to use.
REAL	v_init	The initial membrane voltage.
REAL	v_reset	The reset membrane voltage after a spike.
UREAL	tau	The tau value of the neuron, multiplied by 2^v to get probability.
UREAL	tau_refract	The refractory period of the neuron in milliseconds. The refractory period of the neuron, in ms.
REAL	alpha	The alpha value of the neuron prob = (2^(-2^(alpha x voltage)))
REAL	V_init	membrane voltage [mV]
REAL	c_m	membrane capacitance [nF]
REAL	tau_m	membrane decay time constant
REAL	I_offset	offset current [nA]
REAL	V_reset	post-spike reset membrane voltage [mV]
REAL	T_refract_ms	refractory time of neuron [ms]
int32_t	refract_timer_init	initial refractory timer value (saved)
REAL	time_step	The time step in milliseconds. current timestep in ms
REAL	A
REAL	B
REAL	C
REAL	D
REAL	V
REAL	U
REAL	next_h	next value of this_h (saved)
REAL	V_rest	membrane resting voltage [mV]

◆ neuron_impl_t

struct neuron_impl_t

definition of neuron state

Definition at line 67 of file neuron_impl_stoc_exp.h.

Data Fields
UFRACT	tau_recip	The reciprocal of the tau value.
REAL	bias	The bias value.
uint32_t	t_refract	The refractory timer countdown value.
uint32_t	refract_timer	The refractory timer.
mars_kiss64_seed_t	random_seed	The random state.
input_t	inputs[2]	The inputs to add in the next timestep.
REAL	v_membrane	The membrane voltage.
REAL	v_reset	The reset voltage after a spike.
UREAL	tau	The tau value of the neuron.
REAL	alpha	The alpha value of the neuron prob = (2^(-2^(alpha x voltage)))