neuron_impl_stoc_sigma.h File Reference

Stochastic neuron implementation with sigma shaped 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>

Go to the source code of this file.

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
#define	PROB_HALF   0x7FFFFFFF
	A probability of a half.
#define	MAX_POWER   REAL_CONST(5)
	The power of 2 that == 32.
#define	MIN_POWER   REAL_CONST(-5)

Functions
static bool	neuron_impl_initialise (uint32_t n_neurons)
static uint32_t	stoc_sigma_ceil_accum (UREAL value)
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 sigma shaped probability.

Definition in file neuron_impl_stoc_sigma.h.

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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)))