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PyNN |
| NeuroML2 ComponentType definitions from PyNN.xml |
| Original LEMS ComponentType definitions: PyNN.xml Schema against which NeuroML based on these should be valid: NeuroML_v2.2.xsd |
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basePyNNCell
extends baseCellMembPot |
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| Base type of any PyNN standard cell model. Note: membrane potential v has dimensions voltage, but all other parameters are dimensionless. This is to facilitate translation to and from PyNN scripts in Python, where these parameters have implicit units, see http://neuralensemble.org/trac/PyNN/wiki/StandardModels | ||
| Parameters | cm | Dimensionless | i_offset | Dimensionless | tau_syn_E | Dimensionless | tau_syn_I | Dimensionless | v_init | Dimensionless |
| Constants | MSEC = 1ms | time | MVOLT = 1mV | voltage | NFARAD = 1nF | capacitance |
| Exposures | iSyn | current | v (from baseCellMembPot) | voltage |
| Event Ports | spike (from baseSpikingCell) | Direction: out | spike_in_E | Direction: in | spike_in_I | Direction: in |
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basePyNNIaFCell
extends basePyNNCell |
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| Base type of any PyNN standard integrate and fire model | ||
| Parameters | cm (from basePyNNCell) | Dimensionless | i_offset (from basePyNNCell) | Dimensionless | tau_m | Dimensionless | tau_refrac | Dimensionless | tau_syn_E (from basePyNNCell) | Dimensionless | tau_syn_I (from basePyNNCell) | Dimensionless | v_init (from basePyNNCell) | Dimensionless | v_reset | Dimensionless | v_rest | Dimensionless | v_thresh | Dimensionless |
| Exposures | iSyn (from basePyNNCell) | current | v (from baseCellMembPot) | voltage |
| Event Ports | spike (from baseSpikingCell) | Direction: out | spike_in_E (from basePyNNCell) | Direction: in | spike_in_I (from basePyNNCell) | Direction: in |
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basePyNNIaFCondCell
extends basePyNNIaFCell |
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| Base type of conductance based PyNN IaF cell models | ||
| Parameters | cm (from basePyNNCell) | Dimensionless | e_rev_E | Dimensionless | e_rev_I | Dimensionless | i_offset (from basePyNNCell) | Dimensionless | tau_m (from basePyNNIaFCell) | Dimensionless | tau_refrac (from basePyNNIaFCell) | Dimensionless | tau_syn_E (from basePyNNCell) | Dimensionless | tau_syn_I (from basePyNNCell) | Dimensionless | v_init (from basePyNNCell) | Dimensionless | v_reset (from basePyNNIaFCell) | Dimensionless | v_rest (from basePyNNIaFCell) | Dimensionless | v_thresh (from basePyNNIaFCell) | Dimensionless |
| Exposures | iSyn (from basePyNNCell) | current | v (from baseCellMembPot) | voltage |
| Event Ports | spike (from baseSpikingCell) | Direction: out | spike_in_E (from basePyNNCell) | Direction: in | spike_in_I (from basePyNNCell) | Direction: in |
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IF_curr_alpha
extends basePyNNIaFCell |
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| Leaky integrate and fire model with fixed threshold and alpha-function-shaped post-synaptic current | ||
| Parameters | cm (from basePyNNCell) | Dimensionless | i_offset (from basePyNNCell) | Dimensionless | tau_m (from basePyNNIaFCell) | Dimensionless | tau_refrac (from basePyNNIaFCell) | Dimensionless | tau_syn_E (from basePyNNCell) | Dimensionless | tau_syn_I (from basePyNNCell) | Dimensionless | v_init (from basePyNNCell) | Dimensionless | v_reset (from basePyNNIaFCell) | Dimensionless | v_rest (from basePyNNIaFCell) | Dimensionless | v_thresh (from basePyNNIaFCell) | Dimensionless |
| Exposures | iSyn (from basePyNNCell) | current | v (from baseCellMembPot) | voltage |
| Event Ports | spike (from baseSpikingCell) | Direction: out | spike_in_E (from basePyNNCell) | Direction: in | spike_in_I (from basePyNNCell) | Direction: in |
| Attachments | synapses | baseSynapse |
| Dynamics |
State Variables v voltage (exposed as v) lastSpikeTime time On Start v = v_init * MVOLT Derived Variables iSyn = synapses[*]->i (reduce method: add) (exposed as iSyn) Regime: refractory (initial) On Entry lastSpikeTime = t v = v_reset * MVOLT On Conditions IF t > lastSpikeTime + (tau_refrac*MSEC) THEN TRANSITION to REGIME integrating Regime: integrating (initial) On Conditions IF v > v_thresh * MVOLT THEN EVENT OUT on port spike TRANSITION to REGIME refractory Time Derivatives d v /dt = (MVOLT * ((i_offset/cm) + ((v_rest - (v/MVOLT)) / tau_m))/MSEC) + (iSyn / (cm * NFARAD)) |
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IF_curr_exp
extends basePyNNIaFCell |
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| Leaky integrate and fire model with fixed threshold and decaying-exponential post-synaptic current | ||
| Parameters | cm (from basePyNNCell) | Dimensionless | i_offset (from basePyNNCell) | Dimensionless | tau_m (from basePyNNIaFCell) | Dimensionless | tau_refrac (from basePyNNIaFCell) | Dimensionless | tau_syn_E (from basePyNNCell) | Dimensionless | tau_syn_I (from basePyNNCell) | Dimensionless | v_init (from basePyNNCell) | Dimensionless | v_reset (from basePyNNIaFCell) | Dimensionless | v_rest (from basePyNNIaFCell) | Dimensionless | v_thresh (from basePyNNIaFCell) | Dimensionless |
| Exposures | iSyn (from basePyNNCell) | current | v (from baseCellMembPot) | voltage |
| Event Ports | spike (from baseSpikingCell) | Direction: out | spike_in_E (from basePyNNCell) | Direction: in | spike_in_I (from basePyNNCell) | Direction: in |
| Attachments | synapses | baseSynapse |
| Dynamics |
State Variables v voltage (exposed as v) lastSpikeTime time On Start v = v_init * MVOLT Derived Variables iSyn = synapses[*]->i (reduce method: add) (exposed as iSyn) Regime: refractory (initial) On Entry lastSpikeTime = t v = v_reset * MVOLT On Conditions IF t > lastSpikeTime + (tau_refrac*MSEC) THEN TRANSITION to REGIME integrating Regime: integrating (initial) On Conditions IF v > v_thresh * MVOLT THEN EVENT OUT on port spike TRANSITION to REGIME refractory Time Derivatives d v /dt = (MVOLT * (((i_offset)/cm) + ((v_rest - (v/MVOLT)) / tau_m))/MSEC) + (iSyn / (cm * NFARAD)) |
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IF_cond_alpha
extends basePyNNIaFCondCell |
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| Leaky integrate and fire model with fixed threshold and alpha-function-shaped post-synaptic conductance | ||
| Parameters | cm (from basePyNNCell) | Dimensionless | e_rev_E (from basePyNNIaFCondCell) | Dimensionless | e_rev_I (from basePyNNIaFCondCell) | Dimensionless | i_offset (from basePyNNCell) | Dimensionless | tau_m (from basePyNNIaFCell) | Dimensionless | tau_refrac (from basePyNNIaFCell) | Dimensionless | tau_syn_E (from basePyNNCell) | Dimensionless | tau_syn_I (from basePyNNCell) | Dimensionless | v_init (from basePyNNCell) | Dimensionless | v_reset (from basePyNNIaFCell) | Dimensionless | v_rest (from basePyNNIaFCell) | Dimensionless | v_thresh (from basePyNNIaFCell) | Dimensionless |
| Exposures | iSyn (from basePyNNCell) | current | v (from baseCellMembPot) | voltage |
| Event Ports | spike (from baseSpikingCell) | Direction: out | spike_in_E (from basePyNNCell) | Direction: in | spike_in_I (from basePyNNCell) | Direction: in |
| Attachments | synapses | baseSynapse |
| Dynamics |
State Variables v voltage (exposed as v) lastSpikeTime time On Start v = v_init * MVOLT Derived Variables iSyn = synapses[*]->i (reduce method: add) (exposed as iSyn) Regime: refractory (initial) On Entry lastSpikeTime = t v = v_reset * MVOLT On Conditions IF t > lastSpikeTime + (tau_refrac*MSEC) THEN TRANSITION to REGIME integrating Regime: integrating (initial) On Conditions IF v > v_thresh * MVOLT THEN EVENT OUT on port spike TRANSITION to REGIME refractory Time Derivatives d v /dt = (MVOLT * (((i_offset) / cm) + ((v_rest - (v / MVOLT)) / tau_m)) / MSEC) + (iSyn / (cm * NFARAD)) |
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IF_cond_exp
extends basePyNNIaFCondCell |
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| Leaky integrate and fire model with fixed threshold and exponentially-decaying post-synaptic conductance | ||
| Parameters | cm (from basePyNNCell) | Dimensionless | e_rev_E (from basePyNNIaFCondCell) | Dimensionless | e_rev_I (from basePyNNIaFCondCell) | Dimensionless | i_offset (from basePyNNCell) | Dimensionless | tau_m (from basePyNNIaFCell) | Dimensionless | tau_refrac (from basePyNNIaFCell) | Dimensionless | tau_syn_E (from basePyNNCell) | Dimensionless | tau_syn_I (from basePyNNCell) | Dimensionless | v_init (from basePyNNCell) | Dimensionless | v_reset (from basePyNNIaFCell) | Dimensionless | v_rest (from basePyNNIaFCell) | Dimensionless | v_thresh (from basePyNNIaFCell) | Dimensionless |
| Exposures | iSyn (from basePyNNCell) | current | v (from baseCellMembPot) | voltage |
| Event Ports | spike (from baseSpikingCell) | Direction: out | spike_in_E (from basePyNNCell) | Direction: in | spike_in_I (from basePyNNCell) | Direction: in |
| Attachments | synapses | baseSynapse |
| Dynamics |
State Variables v voltage (exposed as v) lastSpikeTime time On Start v = v_init * MVOLT Derived Variables iSyn = synapses[*]->i (reduce method: add) (exposed as iSyn) Regime: refractory (initial) On Entry lastSpikeTime = t v = v_reset * MVOLT On Conditions IF t > lastSpikeTime + (tau_refrac*MSEC) THEN TRANSITION to REGIME integrating Regime: integrating (initial) On Conditions IF v > v_thresh * MVOLT THEN EVENT OUT on port spike TRANSITION to REGIME refractory Time Derivatives d v /dt = (MVOLT * (((i_offset)/cm) + ((v_rest - (v / MVOLT)) / tau_m)) / MSEC) + (iSyn / (cm * NFARAD)) |
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EIF_cond_exp_isfa_ista
extends basePyNNIaFCondCell |
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| Adaptive exponential integrate and fire neuron according to Brette R and Gerstner W (2005) with exponentially-decaying post-synaptic conductance | ||
| Parameters | a | Dimensionless | b | Dimensionless | cm (from basePyNNCell) | Dimensionless | delta_T | Dimensionless | e_rev_E (from basePyNNIaFCondCell) | Dimensionless | e_rev_I (from basePyNNIaFCondCell) | Dimensionless | i_offset (from basePyNNCell) | Dimensionless | tau_m (from basePyNNIaFCell) | Dimensionless | tau_refrac (from basePyNNIaFCell) | Dimensionless | tau_syn_E (from basePyNNCell) | Dimensionless | tau_syn_I (from basePyNNCell) | Dimensionless | tau_w | Dimensionless | v_init (from basePyNNCell) | Dimensionless | v_reset (from basePyNNIaFCell) | Dimensionless | v_rest (from basePyNNIaFCell) | Dimensionless | v_spike | Dimensionless | v_thresh (from basePyNNIaFCell) | Dimensionless |
| Derived Parameters | eif_threshold = v_spike * H(delta_T-1e-12) + v_thresh * H(-1*delta_T+1e-9) | Dimensionless |
| Exposures | iSyn (from basePyNNCell) | current | v (from baseCellMembPot) | voltage | w | Dimensionless |
| Event Ports | spike (from baseSpikingCell) | Direction: out | spike_in_E (from basePyNNCell) | Direction: in | spike_in_I (from basePyNNCell) | Direction: in |
| Attachments | synapses | baseSynapse |
| Dynamics |
State Variables v voltage (exposed as v) w Dimensionless (exposed as w) lastSpikeTime time On Start v = v_init * MVOLT w = 0 Derived Variables iSyn = synapses[*]->i (reduce method: add) (exposed as iSyn) Conditional Derived Variables IF delta_T > 0 THEN delta_I = delta_T * exp(((v / MVOLT) - v_thresh) / delta_T) IF delta_T = 0 THEN delta_I = 0 Regime: refractory (initial) On Entry lastSpikeTime = t v = v_reset * MVOLT w = w+b On Conditions IF t > lastSpikeTime + (tau_refrac*MSEC) THEN TRANSITION to REGIME integrating Time Derivatives d w /dt = (1 / tau_w) * (a * ((v / MVOLT) - v_rest) - w) / MSEC Regime: integrating (initial) On Conditions IF v > eif_threshold * MVOLT THEN EVENT OUT on port spike TRANSITION to REGIME refractory Time Derivatives d v /dt = (MVOLT * ((-1 * ((v / MVOLT) - v_rest) + delta_I) / tau_m + (i_offset - w) / cm) / MSEC) + (iSyn / (cm * NFARAD)) d w /dt = (1 / tau_w) * (a * ((v / MVOLT) - v_rest) - w) / MSEC |
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EIF_cond_alpha_isfa_ista
extends basePyNNIaFCondCell |
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| Adaptive exponential integrate and fire neuron according to Brette R and Gerstner W (2005) with alpha-function-shaped post-synaptic conductance | ||
| Parameters | a | Dimensionless | b | Dimensionless | cm (from basePyNNCell) | Dimensionless | delta_T | Dimensionless | e_rev_E (from basePyNNIaFCondCell) | Dimensionless | e_rev_I (from basePyNNIaFCondCell) | Dimensionless | i_offset (from basePyNNCell) | Dimensionless | tau_m (from basePyNNIaFCell) | Dimensionless | tau_refrac (from basePyNNIaFCell) | Dimensionless | tau_syn_E (from basePyNNCell) | Dimensionless | tau_syn_I (from basePyNNCell) | Dimensionless | tau_w | Dimensionless | v_init (from basePyNNCell) | Dimensionless | v_reset (from basePyNNIaFCell) | Dimensionless | v_rest (from basePyNNIaFCell) | Dimensionless | v_spike | Dimensionless | v_thresh (from basePyNNIaFCell) | Dimensionless |
| Derived Parameters | eif_threshold = v_spike * H(delta_T-1e-12) + v_thresh * H(-1*delta_T+1e-9) | Dimensionless |
| Exposures | iSyn (from basePyNNCell) | current | v (from baseCellMembPot) | voltage | w | Dimensionless |
| Event Ports | spike (from baseSpikingCell) | Direction: out | spike_in_E (from basePyNNCell) | Direction: in | spike_in_I (from basePyNNCell) | Direction: in |
| Attachments | synapses | baseSynapse |
| Dynamics |
State Variables v voltage (exposed as v) w Dimensionless (exposed as w) lastSpikeTime time On Start v = v_init * MVOLT w = 0 Derived Variables iSyn = synapses[*]->i (reduce method: add) (exposed as iSyn) Conditional Derived Variables IF delta_T > 0 THEN delta_I = delta_T * exp(((v / MVOLT) - v_thresh) / delta_T) IF delta_T = 0 THEN delta_I = 0 Regime: refractory (initial) On Entry lastSpikeTime = t v = v_reset * MVOLT w = w + b On Conditions IF t > lastSpikeTime + (tau_refrac * MSEC) THEN TRANSITION to REGIME integrating Time Derivatives d w /dt = (1 / tau_w) * (a * ((v / MVOLT) - v_rest) - w) / MSEC Regime: integrating (initial) On Conditions IF v > eif_threshold * MVOLT THEN EVENT OUT on port spike TRANSITION to REGIME refractory Time Derivatives d v /dt = (MVOLT * ((-1 * ( (v / MVOLT) - v_rest) + delta_I) / tau_m + (i_offset - w) / cm) / MSEC) + (iSyn / (cm * NFARAD)) d w /dt = (1/ tau_w) * (a*((v/MVOLT)-v_rest) - w) /MSEC |
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HH_cond_exp
extends basePyNNCell |
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| Single-compartment Hodgkin-Huxley-type neuron with transient sodium and delayed-rectifier potassium currents using the ion channel models from Traub. | ||
| Parameters | cm (from basePyNNCell) | Dimensionless | e_rev_E | Dimensionless | e_rev_I | Dimensionless | e_rev_K | Dimensionless | e_rev_Na | Dimensionless | e_rev_leak | Dimensionless | g_leak | Dimensionless | gbar_K | Dimensionless | gbar_Na | Dimensionless | i_offset (from basePyNNCell) | Dimensionless | tau_syn_E (from basePyNNCell) | Dimensionless | tau_syn_I (from basePyNNCell) | Dimensionless | v_init (from basePyNNCell) | Dimensionless | v_offset | Dimensionless |
| Exposures | h | Dimensionless | iSyn (from basePyNNCell) | current | m | Dimensionless | n | Dimensionless | v (from baseCellMembPot) | voltage |
| Event Ports | spike (from baseSpikingCell) | Direction: out | spike_in_E (from basePyNNCell) | Direction: in | spike_in_I (from basePyNNCell) | Direction: in |
| Attachments | synapses | baseSynapse |
| Dynamics |
State Variables v voltage (exposed as v) m Dimensionless (exposed as m) h Dimensionless (exposed as h) n Dimensionless (exposed as n) On Start v = v_init * MVOLT Derived Variables iSyn = synapses[*]->i (reduce method: add) (exposed as iSyn) iLeak = g_leak * (e_rev_leak - (v / MVOLT)) iNa = gbar_Na * (m * m * m) * h * (e_rev_Na - (v / MVOLT)) iK = gbar_K * (n * n * n * n) * (e_rev_K - (v / MVOLT)) iMemb = iLeak + iNa + iK + i_offset alpham = 0.32 * (13 - (v / MVOLT) + v_offset) / (exp((13 - (v / MVOLT) + v_offset) / 4.0) - 1) betam = 0.28 * ((v / MVOLT) - v_offset - 40) / (exp(((v / MVOLT) - v_offset - 40) / 5.0) - 1) alphah = 0.128 * exp((17 - (v / MVOLT) + v_offset) / 18.0) betah = 4.0 / (1 + exp((40 - (v / MVOLT) + v_offset) / 5)) alphan = 0.032 * (15 - (v / MVOLT) + v_offset) / (exp((15 - (v / MVOLT) + v_offset) / 5) - 1) betan = 0.5 * exp((10 - (v / MVOLT) + v_offset) / 40) Time Derivatives d v /dt = (MVOLT * (iMemb / cm) / MSEC) + (iSyn / (cm * NFARAD)) d m /dt = (alpham * (1 - m) - betam * m) / MSEC d h /dt = (alphah * (1 - h) - betah * h) / MSEC d n /dt = (alphan * (1 - n) - betan * n) / MSEC |
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basePynnSynapse
extends baseVoltageDepSynapse |
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| Base type for all PyNN synapses. Note, the current I produced is dimensionless, but it requires a membrane potential v with dimension voltage | ||
| Parameters | tau_syn | Dimensionless |
| Constants | MSEC = 1ms | time | MVOLT = 1mV | voltage | NAMP = 1nA | current |
| Exposures | i (from basePointCurrent) | current |
| Requirements | v (from baseVoltageDepSynapse) | voltage |
| Event Ports | in (from baseSynapse) | Direction: in |
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expCondSynapse
extends basePynnSynapse |
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| Conductance based synapse with instantaneous rise and single exponential decay (with time constant tau_syn) | ||
| Parameters | e_rev | Dimensionless | tau_syn (from basePynnSynapse) | Dimensionless |
| Exposures | g | Dimensionless | i (from basePointCurrent) | current |
| Requirements | v (from baseVoltageDepSynapse) | voltage |
| Event Ports | in (from baseSynapse) | Direction: in |
| Dynamics |
State Variables g Dimensionless (exposed as g) On Events EVENT IN on port: in g = g+weight Derived Variables i = g * (e_rev - (v/MVOLT)) * NAMP (exposed as i) Time Derivatives d g /dt = -g / (tau_syn*MSEC) |
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expCurrSynapse
extends basePynnSynapse |
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| Current based synapse with instantaneous rise and single exponential decay (with time constant tau_syn) | ||
| Parameters | tau_syn (from basePynnSynapse) | Dimensionless |
| Exposures | i (from basePointCurrent) | current |
| Requirements | v (from baseVoltageDepSynapse) | voltage |
| Event Ports | in (from baseSynapse) | Direction: in |
| Dynamics |
State Variables I Dimensionless On Events EVENT IN on port: in I = I + weight Derived Variables i = I * NAMP (exposed as i) Time Derivatives d I /dt = -I / (tau_syn*MSEC) |
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alphaCondSynapse
extends basePynnSynapse |
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| Alpha synapse: rise time and decay time are both tau_syn. Conductance based synapse. | ||
| Parameters | e_rev | Dimensionless | tau_syn (from basePynnSynapse) | Dimensionless |
| Exposures | A | Dimensionless | g | Dimensionless | i (from basePointCurrent) | current |
| Requirements | v (from baseVoltageDepSynapse) | voltage |
| Event Ports | in (from baseSynapse) | Direction: in |
| Dynamics |
State Variables g Dimensionless (exposed as g) A Dimensionless (exposed as A) On Events EVENT IN on port: in A = A + weight Derived Variables i = g * (e_rev - (v/MVOLT)) * NAMP (exposed as i) Time Derivatives d g /dt = (2.7182818*A - g)/(tau_syn*MSEC) d A /dt = -A /(tau_syn*MSEC) |
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alphaCurrSynapse
extends basePynnSynapse |
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| Alpha synapse: rise time and decay time are both tau_syn. Current based synapse. | ||
| Parameters | tau_syn (from basePynnSynapse) | Dimensionless |
| Exposures | A | current | i (from basePointCurrent) | current |
| Requirements | v (from baseVoltageDepSynapse) | voltage |
| Event Ports | in (from baseSynapse) | Direction: in |
| Dynamics |
State Variables I Dimensionless A Dimensionless (exposed as A) On Events EVENT IN on port: in A = A + weight Derived Variables i = I * NAMP (exposed as i) Time Derivatives d I /dt = (2.7182818*A - I)/(tau_syn*MSEC) d A /dt = -A /(tau_syn*MSEC) |
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SpikeSourcePoisson
extends baseSpikeSource |
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| Spike source, generating spikes according to a Poisson process. | ||
| Parameters | duration | time | rate | per_time | start | time |
| Derived Parameters | end = start + duration | time |
| Constants | LONG_TIME = 1e9hour | time | SMALL_TIME = 1e-9ms | time |
| Exposures | isi | time | tnextIdeal | time | tnextUsed | time | tsince (from baseSpikeSource) | time |
| Event Ports | in | Direction: in | spike (from baseSpikeSource) | Direction: out |
| Dynamics |
State Variables tsince time (exposed as tsince) tnextIdeal time (exposed as tnextIdeal) tnextUsed time (exposed as tnextUsed) isi time (exposed as isi) On Start isi = start - log(random(1))/rate tsince = 0 tnextIdeal = isi + H(((isi) - (start+duration))/duration)*LONG_TIME tnextUsed = tnextIdeal On Conditions IF t > tnextUsed THEN isi = -1 * log(random(1))/rate tnextIdeal = (tnextIdeal+isi) + H(((tnextIdeal+isi) - (start+duration))/duration)*LONG_TIME tnextUsed = tnextIdeal*H( (tnextIdeal-t)/t ) + (t+SMALL_TIME)*H( (t-tnextIdeal)/t ) tsince = 0 EVENT OUT on port spike Time Derivatives d tsince /dt = 1 d tnextUsed /dt = 0 d tnextIdeal /dt = 0 |
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