iaf_psc_alpha_canon – Current-based leaky integrate-and-fire neuron with alpha-shaped postsynaptic currents - canonical implementation of precise spike timing version ====================================================================================================================================================================== Description +++++++++++ .. note:: This model is deprecated and will be removed in NEST 3. Please use ``iaf_psc_alpha_ps`` instead. ``iaf_psc_alpha_canon`` is the "canonical" implementatoin of the leaky integrate-and-fire model neuron with alpha-shaped postsynaptic currents in the sense of [1]_. This is the most exact implementation available. PSCs are normalized to an amplitude of 1pA. The canonical implementation handles neuronal dynamics in a locally event-based manner with in coarse time grid defined by the minimum delay in the network, see [1]_. Incoming spikes are applied at the precise moment of their arrival, while the precise time of outgoing spikes is determined by interpolation once a threshold crossing has been detected. Return from refractoriness occurs precisly at spike time plus refractory period. This implementation is more complex than the plain ``iaf_psc_alpha`` neuron, but achieves much higher precision. In particular, it does not suffer any binning of spike times to grid points. Depending on your application, the canonical application may provide superior overall performance given an accuracy goal; see [1]_ for details. Subthreshold dynamics are integrated using exact integration between events [2]_. .. note:: Please note that this node is capable of sending precise spike times to target nodes (on-grid spike time plus offset). A further improvement of precise simulation is implemented in ``iaf_psc_exp_ps`` based on [3]_. .. note:: If ``tau_m`` is very close to ``tau_syn_ex`` or ``tau_syn_in``, the model will numerically behave as if ``tau_m`` is equal to ``tau_syn_ex`` or ``tau_syn_in``, respectively, to avoid numerical instabilities. For implementation details see the `IAF_neurons_singularity <../model_details/IAF_neurons_singularity.ipynb>`_ notebook. This model transmits precise spike times to target nodes (on-grid spike time and offset). If this node is connected to a ``spike_recorder``, the property "precise_times" of the ``spike_recorder`` has to be set to true in order to record the offsets in addition to the on-grid spike times. The ``iaf_psc_delta_ps`` neuron accepts connections transmitting ``CurrentEvents``. These events transmit stepwise-constant currents which can only change at on-grid times. For details about exact subthreshold integration, please see :doc:`../neurons/exact-integration`. Parameters ++++++++++ The following parameters can be set in the status dictionary. =============== ====== ========================================================== V_m mV Membrane potential E_L mV Resting membrane potential V_min mV Absolute lower value for the membrane potential. C_m pF Capacity of the membrane tau_m ms Membrane time constant t_ref ms Duration of refractory period V_th mV Spike threshold V_reset mV Reset potential of the membrane tau_syn ms Rise time of the synaptic alpha function I_e pA Constant external input current Interpol_Order (int) Interpolation order for spike time: 0-none, 1-linear, 2-quadratic, 3-cubic =============== ====== ========================================================== References ++++++++++ .. [1] Morrison A, Straube S, Plesser H E, & Diesmann M (2006) Exact Subthreshold Integration with Continuous Spike Times in Discrete Time Neural Network Simulations. To appear in Neural Computation. .. [2] Rotter S & Diesmann M (1999) Exact simulation of time-invariant linear systems with applications to neuronal modeling. Biologial Cybernetics 81:381-402. .. [3] Hanuschkin A, Kunkel S, Helias M, Morrison A & Diesmann M (2010) A general and efficient method for incorporating exact spike times in globally time-driven simulations Front Neuroinformatics, 4:113 Sends +++++ SpikeEvent Receives ++++++++ SpikeEvent, CurrentEvent, DataLoggingRequest See also ++++++++ :doc:`Neuron `, :doc:`Integrate-And-Fire `, :doc:`Current-Based `, :doc:`Precise `