We describe a simulator for neural networks and action potentials (SNNAP) that can simulate up to 30 neurons, each with up to 30 voltage-dependent conductances, 30 electrical synapses, and 30 multicomponent chemical synapses. Voltage-dependent conductances are described by Hodgkin-Huxley type equations, and the contributions of time-dependent synaptic conductances are described by second-order differential equations. The program also incorporates equations for simulating different types of neural modulation and synaptic plasticity. 2. Parameters, initial conditions, and output options for SNNAP are passed to the program through a number of modular ASCII files. These modules can be modified by commonly available text editors that use a conventional (i.e., character based) interface or by an editor incorporated into SNNAP that uses a graphical interface. The modular design facilitates the incorporation of existing modules into new simulations. Thus libraries can be developed of files describing distinctive cell types and files describing distinctive neural networks. 3. Several different types of neurons with distinct biophysical properties and firing properties were simulated by incorporating different combinations of voltage-dependent Na+, Ca2+, and K+ channels as well as Ca(2+)-activated and Ca(2+)-inactivated channels. Simulated cells included those that respond to depolarization with tonic firing, adaptive firing, or plateau potentials as well as endogenous pacemaker and bursting cells. 4. Several types of simple neural networks were simulated that included feed-forward excitatory and inhibitory chemical synaptic connections, a network of electrically coupled cells, and a network with feedback chemical synaptic connections that simulated rhythmic neural activity. In addition, with the use of the equations describing electrical coupling, current flow in a branched neuron with 18 compartments was simulated. 5. Enhancement of excitability and enhancement of transmitter release, produced by modulatory transmitters, were simulated by second-messenger-induced modulation of K+ currents. A depletion model for synaptic depression was also simulated. 6. We also attempted to simulate the features of a more complicated central pattern generator, inspired by the properties of neurons in the buccal ganglia of Aplysia. Dynamic changes in the activity of this central pattern generator were produced by a second-messenger-induced modulation of a slow inward current in one of the neurons.
