I have a network of LIF neurons ('iaf_cond_alpha') and I would like to implement STDP synapses, rather than the 

standard 'static_synapse'. I would like to be able to set a subset of the network to STDP synapses (e.g. all excitatory ones) 

and leave the rest static. This is how have implemented that currently (see code). I am using a for loop because I want to 

see how STDP changes the activity over time (over many iterations), which leaves me with the following two questions:

1. Is this a correct way to implement STDP in nest? 

You code looks correct. To use STDP for excitatory-excitatory connections, simply replace static_synapse with stdp_synapse. See the documentation for stdp_synapse for additional parameters you can set to control plasticity, which allows you also to choose between different STDP variants.

See hpc_benchmark.py for an example of a network where only E->E connections are plastic.

2. Is there a way to reset the network such that the connections are not lost? ResetNetwork() and ResetKernel() both seem to 

destroy all the network connections. While I would like to keep them, so that the network becomes less and less randomly 

connected per simulation.

Thank you!

Best,

Daphne

CODE

        # define network connectivity
        conn_dict = {'rule': 'pairwise_bernoulli', 'p': 0.1} 
        # define dicts for static synapses
        static_ex_params = {'model':'static_synapse','weight': 6.0, 'delay': 1.5}
        static_in_params = {'model':'static_synapse','weight': -96.0, 'delay': 1.5}
        
        if self.STDP == 'ALL': 
            # all synapses should be stdp ones, make connections between the two populations:
            # from exc neurons to all neurons
            nest.Connect(neurons_all[:self.NE], neurons_all, conn_dict, self.syn_params_ex)
            # from interneurons to all neurons
            nest.Connect(neurons_all[self.NE:], neurons_all, conn_dict, self.syn_params_in)
   
        elif self.STDP == 'EXC':
            # keep the inhibitory synapses static
            # connections from exc neurons to all neurons
            nest.Connect(neurons_all[:self.NE], neurons_all, conn_dict, self.syn_params_ex)
            # connections from interneurons to all neurons
            nest.Connect(neurons_all[self.NE:], neurons_all, conn_dict, static_in_params)

where 

   synapse_params_in = {
        'model':'stdp_synapse',
        'lambda': 0.01,
        'alpha': 1.0,
        'delay': 1.5,
        'weight':-95.0
    }

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