I am currently working on a project involving synaptic weight normalization using the guidelines provided in the NEST simulator documentation. I have implemented the normalization process; however, I encountered some questions that I would appreciate your insights on.

1. Normalization Value: I found that the normalization value for a neuron with approximately 190 synapses is around 420, which I do not fully understand. This looks like the total weight of the neuron synapses. Could you provide clarification on how the normalisation value is determined?

2. Simulation State Preservation: I would like to save and restore the state of synaptic weights to maintain the simulation's behaviour across sessions. Below is the pseudocode I intend to use:

   Save synaptic weights:
       w = array of current weights of neuron connections
       normalization_factor = sum of absolute weights
       if normalization_factor != 0:
           normalized_weights = w / normalization_factor
       save normalized_weights to file
   
   Load synaptic weights:
       read normalized_weights from file
       assign loaded weights back to connection
   

   I would like to know if you have any suggestions for improving this pseudocode or if there are best practices I should consider.

Thank you for your time and assistance. I look forward to your response.