Orn_model.py

import nengo
import numpy as np
from random import *
import csv



# Constants
NUM_ORNS = 40
DELTA = 0.01   # presentation_time


# Read in list of 40 spike trains (40 lines in csv)
with open('spike_trains.csv') as f:
    reader = csv.reader(f)
    spike_trains = np.array([[int(element) if element.isdigit() else element for element in sub] for sub in list(reader)])

# Spike trains to input
spiked_neurons = [None]*NUM_ORNS


# Init nengo model
model = nengo.Network()
with model:

    # Initialize one PRN that combines ORN inputs
    prn = nengo.Ensemble(n_neurons=2, dimensions=1)

    # Iterate through each ORN and connect with PRN
    for orn in range(NUM_ORNS):
        # Initialize ORN
        spiked_neurons[orn] = nengo.Node(nengo.processes.PresentInput(np.array(spike_trains[orn]), DELTA))

        # Connect ORN_orn to PRN
        nengo.Connection(spiked_neurons[orn], prn)