Nengo is a Python library for building and simulating large-scale brain models using the methods of the Neural Engineering Framework. Nengo can create sophisticated neural simulations with sensible defaults in few lines of code:

import nengo
import numpy as np
import matplotlib.pyplot as plt

with nengo.Network() as net:
    sin_input = nengo.Node(output=np.sin)
    # A population of 100 neurons representing a sine wave
    sin_ens = nengo.Ensemble(n_neurons=100, dimensions=1)
    nengo.Connection(sin_input, sin_ens)
    # A population of 100 neurons representing the square of the sine wave
    sin_squared = nengo.Ensemble(n_neurons=100, dimensions=1)
    nengo.Connection(sin_ens, sin_squared, function=np.square)
    # View the decoded output of sin_squared
    squared_probe = nengo.Probe(sin_squared, synapse=0.01)

sim = nengo.Simulator(net)

Yet, Nengo is highly extensible and flexible. You can define your own neuron types and learning rules, get input directly from hardware, drive robots, and even simulate your model on a completely different neural simulator.

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