on_convolution-11.py

N = n_time_points
M = n_hrf_points
bold_signal = np.zeros(N + M - 1)  # adding the tail
for i in range(N):
    input_value = neural_signal[i]
    # Adding the shifted, scaled HRF
    bold_signal[i : i + n_hrf_points] += hrf_signal * input_value
# We have to extend 'times' to deal with more points in 'bold_signal'
extra_times = np.arange(n_hrf_points - 1) * 0.1 + 40
times_and_tail = np.concatenate((times, extra_times))
plt.plot(times_and_tail, bold_signal)
plt.xlabel('time (seconds)')
plt.ylabel('bold signal')
plt.title('Output BOLD signal using our algorithm')