code: def plot_slices(data, title=None):
      plt.figure(figsize=(5.5, 2.2))
      vmax = np.abs(data).max()
      for i in (0, 6, 11):
          plt.subplot(1, 3, i // 5 + 1)
          plt.imshow(
              data[:, :, i],
              vmin=-vmax,
              vmax=vmax,
              interpolation="nearest",
              cmap=plt.cm.RdBu_r,
          )
          plt.xticks(())
          plt.yticks(())
      plt.subplots_adjust(
          hspace=0.05, wspace=0.05, left=0.03, right=0.97, top=0.9
      )
      if title is not None:
          plt.suptitle(title)
  
file_path: nilearn/examples/02_decoding/plot_simulated_data.py
imports: from time import time
  import matplotlib.pyplot
  import nibabel
  import numpy
  from scipy import linalg
  from scipy.ndimage import gaussian_filter
  from sklearn import linear_model, svm
  from sklearn.feature_selection import f_regression
  from sklearn.model_selection import KFold
  from sklearn.pipeline import make_pipeline
  from sklearn.preprocessing import StandardScaler
  from sklearn.utils import check_random_state
  import nilearn.masking
  from nilearn import decoding
  from nilearn.plotting import show
label_desc: Use image node_id 2 for calling a global function with example usage: plot_slices(data, title) without return types