Unable to make a custom color scheme in Nilearn

Question

I am trying to write code so that I am able to highlight lobes of the brain based on various continuous values. However, I am having trouble correctly accessing the indexes of the lobes I believe when calling the color scheme.

# Data for a reproducible answer
left_stage = {'Left_Temporal': 7.53381268745182, 'Left_Frontal': 3.2069698527141495, 'Left_Parietal': 15.321909355803081, 'Left_Occipital': 15.20597303571137, 'Left_MTL': 8.053567272349891}

# Atlases of interest
destrieux_atlas = datasets.fetch_atlas_surf_destrieux()
fsaverage = datasets.fetch_surf_fsaverage()
labels = destrieux_atlas['labels']

# Define the regions of interest for plotting
Temporal =  [
    b'G_temporal_inf', b'S_temporal_inf', b'G_temp_sup-G_T_transv', b'G_temp_sup-Lateral',
    b'G_temp_sup-Plan_polar', b'G_temp_sup-Plan_tempo', b'S_temporal_sup', b'S_temporal_transverse', b'S_temporal_transverse'
    ]

Frontal = [
    b'G_front_sup', b'S_front_sup', b'G_front_middle', b'G_front_middle',
    b'G_front_inf-Opercular', b'G_front_inf-Triangul', b'G_front_inf-Orbital',
    b'G_orbital', b'G_orbital', b'G_rectus', b'S_orbital_med-olfact', b'S_orbital-H_Shaped',
    b'G_precentral', b'S_precentral-inf-part', b'S_precentral-sup-part', b'G_and_S_paracentral'
]

Parietal =  [
    b'G_postcentral', b'S_postcentral', b'G_pariet_inf-Supramar',
    b'G_parietal_sup', b'S_intrapariet_and_P_trans', b'G_pariet_inf-Angular',
    b'G_precuneus'
]

Occipital = [
    b'G_oc-temp_med-Lingual', b'S_oc-temp_med_and_Lingual', b'S_calcarine', b'G_cuneus',
    b'G_occipital_middle', b'G_occipital_sup', b'S_oc_middle_and_Lunatus', b'S_oc_sup_and_transversal'
]

parcellation_left = destrieux_atlas['map_left']
custom_map_left = np.zeros(parcellation_left.shape[0], dtype=int)

temporal_region_indices = [labels.index(region) for region in Temporal]
temporal_labels = np.concatenate([np.where(parcellation_left == idx)[0] for idx in temporal_region_indices])
custom_map_left[temporal_labels] = 1

frontal_region_indices = [labels.index(region) for region in Frontal]
frontal_labels = np.concatenate([np.where(parcellation_left == idx)[0] for idx in frontal_region_indices])
custom_map_left[frontal_labels] = 2

occipital_region_indices = [labels.index(region) for region in Occipital]
occipital_labels = np.concatenate([np.where(parcellation_left == idx)[0] for idx in occipital_region_indices])
custom_map_left[occipital_labels] = 3

parietal_region_indices = [labels.index(region) for region in Parietal]
parietal_labels = np.concatenate([np.where(parcellation_left == idx)[0] for idx in parietal_region_indices])
custom_map_left[parietal_labels] = 4

mtl_region_indices = [labels.index(region) for region in MTL]
mtl_labels = np.concatenate([np.where(parcellation_left == idx)[0] for idx in mtl_region_indices])
custom_map_left[mtl_labels] = 5

# Define a function to map values to colors
def map_value_to_color(subtype_stage):
    cmap = nilearn_cmaps["black_blue_r"]
    norm = plt.Normalize(vmin=0, vmax=10)
    
    colors = [(1,1,1)]
    
    for value in subtype_stage:
        
        if value < 0:
             colors.append((1, 1, 1))
        elif value >= 0 and value < 10:
            colors.append(cmap(norm(value)))
        else:
            colors.append((0, 0, 0))
    
    return  mcolors.LinearSegmentedColormap.from_list('Custom', colors)


cmap = nilearn_cmaps["black_blue_r"]
norm = plt.Normalize(vmin=0, vmax=10)

colors = [(1,1,1)]

for value in left_stage:

    if value < 0:
         colors.append((1, 1, 1))
    elif value >= 0 and value < 10:
        colors.append(cmap(norm(value)))
    else:
        colors.append((0, 0, 0))
        
cmap_left = mcolors.LinearSegmentedColormap.from_list('Custom', colors)

img = plotting.plot_surf_roi(
    fsaverage['pial_left'],
    roi_map = custom_map_left,
    hemi="left",
    view="lateral",
    cmap=cmap_left,
    darkness=.6,
    bg_map=fsaverage['sulc_left']
)

This code however incorrectly colors the occipital lobe as an example

Clearly based on the data the occipital lobe has a value of greater than 10 and based if else it should be assigned black ((0,0,0)). However, its the off greenish blue.

The way that I understand how to provide a custom color map is that I create a custom ROI map which then maps the values in that array to the values based on the corresponding indicies in the colormap. However, this is clearly not working.

Any ideas?