In [1]:

from birdbrain.atlas import atlas
from birdbrain.utils import um_to_vox
import numpy as np

/mnt/cube/tsainbur/conda_envs/tpy3/lib/python3.6/site-packages/tqdm/autonotebook/__init__.py:14: TqdmExperimentalWarning: Using `tqdm.autonotebook.tqdm` in notebook mode. Use `tqdm.tqdm` instead to force console mode (e.g. in jupyter console)
  " (e.g. in jupyter console)", TqdmExperimentalWarning)

Load data, create atlas object¶

In [2]:

dset_dir = '../../data/processed/starling/'

starling_atlas = atlas(
    species = 'starling',
    dset_dir = dset_dir,
    um_mult = 100,
    smoothing =[],
    updated_y_sinus = [0, 1500, 0]
)

qform_code 32 not valid; setting to 0
qform_code 32 not valid; setting to 0

Data already download
Loading brain labels...
Getting voxel data from .img files...

qform_code 32 not valid; setting to 0
qform_code 32 not valid; setting to 0

Getting location for each nucleus/region from voxel data...

HBox(children=(IntProgress(value=0, max=45), HTML(value='')))

Atlas created

Estimate the number of neurons in a region¶

In [3]:

# Estimate of total number of neurons from https://www.pnas.org/content/113/26/7255/tab-figures-data
starling_n_neurons = 482.50*10**6
starling_n_neurons_std = 88.29*10**6

In [4]:

nucleus = 'CMM'

In [5]:

n_brain_voxels = np.sum(starling_atlas.voxel_data.loc['Brain', 'voxels'])
n_region_voxels = np.sum(starling_atlas.voxel_data.loc['Nuclei', 'voxels']==starling_atlas.brain_labels.loc[nucleus,'label'])
n_region_voxels/n_brain_voxels

Out[5]:

0.0026046479908523462

In [6]:

estimated_region_num_neurons = int((n_region_voxels/n_brain_voxels) * starling_n_neurons)
estimated_region_num_neurons_std = int((n_region_voxels/n_brain_voxels) * starling_n_neurons_std) 

In [7]:

print(nucleus+" has an estimated {:,}+={:,} neurons".format(estimated_region_num_neurons, estimated_region_num_neurons_std))

CMM has an estimated 1,256,742+=229,964 neurons

In [8]:

##TODO - print region volume in mL