Note
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natural scene decoding ophys¶
This is an example of how to decode natural images from ophys traces in V1
First, let’s download an experiment from the Allen Institute Brain Observatory
from allensdk.core.brain_observatory_cache import BrainObservatoryCache
boc = BrainObservatoryCache()
OEID = 541206592
nwb_dataset = boc.get_ophys_experiment_data(OEID)
Next, we’ll load the dF/F traces and put them in a DataFrame
timestamps, dff = nwb_dataset.get_dff_traces()
neuron_ids = nwb_dataset.get_cell_specimen_ids()
import pandas as pd
traces = pd.DataFrame(
dff.T,
columns=neuron_ids,
index=timestamps,
)
print(traces.head())
Out:
541510267 541510270 ... 541509957 541511118
10.30338 0.219740 0.151908 ... 0.360267 0.156850
10.33655 0.167939 0.142997 ... 0.308192 0.108658
10.36972 0.136697 0.068048 ... 0.295819 0.033781
10.40289 0.157216 0.105795 ... 0.329818 0.098048
10.43606 0.130490 0.097038 ... 0.487283 0.066526
[5 rows x 154 columns]
Next, we’ll load stim_table
stim_table = nwb_dataset.get_stimulus_table('natural_scenes')
print(stim_table.head())
Out:
frame start end
0 92 16126 16133
1 27 16134 16141
2 52 16141 16148
3 37 16149 16156
4 103 16156 16163
The stim_table lists stimulus times in terms of the start and end frames of the calcium traces, but we need start times and durations for neuroglia, so we’ll need to reshape
stim_table['time'] = timestamps[stim_table['start']]
stim_table['duration'] = timestamps[stim_table['end']+1] - stim_table['time']
print(stim_table.head())
Out:
frame start end time duration
0 92 16126 16133 545.22975 0.26537
1 27 16134 16141 545.49512 0.26538
2 52 16141 16148 545.72733 0.26537
3 37 16149 16156 545.99270 0.26538
4 103 16156 16163 546.22491 0.26538
Reduce the traces to responses
import numpy as np
from neuroglia.epoch import EpochTraceReducer
reducer = EpochTraceReducer(traces,func=np.mean)
X = reducer.fit_transform(stim_table)
y = stim_table['frame'].values
Do some dimensionality reduction on the responses
from sklearn.decomposition import PCA
pca = PCA()
X_reduced = pca.fit_transform(X)
Plot the first two Principal Components
import matplotlib.pyplot as plt
plt.scatter(X_reduced[:,0],X_reduced[:,1],c=y)
Total running time of the script: ( 8 minutes 35.657 seconds)