navis.segregation_index¶
- navis.segregation_index(x)[source]¶
Calculate segregation index (SI).
The segregation index as established by Schneider-Mizell et al. (eLife, 2016) is a measure for how polarized a neuron is. SI of 1 indicates total segregation of inputs and outputs into dendrites and axon, respectively. SI of 0 indicates homogeneous distribution.
- Parameters:
x (NeuronList | list) –
Neuron to calculate segregation index (SI) for. If a NeuronList, will assume that it contains fragments (e.g. from axon/ dendrite splits) of a single neuron. If list, must be records containing number of pre- and postsynapses for each fragment:
[{'presynapses': 10, 'postsynapses': 320}, {'presynapses': 103, 'postsynapses': 21}]
Notes
From Schneider-Mizell et al. (2016): “Note that even a modest amount of mixture (e.g. axo-axonic inputs) corresponds to values near H = 0.5–0.6 (Figure 7—figure supplement 1). We consider an unsegregated neuron (H ¡ 0.05) to be purely dendritic due to their anatomical similarity with the dendritic domains of those segregated neurons that have dendritic outputs.”
- Returns:
H – Segregation Index (SI).
- Return type:
float