A comparison of partial information decompositions using data from real and simulated layer 5b pyramidal cells
Jim W. Kay, Jan M. Schulz, W.A. Phillips

TL;DR
This study compares five partial information decomposition methods on real and simulated pyramidal cell data, revealing differences in synergy, shared, and unique information estimates, and supporting previous findings on dendritic inhibition effects.
Contribution
It systematically evaluates and contrasts multiple partial information decomposition methods using biological and simulated neural data, highlighting their differences and consistencies.
Findings
Two methods estimate higher synergy and shared information.
Most methods agree on the reduction of apical amplification by dendritic inhibition.
Decompositions support properties of cooperative context-sensitivity.
Abstract
Partial information decomposition allows the joint mutual information between an output and a set of inputs to be divided into components that are synergistic or shared or unique to each input. We consider five different decompositions and compare their results on data from layer 5b pyramidal cells in two different studies. The first study was of the amplification of somatic action potential output by apical dendritic input and its regulation by dendritic inhibition. We find that two of the decompositions produce much larger estimates of synergy and shared information than the others, as well as large levels of unique misinformation. When within-neuron differences in the components are examined, the five methods produce more similar results for all but the shared information component, for which two methods produce a different statistical conclusion from the others. There are some…
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