A Partial Information Decomposition for Multivariate Gaussian Systems Based on Information Geometry.

There is much interest in the topic of partial information decomposition, both in developing new algorithms and in developing applications. An algorithm, based on standard results from information geometry, was recently proposed by Niu and Quinn (2019). They considered the case of three scalar random variables from an exponential family, including both discrete distributions and a trivariate Gaussian distribution.

A Comparison of Partial Information Decompositions Using Data from Real and Simulated Layer 5b Pyramidal Cells.

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 using data from layer 5b pyramidal cells in two different studies. The first study was on the amplification of somatic action potential output by apical dendritic input and its regulation by dendritic inhibition.

Within-participant statistics for cognitive science.

Experimental studies in cognitive science typically focus on the population average effect. An alternative is to test each individual participant and then quantify the proportion of the population that would show the effect: the prevalence, or participant replication probability. We argue that this approach has conceptual and practical advantages.

Bayesian inference of population prevalence.

Within neuroscience, psychology, and neuroimaging, the most frequently used statistical approach is null hypothesis significance testing (NHST) of the population mean. An alternative approach is to perform NHST within individual participants and then infer, from the proportion of participants showing an effect, the prevalence of that effect in the population. We propose a novel Bayesian method to estimate such population prevalence that offers several advantages over population mean NHST.

GABA Receptor-Mediated Regulation of Dendro-Somatic Synergy in Layer 5 Pyramidal Neurons.

Synergistic interactions between independent synaptic input streams may fundamentally change the action potential (AP) output. Using partial information decomposition, we demonstrate here a substantial contribution of synergy between somatic and apical dendritic inputs to the information in the AP output of L5b pyramidal neurons. Activation of dendritic GABA receptors (GABA Rs), known to decrease APs , potently decreased synergy and increased somatic control of AP output.

Exact Partial Information Decompositions for Gaussian Systems Based on Dependency Constraints.

The Partial Information Decomposition, introduced by Williams P. L. et al.

Partial information decomposition as a unified approach to the specification of neural goal functions.

In many neural systems anatomical motifs are present repeatedly, but despite their structural similarity they can serve very different tasks. A prime example for such a motif is the canonical microcircuit of six-layered neo-cortex, which is repeated across cortical areas, and is involved in a number of different tasks (e.g.

Intention perception in high functioning people with Autism Spectrum Disorders using animacy displays derived from human actions.

The perception of intent in Autism Spectrum Disorders (ASD) often relies on synthetic animacy displays. This study tests intention perception in ASD via animacy stimuli derived from human motion. Using a forced choice task, 28 participants (14 ASDs; 14 age and verbal-I.

Coherent Infomax as a computational goal for neural systems.

Signal processing in the cerebral cortex is thought to involve a common multi-purpose algorithm embodied in a canonical cortical micro-circuit that is replicated many times over both within and across cortical regions. Operation of this algorithm produces widely distributed but coherent and relevant patterns of activity. The theory of Coherent Infomax provides a formal specification of the objectives of such an algorithm.

Gender recognition from point-light walkers.

Point-light displays of human gait provide information sufficient to recognize the gender of a walker and are taken as evidence of the exquisite tuning of the visual system to biological motion. The authors revisit this topic with the goals of quantifying human efficiency at gender recognition. To achieve this, the authors first derive an ideal observer for gender recognition on the basis of center of moment (J.