We argue that prediction success maximization is a basic objective of cognition and cortex,
that it is compatible with but distinct from prediction error minimization, that neither objective …

Pyramidal neurons have a pivotal role in the cognitive capabilities of neocortex. Though they
have been predominantly modeled as integrate-and-fire point processors, many of them …

Diverse types of inhibitory interneurons (INs) impart computational power and flexibility to
neocortical circuits. Whereas markers for different IN types in cortical layers 2–6 (L2–L6) …

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 …

GABA B receptors (GBRs) are G protein-coupled receptors for GABA, the main inhibitory
neurotransmitter in the brain. GBRs regulate fast synaptic transmission by gating Ca 2+ and …

Describing statistical dependencies is foundational to empirical scientific research. For
uncovering intricate and possibly nonlinear dependencies between a single target variable …

Inhibitory modulation of glutamatergic information processing is a prerequisite for proper
network function. Among the many groups of interneurons (INs), somatostatin-expressing …

Deep learning (DL) has big-data processing capabilities that are as good, or even better,
than those of humans in many real-world domains, but at the cost of high energy …

Electrical activity is considered a key driver for the neurochemical and morphological
maturation of neurons and the formation of neuronal networks. Designer receptors …

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 …