Assembly projections support the assignment of thematic roles to concepts in networks of spiking neurons

Currently existing neural network models lack an important computational capability of networks of neurons in the brain: the capability to reason on an abstract level, and to structure information according to abstract categories. While hardly anything is known about the processes underlying these capabilities in the human brain, experimental evidence for the organization of an important prerequisite for abstract reasoning has recently been found: for assigning words to thematic roles, such as subject or object. Such data from fMRI recordings indicate that assemblies in subregions of temporal cortex which encode thematic roles are shaped by concepts that are assigned to that role. We propose a model for the assignment of thematic content to variables that is consistent with these data and provides new functions to neural network computations. We provide a proof of principle that this model can be implemented even in networks of spiking neurons. It enables structured information retrieval and copying of information without routing, and provides a basis for the emulation of more demanding cognitive computations in networks of spiking neurons.