Variable Binding through Assemblies in Spiking Neural Networks

Robert Legenstein, Christos H. Papadimitriou, Santosh S. Vempala, Wolfgang Maass

Research output: Chapter in Book/Report/Conference proceedingConference paperpeer-review


We propose a model for the binding of variables to concrete fillers in the human
brain. The model is based on recent experimental data about corresponding neural processes in humans. First, electrode recordings from the human brain suggest that concepts are represented in the medial temporal lobe (MTL) through sparse sets of neurons (assemblies). Second, fMRI recordings from the human brain suggest that specific subregions of the temporal cortex are dedicated to the representation of specific roles (e.g., subject or object) of concepts in a sentence or visually presented episode. We propose that quickly recruited assemblies of neurons in these subregions act as pointers to previously created assemblies that represent concepts. As a proof of principle, we performed computer simulations of a spiking neural network model that implemented the proposed paradigm for binding
through assembly pointers. We show that the model supports basic operations of brain computations, such as structured recall and copying of information
Original languageEnglish
Title of host publicationCEUR Workshop Proceedings
Number of pages6
Publication statusPublished - 2016
EventCoCo@NIPS 2016 - Barcelona, Spain
Duration: 9 Dec 2016 → …


ConferenceCoCo@NIPS 2016
Period9/12/16 → …


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