Modeling visual attention via selective tuning
Artificial Intelligence - Special volume on computer vision
Types and Quantifiers in SHRUTI: A Connectionist Model of Rapid Reasoning and Relational Processing
Hybrid Neural Systems, revised papers from a workshop
Memorization and Association on a Realistic Neural Model
Neural Computation
Marker-Passing inference in the scone knowledge-base system
KSEM'06 Proceedings of the First international conference on Knowledge Science, Engineering and Management
A dynamic binding mechanism for retrieving and unifying complex predicate-logic knowledge
ICANN'12 Proceedings of the 22nd international conference on Artificial Neural Networks and Machine Learning - Volume Part I
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To perform automatic, unconscious inference, the human brain must solve the binding problem by correctly grouping properties with objects. Temporal binding models like SHRUTI already suggest much of how this might be done in a connectionist and localist way by using temporal synchrony. We propose a set of alternatives to temporal synchrony mechanisms that instead use short signatures. This serves two functions: it allows us to explore an additional biologically plausible alternative, and it allows us to extend and improve the capabilities of these models. These extensions model the human ability to both perform unification and handle multiple instantiations of logical terms. To verify our model's feasibility, we simulate it with a computer system modeling simple, neuron-like computations.