An Instance of Coincidence Detection Architecture Relying on Temporal Coding

Abstract

Although time and space are interrelated in every occurrence of real-world events, only spatial codes are used at the basic level of most computational architectures. Inspired by neurobiological facts and hypotheses that assign a primordial coding role to the temporal dimension, and developed to address both cognitive and engineering applications, guided propagation networks (GPNs) are aimed at a generic real-time machine, based on time-space coincidence testing. The involved temporal parameters are gradually introduced, in relation with complementary applications in the field of human-machine communication: sensori-motor modeling, pattern recognition and natural language processing.

A Functional Model of Fast Action Selection Guided by Emotional Stimuli

“…Within a high-level 'behavioral module' , a memory path can code for the representation of alternating stimuli and actions, as initially proposed for problem solving tasks [40]. More detailed descriptions of the GP formalism can be found in the annexed S2 document, as well as in several reports in which applications of this approach are introduced [41].…”

“…In a more complete architecture, each series of characters forming the current GPS input/output would stand at the interface with more peripheral levels in charge of identifying or generating the patterns represented by these characters. This low-level capacity of GP has been explored in previous studies [41] and stays beyond the scope of the present work focused on associative levels. Patterns of the labelled DE's below are considered as non-ambiguous and are therefore coded in a binary format (either 0 or A max ).…”