Cognitive Architecture for Direction of Attention Founded on Subliminal Memory Searches, Pseudorandom and Nonstop

TL;DR

This paper proposes a cognitive architecture that models human associative memory using digital-like neurons, incorporating subliminal memory searches with pseudorandom cues to dynamically direct attention.

Contribution

It introduces a novel memory search mechanism using pseudorandom cues and subliminal analysis to determine attention direction in a brain-inspired architecture.

Findings

Memory searches can be conducted subliminally using pseudorandom cues.

The architecture models attention direction based on ongoing sensory and memory analysis.

Recalls and sensory images are processed at high speed to simulate human attention shifts.

Abstract

By way of explaining how a brain works logically, human associative memory is modeled with logical and memory neurons, corresponding to standard digital circuits. The resulting cognitive architecture incorporates basic psychological elements such as short term and long term memory. Novel to the architecture are memory searches using cues chosen pseudorandomly from short term memory. Recalls alternated with sensory images, many tens per second, are analyzed subliminally as an ongoing process, to determine a direction of attention in short term memory.