Neural flip-flops I: Short-term memory

Author:

Yoder LaneORCID

Abstract

The networks proposed here show how neurons can be connected to form flip-flops, the basic building blocks in sequential logic systems. The novel neural flip-flops (NFFs) are explicit, dynamic, and can generate known phenomena of short-term memory. For each network design, all neurons, connections, and types of synapses are shown explicitly. The neurons’ operation depends only on explicitly stated, minimal properties of excitement and inhibition. This operation is dynamic in the sense that the level of neuron activity is the only cellular change, making the NFFs’ operation consistent with the speed of most brain functions. Memory tests have shown that certain neurons fire continuously at a high frequency while information is held in short-term memory. These neurons exhibit seven characteristics associated with memory formation, retention, retrieval, termination, and errors. One of the neurons in each of the NFFs produces all of the characteristics. This neuron and a second neighboring neuron together predict eight unknown phenomena. These predictions can be tested by the same methods that led to the discovery of the first seven phenomena. NFFs, together with a decoder from a previous paper, suggest a resolution to the longstanding controversy of whether short-term memory depends on neurons firing persistently or in brief, coordinated bursts. Two novel NFFs are composed of two and four neurons. Their designs follow directly from a standard electronic flip-flop design by moving each negation symbol from one end of the connection to the other. This does not affect the logic of the network, but it changes the logic of each component to a logic function that can be implemented by a single neuron. This transformation is reversible and is apparently new to engineering as well as neuroscience.

Publisher

Public Library of Science (PLoS)

Reference39 articles.

1. Relative absorption model of color vision;L. Yoder;Color Research & Application,2005

2. Explicit Logic Circuits Discriminate Neural States;L. Yoder;PloS one,2009

3. Explicit logic circuits predict local properties of the neocortex’s physiology and anatomy;L. Yoder;PloS one,2010

4. Yoder L, inventor. Logic circuits with and-not gate for fast fuzzy decoders. United States patent US 9,684,873. 2017 Jun 20.

5. Yoder L, inventor. Systems and methods for brain-like information processing. United States patent US 8,655,797. 2014 Feb 18.

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