Biomedical
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.
The study aims to demonstrate how neurons can be connected to form flip-flops, the basic building blocks in sequential logic systems.
NFFs are explicit, dynamic networks that can generate known phenomena of short-term memory. Each network design includes all neurons, connections, and types of synapses, with neuron operation depending on minimal properties of excitation and inhibition.
NFFs exhibit characteristics associated with memory formation, retention, retrieval, termination, and errors. One neuron in each NFF produces all of these characteristics, and together with a neighboring neuron, they predict additional phenomena related to memory.
NFFs provide a framework for understanding how neurons can operate as functionally complete logic gates, both analog and digital, offering insights into the brain's processing of information.
Yoder's study introduces neural flip-flops (NFFs) as dynamic networks capable of generating phenomena associated with short-term memory. These NFFs
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Show by month | Manuscript | Video Summary |
---|---|---|
2025 April | 4 | 4 |
2025 March | 74 | 74 |
2025 February | 39 | 39 |
2025 January | 47 | 47 |
2024 December | 46 | 46 |
2024 November | 48 | 48 |
2024 October | 30 | 30 |
Total | 288 | 288 |