The nature of quantum parallel processing and its implications for coding in brain neural networks: a novel computational mechanism
Andrew S Johnson, William Winlow

TL;DR
This paper proposes a novel quantum mechanical soliton pulse, called APPulse, as the primary computational mechanism in neural networks, challenging traditional electrical models and Turing-based computation.
Contribution
It introduces the concept of quantum non-electrical soliton pulses (APPulse) as the main neural computational event, diverging from classical electrical action potential models.
Findings
APPulse is a quantum mechanical soliton pulse involved in neural computation.
APPulse operates at microsecond frequencies, faster than traditional electrical signals.
The proposed mechanism is incompatible with Turing-based computation and AI models.
Abstract
Conventionally it is assumed that the nerve impulse is an electrical process based upon the observation that electrical stimuli produce an action potential as defined by Hodgkin Huxley (1952) (HH). Consequently, investigations into the computation of nerve impulses have almost universally been directed to electrically observed phenomenon. However, models of computation are fundamentally flawed and assume that an undiscovered timing system exists within the nervous system. In our view it is synchronisation of the action potential pulse (APPulse) that effects computation. The APPulse, a soliton pulse, is a novel purveyor of computation and is a quantum mechanical pulse: i.e. It is a non-Turing synchronised computational event. Furthermore, the APPulse computational interactions change frequencies measured in microseconds, rather than milliseconds, producing effective efficient…
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