Quantum Model of Memory and Neural Information Processing

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This project is at its initial phase of development. This is completely alternative view of understanding of information processing and storage by the neural system. This approach dismisses classical understanding of information processing inferred from computational sciences to neuroscience. It creates a new idea of the neural system activity, as energetic “fingerprints” impressed “the information”. According to this new logic the information flow in the neural system as perturbations in the miniature electric fields (nanofields) energetic state , generating “information elementary particles”, infotrons, as brain analogs of “computer bits”, while the properties of the infotron can be described by a wave function. The new perception relies on postulates (P), new term definitions and two central hypotheses:

 

P1 (Definition of Infotron): Infotron is a discrete energetic state of the miniature electrical field (nanofield) in response to perturbation by input signal (neuronal energy quantum). Infotron is space-time limited, though not curbed to specific cellular structures, e.g. spines, synapses, neurons etc. Infotron is the NS minimal information unit, a brain analog of “bit” in computational sciences.

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P2 (Definition of Nanofield Wave Function, NWF): NWF is superposition of all electrical density distributions of nanofields at discrete energetic states, including ground state and perturbations by excitation/inhibition. NWF is spatially limited and is a function of input stimuli time evolution and intrinsic nanofield energetic fluctuation (Illustr.1). Infotron is NWF collapse to a specific energetic state in the space.

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P3 (Definition of neuroatom, NA): Infotrons generated by nanofields coherent perturbation, on a short distance, assemble into neuroatom (NA), coding the smallest meaningful information. NA identity is defined by specific rules of infotron association depending on the the involved NWFs state.  NA codes modality specific component of object. NA can be mapped to functional NN.

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P4 (Definition of Neuromolecule, NM): Coherent perturbation of modality specific NAs assembles in a long-distance connection into neuromolecules (NM), which may represents object or object interaction models in the brain.

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P5 (Definition of processing/storage and propagation subspaces of the NS): The NS includes two subspaces: energy propagating and storing/processing. NWF is storing/processing subspace. NWF collapse onto energetic state forms deterministic output, propagated as a neural energy quantum.

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P6 (Interaction of the background oscillations with the NS subspaces): Background oscillations associated with specific forms of brain activity may be involved in interference with the infotron and neural energy quanta, filtering information stream for storing and processing and creating time reference frame.

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P7 (Brain regions vs quantum theory of the NS): NAs are distributed in modality specific cortex, based on recurrent NNs (RNNs). NMs assembled by NAs connection may reside in the associative cortex, while the frontal cortex may have an executive shadow copy of NMs in the associative cortex. Hippocampus feedforwarding NN (FNN) creates spatial reference frames of encoded objects.  

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Primary hypothesis states that memory engram is an energetic fingerprint of nanofield coherent perturbations by combination of neural field quanta and background oscillation. Memory engram is an outcome of interference of multiple parallel input signals of any source with background rhythmic activity altering the NWF spacetime distribution and energetic state. The external source may reflect memory encoding, while the internal may echo memory retrieval or internal data processing.

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Secondary hypothesis states that memory is hierarchically organized from infotron to neuromolecule, while memory coding exhibits quantum behaviour, being probabilistic until the NWF collapses to a measurable state infotrons. In contrast to  McCulloch–Pitts (MCP) neuron32, due to NWF probabilistic nature, infotron properties are unpredictable even for identical inputs; hence, infotrons must be entangled to generate deterministic NA output, necessary hierarchic association into NM  to encode a memory chunk.

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In our Laboratory

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The project is at the initial stage.  

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Plans

Experimental support of the idea requires development of high density/resolution multi FET/LED array (HDMFLA) technology. While the technology already exists, it requires optimization and miniaturization to be capable to conduct recording necessary for substantiation of the project. Hence, on the current stage of the project we will create a proper theoretical model of the ideas proposed for computational simulations to provide support by mathematical formalization based on quantum mechanics paradigms. In parallel, we will collaborate with companies to optimize and adapt the necessary technology for building of the first HDMFLA platform. Once the platform is operating and the mathematical model provides formal foundation for correctness of the model, we will conduct quantum electrophysiological recording from recurrent and feedforwarding networks and test against quantum mechanical model.

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Projects

1. Development of quantum mechanics paradigm driven mathematical model of neural system for information processing and storage (M.Sc or Ph.D. student, mathematician and theoretical physicist, Q001)

2. Elucidation of the infotron properties and the rules of association into neuroatom in recurrent neural network (RNN) (Post-doctoral fellows, Q002)

3. Elucidation of the rules of neuroatom association into neuromolecules in the RNN and feedforward neural networks (FNN) within the context of the background rhythmic activity role (Post-doctoral fellows, Q003)