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Postsynaptic Potential (PSP)

Postsynaptic Potential (PSP)

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Optical Control of a Neuronal Protein Using a Genetically Encoded Unnatural Amino Acid in Neurons

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Spiking Neural P Systems With Enzymes.

Xiang Tian, Xiyu Liu, Qianqian Ren

IEEE Transactions on Nanobioscience

|August 18, 2022

Summary

This study introduces spiking neural P systems with enzymes (SNPE) for modeling neurotransmitter synthesis. These SNPE systems demonstrate Turing universality and efficiently solve computational problems like the subset sum problem.

Area of Science:

Computational Neuroscience
Biomolecular Computing
Theoretical Computer Science

Background:

Neurotransmitters facilitate communication between neurons through synthesis, storage, release, and inactivation.
Acetylcholine synthesis involves enzymes like choline acetylase and acetylcholine coenzyme A.
Existing spiking neural P systems lack the biological realism of enzyme involvement in neuronal processes.

Purpose of the Study:

To propose a novel computational model, spiking neural P systems with enzymes (SNPE), inspired by enzyme-catalyzed neurotransmitter synthesis.
To investigate the computational power and applicability of SNPE systems in modeling biological processes and solving problems.

Main Methods:

Developed SNPE, a variant of spiking neural P systems, incorporating enzymes as key components in neuronal rules.

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Utilized enzyme presence and quantity as conditions for rule execution and reaction control within neurons.

Constructed an SNPE system with 61 neurons to demonstrate function computation and prove Turing universality.

Applied a uniform SNPE model to solve the subset sum problem for comparison with existing models.

Main Results:

SNPE systems were proven to be Turing universal, functioning as number generation and acceptance devices.
A 61-neuron SNPE system successfully performed function computation, confirming its computational universality.
The SNPE model showed promise in solving the subset sum problem, with comparative analysis against standard models.

Conclusions:

SNPE offers a biologically plausible computational framework for modeling enzyme-mediated neuronal processes.
The demonstrated Turing universality highlights the potential of SNPE for complex computations.
SNPE provides a novel approach for exploring computational problems with biologically inspired mechanisms.