Research Topic

Molecule-Based Learning and Memory

About this Research Topic

The brain carries out complex cognitive and computing tasks by optimizing energy efficiency, information processing, and learning in massively parallel, dense networks of highly interconnected neurons. At the cellular level, synaptic plasticity and neuronal excitation are the main mechanisms underlying these processes—fundamental features that artificial neuromorphic systems seek to emulate. Early neuromorphic circuits utilized analog or software-controlled very-large-scale integration models, or hardware based on complementary metal-oxide semiconductor (CMOS) technology, to perform brain-inspired operations.

More recently two-terminal, solid-state devices with memory resistance, “memristors”, have emerged that are capable of synapse-like co-location of memory and processing. However, the brain is not a solid-state device but a highly interconnected and reconfigurable network of cells that communicate using a vast number of sophisticated molecular pathways. Molecular materials, which include both biomolecules and organic molecules that are not biological but that can function biomimetically, offer alternative routes to fault-tolerant computing circuits approaching the parallelism, energy-efficiency, and functional density of the brain. This Research Topic will cover topics that involve biomolecular and/or organic computing systems in the context of neural computing.

Topics include:

1. Molecule-based learning and memory mechanisms, including electrochemical redox reactions, charge trapping, ion channel/pore formation, and chemical recognition

2. Synthetic membrane-based (biomimetic) synapses

3. Biomolecular computing systems (DNA, proteins, etc.)

4. Artificial chemical and electrochemical synapses (not biomembrane-based)

5. Organic computing systems with focus on polymers

6. Choice of electrode material and interactions with molecules


Keywords: Biomembranes, Biophysics, Memory, Neuromorphic Computing, Smart Materials


Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.

The brain carries out complex cognitive and computing tasks by optimizing energy efficiency, information processing, and learning in massively parallel, dense networks of highly interconnected neurons. At the cellular level, synaptic plasticity and neuronal excitation are the main mechanisms underlying these processes—fundamental features that artificial neuromorphic systems seek to emulate. Early neuromorphic circuits utilized analog or software-controlled very-large-scale integration models, or hardware based on complementary metal-oxide semiconductor (CMOS) technology, to perform brain-inspired operations.

More recently two-terminal, solid-state devices with memory resistance, “memristors”, have emerged that are capable of synapse-like co-location of memory and processing. However, the brain is not a solid-state device but a highly interconnected and reconfigurable network of cells that communicate using a vast number of sophisticated molecular pathways. Molecular materials, which include both biomolecules and organic molecules that are not biological but that can function biomimetically, offer alternative routes to fault-tolerant computing circuits approaching the parallelism, energy-efficiency, and functional density of the brain. This Research Topic will cover topics that involve biomolecular and/or organic computing systems in the context of neural computing.

Topics include:

1. Molecule-based learning and memory mechanisms, including electrochemical redox reactions, charge trapping, ion channel/pore formation, and chemical recognition

2. Synthetic membrane-based (biomimetic) synapses

3. Biomolecular computing systems (DNA, proteins, etc.)

4. Artificial chemical and electrochemical synapses (not biomembrane-based)

5. Organic computing systems with focus on polymers

6. Choice of electrode material and interactions with molecules


Keywords: Biomembranes, Biophysics, Memory, Neuromorphic Computing, Smart Materials


Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.

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Submission Deadlines

19 August 2020 Abstract
25 November 2020 Manuscript

Participating Journals

Manuscripts can be submitted to this Research Topic via the following journals:

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Topic Editors

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Submission Deadlines

19 August 2020 Abstract
25 November 2020 Manuscript

Participating Journals

Manuscripts can be submitted to this Research Topic via the following journals:

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