Research Topic

The Non-Learning Plasticity Hypothesis: Computational models, programmability, re-use and neuromodulation

About this Research Topic

In recent years there is increasing evidence that brain areas with a fixed connectivity are capable of exhibiting rapid and reversible behavioral/functional changes. This form of functional plasticity appears to be the outcome of mechanisms that are quite different from standard brain learning mechanisms such as Hebbian learning. This Non-Learning Plasticity Hypothesis (NLPH) contrasts with strongly localizationist hypotheses about brain functions which, in their extreme forms, posit a one-to-one relation between special-purpose brain areas and behaviors/functions. In accordance with this novel view of brain plasticity suggested by NLPH, several authors have proposed theories or exhibited experimental evidence in which brain areas can be controlled by other parts of the brain (programmability), are used in different brain circuits (re-use), or perform different tasks under different contextual conditions (neuromodulation).

Programmability
Local brain circuits, or networks of local brain circuits, endowed with a programming capability, without changing connectivity or efficacies associated with the synaptic connections, are hypothesized to exhibit on-the-fly qualitative behavioral changes caused and controlled by special (programming) inputs which encode different brain circuits and are provided as output of other brain circuits. However, if the brain tissue might be endowed with a real programming capability and what are the possible underlying neural mechanisms is an open issue.

Re-use
Low-level neural circuits can be used and reused for various purposes by other neural circuits in different task categories and cognitive domains. However, the understanding of how neural reuse is actually implemented in the brain leads to a number of open issues which include: How can a specific routing of connections be selectively enabled within reactivity times, if the connections are fixed? How can the same reused areas exhibit qualitatively different input/output behaviors when inserted in different circuits?

Neuromodulation
In addition to being determined by classical inter-neuronal connectivity, the dynamics of neural circuits is strongly influenced by neuromodulators. These substances are typically located in the extracellular fluid, alter the dynamics of neural circuits by selectively changing their structural parameters, but usually leave unaltered inter-neuronal connectivity diagrams, inducing rapid and usually reversible changes in the structural and functional characteristics of neural circuits. However, it is worth emphasizing that models proposed in the literature do not explicitly address several issues such as functional soundness and robustness of modulatory effects.

This research topic is aimed at understanding these neuronal aspects and their interplay from a double perspective: developing new theories and computational models of neural population dynamics, and developing intelligent and adaptable artificial systems. Indeed, mechanisms underlying this neuronal ability can provide new insights for duplicating in artificial systems the capability of those biological organisms to change their sensory-motor patterns under environmental pressure.

Suggested topics include, but are not limited to:
- Computational models of neural circuits subject to neuromodulator actions by artificial neural networks
- Re-use in artificial neural networks aimed at investigating re-use in brain neural circuits.
- Computational models of brain neural circuits endowed with programming capability
- Brain theories about NLPH
- Multi-task learning in artificial neural networks inspired by NLPH
- Adaptive behavior of artificial agents inspired by NLPH
- Artificial neural networks inspired from neuromodulator functionalities
- Artificial neural networks endowed with programmer-interpreter modules inspired by NLPH
- Artificial neural network models inspired by NLHP for sensory-motor controls


Keywords: Programming, Reuse, Neuromodulation, Multitask, Neural Circuits


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.

In recent years there is increasing evidence that brain areas with a fixed connectivity are capable of exhibiting rapid and reversible behavioral/functional changes. This form of functional plasticity appears to be the outcome of mechanisms that are quite different from standard brain learning mechanisms such as Hebbian learning. This Non-Learning Plasticity Hypothesis (NLPH) contrasts with strongly localizationist hypotheses about brain functions which, in their extreme forms, posit a one-to-one relation between special-purpose brain areas and behaviors/functions. In accordance with this novel view of brain plasticity suggested by NLPH, several authors have proposed theories or exhibited experimental evidence in which brain areas can be controlled by other parts of the brain (programmability), are used in different brain circuits (re-use), or perform different tasks under different contextual conditions (neuromodulation).

Programmability
Local brain circuits, or networks of local brain circuits, endowed with a programming capability, without changing connectivity or efficacies associated with the synaptic connections, are hypothesized to exhibit on-the-fly qualitative behavioral changes caused and controlled by special (programming) inputs which encode different brain circuits and are provided as output of other brain circuits. However, if the brain tissue might be endowed with a real programming capability and what are the possible underlying neural mechanisms is an open issue.

Re-use
Low-level neural circuits can be used and reused for various purposes by other neural circuits in different task categories and cognitive domains. However, the understanding of how neural reuse is actually implemented in the brain leads to a number of open issues which include: How can a specific routing of connections be selectively enabled within reactivity times, if the connections are fixed? How can the same reused areas exhibit qualitatively different input/output behaviors when inserted in different circuits?

Neuromodulation
In addition to being determined by classical inter-neuronal connectivity, the dynamics of neural circuits is strongly influenced by neuromodulators. These substances are typically located in the extracellular fluid, alter the dynamics of neural circuits by selectively changing their structural parameters, but usually leave unaltered inter-neuronal connectivity diagrams, inducing rapid and usually reversible changes in the structural and functional characteristics of neural circuits. However, it is worth emphasizing that models proposed in the literature do not explicitly address several issues such as functional soundness and robustness of modulatory effects.

This research topic is aimed at understanding these neuronal aspects and their interplay from a double perspective: developing new theories and computational models of neural population dynamics, and developing intelligent and adaptable artificial systems. Indeed, mechanisms underlying this neuronal ability can provide new insights for duplicating in artificial systems the capability of those biological organisms to change their sensory-motor patterns under environmental pressure.

Suggested topics include, but are not limited to:
- Computational models of neural circuits subject to neuromodulator actions by artificial neural networks
- Re-use in artificial neural networks aimed at investigating re-use in brain neural circuits.
- Computational models of brain neural circuits endowed with programming capability
- Brain theories about NLPH
- Multi-task learning in artificial neural networks inspired by NLPH
- Adaptive behavior of artificial agents inspired by NLPH
- Artificial neural networks inspired from neuromodulator functionalities
- Artificial neural networks endowed with programmer-interpreter modules inspired by NLPH
- Artificial neural network models inspired by NLHP for sensory-motor controls


Keywords: Programming, Reuse, Neuromodulation, Multitask, Neural Circuits


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.

About Frontiers Research Topics

With their unique mixes of varied contributions from Original Research to Review Articles, Research Topics unify the most influential researchers, the latest key findings and historical advances in a hot research area! Find out more on how to host your own Frontiers Research Topic or contribute to one as an author.

Topic Editors

Loading..

Submission Deadlines

15 February 2021 Abstract
15 July 2021 Manuscript

Participating Journals

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

Loading..

Topic Editors

Loading..

Submission Deadlines

15 February 2021 Abstract
15 July 2021 Manuscript

Participating Journals

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

Loading..
Loading..

total views article views article downloads topic views

}
 
Top countries
Top referring sites
Loading..