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Neuroplasticity01:01

Neuroplasticity

Neuroplasticity reflects the brain's remarkable capacity to adapt and evolve, responding dynamically to learning, experiences, or injury by reorganizing its neural circuitry. This reorganization involves creating new neural connections and refining old ones through a series of biological processes that contribute to the brain's lifelong development and adaptability.
Plasticity00:58

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Plasticity is the property where an object loses its elasticity and undergoes irreversible deformation, even after the deformation forces are eliminated. If a material deforms irreversibly without increasing stress or load, then this is called ideal plasticity. For example, when a force is applied to an aluminum rod, it changes its shape, but it does not return to its original shape once the force is removed. Plastic deformation or ductility is thus a permanent deformation or change in the...
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The cerebellum, while traditionally associated with motor control, also plays a crucial role in memory, particularly in procedural memory, which involves learning motor tasks that become automatic through repetition. For example, studies have shown that when the cerebellum is damaged, individuals or animals lose the ability to learn conditioned motor responses, such as the conditioned eye-blink response in classical conditioning experiments with rabbits. This study demonstrates the cerebellum's...
Long-term Potentiation01:25

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Long-term potentiation, or LTP, is one of the ways by which synaptic plasticity—changes in the strength of chemical synapses—can occur in the brain. LTP is the process of synaptic strengthening that occurs over time between pre and postsynaptic neuronal connections. The synaptic strengthening of LTP works in opposition to the synaptic weakening of long-term depression (LTD) and together are the main mechanisms that underlie learning and memory.
Hebbian LTP
LTP can occur when presynaptic neurons...
Long-term Potentiation01:35

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Long-term potentiation, or LTP, is one of the ways by which synaptic plasticity—changes in the strength of chemical synapses—can occur in the brain. LTP is the process of synaptic strengthening that occurs over time between pre- and postsynaptic neuronal connections. The synaptic strengthening of LTP works in opposition to the synaptic weakening of long-term depression (LTD) and together are the main mechanisms that underlie learning and memory.
Higher Mental Functions of Brain: Learning and Memory01:26

Higher Mental Functions of Brain: Learning and Memory

Memory is one of the most vital higher mental functions of the brain. Memory is closely related to learning because it enables us to retain information and experiences from our past to use them in our present life. It also helps us to remember facts, events, and skills, such as riding a bike or swimming. There are two types of memory — declarative memory, which involves memorizing facts or events, and procedural memory, which enables us to remember how to do something like writing or playing an...

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Study Motor Skill Learning by Single-pellet Reaching Tasks in Mice
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Cerebellar motor learning: when is cortical plasticity not enough?

John Porrill1, Paul Dean

  • 1Department of Psychology, Sheffield University, Sheffield, United Kingdom.

Plos Computational Biology
|October 31, 2007
PubMed
Summary

Classical cerebellar learning theories were challenged by new findings. Adding brainstem plasticity to models resolved limitations in learning high-frequency vestibulo-ocular reflex (VOR) gains, even with signal delays.

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Area of Science:

  • Neuroscience
  • Computational Neuroscience
  • Motor Control

Background:

  • Classical Marr-Albus theories propose cerebellar learning relies solely on cortical plasticity.
  • Experimental evidence suggests plasticity exists in both cerebellar cortex and brainstem during vestibulo-ocular reflex (VOR) calibration.
  • A conflict exists regarding the computational role of brainstem plasticity in VOR adaptation.

Purpose of the Study:

  • To investigate the computational role of brainstem plasticity in VOR calibration.
  • To model VOR calibration using an adaptive filter of the cerebellar microcircuit, accounting for oculomotor plant changes.
  • To resolve the conflict between classical theories and experimental findings on VOR plasticity sites.

Main Methods:

  • Utilized an adaptive filter model of the cerebellar microcircuit to simulate VOR calibration.
  • Introduced realistic delays (100 ms) in the retinal-slip error signal to test the impact of cortical plasticity alone.
  • Incorporated an additional brainstem plasticity site, driven by cerebellar and vestibular input correlation, to assess its effect on learning.

Main Results:

  • Cortical plasticity alone, with a 100 ms error signal delay, limited VOR learning to frequencies below 2.5 Hz.
  • The addition of brainstem plasticity overcame the frequency limitation, enabling accurate high-frequency VOR gain learning.
  • This 'cortex-first' learning mechanism aligns with flocculus function in VOR calibration and complements existing models.

Conclusions:

  • Information learned in the cerebellar cortex can be transferred and expressed in the brainstem.
  • A brainstem plasticity site is essential for Marr-Albus type models to achieve high-frequency VOR gain learning with signal delays.
  • The findings reconcile theoretical models with experimental observations of VOR adaptation.