Computational Neuroscience

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Synaptic plasticity

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Computational Neuroscience

Definition

Synaptic plasticity is the ability of synapses, the connections between neurons, to strengthen or weaken over time in response to increases or decreases in their activity. This phenomenon is fundamental for learning and memory, as it allows neural circuits to adapt and reorganize based on experiences. It is a key mechanism underlying various processes in the brain, including motor learning, the coordination of movements, and even pathological conditions like epilepsy.

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5 Must Know Facts For Your Next Test

  1. Synaptic plasticity can be short-term or long-term, affecting how information is processed and stored in the brain.
  2. The cerebellum utilizes synaptic plasticity to fine-tune motor skills through processes like motor learning, where practiced actions become smoother and more coordinated.
  3. In the motor cortex, synaptic plasticity allows for adjustments in motor commands and adaptations to new motor tasks.
  4. Travelling waves and pattern formation in neural networks can also be influenced by synaptic plasticity, contributing to how patterns of activity propagate across the brain.
  5. In conditions like epilepsy, abnormal synaptic plasticity can lead to excessive neuronal excitability, contributing to seizure dynamics.

Review Questions

  • How does synaptic plasticity contribute to motor learning and the refinement of movements?
    • Synaptic plasticity plays a crucial role in motor learning by allowing synapses in the cerebellum and motor cortex to strengthen or weaken based on experience. As an individual practices a movement, the corresponding neural pathways become more efficient through long-term potentiation, which enhances coordination and timing. This adaptability ensures that actions become smoother over time, highlighting how synaptic changes underpin skill acquisition and refinement.
  • Discuss the role of synaptic plasticity in pathological conditions like epilepsy and how it affects seizure dynamics.
    • In epilepsy, abnormal forms of synaptic plasticity can lead to excessive neuronal excitability and abnormal synchronization among neurons. This heightened state of readiness results in seizures, as the typical balance between excitation and inhibition is disrupted. Understanding how synaptic plasticity contributes to these dynamics can provide insights into potential therapeutic targets for managing epilepsy.
  • Evaluate the impact of synaptic plasticity on travelling waves in neural networks and its implications for pattern formation within the brain.
    • Synaptic plasticity influences how travelling waves propagate through neural networks by altering the strength of connections between neurons. This flexibility allows for dynamic adjustments in response to changing inputs or experiences, enabling complex pattern formations essential for cognitive functions. By evaluating these interactions, we can better understand how disruptions in synaptic plasticity might affect overall brain function and behavior, particularly in scenarios involving learning or adaptation.
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