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Related Concept Videos

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.
Long-term Potentiation01:35

Long-term Potentiation

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.
Long-term Potentiation01:25

Long-term Potentiation

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...
Integration of Synaptic Events01:28

Integration of Synaptic Events

Synaptic integration mainly includes the summation of graded potentials. Graded potentials, regardless of their type, cause subtle alterations in membrane voltage, resulting in either depolarization or hyperpolarization. These incremental changes, when combined or summed, can propel the neuron toward its threshold. Consider, for example, a membrane experiencing a +15 mV shift, causing it to depolarize from -70 mV to -55 mV. In this scenario, graded potentials govern the membrane's ability to...
Neural Regulation01:37

Neural Regulation

Digestion begins with a cephalic phase that prepares the digestive system to receive food. When our brain processes visual or olfactory information about food, it triggers impulses in the cranial nerves innervating the salivary glands and stomach to prepare for food.
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Neural Circuits

Neural circuits and neuronal pools are two of the main structures found in the nervous system. Neural circuits are networks of neurons that work together to carry out a specific task or process. They consist of interconnected neurons and glial cells, which provide structural and metabolic support.
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Related Experiment Video

Updated: May 10, 2026

Real-time Electrophysiology: Using Closed-loop Protocols to Probe Neuronal Dynamics and Beyond
08:08

Real-time Electrophysiology: Using Closed-loop Protocols to Probe Neuronal Dynamics and Beyond

Published on: June 24, 2015

Resolution enhancement in neural networks with dynamical synapses.

C C Alan Fung1, He Wang, Kin Lam

  • 1Department of Physics, The Hong Kong University of Science and Technology Hong Kong, China.

Frontiers in Computational Neuroscience
|June 20, 2013
PubMed
Summary

Neuronal networks use population spikes, not just firing rates, to process information. This study shows how network dynamics enhance resolution for moving objects, improving information processing.

Keywords:
continuous attractor neural networkneural field modelshort-term synaptic depressionshort-term synaptic plasticitytransparent motion

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Related Experiment Videos

Last Updated: May 10, 2026

Real-time Electrophysiology: Using Closed-loop Protocols to Probe Neuronal Dynamics and Beyond
08:08

Real-time Electrophysiology: Using Closed-loop Protocols to Probe Neuronal Dynamics and Beyond

Published on: June 24, 2015

Super-Resolution Imaging to Study Co-Localization of Proteins and Synaptic Markers in Primary Neurons
14:02

Super-Resolution Imaging to Study Co-Localization of Proteins and Synaptic Markers in Primary Neurons

Published on: October 31, 2020

Area of Science:

  • Computational neuroscience
  • Neural network modeling
  • Information theory

Background:

  • Traditionally, neural information processing relies on spike rates.
  • Population spikes, arising from synaptic depression, offer additional information encoding.
  • Previous research on motion perception in monkeys highlights resolution changes.

Purpose of the Study:

  • To explore information encoding beyond spike rates in neuronal networks.
  • To investigate the role of temporally modulated activities (population spikes) in information processing.
  • To model resolution enhancement observed in motion perception experiments.

Main Methods:

  • Utilizing a neuronal network model with dynamical synapses.
  • Simulating network responses to multiple external inputs representing object motion.
  • Analyzing the emergence and impact of population spikes.

Main Results:

  • Temporally modulated activities, or population spikes, carry information beyond spike rates.
  • Synaptic depression in the model network generates these population spikes.
  • The model successfully reproduces resolution enhancement observed in macaque monkey experiments.

Conclusions:

  • Dynamical synapses enable neural networks to enhance information processing through population spikes.
  • Temporally modulated activities are crucial for improving resolution in complex sensory tasks.
  • This mechanism offers a new perspective on neural coding and information transmission.