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Related Concept Videos

Long-term Potentiation01:25

Long-term Potentiation

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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...
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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.
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A postsynaptic neuron usually receives numerous impulses from several other presynaptic neurons. The axon hillock of the postsynaptic neuron integrates all these signals and determines the likelihood of firing an action potential.
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Graded Potential01:19

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Graded potentials are localized fluctuations in the cell membrane's electrical charge, commonly found in the dendrites of neurons. The magnitude of these potential changes depends on the strength of the initiating stimulus. In a membrane at its resting potential, a graded potential signifies a voltage shift either above -70 mV or below -70 mV.
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Integration of Synaptic Events01:28

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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...
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Related Experiment Video

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Optical Recording of Suprathreshold Neural Activity with Single-cell and Single-spike Resolution
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Adaptive Spike Threshold Enables Robust and Temporally Precise Neuronal Encoding.

Chao Huang1,2, Andrey Resnik2, Tansu Celikel1

  • 1Department of Neurophysiology, Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, the Netherlands.

Plos Computational Biology
|June 16, 2016
PubMed
Summary
This summary is machine-generated.

An adaptive spike threshold enhances neural computation by improving stimulus discrimination and ensuring robust information transmission across brain states, even with correlated inputs. This reduces information loss during intracellular processing.

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Area of Science:

  • Neuroscience
  • Computational Neuroscience

Background:

  • Neural information processing relies on translating synaptic inputs into action potentials, governed by a dynamic spike threshold.
  • Recent findings show subthreshold membrane potential influences spike threshold, with implications for neural computation yet to be fully understood.

Purpose of the Study:

  • To investigate the computational consequences of an adaptive spike threshold, particularly its impact on stimulus discrimination and information transmission under correlated inputs.

Main Methods:

  • Neural simulations
  • Whole-cell intracellular recordings
  • Information-theoretic analysis

Main Results:

  • An adaptive spike threshold improves stimulus discrimination, especially with tightly correlated inputs, regardless of spike encoding (rate or pattern).
  • Input selectivity timescales are jointly determined by membrane and threshold dynamics.
  • Adaptive thresholds ensure robust information transmission across cortical states, reducing state-dependent decoding errors.

Conclusions:

  • Adaptive spike thresholds minimize information loss in intracellular transfer.
  • They enhance stimulus discriminability and guarantee robust decoding across membrane states for correlated inputs.
  • Findings align with sensory information encoding in sensory nuclei.