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Related Concept Videos

Long-term Potentiation

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...

Long-term Potentiation

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.

Neuroplasticity

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.

The Role of Ion Channels in Neuronal Computation

The Role of Ion Channels in Neuronal Computation

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.
Sometimes a single EPSP is strong enough to induce an action potential in the postsynaptic neuron. However, multiple presynaptic inputs must often create EPSPs around the same time for the postsynaptic neuron to be sufficiently depolarized to fire an action potential.

Graded Potential

Graded Potential

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.
Graded potentials fall into two categories: depolarizing and hyperpolarizing. Depolarizing graded potentials typically occur when sodium (Na+) or calcium...

Long-term Depression

Long-term Depression

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

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Related Experiment Video

Updated: May 7, 2026

Ex Vivo Optogenetic Interrogation of Long-Range Synaptic Transmission and Plasticity from Medial Prefrontal Cortex to Lateral Entorhinal Cortex

Ex Vivo Optogenetic Interrogation of Long-Range Synaptic Transmission and Plasticity from Medial Prefrontal Cortex to Lateral Entorhinal Cortex

Published on: February 25, 2022

Supervised spike-timing-dependent plasticity: a spatiotemporal neuronal learning rule for function approximation and

Jan-Moritz P Franosch¹, Sebastian Urban, J Leo van Hemmen

¹Google Switzerland GmbH, 8002 Zurich, Switzerland mail@franosch.org.

Neural Computation

|September 20, 2013

Summary

This summary is machine-generated.

Animals can learn from experience using supervised spike-timing-dependent plasticity (supervised STDP). This method trains sensory systems, like vision, by using other senses as a supervisor, enabling complex learning and input reconstruction.

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Published on: March 25, 2014

Area of Science:

Neuroscience
Computational Neuroscience
Machine Learning

Background:

Understanding how animals learn from sensory experience is a fundamental question in neuroscience.
The brain integrates information across multiple sensory modalities.
Spike-timing-dependent plasticity (STDP) is a biologically plausible mechanism for synaptic plasticity.

Purpose of the Study:

To investigate the potential of supervised spike-timing-dependent plasticity (supervised STDP) as a mechanism for cross-modal sensory learning.
To demonstrate that supervised STDP can enable one sensory system to learn from another.
To provide theoretical proof of supervised STDP's convergence and ability to reconstruct sensory input.

Main Methods:

Theoretical analysis of supervised STDP.
Mathematical modeling of synaptic weight dynamics.
Convergence analysis under general conditions.

Main Results:

Supervised STDP enables training of one sensory modality using another as a supervisor.
Complex time-dependent relationships between sensory inputs can be learned.
The model converges to a stable synaptic configuration that reconstructs primary sensory input.

Conclusions:

Supervised STDP offers a viable computational framework for cross-modal sensory learning in biological systems.
This learning mechanism allows for the reconstruction of sensory information based on inter-sensory relationships.
The findings support the role of STDP in complex sensory integration and experience-based learning.