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Related Concept Videos

Higher Mental Functions of Brain: Learning and Memory01:26

Higher Mental Functions of Brain: Learning and Memory

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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...
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Associative Learning01:27

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Associative learning is a fundamental concept in behavioral psychology, wherein a connection is established between two stimuli or events, leading to a learned response. This process is critical in understanding how behaviors are acquired and modified. Conditioning, the mechanism through which associations are formed, can be divided into two main types: classical conditioning and operant conditioning, each elucidating different aspects of associative learning.
Classical conditioning, also known...
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Real-World Application of Classical Conditioning01:15

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Classical conditioning not only includes the initial pairing of stimuli but also extends to more complex forms, such as higher-order conditioning. Higher-order conditioning involves creating associations beyond the primary conditioned stimulus, resulting in a chain of conditioned responses.
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Principles of Classical Conditioning01:23

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Classical conditioning, as described by Ivan Pavlov, is a foundational concept in associative learning, where a neutral stimulus becomes capable of eliciting a conditioned response through association with an unconditioned stimulus. The process of acquisition, where this learning occurs, and the subsequent phenomena of contiguity, contingency, generalization, discrimination, extinction, and spontaneous recovery are crucial for a comprehensive understanding of classical conditioning.
During the...
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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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Neural Circuits01:25

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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: Jun 22, 2025

Aversive Associative Learning and Memory Formation by Pairing Two Chemicals in Caenorhabditis elegans
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Artificial Multimodal Neuron with Associative Learning Capabilities: Acquisition, Extinction, and Spontaneous

Sangheon Kim1,2, Unhyeon Kang1,3, Jiyoung Gu1,4

  • 1Center for Neuromorphic Engineering, Korea Institute of Science and Technology, Seoul 02792, Rep. of Korea.

ACS Applied Materials & Interfaces
|July 1, 2024
PubMed
Summary

Researchers developed a novel artificial neuron device mimicking associative learning, including acquisition, extinction, and spontaneous recovery. This breakthrough in neuromorphic engineering offers energy-efficient solutions for artificial multimodal artificial intelligence (AMAI).

Keywords:
artificial neuronassociative learningclassical conditioningmultimodalneuromorphic device

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Area of Science:

  • Neuromorphic Engineering
  • Artificial Intelligence
  • Materials Science

Background:

  • Associative multimodal artificial intelligence (AMAI) faces significant computational and memory resource challenges.
  • Neuromorphic devices offer a promising solution for implementing classical conditioning with simplified circuitry.

Purpose of the Study:

  • To introduce a novel artificial multimodal neuron device capable of demonstrating associative learning behaviors.
  • To address the resource limitations in developing large-scale AMAI systems.

Main Methods:

  • The study utilizes an ovonic threshold switch (OTS)-based neuron device integrated with a conductive bridge memristor (CBM)-based synapse device.
  • The device incorporates passive electrical elements to facilitate associative learning functionalities.

Main Results:

  • The artificial neuron device successfully demonstrated associative learning, including acquisition, extinction, and spontaneous recovery behaviors for the first time.
  • Observed behaviors were explained by the electroforming process and metallic ion diffusion within the CBM.

Conclusions:

  • The developed associative learning neuron device represents a significant advancement in neuromorphic computing.
  • This innovation provides a pathway towards more energy-efficient large-scale AMAI systems.