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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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System of Memory01:23

System of Memory

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Memory is categorized into three major systems: sensory memory, short-term memory (STM), and long-term memory (LTM). These systems differ in their capacity and the duration for which they can hold information. Sensory memory captures raw sensory input from the environment, holding it for just a few seconds or less. For example, on hearing a brief, loud sound, like a car horn honking, the sound seems to linger in the mind for a moment even after it stops. This is an instance of sensory memory...
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Working Memory01:24

Working Memory

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Working memory refers to a combination of components, including short-term memory and attention, that allow an individual to hold information temporarily as we perform cognitive tasks. It is an essential cognitive function that enables the execution of complex tasks such as problem-solving, comprehension, and reasoning. Unlike short-term memory, which simply involves the storage of information for a brief period, working memory involves the active manipulation and processing of this...
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Avoidance Learning and Learned Helplessness01:14

Avoidance Learning and Learned Helplessness

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Avoidance learning and learned helplessness are critical concepts in understanding behavioral responses to negative stimuli.
Avoidance learning occurs when an organism learns that a specific behavior can prevent an unpleasant outcome. For example, a student who receives a bad grade may start studying harder to avoid future poor grades. This behavior persists even when the negative outcome is no longer present. Avoidance learning is powerful because it maintains behavior in the absence of the...
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Long-Term Memory01:18

Long-Term Memory

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Long-term memory is a relatively permanent type of memory, capable of storing vast amounts of information over extended periods. Its storage capacity is generally considered unlimited.
Long-term memory can be categorized into two primary types: explicit and implicit memory. Explicit memory, also known as declarative memory, involves the conscious recollection of information that we deliberately try to remember, recall, and articulate. This type of memory encompasses specific facts, events, and...
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Traumatic Memory01:20

Traumatic Memory

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Emotionally traumatic events often lead to memories that are exceptionally vivid and enduring, sometimes persisting with remarkable clarity throughout an individual's life. A classic example of this phenomenon is a person who survives a car accident. Even years later, they may recall every detail of the event with startling accuracy — the screeching of the tires, the jarring impact, and the acrid smell of burning rubber. Such vividness contrasts sharply with how an individual...
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Updated: Jan 21, 2026

Drosophila Courtship Conditioning As a Measure of Learning and Memory
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Generative Memory for Lifelong Learning.

Xin Su, Shangqi Guo, Tian Tan

    IEEE Transactions on Neural Networks and Learning Systems
    |August 10, 2019
    PubMed
    Summary
    This summary is machine-generated.

    This study introduces Generative Memory (GM) for artificial intelligence lifelong learning. GMNet, using a novel P-invariant learning method, enhances knowledge accumulation and recall for state-of-the-art performance.

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    Area of Science:

    • Artificial Intelligence
    • Machine Learning
    • Neural Networks

    Background:

    • Lifelong learning is essential for advanced AI systems to continuously acquire knowledge from sequential tasks.
    • Current systems struggle with managing an increasing number of domains and tasks.
    • Effective knowledge memorization and recall are key challenges in lifelong learning.

    Purpose of the Study:

    • To propose a novel memory module and learning system for efficient and effective lifelong learning in artificial intelligence.
    • To address the challenge of continuous knowledge accumulation in AI systems.
    • To achieve state-of-the-art performance in lifelong learning tasks.

    Main Methods:

    • Introduction of Generative Memory (GM) as a novel memory module.
    • Development of the GM Net (GMNet) lifelong learning system.
    • Proposal of a P-invariant learning method that uses data distribution memory instead of real data memory.

    Main Results:

    • GMNet demonstrates the ability to accurately and continuously accumulate learned experiences.
    • The P-invariant learning method enables efficient memory of data distributions.
    • GMNet achieves state-of-the-art performance on lifelong learning benchmarks.

    Conclusions:

    • Generative Memory (GM) and the P-invariant learning method provide an effective solution for lifelong learning in AI.
    • GMNet enhances the ability of AI systems to memorize and recall knowledge across sequential tasks.
    • The proposed approach represents a significant advancement in developing robust and adaptable artificial intelligence.