Hebbian Learning

What Is Hebbian Learning

The Hebbian theory is a neuropsychological theory that asserts that an improvement in synaptic efficacy results from the repetitive and persistent stimulation of a postsynaptic cell by a presynaptic cell. This is an effort to explain synaptic plasticity, which refers to the process through which neurons in the brain change in response to learning. It was first presented in Donald Hebb's book titled The Organization of Behavior, which was published in 1949. Hebb's rule, Hebb's postulate, and the cell assembly hypothesis are all names for the same body of thought. The way that Hebb expresses it is as follows: Let us assume that the persistence or repetition of a reverberatory action tends to create long-lasting cellular modifications that add to its stability…. When an axon of cell A is close enough to excite a cell B and takes part in firing it repeatedly or consistently, a growth process or metabolic change takes occur in one or both of the cells, which results in an increase in cell A's efficiency as one of the cells firing cell B. This can happen in either cell.

How You Will Benefit

(I) Insights, and validations about the following topics:

Chapter 1: Hebbian theory

Chapter 2: Chemical synapse

Chapter 3: Long-term potentiation

Chapter 4: Synaptic plasticity

Chapter 5: Long-term depression

Chapter 6: Spike-timing-dependent plasticity

Chapter 7: Neural circuit

Chapter 8: Metaplasticity

Chapter 9: Oja's rule

Chapter 10: BCM theory

(II) Answering the public top questions about hebbian learning.

(III) Real world examples for the usage of hebbian learning in many fields.

Who This Book Is For

Professionals, undergraduate and graduate students, enthusiasts, hobbyists, and those who want to go beyond basic knowledge or information for any kind of hebbian learning.

What Is Artificial Intelligence Series

The artificial intelligence book series provides comprehensive coverage in over 200 topics. Each ebook covers a specific Artificial Intelligence topic in depth, written by experts in the field. The series aims to give readers a thorough understanding of the concepts, techniques, history and applications of artificial intelligence. Topics covered include machine learning, deep learning, neural networks, computer vision, natural language processing, robotics, ethics and more. The ebooks are written for professionals, students, and anyone interested in learning about the latest developments in this rapidly advancing field.
The artificial intelligence book series provides an in-depth yet accessible exploration, from the fundamental concepts to the state-of-the-art research. With over 200 volumes, readers gain a thorough grounding in all aspects of Artificial Intelligence. The ebooks are designed to build knowledge systematically, with later volumes building on the foundations laid by earlier ones. This comprehensive series is an indispensable resource for anyone seeking to develop expertise in artificial intelligence.