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Neural network pioneers in history: Why are Bain and James' theories so crucial?
The study of neural networks has not only promoted our understanding of biological nervous systems, but also stimulated the development of artificial intelligence. Among them, the theories of Alexander Bain and William James are like valuable cornerstones, which have had a profound impact on our contemporary way of thinking. These theories explain how neurons in the brain interact to form behaviors and memories, paving the way for today's neuroscience and artificial intelligence.
Biological neural networks consist of interconnected neurons that can interact chemically or functionally. Each neuron can be connected to many other neurons, and the number of neurons and connections within a neural network can be very large.
Basic concepts of neural networks
The core of biological neural networks lies in the connections between neurons, called synapses, which are usually connected by axons to dendrites. This connection mechanism enables neurons to diffuse electrical signals and neurotransmitters, thereby transmitting information. The operation of these biological networks has also inspired the creation of artificial neural networks, a class of models inspired by how biological nervous systems process data.
Historical background: Bain and James’ contributionsArtificial neural networks have been successfully applied to speech recognition, image analysis and adaptive control, and are widely used in computers and robots.
In the early days of studying neural networks, Bain and James both thought deeply about the relationship between neuronal connections and behavior. Bain believed that every action would trigger the firing of specific neurons. As the behavior is repeated, the connections between these neurons strengthen, forming a memory. Although the scientific community was skeptical at the time, research today has proven that although the brain's structure is very complex, the same "wiring" is able to handle a variety of problems.
William James's theory proposed that memories and actions are caused by electrical currents flowing between neurons in the brain. This idea does not require separate neural connections for every memory or action.
The development and current status of neuroscience
At its core, neuroscience is the construction of models that reflect how biological systems work. This field encompasses theoretical and computational neuroscience, aiming to establish connections between observed biological processes (data), biologically plausible neural processing and learning mechanisms (neural network models), and theory (statistical learning theory and information theory).
Current research not only focuses on the electrical properties of neurons, but also explores the effects of neuromodulators such as dopamine, acetylcholine, and serotonin on behavior and learning.
Models and Connectivity
In neuroscience, many different models are used to describe various aspects of the nervous system, starting from the short-term behavior of individual neurons all the way up to complete subsystems represented by abstract neural modules. These models help researchers understand long-term and short-term plasticity of the nervous system and its relationship to learning and memory.
A 2020 study showed that by adding appropriate feedback connections, bidirectional connections can significantly accelerate and improve communication between neural networks in cerebral cortical modules, lowering the threshold for successful communication. This discovery reveals the complexity of connections in neural networks and highlights the need for further exploration of the architecture and computational properties of neural systems.
Conclusion
Bain and James' theory not only continues to this day, but also becomes an important foundation for neural network research. With the continuous development of science and technology, the relationship between artificial neural networks, as a simplified model of the biological nervous system, and brain function remains a controversial topic. In the future, will these historical explorations lead us to discover deeper cognitive secrets?
