Exploring Virtual and Biological Neural Networks

In summary, the conversation discusses the potential impact of adding more virtual neurons in virtual neural networks on the network's performance in recognizing patterns. It also questions whether this same concept applies to biological neural networks and if there have been any experiments done to verify this. Additionally, the conversation considers if adding extra neurons in specific regions of a mouse's brain would improve its ability to navigate through a maze, but notes that there is currently no experimental evidence for this. It is also clarified that the correct term for these networks is artificial neural networks (ANNs).
  • #1
CuriousArv
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0
I'm a novice here..but in virtual neural networks, does adding more virtual neurons improve the performance of the network in terms of recognizing patterns? Has this been experimentally verified anywhere? Can you then make an analogy that the same would happen in a biological neural network? Or is the virtual neural network too different to a biological one?

For that matter, has anybody added appropriate neuron types in appropriate regions of an adult mice brain and observed how the mice now handled complex tasks such as navigation throught a maze or something?

For that matter, has anybody done an experiment where they deliberately added extra neurons to various regions in a mice's brain and observed whether this improved the mice's ability to navigate through a maze or something like that?
 
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  • #2
YES; YES; it would only be theoretical or hypothesis without experimental evidence; depends;

to my knowledge there are no experiments that have succeeded(or tried) to add neurons to an already existing brain. Then again i only read the cmoputational literature.

and the term is not virtual...its artificial neural networks(ANNs).
 
  • #3
In virtual neural networks, adding more virtual neurons can improve the performance of the network in terms of recognizing patterns. This has been experimentally verified in various studies and is a commonly used technique in deep learning models. The addition of more neurons allows the network to learn more complex patterns and improve its accuracy.

As for the analogy to biological neural networks, it is important to note that virtual neural networks are based on the structure and function of biological neural networks. However, they are not exact replicas and there are differences between the two. Therefore, the same principles may not always apply, but there is certainly a strong connection between the two.

To answer your question about experiments with adult mice, there have been studies where researchers have added specific neuron types in certain regions of the brain and observed changes in the mice's behavior. For example, in a study published in Nature Neuroscience, researchers added neurons to the hippocampus region of adult mice and observed improvements in their spatial memory and navigation skills.

In terms of deliberately adding extra neurons to improve a mouse's ability to navigate through a maze, there have been some studies in this area as well. One study published in the Journal of Neuroscience found that adding extra neurons in the cerebellum region of adult mice improved their motor skills and coordination.

Overall, while there have been some promising findings in terms of adding extra neurons to improve brain function in mice, more research is needed in this area. It is also important to consider that the brain is a complex system and simply adding more neurons may not always result in improved performance. Other factors such as the connections between neurons and the overall structure of the brain also play a crucial role.
 

1. What are virtual and biological neural networks?

Virtual neural networks are computer models that simulate the function and structure of biological neural networks in the brain. They are used in artificial intelligence and machine learning applications. Biological neural networks are the complex network of interconnected neurons in the brain that are responsible for processing and transmitting information.

2. How do virtual and biological neural networks differ?

Virtual neural networks are created and programmed by humans, while biological neural networks are a natural part of the human body. Virtual neural networks are also limited in their complexity and capabilities compared to biological neural networks, which are constantly evolving and adapting.

3. What is the purpose of exploring these networks?

The purpose of exploring virtual and biological neural networks is to better understand how the brain works and to use that knowledge to improve artificial intelligence and machine learning algorithms. It can also help us develop new treatments for neurological disorders and diseases.

4. What are the potential applications of virtual and biological neural networks?

Virtual neural networks can be used in a variety of applications such as image and speech recognition, natural language processing, and autonomous vehicles. Biological neural networks have a wide range of applications in the human body, including controlling movement, regulating emotions, and processing sensory information.

5. What are the ethical implications of exploring virtual and biological neural networks?

Exploring virtual and biological neural networks raises ethical concerns such as privacy, security, and the potential for creating artificial intelligence that could surpass human intelligence. It also raises questions about the responsibility and accountability for the actions of these networks and their potential impact on society.

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