Description: The simulation of neuroplasticity refers to the brain’s ability to reorganize itself by forming new neural connections in response to experience, learning, or injury. This phenomenon is fundamental for cognitive development and adaptation to changes in the environment. Neuroplasticity allows the brain not only to recover from damage but also to enhance its functioning through practice and repetition. In the context of artificial intelligence, the simulation of neuroplasticity involves the use of algorithms and computational models that mimic this biological process, enabling machines to learn and adapt similarly to the human brain. This simulation may include the creation of artificial neural networks that adjust their connections based on the information they receive, thus replicating human learning. The relevance of this simulation lies in its potential to improve artificial intelligence, making systems more flexible and capable of solving complex problems more efficiently. Additionally, the simulation of neuroplasticity can contribute to the understanding of neurological disorders and the development of innovative treatments by providing a framework to study how neural connections can be modified or restored.
