{"title":"人脑启发的人工智能神经网络。","authors":"Paschalis Theotokis","doi":"10.31083/JIN26684","DOIUrl":null,"url":null,"abstract":"<p><p>It is becoming increasingly evident that Artificial intelligence (AI) development draws inspiration from the architecture and functions of the human brain. This manuscript examines the alignment between key brain regions-such as the brainstem, sensory cortices, basal ganglia, thalamus, limbic system, and prefrontal cortex-and AI paradigms, including generic AI, machine learning, deep learning, and artificial general intelligence (AGI). By mapping these neural and computational architectures, I herein highlight how AI models progressively mimic the brain's complexity, from basic pattern recognition and association to advanced reasoning. Current challenges, such as overcoming learning limitations and achieving comparable neuroplasticity, are addressed alongside emerging innovations like neuromorphic computing. Given the rapid pace of AI advancements in recent years, this work underscores the importance of continuously reassessing our understanding as technology evolves exponentially.</p>","PeriodicalId":16160,"journal":{"name":"Journal of integrative neuroscience","volume":"24 4","pages":"26684"},"PeriodicalIF":2.7000,"publicationDate":"2025-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Human Brain Inspired Artificial Intelligence Neural Networks.\",\"authors\":\"Paschalis Theotokis\",\"doi\":\"10.31083/JIN26684\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>It is becoming increasingly evident that Artificial intelligence (AI) development draws inspiration from the architecture and functions of the human brain. This manuscript examines the alignment between key brain regions-such as the brainstem, sensory cortices, basal ganglia, thalamus, limbic system, and prefrontal cortex-and AI paradigms, including generic AI, machine learning, deep learning, and artificial general intelligence (AGI). By mapping these neural and computational architectures, I herein highlight how AI models progressively mimic the brain's complexity, from basic pattern recognition and association to advanced reasoning. Current challenges, such as overcoming learning limitations and achieving comparable neuroplasticity, are addressed alongside emerging innovations like neuromorphic computing. Given the rapid pace of AI advancements in recent years, this work underscores the importance of continuously reassessing our understanding as technology evolves exponentially.</p>\",\"PeriodicalId\":16160,\"journal\":{\"name\":\"Journal of integrative neuroscience\",\"volume\":\"24 4\",\"pages\":\"26684\"},\"PeriodicalIF\":2.7000,\"publicationDate\":\"2025-03-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of integrative neuroscience\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.31083/JIN26684\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"NEUROSCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of integrative neuroscience","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.31083/JIN26684","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"NEUROSCIENCES","Score":null,"Total":0}
Human Brain Inspired Artificial Intelligence Neural Networks.
It is becoming increasingly evident that Artificial intelligence (AI) development draws inspiration from the architecture and functions of the human brain. This manuscript examines the alignment between key brain regions-such as the brainstem, sensory cortices, basal ganglia, thalamus, limbic system, and prefrontal cortex-and AI paradigms, including generic AI, machine learning, deep learning, and artificial general intelligence (AGI). By mapping these neural and computational architectures, I herein highlight how AI models progressively mimic the brain's complexity, from basic pattern recognition and association to advanced reasoning. Current challenges, such as overcoming learning limitations and achieving comparable neuroplasticity, are addressed alongside emerging innovations like neuromorphic computing. Given the rapid pace of AI advancements in recent years, this work underscores the importance of continuously reassessing our understanding as technology evolves exponentially.
期刊介绍:
JIN is an international peer-reviewed, open access journal. JIN publishes leading-edge research at the interface of theoretical and experimental neuroscience, focusing across hierarchical levels of brain organization to better understand how diverse functions are integrated. We encourage submissions from scientists of all specialties that relate to brain functioning.