10 papers analyzed
These studies suggest that attention involves complex processes and networks, including working memory, top-down control, competitive selection, and bottom-up filtering, and is influenced by neural circuitry, brain areas, and neuromodulation.
Attention is a multifaceted cognitive process that plays a crucial role in how humans and machines process information. It is studied across various disciplines, including psychology, neuroscience, and artificial intelligence, each offering unique insights into its mechanisms and applications.
Mechanistic Understanding of Attention:
Neural and Cognitive Frameworks:
Alternative Theories of Attention:
Attention in Artificial Intelligence:
Neuromodulation and Attention:
Shared Attention:
Attention is a complex and multi-dimensional process that is essential for both human cognition and artificial intelligence. It involves various neural and cognitive mechanisms, can be influenced by different factors, and has significant implications for both individual and shared experiences. Understanding attention from multiple perspectives, including mechanistic, neural, and theoretical frameworks, provides a comprehensive view that can inform future research and applications.
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