About this Research Topic
Artificial Deep Neural Networks (DNNs) have made breakthrough progress in recent years based on loose structural similarity to the brain. How seemingly intelligent performance is achieved remains fundamentally distinct from the human brain.
This Research Topic is launched in conjunction with the second Neuro-inspired Computation course held at the University of Tokyo International Center for Neurointelligence (July 16-19, 2024). All course participants are strongly encouraged to submit their work to the Research Topic; while the Topic is also open to non-conference attendees who would be interested.
As biological and artificial intelligence have much to learn from each other, we welcome all article types including research reports, method papers, perspectives, reviews, and case reports related to studying the aspects of structure, function and development of both biological and artificial neural networks.
This editorial project focuses on the interface of neuro-inspired computation, Neurointelligence. It spans broad areas of mutual interest to both communities, like network architectures, intrinsic dynamics, plasticity & criticality, multi-agent (social) learning, neuromodulation or reinforcement learning.
The collection of papers aims to capture the expanding global excitement in this innovative research frontier where neuronal network function in nature and in silico converge.
To this aim we welcome articles addressing, but not limited to:
• network architectures
• intrinsic dynamics
• E-I balance
• Homeostasis
• plasticity & criticality
• multi-agent (social) learning
• reinforcement learning
• neuromodulation
This Research Topic is launched in conjunction with the second Neuro-inspired Computation course held at the University of Tokyo International Center for Neurointelligence (July 16-19, 2024). All course participants are strongly encouraged to submit their work to the Research Topic; while the Topic is also open to non-conference attendees who would be interested.
As biological and artificial intelligence have much to learn from each other, we welcome all article types including research reports, method papers, perspectives, reviews, and case reports related to studying the aspects of structure, function and development of both biological and artificial neural networks.
This editorial project focuses on the interface of neuro-inspired computation, Neurointelligence. It spans broad areas of mutual interest to both communities, like network architectures, intrinsic dynamics, plasticity & criticality, multi-agent (social) learning, neuromodulation or reinforcement learning.
The collection of papers aims to capture the expanding global excitement in this innovative research frontier where neuronal network function in nature and in silico converge.
To this aim we welcome articles addressing, but not limited to:
• network architectures
• intrinsic dynamics
• E-I balance
• Homeostasis
• plasticity & criticality
• multi-agent (social) learning
• reinforcement learning
• neuromodulation
Keywords: A.I., neural networks, brain development, plasticity, learning, homeostasis, dynamics
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.
