Patterns · 2023 · 77 citations · 71 references
Life SciencesComputer ScienceNeuroscienceArtificial IntelligenceCognitive NeuroscienceComputational NeuroscienceCognitive ArchitectureCognitive ModelingNeural EncodingNeural ModelingNeural NetworksSpiking Neural NetworksBrain OrganizationControl-software Co-designEmbedded Hardware Co-designHardware-software Co-optimizationNeural Network ModelingSimulation Of Brain StatesSpiking Network ArchitecturesSpiking Neural Network Models
Spiking neural networks (SNNs) serve as a promising computational framework for integrating insights from the brain into artificial intelligence (AI). Existing software infrastructures based on SNNs exclusively support brain simulation or brain-inspired AI, but not both simultaneously. To decode the nature of biological intelligence and create AI, we present the brain-inspired cognitive intelligence engine (BrainCog). This SNN-based platform provides essential infrastructure support for developing brain-inspired AI and brain simulation. BrainCog integrates different biological neurons, encoding strategies, learning rules, brain areas, and hardware-software co-design as essential components. Leveraging these user-friendly components, BrainCog incorporates various cognitive functions, including perception and learning, decision-making, knowledge representation and reasoning, motor control, social cognition, and brain structure and function simulations across multiple scales. BORN is an AI engine developed by BrainCog, showcasing seamless integration of BrainCog's components and cognitive functions to build advanced AI models and applications.
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Simple model of spiking neurons
Eugene M. Izhikevich · IEEE Transactions on Neural Networks · 2003 · 4.8K citations
Loihi: A Neuromorphic Manycore Processor with On-Chip Learning
Mike Davies, Narayan Srinivasa, Tsung-Han Lin et al. · IEEE Micro · 2018 · 3.7K citations
Engineering, Computer Engineering, Computational Neuroscience +16