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Neuromorphic Correlates of Artificial Consciousness

arXiv 2405.02370 ↗First posted 3 May 2024cs.AI eess.SPcited by 0

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Abstract (arXiv)

The concept of neural correlates of consciousness (NCC), which suggests that specific neural activities are linked to conscious experiences, has gained widespread acceptance. This acceptance is based on a wealth of evidence from experimental studies, brain imaging techniques such as fMRI and EEG, and theoretical frameworks like integrated information theory (IIT) within neuroscience and the philosophy of mind. This paper explores the potential for artificial consciousness by merging neuromorphic design and architecture with brain simulations. It proposes the Neuromorphic Correlates of Artificial Consciousness (NCAC) as a theoretical framework. While the debate on artificial consciousness remains contentious due to our incomplete grasp of consciousness, this work may raise eyebrows and invite criticism. Nevertheless, this optimistic and forward-thinking approach is fueled by insights from the Human Brain Project, advancements in brain imaging like EEG and fMRI, and recent strides in AI and computing, including quantum and neuromorphic designs. Additionally, this paper outlines how machine learning can play a role in crafting artificial consciousness, aiming to realise machine consciousness and awareness in the future.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 1 of its 26 references that are in the map. First posted on arXiv 3 May 2024.

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  1. 2022Linear Leaky-Integrate-and-Fire Neuron Model Based Spiking Neural Networks and Its Mapping Relationship to Deep Neural Networkscited by 8

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