From uncertainty and entropy to coherence and consciousness - Majid Beshkar (Brain-X)
Abstract Understanding the neural basis of consciousness remains a fundamental challenge in neuroscience. This study proposes a novel framework that conceptualizes consciousness through the lens of uncertainty reduction and negative entropy, emphasizing the role of coherence in its emergence. Sensory processing may operate as a Bayesian inference mechanism aimed at minimizing the brain's uncertainty regarding external stimuli, and conscious awareness emerges when uncertainty is reduced below a critical threshold. Computationally, this corresponds to minimizing informational uncertainty, while at a physical level it corresponds to reductions in thermodynamic entropy, thereby linking consciousness to negentropy. This study emphasizes the role of coherence in conscious perception and challenges existing models like Integrated Information Theory by exploring the potential contributions of quantum coherence and entanglement. Although direct empirical validation is currently lacking, we propose the hypothesis that consciousness acts as a cooling mechanism for the brain, as measured by the temperature of neuronal circuits. This perspective affords new insights into the physical and computational foundations of conscious experience and indicates a possible direction for future research in consciousness studies.