Neuroscience

Bayesian brain theories and their link to quantum mechanics

Bayesian brain theories and their link to quantum mechanics

The Bayesian brain hypothesis frames the brain as a probabilistic machine, constantly updating predictions based on incoming sensory data. Emerging research explores striking parallels with quantum mechanics, suggesting that concepts like superposition and entanglement may offer deeper insights into perception, decision-making, and cognitive uncertainty, challenging traditional models and inspiring new approaches to understanding the dynamics of the mind.

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Relativity and quantum processes in the thinking brain

Relativity and quantum processes in the thinking brain

The boundaries between neuroscience and physics are blurring, revealing how concepts from relativity and quantum mechanics may shape the inner workings of the thinking brain. Emerging theories suggest that time perception, memory, and consciousness could stem from quantum entanglement, relativistic signal delays, and non-classical neural architectures, hinting at a reality where cognition arises from the universe’s most fundamental principles.

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Understanding quantum thought through mathematical frameworks

Understanding quantum thought through mathematical frameworks

Dissatisfaction with classical models of reasoning led researchers to explore quantum principles within cognitive science, offering novel explanations for paradoxical human behaviour. Quantum cognition, leveraging concepts like superposition, contextuality, and entanglement, challenges traditional Bayesian frameworks, providing dynamic models of decision-making, memory, and language. By embracing quantum mathematics, this emerging field captures the fluid, context-sensitive nature of thought, reshaping theories of human reasoning and inspiring advances in artificial intelligence, neuroscience, and mental health research.

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Mind mathematics and the Bayesian brain in quantum cognition

Mind mathematics and the Bayesian brain in quantum cognition

Advances in mathematics are reshaping theories of human cognition, moving beyond classical models of rationality to embrace probabilistic and context-dependent frameworks. The integration of Bayesian inference and quantum cognition offers powerful tools for modelling perception, decision-making, and belief updating, aligning more closely with empirical findings from neuroscience. Emerging hybrid models reveal the mind’s dynamic, adaptive nature, challenging traditional assumptions and opening new pathways for understanding the intricate processes underlying thought, memory, and judgement.

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Exploring the Intricacies of Time Perception Through Visual Cues

This article examines recent advances in understanding human time perception, focusing on how sensory inputs, particularly visual cues, influence our sense of time. Grounded in research led by cognitive neuroscientist Virginie van Wassenhove, the article discusses findings from studies that explore the impact of visual features such as scene complexity, clutter, and memorability on time perception. The research reveals that larger, less cluttered scenes tend to cause time dilation, while smaller, cluttered scenes induce time constriction. Additionally, images that are more memorable are perceived for longer durations, suggesting that memorability enhances time perception. These insights not only augment our comprehension of sensory processing but also hint at potential neural mechanisms underlying these phenomena. The article concludes with suggestions for future research directions, including the use of neuroimaging and the potential for artificial stimulation of brain processes to influence time perception and memory.

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