Subscribe to the gold package and get unlimited access to Shamra Academy
Register a new userCan quantum physics help solve the hard problem of consciousness? A hypothesis based on entangled spins and photons
65
0
0.0
(
0
)
Authors
Christoph Simon
Ask ChatGPT about the research
No Arabic abstract
The hard problem of consciousness is the question how subjective experience arises from brain matter. I suggest exploring the possibility that quantum physics could be part of the answer. The simultaneous unity and complexity of subjective experience is difficult to understand from a classical physics perspective. In contrast, quantum entanglement is naturally both complex and unified. Moreover the concept of matter is much more subtle in quantum physics compared to classical physics, and quantum computing shows that quantum effects can be useful for information processing. Building on recent progress in quantum technology and neuroscience, I propose a concrete hypothesis as a basis for further investigation, namely that subjective experience is related to the dynamics of a complex entangled state of spins, which is continuously generated and updated through the exchange of photons. Spins in condensed matter systems at room or body temperature can have coherence times in the relevant range for subjective experience (milliseconds to seconds). Photons are well suited for distributing entanglement over macroscopic distances. Neurons emit photons, reactive oxygen species in the mitochondria being likely sources. Opsins, light-sensitive proteins that are plausible single-photon detectors, exist in the brain and are evolutionarily conserved, suggesting that they serve a function. We have recently shown by detailed numerical modeling that axons can plausibly act as photonic waveguides. The oxygen molecule, which has non-zero electronic spin and emits photons, might serve as an interface between photons and spins. The achievable photon rates seem to be more than sufficient to support the bandwidth of subjective experience. The proposed hypothesis raises many interesting experimental and theoretical questions in neuroscience, quantum physics, evolutionary biology, psychophysics, and philosophy.
rate research
Read More
Scientific studies of consciousness rely on objects whose existence is assumed to be independent of any consciousness. On the contrary, we assume consciousness to be fundamental, and that one of the main features of consciousness is characterized as being other-dependent. We set up a framework which naturally subsumes this feature by defining a compact closed category where morphisms represent conscious processes. These morphisms are a composition of a set of generators, each being specified by their relations with other generators, and therefore co-dependent. The framework is general enough and fits well into a compositional model of consciousness. Interestingly, we also show how our proposal may become a step towards avoiding the hard problem of consciousness, and thereby address the combination problem of conscious experiences.
In low-level sensory systems, it is still unclear how the noisy information collected locally by neurons may give rise to a coherent global percept. This is well demonstrated for the detection of motion in the aperture problem: as luminance of an elongated line is symmetrical along its axis, tangential velocity is ambiguous when measured locally. Here, we develop the hypothesis that motion-based predictive coding is sufficient to infer global motion. Our implementation is based on a context-dependent diffusion of a probabilistic representation of motion. We observe in simulations a progressive solution to the aperture problem similar to physio-logy and behavior. We demonstrate that this solution is the result of two underlying mechanisms. First, we demonstrate the formation of a tracking behavior favoring temporally coherent features independent of their texture. Second, we observe that incoherent features are explained away, while coherent information diffuses progressively to the global scale. Most previous models included ad hoc mechanisms such as end-stopped cells or a selection layer to track specific luminance-based features as necessary conditions to solve the aperture problem. Here, we have proved that motion-based predictive coding, as it is implemented in this functional model, is sufficient to solve the aperture problem. This solution may give insights into the role of prediction underlying a large class of sensory computations.
Mathematical approaches to modeling the mind since the 1950s are reviewed. Difficulties faced by these approaches are related to the fundamental incompleteness of logic discovered by K. Godel. A recent mathematical advancement, dynamic logic (DL) overcame these past difficulties. DL is described conceptually and related to neuroscience, psychology, cognitive science, and philosophy. DL models higher cognitive functions: concepts, emotions, instincts, understanding, imagination, intuition, consciousness. DL is related to the knowledge instinct that drives our understanding of the world and serves as a foundation for higher cognitive functions. Aesthetic emotions and perception of beauty are related to everyday functioning of the mind. The article reviews mechanisms of human symbolic ability, language and cognition, joint evolution of the mind, consciousness, and cultures. It touches on a manifold of aesthetic emotions in music, their cognitive function, origin, and evolution. The article concentrates on elucidating the first principles and reviews aspects of the theory proven in laboratory research.
We construct a complexity-based morphospace to study systems-level properties of conscious & intelligent systems. The axes of this space label 3 complexity types: autonomous, cognitive & social. Given recent proposals to synthesize consciousness, a generic complexity-based conceptualization provides a useful framework for identifying defining features of conscious & synthetic systems. Based on current clinical scales of consciousness that measure cognitive awareness and wakefulness, we take a perspective on how contemporary artificially intelligent machines & synthetically engineered life forms measure on these scales. It turns out that awareness & wakefulness can be associated to computational & autonomous complexity respectively. Subsequently, building on insights from cognitive robotics, we examine the function that consciousness serves, & argue the role of consciousness as an evolutionary game-theoretic strategy. This makes the case for a third type of complexity for describing consciousness: social complexity. Having identified these complexity types, allows for a representation of both, biological & synthetic systems in a common morphospace. A consequence of this classification is a taxonomy of possible conscious machines. We identify four types of consciousness, based on embodiment: (i) biological consciousness, (ii) synthetic consciousness, (iii) group consciousness (resulting from group interactions), & (iv) simulated consciousness (embodied by virtual agents within a simulated reality). This taxonomy helps in the investigation of comparative signatures of consciousness across domains, in order to highlight design principles necessary to engineer conscious machines. This is particularly relevant in the light of recent developments at the crossroads of cognitive neuroscience, biomedical engineering, artificial intelligence & biomimetics.
We have recognized that 2D codes, i.e., a group of strongly connected neurosomes that can be simultaneously excited, are the basic data carriers for memory in a brain. An echoing mechanism between two neighboring layers of neurosomes is assumed to establish temporary memory, and repeating processes enhance the formation of long-term memory. Creation and degradation of memory information are statistically. The maximum capacity of memory storage in a human brain is estimated to be one billion of 2D codes. By triggering one or more neurosomes in a neurosome-based 2D code, the whole strongly connected neurosome network is capable of exciting simultaneously and projecting its excitation onto an analysis layer of neurons in cortex, thus retrieving the stored memory data. The capability of comparing two 2D codes in the analysis layer is one of the major brain functions.
Log in to be able to interact and post comments
comments
Fetching comments
Sign in to be able to follow your search criteria
