Fractalism: The Correlation between Consciousness and Fractals

• Speaker: Loris Zhu, Math and Philosophy, University of Toronto
• Abstract: Fractals are complex geometrical shapes with a self-similar pattern that repeats itself at different scales. Research has suggested that fractals might be fundamental to the functioning of the brain and the processing of information. The concept of fractalism proposes that consciousness, the state of being aware of one's surroundings, thoughts, and emotions, is correlated with fractals, which is a theoretical framework that posits that fractals are not just a mathematical curiosity or an aesthetic pleasure but are fundamental to the functioning of our consciousness. According to this theory, fractals exist at the core of the brain’s information processing and have a profound impact on our perception, cognition, and creativity. This theory explores the philosophical implications of fractalism and its relationship with consciousness, and how can it help to build a real conscious AI, it also compares fractalism with other philosophical theories such as dualism and functionalism, and how fractalism challenges the traditional view of the mind-body problem and suggests that the mind and body are interconnected and interdependent.

Assessment of chaoticity and entropy in models of consciousness, health, and pathology

• Speaker: Alexey Tolchinsky, The George Washington University
• Abstract: I will review the current empirical evidence of chaoticity at various scales of the brain-mind and the application of nonlinear tools in clinical practice. Kolmogorov-Sinai entropy and its approximations for real living systems, such as ApEn, PeEn, will be considered for various states of consciousness in health and disease. I will discuss the general pattern observed in these studies, which is a correlation between EEG entropy measures and generalized arousal. Based on these data, I will propose a hypothesis that the brain-mind at various scales can operate in linear, nonlinear, or hybrid modes, such as chaotic functioning accompanied by noise. Further, I will review existing hypotheses formulated by Liley et al. of a possible phase transition into a chaotic mode of functioning at the level of alpha rhythm which shows weak nonlinearity. I will also consider a thesis formulated by Mark Solms that living systems must minimize Shannon’s entropy of physical states (sensory entropy). Based on the empirical data, minimization of entropy in that sense appears to be describing only a part of the complex brain-mind dynamics. Studies evaluating measures of entropy specifically developed for real living systems such as discrete timescale entropy (ApEn) suggest that a decrease in EEG entropy can indeed be observed in some neuronal processes (e.g. progression from wakefulness to deep sleep); however, EEG entropy is observed to be increasing at other times and in other modes of brain-mind functioning (e.g. progression from deep sleep to REM to wakefulness; and from vegetative state to wakefulness). I will discuss the clinical implications, including the possibility of increasing diagnostic accuracy by incorporating nonlinear tools in the current diagnostic methods. I propose that it would be theoretically and clinically beneficial for future revisions of the models of consciousness and contemporary psychodynamic psychotherapy to consider including the chaos theory framework. This work has already started both theoretically, such as in Friston et al.’s (2021) paper that incorporates the Free Energy Principle with stochastic chaos, and in practical applications, including chaos-theory-informed algorithms in the assessment of epilepsy, prediction of recovery for patients in Minimally Conscious State and in other circumstances. Finally, I will discuss the model of consciousness and specifically an approach to the hard problem of consciousness proposed by Karl Friston and Mark Solms. I will highlight their use of a homeostatic mechanism for various phenomena, including affects and core consciousness. I will suggest possible limitations of this approach and propose possible directions for future revisions.