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Volume 3 Issue 2 ( May 2024)


Quantum of information’ functionality as a measure of subjectivity beyond the capabilities of deep learning

 S. Parida, E. Alemdar & R.R. Poznanski 

The potential of conscious artificial intelligence (AI), with its functional systems that surpass automation and rely on elements of understanding, is a beacon of hope in the AI revolution. The shift from automation to conscious AI, once replaced with machine understanding, offers a future where AI can comprehend without needing to experience, thereby revolutionizing the field of AI. In this context, the proposed Dynamic Organicity Theory of consciousness (DOT) stands out as a promising and novel approach for building artificial consciousness that is more like the brain with physiological nonlocality and diachronicity of self-referential causal closure. However, deep learning algorithms utilize "black box" techniques such as “dirty hooks” to make the algorithms operational by discovering arbitrary functions from a trained set of dirty data rather than prioritizing models of consciousness that accurately represent intentionality as intentions-in-action. 


Principal component analysis on the effect of early morning awakening in major depressive disorder

Julia R. Higdon & Jonghoon Kang  


Sleep disturbance is one of the most prevalent symptoms associated with Major Depressive Disorder (MDD). A recent article (Wu et al., 2022, Journal of Multiscale Neuroscience 1, 133-139) explored the significant relationship between early morning awakening (EMA), a type of sleep disturbance, and recovery in MDD patients. In the paper, the authors examined the relationship between EMA and the treatment of MDD with twelve neuropsychological parameters. The authors employed two univariate statistical techniques, students’ t-test, and ANOVA in the analysis of their data. While their analysis derived a meaningful conclusion that EMA may result in statistically and clinically significant delay in recovery, we found that a multivariate statistical technique, principal component analysis (PCA), extracted additional quantitative information from their study. In this paper, we present quantitative features in the interaction between EMA and the treatment of MDD obtained from PCA 


Treatment of addictions with special reference to anorexia nervosa

Henry C. Tuckwell

Anorexia nervosa (AN) is a disease affecting mainly young women. It involves a pathological desire to be thin and has a complex etiology. Treatments, which have varying degrees of success, focus on medication or supervised counseling, sometimes in a hospital setting. AN has several possible co-morbidities, including obsessive-compulsive disorder, depression, and anxiety. In this article, it is hypothesized that since AN has characteristics in common with those of addiction, it could possibly be treated with supplements, such as N-acetylcysteine (NAC), which act to restore glutamate homeostasis in the nucleus accumbens and have been successfully employed in the treatment of substance abuse and various addictive behaviors.


Some necessary constructs of consciousness as defined in the dynamic organicity theory

Roman R. Poznanski

The Dynamic Organicity Theory (DOT) explains consciousness as a process that cannot be reduced to a thing or a structure. This process, called the Polanyian process, involves the evolving diachronic boundary conditions of our experienceability. These boundary conditions are ontologically intertwined with higher-level boundary conditions, which lead to physiological nonlocal cause-and-effect relationships. Thus, adaptive changes occur when self-referential causal closure transforms syntactic structures into experienceable forms. Self-referential causal closure is a causal agent for diachronic boundary conditions that majorly structure intrinsic information in ways that experienceabilities are across time, suggesting that consciousness is not driven by an “internal clock” or regular biological rhythm but rather by intrinsic intentionality preceding path selection through a non-mechanical force of hidden thermodynamic energy that cascades to form a volitional agency ...


Neurobehavioral perspectives on autistic spectrum disorder

L.A. Cacha

There has been progress in understanding autism in recent years, but there is still much to learn about the genetics and environmental factors that impact it. An autism diagnosis results from a neurological disorder having an adverse effect on normal brain functions, affecting communication and social interaction skills combined with rigid, repetitive patterns of behaviors.  This paper aims to connect the underlying mechanism of how the structure and function of the brain relate to the complex and diverse behavioral manifestations of autism. Mapping this connection can provide us with a better understanding of the autism signs and symptoms. Consequently, individuals with autism process the environment and their interactions with others differently from those without autism – so they make different perceptions and connections between themselves and the environment. An individual with this condition will have difficulty communicating, forming relationships, and responding appropriately to their environment. 



Some aspects of bidomain modeling with volume conductors

R. R. Poznanski

The concept of dynamic multiscaling has changed our approach to multi-neuronal cable theory. Previously, computational neuroscientists considered individual neurons as neural masses or compartmental models, but now a distributed representation of single neurons as ionic cable structures is most likely to lead to a greater understanding of how the distribution of ionic channels and synaptic input along the dendrites of a few neurons can offset the collective behavior of a large ensemble of neurons and, therefore, provide a measure of the dynamical brain. This change in perspective forms the basis of volume conductor-bidomain modeling, a new method 


The Feasibility of Acupuncture on Post-Spinal Cord Injury Treatment

Bong Hyo Lee, Jonghoon Kang, Walker S. Lewis, Nam Jun Lee, Young S. Gwak

Spinal cord injury (SCI) simultaneously causes multiple and interrelated pathophysiological disorders throughout the nervous system, hindering the development of effective treatment strategies. Mechanistically, SCI triggers excitatory signaling activation, downregulation of the inhibitory system, neuronal death, followed by the development of new synaptic circuits and reorganization, leading to neurological dysfunctions and mental disorders. Therefore, a simultaneous treatment strategy, known as overlapping treatment, is needed. Over decades, both preclinical and clinical studies have established that acupuncture treatment offers neuroprotection, pain attenuation, improvement of functional recovery, and promotes reward behaviors, suggesting potential roles of acupuncture in post-SCI treatment. Recently, the importance of overlapping treatment has been recognized in developing effective treatments for post-SCI pathophysiology. However, there has been no systematic study investigating the role of acupuncture in 


Spatial interactions impact on Ca-driven synaptic plasticity: An ionic cable theory perspective

Nicolangelo L. Iannella & Roman R. Poznanski


We extend our previous paper on deriving an approximate analytical solution of a nonlinear cable equation by including other ion channels in neurons and calcium dynamics based on reaction-diffusion dynamics that lead to a system of nonlinear cable equations. Here, excitable dendrite possesses clusters of voltage-activated ion channels that are discretely distributed as point sources or hotspots of transmembrane current along a continuous cable structure of fixed length. Single and/or trains of action potentials and spatially distributed synaptic inputs drive the depolarisation and activate sparsely distributed voltage-dependent calcium channels. This leads to calcium influx and diffusion in the cable. Here, time-dependent analytical solutions were obtained by applying a perturbation expansion of the non-dimensional voltage (Φ) and non-dimensional calcium (ΦCa) and then solving the resulting set of integral equations. We use this framework to gain insights into calcium-driven synaptic plasticity in dendrites. Many previous studies have traditionally focused on the local impact of calcium on whether the synapse's strength is ....

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