Exploring resonance theory and uncontrollability during co-creative art making: A qualitative study among cancer patients.

PURPOSE: Co-creation, characterised by artists and patients creating a joint work of art, may support patients with the integration of life events, such as living with cancer, into their life story. In the process of co-creation, resonance relationships between patients, artists and material may evolve that support such integration. Using the framework of resonance theory, we aim to investigate if and how patients move through the three phases of resonance during a process of co-creation and explore the role of uncontrollability in this process. METHODS: Ten patients who received cancer treatment with palliative intent completed co-creation processes, which were audio recorded. These recordings were imported in Atlas-Ti and analysed by applying content analysis. We searched for the three phases of resonance, Being affected, touched and moved; Self-efficacy and responding; Adaptive transformation. We additionally searched for signs of uncontrollability. RESULTS: Patients used 4-8 sessions (median 5 sessions) with a duration 90-240 min per session (median duration 120 min). We found that patients move through the three phases of resonance during co-creation processes. Uncontrollability both presents a challenge and an invitation to integrate experiences of contingency into one's life narrative. Patients express self-recognition and the experience of contingency in their work of art. CONCLUSIONS: Integration of experiences of contingency into a life narrative can be supported by the process of co-creation of art, which invites patients to relate to their illness, their environment and themselves. The phases of resonance in combination with uncontrollability as a continuously present factor, provide a means to both study and support the integration of experiences of contingency into the life narrative.

Biological systems - "Symphonies of Life": Reviving Friedrich Cramer's general resonance theory.

Understanding biological systems in terms of scientific materialism has arguably reached a frontier, leaving fundamental questions about their complexity unanswered. In 1998, Friedrich Cramer proposed a general resonance theory as a way forward. His theory builds on the extension of the quantum physical duality of matter and wave to the macroscopic world. According to Cramer' theory, agents constituting biological systems oscillate, akin to musical soundwaves, at specific eigenfrequencies. Biological system dynamics can be described as "Symphonies of Life" emerging from the resonance (and dissonance) of eigenfrequencies within the interacting collective. His theory has potential for studying biological problems of increasing complexity in a fast-changing Anthropocene from a new and transdisciplinary angle. Despite data becoming increasingly available for analyses, Cramer's theory remains ignored and therefore untested a quarter century after its publication. This paper discusses how the theory can move to quantitative assessments and application. Cramer's general resonance theory deserves revival.

Fields or firings? Comparing the spike code and the electromagnetic field hypothesis.

Where is consciousness? Neurobiological theories of consciousness look primarily to synaptic firing and "spike codes" as the physical substrate of consciousness, although the specific mechanisms of consciousness remain unknown. Synaptic firing results from electrochemical processes in neuron axons and dendrites. All neurons also produce electromagnetic (EM) fields due to various mechanisms, including the electric potential created by transmembrane ion flows, known as "local field potentials," but there are also more meso-scale and macro-scale EM fields present in the brain. The functional role of these EM fields has long been a source of debate. We suggest that these fields, in both their local and global forms, may be the primary seat of consciousness, working as a gestalt with synaptic firing and other aspects of neuroanatomy to produce the marvelous complexity of minds. We call this assertion the "electromagnetic field hypothesis." The neuroanatomy of the brain produces the local and global EM fields but these fields are not identical with the anatomy of the brain. These fields are produced by, but not identical with, the brain, in the same manner that twigs and leaves are produced by a tree's branches and trunk but are not the same as the branches and trunk. As such, the EM fields represent the more granular, both spatially and temporally, aspects of the brain's structure and functioning than the neuroanatomy of the brain. The brain's various EM fields seem to be more sensitive to small changes than the neuroanatomy of the brain. We discuss issues with the spike code approach as well as the various lines of evidence supporting our argument that the brain's EM fields may be the primary seat of consciousness. This evidence (which occupies most of the paper) suggests that oscillating neural EM fields may make firing in neural circuits oscillate, and these oscillating circuits may help unify and guide conscious cognition.

Electromagnetic-field theories of qualia: can they improve upon standard neuroscience?

How do brains create all our different colors, pains, and other conscious qualities? These various qualia are the most essential aspects of consciousness. Yet standard neuroscience (primarily based on synaptic information processing) has not found the synaptic-firing codes, sometimes described as the "spike code," to account for how these qualia arise and how they unite to form complex perceptions, emotions, et cetera. Nor is it clear how to get from these abstract codes to the qualia we experience. But electromagnetic field (versus synaptic) approaches to how qualia arise have been offered in recent years by Pockett, McFadden, Jones, Bond, Ward and Guevera, Keppler and Shani, Hunt and Schooler, et cetera. These EM-field approaches show promise in offering more viable accounts of qualia. Yet, until now, they have not been evaluated together. We review various EM field theories of qualia, highlight their strengths and weaknesses, and contrast these theories with standard neuroscience approaches.

"Noncovalent Interaction": A Chemical Misnomer That Inhibits Proper Understanding of Hydrogen Bonding, Rotation Barriers, and Other Topics.

We discuss the problematic terminology of "noncovalent interactions" as commonly applied to hydrogen bonds, rotation barriers, steric repulsions, and other stereoelectronic phenomena. Although categorization as "noncovalent" seems to justify classical-type pedagogical rationalizations, we show that these phenomena are irreducible corollaries of the same orbital-level conceptions of electronic covalency and resonance that govern all chemical bonding phenomena. Retention of such nomenclature is pedagogically misleading in supporting superficial dipole-dipole and related "simple, neat, and wrong" conceptions as well as perpetuating inappropriate bifurcation of the introductory chemistry curriculum into distinct "covalent" vs. "noncovalent" modules. If retained at all, the line of dichotomization between "covalent" and "noncovalent" interaction should be re-drawn beyond the range of quantal exchange effects (roughly, at the contact boundary of empirical van der Waals radii) to better unify the pedagogy of molecular and supramolecular bonding phenomena.

Co-creative art processes with cancer patients from the artists' perspective: a qualitative study exploring resonance theory.

PURPOSE: Co-creation, characterised by artists and patients creating a joint work of art, may support patients with the integration of life events into their life story, such as living with cancer. In the process of co-creation, resonance relationships between patients, artists and material may evolve that support integration. We aim to investigate if and if so, how resonance relationships occur from the perspective of the artist. METHODS: We used the first 10 audio recordings of supervision sessions between eight artists and their two supervisors on ongoing co-creation processes with cancer patients. By conducting a qualitative template analysis in AtlasTi, we searched for the presence of resonance, as defined by its four main characteristics, Being affected, touched and moved; Self-efficacy and responding; Moments of uncontrollability; and Adaptive transformation. In addition, two case descriptions are presented. RESULTS: We found resonance relationships to be present in the studied co-creation processes where moments of uncontrollability can lead to a next step in the process of co-creation and as such form an important factor within co-creation. CONCLUSIONS: The current study suggests focus on elements of resonance relationships within co-creation, specifically practising with uncontrollability while working with art, could strengthen interventions targeting integration of life events in advanced cancer patients.

Topological biclustering ARTMAP for identifying within bicluster relationships.

Biclustering is a powerful tool for exploratory data analysis in domains such as social networking, data reduction, and differential gene expression studies. Topological learning identifies connected regions that are difficult to find using other traditional clustering methods and produces a graphical representation. Therefore, to improve the quality of biclustering and module extraction, this work combines the adaptive resonance theory (ART)-based methods of biclustering ARTMAP (BARTMAP) and topological ART (TopoART), to produce TopoBARTMAP. The latter inherits the ability to detect topological associations while performing data reduction. The capabilities of TopoBARTMAP were benchmarked using 35 real world cancer datasets and contrasted with other (bi)clustering methods, where it showed a statistically significant improvement over the other assessed methods on ordered and shuffled data experiments. In experiments with 12 synthetic datasets, the method was observed to perform better at identifying constant, scale, shift, and shift scale type biclusters. The produced graphical representation was refined to represent gene bicluster associations and was assessed on the NCBI GSE89116 dataset containing expression levels of 39,326 probes sampled over 38 observations.

High-Density "Windowpane" Coordination Patterns of Water Clusters and Their NBO/NRT Characterization.

Cluster mixture models for liquid water at higher pressures suggest the need for water clusters of higher coordination and density than those commonly based on tetrahedral H-bonding motifs. We show here how proton-ordered water clusters of increased coordination and density can assemble from a starting cyclic tetramer or twisted bicyclic (Möbius-like) heptamer to form extended Aufbau sequences of stable two-, three-, and four-coordinate "windowpane" motifs. Such windowpane clusters exhibit sharply reduced (~90°) bond angles that differ appreciably from the tetrahedral angles of idealized crystalline ice Ih. Computed free energy and natural resonance theory (NRT) bond orders provide quantitative descriptors for the relative stabilities of clusters and strengths of individual coordinative linkages. The unity and consistency of NRT description is demonstrated to extend from familiar supra-integer bonds of the molecular regime to the near-zero bond orders of the weakest linkages in the present H-bond clusters. Our results serve to confirm that H-bonding exemplifies resonance-covalent (fractional) bonding in the sub-integer range and to further discount the dichotomous conceptions of "electrostatics" for intermolecular bonding vs. "covalency" for intramolecular bonding that still pervade much of freshman-level pedagogy and force-field methodology.

Toward Understanding the Brain Dynamics of Music: Learning and Conscious Performance of Lyrics and Melodies With Variable Rhythms and Beats.

A neural network architecture models how humans learn and consciously perform musical lyrics and melodies with variable rhythms and beats, using brain design principles and mechanisms that evolved earlier than human musical capabilities, and that have explained and predicted many kinds of psychological and neurobiological data. One principle is called factorization of order and rhythm: Working memories store sequential information in a rate-invariant and speaker-invariant way to avoid using excessive memory and to support learning of language, spatial, and motor skills. Stored invariant representations can be flexibly performed in a rate-dependent and speaker-dependent way under volitional control. A canonical working memory design stores linguistic, spatial, motoric, and musical sequences, including sequences with repeated words in lyrics, or repeated pitches in songs. Stored sequences of individual word chunks and pitch chunks are categorized through learning into lyrics chunks and pitches chunks. Pitches chunks respond selectively to stored sequences of individual pitch chunks that categorize harmonics of each pitch, thereby supporting tonal music. Bottom-up and top-down learning between working memory and chunking networks dynamically stabilizes the memory of learned music. Songs are learned by associatively linking sequences of lyrics and pitches chunks. Performance begins when list chunks read word chunk and pitch chunk sequences into working memory. Learning and performance of regular rhythms exploits cortical modulation of beats that are generated in the basal ganglia. Arbitrary performance rhythms are learned by adaptive timing circuits in the cerebellum interacting with prefrontal cortex and basal ganglia. The same network design that controls walking, running, and finger tapping also generates beats and the urge to move with a beat.

A Dynamical, Radically Embodied, and Ecological Theory of Rhythm Development.

Musical rhythm abilities-the perception of and coordinated action to the rhythmic structure of music-undergo remarkable change over human development. In the current paper, we introduce a theoretical framework for modeling the development of musical rhythm. The framework, based on Neural Resonance Theory (NRT), explains rhythm development in terms of resonance and attunement, which are formalized using a general theory that includes non-linear resonance and Hebbian plasticity. First, we review the developmental literature on musical rhythm, highlighting several developmental processes related to rhythm perception and action. Next, we offer an exposition of Neural Resonance Theory and argue that elements of the theory are consistent with dynamical, radically embodied (i.e., non-representational) and ecological approaches to cognition and development. We then discuss how dynamical models, implemented as self-organizing networks of neural oscillations with Hebbian plasticity, predict key features of music development. We conclude by illustrating how the notions of dynamical embodiment, resonance, and attunement provide a conceptual language for characterizing musical rhythm development, and, when formalized in physiologically informed dynamical models, provide a theoretical framework for generating testable empirical predictions about musical rhythm development, such as the kinds of native and non-native rhythmic structures infants and children can learn, steady-state evoked potentials to native and non-native musical rhythms, and the effects of short-term (e.g., infant bouncing, infant music classes), long-term (e.g., perceptual narrowing to musical rhythm), and very-long term (e.g., music enculturation, musical training) learning on music perception-action.

SuPART: supervised projective adapted resonance theory for automatic quality assurance approval of radiotherapy treatment plans.

Radiotherapy is a common treatment modality for the treatment of cancer, where treatments must be carefully designed to deliver appropriate dose to targets while avoiding healthy organs. The comprehensive multi-disciplinary quality assurance (QA) process in radiotherapy is designed to ensure safe and effective treatment plans are delivered to patients. However, the plan QA process is expensive, often time-intensive, and requires review of large quantities of complex data, potentially leading to human error in QA assessment. We therefore develop an automated machine learning algorithm to identify 'acceptable' plans (plans that are similar to historically approved plans) and 'unacceptable' plans (plans that are dissimilar to historically approved plans). This algorithm is a supervised extension of projective adaptive resonance theory, called SuPART, that learns a set of distinctive features, and considers deviations from them indications of unacceptable plans. We test SuPART on breast and prostate radiotherapy datasets from our institution, and find that SuPART outperforms common classification algorithms in several measures of accuracy. When no falsely approved plans are allowed, SuPART can correctly auto-approve 34% of the acceptable breast and 32% of the acceptable prostate plans, and can also correctly reject 53% of the unacceptable breast and 56% of the unacceptable prostate plans. Thus, usage of SuPART to aid in QA could potentially yield significant time savings.

Anti-Electrostatic Pi-Hole Bonding: How Covalency Conquers Coulombics.

Intermolecular bonding attraction at π-bonded centers is often described as "electrostatically driven" and given quasi-classical rationalization in terms of a "pi hole" depletion region in the electrostatic potential. However, we demonstrate here that such bonding attraction also occurs between closed-shell ions of like charge, thereby yielding locally stable complexes that sharply violate classical electrostatic expectations. Standard DFT and MP2 computational methods are employed to investigate complexation of simple pi-bonded diatomic anions (BO-, CN-) with simple atomic anions (H-, F-) or with one another. Such "anti-electrostatic" anion-anion attractions are shown to lead to robust metastable binding wells (ranging up to 20-30 kcal/mol at DFT level, or still deeper at dynamically correlated MP2 level) that are shielded by broad predissociation barriers (ranging up to 1.5 Å width) from long-range ionic dissociation. Like-charge attraction at pi-centers thereby provides additional evidence for the dominance of 3-center/4-electron (3c/4e) nD-π*AX interactions that are fully analogous to the nD-σ*AH interactions of H-bonding. Using standard keyword options of natural bond orbital (NBO) analysis, we demonstrate that both n-σ* (sigma hole) and n-π* (pi hole) interactions represent simple variants of the essential resonance-type donor-acceptor (Bürgi-Dunitz-type) attraction that apparently underlies all intermolecular association phenomena of chemical interest. We further demonstrate that "deletion" of such π*-based donor-acceptor interaction obliterates the characteristic Bürgi-Dunitz signatures of pi-hole interactions, thereby establishing the unique cause/effect relationship to short-range covalency ("charge transfer") rather than envisioned Coulombic properties of unperturbed monomers.

Clustering of genes from microarray data using hierarchical projective adaptive resonance theory: a case study of tuberculosis.

We propose the hierarchical Projective Adaptive Resonance Theory (PART) algorithm for classification of gene expression data. This algorithm is realized by combing transposed quasi-supervised PART and unsupervised PART. We develop the corresponding validation statistics for each process and compare it with other clustering algorithms in a case study of tuberculosis (TB). First, we use sample-based transposed quasi-supervised PART to obtain optimal clustering results of samples distinguished by time post-infection and the representative genes for each cluster including up-regulated, down-regulated and stable genes. The up- and down-regulated genes show more than 90% similarity to the result derived from Linear Models for Microarray Data and are verified by weighted k-nearest neighbor model on TB projection. Second, we use gene-based unsupervised PART algorithm to cluster these representative genes where functional enrichment analysis is conducted in each cluster. We further confirm the main immune response of human macrophage-like THP-1 cells against TB within 2 days is type I interferon-mediated innate immunity. This study demonstrates how hierarchical PART algorithm analyzes microarray data. The sample-based quasi-supervised PART extracts representative genes and narrows down the shortlist of disease-relevant genes and gene-based unsupervised PART classifies representative genes that help to interpret immune response against TB.

ARTFLOW: A Fast, Biologically Inspired Neural Network that Learns Optic Flow Templates for Self-Motion Estimation.

Most algorithms for steering, obstacle avoidance, and moving object detection rely on accurate self-motion estimation, a problem animals solve in real time as they navigate through diverse environments. One biological solution leverages optic flow, the changing pattern of motion experienced on the eye during self-motion. Here I present ARTFLOW, a biologically inspired neural network that learns patterns in optic flow to encode the observer's self-motion. The network combines the fuzzy ART unsupervised learning algorithm with a hierarchical architecture based on the primate visual system. This design affords fast, local feature learning across parallel modules in each network layer. Simulations show that the network is capable of learning stable patterns from optic flow simulating self-motion through environments of varying complexity with only one epoch of training. ARTFLOW trains substantially faster and yields self-motion estimates that are far more accurate than a comparable network that relies on Hebbian learning. I show how ARTFLOW serves as a generative model to predict the optic flow that corresponds to neural activations distributed across the network.

Pauling's Conceptions of Hybridization and Resonance in Modern Quantum Chemistry.

We employ the tools of natural bond orbital (NBO) and natural resonance theory (NRT) analysis to demonstrate the robustness, consistency, and accuracy with which Linus Pauling's qualitative conceptions of directional hybridization and resonance delocalization are manifested in all known variants of modern computational quantum chemistry methodology.

An analysis of valence electronic structure from a viewpoint of resonance theory: Tautomerization of formamide and diazadiboretidine.

The resonance theory is still very useful in understanding the valence electron structure. However, such a viewpoint is not usually obtained by general-purpose quantum chemical calculations, instead requires rather special treatment such as valence bond methods. In this study, we propose a method based on second quantization to analyze the results obtained by general-purpose quantum chemical calculations from the local point of view of electronic structure and analyze diazadiboretidine and the tautomerization of formamide. This method requires only the "PS"-matrix, consisting of the density matrix (P-matrix) and overlap matrix, and can be computed with a comparable load to that of Mulliken population analysis. A key feature of the method is that, unlike other methods proposed so far, it makes direct use of the results of general-purpose quantum chemical calculations.

Response to comment on "Superposition of waves or densities: Which is the nature of chemical resonance?"

I reply to the comment by Weinhold and Glendening on the article (J. Comput. Chem. 2021, 42, 412). I provide further explanation and an additional numerical example to support my previous assertion that the present form of natural resonance theory is fundamentally flawed, at least within the DFT framework.

A Neural Model of Intrinsic and Extrinsic Hippocampal Theta Rhythms: Anatomy, Neurophysiology, and Function.

This article describes a neural model of the anatomy, neurophysiology, and functions of intrinsic and extrinsic theta rhythms in the brains of multiple species. Topics include how theta rhythms were discovered; how theta rhythms organize brain information processing into temporal series of spatial patterns; how distinct theta rhythms occur within area CA1 of the hippocampus and between the septum and area CA3 of the hippocampus; what functions theta rhythms carry out in different brain regions, notably CA1-supported functions like learning, recognition, and memory that involve visual, cognitive, and emotional processes; how spatial navigation, adaptively timed learning, and category learning interact with hippocampal theta rhythms; how parallel cortical streams through the lateral entorhinal cortex (LEC) and the medial entorhinal cortex (MEC) represent the end-points of the What cortical stream for perception and cognition and the Where cortical stream for spatial representation and action; how the neuromodulator acetylcholine interacts with the septo-hippocampal theta rhythm and modulates category learning; what functions are carried out by other brain rhythms, such as gamma and beta oscillations; and how gamma and beta oscillations interact with theta rhythms. Multiple experimental facts about theta rhythms are unified and functionally explained by this theoretical synthesis.

A Canonical Laminar Neocortical Circuit Whose Bottom-Up, Horizontal, and Top-Down Pathways Control Attention, Learning, and Prediction.

All perceptual and cognitive circuits in the human cerebral cortex are organized into layers. Specializations of a canonical laminar network of bottom-up, horizontal, and top-down pathways carry out multiple kinds of biological intelligence across different neocortical areas. This article describes what this canonical network is and notes that it can support processes as different as 3D vision and figure-ground perception; attentive category learning and decision-making; speech perception; and cognitive working memory (WM), planning, and prediction. These processes take place within and between multiple parallel cortical streams that obey computationally complementary laws. The interstream interactions that are needed to overcome these complementary deficiencies mix cell properties so thoroughly that some authors have noted the difficulty of determining what exactly constitutes a cortical stream and the differences between streams. The models summarized herein explain how these complementary properties arise, and how their interstream interactions overcome their computational deficiencies to support effective goal-oriented behaviors.

Attention: Multiple types, brain resonances, psychological functions, and conscious states.

This article describes neural models of attention. Since attention is not a disembodied process, the article explains how brain processes of consciousness, learning, expectation, attention, resonance, and synchrony interact. These processes show how attention plays a critical role in dynamically stabilizing perceptual and cognitive learning throughout our lives. Classical concepts of object and spatial attention are replaced by mechanistically precise processes of prototype, boundary, and surface attention. Adaptive resonances trigger learning of bottom-up recognition categories and top-down expectations that help to classify our experiences, and focus prototype attention upon the patterns of critical features that predict behavioral success. These feature-category resonances also maintain the stability of these learned memories. Different types of resonances induce functionally distinct conscious experiences during seeing, hearing, feeling, and knowing that are described and explained, along with their different attentional and anatomical correlates within different parts of the cerebral cortex. All parts of the cerebral cortex are organized into layered circuits. Laminar computing models show how attention is embodied within a canonical laminar neocortical circuit design that integrates bottom-up filtering, horizontal grouping, and top-down attentive matching. Spatial and motor processes obey matching and learning laws that are computationally complementary to those obeyed by perceptual and cognitive processes. Their laws adapt to bodily changes throughout life, and do not support attention or conscious states.