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This eBook is a collection of articles from a Frontiers Research Topic. Frontiers Research Topics are very popular trademarks of the Frontiers Journals Series: they are collections of at least ten articles, all centered on a particular subject. With their unique mix of varied contributions from Original Research to Review Articles, Frontiers Research Topics unify the most influential researchers, the latest key findings and historical advances in a hot research area! Find out more on how to host your own Frontiers Research Topic or contribute to one as an author by contacting the Frontiers Editorial Office: frontiersin.org/about/contact

self-organization --- cyber-physical system --- swarm robotics --- resilience --- scalability

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In an attempt to cease from reducing the world and its phenomena to linear modeling and analytic dissection, Dynamic Systems Theories (DST) and Embodiment theories and methods aim to account for the complex, dynamic, and non-linear phenomena that we constantly deal with in psychology. For instance, a DST and Embodiment perspective can enrich psychology’s understanding of communicative processes both in clinical and non-clinical settings. In psychotherapy, research has shown that there are a number of common factors contributing to psychotherapy outcome, of which the therapeutic relationship is the most important one. These findings give communication a central role in the psychotherapy process. In the traditional view, the underlying model of understanding psychotherapy processes is that of a number of components summatively coming together enabling us to make a linear causal prediction. Yet, communication is inherently dynamic. A shift to viewing the communication process in psychotherapy as a field dynamic phenomenon helps us to take into account nonlinear phenomena, such as feedback processes within and between persons. We thus propose an embodied enactive dynamic systems view as a new theoretical and methodological perspective that can more realistically capture what happens among and between two persons in psychotherapy. This view is broader than that of most current models in psychotherapy research. DST and Embodied Enactive Approaches can offer solutions to the prevailing neglect of non-linear phenomena in Western science, to better account for the complex dynamics of reality, and to move to a more holistic level of analysis. DST and Embodied Enactive Approaches have developed not in a single discipline but in a joined movement based on various fields such as physics, biology, robotics, anthropology, philosophy, linguistics, neuroscience, and psychology, and have only recently entered clinical theorizing. The two new paradigms are presently triggering a rethinking of the therapeutic process by recognizing the embodied nature of psychological and communicative phenomena. Their integration opens up a promising scenario in the field of psychotherapy research, developing new, profoundly transdisciplinary, theoretical concepts, methodologies, and standards of knowledge. The notion of field dynamics enables us to account for the role of the communicational context in the regulation of intra-psychological processes, while at the same time avoiding the pitfalls of an ontologization of the hierarchy of systemic organization. Moreover, the new approach implements methodological strategies that can transcend the conventional opposition between idiographic and nomothetic sciences.

Enactivism --- self-organization --- dynamic systems --- embodiment --- temporality --- Psychotherapy outcome --- Psychotherapy process --- Complexity

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Biophysical modelling of brain activity has had a long and illustrious history and has during the last few years profited from technological advances that allow obtaining neuroimaging data at an unprecedented spatiotemporal resolution. It is a very active area of research with applications ranging from the characterization of neurobiological and cognitive processes to constructing artificial brains in silico and building brain-machine interface and neuroprosthetic devices. The relevant community has always benefited from interdisciplinary interactions between different and seemingly distant fields ranging from mathematics and engineering to linguistics and psychology. This Research Topic aims to promote such interactions and we welcome all works related or that can contribute to an understanding of and construction of models for neural activity. The focus will be on biophysical models describing brain activity usually measured by fMRI or electrophysiology. Such models can be divided into two large classes: neural mass and neural field models. The main difference between these two classes is that field models prescribe how a quantity characterizing neural activity (such as average depolarization of a neural population) evolves over both space and time as opposed to mass models which characterize the evolution of this quantity over time only and assume that all neurons of a population are located at (approximately) the same point. This Research Topic will focus on both classes of such models and discuss several of their aspects and relative merits focusing on the main ideas of neural field and mass theories that span from synapses to the whole brain, comparisons of their predictions with EEG and MEG spectra of spontaneous brain activity, evoked responses, seizures, and fitting to data to infer brain states and map physiological parameters. We welcome submissions shedding light on the underlying dynamics within the neural tissue that can yield explanations of disorders such as epilepsy and migraine as well as normal functions such as attention, working memory and decision making and encourage papers reporting new theoretical and/or modelling work as well as advances in experimental methods that can benefit modelling endeavours. The aim of this Research Topic is to provide a forum for state-of-the-art research in the field and foster new theoretical advances.

Calculus --- Mathematics --- Physical Sciences & Mathematics --- neural disorders --- self-organization --- Electroencephalogram --- neural networks --- Electrophysiology --- Integro-differential equations --- neural field theory --- neural masses --- oscillations --- anaesthesia

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This eBook is a collection of articles from a Frontiers Research Topic. Frontiers Research Topics are very popular trademarks of the Frontiers Journals Series: they are collections of at least ten articles, all centered on a particular subject. With their unique mix of varied contributions from Original Research to Review Articles, Frontiers Research Topics unify the most influential researchers, the latest key findings and historical advances in a hot research area! Find out more on how to host your own Frontiers Research Topic or contribute to one as an author by contacting the Frontiers Editorial Office: frontiersin.org/about/contact

complexity --- fractality --- non-stationarity --- fractional calculus --- homeostasis --- smart medical devices --- critical phenomena and its implications --- emergence --- self-organization --- robustness --- physiological resiliency --- quality-of-life physiological control --- cyber-physical systems

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Dieser Band beschäftigt sich mit dem maschinellen Lernen - der Autoadaption von algorithmischen Artefakten - als Thema interdisziplinärer Diskurse zu beispielsweise Selbstorganisation oder schwacher künstlicher Intelligenz. Anknüpfend an Heidegger, Goodman und Hubig ermöglicht die Studie einen systematischen interdisziplinären Zugang zu maschinellem Lernen, indem seine Charakteristika - etwa künstliche neuronale Netze oder evolutionäres Lernen - präzise, aber dennoch interdisziplinär verständlich beschrieben werden. Darauf aufbauend nimmt Sebastian Harrach eine technikphilosophische Verortung des maschinellen Lernens vor und geht exemplarisch den Denkrichtungen einer interdisziplinären Diskussion nach.

Technology --- Machine learning. --- Machinery --- Technology and civilization --- Machines --- Manufactures --- Power (Mechanics) --- Mechanical engineering --- Motors --- Power transmission --- Learning, Machine --- Artificial intelligence --- Machine theory --- Philosophy. --- Curious devices --- Maschinelles Lernen; Mensch-Computer-Interaktion; Big Data; Selbstorganisation; Technikphilosophie; Philosophie; Technik; Medienphilosophie; Informatik; Machine Learning; Human-computer Interaction; Self-organization; Philosophy of Technology; Philosophy; Technology; Media Philosophy; Computer Sciences --- Big Data. --- Computer Sciences. --- Human-computer Interaction. --- Media Philosophy. --- Philosophy of Technology. --- Self-organization. --- Technology.