This book introduces a new conceptual framework for understanding nightmares — one of the most prevalent yet theoretically underexplored phenomena in clinical practice. The starting point is a critical observation: despite a robust toolkit of evidence-based interventions — Imagery Rehearsal Therapy (IRT), ERRT, EMDR, TF-CBT, CBT-I, and others — nightmares frequently persist well beyond the remission of a primary disorder, following their own autonomous logic. This persistence demands a different kind of explanation. The book's central argument is that a nightmare should be understood not merely as a symptom, but as a pathologically stabilized functional system of consciousness: a coherent organization of experience with its own goal state (reference point), an internalized model of the world and self, a characteristic mode of action, and a fixed pattern of resolution. This framework is built at the intersection of three intellectual traditions: P. K. Anokhin's theory of functional systems, contemporary predictive processing accounts of brain function, and the evolutionary threat simulation theory of dreaming. From this foundation, the book develops a systematic account of nightmare pathophysiology, reexamines existing psychotherapeutic approaches through the lens of the systems model, proposes a hypothetical clinical model for working with nightmares as functional systems, and outlines integrative strategies for distinct clinical populations. Particular attention is given to the context of mass psychological trauma under conditions of full-scale war in Ukraine — a situation that has sharpened the limits of conventional approaches and raised new demands on clinical reasoning. The book is addressed to clinicians, researchers in sleep medicine, trauma, and consciousness studies, and to anyone who seeks to understand nightmares not simply as symptoms to be managed, but as a specific mode of conscious experience — one that is open to systematic analysis and deliberate transformation.
am a physician and mathematician educated at Donetsk National Medical University and V. N. Karazin Kharkiv National University. My work lies at the intersection of cardiology and other branches of clinical medicine, mathematical modeling, natural intelligence, digital twins, and digital persistence. I explore how living systems organize decisions, maintain adaptive results, and how these processes can be modeled, diagnosed, and augmented in both humans and hybrid human–AI systems. I publish under the names Mykola Yabluchansky and Mykola Iabluchanskyi. More of my work and reflections can be found on my blog and professional profiles: scholar.google.com/citations?