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Hardcover, xi + 358 pages, NOT ex-library. Good condition, clean with unmarked text, no inscriptions, no stamps. Issued without a dust jacket. -- The book brings together 13 chapters, combining state-of-the-field reviews with forward-looking research agendas. The unifying premise is the recognition that while nonlinear dynamics has achieved significant theoretical and computational development, particularly in low-dimensional systems, its future depends on extending methodologies to high-dimensional, spatiotemporal, stochastic, and biologically grounded contexts. The chapters are organized around three interconnected themes: neural and biological systems, spatially extended systems, and experimentation in the physical sciences. Chapter 1 explores bifurcation theory in systems with multiple time scales, emphasizing degenerate decomposition in contexts such as neuronal models. It shows how traditional analytical tools struggle with singular perturbations and calls for refined geometric and computational techniques. Chapter 2 transitions to quantum many-body systems, focusing on nonlinear manifestations such as quantum discrete breathers, and poses mathematical challenges in reconciling nonlinearity with quantum superposition principles. Chapter 3 examines hereditary systems and difference-differential equations, extending bifurcation analysis to systems incorporating memory and delay. The following section discusses stabilizing structures in nonlinear optics, including the creation of stable pulses from interacting unstable waves, and addresses global vs local nonlinear behaviors. Chapter 5 analyzes spatiotemporal communication through chaotic optical signals, linking nonlinear laser dynamics with synchronization theory. Chapter 6 outlines outstanding challenges in pattern formation theory, particularly in lattice systems, nearly inviscid flows, and systems with broken symmetry. It emphasizes limitations of weakly nonlinear approaches in predicting fully nonlinear outcomes. In Chapter 7, Mullin critiques the relevance of chaos theory in fluid mechanics, using Taylor-Couette flow as a central case. He interrogates the extent to which low-dimensional chaotic models capture fluid behavior and identifies the need for experimental frameworks better suited to spatiotemporal complexity. Chapter 8 presents time-reversal acoustics, showing how chaotic cavity dynamics can be exploited for wave focusing, with implications for medical imaging and seismology. Kuramoto's Chapter 9 turns to non-locally coupled oscillators, developing reduction methods for systems between the locally and globally coupled extremes. He introduces new classes of dynamics such as rotating spiral waves without phase singularities. Chapter 10 investigates vortex dynamics in nonlinear media, proposing prime-number-based formulations to analyze organizing centers such as spiral wave filaments in excitable systems. Chapter 11 (Bressloff & Cowan) focuses on spontaneous pattern formation in the primary visual cortex, drawing from symmetry-based models like the Ginzburg?Landau and amplitude equations to describe orientation tuning and columnar structures. Chapter 12 (Ermentrout & Osan) models morphogenetic patterning during development, bridging computational neuroscience with biological morphogenesis using feature maps and competitive dynamics. The final chapter, by Ditto, emphasizes spatiotemporal dynamics as central to future nonlinear science, particularly in biomedical contexts like cardiac fibrillation and neurocomputing. Collectively, the volume addresses the limitations of traditional nonlinear dynamics in capturing real-world complexity, advocating for hybrid approaches combining mathematical rigor, computational scalability, and biological relevance. The book introduces tools from geometric singular perturbation, symmetry analysis, pattern theory, and dynamical systems reduction, while engaging with experimental domains ranging from neuroscience to optics.
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