This book presents the proceedings of the virtual conference NeuroIS Retreat 2020, June 2–4, hosted in Austria, reporting on topics at the intersection of information systems (IS) research, neurophysiology and the brain sciences. Readers will discover the latest findings from top scholars in the field of NeuroIS, which offer detailed insights on the neurobiology underlying IS behavior, essential methods and tools and their applications for IS, as well as the application of neuroscience and neurophysiological theories to advance IS theory.

This edition of Advances in Neurobiology brings together experts in the emerging field of Systems Neuroscience to present an overview of this area of research. Topics covered include: how different neural circuits analyze sensory information, form perceptions of the external world, make decisions, and execute movements; how nerve cells behave when connected together to form neural networks; the relationship between molecular and cellular approaches to understanding brain structure and function; the study of high-level mental functions; and studying brain pathologies and diseases with Systems Neuroscience. A hierarchy of biological complexity arises from the genome, transcriptome, proteome, organelles, cells, synapses, circuits, brain regions, the whole brain, and behaviour. The best way to study the brain, the most complex organ in the body composed of 100 billion cells with trillions of interconnections, is with a Systems Biology approach. Systems biology is an inter-disciplinary field that focuses on complex interactions within biological systems to reveal 'emergent properties' - properties of cells and groups of cells functioning as a system whose actual and theoretical description is only possible using Systems Biology techniques.

This book presents the proceedings of the Gmunden Retreat on NeuroIS 2016, reporting on topics at the intersection of Information Systems (IS) research, neurophysiology and the brain sciences. Readers will discover the latest findings from top scholars in the field of NeuroIS, which offer detailed insights on the neurobiology underlying IS behavior, essential methods and tools and their applications for IS, as well as the application of neuroscience and neurophysiological theories to advance IS theory.

Explains the relationship of electrophysiology, nonlinear dynamics, and the computational properties of neurons, with each concept presented in terms of both neuroscience and mathematics and illustrated using geometrical intuition. In order to model neuronal behavior or to interpret the results of modeling studies, neuroscientists must call upon methods of nonlinear dynamics. This book offers an introduction to nonlinear dynamical systems theory for researchers and graduate students in neuroscience. It also provides an overview of neuroscience for mathematicians who want to learn the basic facts of electrophysiology. Dynamical Systems in Neuroscience presents a systematic study of the relationship of electrophysiology, nonlinear dynamics, and computational properties of neurons. It emphasizes that information processing in the brain depends not only on the electrophysiological properties of neurons but also on their dynamical properties. The book introduces dynamical systems, starting with one- and two-dimensional Hodgkin-Huxley-type models and continuing to a description of bursting systems. Each chapter proceeds from the simple to the complex, and provides sample problems at the end. The book explains all necessary mathematical concepts using geometrical intuition; it includes many figures and few equations, making it especially suitable for non-mathematicians. Each concept is presented in terms of both neuroscience and mathematics, providing a link between the two disciplines. Nonlinear dynamical systems theory is at the core of computational neuroscience research, but it is not a standard part of the graduate neuroscience curriculum—or taught by math or physics department in a way that is suitable for students of biology. This book offers neuroscience students and researchers a comprehensive account of concepts and methods increasingly used in computational neuroscience. An additional chapter on synchronization, with more advanced material, can be found at the author's website, www.izhikevich.com.

This book presents the proceedings of the NeuroIS Retreat 2021, June 1-3, virtual conference, reporting on topics at the intersection of information systems (IS) research, neurophysiology and the brain sciences. Readers will discover the latest findings from top scholars in the field of NeuroIS, which offer detailed insights on the neurobiology underlying IS behavior, essential methods and tools and their applications for IS, as well as the application of neuroscience and neurophysiological theories to advance IS theory.

This book presents the proceedings of the NeuroIS Retreat 2019, held on June 4–6 in Vienna, Austria, reporting on topics at the intersection of information systems (IS) research, neurophysiology and the brain sciences. Featuring the latest findings from top scholars in the field, it offers detailed insights into the neurobiology underlying IS behavior, essential methods and tools and their applications for IS, as well as applying neuroscience and neurophysiological to advance IS theory.