Résumé
This article serves as an introduction to the themed special issue on "Complex Systems in Neurobiology."
The study of complexity in neurobiology has been sensitive to the stochastic processes that dominate the micro-level
architecture of neurobiological systems and the deterministic processes that govern the macroscopic behavior of these systems. A large body of research has traversed these scales of interest, seeking to determine how noise at one spatial or temporal scale influences the activity of the system at another scale. In introducing this special issue, we pay special attention to the history of inquiry in complex systems and why scientists have tended to favor linear, causally driven, reductionist approaches in Neurobiology. We follow this with an elaboration of how an alternative approach might be
formulated. To illustrate our position on how the sciences of complexity and the study of noise can inform neurobiology, we use three systematic examples from the study of human motor control and learning: 1) phase transitions in bimanual coordination; 2) balance, intermittency, and discontinuous control; and 3) sensorimotor synchronization and timing. Using these examples and showing that noise is adaptively utilized by the nervous system, we make the case for the studying complexity with a perspective of understanding the macroscopic stability in biological systems by focusing on component processes at extended spatial and temporal scales. This special issue continues this theme with contributions in topics as diverse as neural network models, physical biology, motor learning, and statistical physics.