Seven properties of self-organization in the human brain

The principle of self-organization has acquired a fundamental significance in the newly emerging field of computational philosophy. Self-organizing systems have been described in various domains in science and philosophy including physics, neuroscience, biology and medicine, ecology, and sociology. While system architecture and their general purpose may depend on domain-specific concepts and definitions, there are (at least) seven key properties of self-organization clearly identified in brain systems: 1) modular connectivity, 2) unsupervised learning, 3) adaptive ability, 4) functional resiliency, 5) functional plasticity, 6) from-local-to-global functional organization, and 7) dynamic system growth. These are defined here in the light of insight from neurobiology, cognitive neuroscience and Adaptive Resonance Theory (ART), and physics to show that self-organization achieves stability and functional plasticity while minimizing structural system complexity. A specific example informed by empirical research is discussed to illustrate how modularity, adaptive learning, and dynamic network growth enable stable yet plastic somatosensory representation for human grip force control. Implications for the design of “strong” artificial intelligence in robotics are brought forward

A formal evaluation of the performance of different corporate styles in stable and turbulent environments

The notion of "parenting styles", introduced by Goold, Campbell and Alexander, has been widely acknowledged by the Corporate Strategy literature as a good broad description of the different ways in which corporate managers choose to manage and organize multibusiness firms. The purpose of this paper is to present a formal test of the relationship between parenting style and performance. For this test, we developed a set of agent-based simulations using the Performance Landscapes framework, which captures and describes the evolution of firms led by different parenting styles in business environments with different levels of complexity and dynamism. We found that the relative performance of each style is contingent upon the characteristics of the environment in which the firm operates. In less complex business environments, the Strategic Planning style outperforms the Strategic Control and Financial Control styles. In highly complex and highly dynamic environments, by contrast, the Strategic Control style performs best. Our results also demonstrate the importance of planning and flexibility at the corporate level and so contribute to the wider debate on Strategic Planning vs. Emergent Strategies.Corporate strategy; Parenting styles; Agent-based models;