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 Neural Model of Biased Oscillations in Aplysia Head-Waving Behavior

A long-term bias in the exploratory head-waving behavior of Aplysia can be induced using bright lights as an aversive stimulus: coupling onset of the lights with head movements to one side results in a bias away from that side (Cook & Carew, 1986). This bias has been interpreted as a form of operant conditioning, and has previously been simulated with a neural network model based on associative synaptic facilitation (Raymond, Baxter, Buonomano, & Byrne, 1992). In this article we simulate the head-waving behavior using a recurrent gated dipole, a nonlinear dynamical neural model that has previously been used to explain various data including oscillatory behavior in biological pacemakers. Within the recurrent gated dipole, two channels operate antagonistically to generate oscillations, which drive the side-to-side head waving. The frequency of oscillations depends on transmitter mobilization dynamics, which exhibit both short- and long-term adaptation. We assume that light onset results in a nonspecific increase in arousal to both channels of the dipole. Repeated pairing of arousal increments with activation of one channel (the "reinforced" channel) of the dipole leads to a bias in transmitter dynamics, which causes the oscillation to last a shorter time on the reinforced channel than on the non-reinforced channel. Our model provides a parsimonious explanation of the observed behavior, and it avoids some of the unexpected results obtained with the Raymond et al. model. In addition, our model makes predictions concerning the rate of onset and extinction of the biases, and it suggests new lines of experimentation to test the nature of the head-waving behavior.Office of Naval Research (N00014-92-J-4015, N00014-91-J-4100, N0014-92-J-1309); Air Force Office of Scientific Research (F49620-92-J-0499); A.P. Sloan Foundation (BR-3122

Reinforced communication and social navigation generate groups in model networks

To investigate the role of information flow in group formation, we introduce a model of communication and social navigation. We let agents gather information in an idealized network society, and demonstrate that heterogeneous groups can evolve without presuming that individuals have different interests. In our scenario, individuals' access to global information is constrained by local communication with the nearest neighbors on a dynamic network. The result is reinforced interests among like-minded agents in modular networks; the flow of information works as a glue that keeps individuals together. The model explains group formation in terms of limited information access and highlights global broadcasting of information as a way to counterbalance this fragmentation. To illustrate how the information constraints imposed by the communication structure affects future development of real-world systems, we extrapolate dynamics from the topology of four social networks.Comment: 7 pages, 3 figure

Territory, Temporality and Clustered Europeanization. IHS Political Science Series: 2006, No. 109

Non-convergence amongst the EU member states, despite a wide range of integration effects, has come to be accepted as conventional wisdom in the Europeanization debate. This paper takes issue with the stress on non-convergence and makes a case for ‘clustered Europeanization’. Clustering is promoted by two variables that have so far received little attention in Europeanization research: territory and temporality. Territory influences Europeanization through (a) ‘families of nations’ and (b) center-periphery structures in an expanding European political space. Temporality matters, in particular, through the ‘relative time of accession’, i.e. when countries joined (c) in relation to their domestic political and economic development and (d) in relation to the phase of European integration. While (a) and (c) promote intra-regional commonalities in Europeanization-related domestic variables, (b) and (d) highlight inter-regional differences in the integration experience. This regional distinctness of both domestic and integration variables, in turn, promotes clustered Europeanization

Indoor thermal environments in Chinese residential buildings responding to the diversity of climates

China has a diversity of climates and a unique historic national heating policy which greatly affects indoor thermal environment and the occupants’ thermal response. This paper quantitatively analyzes the data from a large-scale field study across the country conducted from 2008 to 2011 in residential buildings. The study covers nine typical cities located in the five climate zones including Severe Cold (SC), Cold (C), Hot Summer and Cold Winter (HSCW), Hot Summer and Warm Winter (HSWW) and Mild (M) zones. It is revealed that there exists a large regional discrepancy in indoor thermal environ- ment, the worst performing region being the HSCW zone. Human’s long-term climate adaptation leads to wider range of acceptable thermal comfort temperature. Different graphic comfort zones with accept- able range of temperature and humidity for the five climate zones are obtained using the adaptive Predictive Mean Vote (aPMV) model. The results show that occupants living in the poorer thermal environments in the HSCW and HSWW zones are more adaptive and tolerant to poor indoor conditions than those living in the north part of China where central heating systems are in use. It is therefore recommended to develop regional evaluation standards of thermal environments responding to climate characteristics as well as local occupants’ acclimatization and adaptation in order to meeting dual targets of energy conservation and indoor thermal environment improvement