An Investigation of Synchrony in Transport Networks

The cumulative degree distributions of transport networks, such as air transportation networks and respiratory neuronal networks, follow power laws. The significance of power laws with respect to other network performance measures, such as throughput and synchronization, remains an open question. Evolving methods for the analysis and design of air transportation networks must be able to address network performance in the face of increasing demands and the need to contain and control local network disturbances, such as congestion. Toward this end, we investigate functional relationships that govern the performance of transport networks; for example, the links between the first nontrivial eigenvalue, lambda(2), of a network\u27s Laplacian matrix-a quantitative measure of network synchronizability-and other global network parameters. In particular among networks with a fixed degree distribution and fixed network assortativity (a measure of a networks preference to attach nodes based on a similarity or difference), those with small lambda(2) are shown to be poor synchronizers, to have much longer shortest paths and to have greater clustering in comparison to those with large lambda(2). A simulation of a respiratory network adds data. to our investigation. This study is a beginning step in developing metrics and design variables for the analysis and active design of air transport networks. (C) 2008 Wiley Periodicals, Inc. Complexity 14:34-43,200

Individual and Collective Behavior of Small Vibrating Motors Interacting Through a Resonant Plate

We report on experiments of many small motors -- cell phone vibrators -- glued to and interacting through a resonant plate. We find that individual motors interacting with the plate demonstrate hysteresis in their steady-state frequency due to interactions with plate resonances. For multiple motors running simultaneously, the degree of synchronization between motors increases when the motors' frequencies are near a resonance of the plate, and the frequency at which the motors synchronize shows a history dependence.Comment: 7 pages, 8 figure

Synchronization in complex networks

Synchronization processes in populations of locally interacting elements are in the focus of intense research in physical, biological, chemical, technological and social systems. The many efforts devoted to understand synchronization phenomena in natural systems take now advantage of the recent theory of complex networks. In this review, we report the advances in the comprehension of synchronization phenomena when oscillating elements are constrained to interact in a complex network topology. We also overview the new emergent features coming out from the interplay between the structure and the function of the underlying pattern of connections. Extensive numerical work as well as analytical approaches to the problem are presented. Finally, we review several applications of synchronization in complex networks to different disciplines: biological systems and neuroscience, engineering and computer science, and economy and social sciences.Comment: Final version published in Physics Reports. More information available at http://synchronets.googlepages.com

Feed-Forward Propagation of Temporal and Rate Information between Cortical Populations during Coherent Activation in Engineered In Vitro Networks.

Transient propagation of information across neuronal assembles is thought to underlie many cognitive processes. However, the nature of the neural code that is embedded within these transmissions remains uncertain. Much of our understanding of how information is transmitted among these assemblies has been derived from computational models. While these models have been instrumental in understanding these processes they often make simplifying assumptions about the biophysical properties of neurons that may influence the nature and properties expressed. To address this issue we created an in vitro analog of a feed-forward network composed of two small populations (also referred to as assemblies or layers) of living dissociated rat cortical neurons. The populations were separated by, and communicated through, a microelectromechanical systems (MEMS) device containing a strip of microscale tunnels. Delayed culturing of one population in the first layer followed by the second a few days later induced the unidirectional growth of axons through the microtunnels resulting in a primarily feed-forward communication between these two small neural populations. In this study we systematically manipulated the number of tunnels that connected each layer and hence, the number of axons providing communication between those populations. We then assess the effect of reducing the number of tunnels has upon the properties of between-layer communication capacity and fidelity of neural transmission among spike trains transmitted across and within layers. We show evidence based on Victor-Purpura's and van Rossum's spike train similarity metrics supporting the presence of both rate and temporal information embedded within these transmissions whose fidelity increased during communication both between and within layers when the number of tunnels are increased. We also provide evidence reinforcing the role of synchronized activity upon transmission fidelity during the spontaneous synchronized network burst events that propagated between layers and highlight the potential applications of these MEMs devices as a tool for further investigation of structure and functional dynamics among neural populations

Subjective Experiences of Space and Time: Self, Sensation, and Phenomenal Time

The investigation of subjective experiences (SEs) of space and time is at the core of consciousness research. The term ‘space’ includes the subject and objects. The SE of subject, I-ness, is defined as ‘Self’. The SEs of objects, subject’s external body, and subject’s internal states such as feelings, thoughts, and so on can be investigated using the proto-experience (PE)-SE framework. The SE of time is defined as ‘phenomenal time’ (which includes past, present and future) and the SE of space as ‘phenomenal space’. The three non-experiential materialistic models are as follows: (I) The quantum-dissipation model [25] can connect the discrete neural signals to classical electromagnetic field to ‘quantum field theory and chaos theory’ for explaining memory. (II) The soliton-catalytic model [8] hypothesizes that all living processes including micro- and macro-processes can be explained by catalysis process. (III) The ‘sensation from evolution of action’ model [13] proposes that SEs are internalized during evolution. All these models can address to some extent the function of structures, such as perception. They cannot address explanatory gap. The complementary experiential PE-SE framework [37] addresses this psycho-physical gap and elucidates the SEs of space and time

Enhancement of synchronization in a hybrid neural circuit by spike timing dependent plasticity

Synchronization of neural activity is fundamental for many functions of the brain. We demonstrate that spike-timing dependent plasticity (STDP) enhances synchronization (entrainment) in a hybrid circuit composed of a spike generator, a dynamic clamp emulating an excitatory plastic synapse, and a chemically isolated neuron from the Aplysia abdominal ganglion. Fixed-phase entrainment of the Aplysia neuron to the spike generator is possible for a much wider range of frequency ratios and is more precise and more robust with the plastic synapse than with a nonplastic synapse of comparable strength. Further analysis in a computational model of HodgkinHuxley-type neurons reveals the mechanism behind this significant enhancement in synchronization. The experimentally observed STDP plasticity curve appears to be designed to adjust synaptic strength to a value suitable for stable entrainment of the postsynaptic neuron. One functional role of STDP might therefore be to facilitate synchronization or entrainment of nonidentical neurons