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

Application of Asynchronous Transfer Mode (Atm) technology to Picture Archiving and Communication Systems (Pacs): A survey

Broadband Integrated Services Digital Network (R-ISDN) provides a range of narrowband and broad-band services for voice, video, and multimedia. Asynchronous Transfer Mode (ATM) has been selected by the standards bodies as the transfer mode for implementing B-ISDN; The ability to digitize images has lead to the prospect of reducing the physical space requirements, material costs, and manual labor of traditional film handling tasks in hospitals. The system which handles the acquisition, storage, and transmission of medical images is called a Picture Archiving and Communication System (PACS). The transmission system will directly impact the speed of image transfer. Today the most common transmission means used by acquisition and display station products is Ethernet. However, when considering network media, it is important to consider what the long term needs will be. Although ATM is a new standard, it is showing signs of becoming the next logical step to meet the needs of high speed networks; This thesis is a survey on ATM, and PACS. All the concepts involved in developing a PACS are presented in an orderly manner. It presents the recent developments in ATM, its applicability to PACS and the issues to be resolved for realising an ATM-based complete PACS. This work will be useful in providing the latest information, for any future research on ATM-based networks, and PACS

Oscillatory mechanisms for controlling information flow in neural circuits

Mammalian brains generate complex, dynamic structures of oscillatory activity, in which distributed regions transiently engage in coherent oscillation, often at specific stages in behavioural or cognitive tasks. Much is now known about the dynamics underlying local circuit synchronisation and the phenomenology of where and when such activity occurs. While oscillations have been implicated in many high level processes, for most such phenomena we cannot say with confidence precisely what they are doing at an algorithmic or implementational level. This thesis presents work towards understanding the dynamics and possible function of large scale oscillatory network activity. We first address the question of how coherent oscillatory activity emerges between local networks by measuring phase response curves of an oscillating network in vitro. The network phase response curves provide mechanistic insight into inter-region synchronisation of local network oscillators. Highly simplified firing models are shown to reproduce the experimental data with remarkable accuracy. We then focus on one hypothesised computational function of network oscillations; flexibly controlling the gain of signal flow between anatomically connected networks. We investigate coding strategies and algorithmic operations that support flexible control of signal flow by oscillations, and their implementation by network dynamics. We identify two readout algorithms which selectively recover population rate coded signal with specific oscillatory modulations while ignoring other distracting inputs. By designing a spiking network model that implements one of these mechanisms, we demonstrate oscillatory control of signal flow in convergent pathways. We then investigate constraints on the structures of oscillatory activity that can be used to accurately and selectively control signal flow. Our results suggest that for inputs to be accurately distinguished from one another their oscillatory modulations must be close to orthogonal. This has implications for interpreting in vivo oscillatory activity, and may be an organising principle for the spatio-temporal structure of brain oscillations

Dynamic bandwidth allocation in ATM networks

Includes bibliographical references.This thesis investigates bandwidth allocation methodologies to transport new emerging bursty traffic types in ATM networks. However, existing ATM traffic management solutions are not readily able to handle the inevitable problem of congestion as result of the bursty traffic from the new emerging services. This research basically addresses bandwidth allocation issues for bursty traffic by proposing and exploring the concept of dynamic bandwidth allocation and comparing it to the traditional static bandwidth allocation schemes

Bridges Structural Health Monitoring and Deterioration Detection Synthesis of Knowledge and Technology

INE/AUTC 10.0

Cellular, Wide-Area, and Non-Terrestrial IoT: A Survey on 5G Advances and the Road Towards 6G

The next wave of wireless technologies is proliferating in connecting things among themselves as well as to humans. In the era of the Internet of things (IoT), billions of sensors, machines, vehicles, drones, and robots will be connected, making the world around us smarter. The IoT will encompass devices that must wirelessly communicate a diverse set of data gathered from the environment for myriad new applications. The ultimate goal is to extract insights from this data and develop solutions that improve quality of life and generate new revenue. Providing large-scale, long-lasting, reliable, and near real-time connectivity is the major challenge in enabling a smart connected world. This paper provides a comprehensive survey on existing and emerging communication solutions for serving IoT applications in the context of cellular, wide-area, as well as non-terrestrial networks. Specifically, wireless technology enhancements for providing IoT access in fifth-generation (5G) and beyond cellular networks, and communication networks over the unlicensed spectrum are presented. Aligned with the main key performance indicators of 5G and beyond 5G networks, we investigate solutions and standards that enable energy efficiency, reliability, low latency, and scalability (connection density) of current and future IoT networks. The solutions include grant-free access and channel coding for short-packet communications, non-orthogonal multiple access, and on-device intelligence. Further, a vision of new paradigm shifts in communication networks in the 2030s is provided, and the integration of the associated new technologies like artificial intelligence, non-terrestrial networks, and new spectra is elaborated. Finally, future research directions toward beyond 5G IoT networks are pointed out.Comment: Submitted for review to IEEE CS&