Liz J. Stuart

Animator: a tool for the animation of parallel coordinates

In this paper, an uncommon use of parallel coordinates is illustrated using the Animator software. Animator is used to plot the parallel coordinates of objects in multi-dimensional space. Subsequently, the Animator software is used to animate the movement of individual objects, in this multi-dimensional space over time. Initial empirical studies of this technique for the visualization of data from Neurophysiological research, multi-dimensional spike train datasets, have shown that the technique is useful. Thus, Animator was developed for public access and is now freely available (including source code) from the Visualization Lab at the University of Plymouth, www.plymouth.ac.uk/infovis.

Visualisation of synchronous firing in multi-dimensional spike trains.

The gravity transform algorithm is used to study the dependencies in firing of multi-dimensional spike trains. The pros and cons of this algorithm are discussed and the necessity for improved representation of output data is demonstrated. Parallel coordinates are introduced to visualise the results of the gravity transform and principal component analysis (PCA) is used to reduce the quantity of data represented whilst minimising loss of information.

Easy Grocery: 3D Visualization in e-Grocery

There are many deficiencies in the traditional electronic commerce schema. The main problem for consideration is the text and picture based design that underpins current HTML systems. This paper presents the online grocery shopping system called Easy Grocery which is available at www.easygrocery.co.uk. This system is based on the innovative concept of using a 3D system as an interface to the user during their shopping experience. Furthermore, this 3D system follows the mental model of the user as opposed to that of the developer. Additionally, the user is able to select the layout of the online store so that it matches the layout of their local store, thus enabling even new users to exploit their own knowledge of how items are organized to shop efficiently. The Easy Grocery system demonstrates that 3D online shopping can provide significant advantages for both consumers and retailers

Advanced correlation grid: Analysis and visualisation of functional connectivity among multiple spike trains

BACKGROUND This study analyses multiple spike trains (MST) data, defines its functional connectivity and subsequently visualises an accurate diagram of connections. This is a challenging problem. For example, it is difficult to distinguish the common input and the direct functional connection of two spike trains. NEW METHOD The new method presented in this paper is based on the traditional pairwise cross-correlation function (CCF) and a new combination of statistical techniques. First, the CCF is used to create the Advanced Correlation Grid (ACG) correlation where both the significant peak of the CCF and the corresponding time delay are used for detailed analysis of connectivity. Second, these two features of functional connectivity are used to classify connections. Finally, the visualization technique is used to represent the topology of functional connections. RESULTS Examples are presented in the paper to demonstrate the new Advanced Correlation Grid method and to show how it enables discrimination between (i) influence from one spike train to another through an intermediate spike train and (ii) influence from one common spike train to another pair of analysed spike trains. COMPARISON WITH EXISTING METHODS The ACG method enables scientists to automatically distinguish between direct connections from spurious connections such as common source connection and indirect connection whereas existing methods require in-depth analysis to identify such connections. CONCLUSIONS The ACG is a new and effective method for studying functional connectivity of multiple spike trains. This method can identify accurately all the direct connections and can distinguish common source and indirect connections automatically.

iRaster: a novel information visualization tool to explore spatiotemporal patterns in multiple spike trains.

Over the last few years, simultaneous recordings of multiple spike trains have become widely used by neuroscientists. Therefore, it is important to develop new tools for analysing multiple spike trains in order to gain new insight into the function of neural systems. This paper describes how techniques from the field of visual analytics can be used to reveal specific patterns of neural activity. An interactive raster plot called iRaster has been developed. This software incorporates a selection of statistical procedures for visualization and flexible manipulations with multiple spike trains. For example, there are several procedures for the re-ordering of spike trains which can be used to unmask activity propagation, spiking synchronization, and many other important features of multiple spike train activity. Additionally, iRaster includes a rate representation of neural activity, a combined representation of rate and spikes, spike train removal and time interval removal. Furthermore, it provides multiple coordinated views, time and spike train zooming windows, a fisheye lens distortion, and dissemination facilities. iRaster is a user friendly, interactive, flexible tool which supports a broad range of visual representations. This tool has been successfully used to analyse both synthetic and experimentally recorded datasets. In this paper, the main features of iRaster are described and its performance and effectiveness are demonstrated using various types of data including experimental multi-electrode array recordings from the ganglion cell layer in mouse retina. iRaster is part of an ongoing research project called VISA (Visualization of Inter-Spike Associations) at the Visualization Lab in the University of Plymouth. The overall aim of the VISA project is to provide neuroscientists with the ability to freely explore and analyse their data. The software is freely available from the Visualization Lab website (see www.plymouth.ac.uk/infovis).

Developing Innovative Tool to Enhance the Effectiveness of Decision Support System

This research centres on Usability Evaluation Methods (UEMSs) with the aim of supporting developers’ decisions in the use of learning resources in achieving efficient usable system design. The suggestion is made pertaining to a new usability evaluation model dEv (stand for Design Evaluation) with the objective to support decisions to overcome three key obstacles: firstly, the involvement of users in the preliminary stages of the development process; (2) developers’ mind set-related issues as a result of either their lack of UEMS or the provision of too many; and (3) the complete lack of understanding surrounding UEMS importance. An experimental approach was applied in addition to a survey-based questionnaire in an effort to examining the issues pertaining to UEMS. Empirical works were carried out with system developers in order to test the dEv, the results of which have been presented from the empirical study to support various considerations, such as: system developers’ decisions and their involvement in the earlier phases of the design of systems; the gathering of specifications and end-users’ feedback; and enhancing usability evaluation learning capacity.

Information visualization for knowledge extraction in neural networks

In this paper, a user-centred innovative method of knowledge extraction in neural networks is described. This is based on information visualization techniques and tools for artificial and natural neural systems. Two case studies are presented. The first demonstrates the use of various information visualization methods for the identification of neuronal structure (e.g. groups of neurons that fire synchronously) in spiking neural networks. The second study applies similar techniques to the study of embodied cognitive robots in order to identify the complex organization of behaviour in the robots neural controller.