From Phineas Gage and Monsieur Leborgne to H.M.: Revisiting Disconnection Syndromes

On the 50th anniversary of Norman Geschwind's seminal paper entitled 'Disconnexion syndrome in animal and man', we pay tribute to his ideas by applying contemporary tractographymethods to understand whitematter disconnection in 3 classic cases that made history in behavioral neurology.We first documented the locus and extent of the brain lesion from the computerized tomography of Phineas Gage's skull and themagnetic resonance images of Louis Victor Leborgne's brain, Broca's first patient, and Henry Gustave Molaison. We then applied the reconstructed lesions to an atlas of white matter connections obtained from diffusion tractography of 129 healthy adults. Our results showed that in all 3 patients, disruption extended to connections projecting to areas distant from the lesion.We confirmed that the damaged tracts link areas that in contemporary neuroscience are considered functionally engaged for tasks related to emotion and decision-making (Gage), language production (Leborgne), and declarative memory (Molaison). Our findings suggest that even historic cases should be reappraised within a disconnection framework whose principles were plainly established by the associationist schools in the last 2 centuries

The ABCD of usability testing

We introduce a methodology for tracking and auditing feedback, errors and suggestions for software packages. This short paper describes how we innovate on the evaluation mechanism, introducing an (Antecedent, Barrier, Consequence and Development) ABCD form, embedded within an eParticipation platform to enable end users to easily report on any usability issues. This methodology will be utilised to improve the STEP cloud eParticipation platform (part of the current STEP Horizon2020 project http://step4youth.eu. The platform is currently being piloted in real life contexts, with the participation of public authorities that are integrating the eParticipation platform into their regular decision-making practices. The project is involving young people, through engagement and motivation strategies and giving them a voice in Environmental decision making at the local level. The pilot evaluation aims to demonstrate how open engagement needs to be embedded within public sector processes and the usability methodology reported here will help to identify the key barriers for wide scale deployment of the platform

Wearable Haptic Devices for Gait Re-education by Rhythmic Haptic Cueing

This research explores the development and evaluation of wearable haptic devices for gait sensing and rhythmic haptic cueing in the context of gait re-education for people with neurological and neurodegenerative conditions. Many people with long-term neurological and neurodegenerative conditions such as Stroke, Brain Injury, Multiple Sclerosis or Parkinson’s disease suffer from impaired walking gait pattern. Gait improvement can lead to better fluidity in walking, improved health outcomes, greater independence, and enhanced quality of life. Existing lab-based studies with wearable devices have shown that rhythmic haptic cueing can cause immediate improvements to gait features such as temporal symmetry, stride length, and walking speed. However, current wearable systems are unsuitable for self-managed use for in-the-wild applications with people having such conditions. This work aims to investigate the research question of how wearable haptic devices can help in long-term gait re-education using rhythmic haptic cueing. A longitudinal pilot study has been conducted with a brain trauma survivor, providing rhythmic haptic cueing using a wearable haptic device as a therapeutic intervention for a two-week period. Preliminary results comparing pre and post-intervention gait measurements have shown improvements in walking speed, temporal asymmetry, and stride length. The pilot study has raised an array of issues that require further study. This work aims to develop and evaluate prototype systems through an iterative design process to make possible the self-managed use of such devices in-the-wild. These systems will directly provide therapeutic intervention for gait re-education, offer enhanced information for therapists, remotely monitor dosage adherence and inform treatment and prognoses over the long-term. This research will evaluate the use of technology from the perspective of multiple stakeholders, including clinicians, carers and patients. This work has the potential to impact clinical practice nationwide and worldwide in neuro-physiotherapy

The State of the Art in Multilayer Network Visualization

Modelling relationships between entities in real-world systems with a simple graph is a standard approach. However, reality is better embraced as several interdependent subsystems (or layers). Recently the concept of a multilayer network model has emerged from the field of complex systems. This model can be applied to a wide range of real-world datasets. Examples of multilayer networks can be found in the domains of life sciences, sociology, digital humanities and more. Within the domain of graph visualization there are many systems which visualize datasets having many characteristics of multilayer graphs. This report provides a state of the art and a structured analysis of contemporary multilayer network visualization, not only for researchers in visualization, but also for those who aim to visualize multilayer networks in the domain of complex systems, as well as those developing systems across application domains. We have explored the visualization literature to survey visualization techniques suitable for multilayer graph visualization, as well as tools, tasks, and analytic techniques from within application domains. This report also identifies the outstanding challenges for multilayer graph visualization and suggests future research directions for addressing them

State Transition Graphs for Semantic Analysis of Movement Behaviours

A behaviour can be defined as a sequence of states or activities occurring one after another. A behaviour consisting of a finite number of reoccurring states/activities may be represented by a directed weighted graph with nodes and edges corresponding, respectively, to the possible states and transitions between them, while the weights represent the probabilities or frequencies of the state and transition occurrences. The same applies to multiple behaviours sharing the same set of possible states. In analysis of movement data, state transition graphs can be used to represent semantic abstractions of mobility behaviours, where states correspond to semantic categories of visited places (such as ‘home’, ‘work’, ‘shop’), activities of moving objects (‘driving’, ‘walking’, ‘exercising’, etc.) or characteristics of the movement (‘straight movement’, ‘sharp turn’, ‘acceleration’, ‘stop’, etc.). Such a representation supports the exploration and analysis of the semantic aspect (i.e. the meaning or purposes) of movement. For comprehensive analysis of movement data, state transition graphs need to be combined with representations reflecting the spatial and temporal aspects of the movement. This requires appropriate coordination between different visual displays (graphs, maps and temporal views) and appropriate reaction to analytical operations applied to any of the representations of the same data. We define in an abstract way the reactions of a graph display to analytical operations of querying, partitioning and direct selection. We also propose visual and interactive display features supporting comparisons between data subsets and between results of different operations. We demonstrate the use of the display features by examples of real-world and synthetic data sets

TreeDyn: towards dynamic graphics and annotations for analyses of trees

BACKGROUND: Analyses of biomolecules for biodiversity, phylogeny or structure/function studies often use graphical tree representations. Many powerful tree editors are now available, but existing tree visualization tools make little use of meta-information related to the entities under study such as taxonomic descriptions or gene functions that can hardly be encoded within the tree itself (if using popular tree formats). Consequently, a tedious manual analysis and post-processing of the tree graphics are required if one needs to use external information for displaying or investigating trees. RESULTS: We have developed TreeDyn, a tool using annotations and dynamic graphical methods for editing and analyzing multiple trees. The main features of TreeDyn are 1) the management of multiple windows and multiple trees per window, 2) the export of graphics to several standard file formats with or without HTML encapsulation and a new format called TGF, which enables saving and restoring graphical analysis, 3) the projection of texts or symbols facing leaf labels or linked to nodes, through manual pasting or by using annotation files, 4) the highlight of graphical elements after querying leaf labels (or annotations) or by selection of graphical elements and information extraction, 5) the highlight of targeted trees according to a source tree browsed by the user, 6) powerful scripts for automating repetitive graphical tasks, 7) a command line interpreter enabling the use of TreeDyn through CGI scripts for online building of trees, 8) the inclusion of a library of packages dedicated to specific research fields involving trees. CONCLUSION: TreeDyn is a tree visualization and annotation tool which includes tools for tree manipulation and annotation and uses meta-information through dynamic graphical operators or scripting to help analyses and annotations of single trees or tree collections

Methods for visual mining of genomic and proteomic data atlases

<p>Abstract</p> <p>Background</p> <p>As the volume, complexity and diversity of the information that scientists work with on a daily basis continues to rise, so too does the requirement for new analytic software. The analytic software must solve the dichotomy that exists between the need to allow for a high level of scientific reasoning, and the requirement to have an intuitive and easy to use tool which does not require specialist, and often arduous, training to use. Information visualization provides a solution to this problem, as it allows for direct manipulation and interaction with diverse and complex data. The challenge addressing bioinformatics researches is how to apply this knowledge to data sets that are continually growing in a field that is rapidly changing.</p> <p>Results</p> <p>This paper discusses an approach to the development of visual mining tools capable of supporting the mining of massive data collections used in systems biology research, and also discusses lessons that have been learned providing tools for both local researchers and the wider community. Example tools were developed which are designed to enable the exploration and analyses of both proteomics and genomics based atlases. These atlases represent large repositories of raw and processed experiment data generated to support the identification of biomarkers through mass spectrometry (the PeptideAtlas) and the genomic characterization of cancer (The Cancer Genome Atlas). Specifically the tools are designed to allow for: the visual mining of thousands of mass spectrometry experiments, to assist in designing informed targeted protein assays; and the interactive analysis of hundreds of genomes, to explore the variations across different cancer genomes and cancer types.</p> <p>Conclusions</p> <p>The mining of massive repositories of biological data requires the development of new tools and techniques. Visual exploration of the large-scale atlas data sets allows researchers to mine data to find new meaning and make sense at scales from single samples to entire populations. Providing linked task specific views that allow a user to start from points of interest (from diseases to single genes) enables targeted exploration of thousands of spectra and genomes. As the composition of the atlases changes, and our understanding of the biology increase, new tasks will continually arise. It is therefore important to provide the means to make the data available in a suitable manner in as short a time as possible. We have done this through the use of common visualization workflows, into which we rapidly deploy visual tools. These visualizations follow common metaphors where possible to assist users in understanding the displayed data. Rapid development of tools and task specific views allows researchers to mine large-scale data almost as quickly as it is produced. Ultimately these visual tools enable new inferences, new analyses and further refinement of the large scale data being provided in atlases such as PeptideAtlas and The Cancer Genome Atlas.</p

TMEM33 regulates intracellular calcium homeostasis in renal tubular epithelial cells

Mutations in the polycystins cause autosomal dominant polycystic kidney disease (ADPKD). Here we show that transmembrane protein 33 (TMEM33) interacts with the ion channel polycystin-2 (PC2) at the endoplasmic reticulum (ER) membrane, enhancing its opening over the whole physiological calcium range in ER liposomes fused to planar bilayers. Consequently, TMEM33 reduces intracellular calcium content in a PC2-dependent manner, impairs lysosomal calcium refilling, causes cathepsins translocation, inhibition of autophagic flux upon ER stress, as well as sensitization to apoptosis. Invalidation of TMEM33 in the mouse exerts a potent protection against renal ER stress. By contrast, TMEM33 does not influence pkd2-dependent renal cystogenesis in the zebrafish. Together, our results identify a key role for TMEM33 in the regulation of intracellular calcium homeostasis of renal proximal convoluted tubule cells and establish a causal link between TMEM33 and acute kidney injury