The representation of subordinate shape similarity in human occipitotemporal cortex

We investigated the coding of subordinate shape similarity in human object-selective cortex in two event-related functional magnetic resonance adaptation (fMR-A) experiments. Previous studies using faces have concluded that there is a narrow tuning of neuronal populations selective to each face, and that tuning is relative to the expected "average" face (norm-based encoding). Here we investigated these issues using outlines of animals and tools occupying a particular position on different morphing sequences per category. In a first experiment, we inferred the width of neural tuning to exemplars by examining whether the release from adaptation with increasing shape changes between two stimuli asymptotes. In a second experiment, we compared the response to central and extreme positions in shape space while controlling for the number of presentations of each unique stimulus to study whether the expected "average" category exemplar plays a role. The current fMR-A results show that a small change in exemplar shape produces a large release of adaptation, but only for outline shape changes of animals and not for man-made tools. Furthermore, our results suggested that central and extreme positions were not treated differently. Together, these results suggest a narrow tuning in object-selective cortex for individual exemplars from natural object categories, consistent with an exemplar-based encoding principle

A novel network architecture for train-to-wayside communication with quality of service over heterogeneous wireless networks

In the railway industry, there are nowadays different actors who would like to send or receive data from the wayside to an onboard device or vice versa. These actors are e.g., the Train Operation Company, the Train Constructing Company, a Content Provider, etc. This requires a communication module on each train and at the wayside. These modules interact with each other over heterogeneous wireless links. This system is referred to as the Train-to-Wayside Communication System (TWCS). While there are already a lot of deployments using a TWCS, the implementation of quality of service, performance enhancing proxies (PEP) and the network mobility functions have not yet been fully integrated in TWCS systems. Therefore, we propose a novel and modular IPv6-enabled TWCS architecture in this article. It jointly tackles these functions and considers their mutual dependencies and relationships. DiffServ is used to differentiate between service classes and priorities. Virtual local area networks are used to differentiate between different service level agreements. In the PEP, we propose to use a distributed TCP accelerator to optimize bandwidth usage. Concerning network mobility, we propose to use the SCTP protocol (with Dynamic Address Reconfiguration and PR-SCTP extensions) to create a tunnel per wireless link, in order to support the reliable transmission of data between the accelerators. We have analyzed different design choices, pinpointed the main implementation challenges and identified candidate solutions for the different modules in the TWCS system. As such, we present an elaborated framework that can be used for prototyping a fully featured TWCS

Large-scale real-world data on a multidisciplinary approach to spinal cord stimulation for persistent spinal pain syndromes: first evaluation of the Neuro-Pain® nationwide screening and follow-up interactive register

IntroductionSpinal cord stimulation is a common treatment option for neuropathic pain conditions. Despite its extensive use and multiple technological evolutions, long term efficacy of spinal cord stimulation is debated. Most studies on spinal cord stimulation include a rather limited number of patients and/or follow-ups over a limited period. Therefore, there is an urgent need for real-world, long-term data.MethodsIn 2018, the Belgian government initiated a nationwide secure platform for the follow-up of all new and existing spinal cord stimulation therapies. This is a unique approach used worldwide. Four years after the start of centralized recording, the first global extraction of data was performed.ResultsHerein, we present the findings, detailing the different steps in the centralized procedure, as well as the observed patient and treatment characteristics. Furthermore, we identified dropouts during the screening process, the reasons behind discontinuation, and the evolution of key indicators during the trial period. In addition, we obtained the first insights into the evolution of the clinical impact of permanent implants on the overall functioning and quality of life of patients in the long-term.DiscussionAlthough these findings are the results of the first data extraction, some interesting conclusions can be drawn. The long-term outcomes of neuromodulation are complex and subject to many variables. Future data extraction will allow us to identify these confounding factors and the early predictors of success. In addition, we will propose further optimization of the current process

Similarity, typicality, and category-level matching of morphed outlines of everyday objects

During visual object categorization, a match must be found between the input image and stored information about basic-level categories. Graf (2002) suggested the involvement of analog transformational, shape-changing processes to align the memory representation of the category with the perceptual representation of the current stimulus. Here we compare the predictions of alignment models with exemplar-based models using morphing between four exemplar outlines within each of eleven categories. Overall, with increasing transformational distance between two exemplars of the same category, reaction times to decide whether they belong to the same category in a sequential matching paradigm increased, while rated similarity between both exemplars decreased. However, in contrast to alignment accounts, exemplar-based accounts (a) can correctly predict the observed dissociation between typicality and categorization time, and allow the observed (b) deviations from sequential additivity, and (c) non-linear relations between transformational distance and rated similarity. By discussing integrations of exemplar-based theories with neglected processes such as information accumulation, response competition, response priming, and gain-modulation, a view of the recognition process from input to response emerges, which increases the validity and scope of modern exemplar-based categorization and recognition models.status: publishe