Attributing and Referencing (Research) Software: Best Practices and Outlook from Inria

Software is a fundamental pillar of modern scientiic research, not only in computer science, but actually across all elds and disciplines. However, there is a lack of adequate means to cite and reference software, for many reasons. An obvious rst reason is software authorship, which can range from a single developer to a whole team, and can even vary in time. The panorama is even more complex than that, because many roles can be involved in software development: software architect, coder, debugger, tester, team manager, and so on. Arguably, the researchers who have invented the key algorithms underlying the software can also claim a part of the authorship. And there are many other reasons that make this issue complex. We provide in this paper a contribution to the ongoing eeorts to develop proper guidelines and recommendations for software citation, building upon the internal experience of Inria, the French research institute for digital sciences. As a central contribution, we make three key recommendations. (1) We propose a richer taxonomy for software contributions with a qualitative scale. (2) We claim that it is essential to put the human at the heart of the evaluation. And (3) we propose to distinguish citation from reference

Cellular Self-Organising Maps - CSOM

International audienceThis paper presents CSOM, a Cellular Self-Organising Map which performs weight update in a cellular manner. Instead of updating weights towards new input vectors, it uses a signal propagation originated from the best matching unit to every other neuron in the network. Interactions between neurons are thus local and distributed. In this paper we present performance results showing than CSOM can obtain faster and better quantisation than classical SOM when used on high-dimensional vectors. We also present an application on video compression based on vector quantisation, in which CSOM outperforms SOM

Novelty detection with self-organizing maps for autonomous extraction of salient tracking features

International audienceIn the image processing field, many tracking algorithms rely on prior knowledge like color, shape or even need a database of the objects to be tracked. This may be a problem for some real world applications that cannot fill those prerequisite. Based on image compression techniques, we propose to use Self-Organizing Maps to robustly detect novelty in the input video stream and to produce a saliency map which will outline unusual objects in the visual environment. This saliency map is then processed by a Dynamic Neural Field to extract a robust and continuous tracking of the position of the object. Our approach is solely based on unsupervised neural networks and does not need any prior knowledge, therefore it has a high adaptability to different inputs and a strong robustness to noisy environments

Birds of a Feather Flock Together: Experience-Driven Formation of Visual Object Categories in Human Ventral Temporal Cortex

The present functional magnetic resonance imaging study provides direct evidence on visual object-category formation in the human brain. Although brain imaging has demonstrated object-category specific representations in the occipitotemporal cortex, the crucial question of how the brain acquires this knowledge has remained unresolved. We designed a stimulus set consisting of six highly similar bird types that can hardly be distinguished without training. All bird types were morphed with one another to create different exemplars of each category. After visual training, fMRI showed that responses in the right fusiform gyrus were larger for bird types for which a discrete category-boundary was established as compared with not-trained bird types. Importantly, compared with not-trained bird types, right fusiform responses were smaller for visually similar birds to which subjects were exposed during training but for which no category-boundary was learned. These data provide evidence for experience-induced shaping of occipitotemporal responses that are involved in category learning in the human brain

The skull of Epidolops ameghinoi from the early Eocene Itaboraí fauna, southeastern Brazil, and the affinities of the extinct marsupialiform order Polydolopimorphia

The skull of the polydolopimorphian marsupialiform Epidolops ameghinoi is described in detail for the first time, based on a single well-preserved cranium and associated left and right dentaries plus additional craniodental fragments, all from the early Eocene (53-50 million year old) Itaboraí fauna in southeastern Brazil. Notable craniodental features of E. ameghinoi include absence of a masseteric process, very small maxillopalatine fenestrae, a prominent pterygoid fossa enclosed laterally by a prominent ectopterygoid crest, an absent or tiny transverse canal foramen, a simple, planar glenoid fossa, and a postglenoid foramen that is immediately posterior to the postglenoid process. Most strikingly, the floor of the hypotympanic sinus was apparently unossified, a feature found in several stem marsupials but absent in all known crown marsupials. "Type II" marsupialiform petrosals previously described from Itaboraí plausibly belong to E. ameghinoi; in published phylogenetic analyses, these petrosals fell outside (crown-clade) Marsupialia. "IMG VII" tarsals previously referred to E. ameghinoi do not share obvious synapomorphies with any crown marsupial clade, nor do they resemble those of the only other putative polydolopimorphians represented by tarsal remains, namely the argyrolagids. Most studies have placed Polydolopimorphia within Marsupialia, related to either Paucituberculata, or to Microbiotheria and Diprotodontia. However, diprotodonty almost certainly evolved independently in polydolopimorphians, paucituberculatans and diprotodontians, and Epidolops does not share obvious synapomorphies with any marsupial order. Epidolops is dentally specialized, but several morphological features appear to be more plesiomorphic than any crown marsupial. It seems likely Epidolops that falls outside Marsupialia, as do morphologically similar forms such as Bonapartherium and polydolopids. Argyrolagids differ markedly in their known morphology from Epidolops but share some potential apomorphies with paucituberculatans. It is proposed that Polydolopimorphia as currently recognised is polyphyletic, and that argyrolagids (and possibly other taxa currently included in Argyrolagoidea, such as groeberiids and patagoniids) are members of Paucituberculata. This hypothesis is supported by Bayesian non-clock phylogenetic analyses of a total evidence matrix comprising DNA sequence data from five nuclear protein-coding genes, indels, retroposon insertions and morphological characters: Epidolops falls outside Marsupialia, whereas argyrolagids form a clade with the paucituberculatans Caenolestes and Palaeothentes, regardless of whether the Type II petrosals and IMG VII tarsals are used to score characters for Epidolops or not. There is no clear evidence for the presence of crown marsupials at Itaboraí, and it is possible that the origin and early evolution of Marsupialia was restricted to the "Austral Kingdom" (southern South America, Antarctica, and Australia)

Coherence and recurrency: maintenance, control and integration in working memory

Working memory (WM), including a ‘central executive’, is used to guide behavior by internal goals or intentions. We suggest that WM is best described as a set of three interdependent functions which are implemented in the prefrontal cortex (PFC). These functions are maintenance, control of attention and integration. A model for the maintenance function is presented, and we will argue that this model can be extended to incorporate the other functions as well. Maintenance is the capacity to briefly maintain information in the absence of corresponding input, and even in the face of distracting information. We will argue that maintenance is based on recurrent loops between PFC and posterior parts of the brain, and probably within PFC as well. In these loops information can be held temporarily in an active form. We show that a model based on these structural ideas is capable of maintaining a limited number of neural patterns. Not the size, but the coherence of patterns (i.e., a chunking principle based on synchronous firing of interconnected cell assemblies) determines the maintenance capacity. A mechanism that optimizes coherent pattern segregation, also poses a limit to the number of assemblies (about four) that can concurrently reverberate. Top-down attentional control (in perception, action and memory retrieval) can be modelled by the modulation and re-entry of top-down information to posterior parts of the brain. Hierarchically organized modules in PFC create the possibility for information integration. We argue that large-scale multimodal integration of information creates an ‘episodic buffer’, and may even suffice for implementing a central executive

Effect of spinal manipulation on sensorimotor functions in back pain patients: study protocol for a randomised controlled trial

<p>Abstract</p> <p>Background</p> <p>Low back pain (LBP) is a recognized public health problem, impacting up to 80% of US adults at some point in their lives. Patients with LBP are utilizing integrative health care such as spinal manipulation (SM). SM is the therapeutic application of a load to specific body tissues or structures and can be divided into two broad categories: SM with a high-velocity low-amplitude load, or an impulse "thrust", (HVLA-SM) and SM with a low-velocity variable-amplitude load (LVVA-SM). There is evidence that sensorimotor function in people with LBP is altered. This study evaluates the sensorimotor function in the lumbopelvic region, as measured by postural sway, response to sudden load and repositioning accuracy, following SM to the lumbar and pelvic region when compared to a sham treatment.</p> <p>Methods/Design</p> <p>A total of 219 participants with acute, subacute or chronic low back pain are being recruited from the Quad Cities area located in Iowa and Illinois. They are allocated through a minimization algorithm in a 1:1:1 ratio to receive either 13 HVLA-SM treatments over 6 weeks, 13 LVVA-SM treatments over 6 weeks or 2 weeks of a sham treatment followed by 4 weeks of full spine "doctor's choice" SM. Sensorimotor function tests are performed before and immediately after treatment at baseline, week 2 and week 6. Self-report outcome assessments are also collected. The primary aims of this study are to 1) determine immediate pre to post changes in sensorimotor function as measured by postural sway following delivery of a single HVLA-SM or LVVA-SM treatment when compared to a sham treatment and 2) to determine changes from baseline to 2 weeks (4 treatments) of HVLA-SM or LVVA-SM compared to a sham treatment. Secondary aims include changes in response to sudden loads and lumbar repositioning accuracy at these endpoints, estimating sensorimotor function in the SM groups after 6 weeks of treatment, and exploring if changes in sensorimotor function are associated with changes in self-report outcome assessments.</p> <p>Discussion</p> <p>This study may provide clues to the sensorimotor mechanisms that explain observed functional deficits associated with LBP, as well as the mechanism of action of SM.</p> <p>Trial registration</p> <p>This trial is registered in ClinicalTrials.gov, with the ID number of <a href="http://www.clinicaltrials.gov/ct2/show/NCT00830596">NCT00830596</a>, registered on January 27, 2009. The first participant was allocated on 30 January 2009 and the final participant was allocated on 17 March 2011.</p

Copying and Evolution of Neuronal Topology

We propose a mechanism for copying of neuronal networks that is of considerable interest for neuroscience for it suggests a neuronal basis for causal inference, function copying, and natural selection within the human brain. To date, no model of neuronal topology copying exists. We present three increasingly sophisticated mechanisms to demonstrate how topographic map formation coupled with Spike-Time Dependent Plasticity (STDP) can copy neuronal topology motifs. Fidelity is improved by error correction and activity-reverberation limitation. The high-fidelity topology-copying operator is used to evolve neuronal topologies. Possible roles for neuronal natural selection are discussed

The Brain's Router: A Cortical Network Model of Serial Processing in the Primate Brain

The human brain efficiently solves certain operations such as object recognition and categorization through a massively parallel network of dedicated processors. However, human cognition also relies on the ability to perform an arbitrarily large set of tasks by flexibly recombining different processors into a novel chain. This flexibility comes at the cost of a severe slowing down and a seriality of operations (100–500 ms per step). A limit on parallel processing is demonstrated in experimental setups such as the psychological refractory period (PRP) and the attentional blink (AB) in which the processing of an element either significantly delays (PRP) or impedes conscious access (AB) of a second, rapidly presented element. Here we present a spiking-neuron implementation of a cognitive architecture where a large number of local parallel processors assemble together to produce goal-driven behavior. The precise mapping of incoming sensory stimuli onto motor representations relies on a “router” network capable of flexibly interconnecting processors and rapidly changing its configuration from one task to another. Simulations show that, when presented with dual-task stimuli, the network exhibits parallel processing at peripheral sensory levels, a memory buffer capable of keeping the result of sensory processing on hold, and a slow serial performance at the router stage, resulting in a performance bottleneck. The network captures the detailed dynamics of human behavior during dual-task-performance, including both mean RTs and RT distributions, and establishes concrete predictions on neuronal dynamics during dual-task experiments in humans and non-human primates

Search for dark photons in rare Z boson decays with the ATLAS detector

A search for events with a dark photon produced in association with a dark Higgs boson via rare decays of the standard model Z boson is presented, using 139     fb − 1 of √ s = 13     TeV proton-proton collision data recorded by the ATLAS detector at the Large Hadron Collider. The dark boson decays into a pair of dark photons, and at least two of the three dark photons must each decay into a pair of electrons or muons, resulting in at least two same-flavor opposite-charge lepton pairs in the final state. The data are found to be consistent with the background prediction, and upper limits are set on the dark photon’s coupling to the dark Higgs boson times the kinetic mixing between the standard model photon and the dark photon, α D ϵ 2 , in the dark photon mass range of [5, 40] GeV except for the Υ mass window [8.8, 11.1] GeV. This search explores new parameter space not previously excluded by other experiments