Dynamics of trimming the content of face representations for categorization in the brain

To understand visual cognition, it is imperative to determine when, how and with what information the human brain categorizes the visual input. Visual categorization consistently involves at least an early and a late stage: the occipito-temporal N170 event related potential related to stimulus encoding and the parietal P300 involved in perceptual decisions. Here we sought to understand how the brain globally transforms its representations of face categories from their early encoding to the later decision stage over the 400 ms time window encompassing the N170 and P300 brain events. We applied classification image techniques to the behavioral and electroencephalographic data of three observers who categorized seven facial expressions of emotion and report two main findings: (1) Over the 400 ms time course, processing of facial features initially spreads bilaterally across the left and right occipito-temporal regions to dynamically converge onto the centro-parietal region; (2) Concurrently, information processing gradually shifts from encoding common face features across all spatial scales (e.g. the eyes) to representing only the finer scales of the diagnostic features that are richer in useful information for behavior (e.g. the wide opened eyes in 'fear'; the detailed mouth in 'happy'). Our findings suggest that the brain refines its diagnostic representations of visual categories over the first 400 ms of processing by trimming a thorough encoding of features over the N170, to leave only the detailed information important for perceptual decisions over the P300

On Abduction in Design

The mechanism of design reasoning from function to form is addressed by examining the possibility of explaining it as abduction. We propose a new interpretation to some definitions of innovative abduction, to show first that the concept, idea, as the basis for solution must be present in the inference, and second, that the reasoning from function to form is best modeled as a two-step inference, both of the innovative abduction pattern. This double-abductive reasoning is shown also to be the main form of reasoning in the empirically-derived “parameter analysis” method of conceptual design. Finally, the introduction of abduction into design theory is critically assessed, and in so doing, topics for future research are suggested

On the use of Process Mining and Machine Learning to support decision making in systems design

Research on process mining and machine learning techniques has recently received a significant amount of attention by product development and management communities. Indeed, these techniques allow both an automatic process and activity discovery and thus are high added value services that help reusing knowledge to support decision-making. This paper proposes a double layer framework aiming to identify the most significant process patterns to be executed depending on the design context. Simultaneously, it proposes the most significant parameters for each activity of the considered process pattern. The framework is applied on a specific design example and is partially implemented.FUI GONTRAN

FRASS: the web-server for RNA structural comparison

<p>Abstract</p> <p>Background</p> <p>The impressive increase of novel RNA structures, during the past few years, demands automated methods for structure comparison. While many algorithms handle only small motifs, few techniques, developed in recent years, (ARTS, DIAL, SARA, SARSA, and LaJolla) are available for the structural comparison of large and intact RNA molecules.</p> <p>Results</p> <p>The FRASS web-server represents a RNA chain with its Gauss integrals and allows one to compare structures of RNA chains and to find similar entries in a database derived from the Protein Data Bank. We observed that FRASS scores correlate well with the ARTS and LaJolla similarity scores. Moreover, the-web server can also reproduce satisfactorily the DARTS classification of RNA 3D structures and the classification of the SCOR functions that was obtained by the SARA method.</p> <p>Conclusions</p> <p>The FRASS web-server can be easily used to detect relationships among RNA molecules and to scan efficiently the rapidly enlarging structural databases.</p

Perceptual expertise improves category detection in natural scenes

There is much debate about how detection, categorization, and within-category identification relate to one another during object recognition. Whether these tasks rely on partially shared perceptual mechanisms may be determined by testing whether training on one of these tasks facilitates performance on another. In the present study we asked whether expertise in discriminating objects improves the detection of these objects in naturalistic scenes. Self-proclaimed car experts (N = 34) performed a car discrimination task to establish their level of expertise, followed by a visual search task where they were asked to detect cars and people in hundreds of photographs of natural scenes. Results revealed that expertise in discriminating cars was strongly correlated with car detection accuracy. This effect was specific to objects of expertise, as there was no influence of car expertise on person detection. These results indicate a close link between object discrimination and object detection performance, which we interpret as reflecting partially shared perceptual mechanisms and neural representations underlying these tasks: the increased sensitivity of the visual system for objects of expertise – as a result of extensive discrimination training – may benefit both the discrimination and the detection of these objects. Alternative interpretations are also discussed

Herbivore benefits from vectoring plant virus through reduction of period of vulnerability to predation

Herbivores can profit from vectoring plant pathogens because the induced defence of plants against pathogens sometimes interferes with the induced defence of plants against herbivores. Plants can also defend themselves indirectly by the action of the natural enemies of the herbivores. It is unknown whether the defence against pathogens induced in the plant also interferes with the indirect defence against herbivores mediated via the third trophic level. We previously showed that infection of plants with Tomato spotted wilt virus (TSWV) increased the developmental rate of and juvenile survival of its vector, the thrips Frankliniella occidentalis. Here, we present the results of a study on the effects of TSWV infections of plants on the effectiveness of three species of natural enemies of F. occidentalis: the predatory mites Neoseiulus cucumeris and Iphiseius degenerans, and the predatory bug Orius laevigatus. The growth rate of thrips larvae was positively affected by the presence of virus in the host plant. Because large larvae are invulnerable to predation by the two species of predatory mites, this resulted in a shorter period of vulnerability to predation for thrips that developed on plants with virus than thrips developing on uninfected plants (4.4 vs. 7.9 days, respectively). Because large thrips larvae are not invulnerable to predation by the predatory bug Orius laevigatus, infection of the plant did not affect the predation risk of thrips larvae from this predator. This is the first demonstration of a negative effect of a plant pathogen on the predation risk of its vector

Task-Specific Codes for Face Recognition: How they Shape the Neural Representation of Features for Detection and Individuation

The variety of ways in which faces are categorized makes face recognition challenging for both synthetic and biological vision systems. Here we focus on two face processing tasks, detection and individuation, and explore whether differences in task demands lead to differences both in the features most effective for automatic recognition and in the featural codes recruited by neural processing.Our study appeals to a computational framework characterizing the features representing object categories as sets of overlapping image fragments. Within this framework, we assess the extent to which task-relevant information differs across image fragments. Based on objective differences we find among task-specific representations, we test the sensitivity of the human visual system to these different face descriptions independently of one another. Both behavior and functional magnetic resonance imaging reveal effects elicited by objective task-specific levels of information. Behaviorally, recognition performance with image fragments improves with increasing task-specific information carried by different face fragments. Neurally, this sensitivity to the two tasks manifests as differential localization of neural responses across the ventral visual pathway. Fragments diagnostic for detection evoke larger neural responses than non-diagnostic ones in the right posterior fusiform gyrus and bilaterally in the inferior occipital gyrus. In contrast, fragments diagnostic for individuation evoke larger responses than non-diagnostic ones in the anterior inferior temporal gyrus. Finally, for individuation only, pattern analysis reveals sensitivity to task-specific information within the right "fusiform face area".OUR RESULTS DEMONSTRATE: 1) information diagnostic for face detection and individuation is roughly separable; 2) the human visual system is independently sensitive to both types of information; 3) neural responses differ according to the type of task-relevant information considered. More generally, these findings provide evidence for the computational utility and the neural validity of fragment-based visual representation and recognition

Visualising the invisible: a network approach to reveal the informal social side of student learning

World-wide, universities in health sciences have transformed their curriculum to include collaborative learning and facilitate the students’ learning process. Interaction has been acknowledged to be the synergistic element in this learning context. However, students spend the majority of their time outside their classroom and interaction does not stop outside the classroom. Therefore we studied how informal social interaction influences student learning. Moreover, to explore what really matters in the students learning process, a model was tested how the generally known important constructs—prior performance, motivation and social integration—relate to informal social interaction and student learning. 301 undergraduate medical students participated in this cross-sectional quantitative study. Informal social interaction was assessed using self-reported surveys following the network approach. Students’ individual motivation, social integration and prior performance were assessed by the Academic Motivation Scale, the College Adaption Questionnaire and students’ GPA respectively. A factual knowledge test represented student’ learning. All social networks were positively associated with student learning significantly: friendships (β = 0.11), providing information to other students (β = 0.16), receiving information from other students (β = 0.25). Structural equation modelling revealed a model in which social networks increased student learning (r = 0.43), followed by prior performance (r = 0.31). In contrast to prior literature, students’ academic motivation and social integration were not associated with students’ learning. Students’ informal social interaction is strongly associated with students’ learning. These findings underline the need to change our focus from the formal context (classroom) to the informal context to optimize student learning and deliver modern medics