Cue Recognition and Integration - Eye Tracking Evidence of Processing Differences in Sentence Comprehension in Aphasia

PURPOSE: We aimed at further elucidating whether aphasic patients' difficulties in understanding non-canonical sentence structures, such as Passive or Object-Verb-Subject sentences, can be attributed to impaired morphosyntactic cue recognition, and to problems in integrating competing interpretations. METHODS: A sentence-picture matching task with canonical and non-canonical spoken sentences was performed using concurrent eye tracking. Accuracy, reaction time, and eye tracking data (fixations) of 50 healthy subjects and 12 aphasic patients were analysed. RESULTS: Patients showed increased error rates and reaction times, as well as delayed fixation preferences for target pictures in non-canonical sentences. Patients' fixation patterns differed from healthy controls and revealed deficits in recognizing and immediately integrating morphosyntactic cues. CONCLUSION: Our study corroborates the notion that difficulties in understanding syntactically complex sentences are attributable to a processing deficit encompassing delayed and therefore impaired recognition and integration of cues, as well as increased competition between interpretations.

DAEDALUS at ImageCLEF 2011 Plant Identification Task: Using SIFT Keypoints for Object Detection

This paper describes the participation of DAEDALUS at ImageCLEF 2011 Plant Identification task. The task is evaluated as a supervised classification problem over 71 tree species from the French Mediterranean area used as class labels, based on visual content from scan, scan-like and natural photo images. Our approach to this task is to build a classifier based on the detection of keypoints from the images extracted using Lowe’s Scale Invariant Feature Transform (SIFT) algorithm. Although our overall classification score is very low as compared to other participant groups, the main conclusion that can be drawn is that SIFT keypoints seem to work significantly better for photos than for the other image types, so our approach may be a feasible strategy for the classification of this kind of visual content.

Geometry of circular vectors and pattern recognition of shape of a boundary

This paper deals with pattern recognition of the shape of the boundary of closed figures on the basis of a circular sequence of measurements taken on the boundary at equal intervals of a suitably chosen argument with an arbitrary starting point. A distance measure between two boundaries is defined in such a way that it has zero value when the associated sequences of measurements coincide by shifting the starting point of one of the sequences. Such a distance measure, which is invariant to the starting point of the sequence of measurements, is used in identification or discrimination by the shape of the boundary of a closed figure. The mean shape of a given set of closed figures is defined, and tests of significance of differences in mean shape between populations are proposed.

Activation of target-tissue immune-recognition molecules by double-stranded polynucleotides

Abnormal expression of major histocompatibility complex (MHC) class I and class II in various tissues is associated with autoimmune disease. Autoimmune responses can be triggered by viral infections or tissue injuries. We show that the ability of a virus or a tissue injury to increase MHC gene expression is duplicated by any fragment of double-stranded (ds) DNA or dsRNA introduced into the cytoplasm of nonimmune cells. Activation is sequence-independent, is induced by ds polynucleotides as small as 25 bp in length, and is not duplicated by single-stranded polynucleotides. In addition to causing abnormal MHC expression, the ds nucleic acids increase the expression of genes necessary for antigen processing and presentation: proteasome proteins (e.g., LMP2), transporters of antigen peptides; invariant chain, HLA-DM, and the costimulatory molecule B7.1. The mechanism is different from and additive to that of γ-interferon (γIFN), i.e., ds polynucleotides increase class I much more than class II, whereas γIFN increases class II more than class I. The ds nucleic acids also induce or activate Stat1, Stat3, mitogen-activated protein kinase, NF-κB, the class II transactivator, RFX5, and the IFN regulatory factor 1 differently from γIFN. CpG residues are not responsible for this effect, and the action of the ds polynucleotides could be shown in a variety of cell types in addition to thyrocytes. We suggest that this phenomenon is a plausible mechanism that might explain how viral infection of tissues or tissue injury triggers autoimmune disease; it is potentially relevant to host immune responses induced during gene therapy.

Direct observation of disordered regions in the major histocompatibility complex class II-associated invariant chain.

Invariant chain (Ii) is a trimeric membrane protein which binds and stabilizes major histocompatibility complex class II heterodimers in the endoplasmic reticulum and lysosomal compartments of antigen-presenting cells. In concert with an intracellular class II-like molecule, HLA-DM, Ii seems to facilitate loading of conventional class II molecules with peptides before transport of the class II-peptide complex to the cell surface for recognition by T cells. The interaction of Ii with class II molecules is thought to be mediated in large part through a region of 24 amino acids (the class II-associated Ii peptide, CLIP) which binds as a cleaved moiety in the antigenic peptide-binding groove of class II molecules in HLA-DM-deficient cell lines. Here we use nuclear magnetic resonance techniques to demonstrate that a soluble recombinant Ii ectodomain contains significant disordered regions which probably include CLIP.

Older driver perception-reaction time for intersection sight distance and object detection. Final report. Volume II: appendixes.

Federal Highway Administration, Office of Safety and Traffic Operations Research and Development, McLean, Va.

First- and second-order stimulus length selectivity in New World monkey striate cortex

Motion is a powerful cue for figure-ground segregation, allowing the recognition of shapes even if the luminance and texture characteristics of the stimulus and background are matched. In order to investigate the neural processes underlying early stages of the cue-invariant processing of form, we compared the responses of neurons in the striate cortex (V1) of anaesthetized marmosets to two types of moving stimuli: bars defined by differences in luminance, and bars defined solely by the coherent motion of random patterns that matched the texture and temporal modulation of the background. A population of form-cue-invariant (FCI) neurons was identified, which demonstrated similar tuning to the length of contours defined by first- and second-order cues. FCI neurons were relatively common in the supragranular layers (where they corresponded to 28% of the recorded units), but were absent from layer 4. Most had complex receptive fields, which were significantly larger than those of other V1 neurons. The majority of FCI neurons demonstrated end-inhibition in response to long first- and second-order bars, and were strongly direction selective, Thus, even at the level of V1 there are cells whose variations in response level appear to be determined by the shape and motion of the entire second-order object, rather than by its parts (i.e. the individual textural components). These results are compatible with the existence of an output channel from V1 to the ventral stream of extrastriate areas, which already encodes the basic building blocks of the image in an invariant manner.

Non-rigid object tracking in complex scenes

A recently proposed colour based tracking algorithm has been established to track objects in real circumstances [Zivkovic, Z., Krose, B. 2004. An EM-like algorithm for color-histogram-based object tracking. In: Proc, IEEE Conf. on Computer Vision and Pattern Recognition, pp. 798-803]. To improve the performance of this technique in complex scenes, in this paper we propose a new algorithm for optimally adapting the ellipse outlining the objects of interest. This paper presents a Lagrangian based method to integrate a regularising component into the covariance matrix to be computed. Technically, we intend to reduce the residuals between the estimated probability distribution and the expected one. We argue that, by doing this, the shape of the ellipse can be properly adapted in the tracking stage. Experimental results show that the proposed method has favourable performance in shape adaption and object localisation.

Recognition times of different views of 56 depth-rotated objects: a note concerning Verfaillie and Boutsen (1995)

The present study examines the effect of the goodness of view on the minimal exposure time required to recognize depth-rotated objects. In a previous study, Verfaillie and Boutsen (1995) derived scales of goodness of view, using a new corpus of images of depth-rotated objects. In the present experiment, a subset of this corpus (five views of 56 objects) is used to determine the recognition exposure time for each view, by increasing exposure time across successive presentations until the object is recognized. The results indicate that, for two thirds of the objects, good views are recognized more frequently and have lower recognition exposure times than bad views.

Live 3D shape reconstruction, recognition and registration

We present a video-based system which interactively captures the geometry of a 3D object in the form of a point cloud, then recognizes and registers known objects in this point cloud in a matter of seconds (fig. 1). In order to achieve interactive speed, we exploit both efficient inference algorithms and parallel computation, often on a GPU. The system can be broken down into two distinct phases: geometry capture, and object inference. We now discuss these in further detail. © 2011 IEEE.

Inhibition of object identity in inhibition of return:implications for encoding and retrieving inhibitory processes

Inhibition of return (IOR) effects, in which participants detect a target in a cued box more slowly than one in an uncued box, suggest that behavior is aided by inhibition of recently attended irrelevant locations. To investigate the controversial question of whether inhibition can be applied to object identity in these tasks, in the present research we presented faces upright or inverted during cue and/or target sequences. IOR was greater when both cue and target faces were upright than when cue and/or target faces were inverted. Because the only difference between the conditions was the ease of facial recognition, this result indicates that inhibition was applied to object identity. Interestingly, inhibition of object identity affected IOR both whenencoding a cue face andretrieving information about a target face. Accordingly, we propose that episodic retrieval of inhibition associated with object identity may mediate behavior in cuing tasks.

Rotation invariant iris feature extraction using Gaussian Markov random fields with non-separable wavelet

Rotation invariance is important for an iris recognition system since changes of head orientation and binocular vergence may cause eye rotation. The conventional methods of iris recognition cannot achieve true rotation invariance. They only achieve approximate rotation invariance by rotating the feature vector before matching or unwrapping the iris ring at different initial angles. In these methods, the complexity of the method is increased, and when the rotation scale is beyond the certain scope, the error rates of these methods may substantially increase. In order to solve this problem, a new rotation invariant approach for iris feature extraction based on the non-separable wavelet is proposed in this paper. Firstly, a bank of non-separable orthogonal wavelet filters is used to capture characteristics of the iris. Secondly, a method of Markov random fields is used to capture rotation invariant iris feature. Finally, two-class kernel Fisher classifiers are adopted for classification. Experimental results on public iris databases show that the proposed approach has a low error rate and achieves true rotation invariance. © 2010.

Projective Methods of Image Recognition

We propose a method for image recognition on the base of projections. Radon transform gives an opportunity to map image into space of its projections. Projection properties allow constructing informative features on the base of moments that can be successfully used for invariant recognition. Offered approach gives about 91-97% of correct recognition.

An incremental multilinear system for human face learning and recognition

This dissertation establishes a novel system for human face learning and recognition based on incremental multilinear Principal Component Analysis (PCA). Most of the existing face recognition systems need training data during the learning process. The system as proposed in this dissertation utilizes an unsupervised or weakly supervised learning approach, in which the learning phase requires a minimal amount of training data. It also overcomes the inability of traditional systems to adapt to the testing phase as the decision process for the newly acquired images continues to rely on that same old training data set. Consequently when a new training set is to be used, the traditional approach will require that the entire eigensystem will have to be generated again. However, as a means to speed up this computational process, the proposed method uses the eigensystem generated from the old training set together with the new images to generate more effectively the new eigensystem in a so-called incremental learning process. In the empirical evaluation phase, there are two key factors that are essential in evaluating the performance of the proposed method: (1) recognition accuracy and (2) computational complexity. In order to establish the most suitable algorithm for this research, a comparative analysis of the best performing methods has been carried out first. The results of the comparative analysis advocated for the initial utilization of the multilinear PCA in our research. As for the consideration of the issue of computational complexity for the subspace update procedure, a novel incremental algorithm, which combines the traditional sequential Karhunen-Loeve (SKL) algorithm with the newly developed incremental modified fast PCA algorithm, was established. In order to utilize the multilinear PCA in the incremental process, a new unfolding method was developed to affix the newly added data at the end of the previous data. The results of the incremental process based on these two methods were obtained to bear out these new theoretical improvements. Some object tracking results using video images are also provided as another challenging task to prove the soundness of this incremental multilinear learning method.

Contributions Of the Human Medial Prefrontal Cortex To Associative Recognition Memory: Evidence From Functional Neuroimaging

Neuroimaging studies of episodic memory, or memory of events from our personal past, have predominantly focused their attention on medial temporal lobe (MTL). There is growing acknowledgement however, from the cognitive neuroscience of memory literature, that regions outside the MTL can support episodic memory processes. The medial prefrontal cortex is one such region garnering increasing interest from researchers. Using behavioral and functional magnetic resonance imaging measures, over two studies, this thesis provides evidence of a mnemonic role of the medial PFC. In the first study, participants were scanned while judging the extent to which they agreed or disagreed with the sociopolitical views of unfamiliar individuals. Behavioral tests of associative recognition revealed that participants remembered with high confidence viewpoints previously linked with judgments of strong agreement/disagreement. Neurally, the medial PFC mediated the interaction between high-confidence associative recognition memory and beliefs associated with strong agree/disagree judgments. In an effort to generalize this finding to well-established associative information, in the second study, we investigated associative recognition memory for real-world concepts. Object-scene pairs congruent or incongruent with a preexisting schema were presented to participants in a cued-recall paradigm. Behavioral tests of conceptual and perceptual recognition revealed memory enhancements arising from strong resonance between presented pairs and preexisting schemas. Neurally, the medial PFC tracked increases in visual recall of schema-congruent pairs whereas the MTL tracked increases in visual recall of schema-incongruent pairs. Additionally, ventral areas of the medial PFC tracked conceptual components of visual recall specifically for schema-congruent pairs. These findings are consistent with a recent theoretical proposal of medial PFC contributions to memory for schema-related content. Collectively, these studies provide evidence of a role for the medial PFC in associative recognition memory persisting for associative information deployed in our daily social interactions and for those associations formed over multiple learning episodes. Additionally, this set of findings advance our understanding of the cognitive contributions of the medial PFC beyond its canonical role in processes underlying social cognition.