The role of the right parietal cortex in sound localization: a chronometric single pulse transcranial magnetic stimulation study.

Auditory spatial functions, including the ability to discriminate between the positions of nearby sound sources, are subserved by a large temporo-parieto-frontal network. With the aim of determining whether and when the parietal contribution is critical for auditory spatial discrimination, we applied single pulse transcranial magnetic stimulation on the right parietal cortex 20, 80, 90 and 150 ms post-stimulus onset while participants completed a two-alternative forced choice auditory spatial discrimination task in the left or right hemispace. Our results reveal that transient TMS disruption of right parietal activity impairs spatial discrimination when applied at 20 ms post-stimulus onset for sounds presented in the left (controlateral) hemispace and at 80 ms for sounds presented in the right hemispace. We interpret our finding in terms of a critical role for controlateral temporo-parietal cortices over initial stages of the building-up of auditory spatial representation and for a right hemispheric specialization in integrating the whole auditory space over subsequent, higher-order processing stages.

Urban image classification with semisupervised multiscale cluster kernels

This paper presents a semisupervised support vector machine (SVM) that integrates the information of both labeled and unlabeled pixels efficiently. Method's performance is illustrated in the relevant problem of very high resolution image classification of urban areas. The SVM is trained with the linear combination of two kernels: a base kernel working only with labeled examples is deformed by a likelihood kernel encoding similarities between labeled and unlabeled examples. Results obtained on very high resolution (VHR) multispectral and hyperspectral images show the relevance of the method in the context of urban image classification. Also, its simplicity and the few parameters involved make the method versatile and workable by unexperienced users.

Generating controlled image sets in cognitive neuroscience research.

The investigation of perceptual and cognitive functions with non-invasive brain imaging methods critically depends on the careful selection of stimuli for use in experiments. For example, it must be verified that any observed effects follow from the parameter of interest (e.g. semantic category) rather than other low-level physical features (e.g. luminance, or spectral properties). Otherwise, interpretation of results is confounded. Often, researchers circumvent this issue by including additional control conditions or tasks, both of which are flawed and also prolong experiments. Here, we present some new approaches for controlling classes of stimuli intended for use in cognitive neuroscience, however these methods can be readily extrapolated to other applications and stimulus modalities. Our approach is comprised of two levels. The first level aims at equalizing individual stimuli in terms of their mean luminance. Each data point in the stimulus is adjusted to a standardized value based on a standard value across the stimulus battery. The second level analyzes two populations of stimuli along their spectral properties (i.e. spatial frequency) using a dissimilarity metric that equals the root mean square of the distance between two populations of objects as a function of spatial frequency along x- and y-dimensions of the image. Randomized permutations are used to obtain a minimal value between the populations to minimize, in a completely data-driven manner, the spectral differences between image sets. While another paper in this issue applies these methods in the case of acoustic stimuli (Aeschlimann et al., Brain Topogr 2008), we illustrate this approach here in detail for complex visual stimuli.

A Survey of Active Learning Algorithms for Supervised Remote Sensing Image Classification

Defining an efficient training set is one of the most delicate phases for the success of remote sensing image classification routines. The complexity of the problem, the limited temporal and financial resources, as well as the high intraclass variance can make an algorithm fail if it is trained with a suboptimal dataset. Active learning aims at building efficient training sets by iteratively improving the model performance through sampling. A user-defined heuristic ranks the unlabeled pixels according to a function of the uncertainty of their class membership and then the user is asked to provide labels for the most uncertain pixels. This paper reviews and tests the main families of active learning algorithms: committee, large margin, and posterior probability-based. For each of them, the most recent advances in the remote sensing community are discussed and some heuristics are detailed and tested. Several challenging remote sensing scenarios are considered, including very high spatial resolution and hyperspectral image classification. Finally, guidelines for choosing the good architecture are provided for new and/or unexperienced user.

MSight: an image analysis software for liquid chromatography-mass spectrometry.

Images obtained from high-throughput mass spectrometry (MS) contain information that remains hidden when looking at a single spectrum at a time. Image processing of liquid chromatography-MS datasets can be extremely useful for quality control, experimental monitoring and knowledge extraction. The importance of imaging in differential analysis of proteomic experiments has already been established through two-dimensional gels and can now be foreseen with MS images. We present MSight, a new software designed to construct and manipulate MS images, as well as to facilitate their analysis and comparison.

The spatio-temporal brain dynamics of processing and integrating sound localization cues in humans.

Interaural intensity and time differences (IID and ITD) are two binaural auditory cues for localizing sounds in space. This study investigated the spatio-temporal brain mechanisms for processing and integrating IID and ITD cues in humans. Auditory-evoked potentials were recorded, while subjects passively listened to noise bursts lateralized with IID, ITD or both cues simultaneously, as well as a more frequent centrally presented noise. In a separate psychophysical experiment, subjects actively discriminated lateralized from centrally presented stimuli. IID and ITD cues elicited different electric field topographies starting at approximately 75 ms post-stimulus onset, indicative of the engagement of distinct cortical networks. By contrast, no performance differences were observed between IID and ITD cues during the psychophysical experiment. Subjects did, however, respond significantly faster and more accurately when both cues were presented simultaneously. This performance facilitation exceeded predictions from probability summation, suggestive of interactions in neural processing of IID and ITD cues. Supra-additive neural response interactions as well as topographic modulations were indeed observed approximately 200 ms post-stimulus for the comparison of responses to the simultaneous presentation of both cues with the mean of those to separate IID and ITD cues. Source estimations revealed differential processing of IID and ITD cues initially within superior temporal cortices and also at later stages within temporo-parietal and inferior frontal cortices. Differences were principally in terms of hemispheric lateralization. The collective psychophysical and electrophysiological results support the hypothesis that IID and ITD cues are processed by distinct, but interacting, cortical networks that can in turn facilitate auditory localization.

L'image de la Suisse à l'étranger

L'image qu'un pays a dans le monde est importante à plusieurs titres. Elle peut soutenir la commercialisation de biens et de services exportés, elle revêt un caractère tout particulier dans le cadre des promotions touristique et économique et elle peut aussi être de nature à contribuer aux relations qu'un pays entretient avec d'autres pays aux niveaux politique, économique ou culturel. L'image de la Suisse a fait l'objet d'études dans de nombreux pays, dont les Etats-Unis, l'Allemagne et la Chine, auprès d'échantillons représentatifs de la population ainsi qu'auprès de groupes de leaders d'opinion et cet ouvrage présente de manière synthétique les principaux résultats de ces études. Après une description de l'image globale de la Suisse auprès des personnes interrogées et une analyse des associations faites à l'évocation de la Suisse, une partie importante est consacrée aux dimensions qui caractérisent l'image du pays en différenciant notamment entre les dimensions liées à la Suisse en tant qu'espace socioculturel et les dimensions liées aux aspects économiques. Pour terminer, un dernier chapitre analyse l'impact de faits ayant marqué l'actualité helvétique, comme le grounding de Swissair, sur l'image de la Suisse dans les pays étudiés.

Using a NPWE model observer to assess suitable image quality for a digital mammography quality assurance programme.

A method of objectively determining imaging performance for a mammography quality assurance programme for digital systems was developed. The method is based on the assessment of the visibility of a spherical microcalcification of 0.2 mm using a quasi-ideal observer model. It requires the assessment of the spatial resolution (modulation transfer function) and the noise power spectra of the systems. The contrast is measured using a 0.2-mm thick Al sheet and Polymethylmethacrylate (PMMA) blocks. The minimal image quality was defined as that giving a target contrast-to-noise ratio (CNR) of 5.4. Several evaluations of this objective method for evaluating image quality in mammography quality assurance programmes have been considered on computed radiography (CR) and digital radiography (DR) mammography systems. The measurement gives a threshold CNR necessary to reach the minimum standard image quality required with regards to the visibility of a 0.2-mm microcalcification. This method may replace the CDMAM image evaluation and simplify the threshold contrast visibility test used in mammography quality.