Automatic Recognition of Leaves by Shape Detection Pre-Processing with Ica

In this work we present a simulation of a recognition process with perimeter characterization of a simple plant leaves as a unique discriminating parameter. Data coding allowing for independence of leaves size and orientation may penalize performance recognition for some varieties. Border description sequences are then used to characterize the leaves. Independent Component Analysis (ICA) is then applied in order to study which is the best number of components to be considered for the classification task, implemented by means of an Artificial Neural Network (ANN). Obtained results with ICA as a pre-processing tool are satisfactory, and compared with some references our system improves the recognition success up to 80.8% depending on the number of considered independent components.

Dyslexia in a French-Spanish bilingual girl: behavioural and neural modulations following a visual attention span intervention.

We report the case study of a French-Spanish bilingual dyslexic girl, MP, who exhibited a severe visual attention (VA) span deficit but preserved phonological skills. Behavioural investigation showed a severe reduction of reading speed for both single items (words and pseudo-words) and texts in the two languages. However, performance was more affected in French than in Spanish. MP was administered an intensive VA span intervention programme. Pre-post intervention comparison revealed a positive effect of intervention on her VA span abilities. The intervention further transferred to reading. It primarily resulted in faster identification of the regular and irregular words in French. The effect of intervention was rather modest in Spanish that only showed a tendency for faster word reading. Text reading improved in the two languages with a stronger effect in French but pseudo-word reading did not improve in either French or Spanish. The overall results suggest that VA span intervention may primarily enhance the fast global reading procedure, with stronger effects in French than in Spanish. MP underwent two fMRI sessions to explore her brain activations before and after VA span training. Prior to the intervention, fMRI assessment showed that the striate and extrastriate visual cortices alone were activated but none of the regions typically involved in VA span. Post-training fMRI revealed increased activation of the superior and inferior parietal cortices. Comparison of pre- and post-training activations revealed significant activation increase of the superior parietal lobes (BA 7) bilaterally. Thus, we show that a specific VA span intervention not only modulates reading performance but further results in increased brain activity within the superior parietal lobes known to housing VA span abilities. Furthermore, positive effects of VA span intervention on reading suggest that the ability to process multiple visual elements simultaneously is one cause of successful reading acquisition.

Organization and plasticity of auditory spatial representations

Spatial hearing refers to a set of abilities enabling us to determine the location of sound sources, redirect our attention toward relevant acoustic events, and recognize separate sound sources in noisy environments. Determining the location of sound sources plays a key role in the way in which humans perceive and interact with their environment. Deficits in sound localization abilities are observed after lesions to the neural tissues supporting these functions and can result in serious handicaps in everyday life. These deficits can, however, be remediated (at least to a certain degree) by the surprising capacity of reorganization that the human brain possesses following damage and/or learning, namely, the brain plasticity. In this thesis, our aim was to investigate the functional organization of auditory spatial functions and the learning-induced plasticity of these functions. Overall, we describe the results of three studies. The first study entitled "The role of the right parietal cortex in sound localization: A chronometric single pulse transcranial magnetic stimulation study" (At et al., 2011), study A, investigated the role of the right parietal cortex in spatial functions and its chronometry (i.e. the critical time window of its contribution to sound localizations). We concentrated on the behavioral changes produced by the temporarily inactivation of the parietal cortex with transcranial magnetic stimulation (TMS). We found that the integrity of the right parietal cortex is crucial for localizing sounds in the space and determined a critical time window of its involvement, suggesting a right parietal dominance for auditory spatial discrimination in both hemispaces. In "Distributed coding of the auditory space in man: evidence from training-induced plasticity" (At et al., 2013a), study B, we investigated the neurophysiological correlates and changes of the different sub-parties of the right auditory hemispace induced by a multi-day auditory spatial training in healthy subjects with electroencephalography (EEG). We report a distributed coding for sound locations over numerous auditory regions, particular auditory areas code specifically for precise parts of the auditory space, and this specificity for a distinct region is enhanced with training. In the third study "Training-induced changes in auditory spatial mismatch negativity" (At et al., 2013b), study C, we investigated the pre-attentive neurophysiological changes induced with a training over 4 days in healthy subjects with a passive mismatch negativity (MMN) paradigm. We showed that training changed the mechanisms for the relative representation of sound positions and not the specific lateralization themselves and that it changed the coding in right parahippocampal regions. - L'audition spatiale désigne notre capacité à localiser des sources sonores dans l'espace, de diriger notre attention vers les événements acoustiques pertinents et de reconnaître des sources sonores appartenant à des objets distincts dans un environnement bruyant. La localisation des sources sonores joue un rôle important dans la façon dont les humains perçoivent et interagissent avec leur environnement. Des déficits dans la localisation de sons sont souvent observés quand les réseaux neuronaux impliqués dans cette fonction sont endommagés. Ces déficits peuvent handicaper sévèrement les patients dans leur vie de tous les jours. Cependant, ces déficits peuvent (au moins à un certain degré) être réhabilités grâce à la plasticité cérébrale, la capacité du cerveau humain à se réorganiser après des lésions ou un apprentissage. L'objectif de cette thèse était d'étudier l'organisation fonctionnelle de l'audition spatiale et la plasticité induite par l'apprentissage de ces fonctions. Dans la première étude intitulé « The role of the right parietal cortex in sound localization : A chronometric single pulse study » (At et al., 2011), étude A, nous avons examiné le rôle du cortex pariétal droit dans l'audition spatiale et sa chronométrie, c'est-à- dire le moment critique de son intervention dans la localisation de sons. Nous nous sommes concentrés sur les changements comportementaux induits par l'inactivation temporaire du cortex pariétal droit par le biais de la Stimulation Transcrânienne Magnétique (TMS). Nous avons démontré que l'intégrité du cortex pariétal droit est cruciale pour localiser des sons dans l'espace. Nous avons aussi défini le moment critique de l'intervention de cette structure. Dans « Distributed coding of the auditory space : evidence from training-induced plasticity » (At et al., 2013a), étude B, nous avons examiné la plasticité cérébrale induite par un entraînement des capacités de discrimination auditive spatiale de plusieurs jours. Nous avons montré que le codage des positions spatiales est distribué dans de nombreuses régions auditives, que des aires auditives spécifiques codent pour des parties données de l'espace et que cette spécificité pour des régions distinctes est augmentée par l'entraînement. Dans « Training-induced changes in auditory spatial mismatch negativity » (At et al., 2013b), étude C, nous avons examiné les changements neurophysiologiques pré- attentionnels induits par un entraînement de quatre jours. Nous avons montré que l'entraînement modifie la représentation des positions spatiales entraînées et non-entrainées, et que le codage de ces positions est modifié dans des régions parahippocampales.

The behavioral relevance of multisensory neural response interactions.

Sensory information can interact to impact perception and behavior. Foods are appreciated according to their appearance, smell, taste and texture. Athletes and dancers combine visual, auditory, and somatosensory information to coordinate their movements. Under laboratory settings, detection and discrimination are likewise facilitated by multisensory signals. Research over the past several decades has shown that the requisite anatomy exists to support interactions between sensory systems in regions canonically designated as exclusively unisensory in their function and, more recently, that neural response interactions occur within these same regions, including even primary cortices and thalamic nuclei, at early post-stimulus latencies. Here, we review evidence concerning direct links between early, low-level neural response interactions and behavioral measures of multisensory integration.

Exploring neural cell dynamics with digital holographic microscopy.

In this review, we summarize how the new concept of digital optics applied to the field of holographic microscopy has allowed the development of a reliable and flexible digital holographic quantitative phase microscopy (DH-QPM) technique at the nanoscale particularly suitable for cell imaging. Particular emphasis is placed on the original biological information provided by the quantitative phase signal. We present the most relevant DH-QPM applications in the field of cell biology, including automated cell counts, recognition, classification, three-dimensional tracking, discrimination between physiological and pathophysiological states, and the study of cell membrane fluctuations at the nanoscale. In the last part, original results show how DH-QPM can address two important issues in the field of neurobiology, namely, multiple-site optical recording of neuronal activity and noninvasive visualization of dendritic spine dynamics resulting from a full digital holographic microscopy tomographic approach.

Neural networks complemented with genetic algorithms and fuzzy systems for predicting nitrogenous effluent variables in wastewater treatment plants

This work focuses on the prediction of the two main nitrogenous variables that describe the water quality at the effluent of a Wastewater Treatment Plant. We have developed two kind of Neural Networks architectures based on considering only one output or, in the other hand, the usual five effluent variables that define the water quality: suspended solids, biochemical organic matter, chemical organic matter, total nitrogen and total Kjedhal nitrogen. Two learning techniques based on a classical adaptative gradient and a Kalman filter have been implemented. In order to try to improve generalization and performance we have selected variables by means genetic algorithms and fuzzy systems. The training, testing and validation sets show that the final networks are able to learn enough well the simulated available data specially for the total nitrogen

Survey of prenatal screening policies in Europe for structural malformations and chromosome anomalies, and their impact on detection and termination rates for neural tube defects and Down's syndrome.

OBJECTIVE: To 'map' the current (2004) state of prenatal screening in Europe. DESIGN: (i) Survey of country policies and (ii) analysis of data from EUROCAT (European Surveillance of Congenital Anomalies) population-based congenital anomaly registers. SETTING: Europe. POPULATION: Survey of prenatal screening policies in 18 countries and 1.13 million births in 12 countries in 2002-04. METHODS: (i) Questionnaire on national screening policies and termination of pregnancy for fetal anomaly (TOPFA) laws in 2004. (ii) Analysis of data on prenatal detection and termination for Down's syndrome and neural tube defects (NTDs) using the EUROCAT database. MAIN OUTCOME MEASURES: Existence of national prenatal screening policies, legal gestation limit for TOPFA, prenatal detection and termination rates for Down's syndrome and NTD. RESULTS: Ten of the 18 countries had a national country-wide policy for Down's syndrome screening and 14/18 for structural anomaly scanning. Sixty-eight percent of Down's syndrome cases (range 0-95%) were detected prenatally, of which 88% resulted in termination of pregnancy. Eighty-eight percent (range 25-94%) of cases of NTD were prenatally detected, of which 88% resulted in termination. Countries with a first-trimester screening policy had the highest proportion of prenatally diagnosed Down's syndrome cases. Countries with no official national Down's syndrome screening or structural anomaly scan policy had the lowest proportion of prenatally diagnosed Down's syndrome and NTD cases. Six of the 18 countries had a legal gestational age limit for TOPFA, and in two countries, termination of pregnancy was illegal at any gestation. CONCLUSIONS: There are large differences in screening policies between countries in Europe. These, as well as organisational and cultural factors, are associated with wide country variation in prenatal detection rates for Down's syndrome and NTD.

Neural substrates of social emotion regulation: a FMRI study on imitation and expressive suppression to dynamic facial signals.

Emotion regulation is crucial for successfully engaging in social interactions. Yet, little is known about the neural mechanisms controlling behavioral responses to emotional expressions perceived in the face of other people, which constitute a key element of interpersonal communication. Here, we investigated brain systems involved in social emotion perception and regulation, using functional magnetic resonance imaging (fMRI) in 20 healthy participants. The latter saw dynamic facial expressions of either happiness or sadness, and were asked to either imitate the expression or to suppress any expression on their own face (in addition to a gender judgment control task). fMRI results revealed higher activity in regions associated with emotion (e.g., the insula), motor function (e.g., motor cortex), and theory of mind (e.g., [pre]cuneus) during imitation. Activity in dorsal cingulate cortex was also increased during imitation, possibly reflecting greater action monitoring or conflict with own feeling states. In addition, premotor regions were more strongly activated during both imitation and suppression, suggesting a recruitment of motor control for both the production and inhibition of emotion expressions. Expressive suppression (eSUP) produced increases in dorsolateral and lateral prefrontal cortex typically related to cognitive control. These results suggest that voluntary imitation and eSUP modulate brain responses to emotional signals perceived from faces, by up- and down-regulating activity in distributed subcortical and cortical networks that are particularly involved in emotion, action monitoring, and cognitive control.

Oscillations, phase-of-firing coding, and spike timing-dependent plasticity: an efficient learning scheme

Recent experiments have established that information can be encoded in the spike times of neurons relative to the phase of a background oscillation in the local field potential—a phenomenon referred to as “phase-of-firing coding” (PoFC). These firing phase preferences could result from combining an oscillation in the input current with a stimulus-dependent static component that would produce the variations in preferred phase, but it remains unclear whether these phases are an epiphenomenon or really affect neuronal interactions—only then could they have a functional role. Here we show that PoFC has a major impact on downstream learning and decoding with the now well established spike timing-dependent plasticity (STDP). To be precise, we demonstrate with simulations how a single neuron equipped with STDP robustly detects a pattern of input currents automatically encoded in the phases of a subset of its afferents, and repeating at random intervals. Remarkably, learning is possible even when only a small fraction of the afferents (~10%) exhibits PoFC. The ability of STDP to detect repeating patterns had been noted before in continuous activity, but it turns out that oscillations greatly facilitate learning. A benchmark with more conventional rate-based codes demonstrates the superiority of oscillations and PoFC for both STDP-based learning and the speed of decoding: the oscillation partially formats the input spike times, so that they mainly depend on the current input currents, and can be efficiently learned by STDP and then recognized in just one oscillation cycle. This suggests a major functional role for oscillatory brain activity that has been widely reported experimentally.

The long non-coding RNA NEAT1 is increased in IUGR placentas, leading to potential new hypotheses of IUGR origin/development.

INTRODUCTION: Intrauterine Growth Restriction (IUGR) is a multifactorial disease defined by an inability of the fetus to reach its growth potential. IUGR not only increases the risk of neonatal mortality/morbidity, but also the risk of metabolic syndrome during adulthood. Certain placental proteins have been shown to be implicated in IUGR development, such as proteins from the GH/IGF axis and angiogenesis/apoptosis processes. METHODS: Twelve patients with term IUGR pregnancy (birth weight < 10th percentile) and 12 CTRLs were included. mRNA was extracted from the fetal part of the placenta and submitted to a subtraction method (Clontech PCR-Select cDNA Subtraction). RESULTS: One candidate gene identified was the long non-coding RNA NEAT1 (nuclear paraspeckle assembly transcript 1). NEAT1 is the core component of a subnuclear structure called paraspeckle. This structure is responsible for the retention of hyperedited mRNAs in the nucleus. Overall, NEAT1 mRNA expression was 4.14 (±1.16)-fold increased in IUGR vs. CTRL placentas (P = 0.009). NEAT1 was exclusively localized in the nuclei of the villous trophoblasts and was expressed in more nuclei and with greater intensity in IUGR placentas than in CTRLs. PSPC1, one of the three main proteins of the paraspeckle, co-localized with NEAT1 in the villous trophoblasts. The expression of NEAT1_2 mRNA, the long isoform of NEAT1, was only modestly increased in IUGR vs. CTRL placentas. DISCUSSION/CONCLUSION: The increase in NEAT1 and its co-localization with PSPC1 suggests an increase in paraspeckles in IUGR villous trophoblasts. This could lead to an increased retention of important mRNAs in villous trophoblasts nuclei. Given that the villous trophoblasts are crucial for the barrier function of the placenta, this could in part explain placental dysfunction in idiopathic IUGR fetuses.

Block structured dynamics and neuronal coding

When certain control parameters of nervous cell models are varied, complex bifurcation structures develop in which the dynamical behaviors available appear classified in blocks, according to criteria of dynamical likelihood. This block structured dynamics may be a clue to understand how activated neurons encode information by firing spike trains of their action potentials.

Spatial prediction of monthly wind speeds in complex terrain with adaptive general regression neural networks

This paper presents the general regression neural networks (GRNN) as a nonlinear regression method for the interpolation of monthly wind speeds in complex Alpine orography. GRNN is trained using data coming from Swiss meteorological networks to learn the statistical relationship between topographic features and wind speed. The terrain convexity, slope and exposure are considered by extracting features from the digital elevation model at different spatial scales using specialised convolution filters. A database of gridded monthly wind speeds is then constructed by applying GRNN in prediction mode during the period 1968-2008. This study demonstrates that using topographic features as inputs in GRNN significantly reduces cross-validation errors with respect to low-dimensional models integrating only geographical coordinates and terrain height for the interpolation of wind speed. The spatial predictability of wind speed is found to be lower in summer than in winter due to more complex and weaker wind-topography relationships. The relevance of these relationships is studied using an adaptive version of the GRNN algorithm which allows to select the useful terrain features by eliminating the noisy ones. This research provides a framework for extending the low-dimensional interpolation models to high-dimensional spaces by integrating additional features accounting for the topographic conditions at multiple spatial scales. Copyright (c) 2012 Royal Meteorological Society.

Contribution of neural networks to Alzheimer disease's progression.

The neuropathology of Alzheimer disease is characterized by senile plaques, neurofibrillary tangles and cell death. These hallmarks develop according to the differential vulnerability of brain networks, senile plaques accumulating preferentially in the associative cortical areas and neurofibrillary tangles in the entorhinal cortex and the hippocampus. We suggest that the main aetiological hypotheses such as the beta-amyloid cascade hypothesis or its variant, the synaptic beta-amyloid hypothesis, will have to consider neural networks not just as targets of degenerative processes but also as contributors of the disease's progression and of its phenotype. Three domains of research are highlighted in this review. First, the cerebral reserve and the redundancy of the network's elements are related to brain vulnerability. Indeed, an enriched environment appears to increase the cerebral reserve as well as the threshold of disease's onset. Second, disease's progression and memory performance cannot be explained by synaptic or neuronal loss only, but also by the presence of compensatory mechanisms, such as synaptic scaling, at the microcircuit level. Third, some phenotypes of Alzheimer disease, such as hallucinations, appear to be related to progressive dysfunction of neural networks as a result, for instance, of a decreased signal to noise ratio, involving a diminished activity of the cholinergic system. Overall, converging results from studies of biological as well as artificial neural networks lead to the conclusion that changes in neural networks contribute strongly to Alzheimer disease's progression.