Enhanced visuospatial memory following intracerebroventricular administration of nerve growth factor

The present work assessed the effects of intracerebroventricular injections of rh recombined human nerve growth factor (rh NGF) (5 micrograms/2.5 microl) at postnatal days 12 and 13 upon the development of spatial learning capacities. The treated rats were trained at the age of 22 days to escape onto an invisible platform at a fixed position in space in a Morris navigation task. For half of the subjects, the training position was also cued, a procedure aimed at facilitating escape and at reducing attention to the distant spatial cues. Later, at the age of 6 months, all the rats were trained in a radial-arm maze task. Treatment effects were found in both immature and adult rats. The injection of NGF improved the performance in the Morris navigation task in both training conditions. There was a significant reduction in the escape latency and an increased bias toward the training platform quadrant during probe trials. The most consistent effect was the precocious development of an adult-like spatial memory. In the radial-arm maze, the NGF-treated rats made significantly fewer reentries than vehicle rats and this effect was particularly marked in the treated female rats. Taken together, these experiments reveal that the development and the maintenance of an accurate spatial representation are tightly related to the development of brain structures facilitated by the action of NGF. Moreover, these experiments demonstrate that an acute pharmacological treatment that leads to a transient modification in the choline acetyltransferase activity can induce a behavioral change long after the treatment.

Mice with chronic GSH deficit display phenotypical anomalies that resemble key aspects of schizophrenia

ABSTRACTSchizophrenia is a major psychiatric disorder occurring with a prevalence of 1% in the worldwide population. It develops progressively with psychosis onset in late adolescence or earlyadulthood. The disorder can take many different facets and has a highly diffuse anddistributed neuropathology including deficits in major neurotransmitter systems,myelination, stress regulation, and metabolism. The delayed onset and the heterogeneouspathology suggest that schizophrenia is a developmental disease that arises from interplayof genetic and environmental factors during sensitive periods. Redox dysregulation due to animbalance between pro-oxidants and antioxidant defence mechanisms is among the riskfactors for schizophrenia. Glutathione (GSH) is the major cellular redox regulator andantioxidant. Levels of GSH are decreased in cerebrospinal fluid, prefrontal cortex and postmortemstriatum of schizophrenia patients. Moreover, polymorphisms of the key GSHsynthesizingenzyme, glutamate-cysteine ligase, modifier (GCLM) subunit, are associatedwith the disease, suggesting that GSH deficit is of genetic origin. Here we used miceknockout (KO) for the GCLM gene, which display chronic GSH deficit (~70 to 80% decrease)to investigate the direct link between redox dysregulation and schizophrenia. Accordingly,we evaluated whether GCLM KO compared to normal wildtype mice display behavioralchanges that relate to schizophrenia symptoms and whether their brains showmorphological, functional or metabolic alterations that resemble those in patients.Moreover, we exposed pubertal GCLM mice to repeated mild stress and measured theirhormonal and behavioral stress reactivity. Our data show that chronic GSH deficit isassociated with altered emotion- and stress-related behaviors, deficient prepulse inhibition,pronounced amphetamine-induced hyperlocomotion but normal spatial learning andworking memory. These changes represent important schizophrenia endophenotypes.Moreover, this particular pattern of change indicates impairment of the ventralhippocampus (VH) and related circuitry as opposed to the dorsal hippocampus (DH), which isimplicated in spatial information processing. This is consistent with a selective deficit ofparvalbumin positive interneurons and gamma oscillation in the VH but not DH. Increasedlevels of circulating stress hormones in KO mice following pubertal stress corroborate VHdysfunction as it is involved in negative feedback control of the stress response. VHstructural and functional deficits are frequently found in the schizophrenic brain. Metabolicevaluation of the developing GCLM KO anterior cortex using in vivo magnetic resonancespectroscopy revealed elevated glutamine (Gln), glutamate (Glu), Gln/Glu and N-acetylaspartate(NAA) during the pre-pubertal period. Similar changes are reported in earlyschizophrenia. Overall, we observe phenotypic anomalies in GSH deficient GCLM KO micethat correspond to major schizophrenia endophenotypes. This supports an important rolefor redox dysregulation in schizophrenia and validates the GCLM KO mouse as model for thedisease. Moreover, our results indicate that puberty may be a sensitive period for redoxsensitivechanges highliting the importance of early intervention. Gln, Gln/Glu, Glu and NAAmay qualify as early metabolic biomarkers to identify young at-risk individuals. Since chronictreatment with NAC normalized most metabolic changes in GCLM KO mice, NAC may be oneadjunct treatment of choice for early intervention in patients.RESUMELa schizophrénie est une maladie psychiatrique majeure avec une prévalence de 1% dans lapopulation. Son développement est progressif, les premières psychoses apparaissant àl'adolescence ou au début de l'âge adulte. La maladie a plusieurs présentations et uneneuropathologie étendue, qui inclut des déficits neurochimiques, métaboliques, de lamyélination et de la régulation du stress. L'émergence tardive et l'hétérogénéité de lapathologie suggèrent que la schizophrénie est une maladie développementale, favorisée pardes facteurs génétiques et environnementaux durant des périodes sensibles. La dérégulationrédox, due à un déséquilibre entre facteurs pro-oxidantes et défenses anti-oxidantes,constitue un facteur de risque. Le glutathion (GSH) est le principal régulateur rédox et antioxidantdes cellules, ses taux sont diminués dans le liquide céphalorachidien, le cortexpréfrontal et le striatum de patients. De plus, des variations du gène codant la sous-unitémodulatrice (GCLM) de la glutamate-cystéine ligase, enzyme de synthèse du GSH, sontassociés la maladie, suggérant que le déficit observé chez les patients est d'originegénétique. Nous avons donc utilisé des souris ayant une délétion du gène GCLM (KO), quiont un déficit chronique en GSH (70-80%), afin d'étudier le lien entre une dérégulation rédoxet la schizophrénie. Nous avons évalué si ces souris présentent des altérationscomportementales analogues aux symptômes de la maladie, et des modificationsstructurelles, fonctionnelles et métaboliques au niveau du cerveau, ressemblant à celles despatients. De plus, nous avons soumis les souris à des stresses modérés durant la puberté,puis mesuré les réponses hormonales et comportementales. Les animaux présentent undéficit pré-attentionnel du traitement des informations moto-sensorielles, un déficit pourcertains apprentissages, une réponse accrue à l'amphétamine, mais leurs mémoires spatialeet de travail sont préservées. Ces atteintes comportementales sont analogues à certainsendophénotypes de la schizophrénie. De plus, ces changements comportementaux sontlargement expliqués par une perturbation morphologique et fonctionnelle de l'hippocampeventral (HV). Ainsi, nous avons observé un déficit sélectif des interneurones immunoréactifsà la parvalbumine et une désynchronisation neuronale dans l'HV. L'hippocampe dorsal,impliqué dans l'orientation spatiale, demeure en revanche intact. L'augmentationd'hormones de stress dans le sang des souris KO suite à un stress prépubertal soutien aussil'hypothèse d'une dysfonction de l'HV, connu pour moduler ce type de réponse. Des déficitsstructurels et fonctionnels dans l'hippocampe antérieur (ventral) ont d'ailleurs été rapportéschez des patients schizophrènes. Par de résonance magnétique, nous avons également suivile profil métabolique du le cortex antérieur au cours du développement postnatal des sourisKO. Ces mesures ont révélé des taux élevés de glutamine (Gln), glutamate (Glu), du ratioGln/Glu, et de N-acétyl-aspartate (NAA) durant la période prépubertale. Des altérationssimilaires sont décrites chez les patients durant la phase précoce. Nous avons donc révélédes anomalies phénotypiques chez les souris GCLM KO qui reflètent certainsendophénotypes de la schizophrénie. Nos résultats appuient donc le rôle d'une dérégulationrédox dans l'émergence de la maladie et le potentiel des souris KO comme modèle. De plus,cette étude met en évidence la puberté comme période particulièrement sensible à unedérégulation rédox, renforçant l'importance d'une intervention thérapeutique précoce. Dansce cadre, Gln, Gln/Glu, Glu and NAA seraient des biomarqueurs clés pour identifier de jeunesindividus à risque. De part son efficacité dans notre modèle, NAC pourrait être unesubstance de choix dans le traitement précoce des patients.

Machine learning algorithms for spatial data. Case studies: Environmental pollution, natural hazards, renewable resources

This paper presents general problems and approaches for the spatial data analysis using machine learning algorithms. Machine learning is a very powerful approach to adaptive data analysis, modelling and visualisation. The key feature of the machine learning algorithms is that they learn from empirical data and can be used in cases when the modelled environmental phenomena are hidden, nonlinear, noisy and highly variable in space and in time. Most of the machines learning algorithms are universal and adaptive modelling tools developed to solve basic problems of learning from data: classification/pattern recognition, regression/mapping and probability density modelling. In the present report some of the widely used machine learning algorithms, namely artificial neural networks (ANN) of different architectures and Support Vector Machines (SVM), are adapted to the problems of the analysis and modelling of geo-spatial data. Machine learning algorithms have an important advantage over traditional models of spatial statistics when problems are considered in a high dimensional geo-feature spaces, when the dimension of space exceeds 5. Such features are usually generated, for example, from digital elevation models, remote sensing images, etc. An important extension of models concerns considering of real space constrains like geomorphology, networks, and other natural structures. Recent developments in semi-supervised learning can improve modelling of environmental phenomena taking into account on geo-manifolds. An important part of the study deals with the analysis of relevant variables and models' inputs. This problem is approached by using different feature selection/feature extraction nonlinear tools. To demonstrate the application of machine learning algorithms several interesting case studies are considered: digital soil mapping using SVM, automatic mapping of soil and water system pollution using ANN; natural hazards risk analysis (avalanches, landslides), assessments of renewable resources (wind fields) with SVM and ANN models, etc. The dimensionality of spaces considered varies from 2 to more than 30. Figures 1, 2, 3 demonstrate some results of the studies and their outputs. Finally, the results of environmental mapping are discussed and compared with traditional models of geostatistics.

Learning spatial filters for multispectral image segmentation

We present a novel filtering method for multispectral satellite image classification. The proposed method learns a set of spatial filters that maximize class separability of binary support vector machine (SVM) through a gradient descent approach. Regularization issues are discussed in detail and a Frobenius-norm regularization is proposed to efficiently exclude uninformative filters coefficients. Experiments carried out on multiclass one-against-all classification and target detection show the capabilities of the learned spatial filters.

Learning-induced plasticity in auditory spatial representations revealed by electrical neuroimaging.

Auditory spatial representations are likely encoded at a population level within human auditory cortices. We investigated learning-induced plasticity of spatial discrimination in healthy subjects using auditory-evoked potentials (AEPs) and electrical neuroimaging analyses. Stimuli were 100 ms white-noise bursts lateralized with varying interaural time differences. In three experiments, plasticity was induced with 40 min of discrimination training. During training, accuracy significantly improved from near-chance levels to approximately 75%. Before and after training, AEPs were recorded to stimuli presented passively with a more medial sound lateralization outnumbering a more lateral one (7:1). In experiment 1, the same lateralizations were used for training and AEP sessions. Significant AEP modulations to the different lateralizations were evident only after training, indicative of a learning-induced mismatch negativity (MMN). More precisely, this MMN at 195-250 ms after stimulus onset followed from differences in the AEP topography to each stimulus position, indicative of changes in the underlying brain network. In experiment 2, mirror-symmetric locations were used for training and AEP sessions; no training-related AEP modulations or MMN were observed. In experiment 3, the discrimination of trained plus equidistant untrained separations was tested psychophysically before and 0, 6, 24, and 48 h after training. Learning-induced plasticity lasted <6 h, did not generalize to untrained lateralizations, and was not the simple result of strengthening the representation of the trained lateralizations. Thus, learning-induced plasticity of auditory spatial discrimination relies on spatial comparisons, rather than a spatial anchor or a general comparator. Furthermore, cortical auditory representations of space are dynamic and subject to rapid reorganization.

Multitask learning of environmental spatial data

The present research deals with an application of artificial neural networks for multitask learning from spatial environmental data. The real case study (sediments contamination of Geneva Lake) consists of 8 pollutants. There are different relationships between these variables, from linear correlations to strong nonlinear dependencies. The main idea is to construct a subsets of pollutants which can be efficiently modeled together within the multitask framework. The proposed two-step approach is based on: 1) the criterion of nonlinear predictability of each variable ?k? by analyzing all possible models composed from the rest of the variables by using a General Regression Neural Network (GRNN) as a model; 2) a multitask learning of the best model using multilayer perceptron and spatial predictions. The results of the study are analyzed using both machine learning and geostatistical tools.

Spatial relational learning and memory abilities do not differ between men and women in a real-world, open-field environment

This study assesses gender differences in spatial and non-spatial relational learning and memory in adult humans behaving freely in a real-world, open-field environment. In Experiment 1, we tested the use of proximal landmarks as conditional cues allowing subjects to predict the location of rewards hidden in one of two sets of three distinct locations. Subjects were tested in two different conditions: (1) when local visual cues marked the potentially-rewarded locations, and (2) when no local visual cues marked the potentially-rewarded locations. We found that only 17 of 20 adults (8 males, 9 females) used the proximal landmarks to predict the locations of the rewards. Although females exhibited higher exploratory behavior at the beginning of testing, males and females discriminated the potentially-rewarded locations similarly when local visual cues were present. Interestingly, when the spatial and local information conflicted in predicting the reward locations, males considered both spatial and local information, whereas females ignored the spatial information. However, in the absence of local visual cues females discriminated the potentially-rewarded locations as well as males. In Experiment 2, subjects (9 males, 9 females) were tested with three asymmetrically-arranged rewarded locations, which were marked by local cues on alternate trials. Again, females discriminated the rewarded locations as well as males in the presence or absence of local cues. In sum, although particular aspects of task performance might differ between genders, we found no evidence that women have poorer allocentric spatial relational learning and memory abilities than men in a real-world, open-field environment.

Advanced geostatistical and machine-learning models for spatial data analysis of radioactively contaminated regions

Radioactive soil-contamination mapping and risk assessment is a vital issue for decision makers. Traditional approaches for mapping the spatial concentration of radionuclides employ various regression-based models, which usually provide a single-value prediction realization accompanied (in some cases) by estimation error. Such approaches do not provide the capability for rigorous uncertainty quantification or probabilistic mapping. Machine learning is a recent and fast-developing approach based on learning patterns and information from data. Artificial neural networks for prediction mapping have been especially powerful in combination with spatial statistics. A data-driven approach provides the opportunity to integrate additional relevant information about spatial phenomena into a prediction model for more accurate spatial estimates and associated uncertainty. Machine-learning algorithms can also be used for a wider spectrum of problems than before: classification, probability density estimation, and so forth. Stochastic simulations are used to model spatial variability and uncertainty. Unlike regression models, they provide multiple realizations of a particular spatial pattern that allow uncertainty and risk quantification. This paper reviews the most recent methods of spatial data analysis, prediction, and risk mapping, based on machine learning and stochastic simulations in comparison with more traditional regression models. The radioactive fallout from the Chernobyl Nuclear Power Plant accident is used to illustrate the application of the models for prediction and classification problems. This fallout is a unique case study that provides the challenging task of analyzing huge amounts of data ('hard' direct measurements, as well as supplementary information and expert estimates) and solving particular decision-oriented problems.

Machine learning for spatial environmental data. Theory, applications and software

The book presents the state of the art in machine learning algorithms (artificial neural networks of different architectures, support vector machines, etc.) as applied to the classification and mapping of spatially distributed environmental data. Basic geostatistical algorithms are presented as well. New trends in machine learning and their application to spatial data are given, and real case studies based on environmental and pollution data are carried out. The book provides a CD-ROM with the Machine Learning Office software, including sample sets of data, that will allow both students and researchers to put the concepts rapidly to practice.

Modularity of auditory spatial representations

Abstract : Auditory spatial functions are of crucial importance in everyday life. Determining the origin of sound sources in space plays a key role in a variety of tasks including orientation of attention, disentangling of complex acoustic patterns reaching our ears in noisy environments. Following brain damage, auditory spatial processing can be disrupted, resulting in severe handicaps. Complaints of patients with sound localization deficits include the inability to locate their crying child or being over-loaded by sounds in crowded public places. Yet, the brain bears a large capacity for reorganization following damage and/or learning. This phenomenon is referred as plasticity and is believed to underlie post-lesional functional recovery as well as learning-induced improvement. The aim of this thesis was to investigate the organization and plasticity of different aspects of auditory spatial functions. Overall, we report the outcomes of three studies: In the study entitled "Learning-induced plasticity in auditory spatial representations" (Spierer et al., 2007b), we focused on the neurophysiological and behavioral changes induced by auditory spatial training in healthy subjects. We found that relatively brief auditory spatial discrimination training improves performance and modifies the cortical representation of the trained sound locations, suggesting that cortical auditory representations of space are dynamic and subject to rapid reorganization. In the same study, we tested the generalization and persistence of training effects over time, as these are two determining factors in the development of neurorehabilitative intervention. In "The path to success in auditory spatial discrimination" (Spierer et al., 2007c), we investigated the neurophysiological correlates of successful spatial discrimination and contribute to the modeling of the anatomo-functional organization of auditory spatial processing in healthy subjects. We showed that discrimination accuracy depends on superior temporal plane (STP) activity in response to the first sound of a pair of stimuli. Our data support a model wherein refinement of spatial representations occurs within the STP and that interactions with parietal structures allow for transformations into coordinate frames that are required for higher-order computations including absolute localization of sound sources. In "Extinction of auditory stimuli in hemineglect: space versus ear" (Spierer et al., 2007a), we investigated auditory attentional deficits in brain-damaged patients. This work provides insight into the auditory neglect syndrome and its relation with neglect symptoms within the visual modality. Apart from contributing to a basic understanding of the cortical mechanisms underlying auditory spatial functions, the outcomes of the studies also contribute to develop neurorehabilitation strategies, which are currently being tested in clinical populations.

Perinatal choline supplementation reveals a dissociation between two types of spatial strategies.

Choline supplementation improving memory functions in rodents is assumed to increase the synthesis and release of acetylcholine in the brain. We have found that a combined pre- and postnatal supplementation results in long-lasting facilitation of spatial memory in juvenile rats when training was conducted in presence of a local salient cue. The present work was aimed at analysing the effects of peri- and postnatal choline supplementation on spatial abilities of naive adult rats. Rats given a perinatal choline supplementation were trained in various cued procedures of the Morris navigation task when aged 5 months. The treatment had a specific effect of reducing the escape latency of the rats when the platform was at a fixed position in space and surrounded by a suspended cue. This effect was associated with an increased spatial bias when the cue and platform were removed. In this condition, the control rats showed impaired spatial discrimination following the removal of the target cue, most likely due to an overshadowing of the distant environmental cues. This impairment was not observed in the treated rats. Further training with the suspended cue at unpredictable places in the pool revealed longer escape latencies in the control than in the treated rats suggesting that this procedure induced a selective perturbation of the normal but not of the treated rats. A special probe trial with the cue at an irrelevant position and no escape platform revealed a significant bias of the control rats toward the cue and of the treated rats toward the uncued spatial escape position. This behavioural dissociation suggests that a salient cue associated with the target induces an alternative "non spatial" guidance strategy in normal rats, with the risk of overshadowing of the more distant spatial cues. In this condition, the choline supplementation facilities a spatial reliance on the cue, that is an overall facilitation of learning a set of spatial relations between several visual cues. As a consequence, the improved escape in presence of the cue is associated with a stronger memory of the spatial position following disappearance of the cue. This and previous observations suggest that a specific spatial attention process relies on the buffering of highly salient visual cues.to facilitate integration of their relative position in the environment.

Influence of local environmental olfactory cues on place learning in rats

The aim of the present study was to assess the influence of local environmental olfactory cues on place learning in rats. We developed a new experimental design allowing the comparison of the use of local olfactory and visual cues in spatial and discrimination learning. We compared the effect of both types of cues on the discrimination of a single food source in an open-field arena. The goal was either in a fixed or in a variable location, and could be indicated by local olfactory and/or visual cues. The local cues enhanced the discrimination of the goal dish, whether it was in a fixed or in a variable location. However, we did not observe any overshadowing of the spatial information by the local olfactory or visual cue. Rats relied primarily on distant visuospatial information to locate the goal, neglecting local information when it was in conflict with the spatial information.

A behavioral study of alpha-1b adrenergic receptor knockout mice: increased reaction to novelty and selectively reduced learning capacities.

Knockout mice lacking the alpha-1b adrenergic receptor were tested in behavioral experiments. Reaction to novelty was first assessed in a simple test in which the time taken by the knockout mice and their littermate controls to enter a second compartment was compared. Then the mice were tested in an open field to which unknown objects were subsequently added. Special novelty was introduced by moving one of the familiar objects to another location in the open field. Spatial behavior and memory were further studied in a homing board test, and in the water maze. The alpha-1b knockout mice showed an enhanced reactivity to new situations. They were faster to enter the new environment, covered longer paths in the open field, and spent more time exploring the new objects. They reacted like controls to modification inducing spatial novelty. In the homing board test, both the knockout mice and the control mice seemed to use a combination of distant visual and proximal olfactory cues, showing place preference only if the two types of cues were redundant. In the water maze the alpha-1b knockout mice were unable to learn the task, which was confirmed in a probe trial without platform. They were perfectly able, however, to escape in a visible platform procedure. These results confirm previous findings showing that the noradrenergic pathway is important for the modulation of behaviors such as reaction to novelty and exploration, and suggest that this is mediated, at least partly, through the alpha-1b adrenergic receptors. The lack of alpha-1b adrenergic receptors in spatial orientation does not seem important in cue-rich tasks but may interfere with orientation in situations providing distant cues only.

Learning-induced plasticity in human audition: Objects, time, and space.

The human auditory system is comprised of specialized but interacting anatomic and functional pathways encoding object, spatial, and temporal information. We review how learning-induced plasticity manifests along these pathways and to what extent there are common mechanisms subserving such plasticity. A first series of experiments establishes a temporal hierarchy along which sounds of objects are discriminated along basic to fine-grained categorical boundaries and learned representations. A widespread network of temporal and (pre)frontal brain regions contributes to object discrimination via recursive processing. Learning-induced plasticity typically manifested as repetition suppression within a common set of brain regions. A second series considered how the temporal sequence of sound sources is represented. We show that lateralized responsiveness during the initial encoding phase of pairs of auditory spatial stimuli is critical for their accurate ordered perception. Finally, we consider how spatial representations are formed and modified through training-induced learning. A population-based model of spatial processing is supported wherein temporal and parietal structures interact in the encoding of relative and absolute spatial information over the initial ∼300ms post-stimulus onset. Collectively, these data provide insights into the functional organization of human audition and open directions for new developments in targeted diagnostic and neurorehabilitation strategies.