What can spike train distances tell us about the neural code?

Time scale parametric spike train distances like the Victor and the van Rossum distancesare often applied to study the neural code based on neural stimuli discrimination.Different neural coding hypotheses, such as rate or coincidence coding,can be assessed by combining a time scale parametric spike train distance with aclassifier in order to obtain the optimal discrimination performance. The time scalefor which the responses to different stimuli are distinguished best is assumed to bethe discriminative precision of the neural code. The relevance of temporal codingis evaluated by comparing the optimal discrimination performance with the oneachieved when assuming a rate code.We here characterize the measures quantifying the discrimination performance,the discriminative precision, and the relevance of temporal coding. Furthermore,we evaluate the information these quantities provide about the neural code. Weshow that the discriminative precision is too unspecific to be interpreted in termsof the time scales relevant for encoding. Accordingly, the time scale parametricnature of the distances is mainly an advantage because it allows maximizing thediscrimination performance across a whole set of measures with different sensitivitiesdetermined by the time scale parameter, but not due to the possibility toexamine the temporal properties of the neural code.

Wavelet analysis residual kriging vs. neural network residual kriging

This paper deals with the problem of spatial data mapping. A new method based on wavelet interpolation and geostatistical prediction (kriging) is proposed. The method - wavelet analysis residual kriging (WARK) - is developed in order to assess the problems rising for highly variable data in presence of spatial trends. In these cases stationary prediction models have very limited application. Wavelet analysis is used to model large-scale structures and kriging of the remaining residuals focuses on small-scale peculiarities. WARK is able to model spatial pattern which features multiscale structure. In the present work WARK is applied to the rainfall data and the results of validation are compared with the ones obtained from neural network residual kriging (NNRK). NNRK is also a residual-based method, which uses artificial neural network to model large-scale non-linear trends. The comparison of the results demonstrates the high quality performance of WARK in predicting hot spots, reproducing global statistical characteristics of the distribution and spatial correlation structure.

FGF-2 controls the differentiation of resident cardiac precursors into functional cardiomyocytes.

Recent evidence suggests that the heart possesses a greater regeneration capacity than previously thought. In the present study, we isolated undifferentiated precursors from the cardiac nonmyocyte cell population of neonatal hearts, expanded them in culture, and induced them to differentiate into functional cardiomyocytes. These cardiac precursors appear to express stem cell antigen-1 and demonstrate characteristics of multipotent precursors of mesodermal origin. Following infusion into normal recipients, these cells home to the heart and participate in physiological and pathophysiological cardiac remodeling. Cardiogenic differentiation in vitro and in vivo depends on FGF-2. Interestingly, this factor does not control the number of precursors but regulates the differentiation process. These findings suggest that, besides its angiogenic actions, FGF-2 could be used in vivo to facilitate the mobilization and differentiation of resident cardiac precursors in the treatment of cardiac diseases.

Dual functions of DP1 promote biphasic Wnt-on and Wnt-off states during anteroposterior neural patterning.

DP1, a dimerization partner protein of the transcription factor E2F, is known to inhibit Wnt/β-catenin signalling along with E2F, although the function of DP1 itself was not well characterized. Here, we present a novel dual regulatory mechanism of Wnt/β-catenin signalling by DP1 independent from E2F. DP1 negatively regulates Wnt/β-catenin signalling by inhibiting Dvl-Axin interaction and by enhancing poly-ubiquitination of β-catenin. In contrast, DP1 positively modulates the signalling upon Wnt stimulation, via increasing cytosolic β-catenin and antagonizing the kinase activity of NLK. In Xenopus embryos, DP1 exerts both positive and negative roles in Wnt/β-catenin signalling during anteroposterior neural patterning. From subcellular localization analyses, we suggest that the dual roles of DP1 in Wnt/β-catenin signalling are endowed by differential nucleocytoplasmic localizations. We propose that these dual functions of DP1 can promote and stabilize biphasic Wnt-on and Wnt-off states in response to a gradual gradient of Wnt/β-catenin signalling to determine differential cell fates.

Neuronal autophagy as a mediator of life and death: contrasting roles in chronic neurodegenerative and acute neural disorders.

Autophagy is a cellular mechanism for degrading proteins and organelles. It was first described as a physiological process essential for cellular health and survival, and this is its role in most cells. However, it can also be a mediator of cell death, either by the triggering of apoptosis or by an independent "autophagic" cell death mechanism. This duality is important in the central nervous system, where the activation of autophagy has recently been shown to be protective in certain chronic neurodegenerative diseases but deleterious in acute neural disorders such as stroke and hypoxic/ischemic injury. The authors here discuss these distinct roles of autophagy in the nervous system with a focus on the role of autophagy in mediating neuronal death. The development of new therapeutic strategies based on the manipulation of autophagy will need to take into account these opposing roles of autophagy.

Morphometric shape analysis using learning vector quantization neural networks - an example distinguishing two microtine vole species

Closely related species may be very difficult to distinguish morphologically, yet sometimes morphology is the only reasonable possibility for taxonomic classification. Here we present learning-vector-quantization artificial neural networks as a powerful tool to classify specimens on the basis of geometric morphometric shape measurements. As an example, we trained a neural network to distinguish between field and root voles from Procrustes transformed landmark coordinates on the dorsal side of the skull, which is so similar in these two species that the human eye cannot make this distinction. Properly trained neural networks misclassified only 3% of specimens. Therefore, we conclude that the capacity of learning vector quantization neural networks to analyse spatial coordinates is a powerful tool among the range of pattern recognition procedures that is available to employ the information content of geometric morphometrics.

Fatty acids regulate Thy-1 antigen mRNA stability in T lymphocyte precursors.

In this study, we report the effect of fatty acids on the Thy-1 antigen mRNA decay. Low serum and synthetic medium culture conditions were used to demonstrate that fatty acids, which are important metabolites involved as second messengers in signal transduction, also influence the steady-state mRNA level. Detailed analysis demonstrated that polyunsaturated lipids attached to bovine serum albumin, such as linoleic, linolenic, and arachidonic acids, modulate gene expression specifically in the S1A T lymphoma cell line by inducing a 3-5-fold increase in the steady-state Thy-1 mRNA level, concomitant with a twofold increase in cell surface expression. A similar modulation was observed in the immature CD4-CD8- T cell precursors but not in mature thymocytes. Nuclear run-on and transfection experiments indicated that the observed Thy-1 mRNA level is post-transcriptionally regulated and that the presence of the coding region is sufficient for this adaptive response. A mechanism without a requirement for protein kinase C activation, but involving Ca2+ entry, could account for this difference in Thy-1 mRNA stability.

Cutting edge: thymic NK cells develop independently from T cell precursors.

Although NK cells in the mouse are thought to develop in the bone marrow, a small population of NK cells in the thymus has been shown to derive from a GATA3-dependent pathway. Characteristically, thymic NK cells express CD127 and few Ly49 molecules and lack CD11b. Because these NK cells develop in the thymus, the question of their relationship to the T cell lineage has been raised. Using several different mouse models, we find that unlike T cells, thymic NK cells are not the progeny of Rorc-expressing progenitors and do not express Rag2 or rearrange the TCRγ locus. We further demonstrate that thymic NK cells develop independently of the Notch signaling pathway, supporting the idea that thymic NK cells represent bona fide NK cells that can develop independently of all T cell precursors.

Neural control of vascular reactions: impact of emotion and attention.

This study investigated the neural regions involved in blood pressure reactions to negative stimuli and their possible modulation by attention. Twenty-four healthy human subjects (11 females; age = 24.75 ± 2.49 years) participated in an affective perceptual load task that manipulated attention to negative/neutral distractor pictures. fMRI data were collected simultaneously with continuous recording of peripheral arterial blood pressure. A parametric modulation analysis examined the impact of attention and emotion on the relation between neural activation and blood pressure reactivity during the task. When attention was available for processing the distractor pictures, negative pictures resulted in behavioral interference, neural activation in brain regions previously related to emotion, a transient decrease of blood pressure, and a positive correlation between blood pressure response and activation in a network including prefrontal and parietal regions, the amygdala, caudate, and mid-brain. These effects were modulated by attention; behavioral and neural responses to highly negative distractor pictures (compared with neutral pictures) were smaller or diminished, as was the negative blood pressure response when the central task involved high perceptual load. Furthermore, comparing high and low load revealed enhanced activation in frontoparietal regions implicated in attention control. Our results fit theories emphasizing the role of attention in the control of behavioral and neural reactions to irrelevant emotional distracting information. Our findings furthermore extend the function of attention to the control of autonomous reactions associated with negative emotions by showing altered blood pressure reactions to emotional stimuli, the latter being of potential clinical relevance.

Precursors of functional MHC class I- or class II-restricted CD8alphaalpha(+) T cells are positively selected in the thymus by agonist self-peptides.

The origin and specificity of alphabeta TCR(+) T cells that express CD8alphaalpha have been controversial issues. Here we provide direct evidence that precursors of functional CD8alphaalpha T cells are positively selected in the thymus in the presence of agonist self-peptides. Like conventional positive selection, this agonist selection process requires functional TCR alpha-CPM, whereas it is independent of CD8beta expression. Furthermore, CD8alphaalpha expression on mature, agonist-selected T cells does not imply selection by MHC class I, and CD8alphaalpha(+) T cells can be either class I or class II restricted. Our data define a distinct agonist-dependent, positive selection process in the thymus, and they suggest a function for CD8alphaalpha distinct from the conventional TCR coreceptor function of CD8alphabeta or CD4.

Validation procedures in radiological diagnostic models. Neural network and logistic regression

The objective of this paper is to compare the performance of twopredictive radiological models, logistic regression (LR) and neural network (NN), with five different resampling methods. One hundred and sixty-seven patients with proven calvarial lesions as the only known disease were enrolled. Clinical and CT data were used for LR and NN models. Both models were developed with cross validation, leave-one-out and three different bootstrap algorithms. The final results of each model were compared with error rate and the area under receiver operating characteristic curves (Az). The neural network obtained statistically higher Az than LR with cross validation. The remaining resampling validation methods did not reveal statistically significant differences between LR and NN rules. The neural network classifier performs better than the one based on logistic regression. This advantage is well detected by three-fold cross-validation, but remains unnoticed when leave-one-out or bootstrap algorithms are used.