Adaptive B-spline neural network based nonlinear equalization for high-order QAM systems with nonlinear transmit high power amplifier

High bandwidth-efficiency quadrature amplitude modulation (QAM) signaling widely adopted in high-rate communication systems suffers from a drawback of high peak-toaverage power ratio, which may cause the nonlinear saturation of the high power amplifier (HPA) at transmitter. Thus, practical high-throughput QAM communication systems exhibit nonlinear and dispersive channel characteristics that must be modeled as a Hammerstein channel. Standard linear equalization becomes inadequate for such Hammerstein communication systems. In this paper, we advocate an adaptive B-Spline neural network based nonlinear equalizer. Specifically, during the training phase, an efficient alternating least squares (LS) scheme is employed to estimate the parameters of the Hammerstein channel, including both the channel impulse response (CIR) coefficients and the parameters of the B-spline neural network that models the HPA’s nonlinearity. In addition, another B-spline neural network is used to model the inversion of the nonlinear HPA, and the parameters of this inverting B-spline model can easily be estimated using the standard LS algorithm based on the pseudo training data obtained as a natural byproduct of the Hammerstein channel identification. Nonlinear equalisation of the Hammerstein channel is then accomplished by the linear equalization based on the estimated CIR as well as the inverse B-spline neural network model. Furthermore, during the data communication phase, the decision-directed LS channel estimation is adopted to track the time-varying CIR. Extensive simulation results demonstrate the effectiveness of our proposed B-Spline neural network based nonlinear equalization scheme.

Synapses in digital medium: computational investigations of neural basis of anticipation

Anticipation is an emerging concept that can provide a bridge between the deepest philosophical theories about the nature of life and cognition on one hand and the empirical biological sciences steeped in reductionist and Newtonian conception of causality. Three conceptions of anticipation have been emerging from the literature that may be operationalised in a way leading to a viable empirical programme. The discussion of the research into a novel dynamical concept of anticipating synchronisation lends credence to such a possibility and suggests further links between the three anticipation paradigms. A careful progress mindful to the deep philosophical concerns but also respecting empirical evidence will ultimately lead towards unifying theoretical and empirical biological sciences and may offer progress where reductionist science have been so far faltering.

Human neural stem cell-derived cultures in three- dimensional substrates form spontaneously functional neuronal networks

Differentiated human neural stem cells were cultured in an inert three-dimensional (3D) scaffold and, unlike two-dimensional (2D) but otherwise comparable monolayer cultures, formed spontaneously active, functional neuronal networks that responded reproducibly and predictably to conventional pharmacological treatments to reveal functional, glutamatergic synapses. Immunocytochemical and electron microscopy analysis revealed a neuronal and glial population, where markers of neuronal maturity were observed in the former. Oligonucleotide microarray analysis revealed substantial differences in gene expression conferred by culturing in a 3D vs a 2D environment. Notable and numerous differences were seen in genes coding for neuronal function, the extracellular matrix and cytoskeleton. In addition to producing functional networks, differentiated human neural stem cells grown in inert scaffolds offer several significant advantages over conventional 2D monolayers. These advantages include cost savings and improved physiological relevance, which make them better suited for use in the pharmacological and toxicological assays required for development of stem cell-based treatments and the reduction of animal use in medical research.

Neural emotion regulation circuitry underlying anxiolytic effects of perceived control over pain.

Anxiolytic effects of perceived control have been observed across species. In humans, neuroimaging studies have suggested that perceived control and cognitive reappraisal reduce negative affect through similar mechanisms. An important limitation of extant neuroimaging studies of perceived control in terms of directly testing this hypothesis, however, is the use of within-subject designs, which confound participants' affective response to controllable and uncontrollable stress. To compare neural and affective responses when participants were exposed to either uncontrollable or controllable stress, two groups of participants received an identical series of stressors (thermal pain stimuli). One group ("controllable") was led to believe they had behavioral control over the pain stimuli, whereas another ("uncontrollable") believed they had no control. Controllable pain was associated with decreased state anxiety, decreased activation in amygdala, and increased activation in nucleus accumbens. In participants who perceived control over the pain, reduced state anxiety was associated with increased functional connectivity between each of these regions and ventral lateral/ventral medial pFC. The location of pFC findings is consistent with regions found to be critical for the anxiolytic effects of perceived control in rodents. Furthermore, interactions observed between pFC and both amygdala and nucleus accumbens are remarkably similar to neural mechanisms of emotion regulation through reappraisal in humans. These results suggest that perceived control reduces negative affect through a general mechanism involved in the cognitive regulation of emotion.

Rapid, automated detection of stem canker symptoms in woody perennials using artificial neural network analysis

Background Pseudomonas syringae can cause stem necrosis and canker in a wide range of woody species including cherry, plum, peach, horse chestnut and ash. The detection and quantification of lesion progression over time in woody tissues is a key trait for breeders to select upon for resistance. Results In this study a general, rapid and reliable approach to lesion quantification using image recognition and an artificial neural network model was developed. This was applied to screen both the virulence of a range of P. syringae pathovars and the resistance of a set of cherry and plum accessions to bacterial canker. The method developed was more objective than scoring by eye and allowed the detection of putatively resistant plant material for further study. Conclusions Automated image analysis will facilitate rapid screening of material for resistance to bacterial and other phytopathogens, allowing more efficient selection and quantification of resistance responses.

From molecules to neural morphology: understanding neuroinflammation in autism spectrum condition

Growing evidence points toward a critical role for early (prenatal) atypical neurodevelopmental processes in the aetiology of autism spectrum condition (ASC). One such process that could impact early neural development is inflammation. We review the evidence for atypical expression of molecular markers in the amniotic fluid, serum, cerebrospinal fluid (CSF), and the brain parenchyma that suggest a role for inflammation in the emergence of ASC. This is complemented with a number of neuroimaging and neuropathological studies describing microglial activation. Implications for treatment are discussed.

Enhanced neural response to anticipation, effort and consummation of reward and aversion during Bupropion treatment

Background We have previously shown that the selective serotonergic re-uptake inhibitor, citalopram, reduces the neural response to reward and aversion in healthy volunteers. We suggest that this inhibitory effect might underlie the emotional blunting reported by patients on these medications. Bupropion is a dopaminergic and noradrenergic re-uptake inhibitor and has been suggested to have more therapeutic effects on reward-related deficits. However, how bupropion affects the neural responses to reward and aversion is unclear. Methods 17 healthy volunteers (9 female, 8 male) received 7 days of bupropion (150 mg/day) and 7 days of placebo treatment, in a double-blind crossover design. Our functional Magnetic Resonance Imaging task consisted of 3 phases; an anticipatory phase (pleasant or unpleasant cue), an effort phase (button presses to achieve a pleasant taste or to avoid an unpleasant taste) and a consummatory phase (pleasant or unpleasant tastes). Volunteers also rated wanting, pleasantness and intensity of the tastes. Results Relative to placebo, bupropion increased activity during the anticipation phase in the ventral medial prefrontal cortex (vmPFC) and caudate. During the effort phase, bupropion increased activity in the vmPFC, striatum, dorsal anterior cingulate cortex and primary motor cortex. Bupropion also increased medial orbitofrontal cortex, amygdala and ventral striatum activity during the consummatory phase. Conclusions Our results are the first to show that bupropion can increase neural responses during the anticipation, effort and consummation of rewarding and aversive stimuli. This supports the notion that bupropion might be beneficial for depressed patients with reward-related deficits and blunted affect.

Neural signals of “Intensity” but not “Wanting” or “Liking” of rewards may be trait markers for depression

We have shown previously that particpants “at risk” of depression have decreased neural processing of reward suggesting this might be a neural biomarker for depression. However, how the neural signal related to subjective experiences of reward (wanting, liking, intensity) might differ as trait markers for depression, is as yet unknown. Using SPM8 parametric modulation analysis the neural signal related to the subjective report of wanting, liking and intensity was compared between 25 young people with a biological parent with depression (FH) and 25 age/gender matched controls. In a second study the neural signal related to the subjective report of wanting, liking and intensity was compared between 13 unmedicated recovered depressed (RD) patients and 14 healthy age/gender matched controls. The analysis revealed differences in the neural signal for wanting, liking and intensity ratings in the ventral striatum, dmPFC and caudate respectively in the RD group compared to controls . Despite no differences in the FH groups neural signal for wanting and liking there was a difference in the neural signal for intensity ratings in the dACC and anterior insula compared to controls. These results suggest that the neural substrates tracking the intensity but not the wanting or liking for rewards and punishers might be a trait marker for depression.

Maintenance and differentiation of neural stem cells

The adult mammalian brain contains self-renewable, multipotent neural stem cells (NSCs) that are responsible for neurogenesis and plasticity in specific regions of the adult brain. Extracellular matrix, vasculature, glial cells, and other neurons are components of the niche where NSCs are located. This surrounding environment is the source of extrinsic signals that instruct NSCs to either self-renew or differentiate. Additionally, factors such as the intracellular epigenetics state and retrotransposition events can influence the decision of NSC`s fate into neurons or glia. Extrinsic and intrinsic factors form an intricate signaling network, which is not completely understood. These factors altogether reflect a few of the key players characterized so far in the new field of NSC research and are covered in this review. (C) 2010 John Wiley & Sons, Inc. WIREs Syst Biol Med 2011 3 107-114 DOI:10.1002/wsbm:100

Enhanced Neural Progenitor/Stem Cells Self-Renewal via the Interaction of Stress-Inducible Protein 1 with the Prion Protein

Prion protein (PrPC), when associated with the secreted form of the stress-inducible protein 1 (STI1), plays an important role in neural survival, neuritogenesis, and memory formation. However, the role of the PrP(C)-STI1 complex in the physiology of neural progenitor/stem cells is unknown. In this article, we observed that neurospheres cultured from fetal forebrain of wild-type (Prnp(+/+)) and PrP(C)-null (Prnp(0/0)) mice were maintained for several passages without the loss of self-renewal or multipotentiality, as assessed by their continued capacity to generate neurons, astrocytes, and oligodendrocytes. The homogeneous expression and colocalization of STI1 and PrP(C) suggest that they may associate and function as a complex in neurosphere-derived stem cells. The formation of neurospheres from Prnp(0/0) mice was reduced significantly when compared with their wild-type counterparts. In addition, blockade of secreted STI1, and its cell surface ligand, PrP(C), with specific antibodies, impaired Prnp(+/+) neurosphere formation without further impairing the formation of Prnp(0/0) neurospheres. Alternatively, neurosphere formation was enhanced by recombinant STI1 application in cells expressing PrP(C) but not in cells from Prnp(0/0) mice. The STI1-PrP(C) interaction was able to stimulate cell proliferation in the neurosphere-forming assay, while no effect on cell survival or the expression of neural markers was observed. These data suggest that the STI1-PrP(C) complex may play a critical role in neural progenitor/stem cells self-renewal via the modulation of cell proliferation, leading to the control of the stemness capacity of these cells during nervous system development. STEM CELLS 2011;29:1126-1136

Administration of Neural Precursor Cells Ameliorates Renal Ischemia-Reperfusion Injury

In this study we evaluated whether administration of stem cells of neural origin (neural precursor cells, NPCs) could be protective against renal ischemia-reperfusion injury (IRI). We hypothesized that stem cell outcomes are not tissue-specific and that NPCs can improve tissue damage through paracrine mechanisms, especially due to immunomodulation. To this end, Wistar rats (200-250 g) were submitted to 1-hour ischemia and treated with NPCs (4 x 10(6) cells/animal) at 4 h of reperfusion. To serve as controls, ischemic animals were treated with cerebellum homogenate harvested from adult rat brain. All groups were sacrificed at 24 h of reperfusion. NPCs were isolated from rat fetus telencephalon and cultured until neurosphere formation (7 days). Before administration, NPCs were labeled with carboxyfluorescein diacetate succinimydylester (CFSE). Kidneys were harvested for analysis of cytokine profile and macrophage infiltration. At 24 h, NPC treatment resulted in a significant reduction in serum creatinine (IRI + NPC 1.21 + 0.18 vs. IRI 3.33 + 0.14 and IRI + cerebellum 2.95 + 0.78mg/dl, p < 0.05) and acute tubular necrosis (IRI + NPC 46.0 + 2.4% vs. IRI 79.7 + 14.2%, p < 0.05). NPC-CFSE and glial fibrillary acidic protein (GFAP)-positive cells (astrocyte marker) were found exclusively in renal parenchyma, which also presented GFAP and SOX-2 (an embryonic neural stem cell marker) mRNA expression. NPC treatment resulted in lower renal proinflammatory IL1-beta and TNF-alpha expression and higher anti-inflammatory IL-4 and IL-10 transcription. NPC-treated animals also had less macrophage infiltration and decreased serum proinflammatory cytokines (IL-1 beta, TNF-alpha and INF-gamma). Our data suggested that NPC therapy improved renal function by influencing immunological responses. Copyright (C) 2009 S. Karger AG, Basel

Image indexing and retrieval using an ART-2A neural network architecture

Traditional content-based image retrieval (CBIR) systems use low-level features such as colors, shapes, and textures of images. Although, users make queries based on semantics, which are not easily related to such low-level characteristics. Recent works on CBIR confirm that researchers have been trying to map visual low-level characteristics and high-level semantics. The relation between low-level characteristics and image textual information has motivated this article which proposes a model for automatic classification and categorization of words associated to images. This proposal considers a self-organizing neural network architecture, which classifies textual information without previous learning. Experimental results compare the performance results of the text-based approach to an image retrieval system based on low-level features. (c) 2008 Wiley Periodicals, Inc.

A Road Following Approach Using Artificial Neural Networks Combinations

Navigation is a broad topic that has been receiving considerable attention from the mobile robotic community over the years. In order to execute autonomous driving in outdoor urban environments it is necessary to identify parts of the terrain that can be traversed and parts that should be avoided. This paper describes an analyses of terrain identification based on different visual information using a MLP artificial neural network and combining responses of many classifiers. Experimental tests using a vehicle and a video camera have been conducted in real scenarios to evaluate the proposed approach.