On nonlinearity in neural encoding models applied to the primary visual cortex

Within the regression framework, we show how different levels of nonlinearity influence the instantaneous firing rate prediction of single neurons. Nonlinearity can be achieved in several ways. In particular, we can enrich the predictor set with basis expansions of the input variables (enlarging the number of inputs) or train a simple but different model for each area of the data domain. Spline-based models are popular within the first category. Kernel smoothing methods fall into the second category. Whereas the first choice is useful for globally characterizing complex functions, the second is very handy for temporal data and is able to include inner-state subject variations. Also, interactions among stimuli are considered. We compare state-of-the-art firing rate prediction methods with some more sophisticated spline-based nonlinear methods: multivariate adaptive regression splines and sparse additive models. We also study the impact of kernel smoothing. Finally, we explore the combination of various local models in an incremental learning procedure. Our goal is to demonstrate that appropriate nonlinearity treatment can greatly improve the results. We test our hypothesis on both synthetic data and real neuronal recordings in cat primary visual cortex, giving a plausible explanation of the results from a biological perspective.

A graph-based approach for latency modeling and optimization in multiview video encoding

We present a novel framework for encoding latency analysis of arbitrary multiview video coding prediction structures. This framework avoids the need to consider an specific encoder architecture for encoding latency analysis by assuming an unlimited processing capacity on the multiview encoder. Under this assumption, only the influence of the prediction structure and the processing times have to be considered, and the encoding latency is solved systematically by means of a graph model. The results obtained with this model are valid for a multiview encoder with sufficient processing capacity and serve as a lower bound otherwise. Furthermore, with the objective of low latency encoder design with low penalty on rate-distortion performance, the graph model allows us to identify the prediction relationships that add higher encoding latency to the encoder. Experimental results for JMVM prediction structures illustrate how low latency prediction structures with a low rate-distortion penalty can be derived in a systematic manner using the new model.

A New Fast Motion Estimation and Mode Decision algorithm for H.264 Depth Maps encoding in Free Viewpoint TV

In this paper, we consider a scenario where 3D scenes are modeled through a View+Depth representation. This representation is to be used at the rendering side to generate synthetic views for free viewpoint video. The encoding of both type of data (view and depth) is carried out using two H.264/AVC encoders. In this scenario we address the reduction of the encoding complexity of depth data. Firstly, an analysis of the Mode Decision and Motion Estimation processes has been conducted for both view and depth sequences, in order to capture the correlation between them. Taking advantage of this correlation, we propose a fast mode decision and motion estimation algorithm for the depth encoding. Results show that the proposed algorithm reduces the computational burden with a negligible loss in terms of quality of the rendered synthetic views. Quality measurements have been conducted using the Video Quality Metric.

Remote Effects of Hippocampal Sclerosis on Effective Connectivity during Working Memory Encoding: A Case of Connectional Diaschisis?

Accumulating evidence suggests a role for the medial temporal lobe (MTL) in working memory (WM). However, little is known concerning its functional interactions with other cortical regions in the distributed neural network subserving WM. To reveal these, we availed of subjects with MTL damage and characterized changes in effective connectivity while subjects engaged in WM task. Specifically, we compared dynamic causal models, extracted from magnetoencephalographic recordings during verbal WM encoding, in temporal lobe epilepsy patients (with left hippocampal sclerosis) and controls. Bayesian model comparison indicated that the best model (across subjects) evidenced bilateral, forward, and backward connections, coupling inferior temporal cortex (ITC), inferior frontal cortex (IFC), and MTL. MTL damage weakened backward connections from left MTL to left ITC, a decrease accompanied by strengthening of (bidirectional) connections between IFC and MTL in the contralesional hemisphere. These findings provide novel evidence concerning functional interactions between nodes of this fundamental cognitive network and sheds light on how these interactions are modified as a result of focal damage to MTL. The findings highlight that a reduced (top-down) influence of the MTL on ipsilateral language regions is accompanied by enhanced reciprocal coupling in the undamaged hemisphere providing a first demonstration of “connectional diaschisis.”

Cromosomal location of four genes encoding Class III peroxidases in wheat

In a previous work, deduced amino acid sequences from twenty wheat peroxidase genes were assigned to seven groups designated as TaPrx108 to TaPrx114. Some of these apoplastic peroxidases have previously shown to play different roles in the plant defense responses to infection by the cereal cyst nematode Heterodera avenae. In the present study, PCR marker analysis using Sears’s aneuploid wheat lines cv. ‘Chinese Spring’ was used to locate four genes encoding peroxidase isozymes. The TaPrx111-A, TaPrx112-D and TaPrx113-F genes were located on the short arm of chromosome 2B and the TaPrx109-C on the long arm of chromosome 1B. These results would agree with the synteny between wheat and rice chromosomes previously established in other studies.

Brain dynamics of mild cognitive impairment during face encoding

Brain oscillations are closely correlated with human information processing and fundamental aspects of cognition. Previous literature shows that due to the relation between brain oscillations and memory processes, spectral dynamics during such tasks are good candidates to study and characterize memory related pathologies. Mild cognitive impairment (MCI), defined as a clinical condition characterized by memory impairment and/ or deterioration of additional cognitive domains, is considered a preliminary stage in the dementia process. In consequence, the study of its brain patterns could help to achieve an early diagnosis of Alzheimer Disease.

The AtCathB3 gene, encoding a cathepsin B-like protease, is expressed during germination of Arabidopsis thaliana and transcriptionally repressed by the basic leucine zipper protein GBF1.

Protein hydrolysis plays an important role during seed germination and post-germination seedling establishment. In Arabidopsis thaliana, cathepsin B-like proteases are encoded by a gene family of three members, but only the AtCathB3 gene is highly induced upon seed germination and at the early post-germination stage. Seeds of a homozygous T-DNA insertion mutant in the AtCathB3 gene have, besides a reduced cathepsin B activity, a slower germination than the wild type. To explore the transcriptional regulation of this gene, we used a combined phylogenetic shadowing approach together with a yeast one-hybrid screening of an arrayed library of approximately 1200 transcription factor open reading frames from Arabidopsis thaliana. We identified a conserved CathB3-element in the promoters of orthologous CathB3 genes within the Brassicaceae species analysed, and, as its DNA-interacting protein, the G-Box Binding Factor1 (GBF1). Transient overexpression of GBF1 together with a PAtCathB3::uidA (β-glucuronidase) construct in tobacco plants revealed a negative effect of GBF1 on expression driven by the AtCathB3 promoter. In stable P35S::GBF1 lines, not only was the expression of the AtCathB3 gene drastically reduced, but a significant slower germination was also observed. In the homozygous knockout mutant for the GBF1 gene, the opposite effect was found. These data indicate that GBF1 is a transcriptional repressor of the AtCathB3 gene and affects the germination kinetics of Arabidopsis thaliana seeds. As AtCathB3 is also expressed during post-germination in the cotyledons, a role for the AtCathB3-like protease in reserve mobilization is also inferred.

Arabidopsis thaliana bZIP44: a transcription factor affecting seed germination and expression of the mannanase-encoding gene AtMAN7.

Endo-β-mannanases (MAN; EC. 3.2.1.78) catalyze the cleavage of β1[RIGHTWARDS ARROW]4 bonds in mannan polymers and have been associated with the process of weakening the tissues surrounding the embryo during seed germination. In germinating Arabidopsis thaliana seeds, the most highly expressed MAN gene is AtMAN7 and its transcripts are restricted to the micropylar endosperm and to the radicle tip just before radicle emergence. Mutants with a T-DNA insertion in AtMAN7 have a slower germination than the wild type. To gain insight into the transcriptional regulation of the AtMAN7 gene, a bioinformatic search for conserved non-coding cis-elements (phylogenetic shadowing) within the Brassicaceae MAN7 gene promoters has been done, and these conserved motifs have been used as bait to look for their interacting transcription factors (TFs), using as a prey an arrayed yeast library from A. thaliana. The basic-leucine zipper TF AtbZIP44, but not the closely related AtbZIP11, has thus been identified and its transcriptional activation upon AtMAN7 has been validated at the molecular level. In the knock-out lines of AtbZIP44, not only is the expression of the AtMAN7 gene drastically reduced, but these mutants have a significantly slower germination than the wild type, being affected in the two phases of the germination process, both in the rupture of the seed coat and in the breakage of the micropylar endosperm cell walls. In the over-expression lines the opposite phenotype is observed.

Nitrogen fixation by native Bradyrhizobia in symbiosis with Lupinus mariae-josephae requires a T3SS encoding a NopE-like effector

Several bradyrhizobial isolates from L. mariae-josephae root nodules [1] contain a type III secretion system (T3SS) within a cluster of about 30 genes. Among those genes, ttsI codes for the transcriptional activator of the system. Mutation of ttsI resulted in the formation of white, non-fixing nodules with the natural legume host, L. mariae-josephae. The T3SS cluster also contains a gene coding for a NopE-like protein. NopE proteins have been demonstrated to be effectors in the Bradyrhizobium-soybean symbiosis [2] and belong to a small group of poorly characterized proteins from plant-associated bacteria that contain one or two autocleavage motifs known as DUF1521 (Schirrmeister et al. 2011). The amino acid sequence of a NopE-like protein in the L. mariae-josephae strain LmjC contains just one autocatalytic motif. This is unlike NopE1 and NopE2 proteins secreted by the T3SS of B. japonicum, that contain two motifs [3]. The autocleavage of LmjC NopE protein was analyzed after expression in E. coli and purification. Two protein fragments of the predicted sizes appeared in the presence of Ca2+, Cu2+, Cd2+, Zn2+ and Mn2+ cations. In contrast, autocleavage did not take place in the presence of Ni2+, Co2+ or Mg2+. Site-directed mutagenesis of the DUF1521 motif in LmjC NopE abolished self-cleavage in vitro. Symbiotic competence of a NopE- mutant with the L. mariae-josephae host was not affected. Possible roles of NopE are discussed.

A framework for the analysis and optimization of encoding latency for multiview video

We present a novel framework for the analysis and optimization of encoding latency for multiview video. Firstly, we characterize the elements that have an influence in the encoding latency performance: (i) the multiview prediction structure and (ii) the hardware encoder model. Then, we provide algorithms to find the encoding latency of any arbitrary multiview prediction structure. The proposed framework relies on the directed acyclic graph encoder latency (DAGEL) model, which provides an abstraction of the processing capacity of the encoder by considering an unbounded number of processors. Using graph theoretic algorithms, the DAGEL model allows us to compute the encoding latency of a given prediction structure, and determine the contribution of the prediction dependencies to it. As an example of DAGEL application, we propose an algorithm to reduce the encoding latency of a given multiview prediction structure up to a target value. In our approach, a minimum number of frame dependencies are pruned, until the latency target value is achieved, thus minimizing the degradation of the rate-distortion performance due to the removal of the prediction dependencies. Finally, we analyze the latency performance of the DAGEL derived prediction structures in multiview encoders with limited processing capacity.

Genes encoding beta-mannanases in Brachypodium distachyon seeds have a role not only in cell wall softening upon germination sensu stricto but also during post-germinative reserve mobilization

En la coleorriza en semillas de Brachypodium son abundantes los mananos y estos van desapareciendo conforme progresa la germinación (entre 12-27 h), al mismo tiempo se observa un pico de actividad endo-beta-mananasa. Se ha establecido que de los 6 miembros de la familia MAN en B. distachyon 3 se expresan en el embrión en germinación y BdMAN3 también es abundante en la aleurona.

Logarithmical hopping encoding: a low computational complexity algorithm for image compression

LHE (logarithmical hopping encoding) is a computationally efficient image compression algorithm that exploits the Weber–Fechner law to encode the error between colour component predictions and the actual value of such components. More concretely, for each pixel, luminance and chrominance predictions are calculated as a function of the surrounding pixels and then the error between the predictions and the actual values are logarithmically quantised. The main advantage of LHE is that although it is capable of achieving a low-bit rate encoding with high quality results in terms of peak signal-to-noise ratio (PSNR) and image quality metrics with full-reference (FSIM) and non-reference (blind/referenceless image spatial quality evaluator), its time complexity is O( n) and its memory complexity is O(1). Furthermore, an enhanced version of the algorithm is proposed, where the output codes provided by the logarithmical quantiser are used in a pre-processing stage to estimate the perceptual relevance of the image blocks. This allows the algorithm to downsample the blocks with low perceptual relevance, thus improving the compression rate. The performance of LHE is especially remarkable when the bit per pixel rate is low, showing much better quality, in terms of PSNR and FSIM, than JPEG and slightly lower quality than JPEG-2000 but being more computationally efficient.