A visual processing advantage for young-adolescent deaf observers: Evidence from face and object matching tasks

It is unresolved whether the permanent auditory deprivation that deaf people experience leads to the enhanced visual processing of faces. The current study explored this question with a matching task in which observers searched for a target face among a concurrent lineup of ten faces. This was compared with a control task in which the same stimuli were presented upside down, to disrupt typical face processing, and an object matching task. A sample of young-adolescent deaf observers performed with higher accuracy than hearing controls across all of these tasks. These results clarify previous findings and provide evidence for a general visual processing advantage in deaf observers rather than a face-specific effect

A Rescorla-Wagner Drift-Diffusion Model of Conditioning and Timing

Computational models of classical conditioning have made significant contributions to the theoretic understanding of associative learning, yet they still struggle when the temporal aspects of conditioning are taken into account. Interval timing models have contributed a rich variety of time representations and provided accurate predictions for the timing of responses, but they usually have little to say about associative learning. In this article we present a unified model of conditioning and timing that is based on the influential Rescorla-Wagner conditioning model and the more recently developed Timing Drift-Diffusion model. We test the model by simulating 10 experimental phenomena and show that it can provide an adequate account for 8, and a partial account for the other 2. We argue that the model can account for more phenomena in the chosen set than these other similar in scope models: CSC-TD, MS-TD, Learning to Time and Modular Theory. A comparison and analysis of the mechanisms in these models is provided, with a focus on the types of time representation and associative learning rule used

Temporal Dynamics of Visual Attention Allocation

We often temporally prepare our attention for an upcoming event such as a starter pistol. In such cases, our attention should be properly allocated around the expected moment of the event to process relevant sensory input efficiently. In this study, we examined the dynamic changes of attention levels near the expected moment by measuring contrast sensitivity to a target that was temporally cued by a five-second countdown. We found that the overall attention level decreased rapidly after the expected moment, while it stayed relatively constant before it. Results were not consistent with the predictions of existing explanations of temporal attention such as the hazard rate or the stimulus-driven oscillations. A control experiment ruled out the possibility that the observed pattern was due to biased time perception. In a further experiment with a wider range of cue-stimulus-intervals, we observed that attention level increased until the last 500 ms of the interval range, and thereafter, started to decrease. Based on the performances of a generative computational model, we suggest that our results reflect the nature of temporal attention that takes into account the subjectively estimated hazard rate and the probability of relevant events occurring in the near future

Differential Gene Expression and Epiregulation of Alpha Zein Gene Copies in Maize Haplotypes

Multigenic traits are very common in plants and cause diversity. Nutritional quality is such a trait, and one of its factors is the composition and relative expression of storage protein genes. In maize, they represent a medium-size gene family distributed over several chromosomes and unlinked locations. Two inbreds, B73 and BSSS53, both from the Iowa Stiff Stock Synthetic collection, have been selected to analyze allelic and non-allelic variability in these regions that span between 80–500 kb of chromosomal DNA. Genes were copied to unlinked sites before and after allotetraploidization of maize, but before transposition enlarged intergenic regions in a haplotype-specific manner. Once genes are copied, expression of donor genes is reduced relative to new copies. Epigenetic regulation seems to contribute to silencing older copies, because some of them can be reactivated when endosperm is maintained as cultured cells, indicating that copy number variation might contribute to a reserve of gene copies. Bisulfite sequencing of the promoter region also shows different methylation patterns among gene clusters as well as differences between tissues, suggesting a possible position effect on regulatory mechanisms as a result of inserting copies at unlinked locations. The observations offer a potential paradigm for how different gene families evolve and the impact this has on their expression and regulation of their members

The Zea mays mutants opaque-2 and opaque-7 disclose extensive changes in endosperm metabolism as revealed by protein, amino acid, and transcriptome-wide analyses

<p>Abstract</p> <p>Background</p> <p>The changes in storage reserve accumulation during maize (<it>Zea mays </it>L.) grain maturation are well established. However, the key molecular determinants controlling carbon flux to the grain and the partitioning of carbon to starch and protein are more elusive. The <it>Opaque-2 </it>(<it>O2</it>) gene, one of the best-characterized plant transcription factors, is a good example of the integration of carbohydrate, amino acid and storage protein metabolisms in maize endosperm development. Evidence also indicates that the <it>Opaque-7 </it>(<it>O7</it>) gene plays a role in affecting endosperm metabolism. The focus of this study was to assess the changes induced by the <it>o2 </it>and <it>o7 </it>mutations on maize endosperm metabolism by evaluating protein and amino acid composition and by transcriptome profiling, in order to investigate the functional interplay between these two genes in single and double mutants.</p> <p>Results</p> <p>We show that the overall amino acid composition of the mutants analyzed appeared similar. Each mutant had a high Lys and reduced Glx and Leu content with respect to wild type. Gene expression profiling, based on a unigene set composed of 7,250 ESTs, allowed us to identify a series of mutant-related down (17.1%) and up-regulated (3.2%) transcripts. Several differentially expressed ESTs homologous to genes encoding enzymes involved in amino acid synthesis, carbon metabolism (TCA cycle and glycolysis), in storage protein and starch metabolism, in gene transcription and translation processes, in signal transduction, and in protein, fatty acid, and lipid synthesis were identified. Our analyses demonstrate that the mutants investigated are pleiotropic and play a critical role in several endosperm-related metabolic processes. Pleiotropic effects were less evident in the <it>o7 </it>mutant, but severe in the <it>o2 </it>and <it>o2o7 </it>backgrounds, with large changes in gene expression patterns, affecting a broad range of kernel-expressed genes.</p> <p>Conclusion</p> <p>Although, by necessity, this paper is descriptive and more work is required to define gene functions and dissect the complex regulation of gene expression, the genes isolated and characterized to date give us an intriguing insight into the mechanisms underlying endosperm metabolism.</p

A nonlinear updating algorithm captures suboptimal inference in the presence of signal-dependent noise

Bayesian models have advanced the idea that humans combine prior beliefs and sensory observations to optimize behavior. How the brain implements Bayes-optimal inference, however, remains poorly understood. Simple behavioral tasks suggest that the brain can flexibly represent probability distributions. An alternative view is that the brain relies on simple algorithms that can implement Bayes-optimal behavior only when the computational demands are low. To distinguish between these alternatives, we devised a task in which Bayes-optimal performance could not be matched by simple algorithms. We asked subjects to estimate and reproduce a time interval by combining prior information with one or two sequential measurements. In the domain of time, measurement noise increases with duration. This property takes the integration of multiple measurements beyond the reach of simple algorithms. We found that subjects were able to update their estimates using the second measurement but their performance was suboptimal, suggesting that they were unable to update full probability distributions. Instead, subjects’ behavior was consistent with an algorithm that predicts upcoming sensory signals, and applies a nonlinear function to errors in prediction to update estimates. These results indicate that the inference strategies employed by humans may deviate from Bayes-optimal integration when the computational demands are high

Pathogenic copy number variants and SCN1A mutations in patients with intellectual disability and childhood-onset epilepsy

Background Copy number variants (CNVs) have been linked to neurodevelopmental disorders such as intellectual disability (ID), autism, epilepsy and psychiatric disease. There are few studies of CNVs in patients with both ID and epilepsy. Methods We evaluated the range of rare CNVs found in 80 Welsh patients with ID or developmental delay (DD), and childhood-onset epilepsy. We performed molecular cytogenetic testing by single nucleotide polymorphism array or microarray-based comparative genome hybridisation. Results 8.8 % (7/80) of the patients had at least one rare CNVs that was considered to be pathogenic or likely pathogenic. The CNVs involved known disease genes (EHMT1, MBD5 and SCN1A) and imbalances in genomic regions associated with neurodevelopmental disorders (16p11.2, 16p13.11 and 2q13). Prompted by the observation of two deletions disrupting SCN1A we undertook further testing of this gene in selected patients. This led to the identification of four pathogenic SCN1A mutations in our cohort. Conclusions We identified five rare de novo deletions and confirmed the clinical utility of array analysis in patients with ID/DD and childhood-onset epilepsy. This report adds to our clinical understanding of these rare genomic disorders and highlights SCN1A mutations as a cause of ID and epilepsy, which can easily be overlooked in adults