The dependence of simple reaction time on temporal patterns of stimuli

Simple reaction time has been measured using various distributions of interstimulus intervals (ISIs), which differed both in the shape of their envelope and in their degree of discretization. For each of 7 such conditions, and for three mean ISIs (2.0, 3.3, and 5.8 s) 600 responses of two subjects have been accumulated.Reaction times depend significantly on the shape of ISI-distributions but also on their degree of discretization. Within an experimental run they depend on single ISIs back to the third before reaction, and on sequences of ISIs. The latter effects are again influenced by the discretization of ISIs. Finally it was found that some learning of the distribution pattern (not the mere mean value) of ISIs takes place.Our results shed some light on existing hypotheses of RT. Some inconsistencies of earlier experimental results can probably be explained by insufficient consideration of the discretization and the learning effects.     

Visible binocular beats from invisible monocular stimuli during binocular rivalry

When two qualitatively different stimuli are presented at the same time, one to each eye, the stimuli can either integrate or compete with each other. When they compete, one of the two stimuli is alternately suppressed, a phenomenon called binocular rivalry [1,2]. When they integrate, observers see some form of the combined stimuli. Many different properties (for example, shape or color) of the two stimuli can induce binocular rivalry. Not all differences result in rivalry, however. Visual 'beats', for example, are the result of integration of high-frequency flicker between the two eyes [3,4], and are thus a binocular fusion phenomenon. It remains in dispute whether binocular fusion and rivalry can co-exist with one another [5-7]. Here, we report that rivalry and beats, two apparently opposing phenomena, can be perceived at the same time within the same spatial location. We hypothesized that the interocular difference in visual attributes that are predominantly processed in the Parvocellular pathway will lead to rivalry, and differences in visual attributes that are predominantly processed in the Magnocellular pathway tend to integrate. Further predictions based on this hypothesis were tested and confirmed.     

Speeding up sequence specific assignment of IDPs

The characterization of intrinsically disordered proteins (IDPs) by NMR spectroscopy is made difficult by the extensive spectral overlaps. To overcome the intrinsic low-resolution of the spectra the introduction of high-dimensionality experiments is essential. We present here a set of high-resolution experiments based on direct (13)C-detection which proved useful in the assignment of α-synuclein, a paradigmatic IDP. In particular, we describe the implementation of 4D HCBCACON, HCCCON, HCBCANCO, 4/5D HNCACON and HNCANCO and 3/4D HCANCACO experiments, specifically tailored for spin system identification and backbone resonances sequential assignment. The use of non-uniform-sampling in the indirect dimension and of the H-flip approach to achieve longitudinal relaxation enhancement rendered the experiments very practical.     

Speeding up whole-genome alignment by indexing frequency vectors

MOTIVATION: Many biological applications require the comparison of large genome strings. Current techniques suffer from high computational and I/O costs. RESULTS: We propose an efficient technique for local alignment of large genome strings. A space-efficient index is computed for one string, and the second string is compared with this index in order to prune substring pairs that do not contain similar regions. The remaining substring pairs are handed to a hash-table-based tool, such as BLAST, for alignment. A dynamic strategy is employed to optimize the number of disk seeks needed to access the hash table. Additionally, our technique provides the user with a coarse-grained visualization of the similarity pattern, quickly and before the actual search. The experimental results show that our technique aligns genome strings up to two orders of magnitude faster than BLAST. Our technique can be used to accelerate other search tools as well. AVAILABILITY: A web-based demo can be found at http://bioserver.cs.ucsb.edu/. Source code is available from the authors on request.     

Attentional load modulates responses of human primary visual cortex to invisible stimuli

Visual neuroscience has long sought to determine the extent to which stimulus-evoked activity in visual cortex depends on attention and awareness. Some influential theories of consciousness maintain that the allocation of attention is restricted to conscious representations [1, 2]. However, in the load theory of attention [3], competition between task-relevant and task-irrelevant stimuli for limited-capacity attention does not depend on conscious perception of the irrelevant stimuli. The critical test is whether the level of attentional load in a relevant task would determine unconscious neural processing of invisible stimuli. Human participants were scanned with high-field fMRI while they performed a foveal task of low or high attentional load. Irrelevant, invisible monocular stimuli were simultaneously presented peripherally and were continuously suppressed by a flashing mask in the other eye [4]. Attentional load in the foveal task strongly modulated retinotopic activity evoked in primary visual cortex (V1) by the invisible stimuli. Contrary to traditional views [1, 2, 5, 6], we found that availability of attentional capacity determines neural representations related to unconscious processing of continuously suppressed stimuli in human primary visual cortex. Spillover of attention to cortical representations of invisible stimuli (under low load) cannot be a sufficient condition for their awareness.     

Speeding up the Consensus Clustering methodology for microarray data analysis

Background

Position-specific priors (PSP) have been used with success to boost EM and Gibbs sampler-based motif discovery algorithms. PSP information has been computed from different sources, including orthologous conservation, DNA duplex stability, and nucleosome positioning. The use of prior information has not yet been used in the context of combinatorial algorithms. Moreover, priors have been used only independently, and the gain of combining priors from different sources has not yet been studied.

Results

We extend RISOTTO, a combinatorial algorithm for motif discovery, by post-processing its output with a greedy procedure that uses prior information. PSP's from different sources are combined into a scoring criterion that guides the greedy search procedure. The resulting method, called GRISOTTO, was evaluated over 156 yeast TF ChIP-chip sequence-sets commonly used to benchmark prior-based motif discovery algorithms. Results show that GRISOTTO is at least as accurate as other twelve state-of-the-art approaches for the same task, even without combining priors. Furthermore, by considering combined priors, GRISOTTO is considerably more accurate than the state-of-the-art approaches for the same task. We also show that PSP's improve GRISOTTO ability to retrieve motifs from mouse ChiP-seq data, indicating that the proposed algorithm can be applied to data from a different technology and for a higher eukaryote.

Conclusions

The conclusions of this work are twofold. First, post-processing the output of combinatorial algorithms by incorporating prior information leads to a very efficient and effective motif discovery method. Second, combining priors from different sources is even more beneficial than considering them separately.     

Speeding up the Consensus Clustering methodology for microarray data analysis

Background  

The inference of the number of clusters in a dataset, a fundamental problem in Statistics, Data Analysis and Classification, is usually addressed via internal validation measures. The stated problem is quite difficult, in particular for microarrays, since the inferred prediction must be sensible enough to capture the inherent biological structure in a dataset, e.g., functionally related genes. Despite the rich literature present in that area, the identification of an internal validation measure that is both fast and precise has proved to be elusive. In order to partially fill this gap, we propose a speed-up of Consensus (Consensus Clustering), a methodology whose purpose is the provision of a prediction of the number of clusters in a dataset, together with a dissimilarity matrix (the consensus matrix) that can be used by clustering algorithms. As detailed in the remainder of the paper, Consensus is a natural candidate for a speed-up.     

Speeding up the dynamic algorithm for planar RNA folding.

The simplest dynamic algorithm for planar RNA folding searches for the maximum number of base pairs. The algorithm uses O(n3) steps. The more general case, where different weights (energies) are assigned to stacked base pairs and to the various types of single-stranded region topologies, requires a considerably longer computation time because of the partial backtracking involved. Limiting the loop size reduces the running time back to O(n3). Reduction in the number of steps in the calculations of the various RNA topologies has recently been suggested, thereby improving the time behavior. Here we show how a "jumping" procedure can be used to speed up the computation, not only for the maximal number of base pairs algorithm, but for the minimal energy algorithm as well.     

Speeding up tandem mass spectrometry-based database searching by longest common prefix

Background  

Tandem mass spectrometry-based database searching has become an important technology for peptide and protein identification. One of the key challenges in database searching is the remarkable increase in computational demand, brought about by the expansion of protein databases, semi- or non-specific enzymatic digestion, post-translational modifications and other factors. Some software tools choose peptide indexing to accelerate processing. However, peptide indexing requires a large amount of time and space for construction, especially for the non-specific digestion. Additionally, it is not flexible to use.     

Characteristic reaction paths of biochemical reaction systems with time scale separation

A technique has been developed for characterizing the in vivo behavior of key enzymes from intermediate measurements. The technique is based on the identification of characteristic reaction paths, and it depends on the time scale separation characteristics of the systems. It is shown that useful information can be obtained from the phase plots of properly selected intermediate pairs or combinations which typically show process insensitive algebraic relations approached on time scales short compared to those of most practical interest. These characteristic reaction paths provide useful global measures of enzyme activity. The mathematical basis of reaction path analysis is investigated using linear transformation techniques. General theorems are developed predicting the existence of characteristic reaction paths as asymptotic limits whenever there is effective time scale separation. These limits are reached when fast reactions are relaxed, and available evidence suggests that these conditions will occur for the majority of reaction networks.     

Speeding up Monte Carlo molecular simulation by a non-conservative early rejection scheme

Monte Carlo (MC) molecular simulation describes fluid systems with rich information, and it is capable of predicting many fluid properties of engineering interest. In general, it is more accurate and representative than equations of state. On the other hand, it requires much more computational effort and simulation time. For that purpose, several techniques have been developed in order to speed up MC molecular simulations while preserving their precision. In particular, early rejection schemes are capable of reducing computational cost by reaching the rejection decision for the undesired MC trials at an earlier stage in comparison to the conventional scheme. In a recent work, we have introduced a ‘conservative’ early rejection scheme as a method to accelerate MC simulations while producing exactly the same results as the conventional algorithm. In this paper, we introduce a ‘non-conservative’ early rejection scheme, which is much faster than the conservative scheme, yet it preserves the precision of the method. The proposed scheme is tested for systems of structureless Lennard-Jones particles in both canonical and NVT-Gibbs ensembles. Numerical experiments were conducted at several thermodynamic conditions for different number of particles. Results show that at certain thermodynamic conditions, the non-conservative method is capable of doubling the speed of the MC molecular simulations in both canonical and NVT-Gibbs ensembles.