Modeling of multisensory convergence with a network of spiking neurons: a reverse engineering approach

Multisensory processing in the brain underlies a wide variety of perceptual phenomena, but little is known about the underlying mechanisms of how multisensory neurons are formed. This lack of knowledge is due to the difficulty for biological experiments to manipulate and test the parameters of multisensory convergence, the first and definitive step in the multisensory process. Therefore, by using a computational model of multisensory convergence, this study seeks to provide insight into the mechanisms of multisensory convergence. To reverse-engineer multisensory convergence, we used a biologically realistic neuron model and a biology-inspired plasticity rule, but did not make any a priori assumptions about multisensory properties of neurons in the network. The network consisted of two separate projection areas that converged upon neurons in a third area, and stimulation involved activation of one of the projection areas (or the other) or their combination. Experiments consisted of two parts: network training and multisensory simulation. Analyses were performed, first, to find multisensory properties in the simulated networks; second, to reveal properties of the network using graph theoretical approach; and third, to generate hypothesis related to the multisensory convergence. The results showed that the generation of multisensory neurons related to the topological properties of the network, in particular, the strengths of connections after training, was found to play an important role in forming and thus distinguishing multisensory neuron types.     

Effect of Yttrium Additions in Relation to Oxygen Content on Glass Formation in the Zr50Cu40Al10 Alloy

Metallurgical and Materials Transactions A - The effect of yttrium additions on the glass formation of the Zr50Cu40Al10 alloy with high oxygen content was investigated. Unlike other reports showing...     

A Bayesian approach for dealing with uncertainties in detection ofcoronary artery stenosis using a knowledge-based system

A knowledge-based system that combines subjective Bayesian methods with rules specified by cardiologists to diagnose coronary artery stenosis from postexercise myocardial perfusion scintigrams is discussed. This expert system was used to determine which of the three main coronary arteries had the dominant stenosis. The system also indicated when a patient had a normal myocardial perfusion pattern (no stenosis). The system was run on a set of scans from 91 patients, and the results were compared with an existing expert system that uses the Dempster-Shafer theory of evidence for dealing with uncertainties. The system was able to determine the coronary artery with the dominant stenosis over 90% of the time when supplied with prior knowledge that all the patients have single-vessel stenosis. The system was also able to determine with good accuracy whether a patient had a stenosed coronary artery or normal myocardial perfusion when no prior information was available. The program can be used initially to screen out patients with normal scintigrams. Once the patients with normal scintigrams have been removed, the expert system can then be run on the remaining patients and utilize prior knowledge that they have stenosed coronary arteries. This improves the reliability of the diagnosis.     

Simultaneous quantification of human cardiac alpha- and beta-myosin heavy chain proteins by MALDI-TOF mass spectrometry

We have developed a novel method for quantifying protein isoforms, in both relative and absolute terms, based on MALDI-TOF mass spectrometry. The utility of the approach is demonstrated by quantifying the alpha and beta protein isoforms of myosin heavy chain (MyHC) in human atrial tissue. Alpha-MyHC (726-741) and beta-MyHC (724-739) were identified as isoform-specific tryptic peptides. A calibration curve was constructed by plotting ion current ratios against molar ratios of the two peptides prepared synthetically. MyHC was digested by trypsin and the ion current ratio determined for the two tryptic peptides. The ion current ratio was converted to the peptide ratio and hence the isoform ratio by reference to the standard curve. The accuracy of the method was confirmed by a comparison between these results and those determined by an established method of MyHC isoform ratio determination. So that the molar ratio could be converted to absolute values, a third peptide, an analogue of the two peptides being measured, was synthesized for use as an internal standard (IS). The measured ion current ratios of synthetic alpha-MyHC (726-741), beta-MyHC (724-739), and IS peptides were used to generate standard curves. A known quantity of the IS was added to the MyHC digests. The measured ion current ratios were converted to the actual quantities of the isoform-specific peptides and hence the actual quantity of each protein isoform by reference to the standard curves. This method is of general applicability, especially when isoform quantification is required.     

Unusual Solidification Behavior of the Suction-Cast Cu-Zr-Al-Y Alloy Doped with Fe

The effect of iron addition on the microstructure of the Cu-Zr-Al-Y glass-forming alloy was studied. Despite a high superficial cooling rate, small Fe additions (1.5 and 3 pct) induced formation of crystalline CuZr and AlCu₂Zr phases on the outer layers of suction-cast rods. As the melt composition near the solid/liquid interface was depleted in Fe, the remaining melt vitrified at a relatively low cooling rate.     

A machine learning method for generation of a neural networkarchitecture: a continuous ID3 algorithm

The relation between the decision trees generated by a machine learning algorithm and the hidden layers of a neural network is described. A continuous ID3 algorithm is proposed that converts decision trees into hidden layers. The algorithm allows self-generation of a feedforward neural network architecture. In addition, it allows interpretation of the knowledge embedded in the generated connections and weights. A fast simulated annealing strategy, known as Cauchy training, is incorporated into the algorithm to escape from local minima. The performance of the algorithm is analyzed on spiral data.     

Using fuzzy sets to diagnose coronary artery stenosis

The use of fuzzy sets to represent perfusion defects and to generate expert results to help in diagnosis is reported. Retrospective data collected from 91 patients who underwent both stress thallium-201 myocardial scintigraphy and coronary arteriography were used. Of the total, 64 scans were chosen at random for training, and the remaining 27 scans were used for testing data. It was found that 17 rules generated by fuzzy set theory performed as well as 68 rules specified by cardiologists in diagnosing coronary artery stenosis     

Effects of 445 nm, 520 nm,and 638 nm Laser Irradiation on the Dermal Cells

Background: The invention of non-ionizing emission devices revolutionized science, medicine, industry, and the military. Currently, different laser systems are commonly used, generating the potential threat of excessive radiation exposure, which can lead to adverse health effects. Skin is the organ most exposed to laser irradiation; therefore, this study aims to evaluate the effects of 445 nm, 520 nm, and 638 nm non-ionizing irradiation on keratinocytes and fibroblasts. Methods: Keratinocytes and fibroblasts were exposed to a different fluency of 445 nm, 520 nm, and 638 nm laser irradiation. In addition, viability, type of cell death, cell cycle distribution, and proliferation rates were investigated. Results: The 445 nm irradiation was cytotoxic to BJ-5ta (≥58.7 J/cm²) but not to Ker-CT cells. Exposure influenced the cell cycle distribution of Ker-CT (≥61.2 J/cm²) and BJ-5ta (≥27.6 J/cm²) cells, as well as the Bj-5ta proliferation rate (≥50.5 J/cm²). The 520 nm irradiation was cytotoxic to BJ-5ta (≥468.4 J/cm²) and Ker-CT (≥385.7 J/cm²) cells. Cell cycle distribution (≥27.6 J/cm²) of Ker-CT cells was also affected. The 638 nm irradiation was cytotoxic to BJ-5ta and Ker-CT cells (≥151.5 J/cm²). The proliferation rate and cell cycle distribution of BJ-5ta (≥192.9 J/cm²) and Ker-CT (13.8 and 41.3 J/cm²) cells were also affected. Conclusions: At high fluences, 455 nm, 520 nm, and 638 nm irradiation, representing blue, green, and red light spectra, are hazardous to keratinocytes and fibroblasts. However, laser irradiation may benefit the cells at low fluences by modulating the cell cycle and proliferation rate.