Grain Boundary Wetting by a Second Solid Phase in the High Entropy Alloys: A Review.

In this review, the phenomenon of grain boundary (GB) wetting by the second solid phase is analyzed for the high entropy alloys (HEAs). Similar to the GB wetting by the liquid phase, the GB wetting by the second solid phase can be incomplete (partial) or complete. In the former case, the second solid phase forms in the GB of a matrix, the chain of (usually lenticular) precipitates with a certain non-zero contact angle.

Microstructure Formation in Cast TiZrHfCoNiCu and CoNiCuAlGaIn High Entropy Shape Memory Alloys: A Comparison.

The present study is dedicated to the microstructure characterization of the as-cast high entropy intermetallics that undergo a martensitic transformation, which is associated with the shape memory effect. It is shown that the TiZrHfCoNiCu system exhibits strong dendritic liquation, which leads to the formation of martensite crystals inside the dendrites. In contrast, in the CoNiCuAlGaIn system the dendritic liquation allows the martensite crystals to form only in interdendritic regions.

ASSET: Analysis of Sequences of Synchronous Events in Massively Parallel Spike Trains.

With the ability to observe the activity from large numbers of neurons simultaneously using modern recording technologies, the chance to identify sub-networks involved in coordinated processing increases. Sequences of synchronous spike events (SSEs) constitute one type of such coordinated spiking that propagates activity in a temporally precise manner. The synfire chain was proposed as one potential model for such network processing.

Specimen preparation by ion beam slope cutting for characterization of ductile damage by scanning electron microscopy.

To investigate ductile damage in parts made by cold sheet-bulk metal forming a suited specimen preparation is required to observe the microstructure and defects such as voids by electron microscopy. By means of ion beam slope cutting both a targeted material removal can be applied and mechanical or thermal influences during preparation avoided. In combination with scanning electron microscopy this method allows to examine voids in the submicron range and thus to analyze early stages of ductile damage.

An exploration of plastic deformation dependence of cell viability and adhesion in metallic implant materials.

The relationship between cell viability and adhesion behavior, and micro-deformation mechanisms was investigated on austenitic 316L stainless steel samples, which were subjected to different amounts of plastic strains (5%, 15%, 25%, 35% and 60%) to promote a variety in the slip and twin activities in the microstructure. Confocal laser scanning microscopy (CLSM) and field emission scanning electron microscopy (FESEM) revealed that cells most favored the samples with the largest plastic deformation, such that they spread more and formed significant filopodial extensions. Specifically, brain tumor cells seeded on the 35% deformed samples exhibited the best adhesion performance, where a significant slip activity was prevalent, accompanied by considerable slip-twin interactions.

Characterization of the Microstructure Evolution in IF-Steel and AA6016 during Plane-Strain Tension and Simple Shear.

In the current work, the evolutions of grain and dislocation microstructures are investigated on the basis of plane strain tension and simple shear tests for an interstitial free steel (DC06) and a 6000 series aluminum alloy (AA6016-T4). Both materials are commonly-used materials in the automobile industry. The focus of this contribution is on the characterization and comparison of the microstructure formation in DC06 and AA6016-T4.

Finding neural assemblies with frequent item set mining.

Cell assemblies, defined as groups of neurons exhibiting precise spike coordination, were proposed as a model of network processing in the cortex. Fortunately, in recent years considerable progress has been made in multi-electrode recordings, which enable recording massively parallel spike trains of hundred(s) of neurons simultaneously. However, due to the challenges inherent in multivariate approaches, most studies in favor of cortical cell assemblies still resorted to analyzing pairwise interactions.

Detecting synfire chains in parallel spike data.

The synfire chain model of brain organization has received much theoretical attention since its introduction (Abeles, 1982, 1991). However there has been no convincing experimental demonstration of synfire chains due partly to limitations of recording technology but also due to lack of appropriate analytic methods for large scale recordings of parallel spike trains. We have previously published one such method based on intersection of the neural populations active at two different times (Schrader et al.

Surrogate spike train generation through dithering in operational time.

Detecting the excess of spike synchrony and testing its significance can not be done analytically for many types of spike trains and relies on adequate surrogate methods. The main challenge for these methods is to conserve certain features of the spike trains, the two most important being the firing rate and the inter-spike interval statistics. In this study we make use of operational time to introduce generalizations to spike dithering and propose two novel surrogate methods which conserve both features with high accuracy.

Detecting synfire chain activity using massively parallel spike train recording.

The synfire chain model has been proposed as the substrate that underlies computational processes in the brain and has received extensive theoretical study. In this model cortical tissue is composed of a superposition of feedforward subnetworks (chains) each capable of transmitting packets of synchronized spikes with high reliability. Computations are then carried out by interactions of these chains.

Measurement of time-dependent changes in the irregularity of neural spiking.

Irregularity of firing in spike trains has been associated with coding processes and information transfer or alternatively treated as noise. Previous studies of irregularity have mainly used the coefficient of variation (CV) of the interspike interval distribution. Proper estimation of CV requires a constant underlying firing rate, a condition that most experimental situations do not fulfill either within or across trials.

Two enhancements of the gravity algorithm for multiple spike train analysis.

The gravity method for neuronal assembly analysis represents each neuron as a particle in N-space with a time varying charge that is a filtered version of the corresponding spike train, with appropriate rules for forces between and movements of the charged particles. Resulting trajectories reflect neuronal timing relationships. The usual short time constants in the filter restrict aggregation to highly synchronized neurons and reduce the sensitivity for delayed correlations; long time constants in the filter reduce selectivity.

Searching for significance in spatio-temporal firing patterns.

We examine a specific candidate for temporal coding of information by spike trains, the occurrence of a temporal firing pattern among some number of neurons that repeats more often than expected by chance. Methods for detection of repeating patterns have long been available, but there are no analytic methods for calculating the expected numbers of repeating patterns to enable assignment of significance to the results from the experimental data. The expected numbers can be calculated by Monte-Carlo methods by repeatedly modifying the original data spike trains.

Recordings, behaviour and models related to corticothalamic feedback.

In this paper, we review recent work on aspects of corticothalamic interactions in the auditory and in the visual systems. There are gross similarities in the arrangements of these systems, but considerable contrasts in the processing computations and in the effects of corticothalamic feedback.

A chronic multi-electrode microdrive for small animals.

We describe a simple microdrive device appropriate for chronic microelectrode recording in rats. No precision machining is required; all parts are stock or cut from standard stock material with hand tools and assembled with epoxy. The device together with its electrodes can be discarded at the completion of the experiment.

Signal-to-noise ratio improvement in multiple electrode recording.

Recordings of spike trains made with microwires or silicon electrodes include more noise from various sources that contaminate the observed spike shapes compared with recordings using sharp microelectrodes. This is a particularly serious problem if spike shape sorting is required to separate the several trains that might be observed on a particular electrode. However, if recordings are made with an array of such electrodes, there are several mathematical methods to improve the effective signal (spikes) to noise ratio, thus considerably reducing inaccuracy in spike detection and shape sorting.

Neural assemblies: technical issues, analysis, and modeling.

Neurons often work together to compute and process information, and neural assemblies arise from synaptic interactions and neural circuits. One way to study neural assemblies is to simultaneously record from several or many neurons and study the statistical relations among their spike trains. From this analysis researchers can try to understand the nature of the assemblies, which can also lead to attempts at modeling the underlying mechanisms.

Reorganization in awake rat auditory cortex by local microstimulation and its effect on frequency-discrimination behavior.

In common with other sensory cortices, the mammalian primary auditory cortex (AI) demonstrates the capacity for large-scale reorganization following many experimental situations. For example, training animals in frequency-discrimination tasks has been shown to result in an increase in cortical frequency representation. Such central changes-most commonly, an increase in central representation of specific stimulus parameters-have been hypothesized to underlie the improvements in perceptual acuity (perceptual learning) seen in many learning situations.

Daily variation and appetitive conditioning-induced plasticity of auditory cortex receptive fields.

Long-term modification of cortical receptive field maps follows learning of sensory discriminations and conditioned associations. In the process of determining whether appetitive - as opposed to aversive - conditioning is effective in causing such plastic changes, it was discovered that multineuron receptive fields, when measured in rats under ketamine-sedation, vary substantially over the course of a week, even in the absence of classical conditioning and electrode movement. Specifically, a simple correlation analysis showed that iso-intensity frequency response curves of multiunit clusters and local field potentials recorded from auditory cortex are nonstationary over 7 days.

Role of mammalian auditory cortex in the perception of elementary sound properties.

Studies in several mammalian species have demonstrated that bilateral ablations of the auditory cortex have little effect on simple sound intensity and frequency-based behaviors. In the rat, for example, early experiments have shown that auditory ablations result in virtually no effect on the rat's ability to either detect tones or discriminate frequencies. Such lesion experiments, however, typically examine an animal's performance some time after recovery from ablation surgery.

Determination of response latency and its application to normalization of cross-correlation measures.

It is often of interest experimentally to assess how synchronization between two neurons changes following a stimulus or other behaviorally relevant marker. The joint peristimulus time histogram (JPSTH) achieves this, but assumes that changes in the cells' firing rate following the stimulus are stereotyped from one sweep to the next. Erroneous results can be generated if this is not the case.

Improvements to the sensitivity of gravitational clustering for multiple neuron recordings.

We outline two improvements to the technique of gravitational clustering for detection of neuronal synchrony, which are capable of improving the method's detection of weak synchrony with limited data. The advantages of the enhancements are illustrated using data with known levels of synchrony and different interspike interval distributions. The novel simulation method described can easily generate such test data.

Cross-correlation measures of unresolved multi-neuron recordings.

An increasing number of laboratories are studying population properties of the nervous system using data where the spike activity of more than one neuron is recorded on each electrode and where, accidentally or deliberately, these activities are not resolved into single unit spike trains. We have previously examined the consequences for measurement of cross-correlation between two such electrodes in the limited case where all individual distant (between electrode) correlations are the same and all individual close (on a single electrode) correlations are the same [Bedenbaugh, P.H.

Oscillations and long-lasting correlations in a model of the lateral geniculate nucleus and visual cortex.

We have previously developed a model of the corticogeniculate system to explore cortically induced synchronization of lateral geniculate nucleus (LGN) neurons. Our model was based on the experiments of Sillito et al. Recently Brody discovered that the LGN events found by Sillito et al.

A feedback model of attention and context dependence in visual cortical networks.

We have modeled biologically realistic neural networks that may be involved in contextual modulation of stimulus responses, as reported in the neurophysiological experiments of Motter (1994a, 1994b) (Journal of Neuroscience, 14:2179-2189 and 2190-2199). The networks of our model are structured hierarchically with feedforward, feedback, and lateral connections, totaling several thousand cells and about 300,000 synapses. The contextual modulation, arising from attention cues, is explicitly modeled as a feedback signal coming from the highest-order cortical network.