Internal representations of temporal statistics and feedback calibrate motor-sensory interval timing.

Humans have been shown to adapt to the temporal statistics of timing tasks so as to optimize the accuracy of their responses, in agreement with the predictions of Bayesian integration. This suggests that they build an internal representation of both the experimentally imposed distribution of time intervals (the prior) and of the error (the loss function). The responses of a Bayesian ideal observer depend crucially on these internal representations, which have only been previously studied for simple distributions. To study the nature of these representations we asked subjects to reproduce time intervals drawn from underlying temporal distributions of varying complexity, from uniform to highly skewed or bimodal while also varying the error mapping that determined the performance feedback. Interval reproduction times were affected by both the distribution and feedback, in good agreement with a performance-optimizing Bayesian observer and actor model. Bayesian model comparison highlighted that subjects were integrating the provided feedback and represented the experimental distribution with a smoothed approximation. A nonparametric reconstruction of the subjective priors from the data shows that they are generally in agreement with the true distributions up to third-order moments, but with systematically heavier tails. In particular, higher-order statistical features (kurtosis, multimodality) seem much harder to acquire. Our findings suggest that humans have only minor constraints on learning lower-order statistical properties of unimodal (including peaked and skewed) distributions of time intervals under the guidance of corrective feedback, and that their behavior is well explained by Bayesian decision theory.

High-precision digital lock-in measurements of critical current and AC loss in HTS 2G-Tapes

Application of High Temperature Superconducting (HTS) has been increasingly popular since the new superconducting materials were discovered. This paper presents a new high-precision digital lock-in measurement technique which is used for measuring critical current and AC loss of the 2nd Generation HTS tape. Using a lock-in amplifier and nano-voltage meter, we can resolve signals at nano-volt level, while using a specially designed compensation coil we can cancel out inductive by adjusting the coil inductance. Furthermore, a finer correction for the inductive component can be achieved by adjusting the reference phase of the lock-in amplifier. The critical current and AC loss measurement algorithms and hardware layout are described and analyzed, and results for both numerical and experimental data under varieties of frequencies are presented. © 2008 SICE.

Probabilistic computation in human perception under variability in encoding precision.

A key function of the brain is to interpret noisy sensory information. To do so optimally, observers must, in many tasks, take into account knowledge of the precision with which stimuli are encoded. In an orientation change detection task, we find that encoding precision does not only depend on an experimentally controlled reliability parameter (shape), but also exhibits additional variability. In spite of variability in precision, human subjects seem to take into account precision near-optimally on a trial-to-trial and item-to-item basis. Our results offer a new conceptualization of the encoding of sensory information and highlight the brain's remarkable ability to incorporate knowledge of uncertainty during complex perceptual decision-making.

Variability in encoding precision accounts for visual short-term memory limitations.

It is commonly believed that visual short-term memory (VSTM) consists of a fixed number of "slots" in which items can be stored. An alternative theory in which memory resource is a continuous quantity distributed over all items seems to be refuted by the appearance of guessing in human responses. Here, we introduce a model in which resource is not only continuous but also variable across items and trials, causing random fluctuations in encoding precision. We tested this model against previous models using two VSTM paradigms and two feature dimensions. Our model accurately accounts for all aspects of the data, including apparent guessing, and outperforms slot models in formal model comparison. At the neural level, variability in precision might correspond to variability in neural population gain and doubly stochastic stimulus representation. Our results suggest that VSTM resource is continuous and variable rather than discrete and fixed and might explain why subjective experience of VSTM is not all or none.

Does precision decrease with set size?

The brain encodes visual information with limited precision. Contradictory evidence exists as to whether the precision with which an item is encoded depends on the number of stimuli in a display (set size). Some studies have found evidence that precision decreases with set size, but others have reported constant precision. These groups of studies differed in two ways. The studies that reported a decrease used displays with heterogeneous stimuli and tasks with a short-term memory component, while the ones that reported constancy used homogeneous stimuli and tasks that did not require short-term memory. To disentangle the effects of heterogeneity and short-memory involvement, we conducted two main experiments. In Experiment 1, stimuli were heterogeneous, and we compared a condition in which target identity was revealed before the stimulus display with one in which it was revealed afterward. In Experiment 2, target identity was fixed, and we compared heterogeneous and homogeneous distractor conditions. In both experiments, we compared an optimal-observer model in which precision is constant with set size with one in which it depends on set size. We found that precision decreases with set size when the distractors are heterogeneous, regardless of whether short-term memory is involved, but not when it is homogeneous. This suggests that heterogeneity, not short-term memory, is the critical factor. In addition, we found that precision exhibits variability across items and trials, which may partly be caused by attentional fluctuations.

Independence is elusive: set size effects on encoding precision in visual search.

Looking for a target in a visual scene becomes more difficult as the number of stimuli increases. In a signal detection theory view, this is due to the cumulative effect of noise in the encoding of the distractors, and potentially on top of that, to an increase of the noise (i.e., a decrease of precision) per stimulus with set size, reflecting divided attention. It has long been argued that human visual search behavior can be accounted for by the first factor alone. While such an account seems to be adequate for search tasks in which all distractors have the same, known feature value (i.e., are maximally predictable), we recently found a clear effect of set size on encoding precision when distractors are drawn from a uniform distribution (i.e., when they are maximally unpredictable). Here we interpolate between these two extreme cases to examine which of both conclusions holds more generally as distractor statistics are varied. In one experiment, we vary the level of distractor heterogeneity; in another we dissociate distractor homogeneity from predictability. In all conditions in both experiments, we found a strong decrease of precision with increasing set size, suggesting that precision being independent of set size is the exception rather than the rule.

Temporal difference models describe higher-order learning in humans.

The ability to use environmental stimuli to predict impending harm is critical for survival. Such predictions should be available as early as they are reliable. In pavlovian conditioning, chains of successively earlier predictors are studied in terms of higher-order relationships, and have inspired computational theories such as temporal difference learning. However, there is at present no adequate neurobiological account of how this learning occurs. Here, in a functional magnetic resonance imaging (fMRI) study of higher-order aversive conditioning, we describe a key computational strategy that humans use to learn predictions about pain. We show that neural activity in the ventral striatum and the anterior insula displays a marked correspondence to the signals for sequential learning predicted by temporal difference models. This result reveals a flexible aversive learning process ideally suited to the changing and uncertain nature of real-world environments. Taken with existing data on reward learning, our results suggest a critical role for the ventral striatum in integrating complex appetitive and aversive predictions to coordinate behaviour.

The temporal evolution of feedback gains rapidly update to task demands.

Recent theoretical frameworks such as optimal feedback control suggest that feedback gains should modulate throughout a movement and be tuned to task demands. Here we measured the visuomotor feedback gain throughout the course of movements made to "near" or "far" targets in human subjects. The visuomotor gain showed a systematic modulation over the time course of the reach, with the gain peaking at the middle of the movement and dropping rapidly as the target is approached. This modulation depends primarily on the proportion of the movement remaining, rather than hand position, suggesting that the modulation is sensitive to task demands. Model-predictive control suggests that the gains should be continuously recomputed throughout a movement. To test this, we investigated whether feedback gains update when the task goal is altered during a movement, that is when the target of the reach jumped. We measured the visuomotor gain either simultaneously with the jump or 100 ms after the jump. The visuomotor gain nonspecifically reduced for all target jumps when measured synchronously with the jump. However, the visuomotor gain 100 ms later showed an appropriate modulation for the revised task goal by increasing for jumps that increased the distance to the target and reducing for jumps that decreased the distance. We conclude that visuomotor feedback gain shows a temporal evolution related to task demands and that this evolution can be flexibly recomputed within 100 ms to accommodate online modifications to task goals.

Temporal Coherence of Chlorophyll a during a Spring Phytoplankton Bloom in Xiangxi Bay of Three-Gorges Reservoir, China

Algal bloom phenomenon was defined as "the rapid growth of one or more phytoplankton species which leads to a rapid increase in the biomass of phytoplankton", yet most estimates of temporal coherence are based on yearly or monthly sampling frequencies and little is known of how synchrony varies among phytoplankton or of the causes of temporal coherence during spring algal bloom. In this study, data of chlorophyll a and related environmental parameters were weekly gathered at 15 sampling sites in Xiangxi Bay of Three-Gorges Reservoir (TGR, China) to evaluate patterns of temporal coherence for phytoplankton during spring bloom and test if spatial heterogeneity of nutrient and inorganic suspended particles within a single ecosystem influences synchrony of spring phytoplankton dynamics. There is a clear spatial and temporal variation in chlorophyll a across Xiangxi Bay. The degree of temporal coherence for chlorophyll a between pairs of sites located in Xiangxi Bay ranged from -0.367 to 0.952 with mean and median values of 0.349 and 0.321, respectively. Low levels of temporal coherence were often detected among the three stretches of the bay (Down reach, middle reach and upper reach), while high levels of temporal coherence were often found within the same reach of the bay. The relative difference of DIN between pair sites was the strong predictor of temporal coherence for chlorophyll a in down and middle reach of the bay, while the relative difference in Anorganic Suspended Solids was the important factor regulating temporal coherence in middle and upper reach. Contrary to many studies, these results illustrate that, in a small geographic area (a single reservoir bay of approximately 25 km), spatial heterogeneity influence synchrony of phytoplankton dynamics during spring bloom and local processes may override the effects of regional processes or dispersal.

Temporal and Spatial Distributions of Rotifers in Xiangxi Bay of the Three Gorges Reservoir, China

From July 2003 to June 2005, investigations of rotifer temporal and spatial distributions were carried out in a bay of the Three Gorges Reservoir, Xiangxi Bay, which is the downstream segment of the Xiangxi River and the nearest bay to the Three Gorges Reservoir dam in Hubei Province, China. Thirteen sampling sites were selected. The results revealed a high species diversity, with 76 species, and 14 dominant species; i.e., Polyarthra vulgaris, Keratella cochlearis, Keratella valga, Synchaeta tremula, Synchaeta stylata, Trichocerca lophoessa, Trichocerca pusilla, Brachionus angularis, Brachionus calyciflorus, Brachionus forficula forficula, Ascomorpha ovalis, Conochilus unicornis, Ploesoma truncatum and Anuraeopsis fissa. After the first year of the reservoir impoundment, the rotifer community was dominated by ten species; one year later it was dominated by eight species. The community in 2003/2004 was dissimilar to that in 2004/2005, which resulted from the succession of the dominant species. The rotifer community exhibited a patchy distribution, with significant heterogeneity observed along the longitudinal axis. All rotifer communities could be divided into three groups, corresponding to the riverine, the transition and the lacustrine zone, respectively.

Precision transfer printing of ultra-thin AlInGaN micron-size light-emitting diodes

We report the fabrication of a mechanically-flexible 16×16 array of thin-film, micron-size LEDs emitting at 480 nm. Devices were transfer-printed onto a mechanically-flexible ITO backplane using a modified, high-precision (placement accuracy ±25 nm) assembly system. © 2013 IEEE.

Switch mode constant current LED Driver with high efficiency, high precision and wide dimming ratio

A high efficiency hard switching constant current LED driver is presented with high overall efficiency, high current precision, high LED efficacy, flicker-free and wide constant current dimming ratio. The high stable lighting source provides the best solution for office light, reading light and LCD backlight. © 2013 IEEE.

Hydroacoustic study of spatial and temporal distribution of Gymnocypris przewalskii (Kessler, 1876) in Qinghai Lake, China

Gymnocypris przewalskii (Kessler 1876) is an endangered and state-protected rare fish species in Qinghai Lake, China. To further understand the life history and distribution of this fish, five surveys were carried out in Qinghai Lake between 2002-2006. Results of these surveys indicate that fishes were predominantly distributed about 2 m under the surface. In July, significant differences in fish density were found between surface and bottom layers (P = 0.001), and/or between middle and bottom layers (P = 0.025). Fish density was the greatest in the surface layer. In August and October, no significant differences were found between the different layers, but the bottom layer had a greater fish density. Furthermore, there were very large differences among different zones in fish distribution density. Differences in horizontal distribution were not significantly correlated to factors such as water depth and inshore distance, possibly because of very low and uniform fish density. Feeding, changes in water temperature, over-wintering and spawning appeared to influence fish distribution. Hydroacoustic estimates of G. przewalskii biomass in Qinghai Lake increased significantly between 2002 and 2006. We attribute this increase to the management measures put in place to protect this species.

Spatial and temporal variations of microcystins in hepatopancreas of a freshwater snail from Lake Taihu

In this paper, spatial and temporal variations of three common microcystins (MC-RR, MC-YR, and MC-LR) in the hepatopancreas of a freshwater snail (Bellamya aeruginosa) were studied monthly in two bays of Lake Taihu. Microcystins (MCs) concentration in hepatopancreas was quantified by liquid chromatography-mass spectrometry (LC-MS). The MCs concentrations in hepatopancreas were higher at Site 1 than those at other sites, which was in agreement with the changes of intracellular MCs concentrations in the water column. There was a significant correlation between MCs concentrations in the hepatopancreas and that in the seston, suggesting that spatial variances of MCs; concentrations in hepatopancreas among the five sites were due to spatial changes of toxic Microcystis cells in the water column. PCCA indicates that in addition to Microcystis, other factors (e.g., water temperature) also substantially affected the accumulation of MCs in hepatopancreas of the snail. (C) 2008 Published by Elsevier Inc.