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.

On the generality of crowding: visual crowding in size, saturation, and hue compared to orientation.

Perception of peripherally viewed shapes is impaired when surrounded by similar shapes. This phenomenon is commonly referred to as "crowding". Although studied extensively for perception of characters (mainly letters) and, to a lesser extent, for orientation, little is known about whether and how crowding affects perception of other features. Nevertheless, current crowding models suggest that the effect should be rather general and thus not restricted to letters and orientation. Here, we report on a series of experiments investigating crowding in the following elementary feature dimensions: size, hue, and saturation. Crowding effects in these dimensions were benchmarked against those in the orientation domain. Our primary finding is that all features studied show clear signs of crowding. First, identification thresholds increase with decreasing mask spacing. Second, for all tested features, critical spacing appears to be roughly half the viewing eccentricity and independent of stimulus size, a property previously proposed as the hallmark of crowding. Interestingly, although critical spacings are highly comparable, crowding magnitude differs across features: Size crowding is almost as strong as orientation crowding, whereas the effect is much weaker for saturation and hue. We suggest that future theories and models of crowding should be able to accommodate these differences in crowding effects.

Hierarchical orientation of crystallinity by block-copolymer patterning and alignment in an electric field

Electron and hole conducting 10-nm-wide polymer morphologies hold great promise for organic electro-optical devices such as solar cells and light emitting diodes. The self-assembly of block-copolymers (BCPs) is often viewed as an efficient way to generate such materials. Here, a functional block copolymer that contains perylene bismide (PBI) side chains which can crystallize via π-π stacking to form an electron conducting microphase is patterned harnessing hierarchical electrohydrodynamic lithography (HEHL). HEHL film destabilization creates a hierarchical structure with three distinct length scales: (1) micrometer-sized polymer pillars, containing (2) a 10-nm BCP microphase morphology that is aligned perpendicular to the substrate surface and (3) on a molecular length scale (0.35-3 nm) PBI π-π-stacks traverse the HEHL-generated plugs in a continuous fashion. The good control over BCP and PBI alignment inside the generated vertical microstructures gives rise to liquid-crystal-like optical dichroism of the HEHL patterned films, and improves the electron conductivity across the film by 3 orders of magnitude. © 2013 American Chemical Society.

Controlled growth orientation of carbon nanotube pillars by catalyst patterning in microtrenches

We present a novel method for controlling the growth orientation of individual carbon nanotube (CNT) microstructures on a silicon wafer substrate. Our method controls the CNT forest orientation by patterning the catalyst layer used in the CNTs growth on slanted KOH edges. The overlap of catalyst area on the horizontal bottom and sloped sidewall surfaces of the KOH-etched substrate enables precise variation of the growth direction. These inclined structures can profit from the outstanding mechanical, electrical, thermal, and optical properties of CNTs and can therefore improve the performance of several MEMS devices. Inclined CNT microstructures could for instance be used as cantilever springs in probe card arrays, as tips in dip-pen lithography, and as sensing element in advanced transducers. ©2009 IEEE.

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.

Reversible nanoscale switching of polytwin orientation in a ferroelectric thin film induced by a local electric field

The response to a local, tip-induced electric field of ferroelastic domains in thin polycrystalline lead zirconate titanate films with predominantly (110) orientation has been studied using Enhanced Piezoresponse Force Microscopy. Two types of reversible polytwin switching between well-defined orientations have been observed. When a-c domains are switched to other forms of a-c domains, the ferroelastic domain walls rotate in-plane by 109.5°, and when a-c domains are switched to c-c domains (or vice-versa), the walls rotate by 54.75°. © 2013 AIP Publishing LLC.

A trichordal temporal approach to digital coordination: the sociomaterial mangling of the CERN grid

This paper develops a sociomaterial perspective on digital coordination. It extends Pickering’s mangle of practice by using a trichordal approach to temporal emergence. We provide new understanding as to how the nonhuman and human agencies involved in coordination are embedded in the past, present, and future. We draw on an in-depth field study conducted between 2006 and 2010 of the development, introduction, and use of a computing grid infrastructure by the CERN particle physics community. Three coordination tensions are identified at different temporal dimensions, namelyobtaining adequate transparency in the present, modeling a future infrastructure, and the historical disciplining of social and material inertias. We propose and develop the concept of digital coordination, and contribute a trichordal temporal approach to understanding the development and use of digital infrastructure as being orientated to the past and future while emerging in the present.

Does temporal discounting explain unhealthy behavior? A systematic review and reinforcement learning perspective.

The tendency to make unhealthy choices is hypothesized to be related to an individual's temporal discount rate, the theoretical rate at which they devalue delayed rewards. Furthermore, a particular form of temporal discounting, hyperbolic discounting, has been proposed to explain why unhealthy behavior can occur despite healthy intentions. We examine these two hypotheses in turn. We first systematically review studies which investigate whether discount rates can predict unhealthy behavior. These studies reveal that high discount rates for money (and in some instances food or drug rewards) are associated with several unhealthy behaviors and markers of health status, establishing discounting as a promising predictive measure. We secondly examine whether intention-incongruent unhealthy actions are consistent with hyperbolic discounting. We conclude that intention-incongruent actions are often triggered by environmental cues or changes in motivational state, whose effects are not parameterized by hyperbolic discounting. We propose a framework for understanding these state-based effects in terms of the interplay of two distinct reinforcement learning mechanisms: a "model-based" (or goal-directed) system and a "model-free" (or habitual) system. Under this framework, while discounting of delayed health may contribute to the initiation of unhealthy behavior, with repetition, many unhealthy behaviors become habitual; if health goals then change, habitual behavior can still arise in response to environmental cues. We propose that the burgeoning development of computational models of these processes will permit further identification of health decision-making phenotypes.

The effect of carbon nanotube orientation on erosive wear resistance of CNT-epoxy based composites

Aligned carbon nanotube (CNT) polymer composites are envisioned as the next-generation composite materials for a wide range of applications. In this work, we investigate the erosive wear behavior of epoxy matrix composites reinforced with both randomly dispersed and aligned carbon nanotube (CNT) arrays. The aligned CNT composites are prepared in two different configurations, where the sidewalls and ends of nanotubes are exposed to the composite surface. Results have shown that the composite with vertically aligned CNT-arrays exhibits superior erosive wear resistance compared to any of the other types of composites, and the erosion rate reaches a similar performance level to that of carbon steel at 20° impingement angle. The erosive wear mechanism of this type of composite, at various impingement angles, is studied by Scanning Electron Microscopy (SEM). We report that the erosive wear performance shows strong dependence on the alignment geometries of CNTs within the epoxy matrix under identical nanotube loading fractions. Correlations between the eroded surface roughness and the erosion rates of the CNT composites are studied by surface profilometry. This work demonstrates methods to fabricate CNT based polymer composites with high loading fractions of the filler, alignment control of nanotubes and optimized erosive wear properties. © 2014 Elsevier Ltd. All rights reserved.

Vulnerability assessment of buildings subject to tunnel-induced settlements: the influence of orientation and position of the building

The assessment of settlement induced damage on buildings during the preliminary phase of tunnel excavation projects, is nowadays receiving greater attention. Analyses at different levels of detail are performed on the surface building in proximity to the tunnel, to evaluate the risk of structural damage and the need of mitigation measures. In this paper, the possibility to define a correlation between the main parameters that influence the structural response to settlement and the potential damage is investigated through numerical analysis. The adopted 3D finite element model allows to take into account important features that are neglected in more simplified approaches, like the soil-structure interaction, the nonlinear behaviour of the building, the three dimensional effect of the tunnelling induced settlement trough and the influence of openings in the structure. Aim of this approach is the development of an improved classification system taking into account the intrinsic vulnerability of the structure, which could have a relevant effect on the final damage assessment. Parametric analyses are performed, focusing on the effect of the orientation and the position of the structure with respect to the tunnel. The obtained results in terms of damage are compared with the Building Risk Assessment (BRA) procedure. This method was developed by Geodata Engineering (GDE) on the basis of empirical observations and building monitoring and applied during the construction of different metro lines in urban environment. The comparison shows a substantial agreement between the two procedures on the influence of the analysed parameters. The finite element analyses suggest a refinement of the BRA procedure for pure sagging conditions.