Non-interfering effects of active post-encoding tasks on episodic memory consolidation in humans

So far, studies that investigated interference effects of post-learning processes on episodic memory consolidation in humans have used tasks involving only complex and meaningful information. Such tasks require reallocation of general or encoding-specific resources away from consolidation-relevant activities. The possibility that interference can be elicited using a task that heavily taxes our limited brain resources, but has low semantic and hippocampal related long-term memory processing demands, has never been tested. We address this question by investigating whether consolidation could persist in parallel with an active, encoding-irrelevant, minimally semantic task, regardless of its high resource demands for cognitive processing. We distinguish the impact of such a task on consolidation based on whether it engages resources that are: (1) general/executive, or (2) specific/overlapping with the encoding modality. Our experiments compared subsequent memory performance across two post-encoding consolidation periods: quiet wakeful rest and a cognitively demanding n-Back task. Across six different experiments (total N = 176), we carefully manipulated the design of the n-Back task to target general or specific resources engaged in the ongoing consolidation process. In contrast to previous studies that employed interference tasks involving conceptual stimuli and complex processing demands, we did not find any differences between n-Back and rest conditions on memory performance at delayed test, using both recall and recognition tests. Our results indicate that: (1) quiet, wakeful rest is not a necessary prerequisite for episodic memory consolidation; and (2) post-encoding cognitive engagement does not interfere with memory consolidation when task-performance has minimal semantic and hippocampally-based episodic memory processing demands. We discuss our findings with reference to resource and reactivation-led interference theorie

Brain areas involved in spatial working memory

Spatial working memory entails the ability to keep spatial information active in working memory over a short period of time. To study the areas of the brain that are involved in spatial working memory, a group of stroke patients was tested with a spatial search task. Patients and healthy controls were asked to search through a number of boxes shown at different locations on a touch-sensitive computer screen in order to find a target object. In subsequent trials, new target objects were hidden in boxes that were previously empty. Within-search errors were made if a participant returned to an already searched box; between-search errors occurred if a participant returned to a box that was already known to contain a target item. The use of a strategy to remember the locations of the target objects was calculated as well. Damage to the right posterior parietal and right dorsolateral prefrontal cortex impaired the ability to keep spatial information [`]on-line', as was indicated by performance on the Corsi Block-Tapping task and the within-search errors. Moreover, patients with damage to the right posterior parietal cortex, the right dorsolateral prefrontal cortex and the hippocampal formation bilaterally made more between-search errors, indicating the importance of these areas in maintaining spatial information in working memory over an extended time period.http://www.sciencedirect.com/science/article/B6T0D-4HM7WH2-2/1/b6b13c7b404377bae2b8cf632eb61fe

Advanced Photonics Congress

Abstract: We investigated the passivation of III-V semiconductor nanostructures using wet-chemical ammonium sulfide treatment and SiO x encapsulation. We achieved an ultra-low surface recombination velocity value of ~530 cm/s enabling the future development of high-performance room-temperature nanolasers

N, NH, and NH2 radical densities in a remote Ar-NH3-SiH4 plasma and their role in silicon nitride deposition

The densities of N, NH, and NH2 radicals in a remote Ar-NH3-SiH4 plasma used for high-rate silicon nitride deposition were investigated for different gas mixts. and plasma settings using cavity ringdown absorption spectroscopy and threshold ionization mass spectrometry. For typical deposition conditions, the N, NH, and NH2 radical densities are on the order of 1012 cm-3 and the trends with NH3 flow, SiH4 flow, and plasma source current are reported. We present a feasible reaction pathway for the prodn. and loss of the NHx radicals that is consistent with the exptl. results. Furthermore, mass spectrometry revealed that the consumption of NH3 was typically 40%, while it was over 80% for SiH4. On the basis of the measured N densities we deduced the recombination and sticking coeff. for N radicals on a silicon nitride film. Using this sticking coeff. and reported surface reaction probabilities of NH and NH2 radicals, we conclude that N and NH2 radicals are mainly responsible for the N incorporation in the silicon nitride film, while Si atoms are most likely brought to the surface in the form of SiHx radicals. [on SciFinder (R)

Reaction mechanisms during plasma-assisted atomic layer deposition of metal oxides: A case study for Al2O3

Plasma-assisted atomic layer deposition (ALD) of metal oxide films is increasingly gaining interest, however, the underlying reaction mechanisms have rarely been addressed. In this work, a case study is presented for the plasma-assisted ALD process of Al2O3 based on Al(CH3)3 dosing and O2 plasma exposure. A complementary set of time-resolved in situ diagnostics was employed, including spectroscopic ellipsometry, quartz crystal microbalance, mass spectrometry, and optical emission spectroscopy. The saturation of the Al(CH3)3 adsorption reactions was investigated, as well as the reaction products created during both the precursor dosing and the plasma exposure step. The generality of the observations was cross-checked on a second commercial ALD reactor. The main observations are as follows: (i) during the precursor dosing, the Al(CH3)3 predominantly binds bifunctionally to the surface at 70 °C through a reaction in which H is abstracted from the surface and CH4 is released into the gas phase; (ii) during the plasma exposure, O radicals in the plasma are consumed at the surface by combustionlike reactions with the surface -CH3 ligands, producing mainly H2O, CO2, and CO; (iii) small gas phase densities of CH4 and higher hydrocarbons (C2Hx) are also present during the O2 plasma exposure step indicating complementary surface reactions including a secondary thermal ALD-like reaction by the H2O produced at the surface; (iv) the plasma and its optical emission are strongly affected by the surface reaction products released in the plasma. In the latter respect, optical emission spectroscopy proved to be a valuable tool to study the surface reaction products during the plasma exposure as well as the saturation of the surface reactions. The implications of the experimental observations are addressed and it is discussed that the reaction mechanisms are generic for plasma-assisted ALD processes based on metal organic precursors and O2 plasma as oxidant source

Bayesian D-Optimal Choice Designs for Mixtures

__Abstract__ \n \nConsumer products and services can often be described as mixtures of ingredients. Examples are the mixture of ingredients in a cocktail and the mixture of different components of waiting time (e.g., in-vehicle and out-of-vehicle travel time) in a transportation setting. Choice experiments may help to determine how the respondents\' choice of a product or service is affected by the combination of ingredients. In such studies, individuals are confronted with sets of hypothetical products or services and they are asked to choose the most preferred product or service from each set. \n \nHowever, there are no studies on the optimal design of choice experiments involving mixtures. We propose a method for generating an optimal design for such choice experiments. To this end, we first introduce mixture models in the choice context and next present an algorithm to construct optimal experimental designs, assuming the multinomial logit model is used to analyze the choice data. To overcome the problem that the optimal designs depend on the unknown parameter values, we adopt a Bayesian D-optimal design approach. We also consider locally D-optimal designs and compare the performance of the resulting designs to those produced by a utility-neutral (UN) approach in which designs are based on the assumption that individuals are indifferent between all choice alternatives. We demonstrate that our designs are quite different and in general perform better than the UN designs