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Decisive advances in the fields of nanosciences and nanotechnologies are intimately related to the development of new instruments and of related writing schemes and methodologies. Therefore we have recently proposed exploitation of the nano-structuring potential of a highly Focused Ion Beam as a tool, to overcome intrinsic limitations of current nano-fabrication techniques and to allow innovative patterning schemes urgently needed in many nanoscience challenges. In this work, we will first detail a very high resolution FIB instrument we have developed specifically to meet these nano-fabrication requirements. Then we will introduce and illustrate some advanced FIB processing schemes. These patterning schemes are (i) Ultra thin membranes as an ideal template for FIB nanoprocessing. (ii) Local defect injection for magnetic thin film direct patterning. (iii) Functionalization of graphite substrates to prepare 2D-organized arrays of clusters. (iv) FIB engineering of the optical properties of microcavities.
Reaction time (RT) variability is one of the strongest findings to emerge in cognitive-experimental research of attention deficit hyperactivity disorder (ADHD). We set out to confirm the association between ADHD and slow and variable RTs and investigate the degree to which RT performance improves under fast event rate and incentives. Using a group familial correlation approach, we tested the hypothesis that there are shared familial effects on RT performance and ADHD.
A total of 144 ADHD combined-type probands, 125 siblings of the ADHD probands and 60 control participants, ages 6–18, performed a four-choice RT task with baseline and fast-incentive conditions.
ADHD was associated with slow and variable RTs, and with greater improvement in speed and RT variability from baseline to fast-incentive condition. RT performance showed shared familial influences with ADHD. Under the assumption that the familial effects represent genetic influences, the proportion of the phenotypic correlation due to shared familial influences was estimated as 60–70%.
The data are inconsistent with models that consider RT variability as reflecting a stable cognitive deficit in ADHD, but instead emphasize the extent to which energetic or motivational factors can have a greater effect on RT performance in ADHD. The findings support the role of RT variability as an endophenotype mediating the link between genes and ADHD.
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