When people make decisions they often face opposing demands for response speed and response accuracy, a process likely mediated by response thresholds. According to the striatal hypothesis, people decrease response thresholds by increasing activation from cortex to striatum, releasing the brain from inhibition. According to the STN hypothesis, people decrease response thresholds by decreasing activation from cortex to subthalamic nucleus (STN); a decrease in STN activity is likewise thought to release the brain from inhibition and result in responses that are fast but error-prone. To test these hypotheses-both of which may be true-we conducted two experiments on perceptual decision making in which we used cues to vary the demands for speed vs. accuracy. In both experiments, behavioral data and mathematical model analyses confirmed that instruction from the cue selectively affected the setting of response thresholds. In the first experiment we used ultra-high-resolution 7T structural MRI to locate the STN precisely. We then used 3T structural MRI and probabilistic tractography to quantify the connectivity between the relevant brain areas. The results showed that participants who flexibly change response thresholds (as quantified by the mathematical model) have strong structural connections between presupplementary motor area and striatum. This result was confirmed in an independent second experiment. In general, these findings show that individual differences in elementary cognitive tasks are partly driven by structural differences in brain connectivity. Specifically, these findings support a cortico-striatal control account of how the brain implements adaptive switches between cautious and risky behavior.basal ganglia | response time model | speed-accuracy tradeoff | structural connectivity | subthalamic nucleus F or many everyday life decisions, people and animals face the dilemma that fast decisions tend to be error-prone, whereas accurate decisions tend to be relatively slow. In other words, the temporal benefits of responding quickly come at a cost of increased error rates, a phenomenon known as the speed-accuracy tradeoff (SAT) (1-6).Even though the SAT is ubiquitous in many areas of decision making, relatively little is known about its neurobiological underpinnings. Currently available empirical data (2, 7, 8) and neurocomputational models both suggest several brain mechanisms that could be responsible for how people switch from cautious behavior that is accurate but slow to risky behavior that is fast but errorprone (1). The work presented here is relevant for two hypotheses about how the brain controls the SAT (Fig. 1). First, the striatal hypothesis posits that an emphasis on speed promotes excitatory input from cortex to striatum; the increased baseline activation of the striatum acts to decrease the inhibitory control that the output nuclei of the basal ganglia exert over the brain, thereby facilitating faster but possibly premature responses (2). Second, the STN hypothesis posits that an emphasis on ...

In this paper we explore the potential of multilevel models for meta-analysis of trials with binary outcomes for both summary data, such as log-odds ratios, and individual patient data. Conventional ÿxed e ect and random e ects models are put into a multilevel model framework, which provides maximum likelihood or restricted maximum likelihood estimation. To exemplify the methods, we use the results from 22 trials to prevent respiratory tract infections; we also make comparisons with a second example data set comprising fewer trials. Within summary data methods, conÿdence intervals for the overall treatment e ect and for the between-trial variance may be derived from likelihood based methods or a parametric bootstrap as well as from Wald methods; the bootstrap intervals are preferred because they relax the assumptions required by the other two methods. When modelling individual patient data, a bias corrected bootstrap may be used to provide unbiased estimation and correctly located conÿdence intervals; this method is particularly valuable for the between-trial variance. The trial e ects may be modelled as either ÿxed or random within individual data models, and we discuss the corresponding assumptions and implications. If random trial e ects are used, the covariance between these and the random treatment e ects should be included; the resulting model is equivalent to a bivariate approach to meta-analysis. Having implemented these techniques, the exibility of multilevel modelling may be exploited in facilitating extensions to standard meta-analysis methods.

FLOWERING LOCUS T2 (FT2) is expressed in the distal part of the developing wheat spike and contributes to the regulation of the number of spikelets per spike.

SUMMARYThe 'fruity' attributes of ripe apples (Malus 3 domestica) arise from our perception of a combination of volatile ester compounds. Phenotypic variability in ester production was investigated using a segregating population from a 'Royal Gala' (RG; high ester production) 3 'Granny Smith' (GS; low ester production) cross, as well as in transgenic RG plants in which expression of the alcohol acyl transferase 1 (AAT1) gene was reduced. In the RG 3 GS population, 46 quantitative trait loci (QTLs) for the production of esters and alcohols were identified on 15 linkage groups (LGs). The major QTL for 35 individual compounds was positioned on LG2 and co-located with AAT1. Multiple AAT1 gene variants were identified in RG and GS, but only two (AAT1-RGa and AAT1-GSa) were functional. AAT1-RGa and AAT1-GSa were both highly expressed in the cortex and skin of ripe fruit, but AAT1 protein was observed mainly in the skin. Transgenic RG specifically reduced in AAT1 expression showed reduced levels of most key esters in ripe fruit. Differences in the ripe fruit aroma could be perceived by sensory analysis. The transgenic lines also showed altered ratios of biosynthetic precursor alcohols and aldehydes, and expression of a number of ester biosynthetic genes increased, presumably in response to the increased substrate pool. These results indicate that the AAT1 locus is critical for the biosynthesis of esters contributing to a 'ripe apple' flavour.