Impurity and Trace Tritium Transport in Tokamak Edge Turbulence

The turbulent transport of impurity or minority species, as for example Tritium, is investigated in drift-Alfv\'en edge turbulence. The full effects of perpendicular and parallel convection are kept for the impurity species. The impurity density develops a granular structure with steep gradients and locally exceeds its initial values due to the compressibility of the flow. An approximate decomposition of the impurity flux into a diffusive part and an effective convective part (characterized by a pinch velocity) is performed and a net inward pinch effect is recovered. The pinch velocity is explained in terms of Turbulent Equipartition and is found to vary poloidally. The results show that impurity transport modeling needs to be two-dimensional, considering besides the radial direction also the strong poloidal variation in the transport coefficients.Comment: 12 Pages, 5 Figure

Working memory encoding delays top-down attention to visual cortex

The encoding of information from one event into working memory can delay high-level, central decision-making processes for subsequent events [e.g., Jolicoeur, P., & Dell'Acqua, R. The demonstration of short-term consolidation. Cognitive Psychology, 36, 138-202, 1998, doi:10.1006/cogp.1998.0684]. Working memory, however, is also believed to interfere with the deployment of top-down attention [de Fockert, J. W., Rees, G., Frith, C.D., &Lavie, N. The role ofworking memory in visual selective attention. Science, 291, 1803-1806, 2001, doi:10.1126/science.1056496]. It is, therefore, possible that, in addition to delaying central processes, the engagement of working memory encoding (WME) also postpones perceptual processing as well. Here, we tested this hypothesis with time-resolved fMRI by assessing whether WME serially postpones the action of top-down attention on low-level sensory signals. In three experiments, participants viewed a skeletal rapid serial visual presentation sequence that contained two target items (T1 and T2) separated by either a short (550 msec) or long (1450 msec) SOA. During single-target runs, participants attended and responded only to T1, whereas in dual-target runs, participants attended and responded to both targets. To determine whether T1 processing delayed top-down attentional enhancement of T2, we examined T2 BOLD response in visual cortex by subtracting the single-task waveforms from the dualtask waveforms for each SOA. When the WME demands of T1 were high (Experiments 1 and 3), T2 BOLD response was delayed at the short SOA relative to the long SOA. This was not the case when T1 encoding demands were low (Experiment 2). We conclude that encoding of a stimulus into working memory delays the deployment of attention to subsequent target representations in visual cortex

Characteristics of Feedback that Influence Student Confidence and Performance during Mathematical Modeling

This study focuses on characteristics of written feedback that influence students’ performance and confidence in addressing the mathematical complexity embedded in a Model-Eliciting Activity (MEA). MEAs are authentic mathematical modeling problems that facilitate students’ iterative development of solutions in a realistic context. We analyzed 132 first-year engineering students’ confidence levels and mathematical model scores on aMEA(pre and post feedback), along with teaching assistant feedback given to the students. The findings show several examples of affective and cognitive feedback that students reported that they used to revise their models. Students’ performance and confidence in developing mathematical models can be increased when they are in an environment where they iteratively develop models based on effective feedback

Improved multitasking following prefrontal tDCS

We have a limited capacity for mapping sensory information onto motor responses. This processing bottleneck is thought to be a key factor in determining our ability to make two decisions simultaneously - i.e., to multitask ( Pashler, 1984, 1994; Welford, 1952). Previous functional imaging research ( Dux, Ivanoff, Asplund, & Marois, 2006; Dux etal., 2009) has localised this bottleneck to the posterior lateral prefrontal cortex (pLPFC) of the left hemisphere. Currently, however, it is unknown whether this region is causally involved in multitasking performance. We investigated the role of the left pLPFC in multitasking using transcranial direct current stimulation (tDCS). The behavioural paradigm included single- and dual-task trials, each requiring a speeded discrimination of visual stimuli alone, auditory stimuli alone, or both visual and auditory stimuli. Reaction times for single- and dual-task trials were compared before, immediately after, and 20min after anodal stimulation (excitatory), cathodal stimulation (inhibitory), or sham stimulation. The cost of responding to the two tasks (i.e., the reduction in performance for dual- vs single-task trials) was significantly reduced by cathodal stimulation, but not by anodal or sham stimulation. Overall, the results provide direct evidence that the left pLPFC is a key neural locus of the central bottleneck that limits an individual's ability to make two simple decisions simultaneously

Distinct contributions of attention and working memory to visual statistical learning and ensemble processing

The brain exploits redundancies in the environment to efficiently represent the complexity of the visual world. One example of this is ensemble processing, which provides a statistical summary of elements within a set (e.g., mean size). Another is statistical learning, which involves the encoding of stable spatial or temporal relationships between objects. It has been suggested that ensemble processing over arrays of oriented lines disrupts statistical learning of structure within the arrays (Zhao, Ngo, McKendrick, & Turk-Browne, 2011). Here we asked whether ensemble processing and statistical learning are mutually incompatible, or whether this disruption might occur because ensemble processing encourages participants to process the stimulus arrays in a way that impedes statistical learning. In Experiment 1, we replicated Zhao and colleagues' finding that ensemble processing disrupts statistical learning. In Experiments 2 and 3, we found that statistical learning was unimpaired by ensemble processing when task demands necessitated (a) focal attention to individual items within the stimulus arrays and (b) the retention of individual items in working memory. Together, these results are consistent with an account suggesting that ensemble processing and statistical learning can operate over the same stimuli given appropriate stimulus processing demands during exposure to regularities

Applications of transcranial direct current stimulation for understanding brain function

In recent years there has been an exponential rise in the number of studies employing transcranial direct current stimulation (tDCS) as a means of gaining a systems-level understanding of the cortical substrates underlying behaviour. These advances have allowed inferences to be made regarding the neural operations that shape perception, cognition, and action. Here we summarise how tDCS works, and show how research using this technique is expanding our understanding of the neural basis of cognitive and motor training. We also explain how oscillatory tDCS can elucidate the role of fluctuations in neural activity, in both frequency and phase, in perception, learning, and memory. Finally, we highlight some key methodological issues for tDCS and suggest how these can be addressed

Cathodal electrical stimulation of frontoparietal cortex disrupts statistical learning of visual configural information

Attentional performance is facilitated by exploiting regularities and redundancies in the environment by way of incidental statistical learning. For example, during visual search, response times to a target are reduced by repeating distractor configurations-a phenomenon known as contextual cueing (Chun & Jiang, 1998). A range of neuroscientific methods have provided evidence that incidental statistical learning relies on subcortical neural structures associated with long-term memory, such as the hippocampus. Functional neuroimaging studies have also implicated the prefrontal cortex (PFC) and posterior parietal cortex (PPC) in contextual cueing. However, the extent to which these cortical regions are causally involved in statistical learning remains unclear. Here, we delivered anodal, cathodal, or sham transcranial direct current stimulation (tDCS) to the left PFC and left PPC online while participants performed a contextual cueing task. Cathodal stimulation of both PFC and PPC disrupted the early cuing effect, relative to sham and anodal stimulation. These findings causally implicate frontoparietal regions in incidental statistical learning that acts on visual configural information. We speculate that contextual cueing may rely on the availability of cognitive control resources in frontal and parietal regions

On the mutual effect of ion temperature gradient instabilities and impurity peaking in the reversed field pinch

The presence of impurities is considered in gyrokinetic calculations of ion temperature gradient (ITG) instabilities and turbulence in the reversed field pinch device RFX-mod. This device usually exhibits hollow Carbon/Oxygen profiles, peaked in the outer core region. We describe the role of the impurities in ITG mode destabilization, and analyze whether ITG turbulence is compatible with their experimental gradients.Comment: 19 pages, 9 figures, accepted for publication in Plasma Phys. Control. Fusio