Experimental evidence of near-wall reverse flow events in a zero pressure gradient turbulent boundary layer

This study reports on experimentally observed rare near-wall reverse flow events in a fully developed turbulent flat plate boundary layer at zero pressure gradient with Reynolds numbers between Re_\theta \approx 2500 and Re_\theta \approx 8000 (Re_\tau = 800-2400). The reverse flow events are captured using high magnification particle image velocimetry sequences with record lengths varying from 50 000 to 126 000 samples. Time resolved particle image sequences allow singular reverse flow events to be followed over several time steps whereas long records of nearly statistically independent samples provide a variety of single snapshots at a higher spatial resolution. The probability of occurrence lies in the order of 0.012-0.018% which matches predictions from direct numerical simulations (DNS). The typical size of the reverse flow bubble is about 30 wall units in length and 5 wall units in height which agrees well with similar observations made in existing DNS data

Progressive modulation of resting-state brain activity during neurofeedback of positive-social emotion regulation networks

Neurofeedback allows for the self-regulation of brain circuits implicated in specific maladaptive behaviors, leading to persistent changes in brain activity and connectivity. Positive-social emotion regulation neurofeedback enhances emotion regulation capabilities, which is critical for reducing the severity of various psychiatric disorders. Training dorsomedial prefrontal cortex (dmPFC) to exert a top-down influence on bilateral amygdala during positive-social emotion regulation progressively (linearly) modulates connectivity within the trained network and induces positive mood. However, the processes during rest that interleave the neurofeedback training remain poorly understood. We hypothesized that short resting periods at the end of training sessions of positive-social emotion regulation neurofeedback would show alterations within emotion regulation and neurofeedback learning networks. We used complementary model-based and data-driven approaches to assess how resting-state connectivity relates to neurofeedback changes at the end of training sessions. In the experimental group, we found lower progressive dmPFC self-inhibition and an increase of connectivity in networks engaged in emotion regulation, neurofeedback learning, visuospatial processing, and memory. Our findings highlight a large-scale synergy between neurofeedback and resting-state brain activity and connectivity changes within the target network and beyond. This work contributes to our understanding of concomitant learning mechanisms post training and facilitates development of efficient neurofeedback training

The reference frame for encoding and retention of motion depends on stimulus set size

YesThe goal of this study was to investigate the reference frames used in perceptual encoding and storage of visual motion information. In our experiments, observers viewed multiple moving objects and reported the direction of motion of a randomly selected item. Using a vector-decomposition technique, we computed performance during smooth pursuit with respect to a spatiotopic (nonretinotopic) and to a retinotopic component and compared them with performance during fixation, which served as the baseline. For the stimulus encoding stage, which precedes memory, we found that the reference frame depends on the stimulus set size. For a single moving target, the spatiotopic reference frame had the most significant contribution with some additional contribution from the retinotopic reference frame. When the number of items increased (Set Sizes 3 to 7), the spatiotopic reference frame was able to account for the performance. Finally, when the number of items became larger than 7, the distinction between reference frames vanished. We interpret this finding as a switch to a more abstract nonmetric encoding of motion direction. We found that the retinotopic reference frame was not used in memory. Taken together with other studies, our results suggest that, whereas a retinotopic reference frame may be employed for controlling eye movements, perception and memory use primarily nonretinotopic reference frames. Furthermore, the use of nonretinotopic reference frames appears to be capacity limited. In the case of complex stimuli, the visual system may use perceptual grouping in order to simplify the complexity of stimuli or resort to a nonmetric abstract coding of motion information

Extensive characterization of a high Reynolds number decelerating boundary layer using advanced optical metrology

An experiment conducted in the framework of the EUHIT project and designed to characterize large scale structures in an adverse pressure gradient boundary layer flow is presented. Up to 16 sCMOS cameras were used in order to perform large scale turbulent boundary layer PIV measurements with a large field of view and appropriate spatial resolution. To access the span-wise / wall-normal signature of the structures as well, stereoscopic PIV measurements in span-wise/wall-normal planes were performed at specific stream-wise locations. To complement these large field of view measurements, long-range micro-PIV, time resolved near wall velocity profiles and film-based measurements were performed in order to determine the wall-shear stress and its fluctuations at some specific locations along the model.Comment: 50 page

Can we predict real-time fMRI neurofeedback learning success from pretraining brain activity?

Neurofeedback training has been shown to influence behavior in healthy participants as well as to alleviate clinical symptoms in neurological, psychosomatic, and psychiatric patient populations. However, many real-time fMRI neurofeedback studies report large inter-individual differences in learning success. The factors that cause this vast variability between participants remain unknown and their identification could enhance treatment success. Thus, here we employed a meta-analytic approach including data from 24 different neurofeedback studies with a total of 401 participants, including 140 patients, to determine whether levels of activity in target brain regions during pretraining functional localizer or no-feedback runs (i.e., self-regulation in the absence of neurofeedback) could predict neurofeedback learning success. We observed a slightly positive correlation between pretraining activity levels during a functional localizer run and neurofeedback learning success, but we were not able to identify common brain-based success predictors across our diverse cohort of studies. Therefore, advances need to be made in finding robust models and measures of general neurofeedback learning, and in increasing the current study database to allow for investigating further factors that might influence neurofeedback learning

Self-regulation of the dopaminergic reward circuit in cocaine users with mental imagery and neurofeedback

BACKGROUND: Enhanced drug-related reward sensitivity accompanied by impaired sensitivity to non-drug related rewards in the mesolimbic dopamine system are thought to underlie the broad motivational deficits and dysfunctional decision-making frequently observed in cocaine use disorder (CUD). Effective approaches to modify this imbalance and reinstate non-drug reward responsiveness are urgently needed. Here, we examined whether cocaine users (CU) can use mental imagery of non-drug rewards to self-regulate the ventral tegmental area and substantia nigra (VTA/SN). We expected that obsessive and compulsive thoughts about cocaine consumption would hamper the ability to self-regulate the VTA/SN activity and tested if real-time fMRI (rtfMRI) neurofeedback (NFB) can improve self-regulation of the VTA/SN. METHODS: Twenty-two CU and 28 healthy controls (HC) were asked to voluntarily up-regulate VTA/SN activity with non-drug reward imagery alone, or combined with rtfMRI NFB. RESULTS: On a group level, HC and CU were able to activate the dopaminergic midbrain and other reward regions with reward imagery. In CU, the individual ability to self-regulate the VTA/SN was reduced in those with more severe obsessive-compulsive drug use. NFB enhanced the effect of reward imagery but did not result in transfer effects at the end of the session. CONCLUSION: CU can voluntary activate their reward system with non-drug reward imagery and improve this ability with rtfMRI NFB. Combining mental imagery and rtFMRI NFB has great potential for modifying the maladapted reward sensitivity and reinstating non-drug reward responsiveness. This motivates further work to examine the use of rtfMRI NFB in the treatment of CUD

Multi-PIV Measurements of an Adverse Pressure Gradient Turbulent Boundary Layer

We report on a multi-national measurement campaign aimed at providing highly resolved flow field data of a turbulent boundary layer subjected to an adverse pressure gradient (APG). In the case of APGs the structure and dynamics of large scale turbulent flow structures along with their significance on the statistical properties of the flow is not well understood. Hence the fundamental aim was to resolve and characterise the large-scale coherent structures in an APG boundary layer flow. In addition to large-field-of-view PIV measurements using 16 sCMOS cameras along a 3.5m length, stereoscopic PIV measurements were performed at specific locations in order to also resolve the span-wise velocity statistics. Long-distance, high-speed micro-PIV measurements provided near wall statistics at selected locations including the time-resolved wall shear stress. The measurements were performed in the boundary layer wind tunnel of the Laboratoire de Mécanique de Lille (LML) and funded by EuHIT (www.euhit.org)

Adverse-Pressure-Gradient Effects on Turbulent Boundary Layers: Statistics and Flow-Field Organization

This manuscripts presents a study on adverse-pressure-gradient turbulent boundary layers under different Reynolds-number and pressure-gradient conditions. In this work we performed Particle Image Velocimetry (PIV) measurements supplemented with Large-Eddy Simulations in order to have a dataset covering a range of displacement-thickness-based Reynolds-number 2300 34000 and values of the Clauser pressure-gradient parameter beta up to 2.4. The spatial resolution limits of PIV for the estimation of turbulence statistics have been overcome via ensemble-based approaches. A comparison between ensemble-correlation and ensemble Particle Tracking Velocimetry was carried out to assess the uncertainty of the two methods. The effects of beta, R e and of the pressure-gradient history on turbulence statistics were assessed. A modal analysis via Proper Orthogonal Decomposition was carried out on the flow fields and showed that about 20% of the energy contribution corresponds to the first mode, while 40% of the turbulent kinetic energy corresponds to the first four modes with no appreciable dependence on beta and R e within the investigated range. The topology of the spatial modes shows a dependence on the Reynolds number and on the pressure-gradient strength, in line with the results obtained from the analysis of the turbulence statistics. The contribution of the modes to the Reynolds stresses and the turbulence production was assessed using a truncated low-order reconstruction with progressively larger number of modes. It is shown that the outer peaks in the Reynolds-stress profiles are mostly due to large-scale structures in the outer part of the boundary layer.CSV acknowledges the financial support from Universidad Carlos III de Madrid within the program “Ayudas para la Movilidad del Programa Propio de Investigación”. RÖ, RV and PS acknowledge the financial support from the Swedish Research Council (VR) and the Knut and Alice Wallenberg Foundation. CSV, SD and AI were partially supported by the COTURB project (Coherent Structures in Wall-bounded Turbulence), funded by the European Research Council (ERC), under grant ERC-2014.AdG-669505. CSV, SD and AI have been partially supported by Grant DPI2016-79401-R funded by the Spanish State Research Agency (SRA) and European Regional Development Fund (ERDF)