Intrasession and Intersession Reproducibility of Artificial Scotoma pRF Mapping Results at Ultra- High Fields

Published online September 6, 2022.Functional magnetic resonance imaging (fMRI) combined with population receptive field (pRF) mapping allows for associating positions on the visual cortex to areas on the visual field. Apart from applications in healthy subjects, this method can also be used to examine dysfunctions in patients suffering from partial visual field losses. While such objective measurement of visual deficits (scotoma) is of great importance for, e.g., longitudinal studies addressing treatment effects, it requires a thorough assessment of accuracy and reproducibility of the results obtained. In this study, we quantified the reproducibility of pRF mapping results within and across sessions in case of central visual field loss in a group of 15 human subjects. We simulated scotoma by masking a central area of 2° radius from stimulation to establish ground-truth conditions. This study was performed on a 7T ultra-high field MRI scanner for increased sensitivity. We found excellent intrasession and intersession reproducibility for the pRF center position (Spearman correlation coefficients for x, y: .0.95; eccentricity: .0.87; polar angle: .0.98), but only modest reproducibility for pRF size (Spearman correlation coefficients around 0.4). We further examined the scotoma detection performance using an automated method based on a reference dataset acquired with full-field stimulation. For the 2° artificial scotoma, the group-averaged scotoma sizes were estimated at between 1.92° and 2.19° for different sessions. We conclude that pRF mapping of visual field losses yields robust, reproducible measures of retinal function and suggest the use of pRF mapping as an objective method for monitoring visual deficits during therapeutic interventions or disease progression.Austrian Science Fund (FWF) P35583; P33180; KLI670 Eusko Jaurlaritza (Gobierno Vasco) BERC 2022-2025 Spanish State Research Agency CEX2020-001010-S Spanish Ministry of Science and Innovation IJC2020-042887-

Comparison of Stimulus Types for Retinotopic Cortical Mapping of Macular Disease

Published: March 13, 2023Purpose: Retinotopic maps acquired using functional magnetic resonance imaging (fMRI) provide a valuable adjunct in the assessment of macular function at the level of the visual cortex. The present study quantitatively assessed the performance of different visual stimulation approaches for mapping visual field coverage. Methods: Twelve patients with geographic atrophy (GA) secondary to age-related macular degeneration (AMD)were examined using high-resolution ultra-high field fMRI (Siemens Magnetom 7T) and microperimetry (MP; Nidek MP-3). The population receptive field (pRF)-based coverage maps obtained with two different stimulus techniques (moving bars, and rotating wedges and expanding rings) were compared with the results of MP. Correspondence between MP and pRF mapping was quantified by calculating the simple matching coefficient (SMC). Results: Stimulus choice is shown to bias the spatial distribution of pRF centers and eccentricity values with pRF sizes obtained fromwedge/ring or bar stimulation showing systematic differences. Wedge/ring stimulation results show a higher number of pRF centers in foveal areas and strongly reduced pRF sizes compared to bar stimulation runs. A statistical comparison shows significantly higher pRF center numbers in the foveal 2.5 degrees region of the visual field for wedge/ring compared to bar stimuli. However, these differences do not significantly influence SMC values when compared to MP (bar 2.5 degrees: 0.88±0.11;wedge/ring<2.5 degrees: 0.89 ± 0.12 wedge/ring; >2.5 degrees: 0.86 ± 0.10) for the peripheral visual field. Conclusions: Both visual stimulation designs examined can be applied successfully in patients with GA. Although the two designs show systematic differences in the distribution of pRF center locations, this variability has minimal impact on the SMC when compared to the MP outcome.Supported by the Austrian Science Fund (FWF); KLI 670-B3

Optical Recombination Lines of Heavy-elements in Giant Extragalactic HII Regions

We present high resolution observations of the giant extragalactic H II regions NGC 604, NGC 2363, NGC 5461 and NGC 5471, based on observations taken with the ISIS spectrograph on the William Herschel Telescope. We have detected -by the first time- C II and O II recombination lines in these objects. We find that recombination lines give larger C^{++} and O^{++} abundances than collisionallly excited lines, suggesting that temperature variations can be present in the objects. We detect [Fe IV] lines in NGC 2363 and NGC 5471, the most confident detection of optical lines of this kind in H II regions. Considering the temperature structure we derive their H, He, C, N, O, Ne, S, Ar, and Fe abundances. From the recombination lines of NGC 5461 and NGC 5471 we determine the presence of C/H and O/H gradients in M101. We calculate the Delta Y/Delta O and Delta Y/Delta Z values considering the presence of temperature variations and under the assumption of constant temperature. We obtain a better agreement with models of galactic chemical evolution by considering the presence of temperature variations than by assuming that the temperature is constant in these nebulae.Comment: 42 pages, 5 figures. To be published in Ap

Distinct neural processes are engaged in the modulation of mimicry by social group-membership and emotional expressions

International audiencePeople often spontaneously engage in copying each other's postures and mannerisms, a phenomenon referred to as behavioral mimicry. Social psychology experiments indicate that mimicry denotes an implicit affiliative signal flexibly regulated in response to social requirements. Yet, the mediating processes and neural underpinnings of such regulation are largely unexplored. The present functional magnetic resonance imaging (fMRI) study examined mimicry regulation by combining an automatic imitation task with facial stimuli, varied on two social-affective dimensions: emotional expression (angry vs happy) and ethnic group membership (in-vs out-group). Behavioral data revealed increased mimicry when happy and when out-group faces were shown. Imaging results revealed that mimicry regulation in response to happy faces was associated with increased activation in the right temporo-parietal junction (TPJ), right dorsal premotor cortex (dPMC), and right superior parietal lobule (SPL). Mimicry regulation in response to out-group faces was related to increased activation in the left ventral premotor cortex (vPMC) and inferior pa-rietal lobule (IPL), bilateral anterior insula, and mid-cingulate cortex (MCC). We suggest that mimicry in response to happy and to out-group faces is driven by distinct affiliative goals, and that mimicry regulation to attain these goals is mediated by distinct neuro-cognitive processes. Higher mimicry in response to happy faces seems to denote reciprocation of an affiliative signal. Higher mimicry in response to out-group faces, reflects an appeasement attempt towards an interaction partner perceived as threatening (an interpretation supported by implicit measures showing that out-group members are more strongly associated with threat). Our findings show that subtle social cues can result in the implicit regulation of mimicry. This regulation serves to achieve distinct affiliative goals, is mediated by different regulatory processes, and relies on distinct parts of an overarching network of task-related brain areas. Our findings shed new light on the neural mechanisms underlying the interplay between implicit action control and social cognition

Combining stimulus types for improved coverage in population receptive field mapping

Retinotopy experiments using population receptive field (pRF) mapping are ideal for assigning regions in the visual field to cortical brain areas. While various designs for visual stimulation were suggested in the literature, all have specific shortcomings regarding visual field coverage. Here we acquired high-resolution 7 Tesla fMRI data to compare pRF-based coverage maps obtained with the two most commonly used stimulus variants: moving bars; rotating wedges and expanding rings. We find that stimulus selection biases the spatial distribution of pRF centres. In addition, eccentricity values and pRF sizes obtained from wedge/ring or bar stimulation runs show systematic differences. Wedge/ring stimulation results show lower eccentricity values and strongly reduced pRF sizes compared to bar stimulation runs. Statistical comparison shows significantly higher pRF centre numbers in the foveal 2° region of the visual field for wedge/ring compared to bar stimuli. We suggest and evaluate approaches for combining pRF data from different visual stimulus patterns to obtain improved mapping results

Deep Learning for Fully Automated Radiographic Measurements of the Pelvis and Hip

The morphometry of the hip and pelvis can be evaluated in native radiographs. Artificial-intelligence-assisted analyses provide objective, accurate, and reproducible results. This study investigates the performance of an artificial intelligence (AI)-based software using deep learning algorithms to measure radiological parameters that identify femoroacetabular impingement and hip dysplasia. Sixty-two radiographs (124 hips) were manually evaluated by three observers and fully automated analyses were performed by an AI-driven software (HIPPO™, ImageBiopsy Lab, Vienna, Austria). We compared the performance of the three human readers with the HIPPO™ using a Bayesian mixed model. For this purpose, we used the absolute deviation from the median ratings of all readers and HIPPO™. Our results indicate a high probability that the AI-driven software ranks better than at least one manual reader for the majority of outcome measures. Hence, fully automated analyses could provide reproducible results and facilitate identifying radiographic signs of hip disorders

Deep Learning for Fully Automated Radiographic Measurements of the Pelvis and Hip

The morphometry of the hip and pelvis can be evaluated in native radiographs. Artificial-intelligence-assisted analyses provide objective, accurate, and reproducible results. This study investigates the performance of an artificial intelligence (AI)-based software using deep learning algorithms to measure radiological parameters that identify femoroacetabular impingement and hip dysplasia. Sixty-two radiographs (124 hips) were manually evaluated by three observers and fully automated analyses were performed by an AI-driven software (HIPPO&trade;, ImageBiopsy Lab, Vienna, Austria). We compared the performance of the three human readers with the HIPPO&trade; using a Bayesian mixed model. For this purpose, we used the absolute deviation from the median ratings of all readers and HIPPO&trade;. Our results indicate a high probability that the AI-driven software ranks better than at least one manual reader for the majority of outcome measures. Hence, fully automated analyses could provide reproducible results and facilitate identifying radiographic signs of hip disorders