Absence of direction-specific cross-modal visual–auditory adaptation in motion-onset event-related potentials

Adaptation to visual or auditory motion affects within-modality motion processing as reflected by visual or auditory free-field motion-onset evoked potentials (VEPs, AEPs). Here, a visual–auditory motion adaptation paradigm was used to investigate the effect of visual motion adaptation on VEPs and AEPs to leftward motion-onset test stimuli. Effects of visual adaptation to (i) scattered light flashes, and motion in the (ii) same or in the (iii) opposite direction of the test stimulus were compared. For the motion-onset VEPs, i.e. the intra-modal adaptation conditions, direction-specific adaptation was observed – the change-N2 (cN2) and change-P2 (cP2) amplitudes were significantly smaller after motion adaptation in the same than in the opposite direction. For the motion-onset AEPs, i.e. the cross-modal adaptation condition, there was an effect of motion history only in the change-P1 (cP1), and this effect was not direction-specific – cP1 was smaller after scatter than after motion adaptation to either direction. No effects were found for later components of motion-onset AEPs. While the VEP results provided clear evidence for the existence of a direction-specific effect of motion adaptation within the visual modality, the AEP findings suggested merely a motion-related, but not a direction-specific effect. In conclusion, the adaptation of veridical auditory motion detectors by visual motion is not reflected by the AEPs of the present study

Interaction of perceptual grouping and crossmodal temporal capture in tactile apparent-motion

Previous studies have shown that in tasks requiring participants to report the direction of apparent motion, task-irrelevant mono-beeps can "capture'' visual motion perception when the beeps occur temporally close to the visual stimuli. However, the contributions of the relative timing of multimodal events and the event structure, modulating uni- and/or crossmodal perceptual grouping, remain unclear. To examine this question and extend the investigation to the tactile modality, the current experiments presented tactile two-tap apparent-motion streams, with an SOA of 400 ms between successive, left-/right-hand middle-finger taps, accompanied by task-irrelevant, non-spatial auditory stimuli. The streams were shown for 90 seconds, and participants' task was to continuously report the perceived (left-or rightward) direction of tactile motion. In Experiment 1, each tactile stimulus was paired with an auditory beep, though odd-numbered taps were paired with an asynchronous beep, with audiotactile SOAs ranging from -75 ms to 75 ms. Perceived direction of tactile motion varied systematically with audiotactile SOA, indicative of a temporal-capture effect. In Experiment 2, two audiotactile SOAs-one short (75 ms), one long (325 ms)-were compared. The long-SOA condition preserved the crossmodal event structure (so the temporal-capture dynamics should have been similar to that in Experiment 1), but both beeps now occurred temporally close to the taps on one side (even-numbered taps). The two SOAs were found to produce opposite modulations of apparent motion, indicative of an influence of crossmodal grouping. In Experiment 3, only odd-numbered, but not even-numbered, taps were paired with auditory beeps. This abolished the temporal-capture effect and, instead, a dominant percept of apparent motion from the audiotactile side to the tactile-only side was observed independently of the SOA variation. These findings suggest that asymmetric crossmodal grouping leads to an attentional modulation of apparent motion, which inhibits crossmodal temporal-capture effects

Target Capital Structure Determinants and Speed of Adjustment Analysis to Address the Keynes-Hayek Debate

According to F. A. Hayek, Keynes' General Theory neglects an analysis of the production structure. As a contribution to this research gap, we look at companies' decisions to finance investments and at their agility to adjust their capital structure. We thus study the relationship between capital structure to finance corporate production and shifts in aggregate demand. Target capital structure determinants and speeds of adjustment to these target capital structures will be analyzed for a geographically comprehensive sample of 2,706 companies listed in Asia, Europe and the U.S.A. in the period 1995 – 2009. Aggregate demand turns out to be the coordinating force which determines managers' choices of target capital structures. The speed of adjustments towards target capital structures indicate that firms are agile in adapting to their targets. Our results provide evidence on Keynes' General Theory from a firm level perspective: Firms respond quickly to shifts in aggregate demand by adjusting capital and production structure correspondingly

Effects of Visual and Acoustic Distraction on Driving Behavior and EEG in Young and Older Car Drivers: A Driving Simulation Study

Driving safety depends on the drivers’ attentional focus on the driving task. Especially in complex situations, distraction due to secondary stimuli can impair driving performance. The inhibition of distractors or inadequate prepotent responses to irrelevant stimuli requires cognitive control, which is assumed to be reduced with increasing age. The present EEG study investigated the effects of secondary acoustic and visual stimuli on driving performance of younger and older car drivers in a driving simulator task. The participants had to respond to brake lights of a preceding car under different distraction conditions and with varying task difficulties. Overall, the anticipation of high demanding tasks affected braking response behavior in young and especially in older adults, who showed reduced cognitive control to task-relevant braking stimuli, as reflected by a smaller P3b. In a more easy (perception only) task, simultaneously presented acoustic stimuli accelerated braking response times (RTs) in young and older adults, which was associated with a pronounced P2. In contrast, secondary visual stimuli increased braking RTs in older adults, associated with a reduced P3b. In a more difficult (discrimination) task, braking response behavior was impaired by the presence of secondary acoustic and visual stimuli in young and older drivers. Braking RT increased (and the P3b decreased), especially when the responses to the secondary stimuli had to be suppressed. This negative effect was more pronounced with visual secondary stimuli, and especially so in the older group. In sum, the results suggest an impaired resistance to distractor interference and a reduced inhibition of prepotent responses in older drivers. This was most pronounced when the processing of task-relevant and irrelevant stimuli engage the same mental resources, for example, by sharing the same stimulus modality

Application of deep learning-based image reconstruction in MR imaging of the shoulder joint to improve image quality and reduce scan time

OBJECTIVES To compare the image quality and diagnostic performance of conventional motion-corrected periodically rotated overlapping parallel line with enhanced reconstruction (PROPELLER) MRI sequences with post-processed PROPELLER MRI sequences using deep learning-based (DL) reconstructions. METHODS In this prospective study of 30 patients, conventional (19 min 18 s) and accelerated MRI sequences (7 min 16 s) using the PROPELLER technique were acquired. Accelerated sequences were post-processed using DL. The image quality and diagnostic confidence were qualitatively assessed by 2 readers using a 5-point Likert scale. Analysis of the pathological findings of cartilage, rotator cuff tendons and muscles, glenoid labrum and subacromial bursa was performed. Inter-reader agreement was calculated using Cohen's kappa statistic. Quantitative evaluation of image quality was measured using the signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR). RESULTS Mean image quality and diagnostic confidence in evaluation of all shoulder structures were higher in DL sequences (p value = 0.01). Inter-reader agreement ranged between kappa values of 0.155 (assessment of the bursa) and 0.947 (assessment of the rotator cuff muscles). In 17 cases, thickening of the subacromial bursa of more than 2 mm was only visible in DL sequences. The pathologies of the other structures could be properly evaluated by conventional and DL sequences. Mean SNR (p value = 0.01) and CNR (p value = 0.02) were significantly higher for DL sequences. CONCLUSIONS The accelerated PROPELLER sequences with DL post-processing showed superior image quality and higher diagnostic confidence compared to the conventional PROPELLER sequences. Subacromial bursa can be thoroughly assessed in DL sequences, while the other structures of the shoulder joint can be assessed in conventional and DL sequences with a good agreement between sequences. KEY POINTS • MRI of the shoulder requires long scan times and can be hampered by motion artifacts. • Deep learning-based convolutional neural networks are used to reduce image noise and scan time while maintaining optimal image quality. The radial k-space acquisition technique (PROPELLER) can reduce the scan time and has potential to reduce motion artifacts. • DL sequences show a higher diagnostic confidence than conventional sequences and therefore are preferred for assessment of the subacromial bursa, while conventional and DL sequences show comparable performance in the evaluation of the shoulder joint

Missense mutation of Brain Derived Neurotrophic Factor (BDNF) alters neurocognitive performance in patients with mild traumatic brain injury: a longitudinal study

The predictability of neurocognitive outcomes in patients with traumatic brain injury is not straightforward. The extent and nature of recovery in patients with mild traumatic brain injury (mTBI) are usually heterogeneous and not substantially explained by the commonly known demographic and injury-related prognostic factors despite having sustained similar injuries or injury severity. Hence, this study evaluated the effects and association of the Brain Derived Neurotrophic Factor (BDNF) missense mutations in relation to neurocognitive performance among patients with mTBI. 48 patients with mTBI were prospectively recruited and MRI scans of the brain were performed within an average 10.1 (SD 4.2) hours post trauma with assessment of their neuropsychological performance post full Glasgow Coma Scale (GCS) recovery. Neurocognitive assessments were repeated again at 6 months follow-up. The paired t-test, Cohen’s d effect size and repeated measure ANOVA were performed to delineate statistically significant differences between the groups [wildtype G allele (Val homozygotes) vs. minor A allele (Met carriers)] and their neuropsychological performance across the time point (T1 = baseline/ admission vs. T2 = 6th month follow-up). Minor A allele carriers in this study generally performed more poorly on neuropsychological testing in comparison wildtype G allele group at both time points. Significant mean differences were observed among the wildtype group in the domains of memory (M = -11.44, SD = 10.0, p = .01, d = 1.22), executive function (M = -11.56, SD = 11.7, p = .02, d = 1.05) and overall performance (M = -6.89 SD = 5.3, p = .00, d = 1.39), while the minor A allele carriers showed significant mean differences in the domains of attention (M = -11.0, SD = 13.1, p = .00, d = .86) and overall cognitive performance (M = -5.25, SD = 8.1, p = .01, d = .66).The minor A allele carriers in comparison to the wildtype G allele group, showed considerably lower scores at admission and remained impaired in most domains across the timepoints, although delayed signs of recovery were noted to be significant in the domains attention and overall cognition. In conclusion, the current study has demonstrated the role of the BDNF rs6265 Val66Met polymorphism in influencing specific neurocognitive outcomes in patients with mTBI. Findings were more detrimentally profound among Met allele carriers

Diagnostic performance of deep learning-based reconstruction algorithm in 3D MR neurography

OBJECTIVE The study aims to evaluate the diagnostic performance of deep learning-based reconstruction method (DLRecon) in 3D MR neurography for assessment of the brachial and lumbosacral plexus. MATERIALS AND METHODS Thirty-five exams (18 brachial and 17 lumbosacral plexus) of 34 patients undergoing routine clinical MR neurography at 1.5 T were retrospectively included (mean age: 49 ± 12 years, 15 female). Coronal 3D T2-weighted short tau inversion recovery fast spin echo with variable flip angle sequences covering plexial nerves on both sides were obtained as part of the standard protocol. In addition to standard-of-care (SOC) reconstruction, k-space was reconstructed with a 3D DLRecon algorithm. Two blinded readers evaluated images for image quality and diagnostic confidence in assessing nerves, muscles, and pathology using a 4-point scale. Additionally, signal-to-noise ratio (SNR) and contrast-to-noise ratios (CNR) between nerve, muscle, and fat were measured. For comparison of visual scoring result non-parametric paired sample Wilcoxon signed-rank testing and for quantitative analysis paired sample Student's t-testing was performed. RESULTS DLRecon scored significantly higher than SOC in all categories of image quality (p < 0.05) and diagnostic confidence (p < 0.05), including conspicuity of nerve branches and pathology. With regard to artifacts there was no significant difference between the reconstruction methods. Quantitatively, DLRecon achieved significantly higher CNR and SNR than SOC (p < 0.05). CONCLUSION DLRecon enhanced overall image quality, leading to improved conspicuity of nerve branches and pathology, and allowing for increased diagnostic confidence in evaluation of the brachial and lumbosacral plexus

The use of artificial intelligence in musculoskeletal ultrasound: a systematic review of the literature

Purpose: To systematically review the use of artificial intelligence (AI) in musculoskeletal (MSK) ultrasound (US) with an emphasis on AI algorithm categories and validation strategies. Material and methods: An electronic literature search was conducted for articles published up to January 2024. Inclusion criteria were the use of AI in MSK US, involvement of humans, English language, and ethics committee approval. Results: Out of 269 identified papers, 16 studies published between 2020 and 2023 were included. The research was aimed at predicting diagnosis and/or segmentation in a total of 11 (69%) out of 16 studies. A total of 11 (69%) studies used deep learning (DL)-based algorithms, three (19%) studies employed conventional machine learning (ML)-based algorithms, and two (12%) studies employed both conventional ML- and DL-based algorithms. Six (38%) studies used cross-validation techniques with K-fold cross-validation being the most frequently employed (n = 4, 25%). Clinical validation with separate internal test datasets was reported in nine (56%) papers. No external clinical validation was reported. Conclusion: AI is a topic of increasing interest in MSK US research. In future studies, attention should be paid to the use of validation strategies, particularly regarding independent clinical validation performed on external datasets

The Effect of Paraspinal Fatty Muscle Infiltration and Cumulative Lumbar Spine Degeneration on the Outcome of Patients with Lumbar Spinal Canal Stenosis: Analysis of the Lumbar Stenosis Outcome Study (LSOS) Data

STUDY DESIGN - Prospective. OBJECTIVE To investigate the influence of paraspinal fatty muscle infiltration (FMI) and cumulative lumbar spine degeneration as assessed by magnetic resonance imaging (MRI) on long-term clinical outcome measures in patients with lumbar spinal canal stenosis (LSCS) of the Lumbar Stenosis Outcome Study (LSOS) cohort. SUMMARY OF BACKGROUND DATA Past studies have tried to establish correlations of morphologic imaging findings in LSCS with clinical endpoints. However, the impact of FMI and overall lumbar spinal degeneration load has not been examined yet. METHODS Patients from the LSOS cohort with moderate to severe LSCS were included. Two radiologists assessed the degree of LSCS as well as cumulative degeneration of the lumbar spine. FMI was graded using the Goutallier scoring system. Spinal Stenosis Measure (SSM) was used to measure the severity level of symptoms and disability. European Quality of Life 5 Dimensions 3 Level Version (EQ-5D-3L) was used to measure health-related quality of life. RESULTS The non-surgically treated group consisted of 116 patients (age 74.8±8.5 y), whereas the surgically treated group included 300 patients (age 72.3±8.2 y). Paraspinal FMI was significantly different between the groups (54.3% vs. 32.0% for Goutallier grade ≥2; P0.05). CONCLUSION FMI is associated with higher disability and worse health-related quality of life of LSCS patients in the LSOS cohort. There was no significant association between total cumulative lumbar spine degeneration and the outcome of either surgically or non-surgically treated patients. LEVEL OF EVIDENCE - Level 3

Deep learning-based pseudo-CT synthesis from zero echo time MR sequences of the pelvis

Objectives To generate pseudo-CT (pCT) images of the pelvis from zero echo time (ZTE) MR sequences and compare them to conventional CT. Methods Ninety-one patients were prospectively scanned with CT and MRI including ZTE sequences of the pelvis. Eleven ZTE image volumes were excluded due to implants and severe B1 field inhomogeneity. Out of the 80 data sets, 60 were used to train and update a deep learning (DL) model for pCT image synthesis from ZTE sequences while the remaining 20 cases were selected as an evaluation cohort. CT and pCT images were assessed qualitatively and quantitatively by two readers. Results Mean pCT ratings of qualitative parameters were good to perfect (2–3 on a 4-point scale). Overall intermodality agreement between CT and pCT was good (ICC = 0.88 (95% CI: 0.85–0.90); p  0.05) with the exception of transverse pelvic diameter measurements and lateral center-edge angle measurements (p = 0.001 and p = 0.002, respectively). Image quality and tissue differentiation in CT and pCT were similar without significant differences between CT and pCT CNRs (all p > 0.05). Conclusions Using a DL-based algorithm, it is possible to synthesize pCT images of the pelvis from ZTE sequences. The pCT images showed high bone depiction quality and accurate geometrical measurements compared to conventional CT. Critical relevance statement pCT images generated from MR sequences allow for high accuracy in evaluating bone without the need for radiation exposure. Radiological applications are broad and include assessment of inflammatory and degenerative bone disease or preoperative planning studies. Key Points - pCT, based on DL-reconstructed ZTE MR images, may be comparable with true CT images. - Overall, the intermodality agreement between CT and pCT was good with excellent interreader agreements for pCT. - Geometrical measurements and tissue differentiation were similar in CT and pCT images