Combination of volume-rendering 3D surface modeling and medical illustration to capture the living fetus.

OBJECTIVE: A good medical illustration renders essential aspects of a procedure or condition faithfully, yet idealizes it enough to make it widely applicable. Unfortunately, the live fetus is generally hidden from sight, and illustrating it relies either on autopsy material or manipulated newborn images. High-definition volume rendering of diagnostic imaging data can represent hidden conditions with an almost lifelike realism but is limited by the resolution and artifacts of the data capture. We have combined both approaches to enhance the accuracy and didactic value of illustrations of fetal conditions. METHODS: Three examples, of increasing complexity, are presented to demonstrate the creation of medical illustrations of the fetus based on semiautomatic computerized posthoc manipulation of diagnostic images. RESULTS: The end product utilizes the diagnostic accuracy of ultrasound and magnetic resonance imaging of the fetuses and the spatial manipulation of 3D models to create a lifelike, accurate and informative image of the fetal anomalies. CONCLUSION: Volume-rendering and 3D surface modeling can be combined with medical illustration to create realistic and informative images of the developing fetus, using a level of detail that is tailored to the intended audience.

Electrophysiological and phenomenological effects of short-term immersion in an altered sensory environment.

We examined the spontaneous cerebral electrophysiology and phenomenology during short-term perceptual deprivation consisting of an edgeless visual field combined with monotonous auditory input that eliminated potential grounding cues (multimodal Ganzfeld). Subjects (N = 22) were instructed to self-report perceptual fading using a button press. Relaxed wakefulness with closed eyes and viewing of a time-varying stimulus array served as control conditions. The power of parieto-occipital alpha rhythms during perceptual deprivation was midway between the eyes-closed and eyes-open conditions, with a state-specific frequency acceleration. Oscillatory alpha power remained enhanced in the multimodal Ganzfeld relative to viewing time-varying signals, despite no indication of diminished brain arousal. Subjects experienced a range of perceptual phenomena while in the altered sensory environment and individuals with faster alpha oscillations self-reported a greater number of fading episodes. We suggest that alpha-band electroencephalogram (EEG) dynamics signal internally oriented mentation in response to brief perceptual deprivation.

Differential aversive learning enhances orientation discrimination.

A number of recent studies have documented rapid changes in behavioural sensory acuity induced by aversive learning in the olfactory and auditory modalities. The effect of aversive learning on the discrimination of low-level features in the visual system of humans remains unclear. Here, we used a psychophysical staircase procedure to estimate discrimination thresholds for oriented grating stimuli, before and after differential aversive learning. We discovered that when a target grating orientation was conditioned with an aversive loud noise, it subsequently led to an improvement of discrimination acuity in nearly all subjects. However, no such change was observed in a control group conditioned to an orientation shifted by ±90° from the target. Our findings cannot be explained by contextual learning or sensitisation factors. The results converge with those reported in the olfactory modality and provide further evidence that early sensory systems can be rapidly modified by recently experienced reinforcement histories.

Young Children's Use of Smartphones and Tablets.

BACKGROUND AND OBJECTIVES: Child mobile device use is increasingly prevalent, but research is limited by parent-report survey methods that may not capture the complex ways devices are used. We aimed to implement mobile device sampling, a set of novel methods for objectively measuring child mobile device use. METHODS: We recruited 346 English-speaking parents and guardians of children aged 3 to 5 years to take part in a prospective cohort study of child media use. All interactions with participants were through e-mail, online surveys, and mobile device sampling; we used a passive-sensing application (Chronicle) in Android devices and screenshots of the battery feature in iOS devices. Baseline data were analyzed to describe usage behaviors and compare sampling output with parent-reported duration of use. RESULTS: The sample comprised 126 Android users (35 tablets, 91 smartphones) and 220 iOS users (143 tablets, 77 smartphones); 35.0% of children had their own device. The most commonly used applications were YouTube, YouTube Kids, Internet browser, quick search or Siri, and streaming video services. Average daily usage among the 121 children with their own device was 115.3 minutes/day (SD 115.1; range 0.20-632.5) and was similar between Android and iOS devices. Compared with mobile device sampling output, most parents underestimated (35.7%) or overestimated (34.8%) their child's use. CONCLUSIONS: Mobile device sampling is an unobtrusive and accurate method for assessing mobile device use. Parent-reported duration of mobile device use in young children has low accuracy, and use of objective measures is needed in future research.

The role of low-level image features in the affective categorization of rapidly presented scenes.

It remains unclear how the visual system is able to extract affective content from complex scenes even with extremely brief (< 100 millisecond) exposures. One possibility, suggested by findings in machine vision, is that low-level features such as unlocalized, two-dimensional (2-D) Fourier spectra can be diagnostic of scene content. To determine whether Fourier image amplitude carries any information about the affective quality of scenes, we first validated the existence of image category differences through a support vector machine (SVM) model that was able to discriminate our intact aversive and neutral images with ~ 70% accuracy using amplitude-only features as inputs. This model allowed us to confirm that scenes belonging to different affective categories could be mathematically distinguished on the basis of amplitude spectra alone. The next question is whether these same features are also exploited by the human visual system. Subsequently, we tested observers' rapid classification of affective and neutral naturalistic scenes, presented briefly (~33.3 ms) and backward masked with synthetic textures. We tested categorization accuracy across three distinct experimental conditions, using: (i) original images, (ii) images having their amplitude spectra swapped within a single affective image category (e.g., an aversive image whose amplitude spectrum has been swapped with another aversive image) or (iii) images having their amplitude spectra swapped between affective categories (e.g., an aversive image containing the amplitude spectrum of a neutral image). Despite its discriminative potential, the human visual system does not seem to use Fourier amplitude differences as the chief strategy for affectively categorizing scenes at a glance. The contribution of image amplitude to affective categorization is largely dependent on interactions with the phase spectrum, although it is impossible to completely rule out a residual role for unlocalized 2-D amplitude measures.