Does sleep promote adaptation to acute stress: An experimental study.

Objectives: Evidence of the impact of chronic stress on sleep is abundant, yet experimental sleep studies with a focus on acute stress are scarce and the results are mixed. Our study aimed to fill this gap by experimentally investigating the effects of pre-sleep social stress on sleep dynamics during the subsequent night, as measured with polysomnography (PSG). Methods: Thirty-four healthy individuals (65% females, Mage = 25.76 years SD = 3.35) underwent a stress-inducing (SC) or neutral control condition (CC) in virtual reality (VR). We used overnight EEG measurements to analyze the basic sleep parameters and power spectral density (PSD) across the sleep cycles, and measured heart rate and its variability (HRV), skin electrodermal activity (EDA), and salivary cortisol to capture physiological arousal during the VR task and the pre-sleep period. Results: Following acute stress (SC), the amount of slow-wave sleep (SWS) was higher and N2 sleep lower relative to CC, specifically in the first sleep cycle. In SC, PSD was elevated in the beta-low (16-24 Hz) and beta-high (25-35 Hz) frequency ranges during both stages N2 and SWS over the entire night. Conclusions: Sleep promoted adaptation to acute social stress by a longer duration of SWS in the subsequent sleep period, especially in early sleep. A similar homeostatic effect towards restorative sleep is well-evidenced in animal model stress studies but has not been previously reported in experimental human studies. Whether the high-frequency PSD activity during stages N2 and SWS also serves in the resolution of transient stress, remains open.

Dynamics of retinotopic spatial attention revealed by multifocal MEG.

Visual focal attention is both fast and spatially localized, making it challenging to investigate using human neuroimaging paradigms. Here, we used a new multivariate multifocal mapping method with magnetoencephalography (MEG) to study how focal attention in visual space changes stimulus-evoked responses across the visual field. The observer's task was to detect a color change in the target location, or at the central fixation. Simultaneously, 24 regions in visual space were stimulated in parallel using an orthogonal, multifocal mapping stimulus sequence. First, we used univariate analysis to estimate stimulus-evoked responses in each channel. Then we applied multivariate pattern analysis to look for attentional effects on the responses. We found that attention to a target location causes two spatially and temporally separate effects. Initially, attentional modulation is brief, observed at around 60-130 ms post stimulus, and modulates responses not only at the target location but also in adjacent regions. A later modulation was observed from around 200 ms, which was specific to the location of the attentional target. The results support the idea that focal attention employs several processing stages and suggest that early attentional modulation is less spatially specific than late.

Forgetting in visual working memory: Internal noise explains decay of feature representations.

The precision of visual working memory (VWM) representations decreases as time passes. It is often assumed that VWM decay is random and caused by internal noise accumulation. However, forgetting in VWM could occur systematically, such that some features deteriorate more rapidly than others. There exist only a few studies testing these two models of forgetting, with conflicting results. Here, decay of features in VWM was thoroughly tested using signal detection theory methods: psychophysical classification images, internal noise estimation, and receiver operant characteristic (ROC). A modified same-different memory task was employed with two retention times (500 and 4000 ms). Experiment 1 investigated VWM decay using a compound grating memory task, and Experiment 2 tested shape memory using radial frequency patterns. Memory performance dropped some 15% with increasing retention time in both experiments. Interestingly, classification images showed virtually indistinguishable weighting of stimulus features at both retention times, suggesting that VWM decay is not feature specific. Instead, we found a 77% increase in stimulus-independent internal noise at the longer retention time. Finally, the slope of the ROC curve plotted as z-scores was shallower at the longer retention time, indicating that the amount of stimulus-independent internal noise increased. Together these findings provide strong support for the idea that VWM decay does not result from a systematic loss of some stimulus features but instead is caused by uniformly increasing random internal noise.

Annoyance, perception, and physiological effects of wind turbine infrasound.

Even though some individuals subjectively associate various symptoms with infrasound, there are very few systematic studies on the contribution of infrasound to the perception, annoyance, and physiological reactions elicited by wind turbine sound. In this study, sound samples were selected among long-term measurement data from wind power plant and residential areas, both indoors and outdoors, and used in laboratory experiments. In the experiments, the detectability and annoyance of both inaudible and audible characteristics of wind turbine noise were determined, as well as autonomic nervous system responses: heart rate, heart rate variability, and skin conductance response. The participants were divided into two groups based on whether they reported experiencing wind turbine infrasound related symptoms or not. The participants did not detect infrasonic contents of wind turbine noise. The presence of infrasound had no influence on the reported annoyance nor the measured autonomic nervous system responses. No differences were observed between the two groups. These findings suggest that the levels of infrasound in the current study did not affect perception and annoyance or autonomic nervous system responses, even though the experimental conditions corresponded acoustically to real wind power plant areas.

Stimulus information supporting bilateral symmetry perception.

A classification image (a psychophysical reverse-correlation) method was used to investigate what stimulus regions and information the visual system uses for bilateral symmetry perception. The stimuli were symmetric random-dot patterns with either low or high dot density. First, the spatial integration region supporting symmetry perception was estimated, by analyzing the trial-to-trial correlation between the spatial location of symmetric dots and the corresponding response. It was observed that the integration region was rather compact (3 deg2 with dense stimulus), vertically elongated and located near to the axis of symmetry. The size of the area was dependent on the pattern density, being larger with low-density stimulus. Next, the resolution of the symmetry matching was probed by estimating how close to the perfect symmetry the dots in two stimulus parts must be to be perceived as symmetric (classification image for symmetry tolerance). Dot pairings up to 6 arc min off from the mirror symmetry correlated with symmetry response, suggesting that the process underlying symmetry matching has large tolerance and low resolution. Outside the integration region, the symmetry tolerance classification image weights were essentially zero, suggesting that the lack of symmetry integration there is not a byproduct of high tolerance.

Template optimization and transfer in perceptual learning.

We studied how learning changes the processing of a low-level Gabor stimulus, using a classification-image method (psychophysical reverse correlation) and a task where observers discriminated between slight differences in the phase (relative alignment) of a target Gabor in visual noise. The method estimates the internal "template" that describes how the visual system weights the input information for decisions. One popular idea has been that learning makes the template more like an ideal Bayesian weighting; however, the evidence has been indirect. We used a new regression technique to directly estimate the template weight change and to test whether the direction of reweighting is significantly different from an optimal learning strategy. The subjects trained the task for six daily sessions, and we tested the transfer of training to a target in an orthogonal orientation. Strong learning and partial transfer were observed. We tested whether task precision (difficulty) had an effect on template change and transfer: Observers trained in either a high-precision (small, 60° phase difference) or a low-precision task (180°). Task precision did not have an effect on the amount of template change or transfer, suggesting that task precision per se does not determine whether learning generalizes. Classification images show that training made observers use more task-relevant features and unlearn some irrelevant features. The transfer templates resembled partially optimized versions of templates in training sessions. The template change direction resembles ideal learning significantly but not completely. The amount of template change was highly correlated with the amount of learning.

Investigating shape perception by classification images.

Radial frequency (RF) patterns are circular contours where the radius is modulated sinusoidally. These stimuli can represent a wide range of common shapes and have been popular for investigating human shape perception. Theories postulate a multistage model where a global contour integration mechanism integrates the outputs of local curvature-sensitive mechanisms. However, studies on how the local contour features are processed have been mostly based on indirect experimental manipulations. Here, we use a novel way to explore the contour integration, using the classification image (a psychophysical reverse-correlation) method. RF contours were composed of local elements, and random "radial position noise" offsets were added to element radial positions. We analyzed the relationship between trial-to-trial variations in radial noise and corresponding behavioral responses, resulting in a "shape template": an estimate of the contour parts and features that the visual system uses in the shape discrimination task. Integration of contour features in a global template-like model explains our data well, and we show that observer performance for different shapes can be predicted from the classification images. Classification images show that observers used most of the contour parts. Further analysis suggests linear rather than probability summation of contour parts. Convex forms were detected better than concave forms and the corresponding templates had better sampling efficiency. With sufficient presentation time, we found no systematic preferences for a certain class of contour features (such as corners or sides). However, when the presentation time was very short, the visual system might prefer corner features over side features.

Template changes with perceptual learning are driven by feature informativeness.

Perceptual learning changes the way the human visual system processes stimulus information. Previous studies have shown that the human brain's weightings of visual information (the perceptual template) become better matched to the optimal weightings. However, the dynamics of the template changes are not well understood. We used the classification image method to investigate whether visual field or stimulus properties govern the dynamics of the changes in the perceptual template. A line orientation discrimination task where highly informative parts were placed in the peripheral visual field was used to test three hypotheses: (1) The template changes are determined by the visual field structure, initially covering stimulus parts closer to the fovea and expanding toward the periphery with learning; (2) the template changes are object centered, starting from the center and expanding toward edges; and (3) the template changes are determined by stimulus information, starting from the most informative parts and expanding to less informative parts. Results show that, initially, the perceptual template contained only the more peripheral, highly informative parts. Learning expanded the template to include less informative parts, resulting in an increase in sampling efficiency. A second experiment interleaved parts with high and low signal-to-noise ratios and showed that template reweighting through learning was restricted to stimulus elements that are spatially contiguous to parts with initial high template weights. The results suggest that the informativeness of features determines how the perceptual template changes with learning. Further, the template expansion is constrained by spatial proximity.

Visual features underlying perceived brightness as revealed by classification images.

Along with physical luminance, the perceived brightness is known to depend on the spatial structure of the stimulus. Often it is assumed that neural computation of the brightness is based on the analysis of luminance borders of the stimulus. However, this has not been tested directly. We introduce a new variant of the psychophysical reverse-correlation or classification image method to estimate and localize the physical features of the stimuli which correlate with the perceived brightness, using a brightness-matching task. We derive classification images for the illusory Craik-O'Brien-Cornsweet stimulus and a "real" uniform step stimulus. For both stimuli, classification images reveal a positive peak at the stimulus border, along with a negative peak at the background, but are flat at the center of the stimulus, suggesting that brightness is determined solely by the border information. Features in the perceptually completed area in the Craik-O'Brien-Cornsweet do not contribute to its brightness, nor could we see low-frequency boosting, which has been offered as an explanation for the illusion. Tuning of the classification image profiles changes remarkably little with stimulus size. This supports the idea that only certain spatial scales are used for computing the brightness of a surface.

Detection of irregular spatial structures.

Wilson et al.'s (1997) study on Glass patterns suggested that the integration of stimulus features into a linear shape occurs quite locally, whereas curved structures--such as circular--require global summation. Their conclusion was based on experiments in which they varied the size of the signal area containing a spatial structure. In the present study, we tested the integration of constant-sized linear and curved Glass patterns by varying their global irregularity. If the mechanisms underlying the detection of a Glass pattern pool features globally throughout the stimulus, the irregularity should have a strong effect on detection performance. The irregular Glass patterns were composed of a variable number of sub-areas, each of which contained its own linear or curved structure. The structural irregularity impaired the detection of the curved patterns, whereas the thresholds for the linear patterns were not affected. Thus, our results are in line with the notion that the integration of curved Glass patterns occurs more globally than the integration of linear patterns.

Collinear context (and learning) change the profile of the perceptual filter.

The effect of collinear context on the filter mediating the detection of a Gabor stimulus was investigated by using the classification image method. Classification images were estimated for a 1.5 cpd horizontal Gabor target and the same target flanked by two collinear Gabors horizontally 1.7 degrees displaced from the target. The target was masked by a low-contrast white-noise mask. Obtained classification images were fitted by Gabor functions. The results show that collinear flankers increase the length of the classification image profiles along the collinear axis. At the same time, modest facilitory effects were observed in most subjects. The specificity and the amount of context-induced elongation in the classification images makes it hard to be explained by uncertainty reduction alone. In previous studies, collinear facilitation has been reported to abolish due to perceptual learning. We report a possibly related phenomenon: classification image data was re-analyzed in two parts consisting of the early and the late trials. In the latter trials, differences between the classification images in flankers and no-flankers condition are no longer significant.

Shape perception in human vision: specialized detectors for concentric spatial structures?

It has been suggested that second-order shape integration mechanisms in human spatial vision (e.g. the neurons at V2 and V4 cortical areas) may contain specialized detectors for concentric shapes [Vision Res. 37 (1997) 2325; Vision Res. 38 (1998) 2933]. We tested this notion using psychophysical techniques in which the observers' task was to detect orientation noise (randomly oriented dot pairs) in concentric and linear Glass patterns. Our results showed that the detection of orientation noise was easier in concentric Glass patterns, thus supporting the notion of specialized detectors.

Spatial integration in Glass patterns.

The extraction of a global orientation structure presumably has a different neural mechanism from that of the analysis of its local features. We investigated spatial integration within these two mechanisms using stimulus patterns composed of dot pairs (dipoles). The stimuli targeted local feature detection, contained no global configuration, but rather contained randomly oriented dipoles of a fixed length (the distance between the dots in a pair). For the detection of a global orientation structure, local dipole orientations were arranged in a concentric Glass pattern. Thresholds as a function of a stimulus area were determined by measuring the minimum proportion of dipoles among random-dot noise (signal-to-noise ratio) required for the detection of dipoles (features), as well as for the detection of an orientation structure. Thresholds for feature detection were significantly higher than those for the detection of the global structure--regardless of the stimulus size. Spatial integration, however, did not differ between the two tasks: the exponents of the power functions fitted to data for six observers were -0.48 +/- 0.07 for random dipole orientations and -0.62 +/- 0.1 for Glass patterns.