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Spasticity affects approximately 65% of persons with spinal cord injury (SCI) and negatively impacts function and quality of life. Whole body vibration (WBV) appears to reduce spasticity and improve walking function; however, the optimal dose (frequency/duration) is not known. We compared single-session effects of four different WBV frequency/duration dose conditions on spasticity and walking speed, in preparation for a planned multi-session study. Thirty-five participants with motor-incomplete SCI received four different doses of WBV: high frequency (50 Hz)/short duration (180 s), high frequency/long duration (360 s), low frequency (30 Hz)/short duration, and low frequency/long duration, plus a control intervention consisting of sham electrical stimulation. In all conditions, participants stood on the WBV platform for 45-s bouts with 1 min rest between bouts until the requisite duration was achieved. The frequency/duration dose order was randomized across participants; sessions were separated by at least 1 week. Quadriceps spasticity was measured using the pendulum test at four time points during each session: before, immediately after, 15 min after, and 45 min after WBV. Walking speed was quantified using the 10-m walk test at three time points during each session: baseline, immediately after, and 45 min after WBV. In the full group analysis, no frequency/duration combination was significantly different from the sham-control condition. In participants with more severe spasticity, a greater reduction in stretch reflex excitability was associated with the high frequency/long duration WBV condition. The sham-control condition was associated with effects, indicating that the activity of repeated sitting and standing may have a beneficial influence on spasticity. Trial registration: NCT02340910 (assigned 01/19/2015).

It is difficult to collect objective evidence of interoception. Unlike exteroception, the effective stimuli for interoception are often unknown, and even when identifiable, they are difficult to control experimentally. Furthermore, direct stimulation of the interoceptors is seldom appropriate in human experimentation. Hence, non-invasive behavioural measures of accuracy in heartbeat detection have frequently been adopted to index interoceptive sensitivity. However, there has been little standardization and the two most popular methods for assessing heartbeat detection, heartbeat tracking and two alternative forced choice methods, appear to be biased and of questionable validity. These issues do not arise with other methods that are based on classical psychophysics and that enable subjects to indicate when during the cardiac cycle their heartbeat sensations occur. Not only are these classical methods highly reliable, but they also provide continuous unbiased measures of the temporal locations of heartbeat sensations and the precision with which these sensations are detected. This article is part of the themed issue ‘Interoception beyond homeostasis: affect, cognition and mental health’.

While online experiments have shown tremendous potential to study larger and more diverse participant samples than is possible in the lab, the uncontrolled online environment has prohibited many types of psychophysical studies due to difficulties controlling the viewing distance and stimulus size. We introduce the Virtual Chinrest, a method that measures a participant’s viewing distance in the web browser by detecting a participant’s blind spot location. This makes it possible to automatically adjust stimulus configurations based on an individual’s viewing distance. We validated the Virtual Chinrest in two laboratory studies in which we varied the viewing distance and display size, showing that our method estimates participants’ viewing distance with an average error of 3.25 cm. We additionally show that by using the Virtual Chinrest we can reliably replicate measures of visual crowding, which depends on a precise calculation of visual angle, in an uncontrolled online environment. An online experiment with 1153 participants further replicated the findings of prior laboratory work, demonstrating how visual crowding increases with eccentricity and extending this finding by showing that young children, older adults and people with dyslexia all exhibit increased visual crowding, compared to adults without dyslexia. Our method provides a promising pathway to web-based psychophysical research requiring controlled stimulus geometry.

In this review article, the authors give a brief overview of the sensory capabilities of rodents and of their cortical areas devoted to sensation and decision. They also review methods of psychophysics, focusing on the technical issues that arise in their implementation in rodents. The study of perceptual decision-making offers insight into how the brain uses complex, sometimes ambiguous information to guide actions. Understanding the underlying processes and their neural bases requires that one pair recordings and manipulations of neural activity with rigorous psychophysics. Though this research has been traditionally performed in primates, it seems increasingly promising to pursue it at least partly in mice and rats. However, rigorous psychophysical methods are not yet as developed for these rodents as they are for primates. Here we give a brief overview of the sensory capabilities of rodents and of their cortical areas devoted to sensation and decision. We then review methods of psychophysics, focusing on the technical issues that arise in their implementation in rodents. These methods represent a rich set of challenges and opportunities.

Psychophysical methods are a cornerstone of psychology, cognitive science, and neuroscience where they have been used to quantify behavior and its neural correlates for a vast range of mental phenomena. Their power derives from the combination of controlled experiments and rigorous analysis through signal detection theory. Unfortunately, they require many tedious trials and preferably highly trained participants. A recently developed approach, continuous psychophysics, promises to transform the field by abandoning the rigid trial structure involving binary responses and replacing it with continuous behavioral adjustments to dynamic stimuli. However, what has precluded wide adoption of this approach is that current analysis methods do not account for the additional variability introduced by the motor component of the task and therefore recover perceptual thresholds that are larger compared to equivalent traditional psychophysical experiments. Here, we introduce a computational analysis framework for continuous psychophysics based on Bayesian inverse optimal control. We show via simulations and previously published data that this not only recovers the perceptual thresholds but additionally estimates subjects’ action variability, internal behavioral costs, and subjective beliefs about the experimental stimulus dynamics. Taken together, we provide further evidence for the importance of including acting uncertainties, subjective beliefs, and, crucially, the intrinsic costs of behavior, even in experiments seemingly only investigating perception. Humans often perceive the world around them subjectively. Factors like light brightness, the speed of a moving object, or an individual's interpretation of facial expressions may influence perception. Understanding how humans perceive the world can provide valuable insights into neuroscience, psychology, and even people’s spending habits, making human perception studies important. However, these so-called psychophysical studies often consist of thousands of simple yes or no questions, which are tedious for adult volunteers, and nearly impossible for children. A new approach called ‘continuous psychophysics’ makes perception studies shorter, easier, and more fun for participants. Instead of answering yes or no questions (like in classical psychophysics experiments), the participants follow an object on a screen with their fingers or eyes. One question about this new approach is whether it accounts for differences that affect how well participants follow the object. For example, some people may have jittery hands, while others may be unmotivated to complete the task. To overcome this issue, Straub and Rothkopf have developed a mathematical model that can correct for differences between participants in the variability of their actions, their internal costs of actions, and their subjective beliefs about how the target moves. Accounting for these factors in a model can lead to more reliable study results. Straub and Rothkopf used data from three previous continuous psychophysics studies to construct a mathematical model that could best predict the experimental results. To test their model, they then used it on data from a continuous psychophysics study conducted alongside a classical psychophysics study. The model was able to correct the results of the continuous psychophysics study so they were more consistent with the results of the classical study. This new technique may enable wider use of continuous psychophysics to study a range of human behavior. It will allow larger, more complex studies that would not have been possible with conventional approaches, as well as enable research on perception in infants and children. Brain scientists may also use this technique to understand how brain activity relates to perception.

One of the most precise methods to establish psychometric functions and estimate threshold and slope parameters is the constant stimuli procedure. The large distribution of predetermined stimulus values presented to observers enables the psychometric functions to be fully developed, but makes this procedure time-consuming. Adaptive procedures enable reliable threshold estimation while reducing the number of trials by concentrating stimulus presentations around observers’ supposed threshold. Here, the stimulus value for the next trial depends on observer’s responses to the previous trials. One recent improvement of these procedures is to also estimate the slope (related to discrimination sensitivity). The Bayesian QUEST+ procedure (Watson  Journal of Vision, 17 (3), 10,  2017 ), a generalization and extension of the QUEST procedure, includes this refinement. Surprisingly, this procedure is barely used. Our goal was to empirically assess its precision to evaluate size, orientation, or temporal perception, in three yes/no discrimination tasks that increase in demands. In 72 adult participants in total, we compared points of subjective equivalence (PSEs) or simultaneity (PSSs) as well as discrimination sensitivity obtained with the QUEST+, constant stimuli, and simple up-down staircase procedures. While PSEs did not differ between procedures, sensitivity estimates obtained with the 64-trials QUEST+ procedure were overestimated (i.e., just-noticeable differences, or JNDs, were underestimated). Overall, agreement between procedures was good, and was at its best for the easiest tasks. This study empirically confirmed that the QUEST+ procedure can be considered as a method of choice to accelerate PSE estimation, while keeping in mind that sensitivity estimation should be handled with caution.

In behavioral sciences, there is growing concern about the inflation of false-positive rates due to the amount of under-powered studies that have been shared in the past years. While problematic, having the possibility to recruit (lots of) participants (for a lot of time) is realistically not achievable for many research facilities. Factors that hinder the reaching of optimal sample sizes are, to name but a few, research costs, participants’ availability and commitment, and logistics. We challenge these issues by introducing PsySuite , an Android app designed to foster a remote approach to multimodal behavioral testing. To validate PsySuite , we first evaluated its ability to generate stimuli appropriate to rigorous psychophysical testing, measuring both the app’s accuracy (i.e., stimuli’s onset, offset, and multimodal simultaneity) and precision (i.e., the stability of a given pattern across trials), using two different smartphone models. We then evaluated PsySuite ’s ability to replicate perceptual performances obtained using a classic psychophysical paradigm, comparing sample data collected with the app against those measured via a PC-based setup. Our results showed that PsySuite could accurately reproduce stimuli with a minimum duration of 7 ms, 17 ms, and 30 ms for the auditory, visual, and tactile modalities, respectively, and that perceptual performances obtained with PsySuite were consistent with the perceptual behavior observed using the classical setup. Combined with the high accessibility inherently supported by PsySuite , here we ought to share the app to further boost psychophysical research, aiming at setting it to a cheap, user-friendly, and portable level.

Goal-directed behavior depends on both sensory mechanisms that gather information from the outside world and decision-making mechanisms that select appropriate behavior based on that sensory information. Psychophysical reverse correlation is commonly used to quantify how fluctuations of sensory stimuli influence behavior and is generally believed to uncover the spatiotemporal weighting functions of sensory processes. Here we show that reverse correlations also reflect decision-making processes and can deviate significantly from the true sensory filters. Specifically, changes of decision bound and mechanisms of evidence integration systematically alter psychophysical reverse correlations. Similarly, trial-to-trial variability of sensory and motor delays and decision times causes systematic distortions in psychophysical kernels that should not be attributed to sensory mechanisms. We show that ignoring details of the decision-making process results in misinterpretation of reverse correlations, but proper use of these details turns reverse correlation into a powerful method for studying both sensory and decision-making mechanisms. Reverse correlation is a psychophysics technique used to infer sensory filter properties by measuring how changes in stimuli influence behavior. Here, the authors show that reverse correlation is shaped by both sensory and decision-making processes, and validate a method to partition their contributions.

Spatial orientation is a complex ability that emerges from the interaction of several systems in a way that is still unclear. One of the reasons limiting the research on the topic is the lack of methodologies aimed at studying multimodal psychophysics in an ecological manner and with affordable settings. Virtual reality can provide a workaround to this impasse by using virtual stimuli rather than real ones. However, the available virtual reality development platforms are not meant for psychophysical testing; therefore, using them as such can be very difficult for newcomers, especially the ones new to coding. For this reason, we developed SALLO, the Suite for the Assessment of Low-Level cues on Orientation, which is a suite of utilities that simplifies assessing the psychophysics of multimodal spatial orientation in virtual reality. The tools in it cover all the fundamental steps to design a psychophysical experiment. Plus, dedicated tracks guide the users in extending the suite components to simplify developing new experiments. An experimental use-case used SALLO and virtual reality to show that the head posture affects both the egocentric and the allocentric mental representations of spatial orientation. Such a use-case demonstrated how SALLO and virtual reality can be used to accelerate hypothesis testing concerning the psychophysics of spatial orientation and, more broadly, how the community of researchers in the field may benefit from such a tool to carry out their investigations.

Discovering the visual features and representations used by the brain to recognize objects is a central problem in the study of vision. Recently, neural network models of visual object recognition, including biological and deep network models, have shown remarkable progress and have begun to rival human performance in some challenging tasks. These models are trained on image examples and learn to extract features and representations and to use them for categorization. It remains unclear, however, whether the representations and learning processes discovered by current models are similar to those used by the human visual system. Here we show, by introducing and using minimal recognizable images, that the human visual system uses features and processes that are not used by current models and that are critical for recognition. We found by psychophysical studies that at the level of minimal recognizable images a minute change in the image can have a drastic effect on recognition, thus identifying features that are critical for the task. Simulations then showed that current models cannot explain this sensitivity to precise feature configurations and, more generally, do not learn to recognize minimal images at a human level. The role of the features shown here is revealed uniquely at theminimal level, where the contribution of each feature is essential. A full understanding of the learning and use of such features will extend our understanding of visual recognition and its cortical mechanisms and will enhance the capacity of computational models to learn from visual experience and to deal with recognition and detailed image interpretation.