Intentional binding - Is it just causal binding? A replication study of Suzuki et al. (2019).

Intentional actions produce a temporal compression between the action and its outcome, known as intentional binding. However, Suzuki et al. (2019) recently showed that temporal compression can be observed without intentional actions. However, their results show a clear regression to the mean, which might have confounded the estimates of temporal intervals. To control these effects, we presented temporal intervals block-wise. Indeed, we found systematically greater compression for active than passive trials, in contrast to Suzuki et al. (2019). In our second experiment, our goal was to conceptually replicate the previous study. However, we were unable to reproduce their results and instead found more pronounced temporal compression in active trials compared to passive ones. In a subsequent attempt at a direct replication, we did not observe the same findings as the original study. Our findings reinforce the theory that intentions rather than causality cause temporal binding. During the preparation of this work, the authors used ChatGPT in order to improve the readability of the paper. After using this tool/service, the authors reviewed and edited the content as needed and take full responsibility for the content of the publication.

Serial dependencies between locomotion and visual space.

How do we know the spatial distance of objects around us? Only by physical interaction within an environment can we measure true physical distances. Here, we investigated the possibility that travel distances, measured during walking, could be used to calibrate visual spatial perception. The sensorimotor contingencies that arise during walking were carefully altered using virtual reality and motion tracking. Participants were asked to walk to a briefly highlighted location. During walking, we systematically changed the optic flow, i.e., the ratio between the visual and physical motion speed. Although participants remained unaware of this manipulation, they walked a shorter or longer distance as a function of the optic flow speed. Following walking, participants were required to estimate the perceived distance of visual objects. We found that visual estimates were serially dependent on the experience of the manipulated flow in the previous trial. Additional experiments confirmed that to affect visual perception, both visual and physical motion are required. We conclude that the brain constantly uses movements to measure space for both, actions, and perception.

Temporal perturbations cause movement-context independent but modality specific sensorimotor adaptation.

Complex, goal-directed and time-critical movements require the processing of temporal features in sensory information as well as the fine-tuned temporal interplay of several effectors. Temporal estimates used to produce such behavior may thus be obtained through perceptual or motor processes. To disentangle the two options, we tested whether adaptation to a temporal perturbation in an interval reproduction task transfers to interval reproduction tasks with varying sensory information (visual appearance of targets, modality, and virtual reality [VR] environment or real-world) or varying movement types (continuous arm movements or brief clicking movements). Halfway through the experiments we introduced a temporal perturbation, such that continuous pointing movements were artificially slowed down in VR, causing participants to adapt their behavior to sustain performance. In four experiments, we found that sensorimotor adaptation to temporal perturbations is independent of environment context and movement type, but modality specific. Our findings suggest that motor errors induced by temporal sensorimotor adaptation affect the modality specific perceptual processing of temporal estimates.

Adaptation of pointing and visual localization in depth around the natural grasping distance.

Vision in depth is distorted. A similar distortion can be observed for pointing to visual targets in depth. It has been suggested that pointing errors in depth reflect the visual distortion. Alternatively, pointing in depth might be guided by a prior that biases movements toward the natural grasping distance at which object manipulation is usually performed. To dissociate whether pointing is guided by distorted vision only or whether it takes into account a natural grasping distance prior, we adapted pointing movements. Participants received visual feedback about the success of their pointing once the movement was finished. We distorted the feedback to signal either that pointing was not far enough or in separate sessions that pointing was too far. Participants adapted to this artificial error by either extending or shortening their pointing movements. The generalization of pointing adaptation revealed a bias in movement planning that is inconsistent with pointing being guided only by distorted vision but with the involvement of knowledge about the natural grasping distance. Adaptation was strongest for pointing movements to a middle position that corresponds to the natural grasping distance and it was weakest for movements leading away from it. It has been demonstrated that pointing adaptation in depth changes visual perception (Volcic R, Fantoni C, Caudek C, Assad JA, Domini F. J Neurosci 33: 17081-17088, 2013). We also wondered how effects of pointing adaptation on visual space would generalize in depth. We found that adaptation changed visual space, but that this change was independent of the adaptation direction.NEW & NOTEWORTHY Which information guides pointing in 3D space? Inaccuracies of vision in depth generate the need for the sensorimotor system to rely on other information sources to optimally plan movement trajectories. Here, we implemented pointing adaptation experiments that could dissociate if the generalization of adaptation follows visual distortions or if it is informed by a "natural grasping distance" prior. Adaptation was strongest for movements toward the natural grasping distance, suggesting the latter hypothesis to be true.

Accuracy and precision of stimulus timing and reaction times with Unreal Engine and SteamVR.

The increasing interest in Virtual Reality (VR) as a tool for neuroscientific research contrasts with the current lack of established toolboxes and standards. In several recent studies, game engines like Unity or Unreal Engine were used. It remains to be tested whether these software packages provide sufficiently precise and accurate stimulus timing and time measurements that allow inferring ongoing mental and neural processes. We here investigated the precision and accuracy of the timing mechanisms of Unreal Engine 4 and SteamVR in combination with the HTC Vive VR system. In a first experiment, objective external measures revealed that stimulus durations were highly accurate. In contrast, in a second experiment, the assessment of the precision of built-in timing procedures revealed highly variable reaction time measurements and inaccurate determination of stimulus onsets. Hence, we developed a new software-based method that allows precise and accurate reaction time measurements with Unreal Engine and SteamVR. Instead of using the standard timing procedures implemented within Unreal Engine, time acquisition was outsourced to a background application. Timing benchmarks revealed that the newly developed method allows reaction time measurements with a precision and accuracy in the millisecond range. Overall, the present results indicate that the HTC Vive together with Unreal Engine and SteamVR can achieve high levels of precision and accuracy both concerning stimulus duration and critical time measurements. The latter can be achieved using a newly developed routine that allows not only accurate reaction time measures but also provides precise timing parameters that can be used in combination with time-sensitive functional measures such as electroencephalography (EEG) or transcranial magnetic stimulation (TMS).

Combined expectancies: the role of expectations for the coding of salient bottom-up signals.

The visual system forms predictions about upcoming visual features based on previous visual experiences. Such predictions impact on current perception, so that expected stimuli can be detected faster and with higher accuracy. A key question is how these predictions are formed and on which levels of processing they arise. Particularly, predictions could be formed on early levels of processing, where visual features are represented separately, or might require higher levels of processing, with predictions formed based on full object representations that involve combinations of visual features. In four experiments, the present study investigated whether the visual system forms joint prediction errors or whether expectations about different visual features such as color and orientation are formed independently. The first experiment revealed that task-irrelevant and implicitly learned expectations were formed independently when the features were separately bound to different objects. In a second experiment, no evidence for a mutual influence of both types of task-irrelevant and implicitly formed feature expectations was observed, although both visual features were assigned to the same objects. A third experiment confirmed the findings of the previous experiments for explicitly rather than implicitly formed expectations. Finally, no evidence for a mutual influence of different feature expectations was observed when features were assigned to a single centrally presented object. Overall, the present results do not support the view that object feature binding generates joint feature-based expectancies of different object features. Rather, the results suggest that expectations for color and orientation are processed and resolved independently at the feature level.

An fMRI study into emotional processing in Parkinson's disease: Does increased medial prefrontal activation compensate for striatal dysfunction?

BACKGROUND: Apart from a progressive decline of motor functions, Parkinson's disease (PD) is also characterized by non-motor symptoms, including disturbed processing of emotions. This study aims at assessing emotional processing and its neurobiological correlates in PD with the focus on how medicated Parkinson patients may achieve normal emotional responsiveness despite basal ganglia dysfunction. METHODS: Nineteen medicated patients with mild to moderate PD (without dementia or depression) and 19 matched healthy controls passively viewed positive, negative, and neutral pictures in an event-related blood oxygen level-dependent functional magnetic resonance imaging study (BOLD-fMRI). Individual subjective ratings of valence and arousal levels for these pictures were obtained right after the scanning. RESULTS: Parkinson patients showed similar valence and arousal ratings as controls, denoting intact emotional processing at the behavioral level. Yet, Parkinson patients showed decreased bilateral putaminal activation and increased activation in the right dorsomedial prefrontal cortex (PFC), compared to controls, both most pronounced for highly arousing emotional stimuli. CONCLUSIONS: Our findings revealed for the first time a possible compensatory neural mechanism in Parkinson patients during emotional processing. The increased medial PFC activity may have modulated emotional responsiveness in patients via top-down cognitive control, therewith restoring emotional processing at the behavioral level, despite striatal dysfunction. These results may impact upon current treatment strategies of affective disorders in PD as patients may benefit from this intact or even compensatory influence of prefrontal areas when therapeutic strategies are applied that rely on cognitive control to modulate disturbed processing of emotions.