Psychological Research-Psychologische Forschung最新文献

In the present study, an attempt was made to replicate results found about the influence of valence on prioritisation and decay in iconic memory. Hereby, the evaluative conditioning effect was used to induce valence for formerly neutral stimuli. The effect is gained by pairing neutral stimuli with either positive, negative, or neutral images in a conditioning phase. Afterwards, the conditioned stimuli acted as targets in an iconic memory test. In the iconic memory test, targets were presented together with seven other stimuli on a circular placement on the screen for a short time. A cue delayed by either 17, 68, 221, 493, or 1003 ms pointed at the target to be reported. Participants rated the targets before and after the conditioning phase. In addition, the affective and neutral images used in the pairing procedure were rated at the end of the experiment. While no significant change in rating could be observed for the conditioned targets, a significant effect of conditioned valence was still present in the response times and the accuracy of the iconic memory test. Participants reacted the quickest in response to a cue for positively conditioned targets compared to neutral or negatively conditioned targets. Accuracy was highest for positively conditioned targets and was lowest for negatively conditioned targets. Unlike in prior studies, slower decay of information in iconic memory for negative targets was not revealed. Further research should be conducted to identify reasons for this inconsistency.

Eyewitness identifications from lineups are prone to error. More indirect identification procedures, such as the reaction-time based Concealed Information Test (RT-CIT) could be a viable alternative to lineups. The RT-CIT uses response times to assess facial familiarity. Theory and initial evidence with autobiographical stimuli suggests that the accuracy of RT-CIT can be augmented when participants' reliance on familiarity-based responding increases. We tested this assumption in two pre-registered experiments with 173 participants. Participants witnessed a mock crime. In the subsequent RT-CIT protocol, participants reacted to probe faces from the mock crime video, to irrelevant faces, and to target faces that required a unique response. Targets were either unknown people or were well-known celebrities (e.g., Taylor Swift). As expected, reaction times were longer to probes than to irrelevants in all conditions, indicating a CIT effect. Contrasting our pre-registered predictions, the CIT effect was not larger in the familiar condition (Experiment 1: unfamiliar targets: d = 0.77 vs. celebrity targets: d = 0.24; Experiment 2: unfamiliar targets: d = 1.09 vs. celebrity targets: d = 0.79). This suggests that familiar targets did not increase the validity of the RT-CIT in diagnosing concealed face recognition. A potential lack of saliency of the familiar targets might explain these unexpected findings. Of note, we did find medium to large effect sizes overall, speaking to the potential of diagnosing face recognition with the RT-CIT.

Acting in the environment results in both intended and unintended consequences. Action consequences provide feedback about the adequacy of actions while they are in progress and when they are completed and therefore contribute to monitoring actions, facilitate error detection, and are crucial for motor learning. In action imagery, no actual action takes place, and consequently, no actual action consequences are produced. However, imagined action consequences may replace actual action consequences, serving a similar function and facilitating performance improvements akin to that occurring with actual actions. In this paper, we conceptualize action imagery as a simulation based on internal models. During that simulation, forward models predict action consequences. A comparison of predicted and intended action consequences sometimes indicates the occurrence of action errors (or deviations from optimal performance) in action imagery. We review research indicating that action errors are indeed sometimes imagined in action imagery. These results are compatible with the view that action imagery is based on motor simulation but incompatible with the view that action imagery is solely based on abstract knowledge. The outlined framework seems suitable to cover a wide range of action imagery phenomena and can explain action imagery practice effects.

In this paper, we discuss a variety of ways in which practising motor actions by means of motor imagery (MI) can be enhanced via synchronous action observation (AO), that is, by AO + MI. We review the available research on the (mostly facilitatory) behavioural effects of AO + MI practice in the early stages of skill acquisition, discuss possible theoretical explanations, and consider several issues related to the choice and presentation schedules of suitable models. We then discuss considerations related to AO + MI practice at advanced skill levels, including expertise effects, practical recommendations such as focussing attention on specific aspects of the observed action, using just-ahead models, and possible effects of the perspective in which the observed action is presented. In section "Coordinative AO + MI", we consider scenarios where the observer imagines performing an action that complements or responds to the observed action, as a promising and yet under-researched application of AO + MI training. In section "The dual action simulation hypothesis of AO + MI", we review the neurocognitive hypothesis that AO + MI practice involves two parallel action simulations, and we consider opportunities for future research based on recent neuroimaging work on parallel motor representations. In section "AO + MI training in motor rehabilitation", we review applications of AO, MI, and AO + MI training in the field of neurorehabilitation. Taken together, this evidence-based, exploratory review opens a variety of avenues for future research and applications of AO + MI practice, highlighting several clear advantages over the approaches of purely AO- or MI-based practice.

The recent review by Eaves et al. (Psychological Research/Psychologische Forschung, 2022) outlines the research conducted to-date on combined action-observation and motor imagery (AOMI), and more specifically, its added benefit to learning. Of interest, these findings have been primarily attributed to the dual action simulation hypothesis, whereby AO and MI activate separable representations for action that may be later merged when they are congruent with one another. The present commentary more closely evaluates this explanation. What's more, we offer an alternative information-based argument where the benefit to learning may be served instead by the availability of key information. Along these lines, we speculate on possible future directions including the need for a transfer design.

The mechanism through which motor imagery practice improves motor performance remains unclear. In this special issue, Rieger et al. propose a model to explain why motor imagery practice improves motor performance. According to their model, motor imagery involves a comparison between intended and predicted action effects, allowing for the modification of the internal model upon detecting errors. I believe that the anterior cingulate cortex (ACC) is a candidate as a brain region responsible for comparing intended and predicted action effects. Evidence supports this hypothesis, as a previous study has observed error-related activity in the ACC preceding incorrect responses (i.e., commission errors) in the Go/No-go task (Bediou et al., 2012, Neuroimage). Therefore, the error-related activity can be induced without any feedback. This fact also sheds light on the mechanisms of brain-computer interface. I believe that this additional literature will enhance Rieger's model.

In this position paper, the authors support with recent behavioral findings the theory of internal simulations during motor imagery, initiated in the 90's. In this commentary, I will provide additional evidence from other research groups to support this theory and discuss the neurophysiological basis of inhibition (surround inhibition, inhibition within the primary cortex) and internal models (including the cerebellum).

Imagination can appeal to all our senses and may, therefore, manifest in very different qualities (e.g., visual, tactile, proprioceptive, or kinesthetic). One line of research addresses action imagery that refers to a process by which people imagine the execution of an action without actual body movements. In action imagery, visual and kinesthetic aspects of the imagined action are particularly important. However, other sensory modalities may also play a role. The purpose of the paper will be to address issues that include: (i) the creation of an action image, (ii) how the brain generates images of movements and actions, (iii) the richness and vividness of action images. We will further address possible causes that determine the sensory impression of an action image, like task specificity, instruction and experience. In the end, we will outline open questions and future directions.

(Eaves et al., Psychological Research Psychologische Forschung, 2022) summary review, showing positive behavioural effects of AOMI interventions, is a welcome addition to the field. Several recent studies, however, have reported that AOMI may be no more beneficial than independent MI, and, for some tasks, may add no benefit beyond that obtained via physical practice. We discuss evidence to balance the narrative but support the pragmatic reasons why AOMI remains a suitable and appealing form of action simulation. We propose that further research interrogation of the discrete AOMI states through a more continuum-based approach could address some of the inconsistent data seen in AOMI research.

Frank et al.'s (2023) perceptual-cognitive scaffold meaningfully extends the cognitive action architecture approach and we support this interdisciplinary advancement. However, there are theoretical and applied aspects that could be further developed within this research to maximise practical impact across domains such as sport. In particular, there is a need to consider how these mechanisms (1) might critically inform or relate to other prominent theories within sport (e.g., constrained action hypothesis and ecological approaches) and, (2) reflect the real-world challenges experienced by athletes. With these ideas in mind, this commentary aims to stimulate discussion and enhance the translational application of Frank et al.'s research.