No abstract

Every moment organisms are confronted with complex streams of information which they use to generate a reliable mental model of the world. There is converging evidence for several optimization mechanisms instrumental in integrating (or segregating) incoming information; among them are multisensory interplay (MSI) and temporal expectation (TE). Both mechanisms can account for enhanced perceptual sensitivity and are well studied in isolation; how these two mechanisms interact is currently less well-known. Here, we tested in a series of four psychophysical experiments for TE effects in uni- and multisensory contexts with different levels of modality-related and spatial uncertainty. We found that TE enhanced perceptual sensitivity for the multisensory relative to the best unisensory condition (i.e. multisensory facilitation according to the max-criterion). In the latter TE effects even vanished if stimulus-related spatial uncertainty was increased. Accordingly, computational modelling indicated that TE, modality-related and spatial uncertainty predict multisensory facilitation. Finally, the analysis of stimulus history revealed that matching expectation at trial n-1 selectively improves multisensory performance irrespective of stimulus-related uncertainty. Together, our results indicate that benefits of multisensory stimulation are enhanced by TE especially in noisy environments, which allows for more robust information extraction to boost performance on both short and sustained time ranges.

Only small amounts of visual information, as determined by the capacity of working memory, can be held in an active and accessible state. Thus, it is important to select and maintain information that is relevant while ignoring irrelevant information. However, the underlying neural mechanism of these processes has yet to be identified. One potential candidate are alpha oscillations (8-14 Hz), which have been shown to inhibit stimulus processing in perceptual tasks. During memory maintenance, alpha power increases with set size suggesting that alpha oscillations are involved either in memory maintenance or in the inhibition of task-irrelevant information to protect relevant information from interference. The need for such a protection should increase with the amount of distracting information, but most previous studies did not show any distractors. Therefore, we directly tested whether alpha oscillations are involved in inhibition of distractors during memory maintenance. Participants memorized the orientation of one or two target lines embedded among irrelevant distractors. Distractors were either strong or weak and were present during the retention interval after which participants reported the orientation of probed targets. Computational modeling showed that performance decreased with increasing set size and stronger distraction. Alpha power in the retention interval generally increased with set size, replicating previous studies. However, here stronger distractors reduced alpha power. This finding is in clear contradistinction to previous suggestions, as alpha power decrease indicates higher neuronal excitability. Thus, our data do not support the suggested role of alpha oscillations in inhibition of distraction in working memory.

Learning the statistical regularities of environmental events is a powerful tool for enhancing performance. However, it remains unclear whether this often implicit type of behavioral facilitation can be proactively modulated by explicit knowledge about temporal regularities. Only recently, Menceloglu and colleagues (Attention, Perception & Psychophysics, 79(1), 169-179, 2017) tested for differences between implicit versus explicit statistical learning of temporal regularities by using a within-paradigm manipulation of metacognitive temporal knowledge. The authors reported that temporal expectations were enhanced if participants had explicit knowledge about temporal regularities. Here, we attempted to replicate and extend their results, and to provide a mechanistic framework for any effects by means of computational modelling. Participants performed a letter-discrimination task, with target letters embedded in congruent or incongruent flankers. Temporal predictability was manipulated block-wise, with targets occurring more often after either a short or a long delay period. During the delay a sound was presented in half of the trials. Explicit knowledge about temporal regularities was manipulated by changing instructions: Participants received no information (implicit), information about the most likely cue-target delay (explicit), or received 100% valid cues on each trial (highly explicit). We replicated previous effects of target-flanker congruence and sound presence. However, no evidence was found for an effect of explicit knowledge on temporal expectations using Bayesian statistics. Concordantly, computational modelling suggested that explicit knowledge may only influence non-perceptual processing such as response criteria. Together, our results indicate that explicit metacognitive knowledge does not necessarily alter sensory representations or temporal expectations but rather affects response strategies.