Markus Ostarek

Publications

Displaying 1 - 8 of 8
  • Kochari, A. R., & Ostarek, M. (2018). Introducing a replication-first rule for PhD projects (commmentary on Zwaan et al., ‘Making replication mainstream’). Behavioral and Brain Sciences, 41: e138. doi:10.1017/S0140525X18000730.

    Abstract

    Zwaan et al. mention that young researchers should conduct replications as a small part of their portfolio. We extend this proposal and suggest that conducting and reporting replications should become an integral part of PhD projects and be taken into account in their assessment. We discuss how this would help not only scientific advancement, but also PhD candidates’ careers.
  • Ostarek, M. (2018). Envisioning language: An exploration of perceptual processes in language comprehension. PhD Thesis, Radboud University Nijmegen, Nijmegen.
  • Ostarek, M., Ishag, I., Joosen, D., & Huettig, F. (2018). Saccade trajectories reveal dynamic interactions of semantic and spatial information during the processing of implicitly spatial words. Journal of Experimental Psychology: Learning, Memory, and Cognition, 44(10), 1658-1670. doi:10.1037/xlm0000536.

    Abstract

    Implicit up/down words, such as bird and foot, systematically influence performance on visual tasks involving immediately following targets in compatible vs. incompatible locations. Recent studies have observed that the semantic relation between prime words and target pictures can strongly influence the size and even the direction of the effect: Semantically related targets are processed faster in congruent vs. incongruent locations (location-specific priming), whereas unrelated targets are processed slower in congruent locations. Here, we used eye-tracking to investigate the moment-to-moment processes underlying this pattern. Our reaction time results for related targets replicated the location-specific priming effect and showed a trend towards interference for unrelated targets. We then used growth curve analysis to test how up/down words and their match vs. mismatch with immediately following targets in terms of semantics and vertical location influences concurrent saccadic eye movements. There was a strong main effect of spatial association on linear growth with up words biasing changes in y-coordinates over time upwards relative to down words (and vice versa). Similar to the RT data, this effect was strongest for semantically related targets and reversed for unrelated targets. Intriguingly, all conditions showed a bias in the congruent direction in the initial stage of the saccade. Then, at around halfway into the saccade the effect kept increasing in the semantically related condition, and reversed in the unrelated condition. These results suggest that online processing of up/down words triggers direction-specific oculomotor processes that are dynamically modulated by the semantic relation between prime words and targets.
  • Popov, V., Ostarek, M., & Tenison, C. (2018). Practices and pitfalls in inferring neural representations. NeuroImage, 174, 340-351. doi:10.1016/j.neuroimage.2018.03.041.

    Abstract

    A key challenge for cognitive neuroscience is deciphering the representational schemes of the brain. Stimulus-feature-based encoding models are becoming increasingly popular for inferring the dimensions of neural representational spaces from stimulus-feature spaces. We argue that such inferences are not always valid because successful prediction can occur even if the two representational spaces use different, but correlated, representational schemes. We support this claim with three simulations in which we achieved high prediction accuracy despite systematic differences in the geometries and dimensions of the underlying representations. Detailed analysis of the encoding models' predictions showed systematic deviations from ground-truth, indicating that high prediction accuracy is insufficient for making representational inferences. This fallacy applies to the prediction of actual neural patterns from stimulus-feature spaces and we urge caution in inferring the nature of the neural code from such methods. We discuss ways to overcome these inferential limitations, including model comparison, absolute model performance, visualization techniques and attentional modulation.
  • Ostarek, M., & Huettig, F. (2017). A task-dependent causal role for low-level visual processes in spoken word comprehension. Journal of Experimental Psychology: Learning, Memory, and Cognition, 43(8), 1215-1224. doi:10.1037/xlm0000375.

    Abstract

    It is well established that the comprehension of spoken words referring to object concepts relies on high-level visual areas in the ventral stream that build increasingly abstract representations. It is much less clear whether basic low-level visual representations are also involved. Here we asked in what task situations low-level visual representations contribute functionally to concrete word comprehension using an interference paradigm. We interfered with basic visual processing while participants performed a concreteness task (Experiment 1), a lexical decision task (Experiment 2), and a word class judgment task (Experiment 3). We found that visual noise interfered more with concrete vs. abstract word processing, but only when the task required visual information to be accessed. This suggests that basic visual processes can be causally involved in language comprehension, but that their recruitment is not automatic and rather depends on the type of information that is required in a given task situation.

    Additional information

    XLM-2016-2822_supp.docx
  • Ostarek, M., & Vigliocco, G. (2017). Reading sky and seeing a cloud: On the relevance of events for perceptual simulation. Journal of Experimental Psychology: Learning, Memory, and Cognition, 43(4), 579-590. doi:10.1037/xlm0000318.

    Abstract

    Previous research has shown that processing words with an up/down association (e.g., bird, foot) can influence the subsequent identification of visual targets in congruent location (at the top/bottom of the screen). However, as facilitation and interference were found under similar conditions, the nature of the underlying mechanisms remained unclear. We propose that word comprehension relies on the perceptual simulation of a prototypical event involving the entity denoted by a word in order to provide a general account of the different findings. In three experiments, participants had to discriminate between two target pictures appearing at the top or the bottom of the screen by pressing the left vs. right button. Immediately before the targets appeared, they saw an up/down word belonging to the target’s event, an up/down word unrelated to the target, or a spatially neutral control word. Prime words belonging to target event facilitated identification of targets at 250ms SOA (experiment 1), but only when presented in the vertical location where they are typically seen, indicating that targets were integrated in the simulations activated by the prime words. Moreover, at the same SOA, there was a robust facilitation effect for targets appearing in their typical location regardless of the prime type. However, when words were presented for 100ms (experiment 2) or 800ms (experiment 3), only a location non-specific priming effect was found, suggesting that the visual system was not activated. Implications for theories of semantic processing are discussed.
  • Ostarek, M., & Huettig, F. (2017). Spoken words can make the invisible visible – Testing the involvement of low-level visual representations in spoken word processing. Journal of Experimental Psychology: Human Perception and Performance, 43, 499-508. doi:10.1037/xhp0000313.

    Abstract

    The notion that processing spoken (object) words involves activation of category-specific representations in visual cortex is a key prediction of modality-specific theories of representation that contrasts with theories assuming dedicated conceptual representational systems abstracted away from sensorimotor systems. In the present study, we investigated whether participants can detect otherwise invisible pictures of objects when they are presented with the corresponding spoken word shortly before the picture appears. Our results showed facilitated detection for congruent ("bottle" -> picture of a bottle) vs. incongruent ("bottle" -> picture of a banana) trials. A second experiment investigated the time-course of the effect by manipulating the timing of picture presentation relative to word onset and revealed that it arises as soon as 200-400ms after word onset and decays at 600ms after word onset. Together, these data strongly suggest that spoken words can rapidly activate low-level category-specific visual representations that affect the mere detection of a stimulus, i.e. what we see. More generally our findings fit best with the notion that spoken words activate modality-specific visual representations that are low-level enough to provide information related to a given token and at the same time abstract enough to be relevant not only for previously seen tokens but also for generalizing to novel exemplars one has never seen before.
  • Popov, V., Ostarek, M., & Tenison, C. (2017). Inferential Pitfalls in Decoding Neural Representations. In G. Gunzelmann, A. Howes, T. Tenbrink, & E. Davelaar (Eds.), Proceedings of the 39th Annual Conference of the Cognitive Science Society (CogSci 2017) (pp. 961-966). Austin, TX: Cognitive Science Society.

    Abstract

    A key challenge for cognitive neuroscience is to decipher the representational schemes of the brain. A recent class of decoding algorithms for fMRI data, stimulus-feature-based encoding models, is becoming increasingly popular for inferring the dimensions of neural representational spaces from stimulus-feature spaces. We argue that such inferences are not always valid, because decoding can occur even if the neural representational space and the stimulus-feature space use different representational schemes. This can happen when there is a systematic mapping between them. In a simulation, we successfully decoded the binary representation of numbers from their decimal features. Since binary and decimal number systems use different representations, we cannot conclude that the binary representation encodes decimal features. The same argument applies to the decoding of neural patterns from stimulus-feature spaces and we urge caution in inferring the nature of the neural code from such methods. We discuss ways to overcome these inferential limitations.

Share this page