Publications

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  • 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.
  • 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.
  • 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.

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