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How the brain blinks: towards a neurocognitive model of the attentional blink

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Abstract

When people monitor a visual stream of rapidly presented stimuli for two targets (T1 and T2), they often miss T2 if it falls into a time window of about half a second after T1 onset—the attentional blink (AB). We provide an overview of recent neuroscientific studies devoted to analyze the neural processes underlying the AB and their temporal dynamics. The available evidence points to an attentional network involving temporal, right-parietal and frontal cortex, and suggests that the components of this neural network interact by means of synchronization and stimulus-induced desynchronization in the beta frequency range. We set up a neurocognitive scenario describing how the AB might emerge and why it depends on the presence of masks and the other event(s) the targets are embedded in. The scenario supports the idea that the AB arises from “biased competition”, with the top–down bias being generated by parietal–frontal interactions and the competition taking place between stimulus codes in temporal cortex.

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Notes

  1. To be more precise, phase synchronization was observed in the beta-band at a frequency of about 15 Hz. Beta synchronization is known to play an important role in attentional processes in general (Liang et al. 2002; Wrobel 2000) and in coupling temporal and parietal areas during object processing in particular (Von Stein et al. 1999). Also, simulation studies show that the beta frequency has characteristics that are favorable for long-range interactions, in contrast to the gamma frequency band that is optimal for local processing (Bibbig et al. 2002; Kopell et al. 2000). However, note that the frequency of 15 Hz is close to the first harmonic of the stimulus presentation frequency in the study of Gross et al. (2004) (6.85 Hz), which may suggest that synchronization frequencies are not specific to the operation mode of the communicating network but to the temporal characteristics of the events the communication refers to. In any case, the findings of Gross et al. (2004) do not support the claims of Dehaene et al. (2003) and Fell et al. (2002) that gamma-band oscillations play a crucial role in the AB.

  2. The SI quantifies the phase coupling between different regions. It is computed as the absolute value of the sum of the complex phase differences of both regions divided by the number of epochs and is bounded between 0 (indicating no phase locking) and 1 (indicating perfect phase locking). For further details, see Gross et al. (2004).

  3. The functional reason for why the system is restricted to, or at least better off focusing communication on one topic at a time may be that this solves one of the many binding problems (Treisman 1996) that distributed systems face. Technically speaking, it may well be possible that different subgroups of codes lead concurrent “private discussions” (to stay with the communication metaphor) but that would make it very hard for a global operation to tell relevant discussions (the outcome of which needs to be considered) from useless babble. This is why members of parliaments commonly agree on sequentially organized contributions.

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Acknowledgements

Support for this research by Volkswagenstiftung in the form of a project grant to BH, KS, and AS is gratefully acknowledged. We are also grateful to Andre Achim, Pierre Jolicœur, and an anonymous reviewer for helpful comments on a previous version of this paper. Correspondence and requests for materials should be addressed to Bernhard Hommel, Leiden University, Department of Psychology, Cognitive Psychology Unit, Postbus 9555, 2300 RB Leiden, The Netherlands; hommel@fsw.leidenuniv.nl.

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Hommel, B., Kessler, K., Schmitz, F. et al. How the brain blinks: towards a neurocognitive model of the attentional blink. Psychological Research 70, 425–435 (2006). https://doi.org/10.1007/s00426-005-0009-3

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