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Task-specific signal transmission from prefrontal cortex in visual selective attention

Nature Neuroscience volume 12, pages 8591 (2009) | Download Citation

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Abstract

Our voluntary behaviors are thought to be controlled by top-down signals from the prefrontal cortex that modulate neural processing in the posterior cortices according to the behavioral goal. However, we have insufficient evidence for the causal effect of the top-down signals. We applied a single-pulse transcranial magnetic stimulation over the human prefrontal cortex and measured the strength of the top-down signals as an increase in the efficiency of neural impulse transmission. The impulse induced by the stimulation transmitted to different posterior visual areas depending on the domain of visual features to which subjects attended. We also found that the amount of impulse transmission was associated with the level of attentional preparation and the performance of visual selective-attention tasks, consistent with the causal role of prefrontal top-down signals.

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References

  1. 1.

    & Neural mechanisms of selective visual attention. Annu. Rev. Neurosci. 18, 193–222 (1995).

  2. 2.

    & Mechanisms of visual attention in the human cortex. Annu. Rev. Neurosci. 23, 315–341 (2000).

  3. 3.

    & An integrative theory of prefrontal cortex function. Annu. Rev. Neurosci. 24, 167–202 (2001).

  4. 4.

    & Control of goal-directed and stimulus-driven attention in the brain. Nat. Rev. Neurosci. 3, 201–215 (2002).

  5. 5.

    & Selective attention gates visual processing in the extrastriate cortex. Science 229, 782–784 (1985).

  6. 6.

    & Attentional modulation of visual processing. Annu. Rev. Neurosci. 27, 611–647 (2004).

  7. 7.

    & Feature-based attention in visual cortex. Trends Neurosci. 29, 317–322 (2006).

  8. 8.

    , , , & Who comes first? The role of the prefrontal and parietal cortex in cognitive control. J. Cogn. Neurosci. 17, 1367–1375 (2005).

  9. 9.

    & Timing and sequence of brain activity in top-down control of visual-spatial attention. PLoS Biol. 5, e12 (2007).

  10. 10.

    & Modulation of connectivity in visual pathways by attention: cortical interactions evaluated with structural equation modeling and fMRI. Cereb. Cortex 7, 768–778 (1997).

  11. 11.

    & Prefrontal interactions reflect future task operations. Nat. Neurosci. 6, 75–81 (2003).

  12. 12.

    & Prefrontal set activity predicts rule-specific neural processing during subsequent cognitive performance. J. Neurosci. 26, 1211–1218 (2006).

  13. 13.

    , & Functional interactions between inferotemporal and prefrontal cortex in a cognitive task. Brain Res. 330, 299–307 (1985).

  14. 14.

    , , , & Top-down signal from prefrontal cortex in executive control of memory retrieval. Nature 401, 699–703 (1999).

  15. 15.

    , & Prefrontal modulation of visual processing in humans. Nat. Neurosci. 3, 399–403 (2000).

  16. 16.

    , & FEF TMS affects visual cortical activity. Cereb. Cortex 17, 391–399 (2007).

  17. 17.

    , & Subsecond changes in top down control exerted by human medial frontal cortex during conflict and action selection: a combined transcranial magnetic stimulation electroencephalography study. J. Neurosci. 27, 11343–11353 (2007).

  18. 18.

    & Selective gating of visual signals by microstimulation of frontal cortex. Nature 421, 370–373 (2003).

  19. 19.

    & Rapid enhancement of visual cortical response discriminability by microstimulation of the frontal eye field. Proc. Natl. Acad. Sci. USA 104, 9499–9504 (2007).

  20. 20.

    , & Stimulation of the human frontal eye fields modulates sensitivity of extrastriate visual cortex. J. Neurophysiol. 96, 941–945 (2006).

  21. 21.

    , & Cortical regions involved in eye movements, shifts of attention and gaze perception. Hum. Brain Mapp. 25, 140–154 (2005).

  22. 22.

    et al. Neuronal responses to magnetic stimulation reveal cortical reactivity and connectivity. Neuroreport 8, 3537–3540 (1997).

  23. 23.

    & Fast backprojections from the motion to the primary visual area necessary for visual awareness. Science 292, 510–512 (2001).

  24. 24.

    et al. Functional connectivity in human cortical motor system: a cortico-cortical evoked potential study. Brain 130, 181–197 (2007).

  25. 25.

    et al. Low-resolution brain electromagnetic tomography (LORETA) functional imaging in acute, neuroleptic-naive, first-episode, productive schizophrenia. Psychiatry Res. 90, 169–179 (1999).

  26. 26.

    et al. Functional analysis of human MT and related visual cortical areas using magnetic resonance imaging. J. Neurosci. 15, 3215–3230 (1995).

  27. 27.

    , & The fusiform face area: a module in human extrastriate cortex specialized for face perception. J. Neurosci. 17, 4302–4311 (1997).

  28. 28.

    et al. Ethanol modulates cortical activity: direct evidence with combined TMS and EEG. Neuroimage 14, 322–328 (2001).

  29. 29.

    & Transcranial magnetic stimulation of the human frontal eye field: effects on visual perception and attention. J. Cogn. Neurosci. 14, 1109–1120 (2002).

  30. 30.

    & Transcranial magnetic stimulation of the human frontal eye field facilitates visual awareness. Eur. J. Neurosci. 18, 3121–3126 (2003).

  31. 31.

    , , & Timing of target discrimination in human frontal eye fields. J. Cogn. Neurosci. 16, 1060–1067 (2004).

  32. 32.

    , , & Human frontal eye fields and spatial priming of pop-out. J. Cogn. Neurosci. 19, 1140–1151 (2007).

  33. 33.

    & Effects of similarity and history on neural mechanisms of visual selection. Nat. Neurosci. 2, 549–554 (1999).

  34. 34.

    & A visual salience map in the primate frontal eye field. Prog. Brain Res. 147, 251–262 (2005).

  35. 35.

    , , , & Shape selectivity in primate frontal eye field. J. Neurophysiol. 100, 796–814 (2008).

  36. 36.

    , & Topography of projections to posterior cortical areas from the macaque frontal eye fields. J. Comp. Neurol. 353, 291–305 (1995).

  37. 37.

    et al. Neural integration of top-down spatial and feature-based information in visual search. J. Neurosci. 28, 6141–6151 (2008).

  38. 38.

    , , , & Neuronal oscillations and multisensory interaction in primary auditory cortex. Neuron 53, 279–292 (2007).

  39. 39.

    , , , & Entrainment of neuronal oscillations as a mechanism of attentional selection. Science 320, 110–113 (2008).

  40. 40.

    et al. Investigating the neural basis for functional and effective connectivity. Application to fMRI. Phil. Trans. R. Soc. Lond. B 360, 1093–1108 (2005).

  41. 41.

    , , , & Cortico-cortical interactions in spatial attention: a combined ERP/TMS study. J. Neurophysiol. 95, 3277–3280 (2006).

  42. 42.

    et al. Breakdown of cortical effective connectivity during sleep. Science 309, 2228–2232 (2005).

  43. 43.

    , & Attention lights up new object representations before the old ones fade away. J. Neurosci. 26, 138–142 (2006).

  44. 44.

    , & Different processing phases for features, figures and selective attention in the primary visual cortex. Neuron 56, 785–792 (2007).

  45. 45.

    , , , & Electrophysiological studies of face perception in humans. J. Cogn. Neurosci. 8, 551–565 (1996).

  46. 46.

    , , & The pupil as a measure of emotional arousal and autonomic activation. Psychophysiology 45, 602–607 (2008).

  47. 47.

    & EEGLAB: an open source toolbox for analysis of single-trial EEG dynamics including independent component analysis. J. Neurosci. Methods 134, 9–21 (2004).

  48. 48.

    , & The role of the coil click in TMS assessed with simultaneous EEG. Clin. Neurophysiol. 110, 1325–1328 (1999).

  49. 49.

    et al. The spatial location of EEG electrodes: locating the best-fitting sphere relative to cortical anatomy. Electroencephalogr. Clin. Neurophysiol. 86, 1–6 (1993).

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Acknowledgements

We thank M. Okamoto and N. Yamamoto for assistance with EEG recording. This work was supported by a Grant-in-Aid for Scientific Research (A) and a Grant-in-Aid for Young Scientists (S) from the Japan Society for the Promotion of Science, and a Grant-in-Aid from the Center of Excellence Program, Center for Brain Medical Science, from the Ministry of Education, Culture, Sports, Science and Technology, Japan.

Author information

Affiliations

  1. Department of Cognitive Neuroscience, Graduate School of Medicine, University of Tokyo, Hongo 7-3-1, Bunkyo-ku, Tokyo, Japan, 113-0033.

    • Yosuke Morishima
    • , Rei Akaishi
    • , Yohei Yamada
    • , Keiichiro Toma
    •  & Katsuyuki Sakai
  2. Brain Science Institute, Tamagawa University, Tamagawa-gakuen 6-1-1, Machida-shi, Tokyo, Japan, 194-8610.

    • Jiro Okuda

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Contributions

Y.M. designed the task, conducted the experiments and analyzed the data. R.A., Y.Y., J.O. and K.T. contributed to the experiments and analysis. K.S. conceptualized the original idea for the study. Y.M. and K.S. wrote the paper.

Corresponding author

Correspondence to Katsuyuki Sakai.

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https://doi.org/10.1038/nn.2237

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