Strange IndiaStrange India


  • 1.

    Miller, E. K. & Cohen, J. D. An integrative theory of prefrontal cortex function. Annu. Rev. Neurosci. 24, 167–202 (2001).

    CAS 
    Article 

    Google Scholar 

  • 2.

    Buschman, T. J. & Kastner, S. From behavior to neural dynamics: an integrated theory of attention. Neuron 88, 127–144 (2015).

    CAS 
    Article 

    Google Scholar 

  • 3.

    Buschman, T. J. & Miller, E. K. Top-down versus bottom-up control of attention in the prefrontal and posterior parietal cortices. Science 315, 1860–1862 (2007).

    ADS 
    CAS 
    Article 

    Google Scholar 

  • 4.

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

    ADS 
    CAS 
    Article 

    Google Scholar 

  • 5.

    Gazzaley, A. & Nobre, A. C. Top-down modulation: bridging selective attention and working memory. Trends Cogn. Sci. 16, 129–135 (2012).

    Article 

    Google Scholar 

  • 6.

    Sprague, T. C., Ester, E. F. & Serences, J. T. Restoring latent visual working memory representations in human cortex. Neuron 91, 694–707 (2016).

    CAS 
    Article 

    Google Scholar 

  • 7.

    Myers, N. E., Stokes, M. G. & Nobre, A. C. Prioritizing information during working memory: beyond sustained internal attention. Trends Cogn. Sci. 21, 449–461 (2017).

    Article 

    Google Scholar 

  • 8.

    Ester, E. F., Nouri, A. & Rodriguez, L. Retrospective cues mitigate information loss in human cortex during working memory storage. J. Neurosci. 38, 8538–8548 (2018).

    CAS 
    Article 

    Google Scholar 

  • 9.

    Nobre, A. C. et al. Orienting attention to locations in perceptual versus mental representations. J. Cogn. Neurosci. 16, 363–373 (2004).

    CAS 
    Article 

    Google Scholar 

  • 10.

    Murray, A. M., Nobre, A. C., Clark, I. A., Cravo, A. M. & Stokes, M. G. Attention restores discrete items to visual short-term memory. Psychol. Sci. 24, 550–556 (2013).

    Article 

    Google Scholar 

  • 11.

    Wilken, P. & Ma, W. J. A detection theory account of change detection. J. Vis. 4, 1120–1135 (2004).

    Article 

    Google Scholar 

  • 12.

    Zhang, W. & Luck, S. J. Discrete fixed-resolution representations in visual working memory. Nature 453, 233–235 (2008).

    ADS 
    CAS 
    Article 

    Google Scholar 

  • 13.

    Bays, P. M., Catalao, R. F. G. & Husain, M. The precision of visual working memory is set by allocation of a shared resource. J. Vis. 9, 7 (2009).

    Article 

    Google Scholar 

  • 14.

    Buschman, T. J., Siegel, M., Roy, J. E. & Miller, E. K. Neural substrates of cognitive capacity limitations. Proc. Natl Acad. Sci. USA 108, 11252–11255 (2011).

    ADS 
    CAS 
    Article 

    Google Scholar 

  • 15.

    Sprague, T. C., Ester, E. F. & Serences, J. T. Reconstructions of information in visual spatial working memory degrade with memory load. Curr. Biol. 24, 2174–2180 (2014).

    CAS 
    Article 

    Google Scholar 

  • 16.

    Bays, P. M. Spikes not slots: noise in neural populations limits working memory. Trends Cogn. Sci. 19, 431–438 (2015).

    Article 

    Google Scholar 

  • 17.

    Bouchacourt, F. & Buschman, T. J. A flexible model of working memory. Neuron 103, 147–160.e8 (2019).

    CAS 
    Article 

    Google Scholar 

  • 18.

    Pertzov, Y., Bays, P. M., Joseph, S. & Husain, M. Rapid forgetting prevented by retrospective attention cues. J. Exp. Psychol. Hum. Percept. Perform. 39, 1224–1231 (2013).

    Article 

    Google Scholar 

  • 19.

    Bays, P. M. & Taylor, R. A neural model of retrospective attention in visual working memory. Cognit. Psychol. 100, 43–52 (2018).

    Article 

    Google Scholar 

  • 20.

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

    CAS 
    Article 

    Google Scholar 

  • 21.

    Treue, S. & Maunsell, J. H. Attentional modulation of visual motion processing in cortical areas MT and MST. Nature 382, 539–541 (1996).

    ADS 
    CAS 
    Article 

    Google Scholar 

  • 22.

    Everling, S., Tinsley, C. J., Gaffan, D. & Duncan, J. Filtering of neural signals by focused attention in the monkey prefrontal cortex. Nat. Neurosci. 5, 671–676 (2002).

    CAS 
    Article 

    Google Scholar 

  • 23.

    Schneegans, S. & Bays, P. M. Restoration of fMRI decodability does not imply latent working memory states. J. Cogn. Neurosci. 29, 1977–1994 (2017).

    Article 

    Google Scholar 

  • 24.

    Nee, D. E. & Jonides, J. Common and distinct neural correlates of perceptual and memorial selection. Neuroimage 45, 963–975 (2009).

    Article 

    Google Scholar 

  • 25.

    Quentin, R. et al. Differential brain mechanisms of selection and maintenance of information during working memory. J. Neurosci. 39, 3728–3740 (2019).

    Article 

    Google Scholar 

  • 26.

    Bernardi, S. et al. The geometry of abstraction in the hippocampus and prefrontal cortex. Cell 183, 954–967.e21 (2020).

    CAS 
    Article 

    Google Scholar 

  • 27.

    Rigotti, M. et al. The importance of mixed selectivity in complex cognitive tasks. Nature 497, 585–590 (2013).

    ADS 
    CAS 
    Article 

    Google Scholar 

  • 28.

    Reynolds, J. H., Chelazzi, L. & Desimone, R. Competitive mechanisms subserve attention in macaque areas V2 and V4. J. Neurosci. 19, 1736–1753 (1999).

    CAS 
    Article 

    Google Scholar 

  • 29.

    Reynolds, J. H. & Heeger, D. J. The normalization model of attention. Neuron 61, 168–185 (2009).

    CAS 
    Article 

    Google Scholar 

  • 30.

    Panichello, M. F., DePasquale, B., Pillow, J. W. & Buschman, T. J. Error-correcting dynamics in visual working memory. Nat. Commun. 10, 3366 (2019).

    ADS 
    Article 

    Google Scholar 

  • 31.

    Bruce, C. J. & Goldberg, M. E. Primate frontal eye fields. I. Single neurons discharging before saccades. J. Neurophysiol. 53, 603–635 (1985).

    CAS 
    Article 

    Google Scholar 

  • 32.

    Rolston, J. D., Gross, R. E. & Potter, S. M. Common median referencing for improved action potential detection with multielectrode arrays. Annu. Int. Conf. IEEE Eng. Med. Biol. Soc. 2009, 1604–1607 (2009).

    PubMed 

    Google Scholar 

  • 33.

    Wessberg, J. et al. Real-time prediction of hand trajectory by ensembles of cortical neurons in primates. Nature 408, 361–365 (2000).

    ADS 
    CAS 
    Article 

    Google Scholar 

  • 34.

    Tort, A. B. L., Komorowski, R., Eichenbaum, H. & Kopell, N. Measuring phase-amplitude coupling between neuronal oscillations of different frequencies. J. Neurophysiol. 104, 1195–1210 (2010).

    Article 

    Google Scholar 

  • 35.

    Maris, E. & Oostenveld, R. Nonparametric statistical testing of EEG- and MEG-data. J. Neurosci. Methods 164, 177–190 (2007).

    Article 

    Google Scholar 

  • 36.

    Murray, J. D. et al. Stable population coding for working memory coexists with heterogeneous neural dynamics in prefrontal cortex. Proc. Natl Acad. Sci. USA 114, 394–399 (2017).

    CAS 
    Article 

    Google Scholar 



  • Source link

    By AUTHOR

    Leave a Reply

    Your email address will not be published. Required fields are marked *