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Prefrontal cortex and sensory cortices during working memory: quantity and quality

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Abstract

The activity in sensory cortices and the prefrontal cortex (PFC) throughout the delay interval of working memory (WM) tasks reflect two aspects of WM—quality and quantity, respectively. The delay activity in sensory cortices is fine-tuned to sensory information and forms the neural basis of the precision of WM storage, while the delay activity in the PFC appears to represent behavioral goals and filters out irrelevant distractions, forming the neural basis of the quantity of task-relevant information in WM. The PFC and sensory cortices interact through different frequency bands of neuronal oscillation (theta, alpha, and gamma) to fulfill goal-directed behaviors.

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References

  1. Baddeley A. Working memory: theories, models, and controversies. Annu Rev Psychol 2012, 63: 1–29.

    Article  PubMed  Google Scholar 

  2. Baddeley A. Working memory: looking back and looking forward. Nat Rev Neurosci 2003, 4: 829–839.

    Article  CAS  PubMed  Google Scholar 

  3. Goldman-Rakic PS. Cellular basis of working memory. Neuron 1995, 14: 477–485.

    Article  CAS  PubMed  Google Scholar 

  4. Curtis CE, D’Esposito M. Persistent activity in the prefrontal cortex during working memory. Trends Cogn Sci 2003, 7: 415–423.

    Article  PubMed  Google Scholar 

  5. Sreenivasan KK, Curtis CE, D’Esposito M. Revisiting the role of persistent neural activity during working memory. Trends Cogn Sci 2014, 18: 82–89.

    Article  PubMed Central  PubMed  Google Scholar 

  6. Miller EK, Cohen JD. An integrative theory of prefrontal cortex function. Annu Rev Neurosci 2001, 24: 167–202.

    Article  CAS  PubMed  Google Scholar 

  7. Ruff CC. Sensory processing: who’s in (top-down) control? Ann NY Acad Sci 2013, 1296: 88–107.

    Article  PubMed  Google Scholar 

  8. Miller GA. The magical number seven, plus or minus two: some limits on our capacity for processing information. Psychol Rev 1956, 63: 81.

    Article  CAS  PubMed  Google Scholar 

  9. Cowan N. The magical number 4 in short-term memory: a reconsideration of mental storage capacity. Behav Brain Sci 2001, 24: 87–114.

    Article  CAS  PubMed  Google Scholar 

  10. Engle RW, Tuholski SW, Laughlin JE, Conway ARA. Working memory, short-term memory, and general fluid intelligence: A latent-variable approach. J Exp Psychol Gen 1999, 128: 309–331.

    Article  CAS  PubMed  Google Scholar 

  11. Johnson MK, McMahon RP, Robinson BM, Harvey AN, Hahn B, Leonard CJ, et al. The relationship between working memory capacity and broad measures of cognitive ability in healthy adults and people with schizophrenia. Neuropsychology 2013, 27: 220–229.

    Article  PubMed Central  PubMed  Google Scholar 

  12. Zhang W, Luck SJ. Discrete fixed-resolution representations in visual working memory. Nature 2008, 453: 233–235.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  13. Bays PM, Husain M. Dynamic shifts of limited working memory resources in human vision. Science 2008, 321: 851–854.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  14. Fukuda K, Awh E, Vogel EK. Discrete capacity limits in visual working memory. Curr Opin Neurobiol 2010, 20: 177–182.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  15. Luck SJ, Vogel EK. Visual working memory capacity: from psychophysics and neurobiology to individual differences. Trends Cogn Sci 2013, 17: 391–400.

    Article  PubMed Central  PubMed  Google Scholar 

  16. Ma WJ, Husain M, Bays PM. Changing concepts of working memory. Nat Neurosci 2014, 17: 347–356.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  17. Romo R, Salinas E. Flutter discrimination: neural codes, perception, memory and decision making. Nat Rev Neurosci 2003, 4: 203–218.

    Article  CAS  PubMed  Google Scholar 

  18. Miller EK, Erickson CA, Desimone R. Neural mechanisms of visual working memory in prefrontal cortex of the macaque. J Neurosci 1996, 16: 5154–5167.

    CAS  PubMed  Google Scholar 

  19. Pasternak T, Greenlee MW. Working memory in primate sensory systems. Nat Rev Neurosci 2005, 6: 97–107.

    Article  CAS  PubMed  Google Scholar 

  20. Offen S, Schluppeck D, Heeger DJ. The role of early visual cortex in visual short-term memory and visual attention. Vis Res 2009, 49: 1352–1362.

    Article  PubMed Central  PubMed  Google Scholar 

  21. Bisley JW, Zaksas D, Droll JA, Pasternak T. Activity of neurons in cortical area MT during a memory for motion task. J Neurophysiol 2004, 91: 286–300.

    Article  PubMed  Google Scholar 

  22. Romo R, Brody CD, Hernández A, Lemus L. Neuronal correlates of parametric working memory in the prefrontal cortex. Nature 1999, 399: 470–473.

    Article  CAS  PubMed  Google Scholar 

  23. Salinas E, Hernández A, Zainos A, Romo R. Periodicity and firing rate as candidate neural codes for the frequency of vibrotactile stimuli. J Neurosci 2000, 20: 5503–5515.

    CAS  PubMed  Google Scholar 

  24. Luna R, Hernández A, Brody CD, Romo R. Neural codes for perceptual discrimination in primary somatosensory cortex. Nat Neurosci 2005, 8: 1210–1219.

    Article  CAS  PubMed  Google Scholar 

  25. Super H, Spekreijse H, Lamme VA. A neural correlate of working memory in the monkey primary visual cortex. Science 2001, 293: 120–124.

    Article  CAS  PubMed  Google Scholar 

  26. Zhou YD, Fuster JM. Mnemonic neuronal activity in somatosensory cortex. Proc Natl Acad Sci U S A 1996, 93: 10533–10537.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  27. Haynes JD, Rees G. Decoding mental states from brain activity in humans. Nat Rev Neurosci 2006, 7: 523–534.

    Article  CAS  PubMed  Google Scholar 

  28. Davis T, Poldrack RA. Measuring neural representations with fMRI: practices and pitfalls. Ann NY Acad Sci 2013, 1296: 108–134.

    Article  PubMed  Google Scholar 

  29. Harrison SA, Tong F. Decoding reveals the contents of visual working memory in early visual areas. Nature 2009, 458: 632–635.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  30. Serences JT, Ester EF, Vogel EK, Awh E. Stimulus-specific delay activity in human primary visual cortex. Psychol Sci 2009, 20: 207–214.

    Article  PubMed Central  PubMed  Google Scholar 

  31. Riggall AC, Postle BR. The relationship between working memory storage and elevated activity as measured with functional magnetic resonance imaging. J Neurosci 2012, 32: 12990–12998.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  32. Emrich SM, Riggall AC, LaRocque JJ, Postle BR. Distributed patterns of activity in sensory cortex reflect the precision of multiple items maintained in visual short-term memory. J Neurosci 2013, 33: 6516–6523.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  33. Lee SH, Kravitz DJ, Baker CI. Goal-dependent dissociation of visual and prefrontal cortices during working memory. Nat Neurosci 2013, 16: 997–999.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  34. Zhou YD, Fuster JM. Visuo-tactile cross-modal associations in cortical somatosensory cells. Proc Natl Acad Sci U S A 2000, 97: 9777–9782.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  35. Ku Y, Ohara S, Wang L, Lenz FA, Hsiao SS, Bodner M, et al. Prefrontal cortex and somatosensory cortex in tactile crossmodal association: an independent component analysis of ERP recordings. PLoS One 2007, 2: e771.

    Article  PubMed Central  PubMed  Google Scholar 

  36. Ku Y, Zhao D, Hao N, Hu Y, Bodner M, Zhou YD. Sequential roles of primary somatosensory cortex and posterior parietal cortex in tactile-visual cross-modal working memory: a singlepulse transcranial magnetic stimulation (spTMS) study. Brain Stimul 2015, 8: 88–91.

    Article  PubMed  Google Scholar 

  37. Christophel TB, Haynes JD. Decoding complex flow-field patterns in visual working memory. Neuroimage 2014, 91: 43–51.

    Article  PubMed  Google Scholar 

  38. Fuster JM, Alexander GE. Neuron activity related to shortterm memory. Science 1971, 173: 652–654.

    Article  CAS  PubMed  Google Scholar 

  39. D’Esposito M, Detre JA, Alsop DC, Shin RK, Atlas S, Grossman M. The neural basis of the central executive system of working memory. Nature 1995, 378: 279–281.

    Article  PubMed  Google Scholar 

  40. Smith EE, Jonides J. Storage and executive processes in the frontal lobes. Science 1999, 283: 1657–1661.

    Article  CAS  PubMed  Google Scholar 

  41. Xu Y, Chun MM. Dissociable neural mechanisms supporting visual short-term memory for objects. Nature 2006, 440: 91–95.

    Article  CAS  PubMed  Google Scholar 

  42. Vogel EK, Machizawa MG. Neural activity predicts individual differences in visual working memory capacity. Nature 2004, 428: 748–751.

    Article  CAS  PubMed  Google Scholar 

  43. Todd JJ, Marois R. Capacity limit of visual short-term memory in human posterior parietal cortex. Nature 2004, 428: 751–754.

    Article  CAS  PubMed  Google Scholar 

  44. Vogel EK, McCollough AW, Machizawa MG. Neural measures reveal individual differences in controlling access to working memory. Nature 2005, 438: 500–503.

    Article  CAS  PubMed  Google Scholar 

  45. McNab F, Klingberg T. Prefrontal cortex and basal ganglia control access to working memory. Nat Neurosci 2008, 11: 103–107.

    Article  CAS  PubMed  Google Scholar 

  46. Reinhart RMG, Heitz RP, Purcell BA, Weigand PK, Schall JD, Woodman GF. Homologous mechanisms of visuospatial working memory maintenance in macaque and human: properties and sources. J Neurosci 2012, 32: 7711–7722.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  47. Buschman TJ, Siegel M, Roy JE, Miller EK. Neural substrates of cognitive capacity limitations. Proc Natl Acad Sci USA 2011, 108: 11252–11255.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  48. Viswanathan P, Nieder A. Neuronal correlates of a visual “sense of number” in primate parietal and prefrontal cortices. Proc Natl Acad Sci U S A 2013, 110: 11187–11192.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  49. Nieder A. Supramodal numerosity selectivity of neurons in primate prefrontal and posterior parietal cortices. Proc Natl Acad Sci U S A 2012, 109: 11860–11865.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  50. Charron S, Koechlin E. Divided representation of concurrent goals in the human frontal lobes. Science 2010, 328: 360–363.

    Article  CAS  PubMed  Google Scholar 

  51. Badre D. Cognitive control, hierarchy, and the rostro-caudal organization of the frontal lobes. Trends Cogn Sci 2008, 12: 193–200.

    Article  PubMed  Google Scholar 

  52. Varela F, Lachaux JP, Rodriguez E, Martinerie J. The brainweb: phase synchronization and large-scale integration. Nat Rev Neurosci 2001, 2: 229–239.

    Article  CAS  PubMed  Google Scholar 

  53. Klimesch W. EEG alpha and theta oscillations reflect cognitive and memory performance: a review and analysis. Brain Res Brain Res Rev 1999, 29(2–3): 169–195.

    Article  CAS  PubMed  Google Scholar 

  54. Jensen O, Lisman JE. An oscillatory short-term memory buffer model can account for data on the Sternberg task. J Neurosci 1998, 18: 10688–10699.

    CAS  PubMed  Google Scholar 

  55. Kahana MJ, Seelig D, Madsen JR. Theta returns. Curr Opin Neurobiol 2001, 11: 739–744.

    Article  CAS  PubMed  Google Scholar 

  56. Raghavachari S, Kahana MJ, Rizzuto DS, Caplan JB, Kirschen MP, Bourgeois B, et al. Gating of human theta oscillations by a working memory task. J Neurosci 2001, 21: 3175–3183.

    CAS  PubMed  Google Scholar 

  57. Gevins A, Smith ME, McEvoy L, Yu D. High-resolution EEG mapping of cortical activation related to working memory: effects of task difficulty, type of processing, and practice. Cereb Cortex 1997, 7: 374–385.

    Article  CAS  PubMed  Google Scholar 

  58. Jensen O, Tesche CD. Frontal theta activity in humans increases with memory load in a working memory task. Eur J Neurosci 2002, 15: 1395–1399.

    Article  PubMed  Google Scholar 

  59. Liebe S, Hoerzer GM, Logothetis NK, Rainer G. Theta coupling between V4 and prefrontal cortex predicts visual short-term memory performance. Nat Neurosci 2012, 15: 456–62, S1–2.

    Article  CAS  PubMed  Google Scholar 

  60. Berger H. Über das Elektrenkephalogramm des Menschen. Archiv f Psychiatrie 1929, 87: 527–570.

    Article  Google Scholar 

  61. Palva S, Palva JM. New vistas for alpha-frequency band oscillations. Trends Neurosci 2007, 30: 150–158.

    Article  CAS  PubMed  Google Scholar 

  62. da Silva FL. EEG and MEG: relevance to neuroscience. Neuron 2013, 80: 1112–1128.

    Article  Google Scholar 

  63. Jensen O, Gelfand J, Kounios J, Lisman JE. Oscillations in the alpha band (9–12 Hz) increase with memory load during retention in a short-term memory task. Cereb Cortex 2002, 12: 877–882.

    Article  PubMed  Google Scholar 

  64. Spitzer B, Fleck S, Blankenburg F. Parametric alpha- and beta-band signatures of supramodal numerosity information in human working memory. J Neurosci 2014, 34: 4293–4302.

    Article  CAS  PubMed  Google Scholar 

  65. Jensen O, Gips B, Bergmann TO, Bonnefond M. Temporal coding organized by coupled alpha and gamma oscillations prioritize visual processing. Trends Neurosci 2014, 37: 357–369.

    Article  CAS  PubMed  Google Scholar 

  66. Haegens S, Osipova D, Oostenveld R, Jensen O. Somatosensory working memory performance in humans depends on both engagement and disengagement of regions in a distributed network. Hum Brain Mapp 2010, 31: 26–35.

    PubMed  Google Scholar 

  67. Spitzer B, Blankenburg F. Supramodal parametric working memory processing in humans. J Neurosci 2012, 32: 3287–3295.

    Article  CAS  PubMed  Google Scholar 

  68. Bonnefond M, Jensen O. Alpha oscillations serve to protect working memory maintenance against anticipated distracters. Curr Biol 2012, 22: 1969–1974.

    Article  CAS  PubMed  Google Scholar 

  69. Capotosto P, Babiloni C, Romani GL, Corbetta M. Frontoparietal cortex controls spatial attention through modulation of anticipatory alpha rhythms. J Neurosci 2009, 29: 5863–5872.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  70. Anderson DE, Serences JT, Vogel EK, Awh E. Induced Alpha rhythms track the content and quality of visual working memory representations with high temporal precision. J Neurosci 2014, 34: 7587–7599.

    Article  CAS  PubMed  Google Scholar 

  71. Myers NE, Stokes MG, Walther L, Nobre AC. Oscillatory brain state predicts variability in working memory. J Neurosci 2014, 34: 7735–7743.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  72. Freunberger R, Fellinger R, Sauseng P, Gruber W, Klimesch W. Dissociation Between phaselocked and nonphase-locked alpha oscillations in a working memory task. Hum Brain Mapp 2009, 30: 3417–3425.

    Article  PubMed  Google Scholar 

  73. Eckhorn R, Bauer R, Jordan W, Brosch M, Kruse W, Munk M, et al. Coherent oscillations: A mechanism of feature linking in the visual cortex? Biol Cybern 1988, 60: 121–130.

    Article  CAS  PubMed  Google Scholar 

  74. Singer W, Gray CM. Visual feature integration and the temporal correlation hypothesis. Annu Rev Neurosci 1995, 18: 555–586.

    Article  CAS  PubMed  Google Scholar 

  75. Jensen O, Kaiser J, Lachaux JP. Human gamma-frequency oscillations associated with attention and memory. Trends Neurosci 2007, 30:317–324.

    Article  CAS  PubMed  Google Scholar 

  76. Buzsáki G, Wang XJ. Mechanisms of gamma oscillations. Annu Rev Neurosci 2012, 35: 203–225.

    Article  PubMed Central  PubMed  Google Scholar 

  77. Tallon-Baudry C, Bertrand O. Oscillatory gamma activity in humans and its role in object representation. Trends Cogn Sci 1999, 3: 151–162.

    Article  PubMed  Google Scholar 

  78. Osipova D, Takashima A, Oostenveld R, Fernández G, Maris E, Jensen O. Theta and gamma oscillations predict encoding and retrieval of declarative memory. J Neurosci 2006, 26: 7523–7531.

    Article  CAS  PubMed  Google Scholar 

  79. Howard MW, Rizzuto DS, Caplan JB, Madsen JR, Lisman J, Aschenbrenner-Scheibe R, et al. Gamma oscillations correlate with working memory load in humans. Cereb Cortex 2003, 13: 1369–1374.

    Article  PubMed  Google Scholar 

  80. Palva JM, Monto S, Kulashekhar S, Palva S. Neuronal synchrony reveals working memory networks and predicts individual memory capacity. Proc Natl Acad Sci U S A 2010, 107: 7580–7585.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  81. Palva S, Kulashekhar S, Hamalainen M, Palva JM. Localization of cortical phase and amplitude dynamics during visual working memory encoding and retention. J Neurosci 2011, 31: 5013–5025.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  82. Roux F, Wibral M, Mohr HM, Singer W, Uhlhaas PJ. Gammaband activity in human prefrontal cortex codes for the number of relevant items maintained in working memory. J Neurosci 2012, 32: 12411–12420.

    Article  CAS  PubMed  Google Scholar 

  83. Senkowski D, Talsma D, Grigutsch M, Herrmann CS, Woldorff MG. Good times for multisensory integration: Effects of the precision of temporal synchrony as revealed by gamma-band oscillations. Neuropsychologia 2007, 45: 561–571.

    Article  PubMed  Google Scholar 

  84. Roux F, Uhlhaas PJ. Working memory and neural oscillations: alpha-gamma versus theta-gamma codes for distinct WM information? Trends Cogn Sci 2014, 18: 16–25.

    Article  PubMed  Google Scholar 

  85. Xu Y. The role of the superior intraparietal sulcus in supporting visual short-term memory for multifeature objects. J Neurosci 2007, 27: 11676–11686.

    Article  CAS  PubMed  Google Scholar 

  86. Xu Y. Distinctive neural mechanisms supporting visual object individuation and identification. J Cogn Neurosci 2009, 21: 511–518.

    Article  PubMed  Google Scholar 

  87. Spitzer B, Wacker E, Blankenburg F. Oscillatory correlates of vibrotactile frequency processing in human working memory. J Neurosci 2010, 30: 4496–4502.

    Article  CAS  PubMed  Google Scholar 

  88. Spitzer B, Blankenburg F. Stimulus-dependent EEG activity reflects internal updating of tactile working memory in humans. Proc Natl Acad Sci U S A 2011, 108: 8444–8449.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  89. Spitzer B, Gloel M, Schmidt TT, Blankenburg F. Working memory coding of analog stimulus properties in the human prefrontal cortex. Cereb Cortex 2014, 24: 2229–2236.

    Article  PubMed  Google Scholar 

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Ku, Y., Bodner, M. & Zhou, YD. Prefrontal cortex and sensory cortices during working memory: quantity and quality. Neurosci. Bull. 31, 175–182 (2015). https://doi.org/10.1007/s12264-014-1503-7

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