Evidence for working memory storage operations in perceptual cortex

  • Kartik K. SreenivasanEmail author
  • Caterina Gratton
  • Jason Vytlacil
  • Mark D’Esposito


Isolating the short-term storage component of working memory (WM) from the myriad of associated executive processes has been an enduring challenge. Recent efforts have identified patterns of activity in visual regions that contain information about items being held in WM. However, it remains unclear (1) whether these representations withstand intervening sensory input and (2) how communication between multimodal association cortex and the unimodal perceptual regions supporting WM representations is involved in WM storage. We present evidence that the features of a face held in WM are stored within face-processing regions, that these representations persist across subsequent sensory input, and that information about the match between sensory input and a memory representation is relayed forward from perceptual to prefrontal regions. Participants were presented with a series of probe faces and indicated whether each probe matched a target face held in WM. We parametrically varied the feature similarity between the probe and target faces. Activity within face-processing regions scaled linearly with the degree of feature similarity between the probe face and the features of the target face, suggesting that the features of the target face were stored in these regions. Furthermore, directed connectivity measures revealed that the direction of information flow that was optimal for performance was from sensory regions that stored the features of the target face to dorsal prefrontal regions, supporting the notion that sensory input is compared to representations stored within perceptual regions and is subsequently relayed forward. Together, these findings indicate that WM storage operations are carried out within perceptual cortex.


Working memory Functional connectivity 

Supplementary material

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Figure S1 (PDF 100 kb)
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Table S1 (DOCX 68.0 KB)


  1. Aguirre, G. K. (2007). Continuous carry-over designs for fMRI. NeuroImage, 35, 1480–1494.PubMedCentralPubMedCrossRefGoogle Scholar
  2. Al-Aidroos, N., Said, C. P., & Turk-Browne, N. B. (2012). Top-down attention switches coupling between low-level and high-level areas of human visual cortex. Proceedings of the National Academy of Sciences, 109, 14675–14680. doi: 10.1073/pnas.1202095109 CrossRefGoogle Scholar
  3. Andrews, T. J., & Ewbank, M. P. (2004). Distinct representations for facial identity and changeable aspects of faces in the human temporal lobe. NeuroImage, 23, 905–913. doi: 10.1016/j.neuroimage.2004.07.060 PubMedCrossRefGoogle Scholar
  4. Artchakov, D., Tikhonravov, D., Ma, Y., Neuvonen, T., Linnankoski, I., & Carlson, S. (2009). Distracters impair and create working memory-related neuronal activity in the prefrontal cortex. Cerebral Cortex, 19, 2680–2689. doi: 10.1093/cercor/bhp037 PubMedCrossRefGoogle Scholar
  5. Awh, E., & Jonides, J. (2001). Overlapping mechanisms of attention and spatial working memory. Trends in Cognitive Sciences, 5, 119–126. doi: 10.1016/S1364-6613(00)01593-X PubMedCrossRefGoogle Scholar
  6. Awh, E., Vogel, E. K., & Oh, S. (2006). Interactions between attention and working memory. Neuroscience, 139, 201–208. doi: 10.1016/j.neuroscience.2005.08.023 PubMedCrossRefGoogle Scholar
  7. Badre, D., & Wagner, A. D. (2007). Left ventrolateral prefrontal cortex and the cognitive control of memory. Neuropsychologia, 45, 2883–2901. doi: 10.1016/j.neuropsychologia.2007.06.015 PubMedCrossRefGoogle Scholar
  8. Brass, M., Derrfuss, J., Forstmann, B., & von Cramon, D. Y. (2005). The role of the inferior frontal junction area in cognitive control. Trends in Cognitive Sciences, 9, 314–316. doi: 10.1016/j.tics.2005.05.001 PubMedCrossRefGoogle Scholar
  9. Braver, T. S., Cohen, J. D., Nystrom, L. E., Jonides, J., Smith, E. E., & Noll, D. C. (1997). A parametric study of prefrontal cortex involvement in human working memory. NeuroImage, 5, 49–62.PubMedCrossRefGoogle Scholar
  10. Chelazzi, L., Duncan, J., Miller, E. K., & Desimone, R. (1998). Responses of neurons in inferior temporal cortex during memory-guided visual search. Journal of Neurophysiology, 80, 2918–2940.PubMedGoogle Scholar
  11. Christophel, T. B., Hebart, M. N., & Haynes, J. D. (2012). Decoding the contents of visual short-term memory from human visual and parietal cortex. Journal of Neuroscience, 32, 12983–12989. doi: 10.1523/JNEUROSCI.0184-12.2012 PubMedCrossRefGoogle Scholar
  12. Cohen, J. R., Sreenivasan, K. K., & D’Esposito, M. (2012). Correspondence between stimulus encoding- and maintenance-related neural processes underlies successful working memory. Cerebral Cortex. doi: 10.1093/cercor/bhs339. Advance online publication.Google Scholar
  13. Cowan, N. (1993). Activation, attention, and short-term memory. Memory & Cognition, 21, 162–167.CrossRefGoogle Scholar
  14. Cox, R. W. (1996). AFNI: Software for analysis and visualization of functional magnetic resonance neuroimages. Computers and Biomedical Research, 29, 162–173.PubMedCrossRefGoogle Scholar
  15. D’Esposito, M. (2007). From cognitive to neural models of working memory. Philosophical Transactions of the Royal Society B, 362, 761–772. doi: 10.1098/rstb.2007.2086 CrossRefGoogle Scholar
  16. D’Esposito, M., & Postle, B. R. (1999). The dependence of span and delayed-response performance on prefrontal cortex. Neuropsychologia, 37, 1303–1315. doi: 10.1016/S0028-3932(99)00021-4 PubMedCrossRefGoogle Scholar
  17. D’Esposito, M., Postle, B. R., Jonides, J., & Smith, E. E. (1999). The neural substrate and temporal dynamics of interference effects in working memory as revealed by event-related functional MRI. Proceedings of the National Academy of Sciences, 96, 7514–7519.CrossRefGoogle Scholar
  18. David, S. V., Hayden, B. Y., Mazer, J. A., & Gallant, J. L. (2008). Attention to stimulus features shifts spectral tuning of v4 neurons during natural vision. Neuron, 59, 509–521. doi: 10.1016/j.neuron.2008.07.001 PubMedCentralPubMedCrossRefGoogle Scholar
  19. Deco, G., Rolls, E. T., Albantakis, L., & Romo, R. (2013). Brain mechanisms for perceptual and reward-related decision-making. Progress in Neurobiology, 103, 194–213. doi: 10.1016/j.pneurobio.2012.01.010 PubMedCrossRefGoogle Scholar
  20. Derrfuss, J., Brass, M., Neumann, J., & von Cramon, D. Y. (2005). Involvement of the inferior frontal junction in cognitive control: Meta-analyses of switching and Stroop studies. Human Brain Mapping, 25, 22–34. doi: 10.1002/hbm.20127 PubMedCrossRefGoogle Scholar
  21. Deshpande, G., Sathian, K., & Hu, X. (2010). Effect of hemodynamic variability on Granger causality analysis of fMRI. NeuroImage, 52, 884–896.PubMedCentralPubMedCrossRefGoogle Scholar
  22. Desimone, R., & Duncan, J. (1995). Neural mechanisms of selective visual attention. Annual Review of Neuroscience, 18, 193–222. doi: 10.1146/ PubMedCrossRefGoogle Scholar
  23. Ding, M., Bressler, S. L., Yang, W., & Liang, H. (2000). Short-window spectral analysis of cortical event-related potentials by adaptive multivariate autoregressive modeling: Data preprocessing, model validation, and variability assessment. Biological Cybernetics, 83, 35–45.PubMedCrossRefGoogle Scholar
  24. Druzgal, T. J., & D’Esposito, M. (2001). A neural network reflecting decisions about human faces. Neuron, 32, 947–955.PubMedCrossRefGoogle Scholar
  25. Emrich, S. M., Riggall, A. C., LaRocque, J. J., & Postle, B. R. (2013). Distributed patterns of activity in sensory cortex reflect the precision of multiple items maintained in visual short-term memory. Journal of Neuroscience, 33, 6516–6523. doi: 10.1523/JNEUROSCI.5732-12.2013 PubMedCentralPubMedCrossRefGoogle Scholar
  26. Ester, E. F., Anderson, D. E., Serences, J. T., & Awh, E. (2013). A neural measure of precision in visual working memory. Journal of Cognitive Neuroscience, 25, 754–761. doi: 10.1162/jocn_a_00357 PubMedCrossRefGoogle Scholar
  27. Fiebach, C. J., Rissman, J., & D’Esposito, M. (2006). Modulation of inferotemporal cortex activation during verbal working memory maintenance. Neuron, 51, 251–261. doi: 10.1016/j.neuron.2006.06.007 PubMedCrossRefGoogle Scholar
  28. Friston, K. J. (1994). Functional and effective connectivity in neuroimaging: A synthesis. Human Brain Mapping, 2, 56–78.CrossRefGoogle Scholar
  29. Friston, K. J. (2009). Causal modelling and brain connectivity in functional magnetic resonance imaging. PLoS Biology, 7, e33. doi: 10.1371/journal.pbio.1000033 PubMedCrossRefGoogle Scholar
  30. Friston, K. J., Harrison, L., & Penny, W. (2003). Dynamic causal modelling. NeuroImage, 19, 1273–1302. doi: 10.1016/S1053-8119(03)00202-7 PubMedCrossRefGoogle Scholar
  31. Fuster, J. M., Bauer, R., & Jervey, J. (1985). Functional interactions between inferotemporal and prefrontal cortex in a cognitive task. Brain Research, 330, 299–307.PubMedCrossRefGoogle Scholar
  32. Gazzaley, A., Cooney, J. W., McEvoy, K., Knight, R. T., & D’Esposito, M. (2005). Top-down enhancement and suppression of the magnitude and speed of neural activity. Journal of Cognitive Neuroscience, 17, 507–517. doi: 10.1162/0898929053279522 PubMedCrossRefGoogle Scholar
  33. Gazzaley, A., & Nobre, A. C. (2012). Top-down modulation: Bridging selective attention and working memory. Trends in Cognitive Sciences, 16, 129–135. doi: 10.1016/j.tics.2011.11.014 PubMedCentralPubMedCrossRefGoogle Scholar
  34. Gazzaley, A., Rissman, J., & D’Esposito, M. (2004). Functional connectivity during working memory maintenance. Cognitive, Affective, & Behavioral Neuroscience, 4, 580–599. doi: 10.3758/CABN.4.4.580 CrossRefGoogle Scholar
  35. Gold, J. I., & Shadlen, M. N. (2007). The neural basis of decision making. Annual Review of Neuroscience, 30, 535–574. doi: 10.1146/annurev.neuro.29.051605.113038 PubMedCrossRefGoogle Scholar
  36. Gratton, C., Sreenivasan, K. K., Silver, M. A., & D’Esposito, M. (2013). Attention selectively modifies the representation of individual faces in the human brain. Journal of Neuroscience, 33, 6979–6989. doi: 10.1523/JNEUROSCI.4142-12.2013 PubMedCentralPubMedCrossRefGoogle Scholar
  37. Harrison, S. A., & Tong, F. (2009). Decoding reveals the contents of visual working memory in early visual areas. Nature, 458, 632–635. doi: 10.1038/nature07832 PubMedCentralPubMedCrossRefGoogle Scholar
  38. Jha, A. P., Fabian, S. A., & Aguirre, G. K. (2004). The role of prefrontal cortex in resolving distractor interference. Cognitive, Affective, & Behavioral Neuroscience, 4, 517–527. doi: 10.3758/CABN.4.4.517 CrossRefGoogle Scholar
  39. Jha, A. P., & McCarthy, G. (2000). The influence of memory load upon delay-interval activity in a working-memory task: An event-related functional MRI study. Journal of Cognitive Neuroscience, 12, 90–105.PubMedCrossRefGoogle Scholar
  40. Jiang, Y., Haxby, J. V., Martin, A., Ungerleider, L. G., & Parasuraman, R. (2000). Complementary neural mechanisms for tracking items in human working memory. Science, 287, 643–646. doi: 10.1126/science.287.5453.643 PubMedCrossRefGoogle Scholar
  41. Jonides, J., Schumacher, E. H., Smith, E. E., Lauber, E. J., Awh, E., Minoshima, S., & Koeppe, R. A. (1997). Verbal working memory load affects regional brain activation as measured by PET. Journal of Cognitive Neuroscience, 9, 462–475. doi: 10.1162/jocn.1997.9.4.462 PubMedCrossRefGoogle Scholar
  42. Jonides, J., Smith, E. E., Koeppe, R. A., Awh, E., Minoshima, S., & Mintun, M. A. (1993). Spatial working-memory in humans as revealed by PET. Nature, 363, 623–625. doi: 10.1038/363623a0 PubMedCrossRefGoogle Scholar
  43. Jonides, J., Smith, E. E., Marshuetz, C., Koeppe, R. A., & Reuter-Lorenz, P. A. (1998). Inhibition in verbal working memory revealed by brain activation. Proceedings of the National Academy of Sciences, 95, 8410–8413.CrossRefGoogle Scholar
  44. Kuo, B.-C., Stokes, M. G., & Nobre, A. C. (2012). Attention modulates maintenance of representations in visual short-term memory. Journal of Cognitive Neuroscience, 24, 51–60. doi: 10.1162/jocn_a_00087 PubMedCentralPubMedCrossRefGoogle Scholar
  45. Lee, T. G., & D’Esposito, M. (2012). The dynamic nature of top-down signals originating from prefrontal cortex: A combined fMRI-TMS study. Journal of Neuroscience, 32, 15458–15466. doi: 10.1523/JNEUROSCI.0627-12.2012 PubMedCentralPubMedCrossRefGoogle Scholar
  46. Lepsien, J., & Nobre, A. C. (2007). Attentional modulation of object representations in working memory. Cerebral Cortex, 17, 2072–2083. doi: 10.1093/cercor/bhl116 PubMedCrossRefGoogle Scholar
  47. Leung, H.-C., Gore, J. C., & Goldman-Rakic, P. S. (2002). Sustained mnemonic response in the human middle frontal gyrus during on-line storage of spatial memoranda. Journal of Cognitive Neuroscience, 14, 659–671. doi: 10.1162/08989290260045882 PubMedCrossRefGoogle Scholar
  48. Leung, H.-C., Seelig, D., & Gore, J. C. (2004). The effect of memory load on cortical activity in the spatial working memory circuit. Cognitive, Affective, & Behavioral Neuroscience, 4, 553–563. doi: 10.3758/CABN.4.4.553 CrossRefGoogle Scholar
  49. Lewis-Peacock, J. A., & Postle, B. R. (2008). Temporary activation of long-term memory supports working memory. Journal of Neuroscience, 28, 8765–8771. doi: 10.1523/JNEUROSCI.1953-08.2008 PubMedCentralPubMedCrossRefGoogle Scholar
  50. Liebe, S., Hoerzer, G. M., Logothetis, N. K., & Rainer, G. (2012). Theta coupling between V4 and prefrontal cortex predicts visual short-term memory performance. Nature Neuroscience, 15(456–62), S1–S2. doi: 10.1038/nn.3038 Google Scholar
  51. Liu, T., Hospadaruk, L., Zhu, D. C., & Gardner, J. L. (2011). Feature-specific attentional priority signals in human cortex. Journal of Neuroscience, 31, 4484–4495. doi: 10.1523/JNEUROSCI.5745-10.2011 PubMedCrossRefGoogle Scholar
  52. Miller, E. K., & Desimone, R. (1994). Parallel neuronal mechanisms for short-term memory. Science, 263, 520–522. doi: 10.1126/science.8290960 PubMedCrossRefGoogle Scholar
  53. Miller, E. K., Erickson, C. A., & Desimone, R. (1996). Neural mechanisms of visual working memory in prefrontal cortex of the macaque. Journal of Neuroscience, 16, 5154–5167.PubMedGoogle Scholar
  54. Miller, B. T., Vytlacil, J., Fegen, D., Pradhan, S., & D’Esposito, M. (2011). The prefrontal cortex modulates category selectivity in human extrastriate cortex. Journal of Cognitive Neuroscience, 23, 1–10. doi: 10.1162/jocn.2010.21516 PubMedCrossRefGoogle Scholar
  55. Morris, S. B., & DeShon, R. P. (2002). Combining effect size estimates in meta-analysis with repeated measures and independent-groups designs. Psychological Methods, 7, 105–125. doi: 10.1037/1082-989X.7.1.105 PubMedCrossRefGoogle Scholar
  56. Munk, M. H., Linden, D. E., Muckli, L., Lanfermann, H., Zanella, F. E., Singer, W., & Goebel, R. (2002). Distributed cortical systems in visual short-term memory revealed by event-related functional magnetic resonance imaging. Cerebral Cortex, 12, 866–876. doi: 10.1093/cercor/12.8.866 PubMedCrossRefGoogle Scholar
  57. Pandya, D. N., Dye, P., & Butters, N. (1971). Efferent cortico-cortical projections of the prefrontal cortex in the rhesus monkey. Brain Research, 31, 35–46. doi: 10.1016/0006-8993(71)90632-9 PubMedCrossRefGoogle Scholar
  58. Pandya, D. N., & Kuypers, H. G. J. M. (1969). Cortico-cortical connections in the rhesus monkey. Brain Research, 13, 13–36. doi: 10.1016/0006-8993(69)90141-3 PubMedCrossRefGoogle Scholar
  59. Pasternak, T., & Greenlee, M. W. (2005). Working memory in primate sensory systems. Nature Reviews Neuroscience, 6, 97–107. doi: 10.1038/nrn1603 PubMedCrossRefGoogle Scholar
  60. Peters, J. C., Roelfsema, P. R., & Goebel, R. (2012). Task-relevant and accessory items in working memory have opposite effects on activity in extrastriate cortex. Journal of Neuroscience, 32, 17003–17011. doi: 10.1523/JNEUROSCI.0591-12.2012 PubMedCrossRefGoogle Scholar
  61. Postle, B. R. (2006). Working memory as an emergent property of the mind and brain. Neuroscience, 139, 23–38. doi: 10.1016/j.neuroscience.2005.06.005 PubMedCentralPubMedCrossRefGoogle Scholar
  62. Ranganath, C., Cohen, M. X., Dam, C., & D’Esposito, M. (2004). Inferior temporal, prefrontal, and hippocampal contributions to visual working memory maintenance and associative memory retrieval. Journal of Neuroscience, 24, 3917–3925. doi: 10.1523/JNEUROSCI.5053-03.2004 PubMedCrossRefGoogle Scholar
  63. Riggall, A. C., & Postle, B. R. (2012). The relationship between working memory storage and elevated activity as measured with functional magnetic resonance imaging. Journal of Neuroscience, 32, 12990–12998. doi: 10.1523/JNEUROSCI.1892-12.2012 PubMedCentralPubMedCrossRefGoogle Scholar
  64. Rissman, J., Gazzaley, A., & D’Esposito, M. (2004). Measuring functional connectivity during distinct stages of a cognitive task. NeuroImage, 23, 752–763. doi: 10.1016/j.neuroimage.2004.06.035 PubMedCrossRefGoogle Scholar
  65. Roebroeck, A., Formisano, E., & Goebel, R. (2005). Mapping directed influence over the brain using Granger causality and fMRI. NeuroImage, 25, 230–242. doi: 10.1016/j.neuroimage.2004.11.017 PubMedCrossRefGoogle Scholar
  66. Sakai, K., Rowe, J. B., & Passingham, R. (2002). Active maintenance in prefrontal area 46 creates distractor-resistant memory. Nature Neuroscience, 5, 479–484.PubMedGoogle Scholar
  67. Salazar, R. F., Dotson, N. M., Bressler, S. L., & Gray, C. M. (2012). Content-specific fronto-parietal synchronization during visual working memory. Science, 338, 1097–1100. doi: 10.1126/science.1224000 PubMedCrossRefGoogle Scholar
  68. Schippers, M. B., Renken, R., & Keysers, C. (2011). The effect of intra- and inter-subject variability of hemodynamic responses on group level Granger causality analyses. NeuroImage, 57, 22–36. doi: 10.1016/j.neuroimage.2011.02.008 PubMedCrossRefGoogle Scholar
  69. Serences, J. T., Ester, E. F., Vogel, E. K., & Awh, E. (2009). Stimulus-specific delay activity in human primary visual cortex. Psychological Science, 20, 207–214. doi: 10.1111/j.1467-9280.2009.02276.x PubMedCentralPubMedCrossRefGoogle Scholar
  70. Seth, A. K. (2010). A MATLAB toolbox for Granger causal connectivity analysis. Journal of Neuroscience Methods, 186, 262–273. doi: 10.1016/j.jneumeth.2009.11.020 PubMedCrossRefGoogle Scholar
  71. Seth, A. K., Chorley, P., & Barnett, L. C. (2013). Granger causality analysis of fMRI BOLD signals is invariant to hemodynamic convolution but not downsampling. NeuroImage, 65, 540–555. doi: 10.1016/j.neuroimage.2012.09.049 PubMedCrossRefGoogle Scholar
  72. Smith, E. E., & Jonides, J. (1998). Neuroimaging analyses of human working memory. Proceedings of the National Academy of Sciences, 95, 12061–12068.CrossRefGoogle Scholar
  73. Smith, E. E., & Jonides, J. (1999). Storage and executive processes in the frontal lobes. Science, 283, 1657–1661. doi: 10.1126/science.283.5408.1657 PubMedCrossRefGoogle Scholar
  74. Smith, E. E., Jonides, J., Koeppe, R. A., Awh, E., Schumacher, E. H., & Minoshima, S. (1995). Spatial versus object working memory: PET investigations. Journal of Cognitive Neuroscience, 7, 337–356. doi: 10.1162/jocn.1995.7.3.337 PubMedCrossRefGoogle Scholar
  75. Smith, S. M., Miller, K. L., Salimi-Khorshidi, G., Webster, M., Beckmann, C. F., Nichols, T. E., & Woolrich, M. W. (2011). Network modelling methods for FMRI. NeuroImage, 54, 875–891. doi: 10.1016/j.neuroimage.2010.08.063 PubMedCrossRefGoogle Scholar
  76. Soto, D., Llewelyn, D., & Silvanto, J. (2012). Distinct causal mechanisms of attentional guidance by working memory and repetition priming in early visual cortex. Journal of Neuroscience, 32, 3447–3452. doi: 10.1523/JNEUROSCI.6243-11.2012 PubMedCrossRefGoogle Scholar
  77. Speer, N. K., Jacoby, L. L., & Braver, T. S. (2003). Strategy-dependent changes in memory: Effects on behavior and brain activity. Cognitive, Affective, & Behavioral Neuroscience, 3, 155–167. doi: 10.3758/CABN.3.3.155 CrossRefGoogle Scholar
  78. Sreenivasan, K. K., & Jha, A. P. (2007). Selective attention supports working memory maintenance by modulating perceptual processing of distractors. Journal of Cognitive Neuroscience, 19, 32–41. doi: 10.1162/jocn.2007.19.1.32 PubMedCrossRefGoogle Scholar
  79. Sreenivasan, K. K., Katz, J., & Jha, A. P. (2007). Temporal characteristics of top-down modulations during working memory maintenance: An event-related potential study of the N170 component. Journal of Cognitive Neuroscience, 19, 1836–1844. doi: 10.1162/jocn.2007.19.11.1836 PubMedCrossRefGoogle Scholar
  80. Sreenivasan, K. K., Sambhara, D., & Jha, A. P. (2011). Working memory templates are maintained as feature-specific perceptual codes. Journal of Neurophysiology, 106, 115–121. doi: 10.1152/jn.00776.2010 PubMedCentralPubMedCrossRefGoogle Scholar
  81. St James, J. D., & Eriksen, C. W. (1991). Response competition produces a “fast same effect” in same–different judgments. In G. R. Lockhead & J. R. Pomerantz (Eds.), The perception of structure: Essays in honor of Wendell R. Garner (pp. 157–168). Washington: American Psychological Association. doi: 10.1037/10101-009 CrossRefGoogle Scholar
  82. Steiger, J. H. (1980). Tests for comparing elements of a correlation matrix. Psychological Bulletin, 87, 245–251. doi: 10.1037/0033-2909.87.2.245 CrossRefGoogle Scholar
  83. Sugase-Miyamoto, Y., Liu, Z., Wiener, M. C., Optican, L. M., & Richmond, B. J. (2008). Short-term memory trace in rapidly adapting synapses of inferior temporal cortex. PLoS Computational Biology, 4, e1000073. doi: 10.1371/journal.pcbi.1000073 PubMedCentralPubMedCrossRefGoogle Scholar
  84. Thompson-Schill, S. L., D’Esposito, M., Aguirre, G. K., & Farah, M. J. (1997). Role of left inferior prefrontal cortex in retrieval of semantic knowledge: A reevaluation. Proceedings of the National Academy of Sciences, 94, 14792–14797.CrossRefGoogle Scholar
  85. Todd, J. J., & Marois, R. (2004). Capacity limit of visual short-term memory in human posterior parietal cortex. Nature, 428, 751–754. doi: 10.1038/nature02466 PubMedCrossRefGoogle Scholar
  86. Tsotsos, J. K., Culhane, S. M., Kei Wai, W. Y., Lai, Y., Davis, N., & Nuflo, F. (1995). Modeling visual attention via selective tuning. Artificial Intelligence, 78, 507–545.CrossRefGoogle Scholar
  87. Wager, T. D., & Smith, E. E. (2003). Neuroimaging studies of working memory: A meta-analysis. Cognitive, Affective, & Behavioral Neuroscience, 3, 255–274. doi: 10.3758/CABN.3.4.255 CrossRefGoogle Scholar
  88. Wen, X., Rangarajan, G., & Ding, M. (2013). Is Granger causality a viable technique for analyzing fMRI data? PLoS ONE, 8, e67428. doi: 10.1371/journal.pone.0067428 PubMedCentralPubMedCrossRefGoogle Scholar
  89. Yoon, J. H., Curtis, C. E., & D’Esposito, M. (2006). Differential effects of distraction during working memory on delay-period activity in the prefrontal cortex and the visual association cortex. NeuroImage, 29, 1117–1126. doi: 10.1016/j.neuroimage.2005.08.024 PubMedCrossRefGoogle Scholar
  90. Zanto, T. P., Rubens, M. T., Thangavel, A., & Gazzaley, A. (2011). Causal role of the prefrontal cortex in top-down modulation of visual processing and working memory. Nature Neuroscience, 14, 656–661. doi: 10.1038/nn.2773 PubMedCentralPubMedCrossRefGoogle Scholar
  91. Zhang, J. X., Leung, H.-C., & Johnson, M. K. (2003). Frontal activations associated with accessing and evaluating information in working memory: An fMRI study. NeuroImage, 20, 1531–1539. doi: 10.1016/S1053-8119(03)00466-X PubMedCrossRefGoogle Scholar

Copyright information

© Psychonomic Society, Inc. 2014

Authors and Affiliations

  • Kartik K. Sreenivasan
    • 1
    • 2
    Email author
  • Caterina Gratton
    • 1
  • Jason Vytlacil
    • 1
  • Mark D’Esposito
    • 1
  1. 1.Helen Wills Neuroscience InstituteUniversity of CaliforniaBerkeleyUSA
  2. 2.Division of Science and MathematicsNew York University Abu DhabiAbu DhabiUnited Arab Emirates

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