{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,17]],"date-time":"2025-10-17T14:06:48Z","timestamp":1760710008631},"reference-count":58,"publisher":"MIT Press - Journals","issue":"1","content-domain":{"domain":["direct.mit.edu"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2020,1,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Spatial attention improves performance on visual tasks, increases neural responses to attended stimuli, and reduces correlated noise in visual cortical neurons. In addition to being visually responsive, many retinotopic visual cortical areas exhibit very slow (&amp;lt;0.1 Hz) endogenous fluctuations in functional magnetic resonance imaging signals. To test whether these fluctuations degrade stimulus representations, thereby impairing visual detection, we recorded functional magnetic resonance imaging responses while human participants performed a target detection task that required them to allocate spatial attention to either a rotating wedge stimulus or a central fixation point. We then measured the effects of spatial attention on response amplitude at the frequency of wedge rotation and on the amplitude of endogenous fluctuations at nonstimulus frequencies. We found that, in addition to enhancing stimulus-evoked responses, attending to the wedge also suppressed slow endogenous fluctuations that were unrelated to the visual stimulus in topographically defined areas in early visual cortex, posterior parietal cortex, and lateral occipital cortex, but not in a nonvisual cortical control region. Moreover, attentional enhancement of response amplitude and suppression of endogenous fluctuations were dissociable across cortical areas and across time. Finally, we found that the amplitude of the stimulus-evoked response was not correlated with a perceptual measure of visual target detection. Instead, perceptual performance was accounted for by the amount of suppression of slow endogenous fluctuations. Our results indicate that the amplitude of slow fluctuations of cortical activity is influenced by spatial attention and suggest that these endogenous fluctuations may impair perceptual processing in topographically organized visual cortical areas.<\/jats:p>","DOI":"10.1162\/jocn_a_01470","type":"journal-article","created":{"date-parts":[[2019,9,27]],"date-time":"2019-09-27T15:20:46Z","timestamp":1569597646000},"page":"85-99","update-policy":"http:\/\/dx.doi.org\/10.1162\/mitpressjournals.corrections.policy","source":"Crossref","is-referenced-by-count":3,"title":["Slow Endogenous Fluctuations in Cortical fMRI Signals Correlate with Reduced Performance in a Visual Detection Task and Are Suppressed by Spatial Attention"],"prefix":"10.1162","volume":"32","author":[{"given":"David W.","family":"Bressler","sequence":"first","affiliation":[{"name":"University of California, Berkeley"}]},{"given":"Ariel","family":"Rokem","sequence":"additional","affiliation":[{"name":"University of California, Berkeley"}]},{"given":"Michael A.","family":"Silver","sequence":"additional","affiliation":[{"name":"University of California, Berkeley"}]}],"member":"281","published-online":{"date-parts":[[2020,1,1]]},"reference":[{"key":"2021072107050526600_bib1","doi-asserted-by":"crossref","unstructured":"Berkes,  P., Orb\u00e1n,  G., Lengyel,  M., & Fiser,  J. (2011). Spontaneous cortical activity reveals hallmarks of an optimal internal model of the environment. Science, 331, 83\u201387.","DOI":"10.1126\/science.1195870"},{"key":"2021072107050526600_bib2","doi-asserted-by":"crossref","unstructured":"Birbaumer,  N., Elbert,  T., Canavan,  A. G., & Rockstroh,  B. (1990). Slow potentials of the cerebral cortex and behavior. Physiological Review, 70, 1\u201341.","DOI":"10.1152\/physrev.1990.70.1.1"},{"key":"2021072107050526600_bib3","doi-asserted-by":"crossref","unstructured":"Birn,  R. M., Diamond,  J. B., Smith,  M. A., & Bandettini,  P. A. (2006). Separating respiratory-variation-related fluctuations from neuronal-activity-related fluctuations in fMRI. Neuroimage, 31, 1536\u20131548.","DOI":"10.1016\/j.neuroimage.2006.02.048"},{"key":"2021072107050526600_bib4","doi-asserted-by":"crossref","unstructured":"Bressler,  D. W., Fortenbaugh,  F. C., Robertson,  L. C., & Silver,  M. A. (2013). Visual spatial attention enhances the amplitude of positive and negative fMRI responses to visual stimulation in an eccentricity-dependent manner. Vision Research, 85, 104\u2013112.","DOI":"10.1016\/j.visres.2013.03.009"},{"key":"2021072107050526600_bib5","doi-asserted-by":"crossref","unstructured":"Bressler,  D. W., & Silver,  M. A. (2010). Spatial attention improves reliability of fMRI retinotopic mapping signals in occipital and parietal cortex. Neuroimage, 53, 526\u2013533.","DOI":"10.1016\/j.neuroimage.2010.06.063"},{"key":"2021072107050526600_bib6","doi-asserted-by":"crossref","unstructured":"Brewer,  A. A., Liu,  J., Wade,  A. R., & Wandell,  B. A. (2005). Visual field maps and stimulus selectivity in human ventral occipital cortex. Nature Neuroscience, 8, 1102\u20131109.","DOI":"10.1038\/nn1507"},{"key":"2021072107050526600_bib7","doi-asserted-by":"crossref","unstructured":"Busch,  N. A., Dubois,  J., & VanRullen,  R. (2009). The phase of ongoing EEG oscillations predicts visual perception. Journal of Neuroscience, 29, 7869\u20137876.","DOI":"10.1523\/JNEUROSCI.0113-09.2009"},{"key":"2021072107050526600_bib8","doi-asserted-by":"crossref","unstructured":"Carrasco,  M.\n           (2011). Visual attention: The past 25 years. Vision Research, 51, 1484\u20131525.","DOI":"10.1016\/j.visres.2011.04.012"},{"key":"2021072107050526600_bib9","doi-asserted-by":"crossref","unstructured":"Cohen,  M. R., & Maunsell,  J. H. R. (2009). Attention improves performance primarily by reducing interneuronal correlations. Nature Neuroscience, 12, 1594\u20131600.","DOI":"10.1038\/nn.2439"},{"key":"2021072107050526600_bib10","doi-asserted-by":"crossref","unstructured":"Corbetta,  M., Kincade,  J. M., Ollinger,  J. M., McAvoy,  M. P., & Shulman,  G. L. (2000). Voluntary orienting is dissociated from target detection in human posterior parietal cortex. Nature Neuroscience, 3, 292\u2013297.","DOI":"10.1038\/73009"},{"key":"2021072107050526600_bib11","doi-asserted-by":"crossref","unstructured":"Coste,  C. P., & Kleinschmidt,  A. (2016). Cingulo-opercular network activity maintains alertness. Neuroimage, 128, 264\u2013272.","DOI":"10.1016\/j.neuroimage.2016.01.026"},{"key":"2021072107050526600_bib12","doi-asserted-by":"crossref","unstructured":"Devrim,  M., Demiralp,  T., Kurt,  A., & Y\u00fccesir,  I. (1999). Slow cortical potential shifts modulate the sensory threshold in human visual system. Neuroscience Letters, 270, 17\u201320.","DOI":"10.1016\/S0304-3940(99)00456-5"},{"key":"2021072107050526600_bib13","doi-asserted-by":"crossref","unstructured":"Engel,  S. A., Rumelhart,  D. E., Wandell,  B. A., Lee,  A. T., Glover,  G. H., Chichilnisky,  E. J., et al (1994). fMRI of human visual cortex. Nature, 369, 525.","DOI":"10.1038\/369525a0"},{"key":"2021072107050526600_bib14","doi-asserted-by":"crossref","unstructured":"Fox,  M. D., Snyder,  A. Z., Vincent,  J. L., Corbetta,  M., Van Essen,  D. C., & Raichle,  M. E. (2005). The human brain is intrinsically organized into dynamic, anticorrelated functional networks. Proceedings of the National Academy of Sciences, U.S.A., 102, 9673\u20139678.","DOI":"10.1073\/pnas.0504136102"},{"key":"2021072107050526600_bib15","doi-asserted-by":"crossref","unstructured":"Fransson,  P.\n           (2006). How default is the default mode of brain function? Further evidence from intrinsic BOLD signal fluctuations. Neuropsychologia, 44, 2836\u20132845.","DOI":"10.1016\/j.neuropsychologia.2006.06.017"},{"key":"2021072107050526600_bib16","doi-asserted-by":"crossref","unstructured":"Gandhi,  S. P., Heeger,  D. J., & Boynton,  G. M. (1999). Spatial attention affects brain activity in human primary visual cortex. Proceedings of the National Academy of Sciences, U.S.A., 96, 3314\u20133319.","DOI":"10.1073\/pnas.96.6.3314"},{"key":"2021072107050526600_bib17","doi-asserted-by":"crossref","unstructured":"Genovese,  C. R., Lazar,  N. A., & Nichols,  T. (2002). Thresholding of statistical maps in functional neuroimaging using the false discovery rate. Neuroimage, 15, 870\u2013878.","DOI":"10.1006\/nimg.2001.1037"},{"key":"2021072107050526600_bib18","doi-asserted-by":"crossref","unstructured":"Greicius,  M. D., Krasnow,  B., Reiss,  A. L., & Menon,  V. (2003). Functional connectivity in the resting brain: A network analysis of the default mode hypothesis. Proceedings of the National Academy of Sciences, U.S.A., 100, 253\u2013258.","DOI":"10.1073\/pnas.0135058100"},{"key":"2021072107050526600_bib19","doi-asserted-by":"crossref","unstructured":"Griffis,  J. C., Elkhetali,  A. S., Burge,  W. K., Chen,  R. H., & Visscher,  K. M. (2015). Retinotopic patterns of background connectivity between V1 and fronto-parietal cortex are modulated by task demands. Frontiers in Human Neuroscience, 9, 338.","DOI":"10.3389\/fnhum.2015.00338"},{"key":"2021072107050526600_bib20","doi-asserted-by":"crossref","unstructured":"He,  B. J., & Raichle,  M. E. (2009). The fMRI signal, slow cortical potential and consciousness. Trends in Cognitive Sciences, 13, 302\u2013309.","DOI":"10.1016\/j.tics.2009.04.004"},{"key":"2021072107050526600_bib21","doi-asserted-by":"crossref","unstructured":"Herrero,  J. L., Gieselmann,  M. A., Sanayei,  M., & Thiele,  A. (2013). Attention-induced variance and noise correlation reduction in macaque V1 is mediated by NMDA receptors. Neuron, 78, 729\u2013739.","DOI":"10.1016\/j.neuron.2013.03.029"},{"key":"2021072107050526600_bib22","doi-asserted-by":"crossref","unstructured":"Hesselmann,  G., Kell,  C. A., & Kleinschmidt,  A. (2008). Ongoing activity fluctuations in hMT+ bias the perception of coherent visual motion. Journal of Neuroscience, 28, 14481\u201314485.","DOI":"10.1523\/JNEUROSCI.4398-08.2008"},{"key":"2021072107050526600_bib23","doi-asserted-by":"crossref","unstructured":"Huk,  A., Bonnen,  K., & He,  B. J. (2018). Beyond trial-based paradigms: Continuous behavior, ongoing neural activity, and natural stimuli. Journal of Neuroscience, 38, 7551\u20137558.","DOI":"10.1523\/JNEUROSCI.1920-17.2018"},{"key":"2021072107050526600_bib24","doi-asserted-by":"crossref","unstructured":"Imamoglu,  F., Heinzle,  J., Imfeld,  A., & Haynes,  J. D. (2014). Activity in high-level brain regions reflects visibility of low-level stimuli. Neuroimage, 102, 688\u2013694.","DOI":"10.1016\/j.neuroimage.2014.08.045"},{"key":"2021072107050526600_bib25","doi-asserted-by":"crossref","unstructured":"Jenkinson,  M., Bannister,  P., Brady,  M., & Smith,  S. (2002). Improved optimization for the robust and accurate linear registration and motion correction of brain images. Neuroimage, 17, 825\u2013841.","DOI":"10.1006\/nimg.2002.1132"},{"key":"2021072107050526600_bib26","doi-asserted-by":"crossref","unstructured":"Keller,  C. J., Bickel,  S., Honey,  C. J., Groppe,  D. M., Entz,  L., Craddock,  R. C., et al (2013). Neurophysiological investigation of spontaneous correlated and anticorrelated fluctuations of the BOLD signal. Journal of Neuroscience, 33, 6333\u20136342.","DOI":"10.1523\/JNEUROSCI.4837-12.2013"},{"key":"2021072107050526600_bib27","doi-asserted-by":"crossref","unstructured":"Larsson,  J., & Heeger,  D. J. (2006). Two retinotopic visual areas in human lateral occipital cortex. Journal of Neurosciencce, 26, 13128\u201313142.","DOI":"10.1523\/JNEUROSCI.1657-06.2006"},{"key":"2021072107050526600_bib28","doi-asserted-by":"crossref","unstructured":"Logothetis,  N. K., Pauls,  J., Augath,  M., Trinath,  T., & Oeltermann,  A. (2001). Neurophysiological investigation of the basis of the fMRI signal. Nature, 412, 150\u2013157.","DOI":"10.1038\/35084005"},{"key":"2021072107050526600_bib29","doi-asserted-by":"crossref","unstructured":"Mathewson,  K. E., Gratton,  G., Fabiani,  M., Beck,  D. M., & Ro,  T. (2009). To see or not to see: Prestimulus alpha phase predicts visual awareness. Journal of Neuroscience, 29, 2725\u20132732.","DOI":"10.1523\/JNEUROSCI.3963-08.2009"},{"key":"2021072107050526600_bib30","doi-asserted-by":"crossref","unstructured":"Maunsell,  J. H. R.\n           (2015). Neuronal mechanisms of visual attention. Annual Review of Vision Science, 1, 373\u2013391.","DOI":"10.1146\/annurev-vision-082114-035431"},{"key":"2021072107050526600_bib31","doi-asserted-by":"crossref","unstructured":"McAdams,  C. J., & Maunsell,  J. H. R. (1999). Effects of attention on the reliability of individual neurons in monkey visual cortex. 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Journal of Neuroscience, 28, 8268\u20138272.","DOI":"10.1523\/JNEUROSCI.1910-08.2008"},{"key":"2021072107050526600_bib35","doi-asserted-by":"crossref","unstructured":"Mukamel,  R., Gelbard,  H., Arieli,  A., Hasson,  U., Fried,  I., & Malach,  R. (2005). Coupling between neuronal firing, field potentials, and fMRI in human auditory cortex. Science, 309, 951\u2013954.","DOI":"10.1126\/science.1110913"},{"key":"2021072107050526600_bib36","doi-asserted-by":"crossref","unstructured":"M\u00fcller,  N. G., & Kleinschmidt,  A. (2004). The attentional \u2018spotlight's\u2019 penumbra: Center-surround modulation in striate cortex. NeuroReport, 15, 977\u2013980.","DOI":"10.1097\/00001756-200404290-00009"},{"key":"2021072107050526600_bib37","doi-asserted-by":"crossref","unstructured":"Murray,  S. O., & He,  S. (2006). Contrast invariance in the human lateral occipital complex depends on attention. Current Biology, 16, 606\u2013611.","DOI":"10.1016\/j.cub.2006.02.019"},{"key":"2021072107050526600_bib38","doi-asserted-by":"crossref","unstructured":"Nir,  Y., Fisch,  L., Mukamel,  R., Gelbard-Sagiv,  H., Arieli,  A., Fried,  I., et al (2007). Coupling between neuronal firing rate, gamma LFP, and BOLD fMRI is related to interneuronal correlations. Current Biology, 17, 1275\u20131285.","DOI":"10.1016\/j.cub.2007.06.066"},{"key":"2021072107050526600_bib39","doi-asserted-by":"crossref","unstructured":"Ress,  D., Backus,  B. T., & Heeger,  D. J. (2000). Activity in primary visual cortex predicts performance in a visual detection task. Nature Neuroscience, 3, 940\u2013945.","DOI":"10.1038\/78856"},{"key":"2021072107050526600_bib40","doi-asserted-by":"crossref","unstructured":"Ringach,  D. L.\n           (2009). Spontaneous and driven cortical activity: Implications for computation. Current Opinion in Neurobiology, 19, 439\u2013444.","DOI":"10.1016\/j.conb.2009.07.005"},{"key":"2021072107050526600_bib41","doi-asserted-by":"crossref","unstructured":"Ruff,  D. A., & Cohen,  M. R. (2014). Attention can either increase or decrease spike count correlations in visual cortex. Nature Neuroscience, 17, 1591\u20131597.","DOI":"10.1038\/nn.3835"},{"key":"2021072107050526600_bib42","doi-asserted-by":"crossref","unstructured":"Sch\u00f6lvinck,  M. L., Friston,  K. J., & Rees,  G. (2012). The influence of spontaneous activity on stimulus processing in primary visual cortex. Neuroimage, 59, 2700\u20132708.","DOI":"10.1016\/j.neuroimage.2011.10.066"},{"key":"2021072107050526600_bib43","doi-asserted-by":"crossref","unstructured":"Sch\u00f6lvinck,  M. L., Maier,  A., Ye,  F. Q., Duyn,  J. H., & Leopold,  D. A. (2010). Neural basis of global resting-state fMRI activity. Proceedings of the National Academy of Sciences, U.S.A., 107, 10238\u201310243.","DOI":"10.1073\/pnas.0913110107"},{"key":"2021072107050526600_bib44","doi-asserted-by":"crossref","unstructured":"Sereno,  M. I., Dale,  A. M., Reppas,  J. B., Kwong,  K. K., Belliveau,  J. W., Brady,  T. J., et al (1995). Borders of multiple visual areas in humans revealed by functional magnetic resonance imaging. Science, 268, 889\u2013893.","DOI":"10.1126\/science.7754376"},{"key":"2021072107050526600_bib45","doi-asserted-by":"crossref","unstructured":"Shmuel,  A., & Leopold,  D. A. (2008). Neuronal correlates of spontaneous fluctuations in fMRI signals in monkey visual cortex: Implications for functional connectivity at rest. Human Brain Mapping, 29, 751\u2013761.","DOI":"10.1002\/hbm.20580"},{"key":"2021072107050526600_bib46","doi-asserted-by":"crossref","unstructured":"Shmueli,  K., van Gelderen,  P., de Zwart,  J. A., Horovitz,  S. G., Fukunaga,  M., Jansma,  J. M., et al (2007). Low-frequency fluctuations in the cardiac rate as a source of variance in the resting-state fMRI BOLD signal. Neuroimage, 38, 306\u2013320.","DOI":"10.1016\/j.neuroimage.2007.07.037"},{"key":"2021072107050526600_bib47","doi-asserted-by":"crossref","unstructured":"Silver,  M. A., Ress,  D., & Heeger,  D. J. (2005). Topographic maps of visual spatial attention in human parietal cortex. Journal of Neurophysiology, 94, 1358\u20131371.","DOI":"10.1152\/jn.01316.2004"},{"key":"2021072107050526600_bib48","doi-asserted-by":"crossref","unstructured":"Silver,  M. A., Ress,  D., & Heeger,  D. J. (2007). Neural correlates of sustained spatial attention in human early visual cortex. Journal of Neurophysiology, 97, 229\u2013237.","DOI":"10.1152\/jn.00677.2006"},{"key":"2021072107050526600_bib49","doi-asserted-by":"crossref","unstructured":"Sup\u00e8r,  H., van der Togt,  C., Spekreijse,  H., & Lamme,  V. A. F. (2003). Internal state of monkey primary visual cortex (V1) predicts figure-ground perception. Journal of Neuroscience, 23, 3407\u20133414.","DOI":"10.1523\/JNEUROSCI.23-08-03407.2003"},{"key":"2021072107050526600_bib50","doi-asserted-by":"crossref","unstructured":"Turchi,  J., Chang,  C., Ye,  F. Q., Russ,  B. E., Yu,  D. K., Cortes,  C. R., et al (2018). The basal forebrain regulates global resting-state fMRI fluctuations. Neuron, 97, 940\u2013952.","DOI":"10.1016\/j.neuron.2018.01.032"},{"key":"2021072107050526600_bib51","doi-asserted-by":"crossref","unstructured":"Wandell,  B. A., Chial,  S., & Backus,  B. T. (2000). Visualization and measurement of the cortical surface. Journal of Cognitive Neuroscience, 12, 739\u2013752.","DOI":"10.1162\/089892900562561"},{"key":"2021072107050526600_bib52","doi-asserted-by":"crossref","unstructured":"Weissman,  D. H., Roberts,  K. C., Visscher,  K. M., & Woldorff,  M. G. (2006). The neural bases of momentary lapses in attention. 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Neuroimage, 83, 983\u2013990.","DOI":"10.1016\/j.neuroimage.2013.07.057"},{"key":"2021072107050526600_bib56","doi-asserted-by":"crossref","unstructured":"Xu,  J., Rees,  G., Yin,  X., Song,  C., Han,  Y., Ge,  H., et al (2014). Spontaneous neuronal activity predicts intersubject variations in executive control of attention. Neuroscience, 263, 181\u2013192.","DOI":"10.1016\/j.neuroscience.2014.01.020"},{"key":"2021072107050526600_bib57","doi-asserted-by":"crossref","unstructured":"Yantis,  S., Schwarzbach,  J., Serences,  J. T., Carlson,  R. L., Steinmetz,  M. A., Pekar,  J. J., et al (2002). Transient neural activity in human parietal cortex during spatial attention shifts. Nature Neuroscience, 5, 995\u20131002.","DOI":"10.1038\/nn921"},{"key":"2021072107050526600_bib58","doi-asserted-by":"crossref","unstructured":"Zarahn,  E., Aguirre,  G. K., & D'Esposito,  M. (1997). Empirical analyses of BOLD fMRI statistics. I. Spatially unsmoothed data collected under null-hypothesis conditions. 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