{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,11,15]],"date-time":"2026-11-15T10:47:36Z","timestamp":1794739656081,"version":"4.9.1"},"reference-count":57,"publisher":"Society for Neuroscience","issue":"18","license":[{"start":{"date-parts":[[2016,11,4]],"date-time":"2016-11-04T00:00:00Z","timestamp":1478217600000},"content-version":"vor","delay-in-days":184,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-sa\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["J. Neurosci."],"published-print":{"date-parts":[[2016,5,4]]},"abstract":"<jats:p>\n                    The perception of pain is strongly influenced by cognitive processes, such as expectations toward the efficacy of pain medication. It is reasonable to assume that such processes, among other sources of fluctuation, are reflected in ongoing brain activity, which in turn influences perceptual processing. To identify specific prestimulus EEG activity, and connectivity patterns related to subsequent pain perception in humans, we contrasted painful with nonpainful sensations delivered at the individual threshold level determined by the psychophysical QUEST estimation method (Watson and Pelli, 1983). The 64-channel EEG was recorded using active electrodes during a constant stimulation procedure. The power contrast between trials sorted by rating revealed a signal decrease of 8% before stimulus onset in theta-band (4\u20137 Hz) at T7\/FT7 as well as increased theta-power by 6% at T8\/FT8. Gamma-band power was increased (12%, 28\u201332 Hz) at frontocentral sites (all\n                    <jats:italic>p<\/jats:italic>\n                    &lt; 0.05). Changes in theta-band power are covarying with subsequent pain perception, as well as lowered frontolateral theta-band connectivity for painful percepts. A decrease in frontoparietal connectivity for painful sensations was also identified in the gamma-band (28\u201332 Hz). A single-trial logistic regression revealed significant information content in the EEG signal at temporal electrode T7 in theta-band (\n                    <jats:italic>p<\/jats:italic>\n                    &lt; 0.01) and frontal electrode F1 in gamma-band (all\n                    <jats:italic>p<\/jats:italic>\n                    &lt; 0.02). The observed patterns suggest top-down modulation of the theta-band effects by a frontocentral network node. These findings contribute to the understanding of ongoing subjective pain sensitivity, potentially relevant to both clinical diagnostics and pain management.\n                  <\/jats:p>\n                  <jats:p>\n                    <jats:bold>SIGNIFICANCE STATEMENT<\/jats:bold>\n                    The perceived intensity of a constant stimulus is known to vary considerably across multiple presentations. Here, we used state-of-the-art psychophysical methods in an EEG experiment to identify the specific neuronal activity before stimulus onset that reflects the subsequent perception of pain. We found specific oscillatory activity at the bilateral insular cortices as well as connectivity patterns that reflect and correlate with subsequent ratings. These results further the understanding of pain perception and are potentially relevant for the decoding of ongoing pain sensitivity and pain management.\n                  <\/jats:p>","DOI":"10.1523\/jneurosci.3325-15.2016","type":"journal-article","created":{"date-parts":[[2016,5,4]],"date-time":"2016-05-04T13:52:48Z","timestamp":1462369968000},"page":"5026-5033","source":"Crossref","is-referenced-by-count":84,"title":["Prestimulus Theta Oscillations and Connectivity Modulate Pain Perception"],"prefix":"10.1523","volume":"36","author":[{"given":"Philipp","family":"Taesler","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Michael","family":"Rose","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"393","published-online":{"date-parts":[[2016,5,4]]},"reference":[{"key":"2023041803185698000_36.18.5026.1","doi-asserted-by":"crossref","first-page":"289","DOI":"10.1111\/j.2517-6161.1995.tb02031.x","article-title":"Controlling the false discovery rate: a practical and powerful approach to multiple testing","volume":"57","author":"Benjamini","year":"1995","journal-title":"J R Stat Soc Ser B"},{"key":"2023041803185698000_36.18.5026.2","doi-asserted-by":"publisher","DOI":"10.1126\/scitranslmed.3001244"},{"key":"2023041803185698000_36.18.5026.3","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.0611404104"},{"key":"2023041803185698000_36.18.5026.4","doi-asserted-by":"publisher","DOI":"10.1163\/156856897X00357"},{"key":"2023041803185698000_36.18.5026.5","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2012.08.035"},{"key":"2023041803185698000_36.18.5026.6","doi-asserted-by":"publisher","DOI":"10.1016\/j.pain.2007.05.022"},{"key":"2023041803185698000_36.18.5026.7","doi-asserted-by":"publisher","DOI":"10.1093\/brain\/awl004"},{"key":"2023041803185698000_36.18.5026.8","doi-asserted-by":"publisher","DOI":"10.1016\/j.neulet.2012.02.076"},{"key":"2023041803185698000_36.18.5026.9","unstructured":"Chernick MR (2011) Bootstrap methods: a guide for practitioners and researchers (Wiley, New York)."},{"key":"2023041803185698000_36.18.5026.10","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.1430684100"},{"key":"2023041803185698000_36.18.5026.11","unstructured":"Cohen J (1988) Statistical power analysis for the behavioral sciences (L. 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