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This\n                investigation examines the presence of precise neural markers of imagined\n                motivational states through the combining of electrophysiological and neuroimaging\n                methods. 20 participants were instructed to vividly imagine the desire to move,\n                listen to music or engage in social activities. Their EEG was recorded from 128\n                scalp sites and analysed using individual standardized Low-Resolution Brain\n                Electromagnetic Tomographies (LORETAs) in the N400 time window (400\u2013600 ms).\n                The activation of 1056 voxels was examined in relation to the 3 motivational states.\n                The most active dipoles were grouped in eight regions of interest (ROI), including\n                Occipital, Temporal, Fusiform, Premotor, Frontal, OBF\/IF, Parietal, and Limbic\n                areas. The statistical analysis revealed that all motivational imaginary states\n                engaged the right hemisphere more than the left hemisphere. Distinct markers were\n                identified for the three motivational states. Specifically, the right temporal area\n                was more relevant for \u201cSocial Play\u201d, the orbitofrontal\/inferior\n                frontal cortex for listening to music, and the left premotor cortex for the\n                \u201cMovement\u201d desire. This outcome is encouraging in terms of the\n                potential use of neural indicators in the realm of brain-computer interface, for\n                interpreting the thoughts and desires of individuals with locked-in syndrome.<\/jats:p>","DOI":"10.1007\/s10548-024-01047-1","type":"journal-article","created":{"date-parts":[[2024,4,16]],"date-time":"2024-04-16T15:28:39Z","timestamp":1713281319000},"page":"806-825","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Neural signatures of imaginary motivational\n            states: desire for music, movement and social play"],"prefix":"10.1007","volume":"37","author":[{"given":"Giada","family":"Della Vedova","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Alice Mado","family":"Proverbio","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2024,4,16]]},"reference":[{"issue":"1","key":"1047_CR1","doi-asserted-by":"publisher","first-page":"33","DOI":"10.1080\/19585969.2023.2208586","volume":"25","author":"S Antons","year":"2023","unstructured":"Antons S, Yip SW, Lacadie CM, Dadashkarimi J, Scheinost D, Brand M,\n                    Potenza MN (2023) Connectome-based prediction of craving in gambling disorder\n                    and cocaine use disorder. 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