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Spatiotemporal Properties of Common Semantic Categories for Words and Pictures.
Bezsudnova, Yulia; Quinn, Andrew J; Wynn, Syanah C; Jensen, Ole.
Afiliación
  • Bezsudnova Y; University of Birmingham.
  • Quinn AJ; University of Birmingham.
  • Wynn SC; University of Birmingham.
  • Jensen O; Gutenberg University Medical Center Mainz.
J Cogn Neurosci ; 36(8): 1760-1769, 2024 Jul 01.
Article en En | MEDLINE | ID: mdl-38739567
ABSTRACT
The timing of semantic processing during object recognition in the brain is a topic of ongoing discussion. One way of addressing this question is by applying multivariate pattern analysis to human electrophysiological responses to object images of different semantic categories. However, although multivariate pattern analysis can reveal whether neuronal activity patterns are distinct for different stimulus categories, concerns remain on whether low-level visual features also contribute to the classification results. To circumvent this issue, we applied a cross-decoding approach to magnetoencephalography data from stimuli from two different modalities images and their corresponding written words. We employed items from three categories and presented them in a randomized order. We show that if the classifier is trained on words, pictures are classified between 150 and 430 msec after stimulus onset, and when training on pictures, words are classified between 225 and 430 msec. The topographical map, identified using a searchlight approach for cross-modal activation in both directions, showed left lateralization, confirming the involvement of linguistic representations. These results point to semantic activation of pictorial stimuli occurring at ∼150 msec, whereas for words, the semantic activation occurs at ∼230 msec.
Asunto(s)

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Reconocimiento Visual de Modelos / Semántica / Magnetoencefalografía Límite: Adult / Female / Humans / Male Idioma: En Revista: J Cogn Neurosci Asunto de la revista: NEUROLOGIA Año: 2024 Tipo del documento: Article

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Reconocimiento Visual de Modelos / Semántica / Magnetoencefalografía Límite: Adult / Female / Humans / Male Idioma: En Revista: J Cogn Neurosci Asunto de la revista: NEUROLOGIA Año: 2024 Tipo del documento: Article