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Roger Koenig-Robert, Rufin VanRullen; Frequency-tagging object awareness. Journal of Vision 2011;11(11):882. doi: 10.1167/11.11.882.
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© ARVO (1962-2015); The Authors (2016-present)
The rate of visual information processing in humans has been studied with different techniques. For example, the Steady-State Visual Evoked Potentials (SSVEP) method modulates stimulus luminance at a specific frequency, and reveals a corresponding “frequency tagging” at rates up to 10–20 Hz. Such luminance fluctuations, however, directly affect the earliest processing stages, whose influence cascades to the entire visual system. Hence it is impossible with classic SSVEP to distinguish neural correlates of high-level object representations (semantic content) from low-level activities. Here we present a novel technique called Semantic Wavelet-Induced Frequency Tagging (SWIFT) in which advanced image manipulation allows us to isolate object representations using frequency-tagging. By periodically scrambling the image in the wavelets domain we modulate its semantic content (object form), without disturbing local or global low-level attributes. Human observers (N = 16) watched sequences containing no real object, or objects that were either easily or difficultly detectable. Each trial consisted in two periods: a naive period where the subject saw the sequence for the first time (and sometimes did not consciously recognize the embedded object) and a cognizant period where the sequence was presented again after revealing the object identity. When no object was perceived (i.e., either the sequence contained no object or the object was not recognized), the evoked activity was no different from baseline; but whenever observers were aware of the semantic content a tagging response emerged. In a separate experiment (N = 24) we compared SWIFT with classic SSVEP at 8 tagging frequencies between 1.5 and 12 Hz. While classic SSVEP was insensitive to object-content, SWIFT responded only to sequences containing objects, and at frequencies up to ∼4 Hz. The SWIFT technique promises to be an elegant EEG method for tracking high-level activity –our first results indicate that the visual system can only form 3 to 4 distinct object representations per second.
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