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Allison Bruning, Michael Pratte; Decoding the Contents of Working Memory Using EEG Provides Evidence For the Sensory Recruitment Hypothesis. Journal of Vision 2017;17(10):340. doi: https://doi.org/10.1167/17.10.340.
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© ARVO (1962-2015); The Authors (2016-present)
Recent fMRI studies have shown that the contents of visual working memory can be decoded from early visual areas, including V1. This result has been interpreted as support for the sensory recruitment hypothesis: the idea that the neurons responsible for vision also sub-serve visual working memory and visual imagery. However, whereas these results imply that the same brain areas are responsible for vision and visual memory, they do not rule out the possibility that these processes rely on completely different populations of neurons within these areas. For example, although viewing and remembering an orientation might lead to the same global radial bias pattern in V1, entirely different neurons may produce these patterns during vision and memory. We develop a novel EEG paradigm that allows us to directly test whether the same neurons responsible for processing incoming visual signals are indeed modulated by an internally driven memory signal. Participants held an orientation in working memory while viewing a flicking visual noise patch. This flickering stimulus generated an EEG response known as the steady state visually evoked potential (SSVEP), a measure of early neural responses to the noise stimulus. Critically, if memory relies on these same visual neurons, then the SSVEP response to visual stimulation should also carry information about the stimulus being held in memory. We confirm this prediction by showing that a multivariate pattern classifier can be used to identify a remembered orientation from the stimulus-driven SSVEP. This finding demonstrates a direct interaction between a bottom-up stimulus-driven signal and a top-down memory-driven signal, providing strong evidence for the sensory recruitment hypothesis and a powerful new approach for investigating visual memory with EEG.
Meeting abstract presented at VSS 2017
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