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      Noninvasively decoding the contents of visual working memory in the human prefrontal cortex within high-gamma oscillatory patterns.

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          Abstract

          The temporal maintenance and subsequent retrieval of information that no longer exists in the environment is called working memory. It is believed that this type of memory is controlled by the persistent activity of neuronal populations, including the prefrontal, temporal, and parietal cortex. For a long time, it has been controversially discussed whether, in working memory, the PFC stores past sensory events or, instead, its activation is an extramnemonic source of top-down control over posterior regions. Recent animal studies suggest that specific information about the contents of working memory can be decoded from population activity in prefrontal areas. However, it has not been shown whether the contents of working memory during the delay periods can be decoded from EEG recordings in the human brain. We show that by analyzing the nonlinear dynamics of EEG oscillatory patterns it is possible to noninvasively decode with high accuracy, during encoding and maintenance periods, the contents of visual working memory information within high-gamma oscillations in the human PFC. These results are thus in favor of an active storage function of the human PFC in working memory; this, without ruling out the role of PFC in top-down processes. The ability to noninvasively decode the contents of working memory is promising in applications such as brain computer interfaces, together with computation of value function during planning and decision making processes.

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          Author and article information

          Journal
          J Cogn Neurosci
          Journal of cognitive neuroscience
          1530-8898
          0898-929X
          Feb 2012
          : 24
          : 2
          Affiliations
          [1 ] Department of Clinical Neurophysiology, Georg-August University of Göttingen, Robert Koch Str 40, 37075 Göttingen, Germany. rafael.polania@med.uni-goettingen.de
          Article
          10.1162/jocn_a_00151
          21981673
          481ce4d1-97fe-41f2-9c9b-b4ced01e371b
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