Repository for Ed Awh's presentation at the CSS Workshop (1/10/2018)
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The Computational Social Science Workshop Presents
Ed Awh
Professor, Department of Psychology, The Institute for Mind and Biology, and the Grossman Institute for Neuroscience, Quantitative Biology and Human Behavior
**Summary:** Recent advances in multivariate decoding have enabled a new class of questions to be addressed using neural data. While much progress has been made by focusing on the amplitude and locus of neural responses in the brain, newer methods focused on the specific pattern of activity within a given region or set of regions can complement earlier approaches by decoding the content of the representations in specific neural regions. Here, I'll review recent work from our lab that has applied these methods to EEG activity measured from the human brain. Using an inverted encoding analysis, we are able to reconstruct spatial representations that are held in mind during storage in working memory, during covert orienting of spatial attention, and during the retrieval of spatial representations from long term memory. This precise and temporally-resolved method is opening new doors for studying the limits of online memory and attention.
Thursday, 1/10/2019
11:00am-12:20pm
Kent 120
A light lunch will be provided by Papa John's.
**Ed Awh** is a professor in the Department of Psychology, The Institute for Mind and Biology, and the Grossman Institute for Neuroscience, Quantitative Biology and Human Behavior. His laboratory focuses on behavioral and neural studies of memory and attention. Dr. Awh’s lab employs psychophysics, EEG, and functional MRI to learn about the neural mechanisms underlying these basic cognitive processes and the relationship between these processes and other cognitive functions. Recent work has focused on the use of neural decoding techniques to track the contents of online memories and the locus of covert attention.
The 2018-2019 Computational Social Science Workshop meets Thursdays from 11 a.m. to 12:20 p.m. in Kent 120. All interested faculty and graduate students are welcome.
Students in the Masters of Computational Social Science program are expected to attend and join the discussion by posting a comment on the issues page of the workshop's public repository on GitHub. Further instructions are documented in the Computational Social Science Workshop's README on Github.