Carnegie Mellon University
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Dr. Marlene Behrmann

Dr. Marlene Behrmann is a Professor of Psychology at Carnegie Mellon University, who's research specializes in the cognitive basis of visual perception, with a specific focus on object recognition. Dr. Behrmann received her B.A. in speech and hearing therapy in 1981, followed by her M.A. in speech pathology in 1984, both from the University of Witwatersrand in Johannesburg, South Africa. She then received a Ph.D. in Psychology from the University of Toronto in 1991. Dr Behrmann was inducted into the National Academy of Sciences in 2015.

Dr. Behrmann is widely considered to be a trailblazer and a worldwide leader in the field of visual cognition. Above and below are some examples of recently published papers:

Fig 1

Robinson, A., Venkatesh, P., Boring, M. J., Tarr, M., Behrmann, M., and Grover, P. (2017). Very high density EEG elucidates spatiotemporal aspects of early visual processing, Scientific Reports, 7(1):16248. doi: 10.1038/s41598-017-16377-3. PMID: 29176609

Standard human EEG systems based on spatial Nyquist estimates suggest that 20-30 mm electrode spacing suffices to capture neural signals on the scalp, but recent studies posit that increasing sensor density can provide higher resolution neural information. Here, we compared “super-Nyquist” density EEG (“SND”) with Nyquist density (“ND”) arrays for assessing the spatiotemporal aspects of early visual processing. EEG was measured from 128 electrodes arranged over occipitotemporal brain regions (14 mm spacing) while participants viewed flickering checkerboard stimuli. Analyses compared SND with ND-equivalent subsets of the same electrodes. Frequency-tagged stimuli were classified more accurately with SND than ND arrays in both the time and the frequency domains. Representational similarity analysis revealed that a computational model of V1 correlated more highly with the SND than the ND array. Overall, SND EEG captured more neural information from visual cortex, arguing for increased development of this approach in basic and translational neuroscience.

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