ZiF Research Group

Cognitive Behavior of Humans, Animals, and Machines:

Situation Model Perspectives

October 2019 – July 2020

Convenors: Werner Schneider (Bielefeld, GER), Helge Ritter (Bielefeld, GER)

Michael Herzog

Fellow

Foto Laboratory of Psychophysics,
Brain Mind Institute, EPFL, Switzerland
E-Mail: michael.herzog@epfl.ch
Homepage



CV

Michael Herzog studied mathematics and philosophy and received a Ph.D. in biology (supervision: Prof. Fahle (Tübingen) and Prof. Poggio (MIT)). Post-doc at Caltech (Prof. Koch). 1999-2003, senior researcher (University of Bremen). Professorship for Neurobiopsychology (University of Osnabrück). Since 2004, professor for Psychophysics at the Brain Mind Institute at EPFL.

Current Main Research Interests

To cope with the complexity of vision, most models in neuroscience and computer vision are of hierarchical and feedforward nature. There is an isomorphism between states of the outer world, neural circuits, and perception, inspired by the positivistic philosophy of the mind. We have shown that, although such an approach is conceptually and mathematically appealing, it fails to explain core phenomena including spatial crowding, temporal visual masking, and non-retinotopic processing. We propose that vision is based on a grouping stage, which operates on all levels of processing, last for several hundreds of milliseconds and includes short term memory. Because of the complex grouping process, there cannot be an isomorphism between external world states, basic stereotyped circuits, and perception. Subjective terms such as grouping can, at least for the moment, not be eliminated.

Five selected publications with particular relevance to the Research Group
  • Herzog M. H., Kammer T., Scharnowski F. (2016). Time Slices: What Is the Duration of a Percept? PLoS Biology, 14, e1002433. doi:10.1371/journal.pbio.1002433
  • Herzog M. H., Thunell E., Ögmen H., (2016). Putting low-level vision into Global context: why vision cannot be reduced to basic circuits. Vision Research, 126, 9-18.
  • Herzog, M. H. and Manassi, M. (2015). Uncorking the bottleneck of crowding: a fresh look at object recognition. Current Opinion in Behavioral Sciences, 1, 86-93.
  • Rüter J., Marcille N., Sprekeler, H., Gerstner W. & Herzog M. H. (2012). Paradoxical evidence integration in rapid decision processes. PLoS Computational Biology, 8, e1002382.
  • Tartaglia E. M., Bamert L., Mast F. W., Herzog M. H. (2009). Human perceptual learning by mental imagery. Current Biology, 19, 2081-2085.