Gollisch, Tim, Prof. Dr.

Professor for Sensory Processing in the Retina

  • Diploma in Physics, University of Heidelberg, 2000
  • PhD in Biophysics, Humboldt University Berlin, 2004

  • Postdoctoral Researcher, Harvard University, Dept. of Molecular and Cellular Biology, 2004-2007

  • Max Planck Research Group Leader, Max Planck Institute of Neurobiology, Munich-Martinsried, 2007-2010
  • Professor for Sensory Processing in the Retina, School of Medicine, University of Göttingen since 2010

  • Major Research Interests

    We are interested in how the neuronal network of the retina processes visual information. The focus of our work is on studying the function of the various neuron types in the retina and their synaptic connections. One goal is to better understand the “neural code” of the retina: how do the patterns of electrical activity in retinal neurons transmit information about the visual environment to downstream brain areas? Another goal is to better understand “neural computation” in the retina: how do the cells in the retinal network work, adapt, and interact to produce specific, useful responses? On the basis of these questions, we also study how dysfunction of the retinal circuitry, for example in retinal diseases, compromises sensory processing and how optogenetics can be used to artificially stimulate retinal neurons for vision restoration when photoreceptors are degenerating.
    Our investigations are based on various techniques of recording the activity of neurons in the retina while stimulating the network with visual images or movies. To do so, we use isolated retinas of mice and salamanders and apply extracellular multi-electrode array recordings and intracellular recordings with glass pipettes. A central theme of our work is to combine the experiments with novel tools of data analysis and with mathematical modeling of the signal processing in the retina.

    Homepage Department/Research Group


    Selected Recent Publications

    • Schreyer HM, Gollisch T (2021) Nonlinearities in retinal bipolar cells shape the encoding of artificial and natural stimuli. Neuron 109:1692-1706.
    • Karamanlis D, Gollisch T (2021) Nonlinear spatial integration underlies the diversity of retinal ganglion cell responses to natural images. J Neurosci 41: 3479-3498.
    • Khani MH, Gollisch T (2021) Linear and nonlinear chromatic integration in the mouse retina. Nature Communications 12:1900.
    • Kühn NK, Gollisch T (2019) Activity correlations between direction-selective retinal ganglion cells synergistically enhance motion decoding from complex visual scenes. Neuron 101.963-976.
    • Liu JK, Schreyer HM, Onken A, Rozenblit F, Khani MH, Krishnamoorthy V, Panzeri S, Gollisch T (2017) Inference of neuronal functional circuitry with spike-triggered non-negative matrix factorization. Nature Communications 8:149.
    • Krishnamoorthy V, Weick M, Gollisch T (2017) Sensitivity to image recurrence across eye-movement-like image transitions through local serial inhibition in the retina. eLife 6:322431.
    • Kühn NK, Gollisch T (2016) Joint encoding of object motion and motion direction in the salamander retina. J Neurosci 36:12203-12216.
    • Liu JK, Gollisch T (2015) Spike-triggered covariance analysis reveals phenomenological diversity of contrast adaptation in the retina. PLoS Comput Biol 11:e1004425.
    • Takeshita D, Gollisch T (2014) Nonlinear spatial integration in the receptive field surround of retinal ganglion cells. J Neurosci 34:7548-7561.
    • Garvert MM, Gollisch T (2013) Local and global contrast adaptation in retinal ganglion cells. Neuron 77:915-928.
    • Bölinger D, Gollisch T (2012) Closed-loop measurements of iso-response stimuli reveal dynamic nonlinear stimulus integration in the retina. Neuron 73:333-346.