Contact

Prof. Dr. Jutta Kretzberg 
Tel.: +49-(0)441-798-3314 
E-Mail: jutta.kretzberg@uol.de 
Office: W4-0-078

Computational Neuroscience

Computational Neuroscience

 

 Welcome to the Computational Neuroscience division!

Our group is interested in the question of sensory coding:

How are sensory stimuli represented and processed in nervous systems?

 

Currently, we mainly work on this questions in two systems:

The tactile system of the leech

Even though the leech seems scary to many people because of it's food preference for warm blood, it is much more sensitive than one would expect for an organism with such a tiny nervous system. When touched, the leech is able to behaviorally discriminate the position of the tactile stimulus as precisely as the human finger tip - even though only 10 sensory cells of three types are located in each segment. Since the leech tactile system shows surprising similarities to the primate perception of touch, this simple invertebrate system can help to analyze fundamental principles of sensory coding and the processing of tactile stimuli.

In our research, we study with a combination of intracellular electrophysiology, voltage-sensitive dyes, data analysis and computational modeling how a minimalistic nervous system can produce precise behavioral reactions to sensory stimulation.

Recent publications

  • Scherer, J.S., Sandbote, K., Schultze B.L., Kretzberg, J. (2023) Synaptic input and temperature influence sensory coding in a mechanoreceptor. Front. Cell. Neurosci. 17:1233730.
    doi: 10.3389/fncel.2023.1233730
  • Meiser, S., Sleeboom, J.M., Arkhypchuk, I., Sandbote, K., Kretzberg, J. (2023) Cell anatomy and network input explain differences within but not between leech touch cells at two different locations. Front. Cell. Neurosci. 17:1186997. doi: 10.3389/fncel.2023.1186997
  • Scherer, J.S., Riedesel, O.E., Arkhypchuk, I., Meisner, S., Kretzberg, J. (2022) Initial Variability and Time-Dependent Changes of Neuronal Response Features Are Cell-Type-Specific. Front. Cell. Neurosci. 16:858221. doi: 10.3389/fncel.2022.858221
  • Meiser, S., Ashida, G., & Kretzberg, J. (2019). Non-synaptic Plasticity in Leech Touch Cells. Frontiers in Physiology, 10, article 1444, pp. 1-14. doi: 10.3389/fphys.2019.01444
  • Pirschel, F., Hilgen, G., & Kretzberg, J. (2018). Effects of touch location and intensity on interneurons of the leech local bend network. Scientific reports8(1), 3046
  • Fathiazar, E., Hilgen, G., & Kretzberg, J. (2018). Higher Network Activity Induced by Tactile Compared to Electrical Stimulation of Leech Mechanoreceptors. Frontiers in physiology9, 173.
  • F. Pirschel, J. Kretzberg (2016) "Multiplexed Population Coding of Stimulus Properties by Leech Mechanosensory Cells" The Journal of Neuroscience, 36(13): 3636-3647
  • Kretzberg, J, et al.  (2016), "Encoding of Tactile Stimuli by Mechanoreceptors and Interneurons of the Medicinal Leech", Frontiers in physiology 7 (2016)

The vertebrate auditory system

Humans and many non-human animals have two ears. Having two ears is highly beneficial for our perception of sounds. When a sound is coming from your left side, the sound wave arriving at your left ear is slightly stronger and slightly earlier than at your right ear. Our brain has special circuits for detecting these subtle differences to find out the location of the sound source. Relevant neurons in these neuronal circuits sense, for example, sound timing differences of far less than one millisecond, which constitutes one of the fastest neural computations happening in the nervous system.

In our research, we analyze, model, and simulate the physiological characteristics of auditory neurons in various vertebrate species, including cats, gerbils, and chickens and owls. Such computational approaches enable us to investigate the cellular mechanisms that underlie the precise auditory information processing and perception of sounds under idealized conditions.

Recent publications

  • Ashida, G., Wang, T.Z., Kretzberg, J. (2024) Integrate-and-fire-type models of the lateral superior olive. PLOS ONE 19(6)
  • Carr, C.E., Wang, T.F.Y., Kraemer, I., Capshaw, G., Ashida, G., Köppl, C., Kempter, R. Kuokkanen, P.T. (2024) Experience-Dependent Plasticity in Nucleus Laminaris of the Barn Owl. Journal of Neuroscience 44(1),
  • Heeringa, A.N., Teske, F., Ashida, G. Köppl, C. (2023) Cochlear aging disrupts the correlation between spontaneous rate and sound-level coding in auditory nerve fibers. Journal of Neurophysiology 130(3), pp. 736-750. DOI10.1152/jn.00090.2023
  • Kessler D., Carr C.E., Kretzberg J., Ashida G. (2021) Theoretical relationship between two measures of spike synchrony: Correlation index and vector strength. Front Neurosci Neurosci 15:761826. doi:10.3389/fnins.2021.761826
  • Ashida G, Tollin DJ, Kretzberg J (2021) Robustness of neuronal tuning to binaural sound localization cues against age-related loss of inhibitory synaptic inputs. PLoS Comput Biol 17: e1009130. doi:10.1371/journal.pcbi.1009130
  • Dietz M, Ashida G (2021) Computational Models of binaural processing. In: R. Litvsky, M Gouppell, R.R.Fay, A.N. Popper (eds), Binaural Hearing, Springer Handbook of Auditory Research Vol 73, Chapter 10, pp 281-315. Springer. doi:10.1007/978-3-030-57100-9_10
  • Klug, J., Schmors, L., Ashida, G., & Dietz, M. (2020). Neural Rate Difference Model Can Account for Lateralization of High-frequency Stimuli. The journal of the Acoustical Society of America, 148(2), pp. 678-691
  • Heeringa, A., Zhang, L., Ashida, G., Beutelmann, R., Steenken, F., & Köppl, C. (2020). Temporal Coding of Single Auditory Nerve Fibers Is Not Degraded in Aging Gerbils. The Journal of Neuroscience, 40(2), pp. 343-354. doi: 10.1523/JNEUROSCI.2784-18.2019
  • Aralla, R., Ashida, G., Koppl, C. (2020). Binaural responses in the auditory midbrain of chicken (Gallus gallus). European Journal of Neuroscience, 51(5), pp. 1290-1304. doi: 10.1111/ejn.13891
  • Ashida, G., Heinermann, H., & Kretzberg, J. (2019). Neuronal Population Model of Globular Bushy Cells Covering Unit-to-unit Variability. Public Library of Science, PLoS Computational Biology, 15 (12) article e1007563, pp. 1-38. doi: 10.1371/journal.pcbi.1007563
  • Köpcke, Hildebrandt, Kretzberg, Hildebrandt, K. Jannis, & Kretzberg, Jutta. (2019). Online Detection of Multiple Stimulus Changes Based on Single Neuron Interspike Intervals. Frontiers in Computational Neuroscience, 13, article 69, pp. 1-19. doi: 10.3389/fncom.2019.00069
  • Ashida, G., & Nogueira, W. (2018). Spike-Conducting Integrate-and-Fire Model. eNeuro5(4), ENEURO.0112-18.2018.
  • Nogueira W, Ashida G (2018) Development of a model of the electrically stimulated auditory nerve. In: Biomedical Technology, Lecture Notes in Applied and Computational Mechanics P. Wriggers and T. Lenartz (eds.). pp 349-362. Springer International
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