Developmental emergence of cortical representations

Our research reveals highly structured cortical networks prior to the onset of sensory experience (Smith et al., Nature Neuro 2018; Mulholland et al., Elife 2021). Their representational architecture is highly similar in several sensory and higher association cortices (Powell et al., PNAS 2024) and appears to be shaped through dynamic recurrent interactions of the type local excitation and lateral inhibition (LELI) (Mulholland et al., Nature Commun 2024). Experience-driven network reorganization then transforms these endogenous networks into reliable cortical representations (Trägenap et al., in revision). 

Collaborations: Gordon Smith (UMN), Ben Scholl (UC Denver), David Fitzpatrick (MPFI) 

Flexible representations underlying learning, forgetting and creativity

Different sounds activate overlapping networks in the auditory cortex, potentially reflecting their association. We observe ongoing dynamic changes of this stimulus co-mapping that are flexibly biased during learning (Aschauer et al., Cell Reports 2022), while the coarse auditory map is largely preserved (Chambers et al., Cerebral Cortex 2022), and argue that these changes could underly the spontaneous creation of novel associations.  

Collaborations: Simon Rumpel (University Mainz), Noam Ziv (Technion)

Cognitive control, cognitive maps and representational spaces

We predict general cognitive capabilities from few spontaneous network states in the human brain (Wehrheim et al., Neuroimage 2023), examine the flexible use of visual representations in freely behaving cuttlefish (Reiter et al., 2018 Nature), and shed light on the high-dimensional organisation of representational spaces in deep neural networks (Wehrheim et al., ECCV 2024).  

Collaborations: Christian Fiebach (GU), Gilles Laurent (MPI BR)

Analysis methods for structural and functional neural data

We develop methods for analyzing chronic imaging data of dendritic spines (Vogel et al., Scientific Reports 2023). We also pioneered methods for tracking large numbers of chromatophores in freely behaving cuttlefish (Reiter et al., Nature 2018). Recently, we developed methods for the automated characterization of latent spaces in deep neural networks (Wehrheim et al., ECCV 2024).

• Kaschube M (2023), The Emergence of Cortical Representations, van Vreeswijk Theoretical Neuroscience Seminar (online) [video]
• Mulholland H, Kaschube M, Smith GB (2022), Mechanisms underlying the self-organization of patterned activity in the developing visual cortex, Cosyne Conference, Montreal, Canada [video]
• Trägenap S,  Whitney DE, Fitzpatrick D, Kaschube M (2022), Experience drives the development of novel, reliable cortical sensory representations from endogenous networks, Bernstein Conference 2022, Berlin [link] [video]

• Mulholland, H.N., Kaschube, M. and Smith, G.B., 2024.
  Self-organization of modular activity in immature cortical networks. 
  Nature Communications, 15(1), p.4145.[Link]

• Powell, N.J., Hein, B., Kong, D., Elpelt, J., Mulholland, H.N., Kaschube, M. and Smith, G.B., 2024.
  Common modular architecture across diverse cortical areas in early development. 
  Proceedings of the National Academy of Sciences, 121(11), p.e2313743121. [Link]

• Vogel, F.W., Alipek, S., Eppler, J.B., Osuna-Vargas, P., Triesch, J., Bissen, D., Acker-Palmer, A., Rumpel, S. and Kaschube, M., 2023. 
  Utilizing 2D-region-based CNNs for automatic dendritic spine detection in 3D live cell imaging. 
  Scientific Reports, 13(1), p.20497. [Link]

• Wehrheim, M. H., Faskowitz, J., Sporns, O., Fiebach, C. J., Kaschube*, M., & Hilger*, K., 2023.
  Few temporally distributed brain connectivity states predict human cognitive abilities.
  NeuroImage, Vol. 277, p. 120246.   * jointly directed work

• Trägenap S., Whitney D.E., Fitzpatrick D., Kaschube M., 2022. 
  Experience drives the development of novel, reliable cortical sensory representations from endogenously structured networks. 
  bioRxiv. 2022:2022-11 [Link]
  

• Chambers A.R., Aschauer D.F., Eppler JB., Kaschube M., Rumpel S., 2022. 
  A stable sensory map emerges from a dynamic equilibrium of neurons with unstable tuning properties. 
  Cerebral Cortex [Link]

• Aschauer DF#, Eppler JB#, Ewig L, Chambers A, Pokorny C, Kaschube M*, Rumpel S* (2022) 
  Learning-induced biases in the ongoing dynamics of sensory representations predict stimulus generalization. 
  Cell Reports 38(6):110340  #equal contribution; *jointly directed work. [Link]
  

• Mulholland HN, Hein B, Kaschube M, Smith GB (2021)
  Tightly coupled inhibitory and excitatory functional networks in the developing primary visual cortex.
  Elife. 10:e72456. [Link]

• Aschauer DF^†, Eppler JB^†, Ewig L, Chambers A, Pokorny C, Kaschube M*, Rumpel S*. (August 16, 2019)
  A Basis Set of Elementary Operations Captures Recombination of Neocortical Cell Assemblies During Basal Conditions and Learning.
  CELL-D-19-02189. Available at SSRN.^†equally contributing author; *jointly directed work.

• Harris, KD, Groh JM, DiCarlo J, Fries P, Kaschube M, Laurent G, MacLean J, McCormick D, Pipa G, Reynolds J, Schwartz A, Sejnowski T, Singer W, Vinck M, 2019. Functional Properties of Circuits, Cellular Populations, and Areas.
  The Neocortex, ed. W. Singer, T. J. Sejnowski and P. Rakic, pp. 223-265. Strüngmann Forum Reports, vol. 27, J. Lupp, series editor. Cambridge, MA: MIT Press.
  

• Smith GB^†, Hein B^†, Whitney DE^†, Fitzpatrick D*, Kaschube M*. (2018)
  Distributed network interactions and their emergence in developing neocortex.
  Nat Neurosci.; 21(11) 1600-1608 doi: 10.1038/s41593-018-0247-5. ^†equally contributing author; *jointly directed work. [link] Press release
  Link (MPFI): Movies of spontaneous activity and distributed networks in the visual cortex.

• Reiter S, Hülsdunk P, Woo T, Lauterbach MA, Eberle JS, Akay LA, Longo A, Meier-Credo J, Kretschmer F, Langer JD, Kaschube M, Laurent G. (2018)
  Elucidating the control and development of skin patterning in cuttlefish.
  Nature; 562, 361-366. doi:10.1038/s41586-018-0591-3 [link] Press release

• Kaschube M, Nelson III CA, Benasich AA, Buzsáki G, Gressens P, Hensch TK, Hübener M, Kobor MS, Singer W, Sur M. (2018)
  Early Childhood.
  Emergent Brain Dynamics: Prebirth to Adolescence, edited by A. A. Benasich and U. Ribary. Strüngmann Forum Reports, vol. 25, J. Lupp, series editor.
  Cambridge, MA: MIT Press

• Smith GB, Sederberg A, Elyada YM, Van Hooser SD, Kaschube M*, Fitzpatrick D. (2015). 
  The development of cortical circuits for motion discrimination. 
  Nat Neurosci.; 18(2), 252-261. doi: 10.1038/nn.3921. *jointly directed work. [link]

• Sederberg A, Kaschube M. (2015) 
  Inhibition facilitates direction selectivity in a noisy cortical environment.
  J Comput Neurosci. doi: 10.1007/s10827-014-0538-0. [link]

• Polyakov O, He B, Swan M, Shaevitz JW, Kaschube M, Wieschaus E. (2014) 
  Passive mechanical forces control cell-shape change during Drosophila ventral furrow formation.
  Biophys J.;107(4):998-1010. doi: 10.1016/j.bpj.2014.07.013. [link]

• Khan Z, Wang YC, Wieschaus EF, Kaschube M. (2014) 
  Quantitative 4D analyses of epithelial folding during Drosophila gastrulation. Development.
  141(14):2895-900. doi: 10.1242/dev.107730. [link]

• Kaschube M (2014)
  Neural maps versus salt-and-pepper organization in visual cortex.
  Curr Opin Neurobiol 24:95–102. [link]

• Reichl L, Heide D, Löwel S, Crowley JC, Kaschube M, Wolf F (2012)
  Coordinated Optimization of Visual Cortical Maps (II) Numerical Studies.
  PLoS Comput. Biol. 8(11):e1002756. [link]

• Reichl L, Heide D, Löwel S, Crowley JC, Kaschube M, Wolf F (2012)
  Coordinated Optimization of Visual Cortical Maps (I) Symmetry-based Analysis.
  PLoS Comput. Biol. 8(11):e1002466. [link]

• Gelbart MA, He B, Martin AC, Thiberge SY, Wieschaus EF, Kaschube M. (2012)
  Volume conservation principle involved in cell lengthening and nucleus movement during tissue morphogenesis.
  PNAS 109:19298–303. [link]

• Keil W, Kaschube M, Schnabel M, Kisvarday ZF, Löwel S, Coppola DM, White LE, Wolf F (2012)
  Response to Comment on “Universality in the Evolution of Orientation Columns in the Visual Cortex“.
  Science 336:413. [link]

• Nelson KS, Khan Z, Molnár I, Mihály J, Kaschube M, Beitel GJ (2012)
  Drosophila Src regulates anisotropic apical surface growth to control epithelial tube size.
  Nat Cell Biol 14(5):518–25. [link]

• Wang YC, Khan Z, Kaschube M, Wieschaus EF (2012)
  Differential positioning of adherens junctions is associated with initiation of epithelial folding.
  Nature, 484:390–393. [link]

• Macke JH, Gerwinn S, White LE, Kaschube M, Bethge M (2011)
  Gaussian process methods for estimating cortical maps. 
• NeuroImage 56(2):570–81. [link]

• Kaschube M, Schnabel M, Löwel S, Coppola DM, White LE, Wolf F (2010)
  Universality in the evolution of orientation columns in the visual cortex.
  Science 330:1113–1116. [link]

• Keil W, Schmidt K-F, Löwel S, Kaschube M (2010)
  Reorganization of columnar architecture in the growing visual cortex. 
  PNAS 107:12293–12298. [link]

• Martin AC, Gelbart M, Fernandez-Gonzalez R, Kaschube M, Wieschaus EF (2010)
  Integration of contractile forces during tissue invagination.
  JCB 188:735–749. [link]

• Doubrovinski K, Polyakov O, Kaschube M (2010)
  A mesoscopic description of contractile cytoskeletal meshworks.
  EPJE 33:105–110. [link]

• Martin AC, Kaschube M, Wieschaus EF (2009)
  Pulsed contractions of an actin–myosin network drive apical constriction.
  Nature 457:495–499. [link]

• Kaschube M, Schnabel M, Wolf F, Löwel S (2009)
  Interareal coordination of columnar architectures during visual cortical development.
  PNAS 106:17205–17210. [link]

• Macke JH, Gerwin S, White LE, Kaschube M, Bethge M (2009)
  Bayesian estimation of orientation preference maps.
  NIPS 22. [link]

• Kaschube M, Schnabel M, Wolf F (2008)
  Self-organization and the selection of pinwheel density in visual cortical development.
  NJP 10:015009. [link]

• Schnabel M, Kaschube M, Wolf F (2008)
  Pinwheel stability, pattern selection and the geometry of visual space.
  [link]

• Schnabel M, Kaschube M, Loewel S and Wolf F (2007)
  Random Waves in the Brain: Symmetries and Defect Generation in the Visual Cortex.
  EPJ ST 145:137–157. [link]

• Kaschube M, Wolf F, Puhlmann M, Rathjen S, Schmidt KF, Geisel T and Loewel S (2003)
  The pattern of ocular dominance columns in cat primary visual cortex: Intra- and interindividual variability of column spacing and its dependence on genetic background.
  EJN 18:3251–3266. [link]

• Kaschube M, Wolf F, Geisel T, Löwel S (2002)
  Genetic influence on quantitative features of neocortical architecture.
  J Neurosc. 22:7206–7217. [link]

• Kaschube M, Wolf F, Geisel T, Löwel S (2001) T
  he prevalence of colinear contours in the real world.
  Neurocomputing 38–40:1335–1339. [link]

• Kaschube M, Wolf F, Geisel T, Löwel S (2000)
  Quantifying the variability of patterns of orientation domains in the visual cortex of cats.
  Neurocomputing 32–33:415–423. [link]

• Spine detection in 3D live cell imaging [Vogel et al, Scientific Reports, 2023] [Link]

• Network model of early visual cortex [Smith, Hein, Whitney et al., Nat Neurosci, 2018][link].

• Tools for analysing Calcium imaging data [Smith, Hein, Whitney et al., Nat Neurosci, 2018][link].