1. Optimization and testing of a reduced model of pyramidal neurons Arnd Roth Wolfson Institute for Biomedical Research University College London

2. How do neurons transform synaptic inputs into action potential output?

3. What are the functional compartments in neurons?

4. Backpropagation of action potentials Stuart & Sakmann, 1994

5. Dendritic spikes in vivo Helmchen, Svoboda, Denk & Tank, 1999

6. Local dendritic spikes in vivo Smith, Smith, Branco & Häusser, 2013

7. BAC firing in layer 5 pyramidal cells Larkum, Zhu & Sakmann, 1999

8. Critical frequency for calcium electrogenesis Larkum, Kaiser & Sakmann, 1999

9. Constraining passive parameters in compartmental models Roth & Häusser (2001)

10. „Raw“ and „core“ model parameters

11. Turning bad space clamp into a virtue Schaefer, Helmstaedter, Sakmann & Korngreen, 2003

12. Dendrotomy and „pinching“ Bekkers & Häusser, 2007

13. Dendrotomy and „pinching“ change somatic AP waveforms

14. Detailed and reduced models Traub et al., 1991Pinsky & Rinzel, 1994

15. Case study: a reduced compartmental model of a layer 5 pyramidal neuron Bahl, Stemmler, Herz & Roth, 2012

16. Verification of passive properties

17. Pinching in a layer 5 pyramidal neuron

18. Model generalization

19. f/I curves before and after pinching

20. BAC firing

21. Attwell & Gibb Nature Reviews Neuroscience (2005); Fig. 2 mod. Redistribution of ions: Na + -K + -ATPase Percentage of energy expended on neuronal signalling in rat neocortex Hodgkin & Huxley J. Physiol. (London) (1952d); Figs. 17 and 18 Energy efficiency of action potentials in the Hodgkin-Huxley model Hodgkin´s notion (1975): „In the squid axon... the entry of sodium and loss of potassium per impulse are 3 to 4 times the theoretical minimum of C m   U AP.“ (Charging a pure capacitor)

22. Charge separation Transmembrane ion fluxes during a mossy fiber bouton action potential at 37 °C

23. Transmembrane ion fluxes during a mossy fiber bouton action potential at 37 °C Alle, Roth & Geiger, 2009

24. Challenges Nonlinearity and large number of free parameters present a difficult optimization problem Which data and which distance functions can constrain which type of model? Tradeoff between flexibility and identifiability Access to high-quality, internally consistent, annotated data sets

25. What we need Test suites to objectively compare different (classes of) models (-> Open Source Brain) Standardized, portable model description (-> NeuroML) Simulator-independent model construction (e.g. neuroConstruct) and optimization (e.g. MOO) Integration of data from electrophysiological and optical recordings with morphological and molecular biology data Objective methods for dimensionality reduction