competition

1. Elements of robustness: feedback degeneracy competition modularity

2. Feedback

3. A classic example of feedback in neural circuits: error correction during smooth pursuit feedback retinal inputs Feedback Controller ~100 ms Sensed Variable Feedforward Controller eye movement Goal Eyeball +

4. Degeneracy

5. A classic example of degeneracy in biology: the genetic code

6. Neuron-level degeneracy: robustness of bursting in cerebellar Purkinje cells cell 1 cell 2 acutely dissociated Purkinje somata Swensen & Bean, J. Neurosci. 2005

7. Neuron-level degeneracy: robustness of bursting in cerebellar Purkinje cells cell 1 cell 2 cell 3 cell 4 cell 5 cell 6 Swensen & Bean, J. Neurosci. 2005

8. Neuron-level degeneracy: robustness of bursting in cerebellar Purkinje cells Swensen & Bean, J. Neurosci. 2005

9. Neuron-level degeneracy: robustness of bursting in cerebellar Purkinje cells An acute decrease in Na+ conductance produces a compensatory increase in voltage-dependent and Ca2+–dependent K+ conductances. Swensen & Bean, J. Neurosci. 2005

10. Neuron-level degeneracy: robustness of bursting in cerebellar Purkinje cells Swensen & Bean, J. Neurosci. 2005

11. Neuron-level degeneracy: robustness of bursting in cerebellar Purkinje cells A chronic decrease in Na+ conductance produces a compensatory increase in Ca2+ conductance. Swensen & Bean, J. Neurosci. 2005

12. Degeneracy and feedback system variables output input homeostat set point

13. Degeneracy and feedback set point homeostat system variables output input

14. Mapping the state space of neuron-level degeneracy: robustness of bursting in stomatogastric ganglion neurons model stomatogastric ganglion neuron Goldman, Golowasch, Marder, & Abbott, J. Neurosci. 2001

15. Mapping the state space of neuron-level degeneracy: robustness of bursting in stomatogastric ganglion neurons model stomatogastric ganglion neuron Goldman, Golowasch, Marder, & Abbott, J. Neurosci. 2001

16. Evolution - adaptation by natural selection Evolvability - the capacity to adapt by natural selection Degeneracy can increase evolvability by distributing system outcomes near phenotypic transition boundaries.

17. Circuit-level degeneracy: robustness of patterns in the stomastogastric ganglion data Prinz et al. Nature 2004

18. Circuit-level degeneracy: robustness of patterns in the stomastogastric ganglion model Prinz et al. Nature Neuroscience 2004

19. Competition

20. A classic example of competition in neural circuits: the developing neuromuscular junction Luo & O’Leary, Ann. Rev. Neurosci. 2005

21. Another classic example of competition in neural circuits: developing ocular dominance columns Luo & O’Leary, Ann. Rev. Neurosci. 2005

22. Competitive synaptic interactions: spike-timing dependent plasticity pre leads post pre lags post Song & Abbott, Nat. Neurosci. 1999 Abbott, Zoology 2003

23. Competitive synaptic interactions: spike-timing dependent plasticity presynaptic rate = 10 Hz presynaptic rate = 13 Hz Homeostatic control of total excitatory drive over a range of presynaptic firing rates. Song & Abbott, Nat. Neurosci. 1999 Abbott, Zoology 2003

24. Modularity

25. A classic example of modularity in biology: the domain structure of genes and proteins “Exon shuffling” was recognized early in molecular biology as a potential mechanism to generate diverse novel proteins based on existing functional building-blocks.

26. Modularity in neural circuits a putative example: “cerebellar-like” circuits Bell, Han, & Sawtell, Annu. Rev. Neurosci. 2008 Oertel & Young, Trends Neurosci. 2004 Roberts & Portfors, Biol. Cybern. 2008

27. Modularity in neural circuits “cerebellar-like” circuits in vertebrates mammalian cerebellum teleost cerebellum mammalian dorsal cochlear nucleus teleost medial octavolateral nucleus mormyrid electrosensory lobe gymnotid electrosensory lobe Bell, Han, & Sawtell, Annu. Rev. Neurosci. 2008 Oertel & Young, Trends Neurosci. 2004 Roberts & Portfors, Biol. Cybern. 2008

28. Modularity in neural circuits • common anatomical features of cerebellar-like circuits: • large principal cells (often GABAergic) having large spiny dendrites • principal cells receive excitatory input from a very large population of granule cells forming parallel axon bundles that target the spiny dendrites of principal cells • principal cells also receive excitatory ascending input from sensory regions targeting the perisomatic/proximal region of principal cells • common functional features of cerebellar-like circuits: • parallel fibers carry “higher-level” information (higher-level sensory signals, corollary discharges, proprioceptive info) • ascending inputs by contrast carry lower-level information (pertaining to the same sensory modality or sensorimotor task) • parallel fiber signals can in principle “predict” the lower-level signals • “prediction” is learned by pairing parallel fiber input with ascending sensory input • pairing produces a depression of parallel fiber inputs (anti-Hebbian plasticity) Bell, Han, & Sawtell, Annu. Rev. Neurosci. 2008 Oertel & Young, Trends Neurosci. 2004 Roberts & Portfors, Biol. Cybern. 2008

29. Modularity in neural circuits re-routing experiments show that auditory cortex can process visual inputs Modularity can permit an organism to process a new input without evolving an entirely novel circuit from scratch—in effect, building diverse objects using existing building-blocks. What “modules” (if any) might be the circuit-level equivalent of protein domains at the molecular level? Sharma, Angelucci, & Sur, Nature 2001 von Melchner, Pallas, & Sur, Nature 2001

30. shorten summary (to ~400 words) • add an assessment (probably >300 words) • identify major problems, if any • identify unusual strengths, if any • for each major point, state the implications clearly • for each major problem, indicate appropriate solutions