1. Dieter Jaeger Department of Biology Emory University djaeger@emory.edu

4. KSJ 4th ed., Fig. 10-7

5. Kandel, 4 th edition

7. 100  m GP neuron surface area:17,700  m 2 number of synapses (ex/in):1,200 / 6,800 number of inputs / s12,000 / 6,800 Ca3 pyramidal neuron surface area:38,800  m 2 number of synapses (ex/in):17,000 / 2,000 number of inputs / s170,000 / 20,000 In vivo input levels

8. In vivo recording from striatal medium spiny neuron

10. 5,000 AMPA and 500 GABA A Synapses at 10 Hz E in = -70 mV E ex = 0 mV I syn = G in * (V m - E in ) + G ex * (V m - E ex ) E syn = (G in * E in )+ (G ex * E ex ) / (G in + G ex ) I syn = (G in + G ex ) * (V m - E syn ) I syn = (300 nS) * (60-50mV) = 3 nA

11. AxoClamp 2B Isyn = Iex + Iin = Gex*(Vm-Eex) + Gin*(Vm-Ein) Vm Isyn Vm dynamic current clamp patch pipette To apply in vivo like input DCN neuron slice, 32 C

12. Dynamic current clamping of GP neuron

13. current versus conductance source 100 msec - 40 mV 0.2 nA 5 mV 0 nA outward inward Vm Esyn Isyn Iexp

14. spike triggering events 1.0 input synchronization: 10 groups 100 groups 50 ms Input frequency Input conductance 50 ms 0.1 nA 0 nA outward inward Isyn Iexp Input current

15. Small conductance K [Ca] current (Sk)

16. The effect of Sk block on synaptic integration

17. Space! The next frontier

20. Shunting by somatic conductance

21. Shunting by distributed conductance

23. Functional Implications synaptic conductance stabilizes Vm through shunting spikes can only be triggered from transients spikes reflect inputs correlated on the order of 1-10 ms spike rate reflects correlation as well as input rate inhibition has equal access to the control of spiking

24. More complexity to come gap junctions short term plasticity (history dependence) calcium signaling dendritic spike initiation

25. Acknowledgements Contributors: Volker Gauck Svetlana Gurvich Lisa Kreiner Mayuri Maddi Kelly Suter Other Lab Members: Alfonso Delgado-Reyes Jesse Hanson Chris Roland Simon Peron

28. Current models of basal ganglia function determine spike rates based on simple summing of synaptic inputs Normal Parkinson’s Disease (Obeso et. al., Trends Neurosci 23(10):S8-S19, 2000)

29. DCN from Paxinos & Watson, "The rat brain', Academic Press Cerebellar cortex deep cerebellar nuclei cerebellar cortex mossy fibers climbing fibers !? cerebellar circuit

30. -50 mV 20 mV 200 msec The effect of synchronization 200 msec 100 independent inputs10 independent inputs

31. spike timing precision gain factor spike frequency synchronizationhigh intermediate none 0.5124816 2.5 2.0 1.5 1.0 0.5 124816 0 20 40 60[%] precision & rate [rel.] gain factor

32. 200 msec 20 mV spiking in vitro and in vivo in vivo, awake (from LeDoux et al. 1998, Neuroscience, 86(2):533) in vitro 500 msec10 msectime scale for coding: rate codetemporal code

33. 30,100 UC’s/s inhibitory unitary conductance Constructing in-vivo like synaptic input 100 ms 0.5 10 mV 0 Gex Gin: 1 nS at gain 1 Esyn - 40 mV gmax: 2.1 pS - 69 pS gain 0.5 - gain 16

35. Shink and Smith, J. Comp. Neurol. 358: 119-141 (1995)

36. ~100  m 100  m Purkinje cell surface area:261,000  m 2 number of synapses (ex/in):175,000 / 5,000 number of inputs / s350,000 / 10,000 DCN neuron surface area:11,056  m 2 number of synapses (ex/in):5,000 / 15,000 number of inputs / s25,000 / 750,000

37. 100  m Cerebellar Stellate cell surface area:2,305  m 2 number of synapses (ex/in):1,000 / 100 number of inputs / s2,000 / 200

40. -70 mV = E leak