1. Feedforward networks

3. Complex Network

4. Simpler (but still complicated) Network

5. 1a 1b 1c 1d 1e 2a 2b 2c 2d 2e 3a 3b 3c 3d 3e 1a 1e 1d 1c 1b 2a 2e 2d 2c 2b 3a 3e 3d 3c 3b 1a 1b 1c 1d 1e 2a 2b 2c 2d 2e 3a 3b 3c 3d 3e Feedforward Network 1a 1b 1c 1d 1e 2a 2b 2c 2d 2e 3a 3b 3c 3d 3e

6. Hz ms Signal propagation through the network on off Hz ms “rate mode” Shadlen & Newsome, 1998 Van Rossum et al., 2002 “synchrony mode” Abeles, corticonics, 1991 Diesmann et al.,1999

7. Is synchrony robust ? Why does synchrony develop ? Is it useful for transmitting signals ? Is it found in vivo? Questions

8. Simulations with real neurons Real neurons (God, unpublished results) 1000’s

9. Whole-cell recordings  Rats or mice are 18 days or older  300-500 µm slices of somatosensory or auditory cortex  maintained at 32-34 degrees  recordings were from L5 pyramidal neurons and interneurons

10. Implementation of feedforward in vitro networks 1 2 3 m 1 2 n

11. individual spikes histogram 0200400600800100012001400 ms cells 0200400600800100012001400 ms

12. Network type: -> sparsely connected (10%)

13. L2 L3 L5 L4 L6 L7 L8 Quantification of Synchrony ms L1 0100200300-100-200-300

14. Is synchrony robust ?

15. 1. sparsely connected networks 2. Poisson input 3. heterogeneous networks 4. excitatory & inhibitory networks 5. extremely noisy 6. sinusoidally-modulated inputs 7. NMDA-like EPSPs 8. different initial conditions 9. facilitating/depressing synapses Various network configurations Synchrony persists

16. Periodic Poisson Network type: -> sparsely connected (10%) -> Poisson input

17. cellRnf/I slope A 49164 B 54227 C 28134 D121303 200 ms 50 mV Network type: -> sparsely connected (10%) -> Poisson input -> heterogeneous Heterogeneous Networks

18. Time (ms) Layer 2 Layer 6

19. Excitatory & Inhibitory network membrane voltage I exc I inh net synaptic current = I exc + I inh

20. I syn ( t ) = g syn ( t )*(V( t )-E syn ) I epsp = g * (V - E) dynamic clamp I c-clamp ( t ) I ipsp = g(t)*(V + 80 )-62 mV 0.5 mV 50 ms -62 mV I epsp =g(t)*(V - 0)

21. threshold (V = I/g) -58 mV EPSP rate: 28,000 Hz IPSP rate: 12,000 Hz 200 ms 2 mV -58 mV EPSP rate: 7000 Hz IPSP rate: 3000 Hz Chance, Abbott, Reyes 2002 Effects of conductance noise on membrane potential

22. excitatory cells 20 mV 200 ms excitatory + inhibitory

23. layer 5 Network type: -> sparsely connected (10%) -> Poisson input -> heterogeneous -> excitatory + inhibitory EPSP EPSP + IPSP 1 23 4 5 6

24. Network type: -> sparsely connected (10%) -> Poisson input -> heterogeneous -> epsp + ipsp -> ‘unphysiologically’ noisy layer CCH area 1234566 layer 2 layer 6

25. Why does synchrony develop ?

26. A simple model

27. counts ms 0 10 20 30 40 50 histograms unitary synaptic current * Composite current 1 2 3 4 experiment 0.0 0.4 0.8 1.0 seconds A simple model

28. LIF: FPE: where input: 605040302001070 ms 0 autocorr: Fokker-Planck Equations

29. Diesmann et al., Nature 1999

30. Is it useful for transmitting signals ?

31. Signal propagation through the network on off F1F1 F1F1 F2F2 F2F2

32. 1 nA layer 6 25 mV 200 ms layer 2 F in = 25 Hz 55 Hz 25 Hz F in

33. 25 20 15 10 5 0 1197531 Layer Avg. rate (Hz) k 20 15 10 5 0 Firing Rate (Hz) 16008000 Input rate (=N*F pre ) 1 2 3 N Firing rate = F pre F layer = k*N*F layer-1 Input rate = N*F pre Frequency

34. 20 10 30 0 6 54321 layer avg. firing rate (Hz) K*N < 1 K*N = 1 K*N > 1 F L = k*N*F L-1

35. F2 F1 F3 F4 F2F1F3 F4 Synchrony is necessary for signal propagation

36. Is it found in vivo ?

37. layer 6 (synchronous) 1 nA 25 mV 200 ms layer 2 (asynchronous) What to look for in vivo

38. 10 mV 50 ms In vivo intracellular recordings Azouz & Gray, 1999 Lampl et al.,1999 0.5 mV 25 ms Reyes & Sakmann, 1999 Brecht & Sakmann, 2002 10 mV 25 ms wD4 Ikegaya et al., 2004

39. Is synchrony robust ? yes, for a wide range of physiological conditions Why does synchrony develop ? Neurons become correlated at stimulus onset Is it useful for transmitting signals ? Yes. In fact, it’s necessary! In vivo evidence? Yes. Quite strong. Summary

40. 1a 1b 1c 1d 1e 2a 2b 2c 2d 2e 3a 3b 3c 3d 3e Feedforward Network 1a 1b 1c 1d 1e 2a 2b 2c 2d 2e 3a 3b 3c 3d 3e 1a 1b 1c 1d 1e 2a 2b 2c 2d 2e 3a 3b 3c 3d 3e

42. 04080 Hz 0250 Hz 04080 Hz With inhib pyramidalsinterneuron