1. Basic Mechanisms of Seizure Generation John G.R. Jefferys Marom BiksonPremysl Jiruska John FoxMartin Vreugdenhil Jackie DeansWei-Chih Chang Joseph CsicsvariXiaoli Li Petr MarusicMartin Tomasek MRC (UK)Wellcome Trust Epilepsy Research UK

2. Focal Epilepsy scalp EEG depth EEG field intra- cellular interictal seizure epileptic patient brain slice “paroxysmal depolarization shift” + +  + + 

3. Interictal EEG “spikes”  Last hundreds of ms to a few s,  primarily due to recurrent synaptic excitation between pyramidal neurons  Associated with intracellular paroxysmal depolarizing shift

4. CA3 CA1 Brain Slices and Basic Mechanisms Dentate gyrus Entorhinal cortex

5. Interictal EEG spikes 40 ms 25 mV CA3 pyramidal neuron simulation real cell Network simulation Hippocampal CA3 mutual excitation of pyramidal cells strong synapses (~1mV) intrinsic bursts ~1000 pyramidal cells needed for interictal spikes Traub & Wong 1982, Science

6. Interictal EEG spikes Traub & Wong 1982, Science 50 | 60 ms 4 mV 25 | 20 mV 50 ms

7. What makes chronic epileptic foci epileptic? neuronal loss

8. intrinsic properties ↑ Ca, ↑ Na p, ↓ K channels (channelopathies) neuronal loss M Vreugdenhil W Wadman What makes chronic epileptic foci epileptic?

9. intrinsic properties ↑ Ca, ↑ Na p, ↓ K channels (channelopathies) neuronal loss What makes chronic epileptic foci epileptic?

10. intrinsic properties ↑ Ca, ↑ Na p, ↓ K channels (channelopathies) synaptic efficacy ↑ EPSPs; ↓ IPSPs; presynaptic modulation; dormancy. neuronal loss What makes chronic epileptic foci epileptic?

11. Plus: glia; gap junctions; ion transporters; transmitter transporters… intrinsic properties ↑ Ca, ↑ Na p, ↓ K channels (channelopathies) “Sprouting” synaptic connectivity synaptic efficacy ↑ EPSPs; ↓ IPSPs; presynaptic modulation; dormancy. neuronal loss What makes chronic epileptic foci epileptic?

12. Seizure mechanisms  Interictal discharges normally stopped by IPSPs / AHPs / synaptic vesicle depletion / presynaptic modulation…  Slow excitatory processes, such as increased extracellular potassium ion concentrations which also cause negative DC shifts found in animal models and in appropriate clinical recordings. What prolongs the hypersynchronous discharge beyond the 1 st second?

13. Extracellular Ions and Seizures K+K+ Potassium concentration in extracellular space increases during seizures and depolarizes and excites neurons, promoting and prolonging the seizure Barbarosie & Avoli 2002 Epilepsia K+K+

14. DC Shifts in Human Epilepsy Vanhatalo et al 2003 Neurology

15. Low Ca epileptic bursts Bikson et al 2003 J Neurophys

16. Seizure mechanisms  Interictal discharges normally stopped by IPSPs / AHPs / synaptic vesicle depletion / presynaptic modulation…  Slow excitatory processes, such as increased extracellular potassium ion concentrations which also cause negative DC shifts found in animal models and in appropriate clinical recordings.  Seizure morphology – synaptic and non-synaptic mechanisms for tonic and phasic components  Dynamic interactions between separate cortical structures: re-entrant loops versus couple oscillators.

17. Focal seizures in vivo 4s before motor seizure Stage IV: bilaterally synchronous 16Hz (15-30Hz) Stage III: 12-20Hz irregular Gerald Finnerty  Premek Jiruska Delays between regions ≈ synaptic

18. Seizure mechanisms Dynamic interactions between cortical structures  re-entrant loops versus coupled oscillators. Seizures spread further as well as last longer than interictal events

19. Seizures due to Reverberatory Loops?

20. Reverberatory Loops? No. Lack of phase lags suggests re-entrant loops not essential Maybe have coupled oscillators? Bragin et al, 1997 DG-CA3CA3-CA1

21. R CA1 R CA3 L CA3 L CA1 Reverberation / Distributed Focus R CA3 L CA3 1s Finnerty & Jefferys 2002

22. Longer Range Connections In Seizure Generator From Bertram L R

23. HFA during interictal EEG “spikes”  High frequency interictal activity characteristic of epileptic foci

24. Interictal HFA Staba et al 2004, Ann Neurol

25. Synchronizing mechanisms Neuron-glia interactions Chemical synapse Electrotonic interactions Field effects 0.1 1 10100 1 10 [ms] [s] Extracellular potassium

26. HFA: ripples and IPSPs Ylinen et al 1995 J Neurosci Interneuron firingReversal ≈ IPSP Pyramidal cell

27. HFA: ripples and field effects Bikson et al 2002 J Neurophys; 2004 J Physiol  V TM (mV) + 

28. High Frequency Activity  Low-amplitude high frequency activity preceding seizures

29. Fast Oscillations Preceding Seizures in Man 0 150 [Hz] Wavelet spectrogram 10 s 0.2 mV 50 µV raw data 10 s 0.2 mV raw data ripples (80-250 Hz) 10 s Allen et al. (1992) Fisher et al. (1992) Traub et al. (2001) Worrel et al. (2004) Ochi et al. (2007) Petr Marusic, Martin Tomasek

30. High frequency activity before seizures Clusters 9 8 7 6 5 4 3 2 1 2 mV 5 s 0.4 mV 5 s Wavelet spectrogram 500 0 [Hz] Jefferys & Jiruska in press Raw data (10-250 Hz) Global synchronization index

31. High frequency activity before seizures 0 7 -7 0.02 50 µV 0 prob. Averaged oscillation [ms] Interneurons (n=22) pyramidal cells (n=46) Tetrode recording Multiple cell activity during HFA Cellular firing probability Premek Jiruska

32. High frequency activity before seizures Neuron-glia interactions Chemical synapse Electrotonic interactions Field effects 0.1 1 10100 1 10 [ms] [s] Extracellular potassium +  + 

33. Basic Mechanisms of Seizure Generation Synaptic and nonsynaptic mechanisms involved Interictal spikes ~few 100ms: recurrent excitation terminated by inhibitory processes Seizures continue much longer and spread further Coupled generators Sustained excitation (Slow synapses (mGluR)) Extracellular chemical changes (K + ) High frequency activity: marker for epileptic tissue and transition to seizure ripples, fast ripples Fast synaptic inhibition Field effects

34. Epilepsy Surgery Center, Charles University, Czech Republic Premysl Jiruska John Fox John Jefferys Martin Vreugdenhil Department of Neurophysiology, University of Birmingham, UK MRC Anatomical Neuropharmacology Unit, University of Oxford, UK Jozsef Csicsvari Petr Marusic Martin Tomasek School of Computer Science, University of Birmingham, UK Xiaoli Li Wei-Chih Chang