Summary of the findings

The studies presented in this work have all used EEG-fMRI to study epileptic networks in human and the clinical relevance of the methodological developments was always evaluated with the best available evidence.

In the first two studies, we saw that the conventional analysis of EEG-fMRI yielded localising results that were predictive of intracranial EEG findings and post-operative outcome. However, the majority of the patients included in these two studies showed non-conclusive results because of a lack of epileptic activity recorded during fMRI.

We then showed that EEG source imaging could be reliably performed simultaneously to fMRI analysis, and allowed to discriminate between regions of onset vs propagation of focal epileptic activity. Interestingly, the statistically maximal cluster of BOLD changes was concordant with spike onset in only a third of cases and BOLD negative changes were concordant with spike onset in another third of the cases.

We then proposed two EEG-based methods for extracting more information from the intra-MR EEG and refine the modelling of epileptic activity. These developments could be applied to a wide field in neuroscience research and, in the present studies, greatly improved the sensitivity of the EEG-fMRI for mapping epileptic networks. The discordant cases showed the importance of a rigorous correction of motion- and pulse-artefacts and of the importance of the description of baseline brain activity.

Finally, pioneering studies in simultaneous intracranial EEG-fMRI in human showed that this technique is safe provided a strict acquisition protocol is followed. Despite interference between both EEG and fMRI equipments, the quality of fMRI and EEG was of sufficient quality to interpret the EEG and detect EEG-related BOLD changes at immediate proximity of the electrode. This technique allows the mapping of whole brain network related to the precise temporal and spatial sampling of intracranial EEG.

136 11.2

Neurophysiological relevance

Some of the findings in this series of studies have particular neurophysiological relevance for the understanding of brain function.

Negative BOLD changes that are concordant with spike onset defined with ESI, with confirmation from intracranial recordings in some cases, are consistent with several previous studies (Kobayashi et al. 2006a; Salek-Haddadi et al. 2006; Jacobs et al.

2007). Concordantly, the intracranial EEG-fMRI study also found negative BOLD changes at the vicinity of intracranial electrodes which recorded interictal epileptic activity. An impaired neurovascular coupling could cause negative BOLD changes despite an increased metabolic demand created by increased neuronal activity (spikes).

However, several studies suggest that the neuro-vascular coupling is preserved during interictal epileptic activity, although this evidence has been gathered in generalised epilepsy and should be confirmed in focal epilepsy (Stefanovic et al. 2005; Carmichael et al. 2008a). Moreover, the present finding of BOLD changes at the immediate proximity of very focal epileptic activity recorded with invasive electrodes also supports a preserved neurovascular coupling. Alternatively, spikes could be the result of a local decrease of post-synapitc activity if a high level of inhibition is present at baseline with some reduction time-locked to the occurrence of spikes. This scenario of a metabolically demanding inhibitory baseline could result in a reduction of this metabolic demand at the time of spikes and therefore to local negative BOLD changes.

Our efforts to extract neurophysiologically relevant information from the EEG to guide fMRI analysis were successful when using the fluctuations of the epileptic source estimated by ESI and even more so when using the presence of the epileptic map. The finding that pathological EEG maps can have haemodynamic correlates concordant with focal epileptic activity constitutes a major finding of this work. Together with a recent study showing that physiological EEG maps (microstates) have BOLD correlates corresponding to some fMRI Resting State Networks (Britz et al. 2010), this finding represents an additional validation for the spatio-temporal analysis of scalp EEG and suggests that significant information about the activity of the epileptic focus is present in the interictal EEG beyond the presence of spikes. This approach opens new avenues for a refined investigation of the interictal activity, its localisation and aspects of the neuro-vascular coupling.

137 11.3

Clinical relevance

The studies presented here have used invasive EEG or the outcome of epilepsy surgery as validation of their results. They showed that EEG-fMRI findings are clinically relevant for the localisation of epileptic activity and the prediction of post-operative seizure control. In the first two studies, no BOLD changes could be obtained in a majority of patients, but improvement of EEG-informed fMRI analysis as presented in the last of these three studies, showed a much improved yield of EEG-fMRI with clinically meaningful results in around 80% of studies. Therefore, EEG-fMRI could be a very useful tool in difficult presurgical cases to localise regions of epileptic networks to be targeted by intracranial electrodes and to inform about the prognosis of surgery. Larger studies using the more EEG-fMRI analysis methods shown in this work and post-operatively seizure-free and non-seizure free patients are needed to confirm the promising results found in chapters 3 and 4 obtained only in small groups of patients due to the large proportion of negative results.

Neuro-navigation equipement are increasingly used in operating rooms to provide the position of the operated site with respect to brain structures revealed by preoperative imaging. The integration of functional imaging to the structural imaging used so far would further promote the use of EEG-fMRI for targeting electrode placement and surgical resection but further research is needed to correct distortion inherently affecting fMRI images.

Deep brain stimulation with chronic electric stimulation applied with intracranial electrodes is used to treat patients with pharmaco-resistant epilepsy. Stimulation at the main epileptic focus (e.g. amygdalo-hippocampal stimulation in temporal lobe epilepsy) or at a remote modulating node of the epileptic network (e.g. anterior nucleus of the thalamus) have shown promising results as palliative treatments (Vonck et al. 2005;

Fisher et al. 2010). Transcranial Magnetic Stimulation has also been used in an effort to modulate epileptic activity (Fregni et al. 2006). Deep Brain Stimulation strategy can also be applied to difficult to treat patients suffering from generalised epilepsy (Velasco et al.

1995). The emergence of these techniques would greatly benefit from a better mapping of epileptic networks gained by EEG-fMRI, that has also shown its ability to identify specific thalamic nuclei involved in generalised spike-and-wave discharges observed in generalised epilepsies (Tyvaert et al. 2009).

138 11.4

Future research directions

11.4.1

EEG-informed fMRI analysis of brain networks

The reliability of spatio-temporal EEG analysis can be much improved if high density recordings are available, and skull coverage including low temporal electrodes (cheeks, neck) is particulary needed. New MR-compatible high density (256-channel) EEG systems are entering the field and their use will certainly help to build more reliable EEG-based regressors for fMRI analysis. We are currently implementing their use in our laboratory. More specifically, high density EEG might help discriminate between physiological and disease-related ongoing brain activity and therefore improve the yield of topography-related fMRI analysis in temporal lobe epilepsy. A better modelling of baseline brain activity and BOLD fluctuations could be done by including the physiological maps in the analysis together with the epileptic map. Alternatively to spatio-temporal EEG features, the fluctuation of the EEG baseline can be characterised by the ongoing activity of the typical EEG frequency bands (delta: 0 – 3.5 Hz; theta: 4 – 7 Hz; alpha: 8 -12 Hz; beta: 13 – 30 Hz; gamma: 30 – 100 Hz). The power variation of these frequency bands across time can have haemodynamic correlates (Van Paesschen et al. 1997; Tyvaert et al. 2008) and could therefore be introduced in the explanatory model. Sleep can influence epileptic activity which is typically enhanced during slow wave sleep and reduced in REM sleep. Despite the noisy environment, a good proportion of patients tend to fall asleep during resting state fMRI recording and taking sleep stages into account seems to be beneficial for the statistical analysis (Moehring et al. 2008).

These future studies might help, not only to better localise epileptic activity in the brain, but also to clarify the involvement of brain regions that show spike-related BOLD changes remote from the epileptic focus. Some of these remote regions are supposed to represent spike-related modulations of resting state networks, notably in the Default Mode Network (Gotman et al. 2005; Hamandi et al. 2006; Kobayashi et al. 2006a; Laufs et al. 2007). However, some patients show BOLD changes in other ipsilateral and contralateral remote brain regions that are difficult to link with the epileptic focus. These remote “discordant” BOLD changes are generally described as belonging to wider

“epileptic network” but their involvement is unclear. A better modelling of ongoing fluctuations in brain activity might reveal which of these regions are really involved in the epileptic network.

139 Behavioral and imaging studies have shown that interictal epileptic activity without obvious clinical manifestation might be less silent than previously considered and cause transient cognitive impairment (Nicolai&Kasteleijn-Nolst Trenite 2011). This effect could help understanding cognitive difficulties presented by patients with epilepsy. In functional imaging of cognitive functions in epileptic patients, simultaneous EEG-fMRI recordings could be used to directly investigate the effect of interictal epileptic activity on cognitive performances. Moreover, the methodological developments for the analysis of EEG-fMRI datasets in patients with epilepsy could find interesting applications in cognitive neuroscience. The use of simultaneous EEG features, such as the amplitude of the evoked response in single events can be used to inform fMRI analysis. Of course, like for applications in epilepsy, such parametric models for fMRI analysis require very good quality of the acquired and corrected data.

11.4.2

Neurovascular coupling

As described along this work, EEG-fMRI and particulary intracranial EEG-fMRI can be used to help our understanding of the coupling between neuronal activity and haemodynamic changes in the brain in physiological and pathological conditions. This would be crucial for the scientific community involved in fMRI studies as this brain mapping technique relies on strong assumption regarding this coupling. These assumptions have been derived from invasive animal work in primates (Logothetis et al.

2001) and from task-related haemodynamic changes to infer the haemodynamic response function (Glover 1999), but they have been extended to the growing research field of brain resting states and spatial brain networks associated with endogenous neuronal oscillations (Mantini et al. 2007). The use of flexible haemodynamic functions (e.g. using derivatives or multiple time-lagged functions) is widely used to account for the variability of the coupling in different brain regions and different subject but also to account for deviant neuro-vascular coupling in pathological brain structures.

In patients with epilepsy, negative BOLD changes concordant with the localisation of focal epileptic activity remain poorly understood. Also, “early” spike-releated BOLD changes (correlated to epileptic activity but with earlier onset) have been reported and suggest either undetected pre-spike EEG changes or an altered neurovascular coupling (Hawco et al. 2007; Jacobs et al. 2009; Rathakrishnan et al. 2010). Emphasis should be

140 put on the analysis of EEG to identify pre-spike changes driving these early BOLD changes. Near Infra-Red Spectroscopy (NIRS) is a technique that measures haemodynamic changes in the cortex with a much higher temporal resolution than fMRI (milliseconds vs seconds) but which is limited to the cortical surface because the light used is quickly absorbed when entering brain tissue. NIRS can be applied more easily in invasive animal studies and has revealed complex oscillatory fluctuations of haemodynamic signals prior to epileptic spikes (Osharina et al. 2010). Some new EEG equipments offer simultaneous NIRS acquisition and these systems that could offer complementary information to EEG-fMRI studies.

Definite answers to these points will probably require invasive electrophysiology in humans that is generally only available in patients with epilepsy. Simultaneous intracranial EEG-fMRI studies during rest and tasks could investigate the cortical neurovascular couplingat a finer spatial and temporal level notably by studying specific frequencies and looking at task-related changes. The recent development of micro-electrodes sampling neuronal activity at a much finer scale than the classical clinical intracranial electrodes by measuring multi-unit or single unit (action potentials) rather than the global post-synaptic activity represented by local field power. In patients with epilepsy, these micro-electrodes are well suited to detect very focal high frequency oscillations that are increasingly reported to have a better localising value than traditional spikes to localise epileptic activity and predict the outcome of epilepsy surgery. These electrodes are added to clinical “macro-“electrodes in some epilepsy surgery centres for such purpose and in the context of concomittant basic neuroscience research. Future feasibility and safety studies might allow their use with simultaneous fMRI for a further methodological improvement in the study of neurovascular coupling.

Biophysical models can take into account neuronal activity and haemodynamic changes to offer brain mapping with a realistic underlying model of brain activity. Dynamic Causal Modelling (DCM) represents one of these strategies to select between several putative models of the organisation of specific brain network (Friston et al. 2003). The model underlying the DCM machinery would certainly benefit from experimental evidence on the neurovascular coupling in humans gained with intracranial EEG-fMRI.

141 11.4.3

Functional and structural connectivity of epileptic networks

Given the low temporal resolution of fMRI, simultaneous ESI improves the understanding of the dynamics of interictal brain activity as illustrated in Chapter 5.

Nevertheless, EEG-fMRI studies frequently reveal several clusters of BOLD changes that are remote from the localisation of the epileptic focus and areas of its propagation.

The potential modulating effect of these regions on the activity of the source of epileptic spikes or the reverse mechanism is still poorly understood. The networks revealed by EEG-fMRI consist in brain regions that exhibit functional connectivity between each other, i.e. regions with haemodynamic signal fluctuations (taken as a surrogate of neuronal activity) that are correlated with each other. Functional connectivity cannot inform about the directionality of the information flow between the regions of the network.

However, effective connectivity technique can be used to investigate the directionality of these relationships. The use of effective connectivity analysis on fMRI data is difficult and fraught with methodological issues because the low temporal resolution of fMRI and region-specific variations of the haemodynamic response function prevent a reliable estimate of the underlying connectivity of neuronal activity. With fMRI datasets, the study of effective connectivity therefore requires underlying biophysical models of the neuronal and vascular activity and their coupling, as represented in Dynamic Causal Modelling (Friston et al. 2003).

Alternatively, effective connectivity can be applied to EEG datasets using methods derived from Granger causality theory which states that a signal A is causally influenced by another signal B if the knowledge of past states of signal B help predict the current state of signal A (Astolfi et al. 2004). Therefore, the high temporal resolution of the EEG and its direct relationship with neuronal activity make it a very suitable technique to investigate the causal interactions within a network of brain regions (Astolfi et al. 2009) and better understand the dynamics of the underlying network revealed by EEG-fMRI.

The functional and effective connectivity techniques described above have difficulties discriminating between direct and indirect connections. Insight into the proper anatomical “structural” brain connections can be obtained non-invasively by using Diffusion MRI and tractography techniques that estimate white matter tracts. This is performed by measuring the preferred direction of diffusion of water molecules in the brain which occurs preferentially along axons and myelin membranes rather than across them. Tractography studies have recently mapped anatomical connections subserving

142 physiological networks (e.g. memory, language, motor, visual systems) in patients with epilepsy epilepsy. Such studies showed altered structural connectivity in patients compared to controls (McDonald et al. 2008; Yogarajah et al. 2008; Vulliemoz et al.

2011) and some of these studies found correlations between these alterations and cognitive deficits. Moreover, the reliable mapping of these tracts in individual patients would be crucial for the planning of resective epilepsy surgery and the prediction of post-operative deficits (Powell et al. 2007; Yogarajah et al. 2009; Yogarajah et al. 2010).

Therefore, there are expectations that tractography could also be used to map connections between regions that have been highlighted by the functional mapping techniques of epileptic network. Some studies have combined tractography with functional imaging studies to map epileptic networks in small case series or single case reports and showed the existence of direct structural connections underlying the propagation of epileptic activity and that some of these direct connections might represent aberrant tracts in patients (Hamandi et al. 2008b; Bhardwaj et al. 2010).

However these studies did not investigate whether such connections are altered in a quantitative way by comparison with a control group. Great methodological care will be needed in order to map the connectivity of functionally defined regions in individual subjects. This new field is undergoing continuous technological development, notably to reduce the difficulty of tracking in regions where fibre tracts cross each other. Diffusion Spectrum Imaging, a high angular resolution technique could be precious for this purpose and we are currently implementing this tool in patients with epilepsy (Wedeen et al. 2008).

143

12 Conclusion

Multimodal imaging of epileptic activity in the human brain using simultaneous EEG-fMRI recordings allows the mapping of epileptic networks with unprecedented spatial resolution and whole-brain coverage. Clinical validation studies with invasive electrophysiology and post-surgical follow-up have shown that this methods gives information that can be of great help for the planning of invasive recordings and epilepsy surgery. Methodological developments based on advanced EEG analysis and improved EEG-informed fMRI analysis can significantly improve the yield of EEG-fMRI studies in patients with focal epilepsy. Ongoing improvements in equipment, such as EEG-fMRI with high density EEG systems as well as continuing refinement of analysis techniques will help better understand the flow of neuronal activity underlying epileptic discharges and seizure. Simultaneous intracranial EEG-fMRI can be safely performed in humans following strict safety guideline. This technique opens a new window on the human brain to study neuronal and haemodynamic correlations with the potential to provide crucial clinical information in selected patients.

These scientific methods have been developed in the field of epilepsy with the unique possibility invasive validation and direct clinical translation. They also carry the potential for translation to the analysis of neuronal network activity in physiological conditions as well as other neurological and psychiatric conditions.

144

145

13 References

This chapter includes all references of the main text. References of experimental studies in chapters 4 to 10 can be found at the end of each of these chapters.

Aarts JH, Binnie CD, Smit AM, Wilkins AJ (1984) Selective cognitive impairment during focal and generalized epileptiform EEG activity. Brain 107 (Pt 1), 293-308.

Aghakhani Y, Bagshaw AP, Benar CG, Hawco C, Andermann F, Dubeau F, Gotman J (2004) fMRI activation during spike and wave discharges in idiopathic generalized epilepsy. Brain 127(Pt 5), 1127-44.

Alarcon G, Guy CN, Binnie CD, Walker SR, Elwes RD, Polkey CE (1994) Intracerebral propagation of interictal activity in partial epilepsy: implications for source localisation. J Neurol Neurosurg Psychiatry 57(4), 435-49.

Allen PJ, Josephs O, Turner R (2000) A method for removing imaging artifact from continuous EEG recorded during functional MRI. Neuroimage 12(2), 230-9.

Allen PJ, Polizzi G, Krakow K, Fish DR, Lemieux L (1998) Identification of EEG events in

Allen PJ, Polizzi G, Krakow K, Fish DR, Lemieux L (1998) Identification of EEG events in