Electrophysiological correlates of the BOLD signal for EEG-informed fMRI

EEG and fMRI are important tools in cognitive and clinical neuroscience. Combined EEGfMRI has been shown to help to characterise brain networks involved in epileptic activity, as well as in different sensory, motor and cognitive functions. A good understanding of the electrophysiological correlates of the blood oxygen level dependent (BOLD) signal is necessary to interpret fMRI maps, particularly when obtained in combination with EEG. We review the current understanding of electrophysiological-haemodynamic correlates, during different types of brain activity. We start by describing the basic mechanisms underlying EEG and BOLD signals, and proceed by reviewing EEG-informed fMRI studies using fMRI to map specific EEG phenomena over the entire brain (“EEG-fMRI mapping”), or exploring a range of EEGderived quantities to determine which best explain co-localised BOLD fluctuations (“local EEG-fMRI coupling”). While reviewing studies of different forms of brain activity (epileptic and non-epileptic spontaneous activity; cognitive, sensory and motor functions), a significant attention is given to epilepsy because the investigation of its haemodynamic correlates is the most common application of EEG-informed fMRI. Our review is focused on EEG-informed fMRI, an asymmetric approach of data integration. We give special attention to the invasiveness of electrophysiological measurements and the simultaneity of multimodal acquisitions because these methodological aspects determine the nature of the conclusions that can be drawn from EEG-informed fMRI studies. We emphasise the advantages of, and need for, simultaneous intracranial EEG-fMRI studies in humans, which recently became available and hold great potential to improve our understanding of the electrophysiological correlates of BOLD fluctuations

Tracking slow modulations in synaptic gain using dynamic causal modelling : validation in epilepsy

In thiswork we propose a proof of principle that dynamic causal modelling can identify plausible mechanisms at the synaptic level underlying brain state changes over a timescale of seconds. As a benchmark example for validation we used intracranial electroencephalographic signals in a human subject. These data were used to infer the (effective connectivity) architecture of synaptic connections among neural populations assumed to generate seizure activity. Dynamic causal modelling allowed us to quantify empirical changes in spectral activity in terms of a trajectory in parameter space -identifying key synaptic parameters or connections that cause observed signals. Using recordings from three seizures in one patient, we considered a network of two sources (within and just outside the putative ictal zone). Bayesian model selection was used to identify the intrinsic (within-source) and extrinsic (between-source) connectivity. Having established the underlying architecture, we were able to track the evolution of key connectivity parameters (e.g., inhibitory connections to superficial pyramidal cells) and test specific hypotheses about the synaptic mechanisms involved in ictogenesis. Our key finding was that intrinsic synaptic changes were sufficient to explain seizure onset, where these changes showed dissociable time courses over several seconds. Crucially, these changes spoke to an increase in the sensitivity of principal cells to intrinsic inhibitory afferents and a transient loss of excitatory-inhibitory balance

Influence of deep structures on the EEG and their invasive and non-invasive assessment

Tesis inédita de la Universidad Complutense de Madrid, Facultad de Medicina, Departamento de Fisiología, leída el 22-11-2019El EEG es la prueba diagnóstica de mayor utilidad en el diagnóstico de la epilepsia. Consiste esencialmente en la representación gráfica de los potenciales postsinápticos generados en las neuronas piramidales de la corteza. Los campos eléctricos registrados en la superficie tienen principalmente dos mecanismos de origen: conducción de volumen desde regiones adyacentes y propagación interneuronal sináptica. Las neuronal piramidales se agrupan formando microcircuitos locales siendo estos circuitos los responsables de la generación delos ritmos registrados en el EEG. Uno de los principales retos de la electroencefalografía consiste en descifrar la relación entre la actividad registrada y la actividad subyacente en las redes neuronales. Para encontrar la fuente de dichas actividades, es necesario tener en cuenta complejos mecanismos tanto no lineales como lineales, así como el efecto de la conducción de volumen y la influencia de la morfología y las propiedades eléctricas del cerebro y el cráneo. Además, las regiones cerebrales se encuentran profusamente interconectadas a menudo produciendo una modulación recíproca que añade un mayor grado complejidad...The EEG is the most valuable diagnostic test in epilepsy. In essence, it mainly consists in agraphical representation of the summated postsynaptic potentials generated in the pyramidal neurons from the cortex. The electrical fields can be generated on the scalp by two mechanisms: volume conduction from nearby regions and synaptic inter‐neuronal propagation. Pyramidal cells align conforming local microcircuit configurations which activation lead to the generation of EEG rhythms. One of the main challenges of EEG is to decipher the relation between the recorded EEG activity and the activity in the neuronal networks. To find the source of EEG activity, complex non‐linear and linear mechanisms as well as volume conduction effect and influence of the shape and electrical properties of the brain and skull need to be taken in consideration. In addition, brain regions are profusely interconnected and functionally connected regions often produce mutual modulation that adds additional complexity...Depto. de FisiologíaFac. de MedicinaTRUEunpu

Study of the relationship between the EEG and BOLD signals using intracranial EEG - fMRI data simultaneously acquired in humans

The principal aim of this work was to further characterise the relationship between the electrophysiological and BOLD fMRI signals at the local level, exploiting the unique opportunity to analyse intracranial EEG (icEEG) and fMRI data recorded simultaneously in humans, during a finger tapping task and at rest. The MR-environment (gradient switch and mechanical vibration) related artefacts corrupting the icEEG data were the first problem tackled; they were characterised and removed using techniques developed by me. The two parts that followed aimed to shed further light on the neurophysiological basis of the BOLD effect. Firstly, the influence of the phase of the low frequency EEG activities (70 Hz) (phase-amplitude coupling: PAC) was found to explain variance in addition to a combination of , , and band powers, suggesting that PAC strength and power fluctuations result from complementary neuronal processes. Secondly, five interictal epileptiform discharge (IED) morphology and field extent related features were tested in their individual capability to predict the amplitude of the co-localised BOLD signal; these were the amplitude and rising phase slope, thought to reflect the degree of neuronal activity synchrony; width and energy, thought to reflect the duration of the excitatory post-synaptic potentials; and spatial field extent, thought to reflect the spatial extent of the surrounding, synchronised sources of neuronal activity. Among these features, the IED width was the only one found to explain BOLD signal variance in addition to the IED onsets, suggesting that the amplitude of the BOLD signal is comparatively better predicted by the duration of the underlying field potential, than by the degree of neuronal activity synchrony

Emergent Phenomena From Dynamic Network Models: Mathematical Analysis of EEG From People With IGE

In this thesis mathematical techniques and models are applied to electroencephalographic (EEG) recordings to study mechanisms of idiopathic generalised epilepsy (IGE). First, we compare network structures derived from resting-state EEG from people with IGE, their unaffected relatives, and healthy controls. Next, these static networks are combined with a dynamical model describing the ac- tivity of a cortical region as a population of phase-oscillators. We then examine the potential of the differences found in the static networks and the emergent properties of the dynamic network as individual biomarkers of IGE. The emphasis of this approach is on discerning the potential of these markers at the level of an indi- vidual subject rather than their ability to identify differences at a group level. Finally, we extend a dynamic model of seizure onset to investigate how epileptiform discharges vary over the course of the day in ambulatory EEG recordings from people with IGE. By per- turbing the dynamics describing the excitability of the system, we demonstrate the model can reproduce discharge distributions on an individual level which are shown to express a circadian tone. The emphasis of the model approach is on understanding how changes in excitability within brain regions, modulated by sleep, metabolism, endocrine axes, or anti-epileptic drugs (AEDs), can drive the emer- gence of epileptiform activity in large-scale brain networks. Our results demonstrate that studying EEG recordings from peo- ple with IGE can lead to new mechanistic insight on the idiopathic nature of IGE, and may eventually lead to clinical applications. We show that biomarkers derived from dynamic network models perform significantly better as classifiers than biomarkers based on static network properties. Hence, our results provide additional ev- idence that the interplay between the dynamics of specific brain re- gions, and the network topology governing the interactions between these regions, is crucial in the generation of emergent epileptiform activity. Pathological activity may emerge due to abnormalities in either of those factors, or a combination of both, and hence it is essential to develop new techniques to characterise this interplay theoretically and to validate predictions experimentally

Central benzodiazepine receptors in hippocampal sclerosis and idiopathic generalised epilepsies and opiod receptors in reading epilepsy

Background: Epilepsy is the most common serious disease of the brain. In order to better understand the processes and neuronal circuits involved in the pathophysiology of the epilepsies and to provide structural / functional correlations, positron emission tomography (PET) needs to be evaluated in the light of high quality MRI. Aims: To determine the extent and amount of central benzodiazepine/GABAA receptor (cBZR) abnormalities in mesial temporal lobe epilepsy (mTLE) due to hippocampal sclerosis (HS); to quantify cBZR in idiopathic generalised epilepsy (IGE) and the effect of treatment with sodium valproate (VPA); to investigate dynamic changes of opioid receptors in reading epilepsy (RE) at the time of reading-induced seizures. Methods: 11C-flumazenil (FMZ)-PET scans of 37 controls, 25 candidates for temporal lobe resections with HS, and 10 patients with IGE before and after taking VPA, were analysed with statistical parametric mapping (SPM) and a partial-volume-effect (PVE) corrected regions-of-interest approach to quantify FMZ binding to cBZR. Paired 11C-diprenorphine (DPN)-PET scans of 6 control subjects and 5 patients with RE were analysed with SPM to detect significant localised reductions of DPN binding during reading-induced seizures implying a focal release of endogenous opioids. Results: Using SPM, reductions of cBZR were restricted to the sclerotic hippocampus in unilateral mTLE. Using PVE correction loss of cBZR in HS was shown to be over and above that due to neurone loss and hippocampal atrophy. In-vivo 1IC-FMZ-PET correlated well with ex-vivo 3H-FMZ autoradiography in HS. Subtle reductions of cBZR are seen contralaterally in unilateral mTLE in 30%. cBZR in IGE are increased in the cortex and thalamus, and FMZ binding is not affected by VPA. Endogenous opioids are released locally in the left temporo-parietal cortex at the time of reading-induced seizures. Conclusions: The identification of functional abnormalities of major inhibitory neurotransmitter systems, over and above structural abnormalities, has profound implications for the presurgical investigation of patients, in whom MRI does not reveal a relevant underlying lesion. Elucidation of the neurochemical and functional abnormalities underlying seizures assists the design of new anti-epileptic drugs and helps to identify neurochemical abnormalities underlying specific epilepsy syndromes

A neurophysiological and proteomic study of cognitive enhancing strategies

Improving cognitive function is a growing area of interest for pharmaceutical companies. With an ageing population, cognitive decline is becoming a greater problem. Understanding the physiological effects of nootropic drugs and the changes that occur during cognitive enhancement will enable the design of safer treatments to enhance cognition. In this thesis cognitive enhancing strategies are investigated using neurophysiological and proteomic approaches. The effects of two classes of putatively cognitive enhancing drugs on emergent network oscillatory activities in hippocampal slices are investigated. The effect of an enriched environment, which causes an improvement in cognitive function, on the expression level of proteins in the hippocampus is also investigated. The development of a new muscarinic acetylcholine receptor (mAChR) agonist that is selective for the M1 mAChR subtype, called 77-LH-281, has recently been achieved. 77-LH-281 binds to an allosteric site of the M1 mAChR which accounts for its increased selectivity over other mAChR agonists. This agonist causes gamma frequency oscillatory activity in hippocampal slices, a pattern of network activity that the in vivo equivalent of which is associated with cognitive processes. This gamma activity is dependent upon both excitatory and inhibitory networks. 77-LH-281 does not promote epileptiform-like activity in naïve slices as well as a range of models of epileptiform activity, unlike non-subtype selective mAChR agonists like oxotremorine-M. Oxotremorine-M changes the slow inter-ictal-like events following application of 4-AP and NBQX into continuous beta frequency oscillations. This action is not mediated by the M1 mAChR. Thus selective M¬1 mAChR display a preferable range of oscillatory activities compared to non-subtype selective mAChR agonists. Ampakines are a further class of nootropic drugs. Ampakines are positive modulators of AMPA-type glutamate receptors and they cause improvements in cognitive function of laboratory animals and humans. The ampakines investigated in this thesis are CX691, which increases the amplitude of currents through the AMPA receptor, and CX546, which increases the length of time the AMPA receptor is open. These ampakines do not induce oscillatory activity in naïve hippocampal slices, but they increase the frequency of inter-ictal-like epileptiform activity. CX546 also induces ictal-like activity in the 4-AP induced epileptiform event model. Ampakines may therefore promote epileptiform activity in individuals that are susceptible to epilepsy. Exposure to an enriched environment leads to improvements in cognitive performance. This behavioural change is mediated by changes at the level of the proteome. Exposure to an enriched environment changes the expression of many classes of proteins including signalling proteins and proteins that are involved in the structural changes that occur during cognitive enhancement. One of the proteins that significantly changes in expression is a protein that is associated with cognitive deficits, known as MeCP2. MeCP2 is a transcriptional repressor and increases in expression in the enriched environment. This thesis demonstrates the diversity of molecular, cellular and network level approaches that can be used to induce and investigate cognitive enhancement. A combination of these approaches enables the in vitro evaluation of current cognitive enhancing strategies and may lead to the the development of novel approaches to enhance cognitive function

The Effect of Input from the Cerebellar Nuclei on Activity in Thalamocortical Networks

The cerebellum is a prominent brain structure that contains more than half of all neurons, in the brain, which are densely packed and make up 15% of the total brain mass (Andersen et al., 1992). It is well known for its contribution to the control of motor functions, but it also plays a pivotal role in non-motor behaviours. The cerebellum is also involved in numerous pathological conditions. This thesis contributes to the understanding of the pathophysiology of the cerebello-thalamo-cortical pathways. I concentrate on two cerebellar diseases, namely: absence epilepsy (Noebels, 2005) and downbeat nystagmus (DBN) (Strupp et al., 2007). In this thesis the missing link in explaining the alleviating mechanism of a potassium channel blocker on downbeat nystagmus was found. A simulated single biologically detailed floccular target neuron (FTN) model was stimulated by input from cerebellar Purkinje cells (PCs). It was demonstrated that for both synchronised and unsynchronised input, irregular PC spike trains (which resembles the DBN condition) resulted in elevated FTN firing rates, in comparison with regular (4-AP treated) ones. This increase or decrease of the FTN firing rates during DBN, or after 4-AP treatment, respectively depended on short term depression (STD) at the PC - FTN synapses exclusively in the cases when the PC input was unsynchronised. In contrast, results of previous modelling studies (Glasauer et al, 2011; Glasauer and Rossert, 2008) were not in-line with the corresponding experimental findings (Alvina and Khodakhah, 2010) because they did not take into account the STD on the FTN-PC synapses. It was also demonstrated here that the cerebellar output contributes to the control of absence epilepsy that originates in the thalamocortical network. Moreover, the cerebellar input was most effective when it arrived at the peak of the GSWD burst, with the least effective input arriving during the inter-ictal interval, showing clear phase-dependency. I have also shown that a three-fold increase in the inhibitory time constant, drives the asynchronous-irregular network into an ictal state. This increase reflects the GABAA block. A change to GABAB dominated inhibition results in GSWDs, in which the “wave” component is related to the slow GABAB-mediated K+ currents (Destexhe, 1998). Therefore, in this thesis two important contributions are made to the understanding of cerebellar pathological states: absence epilepsy and DBN, which might in turn be useful in the potential treatment of these conditions.