Innovative research techniques applied to sleep: an insight into sleep patophysiology

As has been stated, we have gained more knowledge on sleep physiology in the last 60 years than in the previous 6000 (Hobson, 1989). This holds true thanks to the massive advances technologies have provided in the past century, ranging from the introduction of electroencephalogram (EEG) in the twenties of the last century by Berger to the latest optogenetic approaches (Adamantidis et al., 2013). The major change put forward by this more detailed understanding of sleep function and functioning has been the transition of sleep as a state of absolute inertia, paralleled to death by almost all the ancient literature, to a reactive state of the brain: during sleep, cerebral activity presents its most diverse expressions, from the bold slow waves sleep of the deep stages to the wake like activity of REM associated with muscular atonia, and is able to differently react to external perturbations with rapid frequency shifts (Terzano and Parrino, 2000). Moreover, the modulations that sleep and sleep deprivation exert have been postulated deriving both from plain clinical observations, i.e. in epilepsy, and from animal studies. Sleep deprivation is the best method for provoking EEG epileptiform abnormalities and seizures (Bennett, 1963; Pratt et al., 1968; Jovanovic, 1991; King et al., 1998) in most types of epilepsy (Dinner, 2002), and many epileptic syndromes, such as the generalized idiopathic epilepsies (IGE), are prone to circadian fluctuations related to the sleep-wake cycle - with seizures gathering mostly early in the morning or at awakening (Niedermeyer et al., 1985). The mechanisms underlying the activation of paroxysmal activity remain to be elucidated. The activation of epileptic patterns has been attributed to drowsiness and sleep (Pratt et al., 1968), while sleep deprivation has been shown to have a specific activating effect on patients who remain awake during recording (Naitoh and Dement, 1974). In animals, sleep deprivation results in a lowering of the threshold for electroshock convulsions (Cohen and Dement, 1965) and kindling (Shouse, 1988) due to a shift in the balance between excitatory and inhibitory neurotransmitters (Naitoh and Dement, 1974). But while animal studies deploy invasive techniques, as did the pioneer physiology studies by (Bremer 1935 and 1936; Moruzzi and Magoun, 1949) that allowed the definition of cerebral and truncal structures involved in sleep building-up and maintenance and their neurotransmitters, growing concerns about in vivo animal studies have pushed towards other research methods, that moreover could be applied to the human being too. Indeed, one of the major limitations in the field of sleep research up to the last decades was determined by the only available technique applicable in humans - electroencephalogram. Since the eighties of the last century, a series of technological advances introduced in clinical practice Magnetic Resonance Imaging (MRI). MRI permits not only a more detailed visualization of brain structures than those of previous neuroimaging, such as computed tomography (CT) scanning, but also, due to the implementation of new acquisition sequences and analysis procedures, the identification of blood oxygenation level dependent (BOLD) activations. The latter consists of a cerebral area in which any sort of metabolic process is going on, in a frame time of a few seconds, and is generally related to areas active due to a given task. The serendipitous observation that persistent BOLD activated areas are present also in the idling brain led to the proposal of the concept of a default mode network (DMN), that is, a series of possibly interconnected cerebral regions that switch on in the very moment any brain engagement is supposed to switch off (Raichle et al., 2001). The persistence of an analogous pattern also during sleep led to the hypothesis of this network to be the neural substrate of mentation and perhaps consciousness. Further improvements in the mathematical models that support BOLD signal analysis were subsequently able to disentangle the various components of the this “resting brain activity”, generating an array of so called resting state networks (RSNs) (Rosazza and Minati, 2011) that encompass diverse physiological functions. A step further was possible with the introduction, almost 15 years ago, of MRI compatible EEG equipment that prevents the generation of oddy currents inside the electrode: the concomitant EEG registration with an MRI scan permits to relate a particular EEG activity with the underlying BOLD signal. The same magnetic field shielded electrodes were later on exploited in the contest of electro-magnetic fields generated through wires rolled into a coil, that were presented by Baker in 1985 as transcranial magnetic stimulation (TMS). TMS final effect is that of electrically stimulating the superficial layers of the cortex, and EEG-TMS co-registration offered the chance to investigate the direct effect of a pulse on the cortex (Ilmoniemi et al., 1997) by removing possible interferences from the descending motor pathways, that were intermixed in the standard parameter by which TMS alone is evaluated - the motor evoked potential (MEP) recorded from a muscle corresponded to the cortical activated area (Groppa et al., 2012). The perturbation TMS induces on the cerebral activity can also be studied as the modulation of EEG rhythms (Thut and Miniussi, 2009), that react differently depending on the stimulating paradigm (Manganotti and Del Felice, 2012) or on the intrinsic brain rhythm or stimulus frequency (Thut et al., 2012). The last technological innovation I am going to describe has been developed over the last decade: the introduction of high-density scalp EEGs (hdEEG), with up to 256 electrodes spread out over the scalp, the occiput and the cheeks of the subject, that offers a much higher spatial resolution than standard EEG caps. This high spatial resolution sampling has revived an older analysis method aimed at identifying via a mathematical approach called the inverse solution method the number, location and orientation of deep generators of scalp activity, the so called electrical source imaging (ESI) (Fender, 1987; Brunet et al., 2011). ESI involves numerous scalp electrodes, HdEEG , and realistic head models derived from structural MRI, and has so far mainly been applied to epileptic discharges (Scherg and Von Cramon, 1985, Liu et al., 1998, Babiloni et al., 2003, Michel et al., 2004), with only few reports in sleep (Siniatchkin et al., 2010). The aim of this dissertation thesis is to discuss the application of these technologies to the clarification of open issues in sleep physiology and pathophysiology. A first approach was to study the effects of sleep deprivation on cortical excitability through EEG-TMS co-registration experiments, both in healthy controls and in the frame of pathologically abnormal cortical excitability (i.e. epilepsy). A second set of experiments focused on fMRI data of subjects sleeping in the bore of the scanner during a concomitant external perturbation – an electrical stimulation at the wrist in the specific case. Finally, the potentiality of ESI has been applied to physiological sleep figures, in order to contribute to the open issue of their generators’ nature. A similar study design was also used in a population of focal epileptic patients, given the still actual debate over the relation of sleep figures and epileptic spikes. These techniques encompass different neurophysiological aspects providing a multiprospective view of sleep phenomena. The translation of such an approach to other states of reduced consciousness (i.e. vegetative or minimally conscious states) should be one of the future directions of research.