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Institute
Sleep is one of the fundamental requirements of all animals from nematodes to humans. It appears in different formats with shared features such as reduced muscle activities and reduced responsiveness to the environment. Despite the long history of sleep research, why a brain must be taken offline for a large portion of each day remains unknown. Moreover, sleep research focused on mammals and birds reveals two stages, rapid-eye-movement (REM) and slow-wave (SW) sleep, alternating during sleep. Whether these two stages of sleep exist in other vertebrates, particularly reptiles, is debated, as is the evolution of sleep in general.
Recordings from the brain of a lizard, the Australian bearded dragon Pogona vitticeps, indicate the presence of two electrophysiological states and provides a better picture of their sleep. Local field potential (LFP) signals, head velocity, eye movements, and heart rate during sleep match the pattern of REM and SW sleep in mammals. The SW and REM sleep patterns that we observed in lizards oscillated continuously for 6 to 10 hours with a period of 80-100 seconds when the ambient temperature was ~27°C. Lizard SW dynamics closely resemble those observed in rodent hippocampal CA1, yet originated from a brain area, the dorsal ventricular ridge (DVR), that does not correspond anatomically or transcriptomically to the mammalian hippocampus. This finding pushes back the probable evolution of these dynamics to the emergence of amniotes, at least 300 million years ago.
Unlike mammals and birds, REM and SW sleep in lizards occupy an almost equal amount of time during sleep. The clock-like alternation between these two sleep states was found initially by measuring the power modulation of two frequency bands, delta and beta. I recorded the full-band LFP and found an infra-slow oscillation (ISO) in the frequency range between 5 and 20 milli-Hz during sleep. The magnitude of ISO increased during sleep and decreased during both wakefulness and arousal during sleep. The up- and down-states of ISO were synchronized with the sleep state alternating rhythm but with a significant time lag dependent on the locations of the recording electrodes. Multi-site LFP recordings indicated that this ISO is a putative propagation wave sweeping extremely slowly, 30-67 µm/sec, from the posterior-dorsal pole to the anterior-ventral pole of the DVR.
Previous studies in other animals showed that brainstem areas such as the locus coeruleus, laterodorsal tegmentum, and periaqueductal gray are involved in sleep states regulation. It is sadly impossible to carry out in vivo recordings in the lizard brainstem without severely affecting them and their quality of life. I thus carried out ex vivo recordings in both DVR and brainstem. Pharmacological stimulation of the brainstem could reversibly silence one distinct EEG pattern characteristic of SW sleep, the sharp-wave and ripple complex, in DVR. An ISO could be recorded simultaneously in both DVR and brainstem. From data collected in both intact and split ex vivo brains, I concluded that there are independent ISO generators in at least two areas, the brainstem and the telencephalon. Their signals may normally be synchronized by long-range connections. The DVR ISO leads the brainstem ISO by ~29 sec. Optogenetic stimulation of brainstem neurons was able to disrupt the ISO in DVR reversibly.
In conclusion, the lizard brain offers a relatively simple model system to study sleep. Despite a diversity of results in different lizard species, my results revealed a number of new findings. Relevant for sleep research in general: 1) REM and SW sleep exist in a reptile. Since they also exist in birds and mammals, they probably existed in their common amniote ancestor, if not earlier. 2) REM and SW occupy equal amounts of time during sleep (50% duty cycle), a unique feature among all described sleep electrophysiological patterns, suggesting the possible existence of a simple central pattern generator of sleep, possibly ancestral. 3) I discovered the existence, in the local field potential, of an infra slow oscillation with extremely slow propagation, locked to the SW-REM alternating rhythm. The causes and mechanisms of this ISO remain to be understood. To my knowledge, the correlation between sleep states and a slow rhythm has only been reported in human scalp EEG recordings so far.
Exploring the in vivo subthreshold membrane activity of phasic firing in midbrain dopamine neurons
(2021)
Dopamine is a key neurotransmitter that serves several essential functions in daily behaviors such as locomotion, motivation, stimulus coding, and learning. Disrupted dopamine circuits can result in altered functions of these behaviors which can lead to motor and psychiatric symptoms and diseases. In the central nervous system, dopamine is primarily released by dopamine neurons located in the substantia nigra pars compacta (SNc) and ventral tegmental area (VTA) within the midbrain, where they signal behaviorally-relevant information to downstream structures by altering their firing patterns. Their “pacemaker” firing maintains baseline dopamine levels at projection sites, whereas phasic “burst” firing transiently elevates dopamine concentrations. Firing activity of dopamine neurons projecting to different brain regions controls the activation of distinct dopamine pathways and circuits. Therefore, characterization of how distinct firing patterns are generated in dopamine neuron populations will be necessary to further advance our understanding of dopamine circuits that encode environmental information and facilitate a behavior.
However, there is currently a large gap in the knowledge of biophysical mechanisms of phasic firing in dopamine neurons, as spontaneous burst firing is only observed in the intact brain, where access to intrinsic neuronal activity remains a challenge. So far, a series of highly-influential studies published in the 1980s by Grace and Bunney is the only available source of information on the intrinsic activity of midbrain dopamine neurons in vivo, in which sharp electrodes were used to penetrate dopamine neurons to record their intracellular activity. A novel approach is thus needed to fill in the gap. In vivo whole-cell patch-clamp method is a tool that enables access to a neuron’s intrinsic activity and subthreshold membrane potential dynamics in the intact brain. It has been used to record from neurons in superficial brain regions such as the cortex and hippocampus, and more recently in deeper regions such as the amygdala and brainstem, but has not yet been performed on midbrain dopamine neurons. Thus, the deep brain in vivo patch-clamp recording method was established in the lab in an attempt to investigate the subthreshold membrane potential dynamics of tonic and phasic firing in dopamine neurons in vivo.
The use of this method allowed the first in-depth examination of burst firing and its subthreshold membrane potential activity of in vivo midbrain dopamine neurons, which illuminated that firing activity and subthreshold membrane activity of dopamine neurons are very closely related. Furthermore, systematic characterization of subthreshold membrane patterns revealed that tonic and phasic firing patterns of in vivo dopamine neurons can be classified based on three distinct subthreshold membrane signatures: 1) tonic firing, characterized by stable, non-fluctuating subthreshold membrane potentials; 2) rebound bursting, characterized by prominent hyperpolarizations that initiate bursting; and 3) plateau bursting, characterized by transient, depolarized plateaus on which bursting terminates. The results thus demonstrated that different types of phasic firing are driven by distinct patterns of subthreshold membrane activity, which may potentially signal distinct types of information. Taken together, the deep brain in vivo patch-clamp technique can be used for the investigation of firing mechanisms of dopamine neurons in the intact brain and will help address open questions in the dopamine field, particularly regarding the biophysical mechanisms of burst firing in dopamine neurons that control behavior.
The objectives of this thesis were to understand how distinct classes of cell types interact to shape oscillatory activity in cortical circuits of the turtle. We chose the turtle cortex as a model system for cortical computations for two reasons. One is that the phylogenetic position of turtles makes their cortex functionally and anatomically particularly interesting. The second is that reptilian brains present several unique experimental advantages. Turtles have a three-layered cortex that forms the dorsalmost part of their pallium and receives direct input from visual thalamus. Thus turtle cortex, while sharing several features with mammalian cortices, constitutes a simpler system for studying cortical computations and dynamics. Freshwater turtles are semiaquatic species, that dive for hours and hibernate for months without breathing. Their brains are adapted to these behaviors so that they can operate under severe anoxia. This property allows for ex vivo wholebrain and whole-cortex (”cortical slab”) preparations in vitro, enabling the use of many sophisticated techniques for monitoring activity in parallel.
I thus set out to utilize the advantages of our model system, by using optogenetic methods to reliably evoke oscillations in an ex vivo whole-cortex preparation while observing activity in parallel with planar multi-electrode arrays (MEA), linear silicon depth-electrodes and patch-clamp recording techniques. This required several technical aspects to be solved. Prior work in turtle cortex (Prechtl, 1994; Prechtl et al., 1997; Senseman and Robbins, 2002) indicated that visual stimuli evoke complex activity patterns (e. g. wave patterns) in dorsal cortex. The goal was to examine these dynamics in detail and to provide mechanistic explanations for them whenever possible. The recent advent of optogenetics, the development of microelectrode arrays, and the possibility to combine these techniques with classical electrophysiological approaches on a resistant, accessible and stable preparation led me to explore a number of technical avenues.
First I had to establish gene delivery methods in reptiles. I settled on recombinant viruses, and show results from several serotypes of adeno-associated virus (AAV), i lentivirus and rabies virus. I report successful gene expression of genes of interest with several subtypes of AAV, including the commonly used AAV2/1 and AAV2/5 serotypes. Second I had to find promoters enabling global and cell-type specific gene expression in reptiles. Ubiquitous high-yield promoters such as CAG/CB7 or CMV drive high levels of expression in turtles; cell-type specific promoters such as hSyn (expression limited to neurons) and CaMKIIa (expression limited exclusively o mostly to excitatory neurons) appear similarly biased in turtles. Other cell-type specific promoters reported in the literature (fNPY, fPV, fSST) failed to express in turtles.
A second major aspect of my work focused on electrophysiological recordings using microelectrode arrays and the interpretation of extracellular signals recorded from cortex in ex vivo preparations. We observed that spike signals produced by pyramidal and inhibitory neurons were very often followed by a slower potential. We identified these slower potentials as reflections of synaptic currents, and thus of the axonal projections of the neurons, at least within the deep layers of cortex. This also resulted in a means to classify neurons as excitatory or inhibitory with much higher reliability than classical methods (e. g. spike width). The final aspect of my work concerns the use of optogenetics to dissect the mechanisms of cortical oscillations and wave propagation. I show that oscillations can be induced by light in turtle cortex after transfection with AAV2/1 carrying the gene for channelrhodopsin 2 (ChR2). By using the CaMKIIa promoter, ChR2 induced currents are limited to LII/III excitatory cells; we can therefore control excitatory drive to cortical networks. If this drive is strong enough, layer III inhibitory interneurons are recruited and fire in a concerted fashion, silencing the excitatory population. The visually evoked 20 Hz oscillations observed in chronically recorded animals (Schneider, 2015) or in anaesthetized animals (Fournier et al., in press) thus appear to result from a feedback loop between E and I cells within layers II & III. Details of these interactions are being investigated but - layer I interneurons, by contrast, do not seem to be involved. By pulsing light I could control the frequency of the oscillations within a range of several Hz around the natural oscillation frequency. Above this range, cortex could only follow the stimulus at a fraction (1/2, 1/3,...) of the light pulse frequency. Using a digital micromirror device, I limited activation of the cortical networks spatially, enabling the study of wave propagation in this system.
Reptilian cortex offers a relatively simple model system for a reductionist and comparative strategy on understanding cortical computations and dynamics. Turtle dorsal cortex could thus give fundamental insights to the primordial organization tional, computational and functional principles of cortical networks. These insights are relevant to our understanding of mammalian brains and may prove valuable to decipher fundamental questions of modern neuroscience.