Patterns of hippocampal ensemble activity that occur during a spatial experience are reactivated during subsequent rest periods and slow wave sleep. Connections between active cells are thought to be strengthened, via long term potentiation (LTP), by repeated co-activation during experience, which suggests that the level of memory trace reactivation would increase proportionately with repetition. Alternatively, plasticity associated with memory formation, such as LTP-dependent place field expansion and the induction of activity-dependent immediate early gene, ARC, saturates after only a few laps, indicating that reactivation would plateau after a few repetitions. The length of the repeated sequence may also affect reactivation, since activation of a very short sequence can be repeated more frequently than a long sequence in a given time period. We studied how memory trace reactivation was affected by repetition and the length of the repeated sequence by observing the reactivated patterns of cell-pair correlations after a rat ran laps around a long circular track versus running more laps around a short track. On the shorter track, fewer cells had place fields, but they covered more of the track, resulting in generally stronger correlations among active cells. In addition, neuronal activity was recorded from dorsal and mid-ventral CA1. In mid-ventral CA1, there were fewer place fields in the environment but they were larger, with generally stronger correlations among active cells. The comparison between dorsal and mid-ventral regions is thus analogous to the comparison between the sequence of place fields on a long versus short track, respectively. Although there were more cells active in the dorsal region, but more potent correlations in the middle region, no differences in memory trace reactivation were found with respect to repetitions, track length or hippocampal region. This suggests that although spatial scaling increased along the dorsoventral axis of the hippocampus, reactivation is balanced, and possibly coherent across the hippocampal axis and it is relatively independent of sequence length or number of repetitions, at least when that number exceeds about 20.

Im Hippokampus gibt es verschiedene Netzwerkoszillationen mit unterschiedlichen Frequenzen. Ein Typ dieser Oszillationen sind die ”Ripple” mit einer Frequenz von etwa 200 Hz, welche in Komplexen mit einer Aktivitätswelle, der ”Sharp wave” auftreten. Sharp wave-ripple Komplexe (SWR) werden mit der Konsolidierung von Gedächtnis in Zusammenhang gebracht. Das Netzwerk, das den SWR unterliegt, hat bestimmte Mechanismen, von denen einige in der vorliegenden Arbeit näher untersucht werden. Im ersten Teil wird untersucht, wie ein hemmendes Interneuron in der hippokampalen Region CA1, das ”oriens-lacunosum moleculare” (O-LM) Interneuron, während der SWR in das Netzwerk eingebunden ist. Wir konnten zeigen, dass O-LM Zellen während der SWR starke synaptische Exzitation erhalten. Die Exzitation tritt spät während des Ripples im lokalen Feldpotential (LFP) auf und zeigt eine Phasenankopplung an die Ripple. In etwa der Hälfte der O-LM Zellen konnten wir Aktionspotentiale während der SWR zeigen, die an die Ripple-Phase im LFP gebunden sind und nach dem Ripple-Maximum auftreten. Der zweite Teil der Arbeit bezieht sich auf die hippokampale Region CA1 und vergleicht während SWR den synaptischen Eingang in zwei Untertypen von Pyramidenzellen, die tiefen und die oberflächlichen Pyramidenzellen. Beide Untertypen bekommen synaptische Eingänge während der SWR. Diese Eingänge sind eine Mischung aus exzitatorischen und inhibitorischen Eingängen, die in den Untertypen in ihrer Stärke vergleichbar sind. Im dritten Teil untersuchen wir die SWR in der Region CA2 des Hippokampus und zeigen, dass Pyramidenzellen in CA2 in das Netzwerk während SWR eingebunden sind. Wir können sowohl exzitatorische als auch inhibitorische synaptische Eingänge in den Pyramidenzellen darstellen und konnten eine Phasenkopplung der synaptischen Eingänge an die SWR im LFP zeigen. Aufgrund der Phasenverschiebung bei verschiedenen Haltepotentialen vermuten wir einen Oszillator für die Exzitation und einen für die Hemmung. / In the hippocampus there are different patterns of activity also known as network oscillations. These oscillations express different frequencies, and one oscillation is the ripple oscillation at around 200 Hz. It is associated with an activity wave called sharp wave and form a so-called sharp wave-ripple complex (SWR). SWRs are implicated in memory consolidation. In this thesis we investigate mechanisms underlying sharp wave-ripple complexes. In the first part of this thesis I examine one type of inhibitory neurons in the region CA1 of the hippocampus during SWR. Oriens-lacunosum moleculare (O-LM) interneurons receive strong excitatory synaptic input during ripples. This input arrives after the ripple maximum and is phase locked with the ripple cycles. Around half of the probed O-LM cells fire during the SWR and thereby show an active participation during SWR. The magnitude of excitation in O-LM cells and the ratio between excitation and inhibition determine if an O-LM cell is active during the SWR. Action potentials in these cells occur late during the SWR and are phase locked. In the second part the synaptic input onto excitatory pyramidal cells were investigated during ripple oscillations. Previous work has identified two different types of pyramidal cells in area CA1. We recorded from deep and superficial pyramidal cells. For both types of pyramidal cells the inhibitory and excitatory synaptic inputs temporally associated with ripples express comparable strength. In the last and third part, I recorded SWR in the CA2 region of the hippocampus and showed incidence, frequency and amplitude of ripples and SWR. Pyramidal cells in the CA2 region are integrated into the network during SWR. They receive SWR associated synaptic input during SWR. The excitatory and inhibitory synaptic inputs in CA2 pyramidal cells were investigated in detail. Phase analysis show phase locking of local field potential ripples and synaptic inputs to the ascending phase of the ripple cycle.

New memories are labile, but over time some of them are stabilized. This thesis investigates the network mechanisms in the brain underlying the gradual consolidation of memory representations. Specifically, I performed a causal test of the long-standing hypothesis that the offline reactivation of new, memory-representing cell assemblies supports memory consolidation by stabilizing those assemblies and increasing the likelihood of their later reinstatement - and therefore presumably of memory recall. I performed multi-unit extracellular recordings in the dorsal CA1 region of behaving mice, from which I detected short-timescale (25 ms) co-activation patterns of principal neurons during exploration of open-field enclosures. These cell assembly patterns appeared to represent space as their expression was spatially tuned and environment specific; and these patterns were preferentially reactivated during sharp wave-ripples (SWRs) in subsequent sleep. Importantly, after exposure to a novel - but not a familiar - enclosure, the strength with which an assembly pattern was reactivated predicted its later reinstatement strength during context re-exposure. Moreover, optogenetic silencing of hippocampal pyramidal neurons during on-the-fly detected SWRs during the sleep following exposure to a novel - but again not a familiar - enclosure impaired subsequent assembly pattern reinstatement. These results are direct evidence for a causal role of SWR-associated reactivation in the stability of new hippocampal cell assemblies. Surprisingly, offline reactivation was only important for the stability of a subset of the assembly patterns expressed in a novel enclosure. Optogenetic SWR silencing only impaired the reinstatement of "gradually strengthened" patterns that had had a significant increasing trend in their expression strength throughout the initial exposure session. Consistent with this result, a positive correlation between reactivation and subsequent reinstatement was only found for these gradually strengthened patterns and not for the other, "early stabilized" patterns. An interesting interpretation is that the properties of the gradually strengthened patterns are all consistent with the Hebbian postulate of "fire together, wire together". To enable investigation of the relation between interneurons and principal cell assembly patterns from extracellular recordings, as a final contribution this thesis describes a statistical framework for the unsupervised classification of interneurons based on their firing properties alone.

Biomedical devices play a crucial role in the healthcare system, enabling more effective treatments, less invasive procedures, and more precise diagnoses. Due to these compelling reasons, development of new biomedical devices and biomaterials have always been in high demand. Exploring and refining fabrication methods are essential to the development of new biomedical devices. Some of the common fabrication methods include microfabrication methods (photolithography and soft lithography), 3D printing (additive manufacturing), laser machining, thermal drawing, and electrospinning. The choice of fabrication methods heavily depends on the materials, geometry, and functionalities of biomedical devices. Currently, the thermal drawing process has proven to be an excellent scalable fabrication platform for neural interface, tissue engineering, tumor/cancer treatment, soft robotics, and smart textiles. This Ph.D. dissertation summarizes my research on the fabrication and validation of thermally drawn multifunctional polymer fiber probes for modern biomedical applications, primarily in the fields of neural interfaces and tumor treatments. Understanding the neural basis of behavior requires monitoring and manipulating combinations of physiological elements and their interactions in behaving animals. Utilizing the thermal drawing process, we developed T-DOpE (Tapered Drug delivery, Optical stimulation, and Electrophysiology) probes and Tetro-DOpE (Tetrode-like Drug delivery, Optical stimulation, and Electrophysiology) probes that can simultaneously record and manipulate neural activity in behaving rodents. Taking advantage of the triple-functionality, we monitored local field potential (LFP) while manipulating cannabinoid receptors (CB1R; microfluidic agonist delivery) and CA1 neuronal activity using optogenetics. Focal infusion of CB1R agonist downregulated theta and sharp wave-ripple oscillations (SPW-Rs). Furthermore, we found that CB1R activation reduces sharp wave-ripples by impairing the innate SPW-R-generating ability of the CA1 circuit. Microscale electroporation devices are mostly restricted to in vitro experiments (i.e., microchannel and microcapillary). We developed a flexible microscale electroporation fiber probe through a thermal drawing process and femtosecond laser micromachining techniques. The novel fiber microprobes enable microscale electroporation and arbitrarily select the cell groups of interest to electroporate. Successful reversible and irreversible microscale electroporation was observed in a 3D collagen scaffold (seeded with U251 human glioma cells) using fluorescent staining. Leveraging the scalable thermal drawing process, we envision a wide distribution of multifunctional polymer fiber probes in research facilities and hospitals. Along with the fiber probes presented in this dissertation, additional insight and future perspective on thermally drawn biomedical devices are discussed. / Doctor of Philosophy / The thermal drawing process is a versatile and scalable platform for fabricating functional fiber technology. The process was formerly adapted from fabrication method for silica optical fibers, widely used in telecommunication (e.g., telephone, internet, cable TV, etc.). To name some functionalities of these fibers, they can move, hear, sense touch, change colors, harvest and store energy, record and manipulate brain activity, and ablate tumors. As imagined, these functionalities are derived from the unique geometry and functional materials embedded along the fiber. Therefore, developing the fiber design tailored to a specific application is a critical step to making a successful fiber product. In this dissertation, I will present my work on biomedical devices fabricated with the thermal drawing process and their application in neuroscience and tumor/cancer treatment. Utilizing the thermal drawing process, we developed neural interfaces that can be implanted into the deep brain and record and simultaneously manipulate the neural activity. These neural interfaces (Chapter 2,3; T-DOpE and Tetro-DOpE probes, respectively) are able to record both local field potentials (LFP; activity of thousands or more neurons) and single action potentials (single on/off signal from individual neurons nearby). By manipulating the gene expression, we can control the activity of neurons with specific light (λ= 470nm; blue light) exposure. We implemented optical waveguide in our probes to guide light from a laser source to the tip of the probe and manipulate the neural activity. Furthermore, we fabricated micro-channels within the device to enable focal drug delivery at the tip of the device. Using the T-DOpE probe, we studied the effect of local synthetic cannabinoid injection in the hippocampus. We found that the local injection of the drug in hippocampus CA1 makes neurons incapable of generating sharp wave-ripples (a neural signal associated with memory). Electroporation is a biophysical phenomenon where short high electric field pulses introduce nanoscale defects in cell membrane. These defects can cause unstable cellular homeostasis and eventually leads to cell death. Due to reduced treatment time, no heat effect, and tissue selectivity, electroporation has been used in clinical trials for cancer treatments. Using the thermal drawing process and laser micromachining techniques, we developed a flexible microscale electroporation fiber probe capable of ablating tumor cells. Due to the low-cost and scalability of thermal drawing process, we envision the use of thermally drawn functional fiber technology in biomedical fields. In this dissertation, I also address some challenges and future directions of thermally drawn functional fibers in biomedical fields.

Eine einzigartige experimentelle Beobachtung, welche die Basis für eine ganzheitliche, neurowissentschafliche Theorie für Gedächtnis darstellen könnte, sind sharp wave-ripples (SWRs). SWRs werden in lokalen Neuronennetzwerken erzeugt und sind wichtig für Gedächtniskonsolidierung; SWRs sind charakteristische Ereignisse der lokalen Feldpotentiale im Hippocampus des Säugetiers, die in Phasen von Schlaf und Ruhe vorkommen. Eine SWR besteht aus einer sharp wave, einer ≈ 100 ms langen Auslenkung des Feldpotentials, welche mit ripples, 110–250 Hz Oszillationen, überlagert ist. Jüngste Experimente bekräftigen die Theorie, dass ripples in Netzwerken inhibitorischer Interneurone (INT-INT) erzeugt werden, die aus parvalbumin-positive basket cells (PV+BCs) bestehen. PV+BCs sind untereinander über rekurrente inhibitorische Synapsen und Gap Junctions (GJs) gekoppelt. In dieser Arbeit untersuche ich die spezifische Funktion von interneuronalen Gap Junctions in ripples. Im Hauptteil dieser Arbeit demonstriere ich, dass GJs in INT-INT Netzwerken die neuronale Synchronität und die Feuerrate während ripples erhöhen, die ripple-Frequenz sich hingegen nur leicht verändert. Zusätzlich zeige ich, dass diese rippleunterstützenden Effekte nur dann auftreten, wenn die GJ-Transmission schnell genug ist (≈< 0.5 ms), was wiederum somanahe Kopplung voraussetzt (≈< 100 µm). Darüber hinaus zeige ich, dass GJs die oszillatorische Stärke der ripples erhöhen und so die minimale für ripples notwendige Netzwerkgröße verringern. Abschließend zeige ich, dass ausschließlich mit Gap Junctions gekoppelte INT-INT Netzwerke zwar mit ripple Frequenz oszillieren können, aber wahrscheinlich nicht der Erzeuger von experimentell beobachteten ripple-artigen Oszillationen sind. Zusammengenommen zeigen meine Resultate, dass schnelle Gap Junction-Kopplung von Interneuronen die Entstehung von ripples begünstigt und somit SWRs unterstützt, welche einen wichtigen Beitrag zur Bildung unserers Gedächtnisses leisten. / A unique experimental observation that opens ways for a holistic, bottom-up theory for memory generation are sharp-wave ripples (SWRs). SWRs are generated in local neuronal networks and are important for memory consolidation. SWRs are prominent features of the extracellular field potentials in the mammalian hippocampus that occur during rest and sleep; they are characterized by sharp waves, ≈ 100 ms long voltage deflections, that are accompanied by ripples, i.e., 110–250 Hz oscillations. Recent experiments support the view that ripples are clocked by recurrent networks of inhibitory interneurons (INT-INT), which are likely constituted by networks of parvalbumin-positive basket cells (PV+BCs). PV+BCs are not only recurrently coupled by inhibition but also by gap junctions (GJs). In this thesis, I investigate the specific function of interneuronal GJs in hippocampal ripples. Consequently, I simulate INT-INT networks and demonstrate that gap junctions increase the neuronal synchrony and firing rates during ripple oscillations, while the ripple frequency is only affected mildly. I further show that GJs only have these supporting effects on ripples when they are sufficiently fast (≈< 0.5 ms), which requires proximal GJ coupling (≈< 100 µm). Additionally, I find that gap junctions increase the oscillatory power of ripple oscillations and by this means reduce the minimal network size required for INT-INT networks to generate ripple oscillations. Finally, I demonstrate that exclusively GJ-coupled INT-INT networks can oscillate at ripple frequency, however, are unlikely the generator of experimentally observed ripple-like oscillations. In sum, my results show that fast interneuronal gap junction coupling promotes the emergence of ripples and hereby supports SWRs, which are important for the formation of memory.

Der Hippokampus spielt eine wichtige Rolle bei der Erfassung, Festigung und dem Wiederabrufen von Gedächtnisinhalten. Diese Prozesse werden von Oszillationen begleitet, die synchronisierte neuronale Aktivität wiederspiegeln. Der erste Teil dieser Arbeit konzentriert sich auf ‘ripples’, eine schnell schwingende Netzwerkaktivität, die an der Festigung von Gedächtnisinhalten beteiligt ist. Das Subikulum ist eine der Hauptausgangsstationen des Hippokampus und überträgt Informationen zu Zielregionen außerhalb dieser Region. Um dies besser zu verstehen, habe ich hier die Eigenschaften von subikulären Pyramidenzellen und deren Regulierung während ripples untersucht. Es zeigte sich, dass eine Untergruppe von Zellen, burst (in Salven) feuernde Zellen, ihre Aktivität erhöht, während eine zweite Untergruppe, regulär feuerende Zellen, ihre Aktivitaet während ripples vermindert. Ferner ist bei regulär feuernden Zellen das Verhältnis zwischen Inhibition und Exzitation höher als bei burst feuernden Zellen. Zusammen mit Erkenntnissen aus früheren Studien lassen diese Ergebnisse vermuten, dass Information während ripples hauptsächlich zu Zielregionen der burst feuernden Zellen geleitet wird. Neben Pyramidenzellen beherbergt der Hippokampus auch eine Vielzahl verschiedener Interneurone. Im zweiten Teil dieser Arbeit habe ich O-LM Interneurone der hippokampalen Region CA1 untersucht. Diese spielen eine wichtige Rolle bei der Kontrolle von Eingängen aus dem entorhinalen Kortex. Wir konnten zeigen, dass die exzitatorische Übertragung auf O-LM Interneurone durch Serotonin, einem von den Raphe-Kernen ausgeschütteten Neuromodulator, vermindert wird. Dies geschieht durch einen präsynaptischen Mechanismus, der wahrscheinlich eine Verminderung des Kalziumeinstroms in präsynaptische Endigungen umfasst. Eine Verminderung der Aktivität von O-LM Interneuronen durch Serotonin könnte die synaptische Übertragung von Signalen aus dem entorhinalen Kortex auf CA1 Pyramidenzelldendriten erleichtern. / The hippocampus plays an important role in the acquisition, consolidation and retrieval of memory. These processes are accompanied by hippocampal oscillations, which reflect synchronized neuronal activity. The first part of this thesis focuses on ripples, a fast oscillatory activity which is involved in memory consolidation. The subiculum as one of the main output areas of the hippocampus is ideally suited to mediate information transfer to extrahippocampal targets. Here I investigated the properties of subicular pyramidal cells and their modulation during ripples. I found that a subset of subicular pyramidal cells increases its firing rate during ripples whereas another subset decreases its firing rate. Furthermore I was able to identify a correlate between modulation and cell subtype: burst firing cells increased their firing rate, and regular firing cells decreased their firing rate. We could further show that regular firing cells receive a higher ratio of inhibition to excitation as compared to burst firing cells. Together with earlier work, these results suggest that information transferred during ripples is likely to be routed preferentially to target regions of the burst firing subtype. Besides pyramidal cells, the hippocampus hosts a variety of interneuron types. The second part of this thesis focuses on GABAergic O-LM interneurons of hippocampal area CA1, which play an important role in controlling input from the entorhinal cortex. We could show that excitatory transmission from local pyramidal cells onto O-LM interneurons is decreased by serotonin, a neuromodulator released from the midbrain raphe nuclei. This modulation is mediated by a presynaptic mechanism and is likely to involve a decrease in calcium influx into presynaptic terminals. We conclude that serotonin, by decreasing O-LM output, might release fibers from entorhinal cortex impinging onto CA1 pyramidal cell dendrites from inhibition.

Hippokampale Sharp Wave-Ripples (SWRs) sind elektrografische Ereignisse, die für die Konsolidierung von Erinnerungen eine Rolle spielen. Eine SWR ist durch eine schnelle Oszillation (>90 Hz, ''ripple'') charakterisiert, die sich mit der langsameren ''sharp wave'' ( / Hippocampal sharp wave-ripples (SWRs) are electrographic events that have been implicated in memory consolidation. A SWR is characterized by a fast (> 90 Hz) oscillation, the ripple, superimposed on a slow (< 30 Hz) sharp wave. In vivo, the fast component can express frequencies either in the ripple range (140-200 Hz) or fast-gamma range (90-140 Hz). Episodes in both bands exhibit intra-ripple frequency accommodation (IFA). In vitro, ripples are frequency-resistant to GABA modulators. These features constrain the type of mechanisms underlying the generation of the fast component. A prominent hypothesis proposes that a recurrent network of parvalbumin-immunoreactive basket cells (PV+BC) is responsible of setting the ripple frequency. The focus of the present thesis is on testing to which extent the PV+BC network can account for the aforementioned features of SWRs, which remain unexplained. Here, I simulated and analyzed a physiologically constrained in silico model of the PV+BC network in CA1 under different conditions of excitatory drive. The response of the network to transient excitation exhibits both IFA in the ripple band and frequency resistance to GABA modulators. The expression of IFA in the fast gamma band requires the involvement of pyramidal cells in a closed loop with the PV+BC network. The model predicts a peculiar relationship between the instantaneous frequency of ripples and the time course of the excitatory input to CA1. This prediction was confirmed in an in vitro model of SWRs. Additionally, I study the involvement of oriens lacunosum-moleculare interneurons (O-LM) during SWRs in vitro. I characterize the excitatory currents received by O-LM cells during SWRs and investigate the factors that determine their recruitment.

Die Aktivität des Hippocampus im Tiefschlaf ist geprägt durch sharp wave-ripple Komplexe (SPW-R): kurze (50–100 ms) Phasen mit erhöhter neuronaler Aktivität, moduliert durch eine schnelle “Ripple”-Oszillation (140–220 Hz). SPW-R werden mit Gedächtniskonsolidierung in Verbindung gebracht, aber ihr Ursprung ist unklar. Sowohl exzitatorische als auch inhibitorische Neuronpopulationen könnten die Oszillation generieren. Diese Arbeit analysiert Ripple-Oszillationen in inhibitorischen Netzwerkmodellen auf mikro-, meso- und makroskopischer Ebene und zeigt auf, wie die Ripple-Dynamik von exzitatorischem Input, inhibitorischer Kopplungsstärke und dem Rauschmodell abhängt. Zuerst wird ein stark getriebenes Interneuron-Netzwerk mit starker, verzögerter Kopplung analysiert. Es wird eine Theorie entwickelt, die die Drift-bedingte Feuerdynamik im Mean-field Grenzfall beschreibt. Die Ripple-Frequenz und die Dynamik der Membranpotentiale werden analytisch als Funktion des Inputs und der Netzwerkparameter angenähert. Die Theorie erklärt, warum die Ripple-Frequenz im Verlauf eines SPW-R-Ereignisses sinkt (intra-ripple frequency accommodation, IFA). Weiterhin zeigt eine numerische Analyse, dass ein alternatives Modell, basierend auf einem transienten Störungseffekt in einer schwach gekoppelten Interneuron-Population, unter biologisch plausiblen Annahmen keine IFA erzeugen kann. IFA kann somit zur Modellauswahl beitragen und deutet auf starke, verzögerte inhibitorische Kopplung als plausiblen Mechanismus hin. Schließlich wird die Anwendbarkeit eines kürzlich entwickelten mesoskopischen Ansatzes für die effiziente Simulation von Ripples in endlich großen Netzwerken geprüft. Dabei wird das Rauschen nicht im Input der Neurone beschrieben, sondern als stochastisches Feuern entsprechend einer Hazard-Rate. Es wird untersucht, wie die Wahl des Hazards die dynamische Suszeptibilität einzelner Neurone, und damit die Ripple-Dynamik in rekurrenten Interneuron-Netzwerken beeinflusst. / Hippocampal activity during sleep or rest is characterized by sharp wave-ripples (SPW-Rs): transient (50–100 ms) periods of elevated neuronal activity modulated by a fast oscillation — the ripple (140–220 Hz). SPW-Rs have been linked to memory consolidation, but their generation mechanism remains unclear. Multiple potential mechanisms have been proposed, relying on excitation and/or inhibition as the main pacemaker. This thesis analyzes ripple oscillations in inhibitory network models at micro-, meso-, and macroscopic scales and elucidates how the ripple dynamics depends on the excitatory drive, inhibitory coupling strength, and the noise model. First, an interneuron network under strong drive and strong coupling with delay is analyzed. A theory is developed that captures the drift-mediated spiking dynamics in the mean-field limit. The ripple frequency as well as the underlying dynamics of the membrane potential distribution are approximated analytically as a function of the external drive and network parameters. The theory explains why the ripple frequency decreases over the course of an event (intra-ripple frequency accommodation, IFA). Furthermore, numerical analysis shows that an alternative inhibitory ripple model, based on a transient ringing effect in a weakly coupled interneuron population, cannot account for IFA under biologically realistic assumptions. IFA can thus guide model selection and provides new support for strong, delayed inhibitory coupling as a mechanism for ripple generation. Finally, a recently proposed mesoscopic integration scheme is tested as a potential tool for the efficient numerical simulation of ripple dynamics in networks of finite size. This approach requires a switch of the noise model, from noisy input to stochastic output spiking mediated by a hazard function. It is demonstrated how the choice of a hazard function affects the linear response of single neurons and therefore the ripple dynamics in a recurrent interneuron network.

Alors que le rat apprend à chercher de multiples sources de nourriture ou d'eau, des processus d'apprentissage de séquences spatiales et de rejeu ont lieu dans l'hippocampe et le cortex préfrontal.Des études récentes (De Jong et al. 2011; Carr, Jadhav, and Frank 2011) mettent en évidence que la navigation spatiale dans l'hippocampe de rat implique le rejeu de l'activation de cellules de lieu durant les étant de sommeil et d'éveil en générant des petites sous séquences contigues d'activation de cellules de lieu cohérentes entre elles. Ces fragments sont observés en particulier lors d'évènements sharp wave ripple (SPWR).Les phénomènes de rejeu lors du sommeil dans le contexte de la consolidation de la mémoire à long terme ont beaucoup attiré l'attention. Ici nous nous focalisons sur le rôle du rejeu pendant l'état d'éveil.Nous formulons l'hypothèse que ces fragments peuvent être utilisés par le cortex préfrontal pour réaliser une tâche d'apprentissage spatial comprenant plusieurs buts.Nous proposons de développer un modèle intégré d'hippocampe et de cortex préfrontal capable de générer des séquences d'activation de cellules de lieu.Le travail collaboratif proposé prolonge les travaux existants sur un modèle de cognition spatiale pour des tâches orientés but plus simples (Barrera and Weitzenfeld 2008; Barrera et al. 2015) avec un nouveau modèle basé sur le rejeu pour la formation de mémoire dans l'hippocampe et l'apprentissage et génération de séquences spatiales par le cortex préfrontal.En contraste avec les travaux existants d'apprentissage de séquence qui repose sur des règles d'apprentissage sophistiquées, nous proposons d'utiliser un paradigme calculatoire appelé calcul par réservoir (Dominey 1995) dans lequel des groupes importants de neurones artificiels dont la connectivité est fixe traitent dynamiquement l'information au travers de réverbérations. Ce modèle calculatoire par réservoir consolide les fragments de séquence d'activations de cellule de lieu en une plus grande séquence qui pourra être rappelée elle-même par des fragments de séquence.Le travail proposé est supposé contribuer à une nouvelle compréhension du rôle du phénomène de rejeu dans l'acquisition de la mémoire dans une tâche complexe liée à l'apprentissage de séquence.Cette compréhension opérationnelle sera mise à profit et testée dans l'architecture cognitive incarnée d'un robot mobile selon l'approche animat (Wilson 1991) [etc...] / As rats learn to search for multiple sources of food or water in a complex environment, processes of spatial sequence learning and recall in the hippocampus (HC) and prefrontal cortex (PFC) are taking place. Recent studies (De Jong et al. 2011; Carr, Jadhav, and Frank 2011) show that spatial navigation in the rat hippocampus involves the replay of place-cell firing during awake and sleep states generating small contiguous subsequences of spatially related place-cell activations that we will call "snippets". These "snippets" occur primarily during sharp-wave-ripple (SPWR) events. Much attention has been paid to replay during sleep in the context of long-term memory consolidation. Here we focus on the role of replay during the awake state, as the animal is learning across multiple trials.We hypothesize that these "snippets" can be used by the PFC to achieve multi-goal spatial sequence learning.We propose to develop an integrated model of HC and PFC that is able to form place-cell activation sequences based on snippet replay. The proposed collaborative research will extend existing spatial cognition model for simpler goal-oriented tasks (Barrera and Weitzenfeld 2008; Barrera et al. 2015) with a new replay-driven model for memory formation in the hippocampus and spatial sequence learning and recall in PFC.In contrast to existing work on sequence learning that relies heavily on sophisticated learning algorithms and synaptic modification rules, we propose to use an alternative computational framework known as reservoir computing (Dominey 1995) in which large pools of prewired neural elements process information dynamically through reverberations. This reservoir computational model will consolidate snippets into larger place-cell activation sequences that may be later recalled by subsets of the original sequences.The proposed work is expected to generate a new understanding of the role of replay in memory acquisition in complex tasks such as sequence learning. That operational understanding will be leveraged and tested on a an embodied-cognitive real-time framework of a robot, related to the animat paradigm (Wilson 1991) [etc...]

A growing interest for Cannabidiol (CBD), a component of Cannabis Sativa, has occurred over the past years. The medical potential of the component is yet to be better characterized, as its effects on sleep, and in particular memory, are to date not well understood or consistently characterized. This master thesis project focuses on analysing the effect of CBD on an anaesthesia-induced sleep-like state in rats, and its effects on the hippocampal sharp-wave-ripples, which have been shown to be associated with memory replay during sleep, and hence system consolidation. The hippocampus and prefrontal cortex, the two structures involved in memory consolidation, were recorded in 19 rats, split in two groups (CBD and vehicle). From these recordings, an automated sleep scorer using principal component analysis was developed to obtain the animals’ hypnograms, which were analysed to study sleep-like structure. From the recordings of the hippocampal pyramidal layer, and an additionnal layer deeper under it, respectively ripples and sharp waves were detected in all animals, and characterized for each group. We observed and demonstrated that CBD changes the sleep-like structure by shortening both REM and NREM bouts, resulting in an increase in transitions between both states. Additionally, we observed that, although ripples are not significantly different between both groups, sharp waves tend to be smaller among CBD animals. Lastly we noticed that both sharp wave and ripple activity, after increasing upon transition to NREM, decreases as the bout last. This finding suggests that vehicle animals, who have longer bouts and less transitions, would display less sharp wave and ripple activity, although we found no significant difference in the amount of both brain events. This paradox suggests that there is still more to characterize in order to understand if CBD enhances or not memory consolidation. In sum, CBD changes anaesthesia-induced sleep by shortening the duration of both NREM and REM bouts, resulting in an increase in transitions between both state. As for sleep events, sharp waves appeared shorter among CBD animals, although the same difference was not observed for ripples. Finally, sharp wave and ripple activity appear to peak upon transition from REM to NREM sleep, and decreases as the NREM bout lasts longer, however, no effect of CBD on this observation was highlighted.