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© Ruggiero Francavilla, 2019

Cell types, connectivity and behavior-dependent

recruitment of vasoactive intestinal peptide-expressing

interneurons in the mouse hippocampus

Thèse

Ruggiero Francavilla

Doctorat en biochimie

Philosophiæ doctor (Ph. D.)

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Cell types, connectivity and behavior-dependent

recruitment of vasoactive intestinal peptide-expressing

interneurons in the mouse hippocampus.

Thèse

Ruggiero Francavilla

Sous la direction de :

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Résumé

L'inhibition joue un rôle important dans l'organisation spatio-temporelle de l’activité synchronisée des réseaux, ce qui est important pour la performance cognitive. Cependant, la compréhension de l'inhibition corticale a été une tâche difficile, car ce processus est exécuté par une grande diversité de neurones GABAergiques locaux et à longue portée (LRP) (Soltesz, 2006). Dans l'hippocampe, les interneurones spécifiques aux interneurones (IS) exprimant le peptide vasoactif intestinal (VIP+) jouent un rôle de désinhibition local et sont divisés en deux groupes: les interneurones spécifiques de type 2 (IS2) et de type 3 (IS3). Récemment, une nouvelle cellule VIP+ à projection longue portée (VIP-LRP) avec un soma située dans le stratum oriens / alveus (O/A) de la corne d’Ammon (CA1) de l'hippocampe et dont l'axone projette vers le subiculum (SUB) a été découverte.

Comme les cibles postsynaptiques et la fonction des cellules GABAergiques à projection sont inconnues pendant différents états chez des animaux éveillés, nous visions à déterminer les cibles des VIP-LRP dans le CA1 et le SUB. J'ai d'abord effectué une libération de glutamate par stimulation à deux photons en combinant la photoactivation des cellules VIP-GFP+ dans le O/A du CA1 et l’enregistrement par patch-clamp de leurs cibles. Nous avons constaté que les VIP-LRP agissent contactent différentes classes d'interneurones dans le O/A et le stratum radiatum (RAD). Cependant, distalement dans le SUB, ils étaient en contact avec cellules pyramidals (PCs) et les interneurones. Ensuite, pour étudier le rôle fonctionnel de ces cellules, nous avons effectué de l’imagerie calcique (Ca2 +) à deux photons in vivo de l'activité des interneurones VIP+ chez des souris fixées par la tête sur un tapis roulant. Nous avons constaté que les cellules VIP-LRPs étaient recrutées pendant les périodes d'immobilité et réduisent leur activité au cours des épisodes thêta lors de la locomotion. Avec ces résultats, nous pouvons considérer les VIP-LRPs comme des régulateurs clés du processus mnémonique, tels que la récupération de la mémoire nécessitant une cohérence entre le CA1 et le SUB lors d'états calmes (Jackson et al., 2011; Roy et al., 2017).

Dans l'hippocampe, on sait peu de choses sur l'implication des cellules IS3 dans les comportements dépendant de l'hippocampe tels que la mémoire spatiale et l'anxiété. En utilisant un water T-maze (WTM) pour étudier l'apprentissage spatial, nous avons constaté que pendant l’extinction de ces cellules, la souris offrait sa pire performance. Dans le contexte de la mémoire, la sous-unité α5 des GABAAR (α5-GABAAR) a été considéré comme l'une des cibles pharmacologiques les plus intéressantes, car son blocage améliore la mémoire dépendante de l'hippocampe (Atack et al., 2006; Caraiscos et al., 2004; Collinson et al., 2002). Le blocage de cette sous-unité chez des souris effectuant un WTM a sauvé la perte de mémoire induite par la désactivation de l'entrée du signal des VIP+ confirmant l'implication de l'inhibition tonique dans la régulation de l'apprentissage spatial. Cependant, cette amélioration des performances cognitives est associée à une augmentation de l'anxiété, indiquant que l’activité de ces cellules peut être impliquée dans la régulation de l'anxiété.

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Finalement, les déficits de mémoire et le déclin cognitif sont considérés comme la marque du vieillissement du cerveau. Jusqu’à présent, il était reporté que les interneurones positifs à la calrétinine (CR) figuraient parmi les premières cibles de modèles de souris associés à l’âge tel que la maladie d'Alzheimer (AD) (Baglietto-Vargas et al., 2010). Compte tenu de ce qui précède, j'ai effectué des enregistrements par patch-clamp d’IS3s pour étudier leur implication dans le déclin de la mémoire lié à l'âge. Les résultats montrent que la morphologie de ces cellules est préservée pendant le vieillissement, mais montre aussi une durée plus longue des potentiels d’action et une réduction du taux de décharge. Ces modifications entraînent une augmentation de l'inhibition des interneurones du O/A ciblés par les cellules IS3. Cela pourrait expliquer l'hyperactivité des PCs associée à une déficience cognitive et une augmentation du risque pour l’AD (Bakker et al., 2012; Busche et al., 2012; El-Hayek et al., 2013).

En conclusion, cette étude a révélé de nouvelles propriétés et motifs d’activités des neurones VIP+ de l’hippocampe pendant des états comportementaux spécifiques durant toute la vie de l’animal. Cela devrait être important pour comprendre les mécanismes de l’apprentissage et la mémoire ainsi que les déficiences cognitive pendant le vieillissement.

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Summary

Inhibition plays an important role in the spatio-temporal organization of synchronized network activity, which is important for cognitive performance. However, understanding cortical inhibition has been a challenging task as it is executed through a large diversity of local and long-range projecting (LRP) GABAergic neurons (Soltesz, 2006). In the hippocampus, the interneuron-selective (IS) vasoactive intestinal peptide (VIP)-expressing (VIP+) interneurons play a role of local disinhibition and are subdivided into 2 groups: type 2 and type 3 interneuron-specific (IS2, IS3) cells. Recently, a novel long-range projecting VIP+ cell (VIP-LRP) with the soma located in the hippocampal cornu ammonis (CA1) stratum oriens/alveus (O/A) and axon innervating CA1 and the subiculum (SUB) has been discovered.

Since little is known about the postsynaptic targets and function of GABAergic projecting cells during different network states in awake animals, we aimed to determine the targets of VIP-LRP cells in CA1 and SUB. I first performed single-cell two-photon glutamate uncaging-based mapping of connections by combining the photoactivation of CA1 O/A VIP-GFP+ cells and patch-clamp recordings of interneuron and PCs targets. We found that VIP-LRP cells locally act as disinhibitory cells contacting different classes of inhibitory interneurons, either in the O/A or in the stratum radiatum (RAD). However distally in the SUB, they were contacting both pyramidal cells (PCs) and interneurons. Next, to study the functional role of these cells we performed in vivo two-photon calcium (Ca2+) imaging

of VIP+ interneuron activity in head-restrained awake mice running on a treadmillI. We found that VIP-LRP cells were recruited during immobility periods and were behaving as theta-off cells, decreasing their activity during theta-run episodes. Based on these findings we can consider VIP-LRPs as important key regulator of mnemonic process such as memory retrieval requiring coherency between hippocampal CA1 and SUB areas during quiet states (Jackson et al., 2011; Roy et al., 2017).

Furthermore, in the hippocampal CA1 area, VIP+ IS interneurons, in particular IS3 cells have been characterized intensively based on their cell identity, physiological properties and connectivity pattern (Chamberland et al., 2010; Tyan et al., 2014). However, differently from neocortical VIP+ interneurons very little is known about the involvement of IS3 in hippocampus-dependent behaviors, such as spatial memory and anxiety. Using a water T-maze (WTM) to investigate egocentric and allocentric spatial learning, we found that silencing VIP+ cells worsens mouse performance. This data indicated clearly the involvement of hippocampal VIP+ IS cell in hippocampus-dependent memory tasks. In the context of memory, the alpha5 subunit-containing GABAA receptor (α5-GABAAR) has

been seen as one of the most interesting pharmacological targets, as blocking this subunit improves hippocampus-dependent memory (Atack et al., 2006; Caraiscos et al., 2004; Collinson et al., 2002). Blocking the α5-GABAAR subunit in mice performing WTM

successfully rescued the memory impairment induced by silencing of VIP+ input, confirming the involvement of tonic inhibition in the regulation of spatial learning. However this improvement in cognitive performance is associated with an increase in anxiety,

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indicating that phasic inhibition by the α5-GABAAR-containing VIP+ inputs onto CA1

interneurons may be involved in regulating anxiety.

Finally, memory deficits and cognitive decline are considered a hallmark of the aging brain, with neocortical circuits being affected the most during age-dependent functional decline (Murman, 2015). So far, it has been reported that calretinin (CR)-positive IS interneurons were among the early targets in mouse models of age-related disorders, such as Alzheimer’s disease (AD) (Baglietto-Vargas et al., 2010). Considering the above, I performed patch-clamp recordings from IS3 cells to study their involvement in age-related memory decline. The results showed that, while the morphology of these cells was preserved during aging, functional remodelling occurred, such as a longer duration of the action potential as well as reduction in the firing rate. These modifications led to an increase inhibitory drive onto O/A interneurons targeted by IS3 cells. This could account for the hyperactivity of PCs associated with cognitive impairment and could increase the risk for AD development (Bakker et al., 2012; Busche et al., 2012; El-Hayek et al., 2013). In conclusion, this study reveals new properties and activity patterns of hippocampal VIP+ neurons during specific behavioral states and across the animal lifespan, which should be important for understanding the circuit mechanisms of learning and memory, as well as cognitive impairments during aging.

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vii Table of Contents Résumé ... iii Summary ... v List of figures ... x Acknowledgements ... xiii Preface ...xv Introduction ... 1

Hippocampus in memory formation and consolidation ... 1

Neuronal substrates of memory formation, retrieval, and recalling ... 1

Gamma rhythm in the hippocampus ... 11

Hippocampal sharp-wave associated ripples ... 12

The hippocampal Large Irregular Activity (LIA) ... 15

Neuronal substrates of hippocampal oscillatory patterns... 19

Interneurons of the hippocampus ... 24

Differential involvement of specific interneuron subtypes in network oscillations. .. 35

Disinhibition as a powerful mechanism for controlling the activity in neural circuits and memory formation and consolidation. ... 47

Disinhibitory cell types ... 47

Connectivity and functional outcome for pyramidal cells ... 50

Functional role of VIP interneurons in vivo ... 57

Disinhibition in spatial memory and anxiety ... 63

Inhibitory mechanisms in age-related cognitive decline ... 67

Age-related structural changes ... 67

Aging and neuronal vulnerability ... 67

Morphological changes associated with normal aging ... 70

Functional remodelling... 72

Changes in intrinsic excitability ... 72

Age-related changes in the biophysical properties of neurons ... 76

Functional plasticity and reorganization of local circuits associated with age-related cognitive deficits ... 80

Specific objectives of study ... 83

Chapter 1 Integrated article 1: Connectivity and network state-dependent recruitment of long-range VIP-GABAergic neurons in the mouse hippocampus ... 87

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viii Abstract ... 87 Introduction ... 88 Results ... 90 Discussion... 99 Methods ... 102 Figure Legends ... 115 Figures ... 121

Supplementary Figures and Tables ... 128

References ... 138

Acknowledgements ... 143

Chapter 2 Integrated article 2: Input-specific synaptic location and function of the alpha5 GABAA receptor subunit in the mouse CA1 hippocampal neurons ... 144

Résumé... 144

Abstract ... 145

Introduction ... 146

Materials and Methods ... 147

Results ... 153

Discussion... 160

Figure Legends ... 166

References ... 170

Figures and tables ... 181

Acknowledgments ... 187

Chapter 3 Integrated article 3: Functional remodelling of hippocampal VIP disinhibitory circuits during aging ... 188

Résumé... 188 Abstract ... 188 Introduction ... 189 Methods ... 191 Results ... 198 Discussion... 205 Disclosure ... 208 Acknowledgments ... 209

Figures and legends ... 210

Chapter 4: Discussion ... 223

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2. VIP-expressing interneurons play an important role in spatial memory and anxiety

... 226

Perspectives ... 229

Conclusion ... 232

Bibliography ... 235

Appendices ... 261

Article 4: Coordination of dendritic inhibition through local disinhibitory circuits ... 261

Résumé ... 261

Abstract: ... 261

Introduction ... 262

Properties and connectivity of is3 cells ... 262

Morphological and neurochemical features ... 262

Physiological properties ... 263

Connectivity ... 263

Properties of IS3 synapses ... 263

Comparison with VIP+ interneurons in the neocortex ... 263

Functional role of disinhibitory circuits ... 264

Acknowledgments ... 265

References ... 266

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List of figures

Figure 1 Anatomical location of hippocampus in the human, monkey and rodents brains and anatomy of the hippocampal memory system. ... 5 Figure 2 Hippocampal removal or damage cause memory deficits in human and rodent brains. ... 6 Figure 3 Rhythms of hippocampal network which can be important for spatial memory and navigation. ... 18 Figure 4 Hippocampal CA1 pyramidal cells are composed of deep and superficial cells, based on their neurochemical, morphological, physiological, and functional properties. ... 23 Figure 5 Three types of pyramidal cell are accompanied by at least 21 classes of interneuron in the hippocampal CA1 area. ... 33 Figure 6 Some GABAergic cells are located in different hippocampal areas and send long-range axonal projections (LRP) to distant areas. ... 34 Figure 7 Spatiotemporal interaction between pyramidal cells and several classes of interneurons during network oscillations, ... 43 Figure 8 Behavior-dependent activity patterns of subicular-projecting GABAergic neurons. Firing patterns of a trilaminar cell recorded in vivo during ripples and theta. ... 46 Figure 9 Interneuron-selective (IS) interneurons are GABAergic cells specialized in the selective innervation of GABAergic interneurons. ... 54 Figure 10 IS3 cells provide dendritic inhibition to different subtypes of CA1 O/A interneurons. ... 55 Figure 11 The region-specific functions of VIP+ IS cells. Effect of light stimulation on OLM interneuron firing. ... 56 Figure 12 VIP+ cells in the neocortex are active during sensory processing and movement. VIP intenreurons generate disinhibition in auditory cortex (ACx) and medial prefrontal cortex (mPFC) of awake mice. ... 62 Figure 13 VIP+ cells are involved in auditory fear learning and spatial learning... 66 Figure 14 Age-related neuronal loss is limited to specific populations of GABAergic neurons. Aging reduces the number of GABAergic interneurons in CA1. ... 69 Figure 15 Aging is associated with a variation of dendritic morphology in layer 3 pyramidal neurons. ... 71 Figure 16 Electrophysiological changes in layer 2/3 pyramidal cells in the prefrontal cortex in aged monkeys. ... 75 Figure 17 KvDR and KvA are involved in the age-related modification of AP duration in PCs.

... 79 Figure 18 Excitatory/inhibitory imbalance as a substrate of aging-associated cognitive impairment. ... 82

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Abbreviations

α5-GABAAR alpha5 GABAA receptor subunit

AAC Axo-axonic cells

AD Alzheimer’s disease

ADI Apical dendrite-targeting interneurons

AP Action potential

BC Basket cell

BIS Bistratified cell

BLA Basolateral amygdala

CA Cornu ammonis CB Calbindin CCK Cholecystokinin CFC Contextual fear-conditioning ChR2 Channelrhodopsin 2 CR Calretinin

COUP-TFII COUP transcription factor 2

DG Dentate gyrus

EC Entorhinal cortex

EEG Electroencephalography

GABA Gamma-aminobutyric acid

H-SUB Hippocampal cell projecting to the subiculum

IS Interneuron-specific

IvC Ivy cells

Kv Voltage-gated potassium channels

KvA A-type voltage–dependent potassium channels

KvDR Delayed rectifier voltage-dependent potassium channel

LEC Lateral entorhinal cortex LFP Local field potential

LIA Large irregular activity

LM Stratum lacunosum-moleculare

LRP Long-range projecting

LTP Long-term potentiation

M2R Muscarinic receptor type 2 MEC Medial entorhinal cortex

mGluR Metabotropic glutamate receptor

Nav Voltage-gated sodium channel

NGFC Neurogliaform cell

NMDAR N-methyl-D-aspartate receptor

NGFC Neurogliaform cell

nNOS Neuronal nitric oxide synthase NPY Neuropeptide Y

O/A Stratum oriens/alveus

O-LM Oriens lacunosum-moleculare interneuron

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Penk Proenkephalin

PC Pyramidal cell

PPA Perforant path-associated cell

PV Parvalbumin

PVBC Basket cell expressing PV

PYR Stratum pyramidale

RAD Stratum radiatum

RELN Reelin

REM Rapid eye movements

SCA Schaffer collateral-associated cell

SO Stratum oriens

SOM Somatostatin

SPW-R Sharp wave-ripple

SUB Subiculum

VIP Vasoactive intestinal peptide

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Acknowledgements

First, I would like to express my gratitude to my supervisor Lisa Topolnik. During these 5 years spent in her lab, she was my driving fource and inspiration source, helping me to increase my knowledge in the field on neuroscience with regard to neurophysiology and neuroanatomy. After these 5 years spent in Topolnik’s lab I feel proud of the work produced together with my Supervisor and the team who worked with me in this time. Also, she helped me in every experimental design and planning being always present also in the moment of analysis related to each of the projects in which I was involved. Despite stressfull situations related to unsuccessfull days, she was always patient providing me good advices to overcome these situations and preparing me for each step of my preparation requiring an intense follow-up such as writing of articles, conceptualization of research and realization of scientific figures. I will never forget all the help I received from her and I will keep in my mind as an ispiration source for my future carrier in science.

Second I would like to thank all external collaborators, including Peter Somogyi, Alexandre Guet-McCreight, Frances Skinner. I honestely think that they amazingly contribute to quality of research we produce during these 5 years. I also would like to thank Matthieu Guitton for helpful advices on the behaviour analysis, and Frédéric Calon who was involved in the aging project in part related to age-related disorder providing me with 3xTg mice.

Next, I would like to thank my parents as without their continuous emotional and finantial support I will never be able to complete my PhD studies in Quebec. I would like to thank all my family as they were always present even if they were very far from, I feel their presence everyday during my life here in Quebec. Family was, is and will be the solid foundation for building my life and to go on in my carrier as man and scientist.

Finally, I want to say my great thank to my current and previous lab collegues including Olivier Camiré, Xiao Luo, Sona Amalyan, Linda Suzanne David, Vincent Villette, Elise Magnin, Étienne Gervais, Dimitry Topolnik, Beatrice Marino and Alfonsa Zamora

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Moratalla. In particular, I would like to thank Vincent for the trainining during mice surgery and 2-photon Ca2+ imaging, Olivier for all the technical help during patch-clamp

experiments, and Dimitry for all the training related to intracardiac perfusion, patch-clamp technique and slice preparation. Also, I want to thank Xiao as well as Olivier, as we worked together for the longest time in the lab publishing many exciting articles as co-authors.

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Preface

I included four articles in my thesis. The first three articles represent my major works in the lab. They are integrated in the main test as chapter 2, 3 and 4. I also contributed as first author to the review article (article 4) attached to the appendix. The information for each article is listed below:

Integrated article 1: Connectivity and network state-dependent recruitment of long-range VIP-GABAergic neurons in the mouse hippocampus

Publication status: Received: 15 February 2018; accepted: 18 October 2018; published

online: 28 November 2018 in the journal Nature Communications. Author status: First

author.

Authors : Ruggiero Francavilla1, 2, 4, Vincent Villette1, 2, 4, Xiao Luo1, 2, Simon

Chamberland2, Einer Muñoz-Pino1, 2, Olivier Camiré1, 2, Kristina Wagner3, Viktor Kis3,

Peter Somogyi3, Lisa Topolnik1, 2, * Affiliations of each author:

1 Neuroscience Axis, CHU de Québec Research Center – Université Laval; Québec, PQ, G1V 4G2, Canada

2 Dept. Biochemistry, Microbiology and Bio-informatics, Université Laval, Québec, PQ,

G1V 0A6,Canada

3 Dept. Pharmacology, Oxford University, Oxford, OX1 3QT, UK 4 Co-first author

Author Contributions:

Conceptualization, L.T.; Methodology, R.F., V.V., X.L., E.M., P.S. and L.T.;

Investigation, R.F., V.V., X.L., S.C., E.M., O.C., K.W., V.K., P.S. and L.T.; Writing – Original Draft, R.F. and L.T.; Writing – Review & Editing, R.F., V.V., X.L., S.C., O.C., P.S. and L.T.; Funding Acquisition, P.S. and L.T.; Supervision, P.S. and L.T.

The authors declare no conflict of interest.

Correspondence should be addressed to:

Dr. Lisa Topolnik Lisa.topolnik@bcm.ulaval.ca

Integrated article 2: Input-specific synaptic location and function of the alpha5 GABAA receptor subunit in the mouse CA1 hippocampal neurons.

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Publication status: Received: 28 February 2018; accepted: 30 October 2018; published

online: 6 December 2018 in the journal Journal of Neuroscience. Author status: Co-First author.

Authors: Elise Magnin1, 2, 3, Ruggiero Francavilla1, 2, 3, Sona Amalyan1, 2, 3, Etienne Gervais1, 2, Linda Suzanne David2, Xiao Luo1, 2 , Lisa Topolnik1, 2.

Affiliations of each author: 1

Dept. Biochemistry, Microbiology and Bio-informatics, Université Laval, Québec, PQ,

G1V 0A6, Canada 2 Neuroscience Axis, CHU de Québec Research Center – Université Laval; Québec, PQ, G1V 4G2, Canada; 3Co-first author.

Contribution: E.M., R.F., S.A., E.G., L.S.D., X.L., and L.T. performed research; E.M.,

R.F., S.A., E.G., L.S.D., and L.T. analyzed data; E.M., R.F., and S.A. wrote the first draft of the paper; R.F., S.A., E.G., and L.T. edited the paper; L.T. designed research.

Correspondence: Dr. Lisa Topolnik Lisa.topolnik@bcm.ulaval.ca

Integrated article 3: Functional remodelling of hippocampal VIP disinhibitory circuits during aging.

Publication status: Submitted to the journal Neurobiology of Aging on 17th January,

2019.

Authors: Ruggiero Francavilla 1,2 , Alexandre Guet-McCreight3,4 , Frances K Skinner3,5,

Lisa Topolnik1,2 *

Affiliations of each author: 1Dept. Biochemistry, Microbiology and Bio-informatics,

Université Laval, Québec, PQ, G1V 0A6, Canada; 2Neuroscience Axis, CHU de Québec

Research Center – Université Laval; Québec, PQ, G1V 4G2, Canada; 3Krembil Research

Institute, University Health Network, Toronto, ON, Canada; 4Department of Physiology,

University of Toronto, Toronto, ON, Canada; 5Departments of Medicine (Neurology) and

Physiology, University of Toronto, Toronto, ON, Canada.

Author status: First author.

Contribution: I conducted all the experiments for examining physiological properties of

IS3 cells together with behavioral screening of VIP-eGFP mice. I contributed to the writing of the entire manuscript working in collaboration with A.G.M. and F.K.S.for the modeling part. Funding Acquisition L.T. The work was supervised by L.T.

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* Correspondence: Dr. Lisa Topolnik Lisa.Topolnik@bcm.ulaval.ca

Attached article 4: Coordination of dendritic inhibition through local disinhibitory circuits

Publication status: Received: 28 November 2014; accepted: 11 February 2015;

published online: 26 February 2015 in the journal Frontiers in Synaptic Neuroscience.

Author status: First Author.

Authors: Ruggiero Francavilla, Xiao Luo, Elise Magnin, Leonid Tyanand Lisa Topolnik* Affiliations of each author: Department of Biochemistry, Microbiology and

Bio-informatics, Université Laval; Axis of Cellular and Molecular Neuroscience, IUSMQ, Québec, PQ, Canada

Contribution: I wrote the first chapter on properties and connectivity of IS3 cells realizing

the Figure included in the article.

*Correspondence:

Lisa Topolnik, Department of Biochemistry, Microbiology and Bio-informatics, Université Laval; Axis of Cellular and Molecular Neuroscience, IUSMQ, 2601 Ch. De La Canardière, CRULRG, Québec, PQ G1J 2G3, Canada

e-mail: Lisa.Topolnik@bcm.ulaval.ca

This article is published in the journal Frontiers in Synaptic Neuroscience. Copyright © 2015 Francavilla, Luo, Magnin, Tyan and Topolnik. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution and reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

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Introduction

Hippocampus in memory formation and consolidation

Neuronal substrates of memory formation, retrieval, and recalling

From the beginning of our life, our every day experience is stored in form of bad and good memories that determine the life we live. In this regard, the brain’s role is crucial since our mood, feelings and actions depend on how the brain process the information coming from outside and generates the outcome. Memory processes play a critical role in selection and consolidation of information necessary throughout our life. These processes involve four stages: 1) encoding, a task which requires attention and motivation for acquisition of new information that will be analyzed, that will determine the efficiency of the consolidation of memory traces; 2) consolidation, a process which transforms weak information into a more stable form with long duration: in this task different cellular mechanisms are involved, such as expression of genes and synthesis of new proteins; 3) storage, a process that allows to keep specific information for a certain period of time; 4) retrieval, a process that allows to recall and rescue stored information. The hippocampus, a small region of the brain located in the medial temporal lobe that constitutes a part of the limbic system, plays a crucial role in memory formation and consolidation. The role of the hippocampus in memory became apparent after the sad case of patient Henry Gustav Molaison, known as H.M., who received the surgical removal of the anterior two-thirds of his hippocampi and others parahippocampal structures to cure his epilepsy. After the surgery, H.M. developed severe anterograde amnesia, and despite the preserved working and procedural memory, he was not able to make the new memories and to consolidate them from short to long-term (memory consolidation) (Milner., 1972; Scoville and Milner., 2000). The role of the hippocampal formation in memory and learning comes also from studies on mammals, such as monkeys and rats commonly used in fundamental memory research. In particular, these early studies were based on the ablation of the hippocampal structure followed by assessment of the induced

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impairment on memory. Studies from monkeys have shown that the hippocampal formation which is comprised of the hippocampal subfields named Cornu Ammonis 1,2, and 3 (CA1, CA2 and CA3) together with dentate gyrus (DG), the subiculum (SUB), and the entorhinal cortex (EC), does play a role in the formation of new memories, but they also suggest that other extrahippocampal structures in the medial temporal lobe are likely to be involved in normal memory function. One of the most elegant behavioral tests used to assess memory impairment is the sample with delayed nonmatching-to-sample task. This test is based on the choice by the animal of the object not seen previously. Using this test, in 1978 Mishkin found that the removal of hippocampal region alone did not produce any relevant impairment on visual recognition memory. Indeed, only after the removal of both regions, amygdala and hippocampus, which corresponds approximately to the damage observed in the patient H.M., there was a strong impairment in memory formation. This study showed that conjoint damage to the amygdala and hippocampal formation is necessary to disrupt recognition memory. One limiting factor of this study was related to the damage of periallocortex adjacent to the hippocampus during its surgical removal. In this regard, the hippocampal formation should not be viewed as the unique neural substrate of the hippocampal-dependent memory system. Other studies of anatomically lesioned rodents have confirmed that the hippocampus is involved in the encoding and early retention of declarative tasks, but it is not engaged in the long-term storage (Squire et al., 1992; Chen et al., 1996).

The capability to remember past experiences is related to the efficient encoding and retrieval of characteristics such as people, places, objects, and moods associated with a given event. Memory consolidation is considered one of the most fascinating and complex brain tasks, and assessing how neuronal networks encode memory has been one of the primary goals in the field of neuroscience. Through the process of consolidation, short-term memories become a long-term memory and, in this regard, consolidation acts as a stabilization process responsible for making a stable and long-lasting memory. The perseveration-consolidation hypothesis was one of the first proposed to explain memory consolidation (Muller and Pilzecker, 1900).

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According to this theory, neural process activated by newly formed memories stabilizes the recently acquired information.

At that period the idea that changes in the strength of the synaptic connection between cortical neurons encode for memory was already put forward (Ramon y Cajal , 1894). Later on, Donald Hebb postulated the modern paradigm for memory research (Hebb , 1949) in which he proposed that a cell assembly linked by adaptable synaptic connections could encode informations in the brain. According to the theory of Donald Hebb, a synaptic input can be potentiated when activity in the presynaptic neuron co-occurs with the activity (membrane depolarization that produces action potential) in the postsynaptic neuron (Hebb, 1949; Brown et al., 1990, Sejnowski., 1999). Memory and synaptic plasticity have many properties in common (Kandel., 2001; Morris, 2003). The first evidence that memory formation relies on synaptic plasticity comes from the discovery of a phenomenon called the long-term potentiation (LTP) by Bliss and Lømo T in 1973. According to this phenomenon, high-frequency stimulation of hippocampal perforant pathway produced a long-lasting increase in synaptic response (Bliss and Lømo, 1973). Different studies have shown that specific molecular mechanisms are the basis of memory formation. In particular, LTP depends on modifications occurring at transcriptional, translational and post-translational cellular levels. One prevailing view related to the process of learning in the field is that the long-lasting facilitation of synapses in hippocampus and other areas is triggered by the activation of ionotropic glutamate receptors, such as N-methyl-D-aspartate (NMDA) and metabotropic glutamate receptors (mGluR) (Nowak et al., 1984; Bliss and Collingridge, 1993; Peng et al., 2010). A hallmark of NMDA receptor-dependent synaptic potentiation is the phosphorylation of α-amino-3-hydroxy-5-methyl-4-isoxazole propionic acid receptors and their insertion into the post synaptic membrane (Barria et al., 1997; Riedel et al., 2003; Bredt and Nicoll, 2003; Kessels and Malinow, 2009). Also, during LTP, intracellular modifications related to the activation of signaling pathways involving different protein kinases lead to de novo protein synthesis. These changes result in the synthesis of new proteins which will

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be used for the structural reinforcement of synapses and growth of new synaptic connections (Sacktor., 2011).

From these studies, it is evident that synaptic plasticity is at the basis of memory consolidation. However, to make a successful memory not only the retention but also the retrieval of the learned information is required. An important mechanism of the memory retrieval is the reactivation of previously established synapses involved in the memory encoding (Eichenbaum, 2004; Franckland and Bontempi, 2005; Tayler et al., 2013). Memory retrieval is a more complex mechanism compared to the memory consolidation and it involves several areas of the brain. In this regard, the hippocampus is typically required for contextually rich explicit retrieval as long as the memory exists (Eichenbaum, 2000; Rugg et al., 2002). At the basis of memory retrieval, there is the concept of memory engram proposed by Richard Semon who theorized that learning induces persistent changes in specific brain cells. These cells retain information and are subsequently reactivated upon appropriate retrieval (Semon, 1904; Semon, 1909; Schacter, 2001). Recent studies highlight the role of synaptic strengthening in memory retrieval, and propose engram cell-specific synaptic strength as a crucial mechanism for retrievalability of memory engrams (Miller and Matzel, 2006; Tonegawa et al., 2015).

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Figure 1 Anatomical location of hippocampus in the human, monkey and rodents brains and anatomy of the hippocampal memory system. a) in this lateral view of human brain the hippocampus is located in the medial temporal lobe surrounded by parahippocampal regions such as parahippocampal gyrus and amygdala. Figure adapted from Aguiar, (2006). b). In both monkeys and rats the origins of specific information for the hippocampus include virtually every neocortical association area. Each of these neocortical areas (blue) project to one or more subdivisions of the parahippocampal region, which includes the perirhinal cortex (purple), the parahippocampal (or postrhinal) cortex (dark purple) and the entorhinal cortex (light purple). The subdivisions of the parahippocampal region are interconnected and send principal efferents to many subdivisions of the hippocampus itself (green), the dentate gyrus, the CA3 and CA1 areas, and the subiculum. So the parahippocampal region serves as a convergence site for cortical input and mediates the distribution of cortical afferents to the hippocampus. Within the hippocampus, there are broadly divergent and convergent connections that could mediate a large network of associations, and these connections support plasticity mechanisms that could participate in the rapid coding of new conjunctions of information. The outcome of hippocampal processing is directed back to the parahippocampal region, and the output of that region is directed in turn back to the same areas of the cerebral cortex that were the source of input to this region. Panel adapted from Eichenbaum, (2000). c) The hippocampus was studied by Santiago Ramón y Cajal (1911). Basically this structures includes the Ammon’s horn (or cornu ammonis, CA), which is formed by CA1, CA2, CA3, the dentate gyrus (DG) which contains the dentata fascia and the hilus, and the subiculum (sub). Picture of hippocampus by Santiago Ramón y Cajal (1911), adapted from Ortega-Martinez, (2017).

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Figure 2 Hippocampal removal or damage cause memory deficits in human and rodent brains. a) Left column Magnetic resonance images arranged from rostral (a) to caudal (c) through the temporal lobe of patient H.M. (in 1993 at age 67) and a 66-year-old healthy male (right). The comparison brain illustrates the structures that appear to have been removed during H.M.’s surgery in 1953. The lesion was bilaterally symmetrical, extending caudally 5.4 cm on the left side and 5.1 cm on the right. The full caudal extent of abnormal tissue is not illustrated. The damage included medial temporal polar cortex, most of the amygdaloid complex, virtually all the entorhinal cortex, and approximately the rostral half of the hippocampal region (dentate gyrus, hippocampus, and subicular complex). The perirhinal cortex was substantially damaged except for its ventrocaudal aspect. The more posterior parahippocampal cortex (areas TF and TH, not shown here) was largely intact. b) Intact working memory and impaired long-term memory. (Left) The number of trials needed to succeed at each string length for patient H.M. and controls. H.M. could not succeed at repeating back 7 digits even after 25 attempts with the same string. (Right) The number of trials needed to learn the locations of different numbers of objects for patient G.P. and controls. G.P. could not reproduce the locations of four objects, even after 10 attempts with the same display. Panels adapted from Squire and Wixted, (2011). c) Performance of rats with hippocampal damage in the Morris water maze. In the conventional version of the task (top left), normal rats (blue) rapidly improve their swim latencies to find the platform across trials, whereas rats with hippocampal damage (red) do not. In the constant start position version of the task (top right), rats with hippocampal damage are slightly impaired in acquisition rate, but successfully learn to locate the platform. (bottom left) During probe testing, normal rats (blue) rapidly locate the escape platform both on repetitions of the original instruction trials and on probe trials that begin at new start positions. Rats with hippocampal damage (red) also do well on repetitions of the instruction trials, but poorly on the probe trials. (bottom left) Example swim paths in new probe trials by normal rats (blue) and rats with hippocampal damage (red). Normal rats swim directly to the platform, but rats with hippocampal damage are severely impaired. Panel adapted from Eichenbaum, (2000).

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Neuronal oscillations in hippocampal networks

Neuronal oscillations represent an essential signature of cortical networks. From a functional point of view, during network oscillations, neurons are assembled together to give origin to a network characterized by reciprocal dynamic connections and defined as cell assemblies (Palm, 1990). Donald Hebb was the first to hypothesize and to correlate the cell assembly to a cognitive entity (Hebb, 1949). Accordingly, cognitive processes, such as memory, planning and recall, could be seen as a sequence of cell assemblies activated for the achievement of a specific task (Hebb’s phase sequences). One of the significant limitations in the first studies addressing the contribution of cell assemblies to the complex cognitive processes was the absence of large multiscale recordings from several groups of cells. With the development of large-scale recordings in multiple brain regions (Eichenbaum and Davis, 1998; Buzsáki et al., 1992; Buzsáki, 2004), the assumption related to cell assemblies comprising neurons coming together in transient time frames becames evident. The synchronized activity of a large number of neurons at the level of cell assemblies gives origin to macroscopic oscillations characterized by the fluctuation of neuron membrane potential or action potential (AP). These oscillatory patterns are rhythmic, and can be detected with electroencephalogram (Buzsáki and Draguhn, 2004). From a biological point of view, brain oscillators share features of both harmonic and relaxation oscillators (Winfree, 1980; Glass, 2001). In the mammalian forebrain, network oscillations have a significant interval of frequency ranging from 0.05 Hz to 600 Hz. Functionally, brain oscillations and their synchrony are relevant to the most appropriate local information processing that can facilitate signal transmission between different regions of the brain.

Since oscillatory patterns arise from the cooperative action of neurons, the recordings of current flow in the extracellular space allows detecting behavior-related changes. In this regard, the local field potential (LFP) recordings give the possibility to detect electrical potentials in the extracellular space around neurons (Buzsáki, 2002). Using LFP recordings, we actually learnt that, in hippocampus, there are four

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characteristic oscillatory patterns defined by a specific frequency range: theta (5-12 Hz), gamma (~ 40-100 Hz), sharp wave-ripple (SPW-R) complexes (125-250 ripples superimposed on ~ 0.01-3 Hz sharp waves) and large (amplitude) irregular activity (LIA) (1-4 Hz) (Vanderwolf, 1969; Buzsáki et al., 1994; Leung, 1998; Bland and Oddie, 2001).

Theta oscillations in the hippocampus

The role of the hippocampus in spatial memory formation comes from the fact that spatial position of the rat can be associated with the spiking activity of some hippocampal neurons (O’Keefe and Dostrovsky, 1971). In the 1970s, the results of several studies come up to the theory that theta has a role in learning and memory because the extent at which theta was present in the electroencephalogram predicted how quickly and how well the animal would learn (Landfield et al., 1972; Winson, 1978; Berry and Thompson, 1978). The identification of “place cells”, which fire when the animal is in a specific location of the space, brings the field to the idea of the hippocampus as a cognitive map of the spatial environment, where the animal is navigating (O’Keefe and Nadel, 1978). In particular, these studies highlighted the correlation between the firing of complex spike cells and the phase of theta (O’Keefe and Recce, 1993; Skaggs et al., 1996), with the APs of a given neuron tending to occur during a specific phase of theta cycle. Taken together, these findings indicated that theta plays an essential role in learning and memory. However Brandon et al. (2014) found that in rats, place fields were formed when the animal was in novel environments despite theta rhythms and theta entrainment of spikes being blocked by septal inactivation. This finding clearly indicated that theta is not required for the formation of spatial memory representations at the single cell level. In this regard, theta is important for the formation of memories represented by neuronal ensembles. At the circuit level, the subset of coactive neurons whose place fields highly overlap was defined as a ‘cell assembly’. A group of cells can exhibit several place fields within an environment (O’ Keefe and Conway 1978; Shen et al., 1997) indicating that a single neuron can be a part of multiple cell assemblies during a specific behavior.

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Theta phase precession could be considered an interesting phenomenon associated with place cells spiking linked to a specific position of the animal in the environment. According to this phenomenon, as rat leaves a specific field, spikes associated to a place cell will appear early in the last theta cycle expressing spikes (O’Keefe and Recce, 1993). As a consequence, for the majority of place fields, there will be a relatively monotonic shift of the timing of spikes relative to the local theta rhythm as a rat traverses the field (Yamaguchi et al., 2002). The rate of theta phase precession is strictly coupled to the place field dimension with larger place fields exhibiting a slower precession (Shen et al., 1997; Ekstrom et al., 2001; Terrazas et al., 2005). This implies that during theta phase precession the firing rate of neuron is modulated at a frequency slightly higher than that of theta oscillations of the LFP. Maurer et al. (2005) confirmed these observations showing that the intrinsic modulation frequency within the large fields expressed by middle hippocampal cells was slower than the smaller fields of the dorsal hippocampal cells. As a consequence, inside an environment, a given place cell can show different place fields characterized by the same pattern of 360˚ of phase precession. In this regard, it was discovered that place fields, defined as single cycles of phase precession,can overlap spatially, with the outcome that cells will fire with spikes clustered at two different phases over the theta cycles in which the fields overlap (Maurer et al., 2006). One of the dynamic features of the place cell is that its preferred firing location (measured by its center of mass, or COM) shifts in the direction opposite to the rat’s movement as the animal repeatedly traverses the same location unidirectionally. This phenomenon, first reported by Mehta et al. (1997) for CA1 place cells, has been interpreted as an experience-dependent plasticity mechanism in the hippocampus for learning specific spatiotemporal sequences of discrete locations, as originally proposed by computational models (Levy, 1989; Blum and Abbott 1996). These models suggested that the temporally asymmetric nature of LTP induction (i.e., the presynaptic cell must fire before the postsynaptic cell) causes the formation of forward associations between place cells in a sequence, resulting in the COM-shift phenomenon.

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These specialized neuronal ensembles have been also defined theta sequences, and different works suggest that, instead of isolated place cells, theta sequences are required for memory operations (Skaggs et al., 1996; Dragoi and Buzsaki, 2006; Foster and Wilson 2007). Furthermore, it has been found that each theta cycle may encode for a specific information related to an episodic memory. In this regard, studies in rats have shown that several representations of different environments or different location of reward are located on separate theta cycles (Jezek et al., 2011; Dupret et al., 2013). The same theta segregation occurred across head direction-coding neuronal ensembles in the medial entorhinal cortex (MEC) and parasubiculum of rats (Brandon et al., 2013). In this regard, head direction cells associated with similar head directions were firing on the same theta cycles while cells that fired on separate theta cycles preferred different head directions.

Additional observations related to the involvement of theta oscillations in hippocampal learning come from in vitro studies. In the hippocampus, stimulation of afferents imitating the theta frequency has been shown to produce LTP, which is essential for memory encoding (Larson et al., 1986; Hölscher et al., 1997). LTP occurs since large amplitude fast Ca2+ spikes can be generated in dendrites of CA1

pyramidal cells (PCs) (Kamondi et al., 1998). In vivo, theta-associated somatic depolarization provides the condition necessary for the synaptic potentiation (Paulsen and Sejnowski, 2000). However, theta rhythm is present not only during active behavior (locomotion) but it is also a prominent sign of the rapid eye movements (REM) phase of sleep in mammals, including human (Jouvet, 1969; Robinson et al., 1977; Buzsáki, 2002). In this regard, one of the significant roles proposed for hippocampal theta during REM sleep is related to memory consolidation by reinforcing the response of neurons that were previously active during awake conditions. For example, hippocampal place cells which have been actives during prior waking will show an increase in their firing during sleep, highlighting that memories of the recent event may be strengthened during REM sleep (Poe et al., 2000; Louie and Wilson 2001). Functional evidence was provided

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recently by the study of Boyce et al.,2016 in which inhibition of medial septum neurons, acting as a pacemaker of theta rhythm in the hippocampus, during REM sleep had a strong impact on the memory consolidation performance.

Gamma rhythm in the hippocampus

However, the hippocampal theta rhythm is not the only one associated with memory encoding and consolidation. Different studies have shown that, during mnemonics processes, there is an increase in hippocampal CA1 gamma rhythms (40-100 Hz) (Buzsaki et al., 1983; Bragin et al., 1995; Johnson and Redish, 2007; Montgomery and Buzsáki, 2007; Sederberg et al., 2007; Jutras et al., 2009; Trimper et al., 2014). Interestingly, successful memory performance also requires coupling of gamma rhythms to a particular phase of the theta cycle (Colgin, 2013). In this regard, different studies have shown that gamma frequency oscillations are nested within slow theta frequency oscillations (Belluscio et al., 2012; Bragin et al., 1995; Colgin et al., 2009; Soltesz and Deschenes, 1993). However, in all these studies, no difference was made between the different frequency variants of gamma, and it is possible that slow gamma (~25-55 Hz) and fast gamma (~60-100 Hz) are associated with different functions in the memory domain. It should be noted, that slow gamma is driven by inputs coming from CA3 and that fast gamma by those from MEC, in rats and mice (Colgin et al., 2009; Belluscio et al., 2012; Kemere et al., 2013; Schomburg et al., 2014). These inputs have important outcomes from a functional point of view. In fact, it has been suggested for the fast gamma that, due to the connection with MEC, this oscillatory rhythm is involved in the encoding of sensory information in memory (Canto et al., 2008; Yamamoto et al., 2014, Colgin, 2016). On the other side, slow gamma related to the inputs coming from CA3 area has been shown to be involved in memory retrieval. In particular, it has been shown that coordination between slow gamma and theta was linked to successful memory retrieval in rats (Shirvalkar et al., 2010). Furthermore, studies on place cell ensemble activity suggested that slow gamma facilitates the activation of the previously stored

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memory of spatial sequences, confirming the role of slow gamma in memory retrieval (Zheng et al., 2016; Bieri et al., 2014).

Hippocampal sharp-wave associated ripples

So far, I have been describing hippocampal oscillatory patterns mainly associated with animal locomotion. However, the memory consolidation is thought to be associated with SPW-Rs occurring during waking immobility ‘consummatory’ behaviours and during slow-wave sleep (Buzsaki, 1986). The term consummatory refers to consummation, meaning to complete or to finish a planned action; on the other hand ‘preparatory’ behavior is related to foraging, exploratory, goal-directed and planned behaviors. From this point of view, theta and SPW-Rs reflect well this dichotomy with preparatory behaviors mainly involved in theta oscillatory patterns. The SPW-Rs are large amplitude negative polarity deflections (40-100 ms) occurring in the stratum radiatum (RAD) that are often associated with fast oscillatory events at the level of pyramidal layer (PYR) known as ripples (O’Keefe and Nadel, 1978; Buzsaki et al., 1983, 1992; Buzsaki 1986; Suzuki and Smith, 1988; Kanamori 1985). The SPW-Rs occur more frequently during non-REM sleep, and with lower frequency during very long immobility periods and when ambulation comes to a temporary halt. The frequency of ripples is faster during transient waking immobility than during non-REM sleep (Ponomarenko et al., 2008). The SPW-Rs are the most prominent self-organized events in the hippocampal system and they are excitatory events originating in the CA3 and transmitted to CA1 (Sullivan et al., 2011, Buzsaki, 2015). On the other hand, ripples are generated locally in the CA1 with place cell spikes in this area phase-locked to ripples. This brain rhythm is well preserved across different species, and it has been found in several mammals including human (Bragin et al., 1999; Le Van Quyen et al., 2010). The SPW-Rs are considered the most synchronous events in the mammalian brain, and these oscillatory patterns are associated with a robust transient increase in the excitability of hippocampus and others associated structures (Buzsaki 1986; Chrobak and Buzsaki, 1994; Csicsvari et al., 1999a). The role of the SPW-Rs in memory consolidation comes from studies

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related to the firing of place cells during active exploration. In particular, CA1 place cells which were firing during active exploration are reactivated during subsequent SPW-Rs. This phenomenon is called replay or reactivation of place cells, and it implies that, when ripples are detected in CA1 during wakefulness, CA3 and CA1 place cells concurrently replay the same spatial memories. Furthermore, in the context of the hippocampus as a cognitive spatial map, the SPW-Rs were involved in the reactivation of neuronal pattern representing novel environment, and this supports the association between SPW-Rs-related reactivation and map stabilization (O’Neill et al., 2008). In particular, spikes from place cell ensemble were re-played during the SWP-Rs in the same order as in exploration but on a faster timescale (Nadasdy et al., 1999; Lee and Wilson, 2002; Carr et al., 2012).

In vivo, cells that were active within the same SPW-Rs episodes were showing

synaptic potentiation (King et al., 1999). During the reactivation of place cell assemblies, associated with a specific location of the mouse during locomotion, the SPW-Rs are generated by cells encoding the same location, which fire together with high temporal synchrony. However, synaptic potentiation associated with SPW-Rs can induce processes that facilitate the separation of maps by strengthening the strongly associated cell assemblies and giving rise to the divergence of maps representing a certain environment. In this regard, the SPW-Rs make weak the joint firing of those cells that belong to different assemblies (O’Neill et al., 2008; Csicsvari and Dupret, 2014). In support of the involvement of the SPW-Rs in memory consolidation, there is a study where selective elimination of ripples during post-learning sleep resulted in the impairment of memory performance (Girardeau et al., 2009; Ego-Stengel and Wilson, 2010; Nokia et al., 2012). Furthermore, recent studies revealed that the SPW-Rs also have a role in the spatial route planning during awake wakefulnes. In rats performing spatial memory tasks, place cells have been shown to represent location that was different from the animal’s current location. In this regard, the SPW-Rs, occurring between phases of active navigation, could provide the excitation that allows place cells to fire outside of their place field. The SPW-Rs were responsible, in this case, for representation of distant locations

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(Karlsson and Frank, 2009; Gupta et al., 2010). During this memory-guided trajectory planning, the multiple ripple cycles of a SPW-R event correspond largely to sequential series of cell assemblies. From this encoding perspective of trajectory planning, sharp wave (SPW) to ripple coupling is analogous to the assembly sequence relationship of theta-nested gamma waves (Lisman and Idiart, 1995; Buzsaki, 2010). Despite their role in memory-guided trajectory planning, recent evidence indicated a role for SWP-Rs also in memory retrieval. In line with this concept, place cell sequences active during SPW-Rs can represent pathways that were not previously experienced. In this regard memories will be retrieved on a faster timescale compared to the one in which they were experienced (Davidson et al., 2009; Carr et al., 2011; Carr et al., 2012). Taken together, the results of these studies indicate that reactivation of memory sequences during SPW-Rs could provide a convenient mechanism not only for the consolidation of long-term memory but also for fast recall of memories during awake state underlying various cognitive functions. In this regard, SPW-Rs represent a mechanism that allows a kind of cementing learned association. Based on the observations that entorhinal inputs can modify the intra-SPW-Rs association of hippocampal neurons, a neurophysiology-based two-stage model was put forward (Buzsaki, 1989, 1994, 1996, 1998; Chrobak and Buzsaki, 1994; Buzsaki, 2015). According to this two-stage model, there is a first stage in which there is a labile form of memory trace. In this phase, there is learning associated with theta brain state, which involves afferents from neocortex bringing a transient change of synaptic strength in CA3 hippocampal region where informations are temporally held. In the second stage, characterized by more stable form of memory traces, during consummatory behavior and slow-wave sleep, spontaneous SPW bursts are initiated in the CA3 recurrent network. The recurring SPW-Rs transfer the newly acquired hippocampal information to the neocortex and the repeating SPW-Rs continue to potentiate those same synapses that were involved in synaptic changes during the learning process. Considering the role of SPW-Rs in strengthening the association in the firing of place cells assemblies during awake wakefulness and slow-wave sleep, this oscillatory rhythm is generated to allow the transfer of information outside the hippocampus. Also, SPW-Rs trigger the activation

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of interrelated memory assembles in different brain areas (O’Neill et al., 2010; Ji and Wilson, 2007). Compared to theta events, SPW-Rs are also characterized by a greater propagation speed along the septotemporal axis of hippocampus, which can be two - fourfold times higher compared to theta waves, and is reflected by the manner in which SPW-Rs are generated. In this regard, recurrent collateral of the CA3 neurons ensure a greater propagation of SPW-Rs (Patel et al., 2013).

The hippocampal Large Irregular Activity (LIA)

In the mid-1960s, LFP recordings from the hippocampus of freely moving rat showed the existence of three oscillatory states: together with the previous mentioned theta (5-12 Hz) the others two oscillatory states recorded were the LIA state, and the small irregular amplitude activity state (Vanderwolf, 1969). LIA is an oscillatory hippocampal rhythm with 1-4 Hz frequency range and is observed during immobility behaviours, such as grooming, eating, quiet sitting and drinking. LIA is characterized by nonrhythmical patterns based on disorganized voltage fluctuations punctuated by transient, population bursts of spiking that engage large numbers of neurons in the hippocampus. In fact, LIA have been found to co-occur with ripples and to show SPWs of about 100 ms duration that occur randomly, with an interval of 1 second (Buzsaki et al., 1983; Buzsaki et al., 1992). Intriguingly, this oscillatory state is characterized by a flatter power spectrum showing more peaks occurring in the lower frequencies (1-5 Hz) (Leung, 1992). Similar to SPW-Rs, this oscillatory hippocampal rhythm has been thought to play an important role in the consolidation process of old memories. As I have mentioned in the previous subchapter, place cell spiking in and around SPW-Rs during sleep represents extended, temporally precise spatial trajectories through previously visited environments (Skaggs and McNaughton, 1996; Lee and Wilson, 2002). In this context, similar sequence representations occur within SPW-Rs during awake LIA with ensemble firing patterns reactivated, and this activity appears to grow with time (O’Neill et al., 2006; Foster and Wilson, 2006; Jackson et al., 2006). This observations could be explained by the fact that during states in which the network was uncoupled from its entorhinal inputs (e.g., slow-wave sleep

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and LIA) (Chrobak and Buzsaki, 1994, 1996; Chrobak et al., 2000), uncorrelated noise in the system would then cascade across these strengthened synapses producing a replay of this stored information during SPWs (Buzsaki, 1989; Csicsvari et al., 2000). Taken together, these data support learning theories that suggest that experience-dependent mechanisms strengthen cell assemblies during tasks and that SPW-Rs occurring during LIA or slow-wave sleep reactivate those cell assemblies in subsequent rest states. Interestingly, during sleep cells that were active during behavior fire at high rate and correlations between pairs of place cells coactive during exploration are enhanced during post-behavior sleep (Pavlides and Winson, 1989; Foster and Wilson, 2006). As during awake immobility behaviors, the enhancement of post-behavior correlation strength reflects the order in which cells were activated during behavior indicating ensemble-level coordination of place cell “reactivation” during sleep.

Another elucidated role of LIA during awake states, such as consummatory behaviors, is the manipulation of previous experience to construct novel, i.e., never-experienced, representations. For instance, in rats performing a multiple-T decision-making task, the probability of a location being included within awake LIA sequences was sometimes inversely related to how often that area was visited (Gupta et al., 2010). Cognitive factors seem to have a strong influence over the content of awake LIA sequences. When animals encounter new environments for the first time, awake LIA sequence content is biased toward representing recently explored portions of space (Cheng and Frank, 2008).

Taken together these finding showed a role of LIA as ‘destabilizer’ factor from the consolidation perspective. Indeed, consolidation during awake LIA would be vulnerable to memory interference, as forward and reverse trajectories represent equally plausible experiences, but the rat may have traveled in only one direction. On the other hand, from a construction perspective, backward sequences could be a key building block for assembling never experienced trajectories.

Finally, it appears that LIA sequences might be involved in the online planning function of the hippocampus. In 2011, Dragoi and Tonegawa showed that LIA

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sequences represent trajectories through regions of an environment that subjects can view but not physically enter suggesting that the hippocampus is equipped to plan trajectories over regions of space it has not yet encountered. Consistent with this idea, Pfeiffer and Foster (2013) showed that sequences recorded while rats performed a goal-directed navigation task were biased to end in the spatial location that the rat would next travel to.

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Figure 3 Rhythms of hippocampal network which can be important for spatial memory and navigation. a) left, theta-related and gamma-related modulation of the field in the dentate gyrus (hilar region) during exploratory walking. Right, sharp-wave associated field ripples in CA1 area during slow-wave sleep. Upper traces, wide band recording, lower traces, band bath (40-50 Hz, left; 150-250 Hz, right) filtered gamma and ripple activity. Panel adapted from Gloveli et al., (2010). b) hippocampal field activity related to large amplitude irregular activity (LIA) recorded from the dentate molecular layer. Adapted from Bland, (2002). c) Responses of a hippocampal (CA1) unit to a restraining tactile stimulus as a function of the rat's spatial orientation. The arrows and associated letters mark the positions at which the animal was restrained as it was pushed or coaxed in a counter-clockwise direction around the test platform. The firing rate of the unit during tiffs procedure is illustrated by the continuous frequency histogram in the middle of the figure. The letters correspond to the positions and the lines indicate the periods when the rat was restrained. In between these periods, the rat sat immobile in the same position for a few seconds and then was moved on to the next position. The bottom two lines show the raw data taken at the onset of the unit response at A (1) and during the absence of a response at D (2). Time calibration for these data is 400 msec. Adapted from O’Keefe and Dostrovsky, (1971). d) top, EEG theta rhythm and place-cell firing (red ticks) on a single run and false-color firing field created from multiple runs. Peak firing occurs on the trough of the theta cycle. Bottom, spike-triggered average of theta waves and autocorrelogram of spikes, initiated by spike occurrence at place-field peak. Groups of spikes occur at higher than theta frequency, causing each successive burst to move to an earlier phase of the theta cycle. Note the progressive forward shift of the preferred phase. Adapted from Buzsáki and Draguhn, (2004). e) Replay during sharp wave-ripples a) Shown here are spikes from successively activated place cells (top) as a rodent passes through the cells’ place fields in a particular trajectory on a linear track (bottom). Each row of colored tick marks represents spikes from a different place cell (calibration: 500 ms). b) Shown here is an example of a sharp wave-ripple (top), recorded during subsequent rest at the end of the linear track; a bandpass filtered (150-300 Hz) version of the sharp wave-ripple is shown immediately below the raw recording. Spikes from the place cell ensemble are shown to reactivate during the sharp wave-ripple in the same order as in exploration but on a faster time scale. Calibration: 50 ms. Panel adapted from Colgin, (2016).

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Neuronal substrates of hippocampal oscillatory patterns

The presence of several oscillatory patterns involved in memory encoding, retrieval and consolidation presumes a specific functional organization inside the neuronal network responsible for their generation. As presented, the coordinated activity of different cell assemblies should be at the basis of oscillatory brain rhythms. In the logic of the brain architecture, these cell assemblies are defined not only by the cells of the same type, like place cells activated by a specified position of the animal in the space. It is well known that brain computations require two forces: excitation and inhibition. The difference in these two forces is reflected well in the distinct neuronal types present in the central nervous system. The neurotransmitter released from the neuronal axon could be considered the critical element depicting the neuronal identity. In this regard, glutamate and gamma-aminobutyric acid (GABA) are considered the neurotransmitters related to excitatory and inhibitory neurons, respectively. GABA is the main inhibitory neurotransmitter in the brain, and its function is mainly associated with a reduction of the firing reducing the neuronal excitability. One the other side, glutamate is the major excitatory neurotransmitter in the nervous system. Nearly all excitatory neurons in the central nervous system are glutamatergic, and it is estimated that over half of all brain synapses release this molecule. Glutamatergic principal cells account for the majority of cortical neurons with the remaining 15-20% represented by the population of inhibitory GABAergic interneurons (Sillito, 1984; Hendry et al., 1987; DeFelipe, 1993; Somogyi et al., 1998; Markram et al., 2004). The dynamic partnership between excitatory and inhibitory neurons ensures an overall homeostatic regulation of global firing rates of neurons over extended territories of the cerebral cortex. This interaction is very important for determining modifications in local excitability within short time windows. This could represent an essential requirement for processing information and modifying network connections. Coordinated inhibition ensures that excitatory trajectories are properly routed and that competing cell assembly are functionally segregated. As a result, in response to the same input, a given network can produce different output patterns at different times, depending on the state of inhibition. In the

Figure

Figure 1 Anatomical location of hippocampus in the human, monkey and rodents brains and anatomy of  the hippocampal memory system
Figure 2  Hippocampal  removal  or  damage  cause  memory  deficits  in  human and  rodent  brains
Figure 3 Rhythms of hippocampal network which can be important for spatial memory and navigation
Figure 4 Hippocampal CA1 pyramidal cells are composed of deep and superficial cells, based on their  neurochemical,  morphological,  physiological,  and  functional  properties
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