Parallel and convergent processing in grid cell, head-direction cell, boundary cell, and place cell networks.

The brain is able to construct internal representations that correspond to external spatial coordinates. Such brain maps of the external spatial topography may support a number of cognitive functions, including navigation and memory. The neuronal building block of brain maps are place cells, which are found throughout the hippocampus of rodents and, in a lower proportion, primates. Place cells typically fire in one or few restricted areas of space, and each area where a cell fires can range, along the dorsoventral axis of the hippocampus, from 30 cm to at least several meters. The sensory processing streams that give rise to hippocampal place cells are not fully understood, but substantial progress has been made in characterizing the entorhinal cortex, which is the gateway between neocortical areas and the hippocampus. Entorhinal neurons have diverse spatial firing characteristics, and the different entorhinal cell types converge in the hippocampus to give rise to a single, spatially modulated cell type-the place cell. We therefore suggest that parallel information processing in different classes of cells-as is typically observed at lower levels of sensory processing-continues up into higher level association cortices, including those that provide the inputs to hippocampus. WIREs Cogn Sci 2014, 5:207-219. doi: 10.1002/wcs.1272 Conflict of interest: The authors have declared no conflicts of interest for this article. For further resources related to this article, please visit the WIREs website

Effects of cannabinoids and novelty on hippocampal electrophysiology

Exposure to novel environments alters hippocampal cell and theta local field potential activity to support the formation of new or updated spatial representations. It induces remapping of place cell fields, a reduction in CA1 theta frequency and an increase in the spatial scale of entorhinal grid cell fields. A recent model proposes that a reduction in the slope of the theta frequency-running speed relationship (TFRSR) can account for these effects (Burgess, 2008, Hippocampus). In contrast, the model proposes that the Y-axis intercept of the TFRSR is unaffected by novelty but instead correlates with anxiety/arousal. Thus, the theta frequency reduction elicited by a wide range of anxiolytic drugs (Gray & McNaughton, 2000) is suggested to result from a decrease in the intercept. Cannabinoids are anxiolytic at low doses, reduce theta frequency and disrupt the theta-timescale dynamics of place cell firing. In contrast, environmental novelty elicits a coordinated shift in CA1 place cell firing to a later theta-phase. This thesis examines the electrophysiological effects of environmental familiarity or novelty in combination with a low, intraperitoneal dose of the cannabinoid agonist O-2545, or its vehicle, saline. It was found that exposure to novel environments reduced the slope of the TFRSR whereas the cannabinoid reduced the intercept, in agreement with the model. These effects were not due to decreased body temperature or changes in behaviour. Combining novelty and drug reduced both slope and intercept. Furthermore, the extent of novelty-induced place cell remapping correlated with the reduction in slope. The mean theta-phase of place cell firing shifted later in novelty, but this was disrupted by the cannabinoid. In contrast, the mean theta-phase of the interneuron population was stable across conditions, but novelty increased the dispersion of interneuron theta-phase preferences. These results help to elucidate the mechanisms underlying novelty processing and cannabinoid action in the hippocampus

Constraining the function of CA1 in associative memory models of the hippocampus

Institute for Adaptive and Neural ComputationCA1 is the main source of afferents from the hippocampus, but the function of CA1 and its perforant path (PP) input remains unclear. In this thesis, Marr’s model of the hippocampus is used to investigate previously hypothesized functions, and also to investigate some of Marr’s unexplored theoretical ideas. The last part of the thesis explains the excitatory responses to PP activity in vivo, despite inhibitory responses in vitro. Quantitative support for the idea of CA1 as a relay of information from CA3 to the neocortex and subiculum is provided by constraining Marr’s model to experimental data. Using the same approach, the much smaller capacity of the PP input by comparison implies it is not a one-shot learning network. In turn, it is argued that the entorhinal-CA1 connections cannot operate as a short-term memory network through reverberating activity. The PP input to CA1 has been hypothesized to control the activity of CA1 pyramidal cells. Marr suggested an algorithm for self-organising the output activity during pattern storage. Analytic calculations show a greater capacity for self-organised patterns than random patterns for low connectivities and high loads, confirmed in simulations over a broader parameter range. This superior performance is maintained in the absence of complex thresholding mechanisms, normally required to maintain performance levels in the sparsely connected networks. These results provide computational motivation for CA3 to establish patterns of CA1 activity without involvement from the PP input. The recent report of CA1 place cell activity with CA3 lesioned (Brun et al., 2002. Science, 296(5576):2243-6) is investigated using an integrate-and-fire neuron model of the entorhinal-CA1 network. CA1 place field activity is learnt, despite a completely inhibitory response to the stimulation of entorhinal afferents. In the model, this is achieved using N-methyl-D-asparate receptors to mediate a significant proportion of the excitatory response. Place field learning occurs over a broad parameter space. It is proposed that differences between similar contexts are slowly learnt in the PP and as a result are amplified in CA1. This would provide improved spatial memory in similar but different contexts

Neuronal Oscillations Enhance Stimulus Discrimination by Ensuring Action Potential Precision

Although oscillations in membrane potential are a prominent feature of sensory, motor, and cognitive function, their precise role in signal processing remains elusive. Here we show, using a combination of in vivo, in vitro, and theoretical approaches, that both synaptically and intrinsically generated membrane potential oscillations dramatically improve action potential (AP) precision by removing the membrane potential variance associated with jitter-accumulating trains of APs. This increased AP precision occurred irrespective of cell type and—at oscillation frequencies ranging from 3 to 65 Hz—permitted accurate discernment of up to 1,000 different stimuli. At low oscillation frequencies, stimulus discrimination showed a clear phase dependence whereby inputs arriving during the trough and the early rising phase of an oscillation cycle were most robustly discriminated. Thus, by ensuring AP precision, membrane potential oscillations dramatically enhance the discriminatory capabilities of individual neurons and networks of cells and provide one attractive explanation for their abundance in neurophysiological systems

Slow Inhibition and Inhibitory Recruitment in the Hippocampal Dentate Gyrus

L’hippocampe joue un rôle central dans la navigation spatiale, la mémoire et l’organisation spatio-temporelle des souvenirs. Ces fonctions sont maintenues par la capacité du gyrus denté (GD) de séparation des patrons d'activité neuronales. Le GD est situé à l’entrée de la formation hippocampique où il reconnaît la présence de nouveaux motifs parmi la densité de signaux afférant arrivant par la voie entorhinale (voie perforante). Le codage parcimonieux est la marque distinctive du GD. Ce type de codage est le résultat de la faible excitabilité intrinsèque des cellules granulaires (CGs) en combinaison avec une inhibition locale prédominante. En particulier, l’inhibition de type « feedforward » ou circuit inhibiteur antérograde, est engagée par la voie perforante en même temps que les CGs. Ainsi les interneurones du circuit antérograde fournissent des signaux GABAergique aux CGs de manière presque simultanée qu’elles reçoivent les signaux glutamatergiques. Cette thèse est centrée sur l’étude des interactions entre ces signaux excitateurs de la voie entorhinale et les signaux inhibiteurs provenant des interneurones résidant dans le GD et ceci dans le contexte du codage parcimonieux et le patron de décharge en rafale caractéristique des cellules granulaires. Nous avons adressé les relations entre les projections entorhinales et le réseau inhibitoire antérograde du GD en faisant des enregistrements électrophysiologiques des CG pendant que la voie perforante est stimulée de manière électrique ou optogénétique. Nous avons découvert un nouvel mécanisme d’inhibition qui apparait à délais dans les CGs suite à une stimulation dans les fréquences gamma. Ce mécanisme induit une hyperpolarisation de longue durée (HLD) et d’une amplitude prononce. Cette longue hyperpolarisation est particulièrement prolongée et dépasse la durée d’autres types d’inhibition transitoire lente décrits chez les CGs. L’induction de HLD crée une fenêtre temporaire de faible excitabilité suite à laquelle le patron de décharge des CGs et l’intégration d’autres signaux excitateurs sont altérés de manière transitoire. Nous avons donc conclu que l’activité inhibitrice antérograde joue un rôle central dans les processus de codage dans le GD. Cependant, alors qu’il existe une multitude d’études décrivant les interneurones qui font partie de ce circuit inhibiteur, la question de comment ces cellules sont recrutées par la voie entorhinale reste quelque peu explorée. Pour apprendre plus à ce sujet, nous avons enregistré des interneurones résidant iii dans la couche moléculaire du GD tout en stimulant la voie perforante de manière optogénétique. Cette méthode de stimulation nous a permis d’induire la libération de glutamate endogène des terminales entorhinales et ainsi d’observer le recrutement purement synaptique d’interneurones. De manière surprenante, les résultats de cette expérience démontrent un faible taux d’activation des interneurones, accompagné d’un tout aussi faible nombre total de potentiels d’action émis en réponse à la stimulation même à haute fréquence. Ce constat semble contre-intuitif étant donné qu’en générale on assume qu’une forte activité inhibitrice est requise pour le maintien du codage parcimonieux. Tout de même, l’analyse des patrons de décharge des interneurones qui ont été activés a fait ressortir la prééminence de trois grands types: décharge précoce, retardée ou régulière par rapport le début des pulses lumineux. Les résultats obtenus durant cette thèse mettent la lumière sur l’important conséquences fonctionnelles des interactions synaptique et polysynaptique de nature transitoire dans les réseaux neuronaux. Nous aimerions aussi souligner l’effet prononcé de l’inhibition à court terme du type prolongée sur l’excitabilité des neurones et leurs capacités d’émettre des potentiels d’action. De plus que cet effet est encore plus prononcé dans le cas de HLD dont la durée dépasse souvent la seconde et altère l’intégration d’autres signaux arrivants simultanément. Donc on croit que les effets de HLD se traduisent au niveau du réseaux neuronal du GD comme une composante cruciale pour le codage parcimonieux. En effet, ce type de codage semble être la marque distinctive de cette région étant donné que nous avons aussi observé un faible niveau d’activation chez les interneurones. Cependant, le manque d’activité accrue du réseau inhibiteur antérograde peut être compensé par le maintien d’un gradient GABAergique constant à travers le GD via l’alternance des trois modes de décharges des interneurones. En conclusion, il semble que le codage parcimonieux dans le GD peut être préservé même en absence d’activité soutenue du réseau inhibiteur antérograde et ceci grâce à des mécanismes alternatives d’inhibition prolongée à court terme.The hippocampus is implicated in spatial navigation, the generation and recall of memories, as well as their spatio-temporal organization. These functions are supported by the processes of pattern separation that occurs in the dentate gyrus (DG). Situated at the entry of the hippocampal formation, the DG is well placed to detect and sort novelty patterns amongst the high-density excitatory signals that arrive via the entorhinal cortex (EC). A hallmark of the DG is sparse encoding that is enabled by a combination of low intrinsic excitability of the principal cells and local inhibition. Feedforward inhibition (FFI) is recruited directly by the EC and simultaneously with the granule cells (GCs). Therefore, FFI provides fast GABA release and shapes input integration at the millisecond time scale. This thesis aimed to investigate the interplay of entorhinal excitatory signals with GCs and interneurons, from the FFI in the DG, in the framework of sparse encoding and GC’s characteristic burst firing. We addressed the long-range excitation – local inhibitory network interactions using electrophysiological recordings of GCs – while applying an electrical or optogenetic stimulation of the perforant path (PP) in the DG. We discovered and described a novel delayed-onset inhibitory post synaptic potential (IPSP) in GCs, following PP stimulation in the gamma frequency range. Most importantly, the IPSP was characterized by a large amplitude and prolonged decay, outlasting previously described slow inhibitory events in GCs. The long-lasting hyperpolarization (LLH) caused by the slow IPSPs generates a low excitability time window, alters the GCs firing pattern, and interferes with other stimuli that arrive simultaneously. FFI is therefore a key player in the computational processes that occurs in the DG. However, while many studies have been dedicated to the description of the various types of the interneurons from the FFI, the question of how these cells are synaptically recruited by the EC remains not entirely elucidated. We tackled this problem by recording from interneurons in the DG molecular layer during PP-specific optogenetic stimulation. Light-driven activation of the EC terminals enabled a purely synaptic recruitment of interneurons via endogenous glutamate release. We found that this method of stimulation recruits only a subset of interneurons. In addition, the total number of action potentials (AP) was surprisingly low even at high frequency stimulation. This result is counterintuitive, as strong and persistent inhibitory signals are assumed to restrict GC v activation and maintain sparseness. However, amongst the early firing interneurons, late and regular spiking patterns were clearly distinguishable. Interestingly, some interneurons expressed LLH similar to the GCs, arguing that it could be a commonly used mechanism for regulation of excitability across the hippocampal network. In summary, we show that slow inhibition can result in a prolonged hyperpolarization that significantly alters concurrent input’s integration. We believe that these interactions contribute to important computational processes such as sparse encoding. Interestingly, sparseness seems to be the hallmark of the DG, as we observed a rather low activation of the interneuron network as well. However, the alternating firing of ML-INs could compensate the lack of persistent activity by the continuous GABA release across the DG. Taken together these results offer an insight into a mechanism of feedforward inhibition serving as a sparse neural code generator in the DG

Hippocampal theta sequences: from phenomenology to circuit mechanisms

The hippocampus is a brain structure involved in episodic memory and spatial cognition. Neuronal activity within the hippocampus exhibits intricate temporal patterning, including oscillatory and sequential dynamics, which are believed to underlie these cognitive processes. In individual cells, a temporal activity pattern called phase precession occurs which leads to the organisation of neuronal populations into sequences. These sequences are hypothesised to form a substrate for episodic memory and the representation of spatial trajectories during navigation. In this thesis, I present a novel theory of the phenomenological properties of these neuronal activity sequences. In particular, I propose that the sequential organisation of population activity is governed by the independent phase precession of each cell. By comparison of models in which cells are independent and models in which cells exhibit coordinated activity against experimental data, I provide empirical evidence to support this hypothesis. Further, I show how independent coding affords a vast capacity for the generation of sequential activity patterns across distinct environments, allowing the representation of episodes and spatial experiences across a large number of contexts. This theory is then extended to account for grid cells, whose activity patterns form a hexagonal lattice over external space. By analysing simple forms of phase coding in populations of grid cells, I show how previously undocumented constraints on phase coding in two dimensional environments are imposed by the symmetries of grid cell firing fields. To overcome these constraints, I propose a more complex phenomenological model which can account for phase precession in both place cells and grid cells in two dimensional environments. Using insights from this theory, I then propose a biophysical circuit mechanism for hippocampal sequences. I show that this biophysical circuit model can account for the proposed phenomenological coding properties and provide experimentally testable predictions which can distinguish this model from existing models of phase precession. Finally, I outline a scheme by which this biophysical mechanism can implement supervised learning using spike time dependent plasticity in order to learn associations between events occurring on behavioural timescales. The models presented in this thesis challenge previous theories of hippocampal circuit function and suggest a much higher degree of flexibility and capacity for the generation of sequences than previously believed. This flexibility may underlie our ability to represent spatial experiences and store episodic memories across a seemingly unlimited number of distinct contexts

The role of the medial entorhinal cortex in spatial and temporal coding

The hippocampus (HIPP) is the core of a memory system crucial for the formation of new episodic (unique event) memories in humans and episodic-like memories (for what, where and when) in rodents. Its prevalent role in the formation of memories is thought to rely on a variety of specialized neural network computations: It is for example believed that hippocampal networks associate information about different aspects of an experience (such as a particular event and the place at which the event occurred) into a coherent memory trace. In order to prevent interference between memories that are similar (such as two different experiences within the same place) each memory is assigned a neural code that is highly distinct from those for previously acquired memories. Finally, hippocampal networks are thought to fuse memories for individual fragments of an experience into a temporally structured sequence which represent an episode. Information about different aspects of an experience reaches the HIPP via the entorhinal cortex (EC), which is its major cortical input structure. Electrophysiological single-unit recordings in behaving rodents revealed that in particular the medial division of the EC (MEC) contains a variety of cell types that are specialized in the representation of spatial and self-motion information. It is therefore believed that input from the MEC supports the spatial component of memory processing in the HIPP. Here, we tested the long-standing hypothesis that hippocampal spatial coding relies on input from the MEC. This was achieved by performing extensive, bilateral excitotoxic lesions of the MEC and placing electrode arrays into the CA1 pyramidal cell layer of the HIPP. Hippocampal neural computations were assessed by recording extracellular action potentials (APs) from individual neurons as rats explored open field environments. The firing patterns of hippocampal neurons are known to correlate with the rat’s behavior, in that each cell fires APs at restricted proportions of the environment, forming spatial receptive fields (so-called place fields). The spatial precision and organization of those place fields was examined in control and MEC-lesioned rats. We found that hippocampal neurons retained their spatial selectivity after MEC lesions, even though the precision and stability of the hippocampal spatial code were reduced. The ability to form distinct spatial representation for different environments was entirely intact in MEC-lesioned rats. Contrary to most contemporary theories of hippocampo-entorhinal function, our findings suggest that the MEC is not the only determinant of hippocampal spatial computations and that sources lacking sophisticated spatial firing, such as the lateral division of the entorhinal cortex (LEC) and local hippocampal network computations are sufficient to support this function. Following the finding that spatial firing was partly preserved in MEC-lesioned rats, we tested whether the MEC is necessary for the temporal organization of spike timing within the place field. Hippocampal place cells that are activated along the rat’s trajectory through space are thought to be linked into synaptically connected neuronal sequences via a mechanisms referred to as hippocampal theta phase precession (hTPP). Theta phase precession reflects the temporal distribution of APs within each place field with reference to the local field potential (LFP) oscillation at theta frequency (4 to 10 Hz). We found that hTPP was strongly disrupted in MEC-lesioned rats, demonstrating that the MEC is necessary for the temporal organization of hippocampal spatial firing. Cognitive functions that rely on sequentially activated place cells are thus likely to rely on the MEC. In summary, the presented data demonstrate that the contribution of the MEC to hippocampal spatial coding is less predominant than postulated by contemporary theories of hippocampo-entorhinal function. In addition, the findings suggest that the MEC, which is widely considered a spatial processing center of the brain, supports memory through the temporal organization of hippocampal spatial firing

Embodying a Computational Model of Hippocampal Replay for Robotic Reinforcement Learning

Hippocampal reverse replay has been speculated to play an important role in biological reinforcement learning since its discovery over a decade ago. Whilst a number of computational models have recently emerged in an attempt to understand the dynamics of hippocampal replay, there has been little progress in testing and implementing these models in real-world robotics settings. Presented first in this body of work then is a bio-inspired hippocampal CA3 network model. It runs in real-time to produce reverse replays of recent spatio-temporal sequences, represented as place cell activities, in a robotic spatial navigation task. The model is based on two very recent computational models of hippocampal reverse replay. An analysis of these models show that, in their original forms, they are each insufficient for effective performance when applied to a robot. As such, choosing particular elements from each allows for a computational model that is sufficient for application in a robotic task. Having a model of reverse replay applied successfully in a robot provides the groundwork necessary for testing the ways in which reverse replay contributes to reinforcement learning. The second portion of the work presented here builds on a previous reinforcement learning neural network model of a basic hippocampal-striatal circuit using a three-factor learning rule. By integrating reverse replays into this reinforcement learning model, results show that reverse replay, with its ability to replay the recent trajectory both in the hippocampal circuit and the striatal circuit, can speed up the learning process. In addition, for situations where the original reinforcement learning model performs poorly, such as when its time dynamics do not sufficiently store enough of the robot's behavioural history for effective learning, the reverse replay model can compensate for this by replaying the recent history. These results are inline with experimental findings showing that disruption of awake hippocampal replay events severely diminishes, but does not entirely eliminate, reinforcement learning. This work provides possible insights into the important role that reverse replays could contribute to mnemonic function, and reinforcement learning in particular; insights that could benefit the robotic, AI, and neuroscience communities. However, there is still much to be done. How reverse replays are initiated is still an ongoing research problem, for instance. Furthermore, the model presented here generates place cells heuristically, but there are computational models tackling the problem of how hippocampal cells such as place cells, but also grid cells and head direction cells, emerge. This leads to the pertinent question of asking how these models, which make assumptions about their network architectures and dynamics, could integrate with the computational models of hippocampal replay which make their own assumptions on network architectures and dynamics