Pattern separation in the dentate gyrus: a role for the CA3 backprojection

Dendrites of dentate gyrus granule cells contribute to pattern separation by controlling sparsity

The hippocampus plays a key role in pattern separation, the process of transforming similar incoming information to highly dissimilar, nonverlapping representations. Sparse firing granule cells (GCs) in the dentate gyrus (DG) have been proposed to undertake this computation, but little is known about which of their properties influence pattern separation. Dendritic atrophy has been reported in diseases associated with pattern separation deficits, suggesting a possible role for dendrites in this phenomenon. To investigate whether and how the dendrites of GCs contribute to pattern separation, we build a simplified, biologically relevant, computational model of the DG. Our model suggests that the presence of GC dendrites is associated with high pattern separation efficiency while their atrophy leads to increased excitability and performance impairments. These impairments can be rescued by restoring GC sparsity to control levels through various manipulations. We predict that dendrites contribute to pattern separation as a mechanism for controlling sparsity. © 2016 The Authors Hippocampus Published by Wiley Periodicals, Inc.

Targeted deletion of AKAP7 in dentate granule cells impairs spatial discrimination

Protein Kinase A (PKA) mediates synaptic plasticity and is widely implicated in learning and memory. The hippocampal dentate gyrus (DG) is thought to be responsible for processing and encoding distinct contextual associations in response to highly similar inputs. The mossy fiber (MF) axons of the dentate granule cells convey strong excitatory drive to CA3 pyramidal neurons and express presynaptic, PKA-dependent forms of plasticity. Here, we demonstrate an essential role for the PKA anchoring protein, AKAP7, in mouse MF axons and terminals. Genetic ablation of AKAP7 specifically from dentate granule cells results in disruption of MF-CA3 LTP directly initiated by cAMP, and the AKAP7 mutant mice are selectively deficient in pattern separation behaviors. Our results suggest that the AKAP7/PKA complex in the MF projections plays an essential role in synaptic plasticity and contextual memory formation.

DOI:http://dx.doi.org/10.7554/eLife.20695.001

Adult-born dentate granule cells show a critical period of dendritic reorganization and are distinct from developmentally born cells

Adult-born dentate granule cells (abGCs) exhibit a critical developmental phase during function integration. The time window of this phase is debated and whether abGCs become indistinguishable from developmentally born mature granule cells (mGCs) is uncertain. We analyzed complete dendritic reconstructions from abGCs and mGCs using viral labeling. AbGCs from 21-77 days post intrahippocampal injection (dpi) exhibited comparable dendritic arbors, suggesting that structural maturation precedes functional integration. In contrast, significant structural differences were found compared to mGCs: AbGCs had more curved dendrites, more short terminal segments, a different branching pattern, and more proximal terminal branches. Morphological modeling attributed these differences to developmental dendritic pruning and postnatal growth of the dentate gyrus. We further correlated GC morphologies with the responsiveness to unilateral medial perforant path stimulation using the immediate-early gene Arc as a marker of synaptic activation. Only abGCs at 28 and 35 dpi but neither old abGCs nor mGCs responded to stimulation with a remodeling of their dendritic arbor. Summarized, abGCs stay distinct from mGCs and their dendritic arbor can be shaped by afferent activity during a narrow critical time window.

The enigmatic mossy cell of the dentate gyrus

Mossy cells comprise a large fraction of the cells in the hippocampal dentate gyrus, suggesting that their function in this region is important. They are vulnerable to ischaemia, traumatic brain injury and seizures, and their loss could contribute to dentate gyrus dysfunction in such conditions. Mossy cell function has been unclear because these cells innervate both glutamatergic and GABAergic neurons within the dentate gyrus, contributing to a complex circuitry. It has also been difficult to directly and selectively manipulate mossy cells to study their function. In light of the new data generated using methods to preferentially eliminate or activate mossy cells in mice, it is timely to ask whether mossy cells have become any less enigmatic than they were in the past.

Apolipoprotein E4 Causes Age-Dependent Disruption of Slow Gamma Oscillations during Hippocampal Sharp-Wave Ripples

Apolipoprotein (apo) E4 is the major genetic risk factor for Alzheimer's disease (AD), but the mechanism by which it causes cognitive decline is unclear. In knockin (KI) mice, human apoE4 causes age-dependent learning and memory impairments and degeneration of GABAergic interneurons in the hippocampal dentate gyrus. Here we report two functional apoE4-KI phenotypes involving sharp-wave ripples (SWRs), hippocampal network events critical for memory processes. Aged apoE4-KI mice had fewer SWRs than apoE3-KI mice and significantly reduced slow gamma activity during SWRs. Elimination of apoE4 in GABAergic interneurons, which prevents learning and memory impairments, rescued SWR-associated slow gamma activity but not SWR abundance in aged mice. SWR abundance was reduced similarly in young and aged apoE4-KI mice; however, the full SWR-associated slow gamma deficit emerged only in aged apoE4-KI mice. These results suggest that progressive decline of interneuron-enabled slow gamma activity during SWRs critically contributes to apoE4-mediated learning and memory impairments. VIDEO ABSTRACT.

Taxonomic Separation of Hippocampal Networks: Principal Cell Populations and Adult Neurogenesis

While many differences in hippocampal anatomy have been described between species, it is typically not clear if they are specific to a particular species and related to functional requirements or if they are shared by species of larger taxonomic units. Without such information, it is difficult to infer how anatomical differences may impact on hippocampal function, because multiple taxonomic levels need to be considered to associate behavioral and anatomical changes. To provide information on anatomical changes within and across taxonomic ranks, we present a quantitative assessment of hippocampal principal cell populations in 20 species or strain groups, with emphasis on rodents, the taxonomic group that provides most animals used in laboratory research. Of special interest is the importance of adult hippocampal neurogenesis (AHN) in species-specific adaptations relative to other cell populations. Correspondence analysis of cell numbers shows that across taxonomic units, phylogenetically related species cluster together, sharing similar proportions of principal cell populations. CA3 and hilus are strong separators that place rodent species into a tight cluster based on their relatively large CA3 and small hilus while non-rodent species (including humans and non-human primates) are placed on the opposite side of the spectrum. Hilus and CA3 are also separators within rodents, with a very large CA3 and rather small hilar cell populations separating mole-rats from other rodents that, in turn, are separated from each other by smaller changes in the proportions of CA1 and granule cells. When adult neurogenesis is included, the relatively small populations of young neurons, proliferating cells and hilar neurons become main drivers of taxonomic separation within rodents. The observations provide challenges to the computational modeling of hippocampal function, suggest differences in the organization of hippocampal information streams in rodent and non-rodent species, and support emerging concepts of functional and structural interactions between CA3 and the dentate gyrus.

Corruption of the dentate gyrus by "dominant" granule cells: Implications for dentate gyrus function in health and disease

The dentate gyrus (DG) and area CA3 of the hippocampus are highly organized lamellar structures which have been implicated in specific cognitive functions such as pattern separation and pattern completion. Here we describe how the anatomical organization and physiology of the DG and CA3 are consistent with structures that perform pattern separation and completion. We then raise a new idea related to the complex circuitry of the DG and CA3 where CA3 pyramidal cell 'backprojections' play a potentially important role in the sparse firing of granule cells (GCs), considered important in pattern separation. We also propose that GC axons, the mossy fibers, already known for their highly specialized structure, have a dynamic function that imparts variance--'mossy fiber variance'--which is important to pattern separation and completion. Computational modeling is used to show that when a subset of GCs become 'dominant,' one consequence is loss of variance in the activity of mossy fiber axons and a reduction in pattern separation and completion in the model. Empirical data are then provided using an example of 'dominant' GCs--subsets of GCs that develop abnormally and have increased excitability. Notably, these abnormal GCs have been identified in animal models of disease where DG-dependent behaviors are impaired. Together these data provide insight into pattern separation and completion, and suggest that behavioral impairment could arise from dominance of a subset of GCs in the DG-CA3 network.

Hippocampal neurogenesis: Learning to remember

Alzheimer's disease, the most prevalent form of dementia in the elderly, is characterized by progressive memory loss and cognitive dysfunction. It has become increasingly clear that while neuronal cell loss in the entorhinal cortex and hippocampus occurs in Alzheimer's disease, it is preceded by a long period of deficits in the connectivity of the hippocampal formation that contributes to the vulnerability of these circuits. Hippocampal neurogenesis plays a role in the maintenance and function of the dentate gyrus and hippocampal circuitry. This review will examine the evidence suggesting that hippocampal neurogenesis plays a role in cognitive function that is affected in Alzheimer's disease, will discuss the cognitive assessments used for the detection of Alzheimer's disease in humans and rodent models of familial Alzheimer's disease, and their value for unraveling the mechanism underlying the development of cognitive impairments and dementia.

Tracking the flow of hippocampal computation: Pattern separation, pattern completion, and attractor dynamics

Classic computational theories of the mnemonic functions of the hippocampus ascribe the processes of pattern separation to the dentate gyrus (DG) and pattern completion to the CA3 region. Until the last decade, the large majority of single-unit studies of the hippocampus in behaving animals were from the CA1 region. The lack of data from the DG, CA3, and the entorhinal inputs to the hippocampus severely hampered the ability to test these theories with neurophysiological techniques. The past ten years have seen a major increase in the recordings from the CA3 region and the medial entorhinal cortex (MEC), with an increasing (but still limited) number of experiments from the lateral entorhinal cortex (LEC) and DG. This paper reviews a series of studies in a local-global cue mismatch (double-rotation) experiment in which recordings were made from cells in the anterior thalamus, MEC, LEC, DG, CA3, and CA1 regions. Compared to the standard cue environment, the change in the DG representation of the cue-mismatch environment was greater than the changes in its entorhinal inputs, providing support for the theory of pattern separation in the DG. In contrast, the change in the CA3 representation of the cue-mismatch environment was less than the changes in its entorhinal and DG inputs, providing support for a pattern completion/error correction function of CA3. The results are interpreted in terms of continuous attractor network models of the hippocampus and the relationship of these models to pattern separation and pattern completion theories. Whereas DG may perform an automatic pattern separation function, the attractor dynamics of CA3 allow it to perform a pattern separation or pattern completion function, depending on the nature of its inputs and the relative strength of the internal attractor dynamics.

Neurogenesis paradoxically decreases both pattern separation and memory interference

The hippocampus has been the focus of memory research for decades. While the functional role of this structure is not fully understood, it is widely recognized as being vital for rapid yet accurate encoding and retrieval of associative memories. Since the discovery of adult hippocampal neurogenesis in the dentate gyrus by Altman and Das in the 1960's, many theories and models have been put forward to explain the functional role it plays in learning and memory. These models postulate different ways in which new neurons are introduced into the dentate gyrus and their functional importance for learning and memory. Few if any previous models have incorporated the unique properties of young adult-born dentate granule cells and the developmental trajectory. In this paper, we propose a novel computational model of the dentate gyrus that incorporates the developmental trajectory of the adult-born dentate granule cells, including changes in synaptic plasticity, connectivity, excitability and lateral inhibition, using a modified version of the Restricted Boltzmann machine. Our results show superior performance on memory reconstruction tasks for both recent and distally learned items, when the unique characteristics of young dentate granule cells are taken into account. Even though the hyperexcitability of the young neurons generates more overlapping neural codes, reducing pattern separation, the unique properties of the young neurons nonetheless contribute to reducing retroactive and proactive interference, at both short and long time scales. The sparse connectivity is particularly important for generating distinct memory traces for highly overlapping patterns that are learned within the same context.

Involvement of Adult Hippocampal Neurogenesis in Learning and Forgetting

Adult hippocampal neurogenesis is a process involving the continuous generation of newborn neurons in the hippocampus of adult animals. Mounting evidence has suggested that hippocampal neurogenesis contributes to some forms of hippocampus-dependent learning and memory; however, the detailed mechanism concerning how this small number of newborn neurons could affect learning and memory remains unclear. In this review, we discuss the relationship between adult-born neurons and learning and memory, with a highlight on recently discovered potential roles of neurogenesis in pattern separation and forgetting.

A Bayesian context fear learning algorithm/automaton

Contextual fear conditioning is thought to involve the synaptic plasticity-dependent establishment in hippocampus of representations of to-be-conditioned contexts which can then become associated with USs in the amygdala. A conceptual and computational model of this process is proposed in which contextual attributes are assumed to be sampled serially and randomly during contextual exposures. Given this assumption, moment-to-moment information about such attributes will often be quite different from one exposure to another and, in particular, between exposures during which representations are created, exposures during which conditioning occurs, and during recall sessions. This presents challenges to current conceptual models of hippocampal function. In order to meet these challenges, our model's hippocampus was made to operate in different modes during representation creation and recall, and non-hippocampal machinery was constructed that controlled these hippocampal modes. This machinery uses a comparison between contextual information currently observed and information associated with existing hippocampal representations of familiar contexts to compute the Bayesian Weight of Evidence that the current context is (or is not) a known one, and it uses this value to assess the appropriateness of creation or recall modes. The model predicts a number of known phenomena such as the immediate shock deficit, spurious fear conditioning to contexts that are absent but similar to actually present ones, and modulation of conditioning by pre-familiarization with contexts. It also predicts a number of as yet unknown phenomena.

Dentate Gyrus circuitry features improve performance of sparse approximation algorithms

Memory-related activity in the Dentate Gyrus (DG) is characterized by sparsity. Memory representations are seen as activated neuronal populations of granule cells, the main encoding cells in DG, which are estimated to engage 2–4% of the total population. This sparsity is assumed to enhance the ability of DG to perform pattern separation, one of the most valuable contributions of DG during memory formation. In this work, we investigate how features of the DG such as its excitatory and inhibitory connectivity diagram can be used to develop theoretical algorithms performing Sparse Approximation, a widely used strategy in the Signal Processing field. Sparse approximation stands for the algorithmic identification of few components from a dictionary that approximate a certain signal. The ability of DG to achieve pattern separation by sparsifing its representations is exploited here to improve the performance of the state of the art sparse approximation algorithm “Iterative Soft Thresholding” (IST) by adding new algorithmic features inspired by the DG circuitry. Lateral inhibition of granule cells, either direct or indirect, via mossy cells, is shown to enhance the performance of the IST. Apart from revealing the potential of DG-inspired theoretical algorithms, this work presents new insights regarding the function of particular cell types in the pattern separation task of the DG.

Bidirectional global spontaneous network activity precedes the canonical unidirectional circuit organization in the developing hippocampus

Spontaneous network activity is believed to sculpt developing neural circuits. Spontaneous giant depolarizing potentials (GDPs) were first identified with single-cell recordings from rat CA3 pyramidal neurons, but here we identify and characterize a large-scale spontaneous network activity we term global network activation (GNA) in the developing mouse hippocampal slices, which is measured macroscopically by fast voltage-sensitive dye imaging. The initiation and propagation of GNA in the mouse is largely GABA-independent and dominated by glutamatergic transmission via AMPA receptors. Despite the fact that signal propagation in the adult hippocampus is strongly unidirectional through the canonical trisynaptic circuit (dentate gyrus [DG] to CA3 to CA1), spontaneous GNA in the developing hippocampus originates in distal CA3 and propagates both forward to CA1 and backward to DG. Photostimulation-evoked GNA also shows prominent backward propagation in the developing hippocampus from CA3 to DG. Mouse GNA is strongly correlated to electrophysiological recordings of highly localized single-cell and local field potential events. Photostimulation mapping of neural circuitry demonstrates that the enhancement of local circuit connections to excitatory pyramidal neurons occurs over the same time course as GNA and reveals the underlying pathways accounting for GNA backward propagation from CA3 to DG. The disappearance of GNA coincides with a transition to the adult-like unidirectional circuit organization at about 2 weeks of age. Taken together, our findings strongly suggest a critical link between GNA activity and maturation of functional circuit connections in the developing hippocampus.

A compressed sensing perspective of hippocampal function

Hippocampus is one of the most important information processing units in the brain. Input from the cortex passes through convergent axon pathways to the downstream hippocampal subregions and, after being appropriately processed, is fanned out back to the cortex. Here, we review evidence of the hypothesis that information flow and processing in the hippocampus complies with the principles of Compressed Sensing (CS). The CS theory comprises a mathematical framework that describes how and under which conditions, restricted sampling of information (data set) can lead to condensed, yet concise, forms of the initial, subsampled information entity (i.e., of the original data set). In this work, hippocampus related regions and their respective circuitry are presented as a CS-based system whose different components collaborate to realize efficient memory encoding and decoding processes. This proposition introduces a unifying mathematical framework for hippocampal function and opens new avenues for exploring coding and decoding strategies in the brain.

Adult neurogenesis in the mammalian hippocampus: why the dentate gyrus?

In the adult mammalian brain, newly generated neurons are continuously incorporated into two networks: interneurons born in the subventricular zone migrate to the olfactory bulb, whereas the dentate gyrus (DG) of the hippocampus integrates locally born principal neurons. That the rest of the mammalian brain loses significant neurogenic capacity after the perinatal period suggests that unique aspects of the structure and function of DG and olfactory bulb circuits allow them to benefit from the adult generation of neurons. In this review, we consider the distinctive features of the DG that may account for it being able to profit from this singular form of neural plasticity. Approaches to the problem of neurogenesis are grouped as "bottom-up," where the phenotype of adult-born granule cells is contrasted to that of mature developmentally born granule cells, and "top-down," where the impact of altering the amount of neurogenesis on behavior is examined. We end by considering the primary implications of these two approaches and future directions.

The hippocampus of the eastern rock sengi: cytoarchitecture, markers of neuronal function, principal cell numbers, and adult neurogenesis

The brains of sengis (elephant shrews, order Macroscelidae) have long been known to contain a hippocampus that in terms of allometric progression indices is larger than that of most primates and equal in size to that of humans. In this report, we provide descriptions of hippocampal cytoarchitecture in the eastern rock sengi (Elephantulus myurus), of the distributions of hippocampal calretinin, calbindin, parvalbumin, and somatostatin, of principal neuron numbers, and of cell numbers related to proliferation and neuronal differentiation in adult hippocampal neurogenesis. Sengi hippocampal cytoarchitecture is an amalgamation of characters that are found in CA1 of, e.g., guinea pig and rabbits and in CA3 and dentate gyrus of primates. Correspondence analysis of total cell numbers and quantitative relations between principal cell populations relate this sengi to macaque monkeys and domestic pigs, and distinguish the sengi from distinct patterns of relations found in humans, dogs, and murine rodents. Calretinin and calbindin are present in some cell populations that also express these proteins in other species, e.g., interneurons at the stratum oriens/alveus border or temporal hilar mossy cells, but neurons expressing these markers are often scarce or absent in other layers. The distributions of parvalbumin and somatostatin resemble those in other species. Normalized numbers of PCNA+ proliferating cells and doublecortin-positive (DCX+) differentiating cells of neuronal lineage fall within the overall ranges of murid rodents, but differed from three murid species captured in the same habitat in that fewer DCX+ cells relative to PCNA+ were observed. The large and well-differentiated sengi hippocampus is not accompanied by correspondingly sized cortical and subcortical limbic areas that are the main hippocampal sources of afferents and targets of efferents. This points to intrinsic hippocampal information processing as the selective advantage of the large sengi hippocampus.

The influence of ectopic migration of granule cells into the hilus on dentate gyrus-CA3 function

Postnatal neurogenesis of granule cells (GCs) in the dentate gyrus (DG) produces GCs that normally migrate from the subgranular zone to the GC layer. However, GCs can mismigrate into the hilus, the opposite direction. Previous descriptions of these hilar ectopic GCs (hEGCs) suggest that they are rare unless there are severe seizures. However, it is not clear if severe seizures are required, and it also is unclear if severe seizures are responsible for the abnormalities of hEGCs, which include atypical dendrites and electrophysiological properties. Here we show that large numbers of hEGCs develop in a transgenic mouse without severe seizures. The mice have a deletion of BAX, which normally regulates apoptosis. Surprisingly, we show that hEGCs in the BAX^-/- mouse have similar abnormalities as hEGCs that arise after severe seizures. We next asked if there are selective effects of hEGCs, i.e., whether a robust population of hEGCs would have any effect on the DG if they were induced without severe seizures. Indeed, this appears to be true, because it has been reported that BAX^-/- mice have defects in a behavior that tests pattern separation, which depends on the DG. However, inferring functional effects of hEGCs is difficult in mice with a constitutive BAX deletion because there is decreased apoptosis in and outside the DG. Therefore, a computational model of the normal DG and hippocampal subfield CA3 was used. Adding a small population of hEGCs (5% of all GCs), with characteristics defined empirically, was sufficient to disrupt a simulation of pattern separation and completion. Modeling results also showed that effects of hEGCs were due primarily to “backprojections” of CA3 pyramidal cell axons to the hilus. The results suggest that hEGCs can develop for diverse reasons, do not depend on severe seizures, and a small population of hEGCs may impair DG-dependent function.

A process analysis of the CA3 subregion of the hippocampus

From a behavioral perspective, the CA3a,b subregion of the hippocampus plays an important role in the encoding of new spatial information within short-term memory with a duration of seconds and minutes. This can easily be observed in tasks that require rapid encoding, novelty detection, one-trial short-term or working memory, and one-trial cued recall primarily for spatial information. These are tasks that have been assumed to reflect the operations of episodic memory and require interactions between CA3a,b and the dentate gyrus (DG) via mossy fiber inputs into the CA3a,b. The CA3a,b is also important for encoding of spatial information requiring the acquisition of arbitrary and relational associations. All these tasks are assumed to operate within an autoassociative network function of the CA3 region. The CA3a,b also supports retrieval of short-term memory information based on a spatial pattern completion process. Based on afferent inputs into CA3a,b from the DG via mossy fibers and afferents from the entorhinal cortex into CA3a,b as well as reciprocal connections with the septum, CA3a,b can bias the process of encoding utilizing the operation of spatial pattern separation and the process of retrieval utilizing the operation of pattern completion. The CA3a,b also supports sequential processing of information in cooperation with CA1 based on the Schaffer collateral output from CA3a,b to CA1. The CA3c function is in part based on modulation of the DG in supporting pattern separation processes.

Age-related changes in place learning for adjacent and separate locations

The effect of spatial interference on place learning was examined in young and old rats. Rats were trained on a radial 8-arm maze to discriminate between a reward arm and a nonreward arm that either were adjacent to each other (high spatial interference) or separated by a distance of 2 arm positions (low spatial interference). Each rat was tested until reaching a criterion of 9 correct choices out of 10 trials across 2 consecutive days. The data revealed that old rats committed significantly more errors than young rats when the arms were adjacent and spatial interference was high. However, no group differences were detected when the arms were separated and spatial interference was low. Group differences also were not detected in the number of trials required to reach the learning criterion in either condition. The results indicate that age-related brain changes result in increased errors during place learning, particularly when spatial interference is high, suggesting that spatial pattern separation might be less efficient in aged animals.

Functional circuits of new neurons in the dentate gyrus

The hippocampus is crucial for memory formation. New neurons are added throughout life to the hippocampal dentate gyrus (DG), a brain area considered important for differential storage of similar experiences and contexts. To better understand the functional contribution of adult neurogenesis to pattern separation processes, we recently used a novel synapse specific trans-neuronal tracing approach to identify the (sub) cortical inputs to new dentate granule cells (GCs). It was observed that newly born neurons receive sequential innervation from structures important for memory function. Initially, septal-hippocampal cells provide input to new neurons, including transient innervation from mature GCs as well as direct feedback from area CA3 pyramidal neurons. After about 1 month perirhinal (PRH) and lateral entorhinal cortex (LEC), brain areas deemed relevant to integration of novel sensory and environmental information, become substantial input to new GCs. Here, we review the developmental time-course and proposed functional relevance of new neurons, within the context of their unique neural circuitry.

Hilar mossy cells of the dentate gyrus: a historical perspective

The circuitry of the dentate gyrus (DG) of the hippocampus is unique compared to other hippocampal subfields because there are two glutamatergic principal cells instead of one: granule cells, which are the vast majority of the cells in the DG, and the so-called “mossy cells.” The distinctive appearance of mossy cells, the extensive divergence of their axons, and their vulnerability to excitotoxicity relative to granule cells has led to a great deal of interest in mossy cells. Nevertheless, there is no consensus about the normal functions of mossy cells and the implications of their vulnerability. There even seems to be some ambiguity about exactly what mossy cells are. Here we review initial studies of mossy cells, characteristics that define them, and suggest a practical definition to allow investigators to distinguish mossy cells from other hilar neurons even if all morphological and physiological information is unavailable due to technical limitations of their experiments. In addition, hypotheses are discussed about the role of mossy cells in the DG network, reasons for their vulnerability and their implications for disease.

Brain-derived neurotrophic factor-estrogen interactions in the hippocampal mossy fiber pathway: implications for normal brain function and disease

The neurotrophin brain-derived neurotrophic factor (BDNF) and the steroid hormone estrogen exhibit potent effects on hippocampal neurons during development and in adulthood. BDNF and estrogen have also been implicated in the etiology of diverse types of neurological disorders or psychiatric illnesses, or have been discussed as potentially important in treatment. Although both are typically studied independently, it has been suggested that BDNF mediates several of the effects of estrogen in the hippocampus, and that these interactions play a role in the normal brain as well as disease. Here we focus on the mossy fiber (MF) pathway of the hippocampus, a critical pathway in normal hippocampal function, and a prime example of a location where numerous studies support an interaction between BDNF and estrogen in the rodent brain. We first review the temporal and spatially regulated expression of BDNF and estrogen in the MFs, as well as their receptors. Then we consider the results of studies that suggest that 17β-estradiol alters hippocampal function by its influence on BDNF expression in the MF pathway. We also address the hypothesis that estrogen influences the hippocampus by mechanisms related not only to the mature form of BDNF, acting at trkB receptors, but also by regulating the precursor, proBDNF, acting at p75NTR. We suggest that the interactions between BDNF and 17β-estradiol in the MFs are potentially important in the normal function of the hippocampus, and have implications for sex differences in functions that depend on the MFs and in diseases where MF plasticity has been suggested to play an important role, Alzheimer's disease, epilepsy and addiction.

Updating the lamellar hypothesis of hippocampal organization

Andersen et al. (1971) proposed that excitatory activity in the entorhinal cortex propagates topographically to the dentate gyrus, and on through a "trisynaptic circuit" lying within transverse hippocampal "slices" or "lamellae." In this way, a relatively simple structure might mediate complex functions in a manner analogous to the way independent piano keys can produce a nearly infinite variety of unique outputs. The lamellar hypothesis derives primary support from the "lamellar" distribution of dentate granule cell axons (the mossy fibers), which innervate dentate hilar neurons and area CA3 pyramidal cells and interneurons within the confines of a thin transverse hippocampal segment. Following the initial formulation of the lamellar hypothesis, anatomical studies revealed that unlike granule cells, hilar mossy cells, CA3 pyramidal cells, and Layer II entorhinal cells all form axonal projections that are more divergent along the longitudinal axis than the clearly "lamellar" mossy fiber pathway. The existence of pathways with "translamellar" distribution patterns has been interpreted, incorrectly in our view, as justifying outright rejection of the lamellar hypothesis (Amaral and Witter, 1989). We suggest that the functional implications of longitudinally projecting axons depend not on whether they exist, but on what they do. The observation that focal granule cell layer discharges normally inhibit, rather than excite, distant granule cells suggests that longitudinal axons in the dentate gyrus may mediate "lateral" inhibition and define lamellar function, rather than undermine it. In this review, we attempt a reconsideration of the evidence that most directly impacts the physiological concept of hippocampal lamellar organization.

Why trace and delay conditioning are sometimes (but not always) hippocampal dependent: a computational model

A recurrent-network model provides a unified account of the hippocampal region in mediating the representation of temporal information in classical eyeblink conditioning. Much empirical research is consistent with a general conclusion that delay conditioning (in which the conditioned stimulus CS and unconditioned stimulus US overlap and co-terminate) is independent of the hippocampal system, while trace conditioning (in which the CS terminates before US onset) depends on the hippocampus. However, recent studies show that, under some circumstances, delay conditioning can be hippocampal-dependent and trace conditioning can be spared following hippocampal lesion. Here, we present an extension of our prior trial-level models of hippocampal function and stimulus representation that can explain these findings within a unified framework. Specifically, the current model includes adaptive recurrent collateral connections that aid in the representation of intra-trial temporal information. With this model, as in our prior models, we argue that the hippocampus is not specialized for conditioned response timing, but rather is a general-purpose system that learns to predict the next state of all stimuli given the current state of variables encoded by activity in recurrent collaterals. As such, the model correctly predicts that hippocampal involvement in classical conditioning should be critical not only when there is an intervening trace interval, but also when there is a long delay between CS onset and US onset. Our model simulates empirical data from many variants of classical conditioning, including delay and trace paradigms in which the length of the CS, the inter-stimulus interval, or the trace interval is varied. Finally, we discuss model limitations, future directions, and several novel empirical predictions of this temporal processing model of hippocampal function and learning.

The operation of pattern separation and pattern completion processes associated with different attributes or domains of memory

Pattern separation and pattern completion processes are central to how the brain processes information in an efficient manner. Research into these processes is escalating and deficient pattern separation is being implicated in a wide array of genetic disorders as well as in neurocognitive aging. Despite the quantity of research, there remains a controversy as to precisely which behavioral paradigms should be used to best tap into pattern separation and pattern completion processes, as well as to what constitute legitimate outcome measures reflecting impairments in pattern separation and pattern completion. This review will discuss a theory based on multiple memory systems that provides a framework upon which behavioral tasks can be designed and their results interpreted. Furthermore, this review will discuss the nature of pattern separation and pattern completion and extend these processes outside the hippocampus and across all domains of information processing. After these discussions, an optimal strategy for designing behavioral paradigms to evaluate pattern separation and pattern completion processes will be provided.

Generalization through the recurrent interaction of episodic memories: a model of the hippocampal system

In this article, we present a perspective on the role of the hippocampal system in generalization, instantiated in a computational model called REMERGE (recurrency and episodic memory results in generalization). We expose a fundamental, but neglected, tension between prevailing computational theories that emphasize the function of the hippocampus in pattern separation (Marr, 1971; McClelland, McNaughton, & O'Reilly, 1995), and empirical support for its role in generalization and flexible relational memory (Cohen & Eichenbaum, 1993; Eichenbaum, 1999). Our account provides a means by which to resolve this conflict, by demonstrating that the basic representational scheme envisioned by complementary learning systems theory (McClelland et al., 1995), which relies upon orthogonalized codes in the hippocampus, is compatible with efficient generalization-as long as there is recurrence rather than unidirectional flow within the hippocampal circuit or, more widely, between the hippocampus and neocortex. We propose that recurrent similarity computation, a process that facilitates the discovery of higher-order relationships between a set of related experiences, expands the scope of classical exemplar-based models of memory (e.g., Nosofsky, 1984) and allows the hippocampus to support generalization through interactions that unfold within a dynamically created memory space.

Functional differences in the backward shifts of CA1 and CA3 place fields in novel and familiar environments

Insight into the processing dynamics and other neurophysiological properties of different hippocampal subfields is critically important for understanding hippocampal function. In this study, we compared shifts in the center of mass (COM) of CA3 and CA1 place fields in a familiar and completely novel environment. Place fields in CA1 and CA3 were simultaneously recorded as rats ran along a closed loop track in a familiar room followed by a session in a completely novel room. This process was repeated each day over a 4-day period. CA3 place fields shifted backward (opposite to the direction of motion of the rat) only in novel environments. This backward shift gradually diminished across days, as the novel environment became more familiar with repeated exposures. Conversely, CA1 place fields shifted backward across all days in both familiar and novel environments. Prior studies demonstrated that CA1 place fields on average do not exhibit a backward shift during the first exposure to an environment in which the familiar cues are rearranged into a novel configuration, although CA3 place fields showed a strong backward shift. Under the completely novel conditions of the present study, no dissociation was observed between CA3 and CA1 during the first novel session (although a strong dissociation was observed in the familiar sessions and the later novel sessions). In summary, this is the first study to use simultaneous recordings in CA1 and CA3 to compare place field COM shift and other associated properties in truly novel and familiar environments. This study further demonstrates functional differentiation between CA1 and CA3 as the plasticity of CA1 place fields is affected differently by exposure to a completely novel environment in comparison to an altered, familiar environment, whereas the plasticity of CA3 place fields is affected similarly during both types of environmental novelty.

Introduction to the fractality principle of consciousness and the sentyon postulate

Recently, consciousness research has gained much attention. Indeed, the question at stake is significant: why is the brain not just a computing device, but generates a perception from within? Ambitious endeavors trying to simulate the entire human brain assume that the algorithm will do the trick: as soon as we assemble the brain in a computer and increase the number of operations per time, consciousness will emerge by itself. I disagree with this simplistic representation. My argument emerges from the "atomism paradox": the irreducible space of the consciously perceived world, the endospace is incompatible with the reducible and decomposable architecture of the brain or a computer. I will first discuss the fundamental challenges in current consciousness models and then propose a new model based on the fractality principle: "the whole is in each of its parts". This new model copes with the atomism paradox by implementing an iterative mapping of information from higher order brain structures to smaller scales on the cellular and molecular level, which I will refer to as "fractalization". This information fractalization gives rise to a new form of matter that is conscious ("bright matter"). Bright matter is composed of conscious particles or units named "sentyons". The internal fractality of these sentyons will close a loop (the "psychic loop") in a recurrent fractal neural network (RFNN) that allows for continuous and complete information transformation and sharing between higher order brain structures and the endpoint substrate of consciousness at the molecular level.