Temporal encoding of place sequences by hippocampal cell assemblies

Path planning in the hippocampo-prefrontal cortex pathway: an adaptive model based receding horizon planner

Four characteristic properties of human path planning strategy are course and fine planning, supervised planning, adaptation and robustness, and complexity reduction. These four characteristics are also observed in "model predictive controller" and its modified version, "receding horizon planner". We hypothesize that the human brain performs path planning tasks, literally like a receding horizon planner. The similarities between human brain and a receding horizon planner are: (1) hippocampus contains the course model and the parietal cortex is responsible for the fine model. (2) Replanning and trajectory tuning using the visual data in parietal cortex and prefrontal cortex is exploited in an adaptive restricted receding horizon. Prefrontal cortex plays the role of the supervisor. (3) Adjusting the sampling time of the planner is implemented based on changes in the complexity of the environment and tasks. This is in fact, the adaptation, which exists both in human behavior and in receding horizon planner. (4) The brain simplifies path-finding problems to reduce computational loads, exactly similar to what engineering controllers intend to do. The visual data is smoothed by clustering of obstacles, before performing any computational task. Finally, we have discussed the consequence of our hypothesis in Alzheimer disease as an optimal planning disorder. Based on some experimental data, Alzheimer patients have a reduced predictive horizon, making the system less robust and exposed to hazardous conditions in sophisticated environments. Patients with mild Alzheimer disease have little trouble with simple optimization problems; working memory of the prefrontal cortex is sufficient for this purpose. However, in complicated tasks, the brain needs huge extended memory. This memory is available through hippocampo-prefrontal pathway, which is to some extent disturbed in Alzheimer patients. We suggest that this fact may be a basis for future experimental diagnosis tests. We predict that Alzheimer patients should have problems with planning for far future; because they have a weak memory, insufficient for heavy optimization tasks, such as moving through moving obstacles in a dynamic environment. Alzheimer disease could be early detected by designing new tests in which the ability of patients to predict the future events is checked. These tests could be accompanied with a multi-step optimization problem. We believe that paying attention to this opinion may provide a good help in diagnosing Alzheimer disease in earlier stages. Surely, experimental studies are needed to validate our hypothesis.

Which computational mechanisms operate in the hippocampus during novelty detection?

A fundamental property of adaptive behavior is the ability to rapidly distinguish what is novel from what is familiar in our environment. Empirical evidence and computational work have provided biologically plausible models of the neural substrate and mechanisms underlying the coding of stimulus novelty in the perirhinal cortex. In this article, we highlight the importance of a different category of novelty, namely associative novelty, which has received relatively little attention, despite its clear ecological importance. While previous studies in both animals and humans have documented hippocampal responses in relation to associative novelty, a key issue concerning the computations underlying these novelty signals has not been previously addressed. We argue that this question has importance not only for our understanding of novelty processing, but also for advancing our knowledge of the fundamental computational operations performed by the hippocampus. We suggest a different approach to this problem, and discuss recent evidence supporting the hypothesis that the hippocampus operates as a comparator during the processing of associative novelty, generating mismatch/novelty signals when prior predictions are violated by sensory reality. We also draw on conceptual similarities between associative novelty and contextual novelty to suggest that empirical findings from these two seemingly distant research fields accord with the operation of a comparator mechanism during novelty detection more generally. We therefore conclude that a comparator mechanism may underlie the role of the hippocampus not only in detecting occurrences that are unexpected given specific associatively retrieved predictions, but also events that violate more abstract properties of the experimental context.

Hippocampal CA3 pyramidal cells selectively innervate aspiny interneurons

The specific connectivity among principal cells and interneurons determines the flow of activity in neuronal networks. To elucidate the connections between hippocampal principal cells and various classes of interneurons, CA3 pyramidal cells were intracellularly labelled with biocytin in anaesthetized rats and the three-dimensional distribution of their axon collaterals was reconstructed. The sections were double-stained for substance P receptor (SPR)- or metabotropic glutamate receptor 1alpha (mGluR-1alpha)-immunoreactivity to investigate interneuron targets of the CA3 pyramidal cells. SPR-containing interneurons represent a large portion of the GABAergic population, including spiny and aspiny classes. Axon terminals of CA3 pyramidal cells contacted SPR-positive interneuron dendrites in the hilus and in all hippocampal strata in both CA3 and CA1 regions (7.16% of all boutons). The majority of axons formed single contacts (87.5%), but multiple contacts (up to six) on single target neurons were also found. CA3 pyramidal cell axon collaterals innervated several types of morphologically different aspiny SPR-positive interneurons. In contrast, spiny SPR-interneurons or mGluR-1alpha-positive interneurons in the hilus, CA3 and CA1 regions were rarely contacted by the filled pyramidal cells. These findings indicate a strong target selection of CA3 pyramidal cells favouring the activation of aspiny classes of interneurons.

Hippocampal place cells: parallel input streams, subregional processing, and implications for episodic memory

The hippocampus is thought to be involved in episodic memory in humans. Place cells of the rat hippocampus offer a potentially important model system to understand episodic memory. However, the difficulties in determining whether rats have episodic memory are profound. Progress can be made by considering the hippocampus as a computational device that presumably performs similar transformations on its inputs in both rats and in humans. Understanding the input/output transformations of rat place cells can thus inform research on the computational basis of human episodic memory. Two examples of different transformations in the CA3 and CA1 regions are presented. In one example, CA3 place fields are shown to maintain a greater degree of population coherence than CA1 place fields after a rearrangement of the salient landmarks in an environment, in agreement with computational models of CA3 as an autoassociative network. In the second example, CA3 place field appears to store information about the spatiotemporal sequences of place fields, starting with the first exposure to a cue-altered environment, whereas CA1 place fields store this information only on a temporary basis. Finally, recordings of hippocampal afferents from the lateral and medial entorhinal cortex (EC) suggest that these two regions convey fundamentally different representations to the hippocampus, with spatial information conveyed by the medial EC and nonspatial information conveyed by the lateral EC. The dentate gyrus and CA3 regions may create configural object+place (or item+context) representations that provide the spatiotemporal context of an episodic memory.

Fast rate coding in hippocampal CA3 cell ensembles

Environments with overlapping features are represented by distinct patterns of activity in the hippocampus, enabling information to be stored and retrieved with minimal interference. This orthogonalization of correlated inputs is thought to take place within the hippocampus itself. However, the orthogonalization process has been shown to take days to develop in CA1. This prolonged time course is in striking contrast to the fast encoding of behavioral memory by the hippocampus. To explore this apparent paradox, we asked whether orthogonalization depended on the type of remapping exhibited by the hippocampal network. We have previously distinguished two types of remapping, global remapping, which results in the activation of different assemblies of place fields, and rate remapping, which encodes differences between cue constellations by substantial changes in firing rate without a change in the place code. Global remapping has previously been shown to be expressed immediately at novel locations. Here we asked if rate remapping follows a slower time course. Ensemble activity was recorded simultaneously from CA3 and CA1 in rats exposed to two similar, novel environments. It was found that rate changes in response to novel sensory cue configurations can form immediately, just as during global remapping, in particular in CA3. The fast encoding of both spatial and nonspatial information in CA3 is consistent with a role for the autoassociative CA3 circuitry in the acquisition and expression of episodic memories.

Gradual translocation of spatial correlates of neuronal firing in the hippocampus toward prospective reward locations

In a continuous T-maze alternation task, CA1 complex-spike neurons in the hippocampus differentially fire as the rat traverses overlapping segments of the maze (i.e., the stem) repeatedly via alternate routes. The temporal dynamics of this phenomenon were further investigated in the current study. Rats learned the alternation task from the first day of acquisition and the differential firing pattern in the stem was observed accordingly. More importantly, we report a phenomenon in which spatial correlates of CA1 neuronal ensembles gradually changed from their original firing locations, shifting toward prospective goal locations in the continuous T-maze alternation task. The relative locations of simultaneously recorded firing fields, however, were preserved within the ensemble spatial representation during this shifting. The within-session shifts in preferred firing locations in the absence of any changes in the environment suggest that certain cognitive factors can significantly alter the location-bound coding scheme of hippocampal neurons.

Towards neural circuit reconstruction with volume electron microscopy techniques

Electron microscopy is the only currently available technique with a resolution adequate to identify and follow every axon and dendrite in dense neuropil. Reconstructions of large volumes of neural tissue, necessary to reconstruct even local neural circuits, have, however, been inhibited by the daunting task of serially sectioning and reconstructing thousands of sections. Recent technological developments have improved the quality of volume electron microscopy data and automated its acquisition. This opens up the prospect of reconstructing almost complete invertebrate and sizable fractions of vertebrate nervous systems. Such reconstructions of complete neural wiring diagrams could rekindle the tradition of relating neural function to the underlying neuroanatomical circuitry.

Encoding New Episodes and Making Them Stick

How do we encode, store, and retrieve new episodic memories, and what are the computations performed by the hippocampus during this process? One system that has been used to model the brain basis of episodic memory in humans is the study of spatial navigation by path integration in rodents. Here I discuss three exciting new findings focused on encoding or replay of spatial sequences in the rat hippocampus. These findings not only provide important new insight into the computations associated with encoding and consolidation of spatial trajectories, but may also have implications for understanding key aspects of human episodic memory.

Episodic memory—From brain to mind

Neuronal mechanisms of episodic memory, the conscious recollection of autobiographical events, are largely unknown because electrophysiological studies in humans are conducted only in exceptional circumstances. Unit recording studies in animals are thus crucial for understanding the neurophysiological substrate that enables people to remember their individual past. Two features of episodic memory--autonoetic consciousness, the self-aware ability to "travel through time", and one-trial learning, the acquisition of information in one occurrence of the event--raise important questions about the validity of animal models and the ability of unit recording studies to capture essential aspects of memory for episodes. We argue that autonoetic experience is a feature of human consciousness rather than an obligatory aspect of memory for episodes, and that episodic memory is reconstructive and thus its key features can be modeled in animal behavioral tasks that do not involve either autonoetic consciousness or one-trial learning. We propose that the most powerful strategy for investigating neurophysiological mechanisms of episodic memory entails recording unit activity in brain areas homologous to those required for episodic memory in humans (e.g., hippocampus and prefrontal cortex) as animals perform tasks with explicitly defined episodic-like aspects. Within this framework, empirical data suggest that the basic structure of episodic memory is a temporally extended representation that distinguishes the beginning from the end of an event. Future research is needed to fully understand how neural encodings of context, sequences of items/events, and goals are integrated within mnemonic representations of autobiographical events.

Interaction between neocortical and hippocampal networks via slow oscillations

Both the thalamocortical and limbic systems generate a variety of brain state-dependent rhythms but the relationship between the oscillatory families is not well understood. Transfer of information across structures can be controlled by the offset oscillations. We suggest that slow oscillation of the neocortex, which was discovered by Mircea Steriade, temporally coordinates the self-organized oscillations in the neocortex, entorhinal cortex, subiculum and hippocampus. Transient coupling between rhythms can guide bidirectional information transfer among these structures and might serve to consolidate memory traces.