GABA(B) modulation improves sequence disambiguation in computational models of hippocampal region CA3

Cortical oscillations support sampling-based computations in spiking neural networks

Being permanently confronted with an uncertain world, brains have faced evolutionary pressure to represent this uncertainty in order to respond appropriately. Often, this requires visiting multiple interpretations of the available information or multiple solutions to an encountered problem. This gives rise to the so-called mixing problem: since all of these "valid" states represent powerful attractors, but between themselves can be very dissimilar, switching between such states can be difficult. We propose that cortical oscillations can be effectively used to overcome this challenge. By acting as an effective temperature, background spiking activity modulates exploration. Rhythmic changes induced by cortical oscillations can then be interpreted as a form of simulated tempering. We provide a rigorous mathematical discussion of this link and study some of its phenomenological implications in computer simulations. This identifies a new computational role of cortical oscillations and connects them to various phenomena in the brain, such as sampling-based probabilistic inference, memory replay, multisensory cue combination, and place cell flickering.

Probabilistic associative learning suffices for learning the temporal structure of multiple sequences

From memorizing a musical tune to navigating a well known route, many of our underlying behaviors have a strong temporal component. While the mechanisms behind the sequential nature of the underlying brain activity are likely multifarious and multi-scale, in this work we attempt to characterize to what degree some of this properties can be explained as a consequence of simple associative learning. To this end, we employ a parsimonious firing-rate attractor network equipped with the Hebbian-like Bayesian Confidence Propagating Neural Network (BCPNN) learning rule relying on synaptic traces with asymmetric temporal characteristics. The proposed network model is able to encode and reproduce temporal aspects of the input, and offers internal control of the recall dynamics by gain modulation. We provide an analytical characterisation of the relationship between the structure of the weight matrix, the dynamical network parameters and the temporal aspects of sequence recall. We also present a computational study of the performance of the system under the effects of noise for an extensive region of the parameter space. Finally, we show how the inclusion of modularity in our network structure facilitates the learning and recall of multiple overlapping sequences even in a noisy regime.

Dendrites, deep learning, and sequences in the hippocampus

The hippocampus places us both in time and space. It does so over remarkably large spans: milliseconds to years, and centimeters to kilometers. This works for sensory representations, for memory, and for behavioral context. How does it fit in such wide ranges of time and space scales, and keep order among the many dimensions of stimulus context? A key organizing principle for a wide sweep of scales and stimulus dimensions is that of order in time, or sequences. Sequences of neuronal activity are ubiquitous in sensory processing, in motor control, in planning actions, and in memory. Against this strong evidence for the phenomenon, there are currently more models than definite experiments about how the brain generates ordered activity. The flip side of sequence generation is discrimination. Discrimination of sequences has been extensively studied at the behavioral, systems, and modeling level, but again physiological mechanisms are fewer. It is against this backdrop that I discuss two recent developments in neural sequence computation, that at face value share little beyond the label "neural." These are dendritic sequence discrimination, and deep learning. One derives from channel physiology and molecular signaling, the other from applied neural network theory - apparently extreme ends of the spectrum of neural circuit detail. I suggest that each of these topics has deep lessons about the possible mechanisms, scales, and capabilities of hippocampal sequence computation.

Involvement of the lateral entorhinal cortex for the formation of cross-modal olfactory-tactile associations in the rat

While the olfactory and tactile vibrissal systems have been extensively studied in the rat, the neural basis of these cross-modal associations is still elusive. Here we tested the hypothesis that the lateral entorhinal cortex (LEC) could be particularly involved. In order to tackle this question, we have developed a new behavioral paradigm which consists in finding one baited cup (+) among three, each of the cups presenting a different and specific odor/texture (OT) combination. During the acquisition of a first task (Task OT1), the three cups were associated with the following OT combination: O1T1 for the baited cup; O2T1 and O1T2 for non-baited ones. Most rats learn this task within three training sessions (20 trials/session). In a second task (Task OT2) animals had to pair another OT combination with the reward using a new set of stimuli (O3T3+, O4T3, and O3T4). Results showed that rats manage to learn Task OT2 within one session only. In a third task (Task OT3) animals had to learn another OT combination based on previously learned items (e.g. O4T4+, O1T4 and O4T1). This task is called the "recombination task." Results showed that control rats solve the recombination task within one session. Animals bilaterally implanted with cannulae in the LEC were microinfused with d-APV (3 µg/0.6 µL) just before the acquisition or the test session of each task. The results showed that NMDA receptor blockade in LEC did not affect recall of Task OT1 but strongly impaired acquisition of both Task OT2 and OT3. Moreover, two control groups of animals infused with d-APV showed no deficit in the acquisition of unimodal olfactory and tactile tasks. Taken together, these data show that the NMDA system in the LEC is involved in the acquisition of association between an olfactory and a tactile stimulus during cross-modal learning task.

Hippocampal activity patterns carry information about objects in temporal context

The hippocampus is critical for human episodic memory, but its role remains controversial. One fundamental question concerns whether the hippocampus represents specific objects or assigns context-dependent representations to objects. Here, we used multivoxel pattern similarity analysis of fMRI data during retrieval of learned object sequences to systematically investigate hippocampal coding of object and temporal context information. Hippocampal activity patterns carried information about the temporal positions of objects in learned sequences, but not about objects or temporal positions in random sequences. Hippocampal activity patterns differentiated between overlapping object sequences and between temporally adjacent objects that belonged to distinct sequence contexts. Parahippocampal and perirhinal cortex showed different pattern information profiles consistent with coding of temporal position and object information, respectively. These findings are consistent with models proposing that the hippocampus represents objects within specific temporal contexts, a capability that might explain its critical role in episodic memory.

Contributions of the hippocampal subfields and entorhinal cortex to disambiguation during working memory

The hippocampus and medial temporal lobes (MTL) support the successful formation of new memories without succumbing to interference from related, older memories. Computational models and animal findings have implicated the dentate gyrus (DG), CA3, CA1, and entorhinal cortex (EC) in the disambiguation and encoding of well-established, episodic events that share common elements. However, it is unknown if these hippocampal subfields and MTL (entorhinal, perirhinal, parahippocampal) cortices also contribute during working memory when overlapping stimuli that share related features are rapidly encoded and subsequently maintained over a brief temporal delay. We hypothesized that activity in CA3/DG hippocampal subfields would be greater for the rapid encoding of stimuli with overlapping features than for the rapid encoding of stimuli with distinct features. In addition, we predicted that CA1 and EC, regions that are associated with creating long-term episodic representations, would show greater sustained activity across both encoding and delay periods for representations of stimuli with overlapping features than for those with distinct features. We used high-resolution fMRI during a delayed matching-to-sample (DMS) task using face pairs that either shared (overlapping condition, OL) or did not share (non-overlapping condition, NOL) common elements. We contrasted the OL condition with the NOL condition separately at sample (encoding) and during a brief delay (maintenance). At sample, we observed activity localized to CA3/DG, the subiculum, and CA1. At delay, we observed activity localized to the subiculum and CA1 and activity within the entorhinal, perirhinal, and parahippocampal cortices. Our findings are consistent with our hypotheses and suggest that CA3/DG, CA1 and the subiculum support the disambiguation and encoding of overlapping representations while CA1, subiculum and entorhinal cortex maintain these overlapping representations during working memory.

Neural dynamics of the cognitive map in the hippocampus

The rodent hippocampus has been thought to represent the spatial environment as a cognitive map. In the classical theory, the cognitive map has been explained as a consequence of the fact that different spatial regions are assigned to different cell populations in the framework of rate coding. Recently, the relation between place cell firing and local field oscillation theta in terms of theta phase precession was experimentally discovered and suggested as a temporal coding mechanism leading to memory formation of behavioral sequences accompanied with asymmetric Hebbian plasticity. The cognitive map theory is apparently outside of the sequence memory view. Therefore, theoretical analysis is necessary to consider the biological neural dynamics for the sequence encoding of the memory of behavioral sequences, providing the cognitive map formation. In this article, we summarize the theoretical neural dynamics of the real-time sequence encoding by theta phase precession, called theta phase coding, and review a series of theoretical models with the theta phase coding that we previously reported. With respect to memory encoding functions, instantaneous memory formation of one-time experience was first demonstrated, and then the ability of integration of memories of behavioral sequences into a network of the cognitive map was shown. In terms of memory retrieval functions, theta phase coding enables the hippocampus to represent the spatial location in the current behavioral context even with ambiguous sensory input when multiple sequences were coded. Finally, for utilization, retrieved temporal sequences in the hippocampus can be available for action selection, through the process of reverting theta rhythm-dependent activities to information in the behavioral time scale. This theoretical approach allows us to investigate how the behavioral sequences are encoded, updated, retrieved and used in the hippocampus, as the real-time interaction with the external environment. It may indeed be the bridge to the episodic memory function in human hippocampus.

The dynamics of hippocampal activation during encoding of overlapping sequences

Sequence disambiguation, the process by which overlapping sequences are kept separate, has been proposed to underlie a wide range of memory capacities supported by the hippocampus, including episodic memory and spatial navigation. We used functional magnetic resonance imaging (fMRI) to explore the dynamic pattern of hippocampal activation during the encoding of sequences of faces. Activation in right posterior hippocampus, only during the encoding of overlapping sequences but not nonoverlapping sequences, was found to correlate robustly with a subject-specific behavioral index of sequence learning. Moreover, our data indicate that hippocampal activation in response to elements common to both sequences in the overlapping sequence pair, may be particularly important for accurate sequence encoding and retrieval. Together, these findings support the conclusion that the human hippocampus is involved in the earliest stage of sequence disambiguation, when memory representations are in the process of being created, and provide empirical support for contemporary computational models of hippocampal function.

Effects of 5-HT on memory and the hippocampus: model and data

5-Hydroxytryptamine (5-HT) transmission has been implicated in memory and in depression. Both 5-HT depletion and specific 5-HT agonists lower memory performance, while depression is also associated with memory deficits. The precise neuropharmacology and neural mechanisms underlying these effects are unknown. We used neural network simulations to elucidate the neuropharmacology and network mechanisms underlying 5-HT effects on memory. The model predicts that these effects are largely dependent on transmission over the 5-HT1A and 5-HT3 receptors, which regulate the selectivity of retrieval. It also predicts differential memory deficit profiles for 5-HT depletion and overactivation. The latter predictions were confirmed in studies with healthy and depressed participants undergoing acute tryptophan depletion or ipsipirone challenge. The results suggest that the memory impairments in depressed subjects may be related to 5-HT undertransmission, and support the notion that 5-HT1A agonists ameliorate memory deficits in depression.

What is the function of hippocampal theta rhythm?--Linking behavioral data to phasic properties of field potential and unit recording data

The extensive physiological data on hippocampal theta rhythm provide an opportunity to evaluate hypotheses about the role of theta rhythm for hippocampal network function. Computational models based on these hypotheses help to link behavioral data with physiological measurements of different variables during theta rhythm. This paper reviews work on network models in which theta rhythm contributes to the following functions: (1) separating the dynamics of encoding and retrieval, (2) enhancing the context-dependent retrieval of sequences, (3) buffering of novel information in entorhinal cortex (EC) for episodic encoding, and (4) timing interactions between prefrontal cortex and hippocampus for memory-guided action selection. Modeling shows how these functional mechanisms are related to physiological data from the hippocampal formation, including (1) the phase relationships of synaptic currents during theta rhythm measured by current source density analysis of electroencephalographic data from region CA1 and dentate gyrus, (2) the timing of action potentials, including the theta phase precession of single place cells during running on a linear track, the context-dependent changes in theta phase precession across trials on each day, and the context-dependent firing properties of hippocampal neurons in spatial alternation (e.g., "splitter cells"), (3) the cholinergic regulation of sustained activity in entorhinal cortical neurons, and (4) the phasic timing of prefrontal cortical neurons relative to hippocampal theta rhythm.

Recall of memory sequences by interaction of the dentate and CA3: A revised model of the phase precession

Behavioral and electrophysiological evidence indicates that the hippocampus has a special role in the encoding and recall of memory sequences. Importantly, the hippocampal phase precession, a phenomenon recorded as a rat moves through place fields, can be interpreted as cued recall of the sequence of upcoming places. The phase precession can be recorded in all hippocampal regions, but the role of each region has been unclear. Here, we suggest how the dentate and CA3 regions can work together to learn sequences, recall sequences, and generate the phase precession. Our proposal is constrained by information regarding synaptic plasticity rules, network connectivity, timing delays and theta/gamma oscillations.

Computational theories on the function of theta oscillations

Neural rhythms can be studied in terms of conditions for their generation, or in terms of their functional significance. The theta oscillation is a particularly prominent rhythm, reported to be present in many brain areas, and related to many important cognitive processes. The generating mechanisms of theta have extensively been studied and reviewed elsewhere; here we discuss ideas that have accumulated over the past decades on the computational roles it may subserve. Theories propose different aspects of theta oscillations as being relevant for their cognitive functions: limit cycle oscillations in neuronal firing rates, subthreshold membrane potential oscillations, periodic modulation of synaptic transmission and plasticity, and phase precession of hippocampal place cells. The relevant experimental data is briefly summarized in the light of these theories. Specific models proposing a function for theta in pattern recognition, memory, sequence learning and navigation are reviewed critically. Difficulties with testing and comparing alternative models are discussed, along with potentially important future research directions in the field.

Ionic mechanisms in the generation of subthreshold oscillations and action potential clustering in entorhinal layer II stellate neurons

A multicompartmental biophysical model of entorhinal cortex layer II stellate cells was developed to analyze the ionic basis of physiological properties, such as subthreshold membrane potential oscillations, action potential clustering, and the medium afterhyperpolarization. In particular, the simulation illustrates the interaction of the persistent sodium current (I(Nap)) and the hyperpolarization activated inward current (Ih) in the generation of subthreshold membrane potential oscillations. The potential role of Ih in contributing to the medium hyperpolarization (mAHP) and rebound spiking was studied. The role of Ih and the slow calcium-activated potassium current Ikappa(AHP) in action potential clustering was also studied. Representations of Ih and I(Nap) were developed with parameters based on voltage-clamp data from whole-cell patch and single channel recordings of stellate cells (Dickson et al., J Neurophysiol 83:2562-2579, 2000; Magistretti and Alonso, J Gen Physiol 114:491-509, 1999; Magistretti et al., J Physiol 521:629-636, 1999a; J Neurosci 19:7334-7341, 1999b). These currents interacted to generate robust subthreshold membrane potentials with amplitude and frequency corresponding to data observed in the whole cell patch recordings. The model was also able to account for effects of pharmacological manipulations, including blockade of Ih with ZD7288, partial blockade with cesium, and the influence of barium on oscillations. In a model with a wider range of currents, the transition from oscillations to single spiking, to spike clustering, and finally tonic firing could be replicated. In agreement with experiment, blockade of calcium channels in the model strongly reduced clustering. In the voltage interval during which no data are available, the model predicts that the slow component of Ih does not follow the fast component down to very short time constants. The model also predicts that the fast component of Ih is responsible for the involvement in the generation of subthreshold oscillations, and the slow component dominates in the generation of spike clusters.

Mode shifting between storage and recall based on novelty detection in oscillating hippocampal circuits

It has been suggested that hippocampal mode shifting between a storage and a retrieval state might be under the control of acetylcholine (ACh) levels, as set by an autoregulatory hippocampo-septo-hippocampal loop. The present study investigates how such a mechanism might operate in a large-scale connectionist model of this circuitry that takes into account the major hippocampal subdivisions, oscillatory population dynamics and the time scale on which ACh exerts its effects in the hippocampus. The model assumes that hippocampal mode shifting is regulated by a novelty signal generated in the hippocampus. The simulations suggest that this signal originates in the dentate. Novel patterns presented to this structure lead to brief periods of depressed firing in the hippocampal circuitry. During these periods, an inhibitory influence of the hippocampus on the septum is lifted, leading to increased firing of cholinergic neurons. The resulting increase in ACh release in the hippocampus produces network dynamics that favor learning over retrieval. Resumption of activity in the hippocampus leads to the reinstatement of inhibition. Despite theta-locked rhythmic firing of ACh neurons in the septum, ACh modulation in the model fluctuates smoothly on a time scale of seconds. It is shown that this is compatible with the time scale on which memory processes take place. A number of strong predictions regarding memory function are derived from the model.

Computational models of the hippocampal region: linking incremental learning and episodic memory

The hippocampal region, a group of brain structures important for learning and memory, has been the focus of a large number of computational models. These tend to fall into two groups: (1) models of the role of the hippocampal region in incremental learning, which focus on the development of new representations that are sensitive to stimulus regularities and environmental context; (2) models that focus on the role of the hippocampal region in the rapid storage and retrieval of episodic memories. Rather than being in conflict, it is becoming apparent that both approaches are partially correct and might reflect the different functions of substructures of the hippocampal region. Future computational models will help to elaborate how these different substructures interact.

Hippocampal synaptic plasticity is modulated by theta rhythm in the fascia dentata of adult and aged freely behaving rats

A modulatory role for the hippocampal theta rhythm in synaptic plasticity is suggested by the observations that theta occurs during exploratory behaviors, spatial learning is impaired when the theta rhythm is disrupted, and excitation of hippocampal principal cells is phase-coupled to the theta wave. The theta phase affects the nature of the plasticity induced in urethane-anesthetized rats and in the carbachol-treated in vitro slice preparation, but these oscillations are phenomenologically different from natural theta, and the effects of theta phase on plasticity under natural conditions have not been reported. We therefore examined the effects of theta phase on the magnitude of long-term potentiation (LTP) in awake rats running on a linear track for a food reward. Twelve adult and 10 aged F344 male rats were implanted with a stimulating electrode in the perforant path and a recording electrode in the hilus of the fascia dentata. Stimuli were delivered at the peak or trough of the hilar theta rhythm. In both adult and aged, memory-impaired rats, LTP lasting at least 48 h was induced when stimuli were delivered at the positive theta peak, whereas LTP was not induced when stimuli were delivered at the negative troughs. Consistent with the finding that the threshold for LTP induction is increased at this synapse in old rats, the magnitude of LTP induced at the peak of theta rhythm was significantly lower in old animals. These data confirm that LTP can be modulated by locomotion-induced theta, and that this modulation is at least qualitatively preserved across age.

GABA(B) presynaptic inhibition has an in vivo time constant sufficiently rapid to allow modulation at theta frequency

Cyclical activity of GABAergic interneurons during theta rhythm could mediate phasic changes in strength of glutamatergic synaptic transmission in the hippocampal formation if presynaptic inhibition from activation of GABA(B) receptors is sufficiently rapid to change within a theta cycle. The experiments described here analyzed the time course of GABA(B) modulation using a heterosynaptic depression paradigm in anesthetized rats at physiological temperatures. Heterosynaptic depression of the slope of evoked potentials decayed with a time constant that would allow significant changes in transmission across different phases of the theta cycle. This heterosynaptic depression was significantly reduced by local infusion of the GABA(B) receptor antagonist CGP55845A.

Differences in time course of ACh and GABA modulation of excitatory synaptic potentials in slices of rat hippocampus

Activation of muscarinic receptors and GABA(B) receptors causes presynaptic inhibition of glutamatergic synaptic potentials at excitatory feedback connections in cortical structures. These effects may regulate dynamics in cortical structures, with presynaptic inhibition allowing extrinsic afferent input to dominate during encoding, while the absence of presynaptic inhibition allows stronger excitatory feedback during retrieval or consolidation. However, proposals for a functional role of such modulatory effects strongly depend on the time course of these modulatory effects; how rapidly can they turn off and on? In brain slice preparations of hippocampal region CA1, we have explored the time course of suppression of extracellularly recorded synaptic potentials after pressure pulse application of acetylcholine and GABA. Acetylcholine causes suppression of extracellular potentials with onset time constants between 1 and 2 s, and decay constants ranging between 10 and 20 s, even with very brief injection pulses. GABA causes suppression of extracellular potentials with onset time constants between 0.2 and 0.7 s, and decay time constants that decrease to values shorter than 2 s for very brief injection pulses. These techniques do not give an exact measure of the physiological time course in vivo, but they give a notion of the relative time course of the two modulators. The slow changes due to activation of muscarinic acetylcholine receptors may alter the dynamics of cortical circuits over longer intervals (e.g., between different stages of waking and sleep), setting dynamics appropriate for encoding versus consolidation processes. The faster changes in synaptic potentials caused by GABA could cause changes within each cycle of the theta rhythm, rapidly switching between encoding and retrieval dynamics during exploration.

A model of theta rhythm production in the septal-hippocampal system and its modulation by ascending brain stem pathways

Recent experimental observations have disclosed the existence of a septal-hippocampal feedback circuit, composed of medial septum diagonal band of Broca (ms-dbB) GABAergic projections to the inhibitory interneurons of the hippocampus, and hippocampal GABAergic projections to the ms-dbB, the major targets of which are the GABAergic septo-hippocampal projection cells. We propose that this feedback circuit provides the mechanism for the rhythmic suppression of interneuronal activity in the hippocampus, which is observed as low-level GABAergic-mediated theta activity. We also propose that this circuit may be the mechanism by which ascending brain stem pathways to the ms-dbB, in particular from the reticular formation, can influence hippocampal information processing in response to particular behavioral states, by exercising control over the level and frequency of theta activity in the hippocampus. In support of these proposals, we describe a minimal computational model of the feedback circuit which uses a set of four coupled differential equations describing the average dynamic activity of the populations of excitatory and inhibitory cells involved in the circuit. We demonstrate through simulations the inherently robust 4-6-Hz oscillatory dynamics of the circuit, and show that manipulation of internal connection strengths and external modulatory influences on this circuit changes the dynamics in a way which closely mimics corresponding manipulations in recent neurophysiological experiments investigating theta activity.

The involvement of recurrent connections in area CA3 in establishing the properties of place fields: a model

Strong constraints on the neural mechanisms underlying the formation of place fields in the rodent hippocampus come from the systematic changes in spatial activity patterns that are consequent on systematic environmental manipulations. We describe an attractor network model of area CA3 in which local, recurrent, excitatory, and inhibitory interactions generate appropriate place cell representations from location- and direction-specific activity in the entorhinal cortex. In the model, familiarity with the environment, as reflected by activity in neuromodulatory systems, influences the efficacy and plasticity of the recurrent and feedforward inputs to CA3. In unfamiliar, novel, environments, mossy fiber inputs impose activity patterns on CA3, and the recurrent collaterals and the perforant path inputs are subject to graded Hebbian plasticity. This sculpts CA3 attractors and associates them with activity patterns in the entorhinal cortex. In familiar environments, place fields are controlled by the way that perforant path inputs select among the attractors. Depending on the training experience provided, the model generates place fields that are either directional or nondirectional and whose changes when the environment undergoes simple geometric transformations are in accordance with experimental data. Representations of multiple environments can be stored and recalled with little interference, and these have the appropriate degrees of similarity in visually similar environments.

Computational modeling of entorhinal cortex

Computational modeling provides a means for linking the physiological and anatomical characteristics of entorhinal cortex at a cellular level to the functional role of this region in behavior. We have developed detailed simulations of entorhinal cortical neurons and networks, with an emphasis on the role of acetylcholine in entorhinal cortical function. Computational modeling suggests that when acetylcholine levels are high, this sets appropriate dynamics for the storage of stimuli during performance of delayed matching tasks. In particular, acetylcholine activates a calcium-sensitive nonspecific cation current which provides an intrinsic cellular mechanism which could maintain neuronal activity across a delay period. Simulations demonstrate how this phenomena could underlie entorhinal cortex delay activity as described in previous unit recordings. Acetylcholine also induces theta rhythm oscillations which may be appropriate for timing of afferent input to be encoded in hippocampus and for extraction of individual stored sequences from multiple stored sequences. Lower levels of acetylcholine may allow sharp wave dynamics which can reactivate associations encoded in hippocampus and drive the formation of additional traces in hippocampus and entorhinal cortex during consolidation.

Latent attractors: a model for context-dependent place representations in the hippocampus

Cells throughout the rodent hippocampal system show place-specific patterns of firing called place fields, creating a coarse-coded representation of location. The dependencies of this place code--or cognitive map--on sensory cues have been investigated extensively, and several computational models have been developed to explain them. However, place representations also exhibit strong dependence on spatial and behavioral context, and identical sensory environments can produce very different place codes in different situations. Several recent studies have proposed models for the computational basis of this phenomenon, but it is still not completely understood. In this article, we present a very simple connectionist model for producing context-dependent place representations in the hippocampus. We propose that context dependence arises in the dentate gyrus-hilus (DGH) system, which functions as a dynamic selector, disposing a small group of granule and pyramidal cells to fire in response to afferent stimulus while depressing the rest. It is hypothesized that the DGH system dynamics has "latent attractors," which are unmasked by the afferent input and channel system activity into subpopulations of cells in the DG, CA3, and other hippocampal regions as observed experimentally. The proposed model shows that a minimally structured hippocampus-like system can robustly produce context-dependent place codes with realistic attributes.

Size of CA1-evoked synaptic potentials is related to theta rhythm phase in rat hippocampus

Cholinergic and GABAergic neurons projecting to the hippocampus fire with specific phase relations to theta rhythm oscillations in the electroencephalogram (EEG). To determine if this phasic input has an impact on synaptic transmission within the hippocampus, we recorded evoked population excitatory postsynaptic potential (EPSPs) during different phases of theta rhythm by using techniques similar to those described in Rudell and Fox. Synaptic potentials elicited by stimulation of region CA3 of the contralateral hippocampus were recorded in region CA1 and CA3. In these experiments, the initial slope of evoked potentials showed a change in magnitude during different phases of the theta rhythm recorded in the dentate fissure, with individual trials showing an average of 9.5% change in slope of potentials, and the average across all experiments showing a change of 7.8%. Evoked potentials were maximal 18 degrees after the positive peak of the dentate fissure theta EEG. These potentials were also smaller by 18.2% during theta as opposed to non-theta states. Phasic changes in modulation of synaptic transmission could contribute to phase precession of hippocampal place cells and could enhance storage of new sequences of activity as demonstrated by computational models.

Human theta oscillations exhibit task dependence during virtual maze navigation

Theta oscillations (electroencephalographic activity with a frequency of 4-8 Hz) have long been implicated in spatial navigation in rodents; however, the role of theta oscillators in human spatial navigation has not been explored. Here we describe subdural recordings from epileptic patients learning to navigate computer-generated mazes. Visual inspection of the raw intracranial signal revealed striking episodes of high-amplitude slow-wave oscillations at a number of areas of the cortex, including temporal cortex. Spectral analysis showed that these oscillations were in the theta band. These episodes of theta activity, which typically last several cycles, are dependent on task characteristics. Theta oscillations occur more frequently in more complex mazes; they are also more frequent during recall trials than during learning trials.

Neural models of memory

Neural models assist in characterizing the processes carried out by cortical and hippocampal memory circuits. Recent models of memory have addressed issues including recognition and recall dynamics, sequences of activity as the unit of storage, and consolidation of intermediate-term episodic memory into long-term memory.

Bridging the gap: integrating cellular and functional magnetic resonance imaging studies of the hippocampus

The importance of the medial temporal lobe in memory has been studied extensively at the neuronal, neural ensemble, and systems level. In this report, we discuss recent systems level neuroimaging results in relation to neurophysiological studies of the hippocampus and related structures within the medial temporal lobe. By combining our knowledge across the cellular and systems levels we sought to gain theoretical insight and a better understanding of the function of the hippocampus and related medial temporal lobe structures. The integration of information from studies carried out at the cellular and neural ensemble level with studies at the systems level is difficult because of the vast differences in spatial and temporal resolution of the different research methodologies, differences in neuroanatomy across species, and differences in the types of behavioral and cognitive paradigms used in rat, nonhuman primate, and human studies. Despite these methodological and species-related differences, the neurophysiological studies offer insight into many of the questions raised by recent neuroimaging studies. For instance, there is physiological evidence that suggests that the hippocampal memory system is functionally heterogeneous, which may explain some of the discrepancies in the location and extent of activation reported by different imaging studies of the medial temporal lobe. In addition, we describe recent computational models of the hippocampus which may be useful for bridging the gap between neurophysiological and neuroimaging data.