The medial temporal lobe (MTL) has been studied extensively at all levels of analysis, yet its function remains unclear. Theory regarding the cognitive function of the MTL has centered along 3 themes. Different authors have emphasized the role of the MTL in episodic recall, spatial navigation, or relational memory. Starting with the temporal context model (M.W. Howard and M. J. Kahana, 2002), a distributed memory model that has been applied to benchmark data from episodic recall tasks, the authors propose that the entorhinal cortex supports a gradually changing representation of temporal context and the hippocampus proper enables retrieval of these contextual states. Simulation studies show this hypothesis explains the firing of place cells in the entorhinal cortex and the behavioral effects of hippocampal lesion in relational memory tasks. These results constitute a first step towards a unified computational theory of MTL function that integrates neurophysiological, neuropsychological and cognitive findings.

ABSTRACT: 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 (I h)inthe generation of subthreshold membrane potential oscillations. The potential role of I h in contributing to the medium hyperpolarization (mAHP) and rebound spiking was studied. The role of I h and the slow calcium-activated potassium current I K(AHP) in action potential clustering was also studied. Representations of I h 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

Recent theoretical models based on cellular processes in parahippocampal structures show that persistent neuronal spiking in the absence of stimulus input is important for encoding. The goal of this study was to examine in humans how sustained activity in the parahippocampal gyrus may underlie long-term encoding as well as active maintenance of novel information. The relationship between long-term encoding and active maintenance of novel information during brief memory delays was studied using functional magnetic resonance imaging (fMRI) in humans performing a delayed matching-to-sample (DMS) task and a post-scan subsequent recognition memory task of items encountered during DMS task performance. Multiple regression analyses revealed fMRI activity in parahippocampal structures associated with the active maintenance of trial-unique visual information during a brief memory delay. In addition to a role in active maintenance, we found that the subsequent memory for the sample stimuli as measured by the post-scan subsequent recognition memory task correlated with activity in the parahippocampal gyrus during the delay period. The results provide direct evidence that encoding mechanisms are engaged during brief memory delays when novel information is actively maintained. The relationship between active maintenance during the delay period and long-term subsequent memory is consistent with current theoretical models and experimental data that suggest that long-term encoding is enhanced by sustained parahippocampal activity. Key words: memory; parahippocampal; neuroimaging; medial temporal lobe; delayed match to sample; computational modeling

ABSTRACT: Intracellular recording and computational modelling suggest that interactions of subthreshold membrane potential oscillation frequency in different dendritic branches of entorhinal cortex stellate cells could underlie the functional coding of continuous dimensions of space and time. Among other things, these interactions could underlie properties of grid cell field spacing. The relationship between experimental data on membrane potential oscillation frequency (f) and grid cell field spacing (G) indicates a constant scaling factor H 5 fG. This constant scaling factor between temporal oscillation frequency and spatial periodicity provides a starting constraint that is used to derive the model of Burgess et al. (Hippocampus, 2007). This model provides a consistent quantitative link between single cell physiological properties and properties of spiking units in awake behaving animals. Further properties and predictions of this model about single cell and network physiological properties are analyzed. In particular, the model makes quantitative predictions about the change in membrane potential, single cell oscillation frequency, and network oscillation frequency associated with speed of movement, about the independence of single cell properties from network theta rhythm oscillations, and about the effect of variations in initial oscillatory phase on the pattern of grid cell firing fields. These same mechanisms of subthreshold oscillations may play a more general role in memory function, by providing a method for learning arbitrary time intervals in memory sequences. VC 2007 Wiley-Liss, Inc. KEY WORDS: entorhinal cortex; stellate cells; field potential; head direction cells; memory encoding

ABSTRACT: This article presents a model of grid cell firing based on the intrinsic persistent firing shown experimentally in neurons of entorhinal cortex. In this model, the mechanism of persistent firing allows individual neurons to hold a stable baseline firing frequency. Depolarizing input from speed-modulated head direction cells transiently shifts the frequency of firing from baseline, resulting in a shift in spiking phase in proportion to the integral of velocity. The convergence of input from different persistent firing neurons causes spiking in a grid cell only when the persistent firing neurons are within similar phase ranges. This model effectively simulates the two-dimensional firing of grid cells in open field environments, as well as the properties of theta phase precession. This model provides an alternate implementation of oscillatory interference models. The persistent firing could also interact on a circuit level with rhythmic inhibition and neurons showing membrane potential oscillations to code position with spiking phase. These mechanisms could operate in parallel with computation of position from visual angle and distance of stimuli. In addition to simulating two-dimensional grid patterns, models of phase interference can account for context-dependent firing in other tasks. In network simulations of entorhinal cortex, hippocampus, and postsubiculum, the reset of phase effectively replicates context-dependent firing by entorhinal and hippocampal neurons during performance of a continuous spatial alternation task, a delayed spatial alternation task with running in a wheel during the delay period (Pastalkova et al., Science, 2008), and a hairpin maze task. VC 2008 Wiley-Liss, Inc. KEY WORDS: grid cells; place cells; persistent spiking; membrane potential oscillations; theta rhythm; neuromodulation; stellate cells;

ABSTRACT: 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 contextdependent 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. VC 2005 Wiley-Liss, Inc. KEY WORDS: EEG oscillations; region CA3; region CA1; spatial alternation; fornix; septum; theta phase precession; computational modeling

The rat postsubiculum has head direction cells that fire persistently when the rat’s head is oriented in particular directions. This persistent firing is maintained even if the rat is motionless, when spatial cues are removed from the environment and in the dark, but the mechanism that supports persistent firing of the head direction cells is still unclear. Here, using in vitro whole-cell patch recording, we found that a short-triggering stimulus (as few as five induced spikes) can initiate persistent firing in cells of the postsubiculum. Pharmacological results indicated that this persistent firing is driven by a calcium-sensitive nonselective cation current. The distribution of cells with persistent firing in superficial and deep layers in the postsubiculum was similar to that of head direction cells. These results suggest that persistent firing of head direction cells in the postsubiculum could be supported by an intrinsic mechanism.

Experimental data and computational models suggest that blockade of muscarinic cholinergic receptors impairs paired-associate learning and increases proactive interference (E. DeRosa & M. E. Hasselmo, 2000; M. E. Hasselmo & J. M. Bower, 1993). The results presented here provide evidence in humans supporting these hypotheses. Young healthy subjects first learned baseline word pairs (A–B) and, after a delay, learned additional overlapping (A–C) and nonoverlapping (D–E) word pairs. As predicted, when compared with subjects who received the active placebo glycopyrrolate (4 �g/kg) and subjects who were not injected, those who received scopolamine (8 �g/kg) showed (a) overall impairment in new word paired-associate learning, but no impairment in cued recall of previously learned associates; and (b) greater impairment in learning overlapping (A–C) compared with nonoverlapping (D–E) paired associates. Acetylcholine may play an important role in the encoding of new information. Numerous studies demonstrate that blockade of muscarinic acetylcholine receptors by systemic administration of the drug scopolamine interferes with the encoding of new verbal

Models of the hexagonally arrayed spatial activity pattern of grid cell firing in the literature generally fall into two main categories: continuous attractor models or oscillatory interference models. Burak and Fiete (2009, PLoS Comput Biol) recently examined noise in two continuous attractor models, but did not consider oscillatory interference models in detail. Here we analyze an oscillatory interference model to examine the effects of noise on its stability and spatial firing properties. We show analytically that the square of the drift in encoded position due to noise is proportional to time and inversely proportional to the number of oscillators. We also show there is a relatively fixed breakdown point, independent of many parameters of the model, past which noise overwhelms the spatial signal. Based on this result, we show that a pair of oscillators are expected to maintain a stable grid for approximately t=5m 3 /(4ps) 2 seconds where m is the mean period of an oscillator in seconds and s 2 its variance in seconds 2. We apply this criterion to recordings of individual persistent spiking neurons in postsubiculum (dorsal presubiculum) and layers III and V of entorhinal cortex, to subthreshold membrane potential oscillation recordings in layer II stellate cells of medial entorhinal cortex and to values from the literature regarding medial septum theta bursting cells. All oscillators examined have expected stability times far below those seen in experimental recordings of grid cells, suggesting the examined biological oscillators are unfit as a substrate for current implementations of oscillatory interference models. However, oscillatory interference models can tolerate small amounts of

ABSTRACT: Recordings in awake, behaving animals demonstrate that cells in medial entorhinal cortex (mEC) show ‘‘grid cell’ ’ firing activity when a rat explores an open environment. Intracellular recording in slices from different positions along the dorsal to ventral axis show differences in intrinsic properties such as subthreshold membrane potential oscillations (MPO), resonant frequency, and the presence of the hyperpolarization-activated cation current (h-current). The differences in intrinsic properties correlate with differences in grid cell spatial scale along the dorsal–ventral axis of mEC. Two sets of computational models have been proposed to explain the grid cell firing phenomena: oscillatory interference models and attractor-dynamic models. Both types of computational models are briefly reviewed, and cellular experimental evidence is interpreted and presented in the context of both models. The oscillatory interference model has variations that include an additive model and a multiplicative model. Experimental data on the voltage-dependence of oscillations presented here support the additive model. The additive model also simulates data from ventral neurons showing large spacing between grid firing fields within the limits of observed MPO frequencies. The interactions of h-current with synaptic modification suggest that the difference in intrinsic properties could also contribute to differences in grid cell properties due to attractor dynamics along the dorsal to ventral axis of mEC. Mechanisms of oscillatory interference and attractor dynamics may make complementary contributions to the properties of grid cell firing in entorhinal cortex. VC 2008 Wiley-Liss, Inc. KEY WORDS: grid cells; entorhinal cortex; stellate cell; membrane oscillations; computational models