Mechanism of Graded Persistent Cellular Activity of Entorhinal Cortex Layer V Neurons

Fransén, Erik; Tahvildari, Babak; Egorov, Alexei V.; Hasselmo, Michael E.; Alonso, Ángel

doi:10.1016/j.neuron.2006.01.036

Cited by 252 publications

(319 citation statements)

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“…Stable persistent firing has also been shown in Layer III pyramidal cells of medial entorhinal cortex (Yoshida et al, 2007), whereas Layer II cells tend to show persistent firing that turns off and on over extended periods (Klink and Alonso, 1997). The currents underlying persistent spiking appear to be calcium-sensitive nonspecific cation currents regulated by cholinergic or metabotropic glutamate activation (Shalinsky et al, 2002;Fransen et al, 2006;Yoshida et al, 2007). Persistent spiking is activated by 5 lM concentrations of cholinergic agonists (Egorov et al, 2002) consistent with acetylcholine (ACh) concentrations measured during behavior (Parikh et al, 2007).…”

Section: Introductionmentioning

confidence: 62%

“…However, in the presence of cholinergic or metabotropic glutamate agonists, pyramidal cells in medial entorhinal cortex commonly show persistent firing (Klink and Alonso, 1997;Egorov et al, 2002;Fransen et al, 2006;Tahvildari et al, 2007;Yoshida et al, 2007) even when all synaptic input is blocked. As shown in Figure 1A, Layer V pyramidal neurons of medial entorhinal cortex continue firing at stable frequencies for an extended period after termination of current injection or synaptic stimulation.…”

Section: Introductionmentioning

confidence: 99%

“…As shown in Figure 1A, Layer V pyramidal neurons of medial entorhinal cortex continue firing at stable frequencies for an extended period after termination of current injection or synaptic stimulation. For Layer V pyramidal cells, the stable persistent firing frequency of neurons is determined by the integral of previous input (Egorov et al, 2002;Fransen et al, 2006), whereas in Layer III of lateral entorhinal cortex individual pyramidal cells show persistent firing at cell-specific frequencies (Tahvildari et al, 2007). Stable persistent firing has also been shown in Layer III pyramidal cells of medial entorhinal cortex (Yoshida et al, 2007), whereas Layer II cells tend to show persistent firing that turns off and on over extended periods (Klink and Alonso, 1997).…”

Section: Introductionmentioning

confidence: 99%

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Grid cell mechanisms and function: Contributions of entorhinal persistent spiking and phase resetting

2008

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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.

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Section: Introductionmentioning

confidence: 62%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Grid cell mechanisms and function: Contributions of entorhinal persistent spiking and phase resetting

2008

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“…The model is compatible with maintenance of grid cell representations by persistent firing (23) or attractor dynamics arising from patterned excitatory connectivity (2,24,25). Long-term stability of grid fields could require place cell input dependent on external landmarks (3,8,26).…”

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Temporal Frequency of Subthreshold Oscillations Scales with Entorhinal Grid Cell Field Spacing

Giocomo

Zilli

Fransén

et al. 2007

Science

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SummaryIntracellular recording shows how differences in single cell subthreshold oscillation frequency could directly underlie the differences in spacing of grid cell firing locations shown previously in awake, behaving animals.Grid cells in layer II of entorhinal cortex fire to spatial locations in a repeating hexagonal grid with smaller spacing between grid fields for neurons in more dorsal anatomical locations. Data from in vitro whole-cell patch recordings show a corresponding difference in frequency of subthreshold membrane potential oscillations in entorhinal neurons at different positions along the dorsal to ventral axis, supporting a model of physiological mechanism for grid cell responses.The entorhinal cortex plays an important role in encoding of spatial information (1-3) and episodic memory (4). Many layer II neurons of rat entorhinal cortex are "grid cells," firing when the rat is in an array of spatial locations forming a hexagonal grid within the environment (5-7). The spacing of firing fields in the grid varies with anatomical position of the cell along the dorsal to ventral axis of entorhinal cortex, as measured by distance from the postrhinal border (5). Neurons closer to the dorsal border of entorhinal cortex have shorter distances between firing fields. Computational models explicitly predict that differences in grid field spacing should correspond to differences in intrinsic frequencies of neurons along the dorsal to ventral axis (3,8). This could provide systematic variation in the gain of a movement-speed signal for path integration (2,3,9).Subthreshold membrane potential oscillations in entorhinal cortical stellate cells (10) arise from a single-cell mechanism involving voltage-sensitive currents (11-13) and could contribute to network dynamics (14). We recorded subthreshold oscillations from 57 stellate cells in layer II of medial entorhinal cortex (Fig. S1) in slices from different anatomical positions along the dorsal to ventral axis, using whole-cell patch clamp techniques (15). The position of individual horizontal slices was measured relative to the dorsal surface of the brain (Fig. 1A).Stellate cells in dorsal entorhinal cortex show higher temporal frequencies of subthreshold membrane potential oscillations compared to lower frequencies in cells from more ventral entorhinal slices (Fig. 1B). Dorsal cells (n = 30) are defined as cells recorded in slices taken between 3.8 mm (the border with postrhinal cortex (16)) and 4.9 mm from the dorsal surface of the brain. Ventral cells (n = 27) are defined as cells recorded in slices between 4.9 and 7.1 mm from the dorsal surface. Fig. 1B shows the group means of the frequency of subthreshold oscillations recorded from these populations. Because frequency of subthreshold oscillations can depend upon the mean membrane potential voltage, we performed this analysis separately for data gathered at different approximate holding membrane potentials of −50 mV and −45 mV. The mean frequency in dorsal cells was significantly higher than the mean frequ...

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“…This remarkable finding simplifies considerably the neural hardware required to implement an integrator. Of course the intracellular machinery that supports the properties of these cells is of tremendous interest (Fransen, Egorov, Hasselmo, & Alonso, 2003).…”

Section: Relationship To Other Workmentioning

confidence: 99%

The Temporal Context Model in Spatial Navigation and Relational Learning: Toward a Common Explanation of Medial Temporal Lobe Function Across Domains.

Howard¹,

Fotedar²,

Datey³

et al. 2005

Psychological Review

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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. , 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.The medial temporal lobe (MTL) is a region that includes the hippocampus proper, the subicular complex and parahippocampal cortical regions, including entorhinal, perirhinal, and parahippocampal/postrhinal cortices. A great deal of data from neuropsychology (e.g. Eichenbaum & Cohen, 2001;Scoville & Milner, 1957;Squire, 1992) and functional imaging (e.g. Fernandez, Effern, Grunwald, et al., 1999;Stern, Corkin, Gonzalez, et al., 1996;Wagner et al., 1998) has converged on the idea that the MTL is important in learning and memory. In order to bridge the gap between cognition and cellular-level physiology, we need a mechanistic, mesoscopic description of MTL computational function. We already have several successful verbally-formulated theories of the cognitive function of the MTL. These are described in turn in the following subsections. This paper will attempt to draw these multiple verbal theories together into a single computational framework that is consistent with known neurophysiological and neuroanatomical data.

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Mechanism of Graded Persistent Cellular Activity of Entorhinal Cortex Layer V Neurons

Cited by 252 publications

References 50 publications

Grid cell mechanisms and function: Contributions of entorhinal persistent spiking and phase resetting

Grid cell mechanisms and function: Contributions of entorhinal persistent spiking and phase resetting

Temporal Frequency of Subthreshold Oscillations Scales with Entorhinal Grid Cell Field Spacing

The Temporal Context Model in Spatial Navigation and Relational Learning: Toward a Common Explanation of Medial Temporal Lobe Function Across Domains.

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