The anatomical and computational basis of the rat head-direction cell signal

Sharp, Patricia E.; Blair, Hugh T.; Cho, Jeiwon

doi:10.1016/s0166-2236(00)01797-5

Cited by 220 publications

(213 citation statements)

References 48 publications

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“…In this model, grid cell periodicity arises from an interference pattern generated by intrinsic temporal oscillations in the soma and dendrites of a single cell. During simulated rat movement, cells modulated by head direction and speed (7,21,22) shift the frequency of dendritic oscillations (consistent with voltage effects on frequency). The grid pattern is the product of interference by three dendritic oscillations, each receiving a different head direction input, shifting in and out of phase with soma oscillations in proportion to distance moved in the preferred direction of each head direction cell.…”

Section: Nih-pa Author Manuscriptsupporting

confidence: 63%

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

Giocomo

Zilli

Fransén

et al. 2007

Science

360

527

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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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Section: Nih-pa Author Manuscriptsupporting

confidence: 63%

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

Giocomo

Zilli

Fransén

et al. 2007

Science

360

527

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“…While theories of how HD cells maintain their correlations with orientation have converged on the idea that the system forms an attractor network (Skaggs et al, 1995;Redish et al, 1996;Zhang, 1996;Blair et al, 1998;Redish, 1999;Goodridge and Touretzky, 2000;Sharp et al, 2001a), the location of an attractor network is still under debate. Redish et al (1996) suggested that attractor networks exist within both postsubiculum and the anterior dorsal thalamus.…”

Section: Implications For Modelingmentioning

confidence: 99%

“…Attractor network models are composed of local excitatory and global inhibitory connections and represent head direction as a bump of activity with the cell population. These models are capable of producing realistic tuning curves while tracking realistic rotations (Redish et al, 1996;Redish, 1999;Goodridge and Touretzky, 2000;Sharp et al, 2001a).…”

Section: Introductionmentioning

confidence: 99%

“…An alternative view presented by Blair and Sharp (Blair et al, 1997;Sharp et al, 2001a) suggested an interaction between the lateral mammillary nucleus and the dorsal tegmental nucleus as the locus of the attractor network. Despite these different perspectives, most theories assume that postsubiculum contains a complete HD signal (Taube et al, 1996;Redish, 1999;Sharp et al, 2001a). The data presented here confirm that postsubiculum does contain a complete HD signal.…”

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confidence: 99%

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Reconstruction of the postsubiculum head direction signal from neural ensembles

2005

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“…There has recently been a growing interest in states of sustained activity within neuronal networks, and it has been suggested that such states may form the dynamical underpinnings of working memory (Wang, 2001), orientation tuning (Hansel and Sompolinsky, 1996), maintenance of head direction (Sharp et al, 2001), and perhaps other neuronal phenomena such as ocular saccade control (Aksay et al, 2001). States of sustained activity have also been implicated in pathological phenomena.…”

Section: Introductionmentioning

confidence: 99%

A Model of the Effects of Applied Electric Fields on Neuronal Synchronization

et al. 2005

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We examine the effects of applied electric fields on neuronal synchronization. Two-compartment model neurons were synaptically coupled and embedded within a resistive array, thus allowing the neurons to interact both chemically and electrically. In addition, an external electric field was imposed on the array. The effects of this field were found to be nontrivial, giving rise to domains of synchrony and asynchrony as a function of the heterogeneity among the neurons. A simple phase oscillator reduction was successful in qualitatively reproducing these domains. The findings form several readily testable experimental predictions, and the model can be extended to a larger scale in which the effects of electric fields on seizure activity may be simulated.

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The anatomical and computational basis of the rat head-direction cell signal

Cited by 220 publications

References 48 publications

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

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

Reconstruction of the postsubiculum head direction signal from neural ensembles

A Model of the Effects of Applied Electric Fields on Neuronal Synchronization

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