The dynamic nature of spatial encoding in the hippocampus.

Bilkey, David K.; Clearwater, J. M.

doi:10.1037/0735-7044.119.6.1533

Cited by 16 publications

(24 citation statements)

References 94 publications

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“…Although a map-like representation was used to tune the firing of goal cells, the goal cells themselves did not form a map-like representation. Bilkey and Clearwater (2005) used an essentially similar gradient ascent mechanism by ignoring the spatial signal in place cell firing and taking advantage of the finding that there is an increased density of place cell firing fields at a goal in the water maze (Hollup et al, 2001). Similarly, other models that proposed physiologically plausible methods for goal-directed navigation used location-specific and direction-specific signals to tune motor output elements that themselves were not organized in a map-like manner (Brown and Sharp, 1995;Sharp et al, 1996;Touretzky and Redish, 1996;Redish and Touretzky, 1998).…”

Section: Relevance Of a Map-like Representationmentioning

confidence: 96%

Heading‐vector navigation based on head‐direction cells and path integration

Kubie

Fenton

2008

Hippocampus

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Insect navigation is guided by heading vectors that are computed by path integration. Mammalian navigation models, on the other hand, are typically based on map-like place representations provided by hippocampal place cells. Such models compute optimal routes as a continuous series of locations that connect the current location to a goal. We propose a "heading-vector" model in which head-direction cells or their derivatives serve both as key elements in constructing the optimal route and as the straight-line guidance during route execution. The model is based on a memory structure termed the "shortcut matrix," which is constructed during the initial exploration of an environment when a set of shortcut vectors between sequential pairs of visited waypoint locations is stored. A mechanism is proposed for calculating and storing these vectors that relies on a hypothesized cell type termed an "accumulating head-direction cell." Following exploration, shortcut vectors connecting all pairs of waypoint locations are computed by vector arithmetic and stored in the shortcut matrix. On re-entry, when local view or place representations query the shortcut matrix with a current waypoint and goal, a shortcut trajectory is retrieved. Since the trajectory direction is in head-direction compass coordinates, navigation is accomplished by tracking the firing of head-direction cells that are tuned to the heading angle. Section 1 of the manuscript describes the properties of accumulating head-direction cells. It then shows how accumulating head-direction cells can store local vectors and perform vector arithmetic to perform path-integration-based homing. Section 2 describes the construction and use of the shortcut matrix for computing direct paths between any pair of locations that have been registered in the shortcut matrix. In the discussion, we analyze the advantages of heading-based navigation over map-based navigation. Finally, we survey behavioral evidence that nonhippocampal, heading-based navigation is used in small mammals and humans.

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Section: Relevance Of a Map-like Representationmentioning

confidence: 96%

Heading‐vector navigation based on head‐direction cells and path integration

Kubie

Fenton

2008

Hippocampus

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“…Activity in the anterior hippocampus can be interpreted in terms of complementary spatial and nonspatial processes. Models of rodent navigation posit that the place cell representation of location drives representations of reward expectation (Foster et al, 2000) or goal proximity (goal proximity and expectation of reward are equivalent in the context of navigation in simple environments) (Burgess et al, 1994;Burgess and O'Keefe, 1996;Bilkey and Clearwater, 2005). These goal cells would have firing fields covering the entire environment, with peak rates at the goal location, and were postulated for the subiculum or nucleus accumbens.…”

Section: Effect Of Goal Proximitymentioning

confidence: 99%

“…Hippocampal place cells have been proposed to provide spatially extended evaluation functions encoding goal proximity (Burgess et al, 1994;Burgess and O'Keefe, 1996;Bilkey and Clearwater, 2005) or expectancy of reward (Dayan, 1991;Foster et al, 2000). In humans, neuronal representations of location can reflect the current goal of search within a virtual town (Ekstrom et al, 2003), and navigational accuracy is impaired by hippocampal damage (Spiers et al, 2001a,b;Bohbot et al, 2004) and correlates with hippocampal activation (Maguire et al, 1998;Grön et al, 2000;Hartley et al, 2003;Iaria et al, 2003).…”

Section: Introductionmentioning

confidence: 99%

Anterior Hippocampus and Goal-Directed Spatial Decision Making

Viard¹,

Doeller²,

Hartley³

et al. 2011

J. Neurosci.

135

126

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Planning spatial paths through our environment is an important part of everyday life and is supported by a neural system including the hippocampus and prefrontal cortex. Here we investigated the precise functional roles of the components of this system in humans by using fMRI as participants performed a simple goal-directed route-planning task. Participants had to choose the shorter of two routes to a goal in a visual scene that might contain a barrier blocking the most direct route, requiring a detour, or might be obscured by a curtain, requiring memory for the scene. The participant's start position was varied to parametrically manipulate their proximity to the goal and the difference in length of the two routes. Activity in medial prefrontal cortex, precuneus, and left posterior parietal cortex was associated with detour planning, regardless of difficulty, whereas activity in parahippocampal gyrus was associated with remembering the spatial layout of the visual scene. Activity in bilateral anterior hippocampal formation showed a strong increase the closer the start position was to the goal, together with medial prefrontal, medial and posterior parietal cortices. Our results are consistent with computational models in which goal proximity is used to guide subsequent navigation and with the association of anterior hippocampal areas with nonspatial functions such as arousal and reward expectancy. They illustrate how spatial and nonspatial functions combine within the anterior hippocampus, and how these functions interact with parahippocampal, parietal, and prefrontal areas in decision making and mnemonic function.

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“…For this type of gradient ascent model to be useful a gradient would have to cover the entire environment, with a peak at the goal location and without local maxima. In simulations presented in Bilkey and Clearwater (2005), it was found that when 5% of place fields were shifted toward the goal location an appropriate gradient that extended over the entire environment was formed. This whole-environment gradient occurred even though individual place fields only covered a small proportion of the region.…”

Section: Introductionmentioning

confidence: 94%

“…In addressing this concern we developed the Field Density Model of place cell function (Bilkey and Clearwater, 2005), showing that information about both current location and direction to goal location can be instantiated in a place cell representation of an environment provided a small proportion of place fields shift position in a goal-directed manner so that the total amount of place cell firing at a particular subregion is graded toward a goal location. An animal could potentially sense this gradient with small movements that would allow it to navigate to ''remembered'' goals.…”

Section: Introductionmentioning

confidence: 99%

Place, space, and taste: Combining context and spatial information in a hippocampal navigation system

Clearwater

Bilkey

2011

Hippocampus

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The hippocampus appears to play an important role in episodic-like, or "what, where, when" memory that may be used for goal finding. We have previously presented a model of the hippocampus describing how navigation to a distal goal location could be achieved through gradient ascent processes based on place field density. Here we extend that model to show that information about both where a goal is, and the attributes of that goal, can be incorporated with relatively simple modifications. In this model both the spatial and attribute information would be available to the animal at any location within the environment although differential recall requires two different firing modes. "Where" information is available when cells in the model are firing in "place field" firing mode. The recall of "what" information requires, however, near simultaneous firing of a large number of place cells. We discuss how this "what" firing mode could potentially depend upon sharp-wave ripple (SPW-R) events. This conception has implications for how we interpret SPW-R related firing. In particular, we suggest that the near simultaneous firing that occurs in large groups of cells during SPW-Rs may be sufficient for "what" recall and that the forward and reverse "replay" of place cell sequences that are often observed during SPW-Rs may be an epiphenomenon of this process.

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The dynamic nature of spatial encoding in the hippocampus.

Cited by 16 publications

References 94 publications

Heading‐vector navigation based on head‐direction cells and path integration

Heading‐vector navigation based on head‐direction cells and path integration

Anterior Hippocampus and Goal-Directed Spatial Decision Making

Place, space, and taste: Combining context and spatial information in a hippocampal navigation system

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