Framing of grid cells within and beyond navigation boundaries

Savelli, Francesco; Luck, JD; Knierim, James

doi:10.7554/elife.21354

Cited by 54 publications

(64 citation statements)

References 94 publications

(162 reference statements)

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“…Rather, these representations are dynamically updated when boundaries are nearby. Our results add to a growing body of literature highlighting the unique ways in which environmental boundaries shape spatial representations in the brain [9][10][11][12][13][14]16,19,20,[46][47][48], and invite a reconceptualization of how these representations dynamically adapt to a changing world.…”

Section: Discussionsupporting

confidence: 62%

Environmental deformations dynamically shift the grid cell spatial metric

Keinath

Epstein

Balasubramanian

2017

Preprint

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2 SummaryWe propose a unified explanation for the diverse distortions in time-averaged activity of grid and place cells observed after environmental deformations. In our account, input from border cells resets the spatial phase but not the spatial scale of grid cells, maintaining learned relationships between grid phase and environmental boundaries. A computational model implementing this mechanism reproduced several commonly observed experimental effects, including scaledependent distortions in time-averaged grid fields after environmental deformation, and stretched, duplicated, and fractured place fields. Furthermore, this model predicted a striking new effect: dynamic, history-dependent 'shifts' in grid phase. We reanalyzed two classic datasets on grid rescaling and found clear evidence for such shifts, which have not previously been reported. These results invite a reconceptualization of the effects of environmental deformations on spatial representations -rather than rescaling the spatial metric of the cognitive map, as previously believed, alterations in environmental geometric may dynamically shift the map.. CC-BY-NC-ND 4.0 International license peer-reviewed) is the author/funder. It is made available under aThe copyright holder for this preprint (which was not . http://dx.doi.org/10.1101/174367 doi: bioRxiv preprint first posted online Aug. 10, 2017; 3 The cognitive map is thought to be a metric representation of space that preserves distances between represented locations [1,2]. Entorhinal grid cells are hypothesized to generate this metric by maintaining an internally-generated, path-integrated representation of space [3][4][5][6][7][8]. Results of environmental deformation experiments have led to the belief that this metric is fundamentally malleable [9][10][11]. In these experiments, neural activity is recorded as a rat explores deformed versions of a familiar environment where chamber walls have been stretched, compressed, removed, or inserted. Such deformations induce a number of distortions in the time-averaged activity of both grid [9,11] and hippocampal place cells [12][13][14][15][16]. Often described as 'rescaling', these distortions have been taken to suggest that the spatial metric of the cognitive map can be reshaped by altering environmental geometry [9,17,18]. Crucially, however, this interpretation assumes that the distortions observed in the time-averaged rate maps of these cells directly reflect corresponding changes to the underlying spatial code. Here, we propose and test an alternative mechanism which challenges this interpretation and instead indicates that during environmental deformations the grid cell spatial metric does not rescale, but instead undergoes dynamical, history-dependent phase shifts.We hypothesize, as others have [10,[19][20][21][22][23], that border cells interact with grid cells in familiar environments to maintain learned relationships between grid phase and boundaries. Here we further propose that the same mechanism is responsible for inducing diverse and u...

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Section: Discussionsupporting

confidence: 62%

Environmental deformations dynamically shift the grid cell spatial metric

Keinath

Epstein

Balasubramanian

2017

Preprint

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“…In much the same way the microscopic hippocampal CANN proposed here can effectively be reduced to a 2-state model (Fig. 4B), we expect CANN models for the grid-cell networks to be approximately described by a 2-state model, corresponding to the PI aligned with map A or B [11,54,55]. This motivates the simple model for the PI we have considered here.…”

Section: Discussionsupporting

confidence: 54%

Integration and multiplexing of positional and contextual information by the hippocampal network

Posani¹,

Monasson

2018

Preprint

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The hippocampus is known to store cognitive representations, or maps, that encode both positional and contextual information, critical for episodic memories and functional behavior. How path integration and contextual cues are dynamically combined and processed by the hippocampus to maintain these representations accurate over time remains unclear. To answer this question, we propose a two-way data analysis and modeling approach to CA3 multi-electrode recordings of a moving rat submitted to rapid changes of contextual (light) cues, triggering back-and-forth instabitilies between two cognitive representations (Jezek et al, Nature 478, p 246 (2011)). We develop a dual neural activity decoder, capable of independently identifying the recalled cognitive map at high temporal resolution (comparable to theta cycle) and the position of the rodent given a map. Remarkably, position can be reconstructed at any time with an accuracy comparable to fixed-context periods, even during highly unstable periods. These findings provide evidence for the capability of the hippocampal neural activity to maintain an accurate encoding of spatial and contextual variables, while one of these variables undergoes rapid changes independently of the other. To explain this result we introduce an attractor neural network model for the hippocampal activity that process inputs from external cues and the path integrator. Our model allows us to make predictions on the frequency of the cognitive map instability, its duration, and the detailed nature of the place-cell population activity, which are validated by a further analysis of the data. Our work therefore sheds light on the mechanisms by which the hippocampal network achieves and updates multi-dimensional neural representations from various input streams.

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“…In larger environments, it is likely that grid cells have more input to the firing of place cells while boundary cells have less (Wang et al, 2015). Geometric boundaries drive grid cells but so do salient remote cues (Savelli et al, 2017). It would be intriguing to see work at the cellular level on rodent navigation and reorientation in larger enclosures.…”

Section: The Geometric Module Debatementioning

confidence: 99%

Navigation and the developing brain

Newcombe

2019

Journal of Experimental Biology

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As babies rapidly acquire motor skills that give them increasingly independent and wide-ranging access to the environment over the first two years of human life, they decrease their reliance on habit systems for spatial localization, switching to their emerging inertial navigation system and to allocentric frameworks. Initial place learning is evident towards the end of the period. From 3 to 10 years, children calibrate their ability to encode various sources of spatial information (inertial information, geometric cues, beacons, proximal landmarks and distal landmarks) and begin to combine cues, both within and across systems. Geometric cues are important, but do not constitute an innate and encapsulated module. In addition, from 3 to 10 years, children build the capacity to think about frames of reference different from their current one (i.e. to perform perspective taking). By around 12 years, we see adult-level performance and adult patterns of individual differences on cognitive mapping tasks requiring the integration of vista views of space into environmental space. These lines of development are continuous rather than stage-like. Spatial development builds on important beginnings in the neural systems of newborns, but changes in experience-expectant ways with motor development, action in the world and success-failure feedback. Human systems for integrating and manipulating spatial information also benefit from symbolic capacities and technological inventions.

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Framing of grid cells within and beyond navigation boundaries

Cited by 54 publications

References 94 publications

Environmental deformations dynamically shift the grid cell spatial metric

Environmental deformations dynamically shift the grid cell spatial metric

Integration and multiplexing of positional and contextual information by the hippocampal network

Navigation and the developing brain

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