Grid-cell modules remain coordinated when neural activity is dissociated from external sensory cues

Waaga, Torgeir; Agmon, Haggai; Normand, Valentin A; Nagelhus, Anne; Gardner, Richard J.; Moser, May‐Britt; Moser, Edvard I; Burak, Yoram

doi:10.1016/j.neuron.2022.03.011

Cited by 30 publications

(37 citation statements)

References 48 publications

(101 reference statements)

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“…At times, the movement on the torus was aligned with the spatial movement (visible in the figures as segments with a stable horizontal pattern), but would occasionally shift or drift, supporting findings by Low et al [19]. For ensembles M1 and M2, this seemed to happen in coordination, in line with recent work [54]. However, gain and contrast manipulations clearly elicited a shift in the alignment between the torus and virtual space.…”

Section: Introductionsupporting

confidence: 88%

“…Bernoulli and Poisson generalized linear models were fitted to (binarized) calcium events and binned spike counts, respectively, using either the toroidal coordinates or the spatial positions as regressors, allowing a comparison of the explanatory power of the two descriptors. The setup was like Lederger et al (2021) and Gardner et al (2022), and included a smoothness prior to avoid overfitting.…”

Section: Generalized Linear Modelmentioning

confidence: 99%

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Uncovering 2-D toroidal representations in grid cell ensemble activity during 1-D behavior

Hermansen¹,

Klindt²,

Dunn³

2022

Preprint

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Neuroscience is pushing toward studying the brain during naturalistic behaviors with open-ended tasks. Grid cells are a classic example, where free behavior was key to observing their characteristic spatial representations in two-dimensional environments. In contrast, it has been difficult to identify grid cells and study their computations in more restrictive experiments, such as head-fixed wheel running. Here, we challenge this view by showing that shifting the focus from single neurons to the population level changes the minimal experimental complexity required to study grid cell representations. Specifically, we combine the manifold approximation in UMAP with persistent homology to study the topology of the population activity. With these methods, we show that the population activity of grid cells covers a similar two-dimensional toroidal state space during wheel running as in open field foraging, with and without a virtual reality setup. Trajectories on the torus correspond to single trial runs in virtual reality and changes in experimental conditions are reflected in the internal representation, while the toroidal representation undergoes occasional shifts in its alignment to the environment. These findings show that our method can uncover latent topologies that go beyond the complexity of the task, allowing us to investigate internal dynamics in simple experimental settings in which the analysis of grid cells has so far remained elusive.

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Section: Introductionsupporting

confidence: 88%

Section: Generalized Linear Modelmentioning

confidence: 99%

Uncovering 2-D toroidal representations in grid cell ensemble activity during 1-D behavior

Hermansen¹,

Klindt²,

Dunn³

2022

Preprint

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“…Given that each of these functional cell classes accounts for less than 15-25% of the local cell population in dorsal MEC 41,42 , whereas nearly all recorded neurons in the present study were locked to and participated in the population oscillation, the population oscillation is likely to consist of a mixture of functional cell types. Coordination by the population oscillation may prevent functional cell classes from drifting apart and help the circuit maintain correlated firing over the entire duration of an experience 89,90 . Second, the MEC oscillatory sequences may act as a scaffold to support computations that must take place on the fly with little time for extensive circuit plasticity, such as fast storage of memories associated with one-time experiences 69,91 , or the assembly of representations for complex sensory stimuli that evolve over time 37,92 .…”

Section: Discussionmentioning

confidence: 99%

Minute-scale oscillatory sequences in medial entorhinal cortex

Cogno

Obenhaus

Jacobsen

et al. 2022

Preprint

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The medial entorhinal cortex (MEC) hosts many of the brain's circuit elements for spatial navigation and episodic memory, operations that require neural activity to be organized across long durations of experience[1]. While location is known to be encoded by a plethora of spatially tuned cell types in this brain region[2-6], little is known about how the activity of entorhinal cells is tied together over time. Among the brain's most powerful mechanisms for neural coordination are network oscillations, which dynamically synchronize neural activity across circuit elements[7-10]. In MEC, theta and gamma oscillations provide temporal structure to the neural population activity at subsecond time scales[1,11-13]. It remains an open question, however, whether similarly powerful coordination occurs in MEC at behavioural time scales, in the second-to-minute regime. Here we show that MEC activity can be organized into a minute-scale oscillation that entrains nearly the entire cell population, with periods ranging from 10 to 100 seconds. Throughout this ultraslow oscillation, neural activity progresses in periodic and stereotyped sequences. This activity was elicited while mice ran at free pace on a rotating wheel in darkness, with no change in its location or running direction and no scheduled rewards. The oscillation sometimes advanced uninterruptedly for tens of minutes, transcending epochs of locomotion and immobility. Similar oscillatory sequences were not observed in neighboring parasubiculum or in visual cortex. The ultraslow oscillation of activity sequences in MEC may have the potential to couple its neurons and circuits across extended time scales and to serve as a scaffold for processes that unfold at behavioural time scales, such as navigation and episodic memory formation.

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“…When sensory inputs that provide allothetic (external) cues are restricted, path integration using idiothetic (self-motion) cues provides the primary source of location information. Accumulating evidence points to grid cells as a likely source of path integration [3], [6]- [11], in which the activity forms firing fields in tessellated triangles. It has been repeatedly shown that idiothetic cues govern the activity of grid cells.…”

Section: Introductionmentioning

confidence: 99%

“…It has been repeatedly shown that idiothetic cues govern the activity of grid cells. Specifically, grid cells remain active in darkness, i.e., in the absence of visual cues [3], [11] and are conversely inactivated during passive transportation [9] (no idiothetic cues). Moreover, when modulating a self-motion gain signal compared to a virtual reality scene, the grid cell pattern stretches in accordance [6]- [8], indicating a direct causal link between idiothetic sensory input and grid cell activity.…”

Section: Introductionmentioning

confidence: 99%

Coherently Remapping Toroidal Cells But Not Grid Cells are Responsible for Path Integration in Virtual Agents

Schøyen

Pettersen

Holzhausen

et al. 2022

Preprint

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When animals encounter a new environment, their cells with spatially modulated activity such as place cells and grid cells remap. Grid cells are particular in their remapping in that populations coherently remap as observed in spacing, orientation and phase changes. This process points to generality in grid cell activity that forms a standard computation across environments, which many speculate is path integration. Recently, normative artificial neural network models have shown that path integration and grid-cell-like activity can be obtained in recurrent neural networks (RNN) trained to navigate in a simulated two-dimensional environment. Remarkably, the emergent spatial profile of these grid-like cells is similar to biological cell responses in that they set up a toroidal structure. However, these models have not yet been tested in multiple environments relative to biological remapping. In this work, we extend the RNN normative model to multiple environments, modelled with place cell global remapping. Through this perturbation, we show (i) that the model can navigate multiple environments, (ii) that putative grid cells remain biologically plausible, (iii) a mechanism of how grid cells may remap, and (iv) a discussion on generalisation with inertial navigation in the grid and place cell network.

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Grid-cell modules remain coordinated when neural activity is dissociated from external sensory cues

Cited by 30 publications

References 48 publications

Uncovering 2-D toroidal representations in grid cell ensemble activity during 1-D behavior

Uncovering 2-D toroidal representations in grid cell ensemble activity during 1-D behavior

Minute-scale oscillatory sequences in medial entorhinal cortex

Coherently Remapping Toroidal Cells But Not Grid Cells are Responsible for Path Integration in Virtual Agents

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