Framing Spatial Cognition: Neural Representations of Proximal and Distal Frames of Reference and Their Roles in Navigation

The most common behavioral test of hippocampus-dependent, spatial learning and memory is the Morris water task, and the most commonly studied behavioral correlate of hippocampal neurons is the spatial specificity of place cells. Despite decades of intensive research, it is not completely understood how animals solve the water task and how place cells generate their spatially specific firing fields. Based on early work, it has become the accepted wisdom in the general neuroscience community that distal spatial cues are the primary sources of information used by animals to solve the water task (and similar spatial tasks) and by place cells to generate their spatial specificity. More recent research, along with earlier studies that were overshadowed by the emphasis on distal cues, put this common view into question by demonstrating primary influences of local cues and local boundaries on spatial behavior and place-cell firing. This paper first reviews the historical underpinnings of the “standard” view from a behavioral perspective, and then reviews newer results demonstrating that an animal's behavior in such spatial tasks is more strongly controlled by a local-apparatus frame of reference than by distal landmarks. The paper then reviews similar findings from the literature on the neurophysiological correlates of place cells and other spatially correlated cells from related brain areas. A model is proposed by which distal cues primarily set the orientation of the animal's internal spatial coordinate system, via the head direction cell system, whereas local cues and apparatus boundaries primarily set the translation and scale of that coordinate system.

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Targeted Activation of Hippocampal Place Cells Drives Memory-Guided Spatial Behavior

Cell ◽

10.1016/j.cell.2020.12.010 ◽

2020 ◽

Vol 183 (7) ◽

pp. 2041-2042

Author(s):

Nick T.M. Robinson ◽

Lucie A.L. Descamps ◽

Lloyd E. Russell ◽

Moritz O. Buchholz ◽

Brendan A. Bicknell ◽

...

Keyword(s):

Place Cells ◽

Spatial Behavior

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Hippocampal Place-Cell Firing During Movement in Three-Dimensional Space

Journal of Neurophysiology ◽

10.1152/jn.2001.85.1.105 ◽

2001 ◽

Vol 85 (1) ◽

pp. 105-116 ◽

Cited By ~ 44

Author(s):

James J. Knierim ◽

Bruce L. McNaughton

Keyword(s):

Hippocampal Neurons ◽

Horizontal Plane ◽

Three Dimensional ◽

Place Cell ◽

Place Cells ◽

Limbic Cortex ◽

Head Direction ◽

Head Direction Cells ◽

Recording Apparatus ◽

Place Fields

“Place” cells of the rat hippocampus are coupled to “head direction” cells of the thalamus and limbic cortex. Head direction cells are sensitive to head direction in the horizontal plane only, which leads to the question of whether place cells similarly encode locations in the horizontal plane only, ignoring the z axis, or whether they encode locations in three dimensions. This question was addressed by recording from ensembles of CA1 pyramidal cells while rats traversed a rectangular track that could be tilted and rotated to different three-dimensional orientations. Cells were analyzed to determine whether their firing was bound to the external, three-dimensional cues of the environment, to the two-dimensional rectangular surface, or to some combination of these cues. Tilting the track 45° generally provoked a partial remapping of the rectangular surface in that some cells maintained their place fields, whereas other cells either gained new place fields, lost existing fields, or changed their firing locations arbitrarily. When the tilted track was rotated relative to the distal landmarks, most place fields remapped, but a number of cells maintained the same place field relative to the x-y coordinate frame of the laboratory, ignoring the z axis. No more cells were bound to the local reference frame of the recording apparatus than would be predicted by chance. The partial remapping demonstrated that the place cell system was sensitive to the three-dimensional manipulations of the recording apparatus. Nonetheless the results were not consistent with an explicit three-dimensional tuning of individual hippocampal neurons nor were they consistent with a model in which different sets of cells are tightly coupled to different sets of environmental cues. The results are most consistent with the statement that hippocampal neurons can change their “tuning functions” in arbitrary ways when features of the sensory input or behavioral context are altered. Understanding the rules that govern the remapping phenomenon holds promise for deciphering the neural circuitry underlying hippocampal function.

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Efficient neural decoding of self-location with a deep recurrent network

10.1101/242867 ◽

2018 ◽

Cited By ~ 1

Author(s):

Ardi Tampuu ◽

Tambet Matiisen ◽

H. Freyja Ólafsdóttir ◽

Caswell Barry ◽

Raul Vicente

Keyword(s):

Hippocampal Neurons ◽

Cell Activity ◽

Recurrent Network ◽

Brain Network ◽

Place Cells ◽

Neuronal Firing ◽

Temporal Context ◽

Central Component ◽

Neural Decoding ◽

Freely Moving

AbstractPlace cells in the mammalian hippocampus signal self-location with sparse spatially stable firing fields. Based on observation of place cell activity it is possible to accurately decode an animal’s location. The precision of this decoding sets a lower bound for the amount of information that the hippocampal population conveys about the location of the animal. In this work we use a novel recurrent neural network (RNN) decoder to infer the location of freely moving rats from single unit hippocampal recordings. RNNs are biologically plausible models of neural circuits that learn to incorporate relevant temporal context without the need to make complicated assumptions about the use of prior information to predict the current state. When decoding animal position from spike counts in 1D and 2D-environments, we show that the RNN consistently outperforms a standard Bayesian model with flat priors. In addition, we also conducted a set of sensitivity analysis on the RNN decoder to determine which neurons and sections of firing fields were the most influential. We found that the application of RNNs to neural data allowed flexible integration of temporal context, yielding improved accuracy relative to a commonly used Bayesian approach and opens new avenues for exploration of the neural code.Author summaryBeing able to accurately self-localize is critical for most motile organisms. In mammals, place cells in the hippocampus appear to be a central component of the brain network responsible for this ability. In this work we recorded the activity of a population of hippocampal neurons from freely moving rodents and carried out neural decoding to determine the animals’ locations. We found that a machine learning approach using recurrent neural networks (RNNs) allowed us to predict the rodents’ true positions more accurately than a standard Bayesian method with flat priors. The RNNs are able to take into account past neural activity without making assumptions about the statistics of neuronal firing. Further, by analyzing the representations learned by the network we were able to determine which neurons, and which aspects of their activity, contributed most strongly to the accurate decoding.

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Navigation by Dead Reckoning and Local Cues

Journal of Navigation ◽

10.1017/s0373463300011802 ◽

1993 ◽

Vol 46 (3) ◽

pp. 364-370 ◽

Cited By ~ 4

Author(s):

A. S. Etienne ◽

V. Séguinot

Keyword(s):

Coordinate System ◽

Dead Reckoning ◽

Cognitive Map ◽

Familiar Environment ◽

The Subject ◽

Absolute Coordinate System ◽

Actual Location ◽

Local Cues

According to comprehensive theories of navigation, animals navigate by using two complementary strategies: (1) dead reckoning informs the subject in a continuous manner on its actual location with respect to an Earthbound or absolute coordinate system; while (2) long-term associations between particular landmarks and specific locations allow the animal to find its way within a familiar environment. If the subject structures familiar space as a system of interconnected places – the so-called ‘cognitive map’ – it may know through dead reckoning where it is located on its map and relate its route-based expectations to the actually perceived scenario of local cues.

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Persistent trajectory-modulated hippocampal neurons support memory-guided navigation

10.1101/676593 ◽

2019 ◽

Author(s):

Nathaniel R. Kinsky ◽

William Mau ◽

David W. Sullivan ◽

Samuel J. Levy ◽

Evan A. Ruesch ◽

...

Keyword(s):

Calcium Imaging ◽

Hippocampal Neurons ◽

Spatial Information ◽

Single Photon ◽

Place Cells ◽

Dependent Activity ◽

Freely Moving ◽

Stable Trajectory ◽

Alternation Task

ABSTRACTTrajectory-dependent splitter neurons in the hippocampus encode information about a rodent’s prior trajectory during performance of a continuous alternation task. As such, they provide valuable information for supporting memory-guided behavior. Here, we employed single-photon calcium imaging in freely moving mice to investigate the emergence and fate of trajectory-dependent activity through learning and mastery of a continuous spatial alternation task. We found that the quality of trajectory-dependent information in hippocampal neurons correlated with task performance. We thus hypothesized that, due to their utility, splitter neurons would exhibit heightened stability. We found that splitter neurons were more likely to remain active and retained more consistent spatial information across multiple days than did place cells. Furthermore, we found that both splitter neurons and place cells emerged rapidly and maintained stable trajectory-dependent/spatial activity thereafter. Our results suggest that neurons with useful functional coding properties exhibit heightened stability to support memory guided behavior.

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Elemental and Configural Associative Learning in Spatial Tasks: Could Zebrafish be Used to Advance Our Knowledge?

Frontiers in Behavioral Neuroscience ◽

10.3389/fnbeh.2020.570704 ◽

2020 ◽

Vol 14 ◽

Author(s):

Alexis Buatois ◽

Robert Gerlai

Keyword(s):

Spatial Learning ◽

Molecular Mechanisms ◽

Spatial Task ◽

Future Research ◽

Spatial Learning And Memory ◽

Configural Learning ◽

Association Learning ◽

Laboratory Rodents ◽

Spatial Tasks ◽

Behavioral Mechanisms

Spatial learning and memory have been studied for several decades. Analyses of these processes pose fundamental scientific questions but are also relevant from a biomedical perspective. The cellular, synaptic and molecular mechanisms underlying spatial learning have been intensively investigated, yet the behavioral mechanisms/strategies in a spatial task still pose unanswered questions. Spatial learning relies upon configural information about cues in the environment. However, each of these cues can also independently form part of an elemental association with the specific spatial position, and thus spatial tasks may be solved using elemental (single CS and US association) learning. Here, we first briefly review what we know about configural learning from studies with rodents. Subsequently, we discuss the pros and cons of employing a relatively novel laboratory organism, the zebrafish in such studies, providing some examples of methods with which both elemental and configural learning may be explored with this species. Last, we speculate about future research directions focusing on how zebrafish may advance our knowledge. We argue that zebrafish strikes a reasonable compromise between system complexity and practical simplicity and that adding this species to the studies with laboratory rodents will allow us to gain a better understanding of both the evolution of and the mechanisms underlying spatial learning. We conclude that zebrafish research will enhance the translational relevance of our findings.

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Treadmill Running Regulates Adult Neurogenesis, Spatial and Non-Spatial Learning by ErbB4 Signaling

10.21203/rs.3.rs-122649/v1 ◽

2020 ◽

Author(s):

Yandong Yi ◽

Yuanlong Song ◽

Bo Liu ◽

Yisheng Lu

Keyword(s):

Cognitive Impairment ◽

Discrimination Learning ◽

Spatial Learning ◽

Hippocampal Neurons ◽

Reference Memory ◽

Contextual Fear Conditioning ◽

Treadmill Running ◽

Spatial Learning And Memory ◽

Contextual Fear ◽

Adult Hippocampus

Abstract Recent studies have shown exercise is effective for adult hippocampus neurogenesis and memory. However, the molecular mechanism of exercise is unclear. In this study, AG1478, an ErbB4 inhibitor, was used to explore the involvement of ErbB4 receptors. Four weeks post-running, cognitive impairment was analyzed using T-maze, Morris water maze (MWM) and contextual fear discrimination learning tests, followed by histological assessment of the proliferation and survival of hippocampal neurons using Ki67, NeuN and BrdU immunostaining respectively. Expression of total and phosphate ErbB4 protein level was evaluated by Western blotting. The results showed that AG1478 significantly impaired the performances in T-maze and MWM (spatial learning and memory), contextual fear conditioning and discrimination learning paradigm (non-spatial working and reference memory), enhanced neurogenesis loss, downregulated the expression of p-ErbB4 and total ErbB4 protein, which could be reversed by running. Taken together, our study suggested that running ameliorates cognitive impairment and neurogenesis via ErbB4 signaling.

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Different encoding of reward location in dorsal and ventral hippocampus

10.1101/2021.09.07.459245 ◽

2021 ◽

Author(s):

Przemyslaw Jarzebowski ◽

Y. Audrey Hay ◽

Benjamin F. Grewe ◽

Ole Paulsen

Keyword(s):

Calcium Imaging ◽

Hippocampal Neurons ◽

Dorsal Hippocampus ◽

Spatial Navigation ◽

Ventral Hippocampus ◽

Place Cells ◽

Cognitive Map ◽

Population Activity ◽

Reward Seeking ◽

Seeking Behavior

SummaryHippocampal neurons encode a cognitive map for spatial navigation1. When they fire at specific locations in the environment, they are known as place cells2. In the dorsal hippocampus place cells accumulate at current navigational goals, such as learned reward locations3–6. In the intermediate-to-ventral hippocampus (here collectively referred to as ventral hippocampus), neurons fire across larger place fields7–10 and regulate reward- seeking behavior11–16, but little is known about their involvement in reward-directed navigation. Here, we compared the encoding of learned reward locations in the dorsal and ventral hippocampus during spatial navigation. We used calcium imaging with a head- mounted microscope to track the activity of CA1 cells over multiple days during which mice learned different reward locations. In dorsal CA1 (dCA1), the overall number of active place cells increased in anticipation of reward but the recruited cells changed with the reward location. In ventral CA1 (vCA1), the activity of the same cells anticipated the reward locations. Our results support a model in which the dCA1 cognitive map incorporates a changing population of cells to encode reward proximity through increased population activity, while the vCA1 provides a reward-predictive code in the activity of a specific subpopulation of cells. Both of these location-invariant codes persisted over time, and together they provide a dual hippocampal reward-location code, assisting goal- directed navigation17, 18.

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