Compromised Grid-Cell-like Representations in Old Age as a Key Mechanism to Explain Age-Related Navigational Deficits

Abstract

A progressive loss of navigational abilities in old age has been observed in numerous studies, but we have only limited understanding of the neural mechanisms underlying this decline [1]. A central component of the brain's navigation circuit are grid cells in entorhinal cortex [2], largely thought to support intrinsic self-motion-related computations, such as path integration (i.e., keeping track of one's position by integrating self-motion cues) [3-6]. Given that entorhinal cortex is particularly vulnerable to neurodegenerative processes during aging and Alzheimer's disease [7-14], deficits in grid cell function could be a key mechanism to explain age-related navigational decline. To test this hypothesis, we conducted two experiments in healthy young and older adults. First, in an fMRI experiment, we found significantly reduced grid-cell-like representations in entorhinal cortex of older adults. Second, in a behavioral path integration experiment, older adults showed deficits in computations of self-position during path integration based on body-based or visual self-motion cues. Most strikingly, we found that these path integration deficits in older adults could be explained by their individual magnitudes of grid-cell-like representations, as reduced grid-cell-like representations were associated with larger path integration errors. Together, these results show that grid-cell-like representations in entorhinal cortex are compromised in healthy aging. Furthermore, the association between grid-cell-like representations and path integration performance in old age supports the notion that grid cells underlie path integration processes. We therefore conclude that impaired grid cell function may play a key role in age-related decline of specific higher-order cognitive functions, such as spatial navigation.

Keywords: aging; entorhinal cortex; fMRI; grid cells; human; path integration; spatial navigation.

Figure 1

Object-Location Memory Task (A) During fMRI scanning, participants performed multiple trials of an object-location memory task in a virtual environment (160 × 160 virtual meters [vm]), which contained three target objects. In each trial, participants had to navigate to the location of one cued target object. Task accuracy was expressed for each trial by the “error distance,” which was calculated as the Euclidean distance between the target object’s correct location and the participant’s response. (B) Example trial of the object-location memory task: First, all target objects disappeared, and a cue image of one target object was shown (e.g., a soccer ball). Participants navigated to the position of the cued target object and confirmed their choice of location with a button press. A smiley face provided feedback as to the accuracy of the response. Participants were instructed to aim for green smiley face feedback (error distances <20 vm) and avoid yellow smiley faces (error distances 20–30 vm) or red smiley faces (error distances >30 vm). If the error distance was larger than 20 vm, the target object reappeared and had to be collected, allowing for (re-)encoding of its correct location. After each trial, the participant was automatically transported to a random position within the environment before the next trial started. (C) Task accuracy in the object-location memory task. After having learned the target object’s locations in the preparatory session (left panel), both young and older adults were able to perform the task with required accuracy during fMRI scanning (right panel). Blue and orange lines indicate group mean ± SEM; black dashed lines indicate error distance thresholds for different smiley face feedback. Plots show the first 30 trials of the preparatory session and 115 trials for fMRI scanning, which are the minimum numbers of trials that all participants completed.

Figure 2

Grid-Cell-like Representations in Entorhinal Cortex of Young and Older Adults (A) Higher magnitude of grid-cell-like representations in young relative to older adults. The effect of grid-cell-like representations in older adults was not significantly different from zero. (B) In control analyses for different symmetrical models (5-fold/7-fold), representational magnitudes were not significantly different from zero, either for young or for older adults. (C) Lower temporal stability of grid-cell-like representations in older as compared to young adults. Dashed line indicates 50% chance level. Temporal stability scores were significantly different from chance level in young, but not in older, adults (young: t₁₉ = 4.93, p < 0.001; old: t₂₀ = −1.55, p = 0.136). (D) Significant grid-cell-like representations in young adults for models with reduced data, both when the duration of scanning runs (left bar) or the duration of individual translation events (right bar) was reduced. Dashed line indicates mean grid-cell-like representation magnitude of young adults for the full dataset. Error bars indicate SEM; ^∗p < 0.05; units of representational magnitudes are parameter estimates. See also Figures S1 and S2 and STAR Methods.

Figure 3

Path Integration Performance and Association with Entorhinal Grid-Cell-like Representations (A) Example path from top-down perspective. There were three stopping points along each path. While walking along a path, participants had to stop at each stopping point and estimate the direct distance and orientation to the path’s starting point (black dashed arrows). (B) In the “body-based” modality, the head-mounted display showed no visual input, so that participants experienced only body-based cues during movement along the path. Participants held a wooden stick and were guided by the experimenter along the path. At each stopping point, the distance to the starting point had to be estimated verbally in meters and centimeters and participants turned their body on the spot to indicate the orientation to the starting point. (C) In the “visual” modality, participants sat stationary on a chair. The head-mounted display showed a floor texture consisting of white “limited lifetime dots” on a black ground plane, which provided optic flow information while preventing use of fixed reference points (see STAR Methods). Automated movement along each path was shown from first-person perspective, and on each stopping point, participants estimated the distance to the path’s starting point verbally in meters and centimeters and indicated the presumed orientation by turning their view in the virtual environment to the left or right using a joystick. (D) Higher path integration errors of older adults, both in the body-based and the visual modality. Error bars indicate SEM; ^∗p < 0.05. (E) In young adults (left), the magnitude of grid-cell-like representations was not associated with path integration errors in either the body-based or the visual modality. In older adults (right), higher magnitudes of grid-cell-like representations were associated with lower path integration errors. Path integration errors were z-scored for display purposes. See also Figure S3 and STAR Methods.