Spatial Navigation in the Elderly with Alzheimer’s Disease: A Cross-Sectional Study

Abstract

Background:

Spatial navigation is a fundamental cognitive ability that allows an individual to maintain independence by facilitating the safe movement from one place to another. It emerges as one of the first deficits in patients with Alzheimer’s disease (AD).

Objective:

To compare spatial navigation performance in the healthy elderly and AD patients through use of the Floor Maze Test (FMT)— an easy-to-apply two-dimensional (2D) maze— and determine which cognitive and functional capacities were associated with performance in this task.

Methods:

The FMT was administered to 24 AD patients and 36 healthy controls. Spatial navigation was evaluated through the FMT. Functional capacity was evaluated through the Senior Fitness Test battery of tests. Cognitive functions were evaluated through the Mini-Mental State Examination (MMSE), verbal fluency, digit span test, and the Rey Auditory Verbal Learning Test (RAVLT).

Results:

The group with AD was significantly slower and presented more errors at all stages of the FMT. Planning Time (PT) performance was associated with cardiorespiratory resistance (Step test) and delayed memory according to the RAVLT (R² = 0.395, p < 0.001). Performance in the Immediate Maze Time (IMT) and Delayed Maze Time (DMT) was associated with global cognitive status (MMSE) (R² = 0.509) and delayed memory (R² = 0.540).

Conclusion:

Patients with AD present significant spatial navigation deficits. Their performance on the FMT is influenced by cardiorespiratory capacity, memory, and global cognitive function. As exercise helps to improve executive function and functional capacity, future intervention studies should be carried out to analyze the possible effects of physical exercise on spatial navigation.

Keywords

Alzheimer’s disease functional capacity executive function spatial navigation

INTRODUCTION

The pathology of Alzheimer’s disease (AD) is initially selective for temporal regions, and the appearance of neurofibrillary tangles in the entorhinal cortex and hippocampus is known to be associated with the early clinical stages of the disease [1]. Deficits in the ability to learn and remember new information may be considered the main clinical symptoms of the disease, although several other cognitive impairments have been observed in patients with AD, such as deficits in executive function and spatial orientation [2, 3].

Memory impairment and topographical disorientation arise among the first symptoms of AD [4, 5]. Spatial navigation is a complex, fundamental cognitive ability that allows an individual to maintain independence by facilitating the safe movement from one place to another, and it emerges as one of the first deficits in patients with AD [6, 7]. A spatial navigation task can be divided by the reference frames used to construct the representation of space, namely the allocentric reference frame (object-to-object) or egocentric reference frame (self-centered). Allocentric navigation relies on the spatial relationships among landmarks to construct a cognitive map of the environment. This representation occurs regardless of the location of the navigator, and is associated with place cells located in the hippocampus and grade cells (entorhinal cortex). Egocentric navigation provides metric information about the position of the body in space with a constant update. This type of frame depends on head direction cells located in the retrosplenial cortex, as well as the caudate nucleus, medial parietal lobe, posterior parietal area, and precuneus [6]. Some studies suggest that navigation deficits in healthy older people may be restricted to allocentric navigation, with a maintenance of egocentric strategies [6, 8]. However, patients with AD have demonstrated both egocentric and allocentric spatial impairments [7]. Whereas the deficits observed in healthy aging may be explained by neurobiological changes in the prefrontal cortex and their effects on executive function and working memory, individuals with AD exhibit a decline that is associated with atrophy of the hippocampus and entorhinal cortex [6]. An allocentric representation is created by CA3 (allocentric view-point dependent representation) and CA1 (allocentric view-point independent representation) neurons [9]. Considering the preservation of these areas (particularly CA1) in normal aging as compared to AD, the impact on allocentric navigation may be even greater in AD, because while normal aging is supposed to affect only the representation creation of the general scene, patients with AD are affected in both allocentric abilities [6]. In this sense, this specific decline in spatial navigation may help to discriminate normal aging from AD. Studies using magnetic resonance imaging (MRI) have shown an association between impaired performance in spatial navigation tasks in elderly people with AD and reduced volumes of the hippocampus and regions of the parietal cortex [10, 11].

Considering that spatial navigation is a complex task that involves route-planning and way-finding strategies, a decline in this capacity may contribute to a loss of independence in the activities of daily living through impairment of the ability to navigate in unfamiliar and familiar environments, as the severity of AD progresses [6]. Several authors have shown that spatial navigation may help to differentiate healthy older people from those with AD, both in tasks that involve learning a route and in path-finding tasks [12, 13].

Virtual reality tests, such as the Morris water maze task and Virtual Y-maze can be used to test for navigation, but such tests are typically based on spatial navigation tasks [6 , 14], or displacement tasks in real environments [12 , 16]. However, from the perspective of clinical applicability, the instruments used to evaluate spatial navigation have limitations. Virtual reality tests exclude movement through the environment. In real conditions, it is through the integration of sensory information from the vestibular, proprioceptive, and visual systems that the human body generates information about movement [17, 18]. In addition, the high cost to develop, apply, and maintain these tests reflect important difficulties faced in their implementation on a large scale, as well as the need for specific technical support to set up virtual environments [19]. Regarding the tests in real environments, wide public spaces are generally used, which can be affected by the interference of other people during the execution of tasks, and are associated with the establishment of very different protocols and evaluation forms, thereby making it difficult to reproduce the evaluations and interpret the results.

Among the different strategies employed to evaluate spatial navigation, the Floor Maze Test (FMT) emerges as an easy-to-apply task, which requires an allocentric orientation during a navigation task, through the integration of walking and navigation in a two-dimensional (2D) (width×length) maze. This evaluation was presented as a clinical spatial navigation test with applicability in real-life daily situations [20], which highlights its ecological validity. Participants are guided to find the only existing correct path that leads to the exit of the maze.

A recent study [21] investigated the relationship between spatial navigation performance and the risk of developing mild cognitive impairment (MCI), in which healthy subjects were monitored for 4 years (2011–2015). The authors of that study showed that poorer performance in spatial navigation, as measured by the FMT, doubled the chances of developing MCI. When separated by steps, increases in the Immediate Maze Time (IMT) may represent up to a 25% chance of developing MCI. The Delayed Maze Time (DMT) alone showed no associations with the incidence of MCI. It should be noted that MCI is a clinical syndrome that has been associated with an increased risk for AD. Most studies report that the progression rates of MCI to AD are between 20% and 40%, being 10% to 15% per year [22].

In addition to the FMT evaluation of spatial navigation, other cognitive abilities are associated with performance in navigational tasks such as executive functions [12, 17], namely episodic, verbal and non-verbal memory [14, 17], and the discrimination of optical flow [23]. Those skills are influenced by physical activity and may be mediated by functional capacities, such as aerobic capacity, strength, and mobility. In this sense, Vidoni et al. [24] verified relationships among aerobic capacity, brain atrophy, and dementia progression in patients with AD. Perea et al. [25] also reported a correlation between higher levels of aerobic fitness and the preservation of white matter integrity. Furthermore, Eggermont et al. [26] showed a relationship between mobility (assessed by the four-meter walk test, timed Up and Go test, and sit-to-stand test) and executive function. Moreover, a recent study showed that sedentary behavior is associated with reduced thickness of the medial temporal lobe [27], an important area related to allocentric navigation.

Thus, the objectives of the present study were twofold: to compare the performance in the FMT of healthy elderly individuals and those diagnosed with AD; and examine the relationships between spatial navigation performance in the FMT, and cognitive and functional abilities. Considering the positive relationship between physical activity and cognition, we hypothesized that functional capacity could also predict spatial navigation performance in the FMT.

MATERIALS AND METHODS

In this cross-sectional study, the final sample consisted of 60 literate elderly adults, aged 60 years and older, including 24 patients diagnosed with AD and 36 healthy controls. The selection and diagnoses were performed by the medical staff at the Center of Alzheimer’s Disease of the Psychiatry Institute in the Federal University of Rio de Janeiro. Diagnostic assessments were performed using a structured clinical interview to assess mental disorders, according to the Diagnostic and Statistical Manual of Mental Disorders (DSM-V). The Clinical Dementia Rating (CDR) scale was applied to measure the severity of dementia in patients with AD [28]. Patients with AD classified with mild (CDR1) or moderate (CDR2) dementia were included. All individuals without any type of cognitive impairment, or psychiatric or neurological disorder, as confirmed by a psychiatrist through clinical interviews using the same clinical protocol were considered healthy elderly people. The exclusion criteria for AD were: cerebral infarction; ongoing treatments like electroconvulsive therapy and psychotherapy; any other presenting neurological disorders; dementia diagnoses other than AD; and the presence of any physical disability that rendered the individual unable to perform assessments; and severe visual and/or hearing impairment. For healthy elderlies, the exclusion criteria were the presence of any physical disability that rendered the individual unable to perform assessments; the presence of neurological or mental disorders, and severe visual and/or hearing impairment. All patients signed the written informed consent form, and had access to all relevant research information and the main researcher’s contact information. A flowchart showing the method of selection of the participants is presented in Fig. 1 The study was approved by the Research Ethics Committee at IPUB-UFRJ, under the following CAAE registration number: 24904814.0.0000.5263, and is part of the main research project titled “Efficacy of physical exercise in the treatment of major depression, Alzheimer’s Disease, and Parkinson’s Disease,” which was registered under the Brazilian Registry of Clinical Trials (REBEC) protocol RBR-4M3K2C.

Fig. 1.

. Flow chart showing method of selection of subjects.

Procedures and tests

All participants performed the assessments over three visits. During the first visit, we presented to them the details of the study, they signed the written informed consent form, anthropometric measurements were taken, and responses to anamnesis and neuropsychological tests were recorded. During the second visit, individuals underwent a cardiac examination, consisting of a cardiovascular stress test on a treadmill ergometer (a ramp protocol) [29], before being released to the physical tests. During the third visit, individuals performed physical tests and the FMT.

Cognitive assessment

All participants were subjected to a neuropsychological assessment comprising the following tests: the MMSE to evaluate global cognitive status (0–30 score) [30]; and the Rey Auditory Verbal Learning Test (RAVLT), for the assessment of learning and memory [31]. Only the RAVLT-A7 measure for the 30-min delayed recall (0–15 score) was recorded in this study. The Verbal Fluency - Animal Category (VF) was used to assess executive functions, semantic memory, and language (0–max score) [32]; and the digit span test (forward - backward), a subtest of the Wechsler Adults Intelligence Scale (WAIS-R), assessed short-term memory, attention, and working memory [33]. In all of these tests, the highest scores represented the best performance. We also performed the Trail Making Test, forms A (TMT A) and B (TMT B) to evaluate visuospatial skills and executive function, and the Stroop test (color-word condition) to investigate attention and inhibitory control [34].

Senior fitness test

After the cardiologist’s approval, participants underwent the battery of functional tests of the Senior Fitness Test [35]. The following tests of the original battery were used: The 8-foot Up and Go test, the sit-to-stand test, and the stationary gait for 2 min (Step test) to evaluate aerobic endurance.

The 8-foot Up and Go test: The participant started from the sitting position in a chair, moved in a straight line for 2.44 m, proceeded around a cone, and returned to the initial position, in the shortest time possible. Three trials were performed and the best performance was used in the analysis. The purpose of this test was to evaluate speed, agility, and dynamic balance.

Sit-to-stand test: In this evaluation, the participant had to rise to a full stand and return to a fully seated position in a chair, as many times as possible within a 30-s interval. The test was used to measure the strength of the lower limbs.

Step test: 2-min Step test is an easy-to-use method to assess the aerobic endurance of older adults. A mark was drawn on a wall or door with the aid of tape, which corresponded to a point exactly midway between the subject’s patella and the iliac crest. After the signal to “go,” the participant had to alternate steps, without moving forward, within a given timeframe. The score recorded was the number of times the right knee reached the required height within 2 min.

Floor Maze Test

The FMT (Fig. 2) was applied on the third visit, along with functional tests. This test was easy to apply and required skills of orientation, as it entailed walking through a 2-D maze [20]. Participants were positioned at the entry of the maze and then given instructions to find the only correct way that led to the exit. Three stages were evaluated: Planning Time (PT), which is the time spent between the receipt of instructions and discovery of the correct way out, excluding the time spent walking; IMT, which is the time spent walking between the entry of the maze and the successful exit; and DMT, which is the time spent on repetition of the second time period, performed after 10 min without planning. During this interval, the participants were not able to maintain visual contact with the maze. Route corrections while walking were counted as errors. The two main measurements used for this test were the time spent during each stage and the number of errors.

Fig. 2.

. Floor Maze Test. The beginning occurs in the triangle and X represents the exit.

Statistical analysis

Normality and homoscedasticity were analyzed by the Kolmogorov–Smirnov and Levene tests, respectively. The differences between groups for variables that presented a normal distribution were analyzed through the independent samples t-test. The Mann–Whitney U-test was performed for variables that did not present a normal distribution. Chi-squared analysis was performed to evaluate differences between both groups in the percentage of error-free performance in the IMT.

The relationship and possible association between FMT performance and independent variables (cognitive and functional) were analyzed using Pearson’s correlation for variables with a normal distribution, or Spearman’s correlation for variables that did not show a normal distribution. They were both later adjusted by the Bonferroni test (p = 0.005 for Pearson’s correlation, and p = 0.004 for Spearman’s correlation). Associations were also evaluated using multiple regression models. Because the PT, IMT, DMT, and delta (i.e., DMT - IMT) data, used as a measure of retention ability during the test, were not normally distributed, these variables were transformed to log¹⁰. Multiple linear regression analysis was performed for all functional and cognitive variables of interest for the three stages measured by the FMT. Immediately thereafter, a stepwise model was used, removing the least significant variables, until only the significant variables remained in the model. Statistical analysis was conducted using the SPSS ^® software version 20.0 (IBM Corporation, NY, USA). The level of significance was set at p≤0.05.

RESULTS

Among patients with AD, 18 (75%) were classified as CDR 1 and 6 (25%) were classified as CDR 2. Descriptive data of the sample, as well as the results of functional tests and cognitive tests are presented in Table 1.

The performance of the groups at each FMT stage is shown in Table 2. In the control group, 28 individuals (77.8%) completed the test without errors, whereas only six patients in the group with AD (25%) showed similar performance. A significant difference was noted between the two groups for IMT and DMT errors (p < 0.001), and a greater number of individuals in the AD group committed errors during the task.

Table 1

Demographic, functional and cognitive characteristics of the samples

	Controls (n = 36)	AD (n = 24)	t/ U	p
Age (years)	70 (60–94)	79 (61–90)	201.5^b	<0.001^*
Education (years)	13 (3–24)	12 (3–23)	331.5b	0.12
BMI (kg/m²)	26.1±2.9	24.5±4.6	–1.588^a	0.118
VO₂ max (mL. kg-¹.min^–1)	23.1±6.1	18.3±5.3	–2.897^a	0.006^*
8-foot Up and Go (s)	6.2±1.1	7.9±2.3	3.669^a	0.001^*
Sit-to-stand	12.9±2.9	10.5±2.1	–3.473^a	0.001^*
Step test (score)	89.7±19.6	68.3±26.0	–3.482^a	0.001^*
MMSE (score)	29 (24–30)	21 (11–28)	28.5^b	<0.001^*
RAVLT- A7 (score)	8 (2–13)	0 (0–3)	22.0^b	<0.001^*
Verbal Fluency (score)	18.5 (7–28)	9.5 (2–28)	95.5^b	<0.001^*
Stroop (s)	30.4 (19.7–96.8)	45.8 (29.8–110.1)	109.5^b	<0.001^*
Trail A (s)	56.4 (24.6–168.8)	93.7 (50.0–239.1)	134.5^b	<0.001^*
Trail B (s)	110.8±34.7	143.3±96.1	1.43^a	0.16
Digit Backward (score)	5 (2–10)	4 (1–8)	259.0^b	0.02^*

BMI, Body Mass Index; MMSE, Mini-Mental State Exam; RAVLT, Rey Auditory-Verbal Learning Test. Values are presented as mean±standard deviation, or median (minimum–maximum). a = t, t-test of independent samples. b = Mann–Whitney U-test. AD, Alzheimer’s disease. ^* = statistically significant difference (^*p≤0.05).

Table 2

Performance on each FMT stage of the samples

Completed FMT	Controls (n = 34)	AD (n = 24)	U	p	d
Planning Time (s)^a	34.1 (8.7–122)	104.2 (25.8–165.6)	110	<0.001	1.67
IMT (s)^a	20.5 (9.6–69.5)	87.4 (25.4–146.7)	41	<0.001	2.28
Delayed Maze Time (s)^a	14.2 (9.5–53.8)	85.6 (16.4–186.6)	30	<0.001	2.47
Delta (s)^a	–6.0 (–39.1–21.7)	–2.3 (–70.0–10.5)	397	0.597	4.51
IMT errors (score)^a	0 (0–4)	1 (0–5)	183.0	<0.001	–1.18
DMT errors (score)^a	0 (0–3)	2 (0–6)	97.0	<0.001	–1.63

FMT, Floor Maze Test; ^amedian (minimum–maximum). Mann–Whitney U-test; AD, Alzheimer’s disease; d, effect size; IMT, Immediate Maze Time; DMT, Delayed Maze Time. Delta = (DMT - IMT).

The AD patients were significantly slower than the controls at all stages, leading to a relatively large effect size, ranging from 1.67 to 2.47, and highlighting the greater difficulty faced by AD group to complete the FMT. The average median values observed in both controls and AD patients showed a progressive reduction in time spent as follows: PT > IMT > DMT.

The FMT presented strong and significant correlations between each stage. The PT was correlated with both the IMT (r_s = 0.691, p < 0.001) and DMT (r_s = 0.698, p < 0.001). Moreover, the IMT was significantly correlated with the DMT (r_s = 0.778, p < 0.001). The delta measurement had no significant correlations with functional or cognitive variables. Correlations between each stage of the FMT, and the cognitive and functional tests are presented in Fig. 3A, 3B, and 4, respectively. Analysis of the results of multiple regression models (Table 3), and the RAVLT-A7 measure and aerobic capacity (Step test) combined model showed associations with PT (R² = 0.395, p < 0.001).

Fig. 3.

A. Correlations between stages on the Floor Maze Test and neuropsychological tests. PT, planning time; IMT, immediate maze time; DMT, delayed maze time; MMSE, Mini-Mental State Exam; RAVLT, Rey Auditory Verbal Learning Test; r, Pearson’s correlations; r_s, Spearman’s corrections. B. Correlations between stages on the Floor Maze Test and neuropsychological tests. PT, planning time; IMT, immediate maze time; DMT, delayed maze time; TMT, Trail Making Test; r_s, Spearman’s corrections. Level of significance, p≤0.05.

Fig. 4.

. Correlations between stages on the Floor Maze Test and functional tests. PT, planning time; IMT, immediate maze time; DMT, delayed maze time; r, Pearson’s correlations; r_s, Spearman’s corrections. Level of significance, p≤0.05.

Table 3

Multiple regression models of the associations between the FMT components and independent variables

	Planning Time			Immediate Maze Time			Delayed Maze Time			ΔFMT
	R² adjusted = 0.395–0.367*			R² adjusted = 0.509–0.474*			R² adjusted = 0.540–0.527*			R² adjusted = 0.776–0.199*
	B	95% CI	p	B	95% CI	p	B	95% CI	p	B	95% CI	p
MMSE	–	–	–	–0.025	–0.043, –0.007	0.007	–0.029	–0.049, –0.009	0.005	–	–	–
RAVLT-A7	–0.046	–0.067,–0.025	<0.001	–0.031	–0.055, –0.007	0.011	–0.038	–0.065, –0.011	0.006	–	–	–
Step test	–0.004	–0.007, 0.000	0.038	–	–	–	–	–	–	–	–	–
Stroop	–	–	–	–	–	–	–	–	–	0.457	0.226, 0.689	<0.001
Trail A	–	–	–	–	–	–	–	–	–	–0.149	–0.287, –0.011	0.035
Controlled by age
MMSE*	–	–	–	–3.526	–5.750, –1.302	0.002	–4.725	–7.129, –2.320	<0.001	–	–	–
RAVLT-A7*	–5.357	–8.011, –2,705	<0.001	–3.144	–5.873, –0.416	0.025	–3.112	–6.061, –0.162	0.039	–	–	–
Step test*	–0.516	–0.976, –0.057	0.028	–	–	–	–	–	–	–	–	–
Stroop*	–	–	–	–	–	–	–	–	–	0.810	0.376, 1.244	<0.001
TMT A*	–	–	–	–	–	–	–	–	–	–0.321	–0.578, –0.064	0.015

FMT, Floor Maze Test; MMSE, Mini-Mental State Exam; RAVLT, Rey Auditory Verbal Test; TMT, Trail Making Test; B, unstandardized coefficients; CI, Confidence Interval; Delta, (DMT - IMT). *Adjusted by age. Level of significance, (p≤0.05).

Regarding the IMT and DMT, an association was found between the global cognitive status (MMSE) and RAVLT-A7 delayed recall (R² = 0.509 and R² = 0.540, respectively); whereas a more favorable delta model consisted of the combination of attention and inhibitory control (Stroop) and visuospatial skills (TMT A) (R² = 0.776, p < 0.001). All models remained significant after controlling for age: PT (R² = 0.367, p < 0.001), IMT (R² = 0.474, p < 0.001), DMT (R² = 0.527, p < 0.001), and delta (R² = 0.199, p = 0.002). The overall results are presented in Table 3.

DISCUSSION

In this study, patients with AD had impaired performance on all the three stages of the FMT compared to controls. This means that individuals with AD presented a greater number of errors, and were consequently slower than the control group in this spatial navigation task, both in planning of the task, and in its execution immediately thereafter, as well as recalling the route after a ten-minute period. In another study corroborating our results, in tasks that required planning, individuals with AD showed greater difficulty in distinguishing relevant from irrelevant information, resulting in difficulties in planning and finding the solution to a path-finding task [12]. The deficit presented in recalling a route was also observed in studies in which elderly individuals with AD were required to remember the correct route through the corridors of a clinic, and presented a greater number of errors than individuals in other groups [15, 36].

In verifying the magnitude of the deficits presented by the AD patients, we observed that the effect sizes were large during the three periods of observation in the FMT, which highlights the considerable difficulty with which these individuals are faced to perform the task, as compared to the controls. However, Tangen et al. [37] also used the FMT, and obtained moderate effect sizes for PT and DMT (d = 0.40 and 0.35, respectively)—results that are four to five times lower than those observed in the present study. One possible explanation is the composition of the control group; in the present study, the control group was composed of healthy subjects, whereas in the study of Tangen et al. [37], the group with AD was compared to subjects with MCI and subjective memory complaints. Indeed, the inclusion of healthy subjects as controls in the present study might overestimate the discriminative performance of the FMT.

In the present study, significant associations were found between FMT performance and both functional and cognitive tests. Cardiorespiratory fitness, as measured by the Step test, along with delayed memory, evaluated by the RAVLT-A7 test, explained almost 40% of the PT performance, both before and after controlling for age. The involvement of cardiorespiratory fitness in planning of the task corroborates studies that show positive associations between cardiorespiratory fitness and executive functions, and cognitive abilities responsible for planning, cognitive flexibility, and decision making [38, 39]. Performance in the IMT and DMT was associated with global cognitive status, as evaluated by the MMSE, as well as delayed memory. These tests accounted for 51% of IMT performance and 54% of DMT performance, and showed a reduction in these values after controlling for age (47% and 52%, respectively). Memory during the three stages of the FMT could be explained by imaging studies that have shown the activation of the hippocampus both for the formation and recall of cognitive maps [40], which highlights the importance of this brain structure in spatial navigation. However, the understanding that navigation is a complex skill that requires connections between various areas of the brain, such as the parietal, temporal, and frontal cortices [3, 41], supports an understanding of the association between the FMT and MMSE, as these instruments evaluate different cognitive capacities, such as temporal and spatial orientation, attention, and language [30].

An association between memory and FMT was also reported by Tangen et al. [37], but only in the DMT. Sanders et al. [20] observed an association between memory and the IMT alone. It is important to highlight that different instruments were used to evaluate memory among the previous studies, which makes it difficult to compare the results obtained. However, memory tests generally showed an association with spatial navigation performance even when evaluation protocols other than the FMT were used [14, 36].

We also found a positive correlation between TMT A and FMT performance, suggesting a relationship between visuospatial skills and spatial navigation. These findings corroborate the results of Verghese et al. [21] and Tangen et al. [37]. By investigating the relationship between spatial navigation performance and the risk of developing MCI in a community of healthy elderly individuals, Verghese et al. [21] found an association between FMT and TMT A, but no such association with TMT B. Tangen et al. [37] also found an association between the TMT and spatial navigation in individuals with MCI and AD, with a 10-s increase in TMT B, representing a 4% worsening of the IMT. These results suggest that with progression of the disease, there is a greater demand for executive functions to carry out the task. One possible explanation for the greater association between executive functions and spatial navigation performance in patients with MCI and AD is the need to recruit other cognitive resources, in addition to those expected for the task in healthy subjects. In addition, Lithfous et al. [7] suggested that increased frontal demand may represent greater use of egocentric strategies to compensate for cognitive deficits in spatial navigation tasks. However, in contrast to our findings and those of Tangen et al. [37], Verghese et al. [21] found no relationship between FMT and memory, which may be justified by the differences between the populations investigated. These data support the idea that spatial navigation is a complex skill that is dependent on several brain circuits, which tend to be modified with the progression of AD.

According to Verghese et al. [21], the FMT delta is a variable that is able to measure the learning ability for a task. However, considering that the learning process is complex and involves memory consolidation [42], FMT delta in the present study was interpreted as a variable that is related to retention capacity. Although the delta was not statistically significant, in comparison to the control group, the AD group showed higher variability in delta scores, made more errors, and was slower during the DMT, representing a less favorable retention index in these individuals. In the regression model, the delta showed an association between inhibitory control and attention, and was responsible for predicting 77% of performance in the task. Even after controlling for age, the results remained significant. According to Proulx et al. [43], an important neurobiological mechanism for the attention process is cholinergic modulation through the excitation of neurons that have nicotinic receptors in layer VI of the prefrontal cortex. However, these systems are impaired by increasing age and AD, and the availability of acetylcholine in the synaptic cleft is reduced, with atrophy in the prefrontal areas [44]. Although we found no correlations between functional performance and the FMT delta, aerobic capacity has often been associated with preservation of the prefrontal cortex and executive functions in older people who are healthy, and those with AD [45, 46]. In this sense, an association between increased retention capacity during spatial navigation tasks and higher levels of physical conditioning could be expected. However, the large variability of delta values reported by Verghese et al. [21] and found in the present study, mainly in the group with AD, suggest the possibly low sensitivity of the measure to differentiate the performance of different groups. Thus, caution is needed in the use and interpretation of data generated by this measure, particularly when isolated from the other FMT variables.

To our knowledge, this is the first study to evaluate spatial navigation using the FMT in a Brazilian population diagnosed with AD. Another important aspect was the inclusion of functional variables to verify the possible effects on spatial navigation performance through application of the FMT. It is reasonable to propose, considering the relationship between aerobic capacity and the PT of the FMT, that clinical interventions should include aerobic training, to maintain or improve spatial navigation in patients with AD. However, it should be noted that this study has some important limitations. The cross-sectional design did not allow the establishment of cause-effect inferences regarding the decline in navigational skills. In addition, the sample was relatively small, thereby requiring cautious interpretation of the results obtained.

Conclusion

Patients with AD present significant deficits in spatial navigation at all stages of the FMT. Furthermore, FMT performance is influenced by cardiorespiratory capacity, memory, and global cognitive status. The retention capacity during the FMT might be limited mainly by executive function performance (e.g., attention and inhibitory control). As exercise helps to improve executive function and functional capacity, future intervention studies should be carried out to analyze the possible effects of physical exercise on spatial navigation.

DISCLOSURE STATEMENT

Authors’ disclosures available online (https://www.j-alz.com/manuscript-disclosures/18-0819r2).

Footnotes

ACKNOWLEDGMENTS

This study was supported by grants received from CNPq (301483/2016-7) and FAPERJ (E-26/ 203.193/2016).

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