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. Author manuscript; available in PMC: 2026 Jan 24.
Published in final edited form as: Gait Posture. 2026 Jan 7;125:110095. doi: 10.1016/j.gaitpost.2026.110095

Links Between Central Visual Field Loss and Movement Processing during Walking

Natela M Shanidze 1,*, Catherine P Agathos 1, Toby J Ellmers 2, William R Young 3
PMCID: PMC12829985  NIHMSID: NIHMS2136949  PMID: 41512710

Abstract

Background:

Central visual field loss (CFL) is the most common irreversible visual impairment in aging and is associated with higher fall risk and concerns about falling. This study explored the links between CFL severity, functional balance, and walking-related attentional processing implicated in reduced gait performance.

Methods:

In Study 1, 29 individuals with CFL and 29 age-matched controls completed the Timed Up and Go (TUG) test. In Study 2, 10 CFL participants and 10 controls performed the TUG while acceleration data were collected from head and trunk IMUs. For both studies, we assessed visual impairment severity (contrast sensitivity) and participants’ attentional processing during walking (Gait-Specific Attentional Profile, G-SAP).

Results:

Both groups showed positive correlations between TUG duration and G-SAP subscales. G-SAP scores were lower in CFL participants with worse contrast sensitivity indicating reduced cognitive processing during walking. Worse contrast sensitivity was also associated with greater head and trunk acceleration and acceleration variability during walking, suggesting reduced gait stability. Higher rumination and conscious movement processing scores also correlated with improved segmental control in CFL.

Significance:

Increased cognitive processing of gait is associated with impaired functional balance. This association appears to be reversed in CFL, with severe visual deficit diverting cognitive resources from movement control. This altered strategy may prioritise the acquisition and processing of visuospatial information in CFL. The observed postural instability with increasing CFL severity and a lack of excessive cognitive involvement in movement control suggest heightened gait-specific attention could be leveraged for balance and gait training in CFL.

Keywords: visual deficit, macular degeneration, gait-specific attention, aging, contrast sensitivity, timed up and go

1. Introduction

Age related macular degeneration (AMD) affects nearly 200 million people worldwide [1] and is projected to increase with the aging population [2]. Macular degeneration (both age-related and juvenile) is the leading cause of central visual field loss (CFL). This loss of vision has significant implications for quality of life [3,4], leads to mobility limitations [5], and presents significant risk of falling [6-8]. While much is known about the visual limitations associated with CFL, increased fall risk is one of its most dangerous potential consequences that requires further study, especially in older people most often affected by macular degeneration [9].

Loss of the central visual field compromises visual acuity, contrast sensitivity, stereovision and dark adaptation [10,11]. Loss of contrast sensitivity seems to be particularly debilitating for safe and efficient mobility [12]. Not only is CFL a significant predictor of increased fall risk and non-fall-related injuries [7,13], evidence from laboratory-based studies show that people with CFL tend to adopt a more cautious (and less efficient) gait pattern, including reduced walking speed and longer double-support duration [14-17]. Yet, despite this caution, people with CFL also produce a larger number of gross stepping errors increasing the risk of tripping [18]. In addition to changes in mobility, CFL is also associated with psychological changes related to balance/falls, e.g., greater concerns (i.e., “fears) about falling [19,20] and mobility [21], and associated activity avoidance [22] .

There is strong evidence that psychological processes related to concern about falling [23] can have a profound influence on balance and gait (i.e., the adoption of conservative movement strategies [24]). For instance, both conscious movement processing (CMP) and worrisome thoughts about falling are linked with increased cognitive demands of walking, maladaptive changes in movement planning, and stepping errors [24]. These psychological factors are also associated with restrictions in visual search of the intended walking route [25,26] processes that are presumably affected by CFL [26].

It is now widely understood that people with compromised coordination of balance and gait tend to consciously control movement, presumably in an attempt to compensate for loss of automatic movement control [27]. There is ongoing debate regarding the extent to which these cognitive movement processes are maladaptive [24]. On one hand, cognitive and motor inefficiencies associated with CMP might be considered a necessary consequence of consciously prioritising walking safety. On the other, prolonged anxious or worrisome thoughts could increase cognitive load, potentially fuelling fear and arousal, at the detriment to walking safety [24]. Yet, to date, no studies have explored the potential relationship between sensory deficit in CFL, cognitive involvement in gait, and changes in gait stability. This is the aim of the present work.

First, we evaluate relationships between functional balance (assessed via the Timed Up and Go test, TUG, [28,29]) and attentional processes measured by Gait-Specific Attentional Profile (GSAP [30]) in people with CFL and age-matched controls. Additionally, we evaluated the potential relationship between the severity of CFL (in terms of contrast sensitivity loss) and these outcomes. Second, we aimed to evaluate associations with both the diagnosis and severity of CFL, and objective measures of head and trunk stability while walking. The current study thus allows us to examine the relationship between sensory loss (central vision loss) and the adoption of gait-specific cognitive changes. From an applied perspective, exploring how cognitive processes influence body coordination in CFL is an important step for identifying rehabilitation opportunities in this population.

We predicted that both groups would demonstrate a clear positive relationship between the degree of functional balance deficit and G-SAP sub-scales, with higher scores for the latter in CFL due to vision loss inflating concerns about falling and associated attempts to consciously control movements to avoid gross errors/falls. Within the CFL group, we further predicted that greater visual deficits would be associated with higher G-SAP sub-scale scores. For walking, we predicted that individuals with CFL would show greater acceleration and acceleration variability in head and trunk during the TUG, given their poor vision and thus greater tolerance for retinal slip required to maintain head stability during gait. As turns are more challenging than straight walking for older adults, we also expected individuals to show reduced adaptability in segmental stabilization (e.g., increased rigidity) while turning [31,32].

2. Gait-specific attentional processing in central visual field loss

2.1.1. Participants & Vision Screening

Research for both studies was performed in accordance with the Declaration of Helsinki and was approved by the Institutional Review Boards at the Smith-Kettlewell Eye Research Institute (SKERI, CFL group) and Department of Clinical Sciences, Brunel University London (control group). Informed consent was obtained from all participants. We tested 29 individuals with CFL (15F, age: 76.6 ± 18.1). Participants were recruited in San Francisco, USA, immediately following their low vision ophthalmology appointment. Snellen visual acuity (VA) was measured monocularly in each eye (for better eye VA see Table S1), contrast sensitivity (CS) was assessed binocularly, and binocular central field defect was confirmed using the California Central Visual Field (CCVFT) tangent field test [33] (Table S1, Supplementary Materials). Twenty-nine control participants were recruited from community groups in West London, UK (22F, age: 75.1 ± 16.2). Control participants had no visual acuity or CS deficits when tested with uncorrected vision.

Inclusion criteria for CFL participants included central field deficit affecting the macula, ability to walk independently, and a score of >13 on the Montreal Cognitive Assessment for those with blindness or severe visual impairment (MoCA-Blind, [34]). Control participants had to have not been diagnosed with any uncorrectable visual impairment and had to have scored ≥3 on the mini-COG [35]. Controls were selected from a larger cohort of healthy older adult data and matched on age.

2.1.2. Procedure

CFL testing was performed by an experimenter (NMS) immediately following participants’ low vision rehabilitation appointment at the Frank Stein and Paul S. May Center for Low Vision Rehabilitation in San Francisco, CA. Testing of control participants was performed in a laboratory setting, at Brunel University of London by an experimenter (TJE).

All participants completed the Gait-Specific Attentional Profile (G-SAP, [30]). The instrument consists of 11 questions asking the participants to rate on a 5-point Likert scale [① Not at all; ② Not very much; ③ Moderately so; ④ Often; ⑤ Very much so] how they feel when they walk. Separate total scores (summed across all questions within a subscale, max range: 3-15) were generated for the following subscales: CMP (GSAPCMP; QA7-A9; e.g., “I examine the way I walk/move”), anxiety (GSAPANX; QA1-A2, QA10; e.g., “I feel tense”), fall-related ruminations (GSAPRUMS; QA3-A4, QA6; e.g., “Worrisome thoughts about falling run through my mind”). The G-SAP is scored such that higher scores indicate greater propensity for engaging in the subscale-specific attentional/psychological process during gait.

Participants also performed the Timed Up and Go test (TUG, [28,29]), where they stood up from a chair, walked 3 meters, turned around, returned to the chair and sat down. The time (in seconds) to complete the task was recorded as the TUG score.

2.2. Results

2.2.1. Participant Demographics

Control participants were matched based on age to the CFL group (Mann-Whitney, U = 363.5, n1=n2=29, p = 0.38, two-tailed). Participants had comparable outcomes for previous falls (χ2(1, 29) = 1.225, p = 0.268), and TUG duration (paired for age, Wilcoxon matched-pairs signed rank test, p = 0.27).

2.2.2. Walking-related Attentional Processing and Functional Balance

No differences were observed between CFL and control groups in any G-SAP sub-scale (GSAPANX F = 1.248, p = 0.269, GSAPCMP F = 0.228, p=0.635, GSAPRUMS F = 0.29, p=0.593, ANCOVA [age, sex], Figure 1.

Figure 1.

Figure 1.

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G-SAP subscale comparison for anxiety (red), conscious movement processing (blue), and ruminations (purple), (ANCOVA, controlling for age).

We did not observe a significant relationship between the TUG scores and contrast sensitivity in the CFL participants (Spearman ρ = 0.03, p = 0.44).

There were significant positive correlations (partial correlation controlling for age) in participants with CFL between TUG completion times and GSAPANX (r = 0.33, p = 0.045), GSAPCMP (r = 0.61, p < 0.001), and GSAPRUMS (r = 0.51, p = 0.003). There were also significant correlations between TUG times and both GSAPANX and GSAPRUMS in control participants (anxiety: r = 0.43, p = 0.011; ruminations: r = 0.33, p = 0.043). Unexpectedly, we observed stronger relationships between TUG, G-SAPRUMS (Fisher’s zCFL = 0.56 > zCont = 0.34) and G-SAPCMP (zCFL = 0.71 > zCont = 0.31) subscales in CFL participants, compared to controls (Figure 2 A-C).

Figure 2:

Figure 2:

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Attentional profiles. Timed Up and Go scores plotted against G-SAP sub-scales of anxiety (A), conscious movement processing (CMP, B), and ruminations (C). Binocular contrast sensitivities plotted against G-SAP sub-scales of anxiety (D), conscious movement processing (E), and ruminations (F). Filled circles: CFL; open circles: controls; red/blue/purple lines: CFL correlations, grey lines: control.

Within the CFL group, we also examined whether visual acuity and contrast sensitivity were associated with the G-SAP subscale scores. While visual acuity was not correlated with any G-SAP sub-scales (r = [0.17 - 0.23], p = [0.13 – 0.21]), we found significant moderate positive relationships between binocular contrast sensitivity and GSAPANX (Figure 2D) and GSAPCMP (Figure 2E), but not GSAPRUMS (Figure 2F).

2.3. Discussion

The aims of our first study were to explore relationships between functional balance, the severity of CFL, and psychological processes influencing the efficiency of balance and walking. We find that the self-reported attentional processing of walking action is equivalent in both groups and reductions in functional balance (larger TUG score) are associated with higher anxiety, as well as greater propensity to focus on fall-related ruminations and consciously process movement during walking. In those with CFL, however, the degree of vision loss is inversely proportional to their conscious movement processing, anxiety, and ruminations while walking, and is not correlated to their functional mobility.

We expected CFL to exacerbate conscious intervention and worrisome/ruminative thoughts, reasoning that, under threats to stability and/or compromised sensorimotor systems (e.g., in individuals living with neurological disorders, like Parkinson’s [36]), people attempt to consciously control balance and gait actions [40]. While CFL constitutes a sensory deficit, assumed to generate similar compensatory conscious intervention in gait, our prediction was not borne out, as no group differences in any G-SAP sub-scale were observed.

All G-SAP subscales correlated with functional balance for both groups. This is likely an adaptive process of recognising potential threats to stability, allowing individuals to take appropriate actions to minimise risks. For those with CFL, these actions could be practical decisions (e.g., to walk with a white cane), in addition to conscious intervention to guard against movement errors, as suggested by the CMP outcomes [37]. Recent findings on stepping up under time pressure suggest that those with CFL are more cautious than their age-matched healthy-sighted peers, maintaining a more controlled landing strategy [38]. However, this strategic increase in conscious control of movement may not be possible in those with more severe vision loss (and likely, more compromised oculomotor control), due to increased attentional demands of acquiring and processing visual information [39]. Indeed, within the CFL group, we observed clear associations between CFL severity (reduction in contrast sensitivity) and lower G-SAP sub-scale scores. These results initially appear to be in direct contradiction to the observation that impairments in a variety of sensory and/or motor processes often lead to greater general concern about falling [20,40,41] and cognitive demands of walking [42-44] – demands that are thought to be a potential consequence of CMP [45].

Our interpretation of this unexpected finding relates to the Threat-Distraction model [46], where experimentally manipulating anxiety leads to engagement in CMP – unless participants are engaging in another cognitive task that ‘distracts’ attention. In CFL, we assume that there are cognitive demands associated with extracting [39] and processing visual information and maintaining a visual spatial map of the environment [47]. These processes may serve to detract from CMP, thus providing a rationale for the progressive reduction in CMP in people with more severe vision loss. This cognitive demand may be due to the added difficulty of distinguishing [48] and locating [49] features in the environment, diverting attention to external factors instead of the individuals’ own body movements. The association found between functional balance and cognitive processing while walking in this population may thus be related to extracting and exploiting visual environmental features while moving rather than the control of motion itself [44]. This interpretation finds support from previous work reporting that individuals with CFL were particularly affected by standing dual tasks compared to controls and those with peripheral field loss [50].

The next question relates to the implications for balance control. CMP is generally considered to promote stability through the avoidance of gross errors, albeit at the cost of cognitive and motor efficiency [24]. It is therefore important to determine whether reductions in CMP in people with more pronounced CFL are associated with greater postural instability. In the Threat-Distraction model, older adults with poorer balance ability showed reduced benefits from the simple distraction task and corresponding reductions in CMP [51]. Similarly, we would expect gait stability to be compromised if the cognitive demands of CFL detract from the capacity to engage in CMP.

In the next study we first examine whether the relationship between CMP and CFL severity persists (albeit in a smaller sample). Subsequently, we explore whether these individuals with reduced CMP and severe CFL show more or less stable gait.

3. Associations between gait-specific attention and walking characteristics in people with central field loss

3.1.1. Participants

We tested 10 participants with CFL (age: 71.5 ± 8.1, 4F) and 10 age-matched controls (73.2 ± 8.1 7F) who had normal or corrected to normal vision for their age cohort. For all participants we measured ‘better eye’ visual acuity and binocular contrast sensitivity (Table S2, Supplementary Materials). Contrast sensitivity of one CFL participant could not be measured due to poor visual acuity. All participants reported having no (other than CFL) diagnosed neurological or musculoskeletal conditions that significantly affected their walking.

3.1.2. Assessments and Analysis

All participants were tested by an experimenter (CPA) in a laboratory setting. All control participants and six of the participants with CFL were tested in the Eye-Head Movement laboratory at the Smith-Kettlewell Eye Research Institute (San Francisco, CA, USA). Four additional participants with CFL were tested by CPA off-site at the Envision Research Institute (Wichita, KS, USA). Participants were instrumented with three wireless, Bluetooth-enabled, 9-Axis Inertial Measurement Units (IMUs, LPMS-B2, LP Research, Tokyo, Japan) placed just above the right ankle, between the sternum and clavicle on the chest (or near the T8 vertebra for 3 participants), and on the forehead, and asked to perform the instrumented TUG (iTUG) three times. Angular velocities and linear accelerations were recorded over all three axes using a sampling frequency of 50 Hz and filtered using a Kalman filter (for detailed methods, see [17]).

A custom algorithm was used to detect gait cycles (strides) and TUG events (e.g., rising from the chair, turning) [17]. Only the strides corresponding to steady state gait (avoiding initiation and termination) and first turn of each TUG were used. Head and trunk horizontal linear acceleration (median magnitude of the XY components of the acceleration signal) and acceleration variability (mean absolute deviation) during these portions of the TUG were measured and assessed separately. We chose these metrics due to the known contribution of vision to head stabilization [52,53] and potential head stabilization deficit in CFL [54], as well as the importance of segmental coordination in aging related to fall risk [32]. Normality was tested using the Shapiro-Wilk test. Alpha level was set at 0.05.

3.2. Results

Participants with CFL took significantly longer to complete the iTUG task (t=−2.27, p=0.036, Figure 3A). As reported in Study 1, we did not observe a significant relationship between the iTUG scores and contrast sensitivity in the CFL participants (r = 0.09, p=0.82). We compared acceleration metrics of the trunk and head between the CFL and control groups (generalized linear model with Šidák correction for multiple comparisons) during the straight walking and turning portion of the iTUG. While there were no differences between groups in the median acceleration of the head or trunk, we did observe a significant group difference in acceleration variability of the trunk during straight walking (p=0.02, Figure 3B).

Figure 3.

Figure 3.

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A. Total iTUG duration for each age group, participants with CFL took significantly longer to complete the task. B. There is a significant difference in linear trunk acceleration variability in the horizontal plane between the control and CFL groups during straight walking. C. Relationship between conscious movement processing (CMP) subscale of the GSAP and contrast sensitivity in participants with CFL.

In both groups, we examined the relationship between head and trunk acceleration/acceleration variability. Head and trunk movement was always correlated in the control group (straight walk – median acceleration: r=0.66, p=0.038, acceleration variability: r=0.88, p=0.0006; turn - median acceleration: r=0.85, p=0.002, acceleration variability: ρ = 0.87, p = 0.0012). In CFL, we only found a signiticant correlation between head and trunk acceleration during straight walking (r=0.68, p=0.03). See Supplementary Materials, Figure S1 for more information.

We also evaluated the relationship between acceleration and its variability for each segment in both groups. There were significant correlations in the control group for both segments and in both walking tasks (straight – head: r=0.88, p=0.0006, trunk: r=0.86, p=0.0013 ; turns– head: r=0.86, p=0.0016, trunk: ρ =0.89, p=0.0005), while this was only observed for the head in the CFL group (straight: r=0.71, p=0.02 ; turns: r=0.86, p=0.001). See Supplementary Materials, Figure S2 for more information.

We also examined the relationship between the GSAP subscales and contrast sensitivity in this smaller CFL sample. Similar to Study 1, we found a positive relationship between contrast sensitivity and conscious movement processing scores (ρ = 0.73, p = 0.027, Figure 3C), but not with any other subscale.

We next examined head and trunk acceleration and acceleration variability as a function of contrast sensitivity among CFL participants. We found a significant negative correlation with head acceleration during both straight walk and turn segments of the iTUG (Pearson correlation, straight: r = −0.73, p = 0.026, Figure 4A; turn: r = −0.68, p = 0.042, Figure 4D), as well as with head acceleration variability and trunk acceleration during straight walking only (Figure 4C and B respectively, head: r = −0.83, p = 0.005; trunk: r = −0.73, p = 0.026).

Figure 4.

Figure 4.

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Head and trunk linear acceleration metrics in the horizontal plane during the TUG plotted against log(contrast sensitivity) within the CFL group. Relationship between contrast sensitivity and head (A) and trunk (B) acceleration and head acceleration variability (C) during straight walking and Head acceleration while turning (D).

We then examined the relationship between GSAPANX, GSAPCMP, and GSAPRUMS with iTUG duration and head and trunk acceleration metrics for both groups. iTUG duration was positively correlated to GSAPRUMS only in controls (r=0.65, p=0.043) and no significant relationships were found in the CFL group. We did find, however, significant negative correlations between GSAPRUMS during straight walking and head acceleration variability (ρ = −0.73, p = 0.017, Figure 5A) and with trunk acceleration (ρ = −0.64, p = 0.046, Figure 5B) in CFL. We also observed a negative correlation between head acceleration variability and GSAPCMP during turns (ρ = −0.70, p = 0.025, Figure 5C). No associations with the head and trunk acceleration metrics were found in controls during straight walking or turns.

Figure 5.

Figure 5.

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A, B. Relationship between head acceleration variability and trunk median acceleration, respectively and the rumination subscale of the GSAP during straight walking in those with CFL. C. CMP scores are negatively correlated to head acceleration variability while turning in those with CFL. Regression lines added for illustrative purposes.

3.3. Discussion

Results are consistent with those in Study 1, as they both suggest that those with severe CFL exhibit less conscious control of their movements. While we did not observe the same relationships with iTUG duration in this smaller sample (except regarding ruminations in the control group), our findings on the head and trunk acceleration metrics suggest an association between increased walking-related attentional processes and more controlled head and trunk motion. These findings indicate that walking-related attentional processes in CFL are likely protective, rather than harmful (see also [24]). Taken together with the observation of greater head-trunk coupling in the control as compared to the CFL group, we suggest that aging with CFL does not clearly exacerbate typical age-related changes in locomotor control.

As expected, worse contrast sensitivity was associated with greater and more variable head-in-space and trunk accelerations in CFL. Given that head and trunk stabilization is important for maintaining a clear image on the retina [55], it is possible that visual deficits lead to greater tolerance for head movement while walking. While our observations suggest that greater visual impairment is associated with poorer locomotor control, it is important to note that during turning, those with CFL had lower trunk acceleration variability than controls, which may be an adaptive strategy to maintain postural control. Given the associations between CMP and ruminations with improved head and trunk control (Figure 5), we speculate that the relationship between CMP and head acceleration variability during turns infers an adaptive strategy to limit engagement in CMP to the most challenging aspects of iTUG.

Taken together our results suggest that individuals with CFL with better visual function pay greater attention to their movements and tend to have better controlled (less variable, lower acceleration) head and body movements. This approach may not be viable with greater visual deficit, possibly due to greater attentional demand on visual processing and greater visual dependence [56].

4. Future Directions

While the studies reported here provide initial insight into CFL-related changes in attentional and cognitive processing during gait, future work should evaluate these relationships in a larger cohort using additional visual deficit metrics, such as fixation stability and eccentricity, size of visual field defect, and stereoacuity. While these additional metrics are not as readily available in the clinic, they may vary in their respective influence on cognition, motor performance and fall risk. Increases in anxiety and conscious movement processing are also associated with changes in eye movement patterns during locomotion [57]. While non-trivial, an important future direction would be to examine the changes that might occur in those with CFL in the context of known oculomotor deficits in this population [49].

5. Conclusion

Participants with CFL likely utilise CMP to avoid major destabilising errors but may lose this ability when visual deficits become too severe [15]. CMP is likely to be predominantly beneficial in CFL, though current evidence suggests that these adaptations can manifest in inefficient cognitive and motor behaviours and associated conservative movement patterns in healthy aging [24] . While overly cautious movement patterns may often appear disproportionate and inefficient, it is important to consider the potentially protective role of CMP.

Supplementary Material

1

Highlights.

  • Individuals with worse contrast sensitivity due to severe central visual field loss exhibit less conscious movement control

  • Worse contrast sensitivity is associated with greater and more variable head-in space and trunk accelerations

  • Increased walking-related attention improves body stability during walking in central visual field loss

  • Gait-specific attentional processes could be a potentially protective adaptation in central visual field loss

Acknowledgements:

We thank Dr. Don Fletcher for help with patient recruitment and welcoming us to his practice for data collection. We thank Anca Velisar for her expert assistance with the processing and analysis of kinematic data. This work was supported by National Institutes of Health grant R00 EY026994 to NMS, National Institute on Disability, Independent Living, and Rehabilitation Research grant 90REGE0018, and the Smith-Kettlewell Eye Research Institute.

Footnotes

Declaration of Competing Interest

The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Natela M. Shanidze reports financial support was provided by National Institutes of Health. Natela M. Shanidze reports a relationship with Science Corporation that includes: consulting or advisory. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

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