Factors associated to the increased perceptual reliance on the visual reference frame with age

When interacting with their environment, humans select alternative Frames of Reference (FoRs) for spatial orientation, depending on the setting/task.

Greater reliance on the visual FoR is extensively reported in the elderly, termed Visual Field Dependence (VFD). Alterations of the internal model with age [1] and the decline of proprioceptive and vestibular systems for postural control [2] inevitably upweight visual input.

The proprioceptive chain from eye to foot [3] is important for egocentric perception. Oculomotor control is affected by age [4] which may alter both extra-retinal and peripheral visual cues used for spatial orientation. Eye Fixation Instability (EFI) with age could impact peripheral visual information (PVI) processing.

It is well known that the Useful Field Of View (UFOV), a visual attention measure important for PVI processing, shrinks with age. With this respect, it has been suggested that the elderly may develop compensatory oculomotor strategies [5].

We wish to better understand increased VFD with respect to Egocentric Dependence (ED) and associated factors, i.e. UFOV and EFS, in the context of ageing.

ParticipantsParticipants 20 young adults (YA, 10 ♂, 10♀; 31.7 ± 6.4 yo), 18 middle-aged adults, (MA, 7 ♂, 11 ♀; 51.5 ± 5.6 yo) and 20 old adults (OA, 10 ♂, 10 ♀; 74.1 ± 3.7 yo)

1) Shift towards greater reliance on the visual FoR with age

DiscussionDistinguish VFD as a preferred spatial referencing mode or as a constraint associated with other age-affected factors in OA.

Training programs would serve to reduce noise associated to non-visual (or confounding visual) cues but also to improve OA’s capacity to distinguish exploitable signal from noise in available sensory information

References[1] M. Boisgontier and V. Nougier, "Ageing of internal models: from a continuous to an intermittent proprioceptive control of movement" AGE, vol. 35, no. 4, pp. 1339-1355, 2013[2] D. Manchester, M. Woollacott, N. Zederbauer-Hylton, and O. Marin, "Visual, Vestibular and Somatosensory Contributions to Balance Control in the Older Adult" Journal of Gerontology, vol. 44, no. 4, p. M118-M127, July1989[3] J. P. Roll and R. Roll, "From eye to foot: a proprioceptive chain involved in postural control" in Posture and gait. B. Amblard, A.Berthoz, and F.Clarac, Eds. Amsterdam: Elsevier, 1988, pp. 155-164[4] G. Paige, "Senescence of human visual-vestibular interactions: smooth pursuit, optokinetic, and vestibular control of eye movements with aging" Exp Brain Res, vol. 98, no. 2, pp. 355-372, 1994[5] R. Beurskens and O. Bock, "Age-related decline of peripheral visual processing: the role of eye movements" Exp Brain Res, vol. 217, no. 1, pp. 117-124, 2012

A microperimeter (MP1© Nidek Technologies) was used. Participants fixate a central target monocularly during 30s. EFI was quantified by calculating a bivariate contour ellipse area (BCEA) encompassing 68% of fixation points.

UFOV assessmentUFOV assessment

Visual processing speed is measured by varying display duration via a double staircase method

2) Associated factors: EFI and UFOV

Individuals show greater reliance on the visual FoR with age, and this process is accompanied by a lower reliance on the egocentric FoR.

Greater AESDs with age could be associated with age-related declines in higher order processes in old adults.

The UFOV-VFD correlation supports of age-related VFD being associated to slower processing speed as well as reduced visual inhibition

OA (and to a lesser degree MA, thought still more than YA) have trouble exploiting body-based cues in the absence of visual information.

The intra-individual variability of OA in the RBT points towards age-related decline in somatosensation

Eye fixation instability adds noise to the chain of proprioceptive information.

For more VFD participants, PVI is distracting as it adds noise, but also disorienting as it adds information that is hard to ignore.

Visual attention allocation to central and peripheral visual fields constitutes a double task

UFOV reduction implies greater EFI and vice versa

a Paris-Sud University, UR CIAMS EA 4532 – Motor Control & Perception team, Orsay, France b Essilor International, R&D, Visual System, Paris, France c Aix-Marseille University, Laboratory of Cognitive Neuroscience, Marseille, France

Methods

Results

EFI assessmentEFI assessment

Perspectives

Background & Aim

GEFT score is the number of figures not found or traced. Absolute Error accuracy (AEA) and precision (AESD) of SV estimations were calculated with respect to gravity (in degrees) for the RFT, RDT & RBT.

Figure 3:

Distributions of scores on FD and ED tests for each age group. For the GEFT (a) RFT (b) and RDT (c) scores, larger values indicate greater VFD. For RBT data, larger values lower ED for the BE condition (d) and greater ED for the BT postural condition (e)

Figure 4: ANOVA for VFD and ED tests by age group*

a) Mean Adjustment Error Accuracy (AEA) of SV tests and mean GEFT scores

b) Mean intra individual variability in Adjustment Error (AESD), calculated over

the number of trials of each SV test. Confidence intervals are indicated with each mean value.

* Z scores were used due to differences in the various test scales

Figure 1: Example of exercise on the Group Embedded Figures Test (a. GEFT) volunteers must find and trace simple figures hidden within complex ones. Apparatus, postural conditions and stimuli used for the Subjective Vertical (SV) estimations tests: volunteers had to adjust a tilted rod (±18°) to vertical whilst confronted to a tilted frame on the Rod and Frame Test (b. RFT, ±18°) or a rotating disc on the Rod and Discc Test (c. RDT, ±30°/s); for the Rod and Body Test, SV was made whilst standing with the body erect (d. RBT BE) or body laterally tilted ~70°(e. RBT BT)

a.

c.b. d. e.

Catherine P Agathos ab, Delphine Bernardin b, Delphine Nauleau b, Anne-Catherine Scherlen b

Christine Assaiante c, Brice Isableu a

Figure 7: EFI correlation with UFOV 2 (R² = 0.23, p < 0.001) and UFOV 3 (R² = 0.15, p = 0.003)

Figure 6: UFOV – VFD relationship*a) GEFT correlation with UFOV 2 (R² = 0.30, p < 0.001) and UFOV 3 (R² = 0.36,  p < 0.001)b) RFT correlation with UFOV 2 (R² = 0.39, p < 0.001) and UFOV 3 (R² = 0.36,  p < 0.001)c) RFT correlation with UFOV 2 (R² = 0.20,  p < 0.001) and UFOV 3 (R² = 0.27, p < 0.001)

Figure 5: EFI – VFD/ED relationships*a) EFI correlation with RFT (R² = 0.276,  p < 0.001 ) and RDT (R² = 0.25,  p < 0.001 ) scoresb) EFI correlation with RBT BE (R² = 0.18, p < 0.001) and RBT BT (R² = 0.15,  p = 0.002 )

Figure 2: UFOV subtest displays © Visual Awareness Research Groupa) UFOV 1 - stimulus identificantionb) UFOV 2 – divided attentionc) UFOV 3 – selective attention

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