Spontaneous Ocular Scanning of Visual Symmetry Is Similar During Classification and Evaluation Tasks

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Abstract

Visual symmetry perception and symmetry preference have been studied extensively. However, less is known about how people spontaneously scan symmetrical stimuli with their eyes. We thus examined spontaneous saccadic eye movements when participants ( N = 20) observed patterns with horizontal or vertical mirror reflection. We found that participants tend to make saccades along the axis of reflection and that this oculomotor behaviour was similar during objective classification and subjective evaluation tasks. The axis-scanning behaviour generates a dynamic sequence of novel symmetrical images from a single static stimulus. This could aid symmetry perception and evaluation by enhancing the neural response to symmetry.

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PsychoPy—Psychophysics software in Python

Jonathan W. Peirce (2007)

The vast majority of studies into visual processing are conducted using computer display technology. The current paper describes a new free suite of software tools designed to make this task easier, using the latest advances in hardware and software. PsychoPy is a platform-independent experimental control system written in the Python interpreted language using entirely free libraries. PsychoPy scripts are designed to be extremely easy to read and write, while retaining complete power for the user to customize the stimuli and environment. Tools are provided within the package to allow everything from stimulus presentation and response collection (from a wide range of devices) to simple data analysis such as psychometric function fitting. Most importantly, PsychoPy is highly extensible and the whole system can evolve via user contributions. If a user wants to add support for a particular stimulus, analysis or hardware device they can look at the code for existing examples, modify them and submit the modifications back into the package so that the whole community benefits.

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Computational modelling of visual attention.

L Itti, C Koch (2001)

Five important trends have emerged from recent work on computational models of focal visual attention that emphasize the bottom-up, image-based control of attentional deployment. First, the perceptual saliency of stimuli critically depends on the surrounding context. Second, a unique 'saliency map' that topographically encodes for stimulus conspicuity over the visual scene has proved to be an efficient and plausible bottom-up control strategy. Third, inhibition of return, the process by which the currently attended location is prevented from being attended again, is a crucial element of attentional deployment. Fourth, attention and eye movements tightly interplay, posing computational challenges with respect to the coordinate system used to control attention. And last, scene understanding and object recognition strongly constrain the selection of attended locations. Insights from these five key areas provide a framework for a computational and neurobiological understanding of visual attention.

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Facial attractiveness: evolutionary based research.

Jeffrey B. Jones, William C Little, T. J. Jones … (2011)

Face preferences affect a diverse range of critical social outcomes, from mate choices and decisions about platonic relationships to hiring decisions and decisions about social exchange. Firstly, we review the facial characteristics that influence attractiveness judgements of faces (e.g. symmetry, sexually dimorphic shape cues, averageness, skin colour/texture and cues to personality) and then review several important sources of individual differences in face preferences (e.g. hormone levels and fertility, own attractiveness and personality, visual experience, familiarity and imprinting, social learning). The research relating to these issues highlights flexible, sophisticated systems that support and promote adaptive responses to faces that appear to function to maximize the benefits of both our mate choices and more general decisions about other types of social partners.

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Author and article information

Contributors

Alexis D. J. Makin:

ORCID: https://orcid.org/0000-0002-4490-7400

Ellen Poliakoff

Journal

Journal ID (nlm-ta): Iperception

Journal ID (iso-abbrev): Iperception

Journal ID (publisher-id): IPE

Journal ID (hwp): spipe

Title: i-Perception

Publisher: SAGE Publications (Sage UK: London, England )

ISSN (Electronic): 2041-6695

Publication date (Electronic): 12 October 2020

Publication date Collection: Sep-Oct 2020

Volume: 11

Issue: 5

Electronic Location Identifier: 2041669520946356

Affiliations

[1-2041669520946356]Department of Psychological Sciences, University of Liverpool, United Kingdom

[2-2041669520946356]Division of Neuroscience and Experimental Psychology, School of Biological Sciences, Faculty of Biological, Medical and Human Sciences, Manchester Academic Health Science Centre, The University of Manchester, United Kingdom

[3-2041669520946356]Department of Psychological Sciences, University of Liverpool, United Kingdom

Author notes

[*]Alexis Makin, Department of Psychological Sciences, University of Liverpool, Eleanor Rathbone Building, Liverpool L69 7ZA, United Kingdom. Email: alexis.makin@ 123456liverpool.ac.uk

Author information

Alexis D. J. Makin https://orcid.org/0000-0002-4490-7400

Article

Publisher ID: 10.1177_2041669520946356

DOI: 10.1177/2041669520946356

PMC ID: 7557695

SO-VID: bfcb644d-11ad-4e20-846b-b399a247ee85

License:

Creative Commons CC BY: This article is distributed under the terms of the Creative Commons Attribution 4.0 License ( https://creativecommons.org/licenses/by/4.0/) which permits any use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages ( https://us.sagepub.com/en-us/nam/open-access-at-sage).

History

Date received : 14 May 2020

Date accepted : 9 July 2020

Funding

Funded by: Economic and Social Research Council, FundRef https://doi.org/10.13039/501100000269;

Award ID: ES/S014691/1

Custom metadata

cover-date September-October 2020

typesetter ts2

ScienceOpen disciplines: Neurosciences

Keywords: aesthetics,reflection,symmetry,saccades,eye movements

Data availability:

ScienceOpen disciplines: Neurosciences

Keywords: aesthetics, reflection, symmetry, saccades, eye movements

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Spontaneous Ocular Scanning of Visual Symmetry Is Similar During Classification and Evaluation Tasks

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The Dynamic Brain

Most cited references 31

PsychoPy—Psychophysics software in Python

Computational modelling of visual attention.

Facial attractiveness: evolutionary based research.

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