Through my research, I seek to understand how the mind processes incoming physical information from the world, and how that processing affects behaviour.
My focus is to understand how low-level and mid-level features (e.g., orientation statistics, symmetry, etc.) form high-level representations of real-world objects and scenes. My research also explores how these representations influence several aspects of cognition - i.e., visual attention, memory formation, and emotional appraisals.
I outline my broad topics of interest below, highlighting particular studies that have addressed specific questions within each topic. Read on to learn more about each project.
What are the visual features of real-world scenes that make us prefer one scene over another?
How do visual features influence basic emotional appraisals (e.g., threat or valence judgements)?
Horizon 2020: I have been granted an MSCA Individual Fellowship to study the impact of nature on cognitive and emotional well-being. We are investigating this broad topic using a combination of techniques, including VR with integrated eye tracking, portable EEG, and deep learning. Part of this work was presented at ECVP 2022 and VSS 2023.
Damiano, C., Wilder, J., Zhou, E.Y., Walther, D.B., and Wagemans, J. (2021) -- We investigated the roles of both local and global symmetry in subjective complexity, pleasure, and interest judgements of natural scenes, using a canonical correlation analysis. The analysis revealed two significant canonical roots. In the first root, we found that the presence of local symmetry and vertical global symmetry reduces complexity and renders scenes boring and unpleasant. Conversely, in the second root, local symmetry and horizontal symmetry were positively related to pleasure and interest. This work was presented at last year's V-VSS and is published in Psychology of Aesthetics, Creativity, and the Arts (see paper). Stimuli and data are available here.
We are conducting a study to understand how spatial frequency filtering choices affect results of rapid threat detection studies. We find that when contrast is normalized across low- and high-spatial freqeuncy filtered images, there is no longer an advantage of low spatial frequencies for rapid threat detection. This work was presented at VSS 2022. Stay tuned for the full paper coming soon!
Damiano, Walther, & Cunningham (2021) -- Low-level visual features extracted rapidly from the environment may help people detect threats. In a series of experiments, we explored this link between emotional judgments and features of visual scenes. We generally find that low curvature, long, horizontal contours are rated as positive and safe, while short, high curvature contours are rated as negative and threatening. This work shows that combinations of low-level scene features help people make judgments about potential threat in the environment. This work has been published in Scientific Reports (see paper). Stimuli and data are available here.
Can people infer emotions from abstract artworks? Do artworks convey information about the artists?
How are aspects of the visual world integrated into meaningful units? And how do they guide attention?
Following art historical critiques of women artists in the 60s, we are currently studying whether an artist's gender is conveyed through their artworks, or whether there is simply a gender bias carried by the viewers.
Damiano, et al. (2023) -- Here we explored how colours and lines are used to express basic emotions (i.e., anger, disgust, fear, joy, sadness, and wonder) in abstract artworks. Computational analyses of the drawings revealed systematic use of certain colours and line features to depict each basic emotion (e.g., anger is generally redder and more densely drawn than other emotions, sadness is more blue and contains more vertical lines, etc.). People use these features to understand emotions in art. Click here to read the full paper, which is part of Journal of Vision's special issue on Art and Perception!
We are currently exploring the extent to which scene meaning comes from semantic vs. non-semantic features of real-world scenes, and how these distinct aspects of "meaning" guide overt visual attention.
Damiano, Wilder, & Walther (2019) -- Here we studied the extent to which image features at different representational levels (low-, mid-, and high-level) contribute toward guiding gaze in a category-specific manner. Importantly, we found that the mid-level features that describe scene structure (i.e., local symmetry and junctions) split their contributions between bottom-up and top-down attentional guidance, with symmetry contributing to both bottom-up and top-down guidance, while junctions play a more prominent role in the top-down guidance of gaze. Click here to read the full paper!
What factors (e.g., visual features, memorability, overt attention) influence visual memory? And how?
How is the brain organized? How does this organization influence the processing of visual information?
Damiano & Walther (2019) -- A long line of research has shown that vision and memory are closely linked, such that particular eye movement behaviour aids memory performance. Here we asked whether the positive influence of eye movements on memory is primarily a result of overt visual exploration during the encoding or the recognition phases. We found a dissociation of the role of eye movements during the encoding and recognition of scenes. Eye movements during study are instrumental in forming memories, and eye movements during recognition support the judgment of memory veracity. Click here to read the full paper!
We use open source fMRI data from the BOLD5000 dataset to explore how subjective judgements of complexity, symmetry, and aesthetic pleasure relate to people's brain activity when viewing photographs of scenes. This work is currently under review at the journal Psychology of Aesthetics, Creativity, and the Arts.
We are investigating the population receptive field properties of several high-level visual areas in order to understand how the brain's organization allows for object and scene perception (through the processing of specific visual information, such as high vs. low spatial frequencies).