Sign in to use this feature.

Years

Between: -

Subjects

remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline

Journals

remove_circle_outline

Article Types

Countries / Regions

Search Results (1)

Search Parameters:
Keywords = debiased weighted phase lag index (dwPLI)

Order results
Result details
Results per page
Select all
Export citation of selected articles as:
15 pages, 11010 KB  
Article
Functional Connectivity Differences in the Perception of Abstract and Figurative Paintings
by Iffah Syafiqah Suhaili, Zoltan Nagy and Zoltan Juhasz
Appl. Sci. 2024, 14(20), 9284; https://doi.org/10.3390/app14209284 - 12 Oct 2024
Cited by 2 | Viewed by 2059
Abstract
The goal of neuroaesthetic research is to understand the neural mechanisms underpinning the perception and appreciation of art. The human brain has the remarkable ability to rapidly recognize different artistic styles. Using functional connectivity, this study investigates whether there are differences in connectivity [...] Read more.
The goal of neuroaesthetic research is to understand the neural mechanisms underpinning the perception and appreciation of art. The human brain has the remarkable ability to rapidly recognize different artistic styles. Using functional connectivity, this study investigates whether there are differences in connectivity networks formed during the processing of abstract and figurative paintings. Eighty paintings (forty abstract and forty figurative) were presented in a random order for eight seconds to each of the 29 participants. High-density EEG recordings were taken, from which functional connectivity networks were extracted at several time points (−300, 100, 300 and 500 ms). The debiased weighted phase lag index (dwPLI) was used to extract the connectivity networks for the abstract and figurative conditions across multiple frequency bands. Significant connectivity differences were detected for both conditions at each time point and in each frequency band: delta (p < 0.0273), theta (p < 0.0292), alpha (p < 0.0299), beta (p < 0.0275) and gamma (p < 0.0266). The topology of the connectivity networks also varied over time and frequency, indicating the multi-scale dynamics of art style perception. The method used in this study has the ability to identify not only brain regions but their interaction (communication) patterns and their dynamics at distinct time points, in contrast to average ERP waveforms and potential distributions. Our findings suggest that the early perception stage of visual art involves complex, distributed networks that vary with the style of the artwork. The difference between the abstract and figurative connectivity network patterns indicates the difference between the underlying style-related perceptual and cognitive processes. Full article
Show Figures

Figure 1

Back to TopTop