Find the difference! : eye tracking study on information seeking behavior using an online game

With the advent of digital era web applications have become inevitable part of our lives. We are using the web to manage even the financially or ethically sensitive issues. For this reason exploration of information seeking behavior is an exciting area of research. Current study provides insight on information seeking behavior using a classic ‘Find the Difference’ game. 50 university students between the age of 19 and 26 participated in the study. Eye movement data were recorded with a Tobii T120 device. Participants carried out 4 continuous tasks. Each task included two pictures side by side with 7 hidden differences. After finishing the tasks, participants were asked to repeat the game with the same picture set. This data collection methodology allows the evaluation of learning curves. Additionally, participants were asked about their hand preference. For the purpose of analysis the following metrics were applied: task times (including saccades), fixation count and fixation duration (without saccades). The right- and left-hand side on each picture was selected as AOI (Area of Interest) to detect side preference in connection with hand preference. Results suggest a significant difference between male and female participants regarding aggregated task times (male 58.37s respectively female 68.37s), deviation in the number of fixations and fixation duration (apparently female have less but longer fixations) and also in the distribution of fixations between AOIs. Using eyetracking data current paper highlights the similarities and differences in information acquisition strategies respectively reveals gender and education (Arts vs. Sciences) dependent characteristics of interaction.

Social perception gaze patterns, symptom severity and resting brain function measured using Arterial Spin Labelling

Autistic spectrum disorder (ASD) is characterised by qualitative alterations in reciprocal social interactions. Some recent studies show alterations in gaze patterns during social perception and rest-functional abnormalities in the ‘social brain network’. This study investigated: i) social perception gaze patterns in children with ASD and controls, ii) the relationship between autism clinical severity and social perception gaze patterns, iii) the relationship between resting cerebral blood flow (rCBF) and social perception gaze patterns. Methods: Nine children with ASD and 9 children with typical development were studied. Eye-tracking was used to detect gaze patterns during presentation of stimuli depicting social scenes. Autism clinical severity was established using the Autism Diagnostic Interview Revised (ADI-R). Arterial spin labelling MRI was used to quantify rCBF. Results: The ASD group looked less at social regions and more at non-social regions than controls. No significant correlation was found between ASD clinical severity and social perception gaze patterns. In the ASD group, gaze behaviour was related to rCBF in the temporal lobe regions at trend level. Positive correlations were found between temporal rCBF and gaze to the face region, while negative correlations were found between temporal rCBF and gaze to non-social regions. Conclusions: These preliminary results suggest that social perception gaze patterns are altered in children with ASD, and could be related to temporal rCBF.