BURA Community:

A highly sensitive famous face recognition paradigm for prosopagnosia screening

2026-05-21T02:01:14Z

Title: A highly sensitive famous face recognition paradigm for prosopagnosia screening Authors: Bate, S; Portch, E; Dark, O; Bennetts, R Abstract: Famous face recognition tasks have traditionally been used to diagnose prosopagnosia, offering striking examples of the inability to recognise highly familiar faces. Yet, their popularity has dwindled with the development of standardised unfamiliar face recognition tasks that are less cumbersome to administer and can readily be implemented online. Here, we argue that there is a danger of omitting measures of familiar face recognition from prosopagnosia screening: not only may this challenge the very definition of the condition, but, with some adjustments, famous face recognition tasks can continue to offer highly sensitive measures of everyday face recognition ability. Thus, we developed and evaluated an online, automated famous face recognition paradigm that can readily be implemented into large-scale screening programmes. This task improves on previous designs by (a) eliminating extrinsic cues to identity by including distractor as well as familiar faces, (b) supporting the use of unseen rather than “iconic” images of celebrities, and (c) offering a method for automated scoring. Multiple versions of the task were found to have high sensitivity in the detection of developmental prosopagnosia. When required, sub-scores collected from the same paradigm can be used to assess performance at different stages of recognition and identification, helping to probe more precise loci of impairment. The latter is important to guide the diagnosis of more complex cases and, potentially, their remediation. Description: Open practices statement: The data for the experiment are available at https://osf.io/wa56h . None of the experiments were preregistered.

Lifetime Exposure to Endogenous Estradiol and Markers of Dementia Risk: Associations with Later Life Cognitive, Behavioral, and Functional Complaints

2026-05-20T02:01:11Z

Title: Lifetime Exposure to Endogenous Estradiol and Markers of Dementia Risk: Associations with Later Life Cognitive, Behavioral, and Functional Complaints Authors: Crockford, JFE; Guan, DX; Ghahremani, M; Ballard, C; Creese, B; Corbett, A; Pickering, E; Bloomfield, A; Roach, P; Barha, CK; Smith, EE; Ismail, Z Abstract: Background/Objectives: Longer lifetime exposure to endogenous estradiol (LEE2) has been associated with lower risk of age-related cognitive decline and dementia. Complementary to cognitive decline, behavioral and functional decline are also predictive of dementia risk; however, the association between LEE2 and these domains is underexplored. We investigated whether LEE2 is correlated with later-life changes in behavior and function. Methods: Baseline data from 1156 females enrolled in the CAN-PROTECT study were analyzed. LEE2 was estimated based on the length of the reproductive period (menopause age–menarche age) plus years pregnant and scaled in 5-year increments. Objective cognition was measured using the CAN-PROTECT neuropsychological battery, while subjective cognition, behavior, and function were measured using the Revised Everyday Cognition (ECog-II) scale, Mild Behavioral Impairment Checklist (MBI-C), and Standard Assessment of Global Everyday Activities (SAGEA) scale, respectively. Linear regressions modeled the association between LEE2 and neuropsychological performance. Three separate negative binomial regression models examined the association between LEE2 and ECog-II, MBI-C, and SAGEA total scores. All models adjusted for menopause hormone therapy, menopause type, age at first childbirth, body mass index, age, education, and ethnocultural background. Results: Each five-year increase in LEE2 was associated with a lower MBI-C score (count ratio [CR] = 0.89, 95% CI [0.82, 0.97]) and lower SAGEA score (CR = 0.91, 95% CI [0.84, 0.98]). LEE2 was not significantly associated with any objective or subjective cognitive measures. Conclusions: Longer LEE2 may associate with lower severity of later-life behavioral and functional symptoms in older women. Description: Data Availability Statement: The data presented in this study are available on request from the corresponding author due to ethical and legal reasons.

Consistency and changes in eye movements during static, dynamic, and audio-visual emotion processing

2026-05-19T02:01:15Z

Title: Consistency and changes in eye movements during static, dynamic, and audio-visual emotion processing Authors: Cooper, H; Jennings, BJ; Kumari, V; Luft, CDB; Bennetts, RJ Abstract: Tracking eye movements as individuals view emotional facial expressions can offer insight into the mechanisms underlying emotion recognition. Few studies compare eye gaze patterns across static and dynamic expressions, and even fewer use ecologically valid audio-visual stimuli. Research is also limited on individual differences in emotion processing and how these relate to recognition performance. In this study, we address this gap by examining the eye movement patterns of adult participants ( n = 73) during emotion recognition of individuals in static photos, dynamic videos, and audio-visual videos. Using pre-defined region-of-interest analyses and Hidden Markov Models, we explored whether individuals focused on different areas of the face across conditions, whether individual eye movement patterns were consistent across conditions, and whether certain patterns were associated with better performance. The findings showed that a) individuals focused more on the eye region when recognising static expressions compared to moving expressions; b) individuals’ eye movement patterns during emotion recognition were highly consistent, albeit most likely to change between static and moving conditions; c) there was not one particular pattern associated with improved emotion recognition accuracy. Ultimately, we report that the emotion recognition of static emotional expressions differs from moving expressions, suggesting recognition is influenced by movement, highlighting important considerations for future research to include more realistic stimuli to be better able to generalise to real-world social interactions. Description: Data availability statement: The data files and stimuli created for the experiment are available on Open Science Framework: (https://osf.io/vyg7p/).; Supplementary Material is available online at: https://journals.sagepub.com/doi/suppl/10.1177/03010066261439924/suppl_file/sj-docx-1-pec-10.1177_03010066261439924.docx (111.33 KB).

GenAI-Enabled AI Teachers and Student Learning Engagement Across International Higher Education Contexts

2026-05-15T02:01:26Z

Title: GenAI-Enabled AI Teachers and Student Learning Engagement Across International Higher Education Contexts Authors: Berglund, A; Otermans, PCJ; Aditya, D Abstract: Generative Artificial Intelligence (GenAI) is reshaping how students engage with learning both within and beyond traditional classroom settings. In a time when the development of transferable skills is essential for enabling students to thrive in varied and rapidly evolving environments, the potential of GenAI to enhance learning engagement remains insufficiently understood. Despite rising interest in interactive, personalised learning companions that enable deep engagement and ongoing skills development, scholarly research remains limited. This gap constrains effective institutional use of GenAI, reinforces black-box thinking, and restricts understanding of meaningful student engagement and skills acquisition. This paper investigates how a GenAI-enabled AI teacher supports student learning engagement, focusing on behavioral engagement as evidenced by learner interaction and participation patterns across diverse international higher education institutions. Using a combination of quantitative engagement metrics and qualitative learner reflections, the study examines how GenAI supports personalised learning, sustained interaction, autonomy, and cognitive engagement among students with varying educational backgrounds. The findings demonstrate that GenAI-based teaching systems can promote meaningful learning engagement, enhance motivation, and strengthen the development of transferable and employability skills. The study contributes empirical evidence to current debates on GenAI integration, teacher practices, and student engagement, offering implications for curriculum design and institutional adoption of GenAI-enabled learning tools. Description: Data Availability Statement: The data presented in this study are available on request from the corresponding author.