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Attention bias to threat is considered an adaptive cognitive phenomenon that is associated with developmental and psychopathological outcomes across the lifespan. However, investigations into the development of attention bias to threat in infancy have produced mixed results. Steady-state visual evoked potentials provide a robust measure of visual cortex processing and attention by capturing brain entrainment to the rhythmic flicker of visual stimuli. This investigation leveraged a novel steady-state visual evoked potential task to examine attention bias to threat via affective expressions and its changes with age within the first 2 years of life. Infants ( = 118, = 9.21 months; range = 3-22 months; 57.61% female) viewed a series of affective face pairs (neutral with happy, fearful, or angry) in which one face flickered at 6 Hz and the other at 7.5 Hz, while their brain activity was measured with electroencephalography. Infants' frequency-tagged brain responses were larger to fearful faces, above all other expressions, consistent with the presence of an attention bias to threat in infancy. Affect-biased attention did not change with age. Furthermore, the presence of an attention bias toward fear was found prior to the literature-suggested age of 7 months. This study demonstrated the utility of using a robust and novel measure of attention, steady-state visual evoked potentials, to examine attention bias to threat and its development during infancy. (PsycInfo Database Record (c) 2025 APA, all rights reserved).
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http://dx.doi.org/10.1037/dev0002066 | DOI Listing |
Am Psychol
September 2025
State Key Laboratory of Cognitive Science and Mental Health, Institute of Psychology, Chinese Academy of Sciences.
In cluttered and complex natural scenes, selective attention enables the visual system to prioritize relevant information. This process is guided not only by perceptual cues but also by imagined ones. The current research extends the imagery-induced attentional bias to the unconscious level and reveals its cross-category applicability between different social cues (e.
View Article and Find Full Text PDFFront Pharmacol
August 2025
Luzhou Key Laboratory of Traditional Chinese Medicine for Chronic Diseases Jointly Built by Sichuan and Chongqing, The Affiliated Traditional Chinese Medicine Hospital, Southwest Medical University, Luzhou, Sichuan, China.
Introduction: Depression and anxiety are prevalent comorbidities in individuals with chronic diseases, significantly impairing their quality of life and complicating disease management. Curcumin, derived from turmeric (Curcuma longa), has garnered attention for its potential therapeutic benefits in alleviating symptoms of depression and anxiety. However, its specific effects on depressive or anxiety symptoms associated with chronic diseases (DACD) remain unclear.
View Article and Find Full Text PDFFront Psychol
August 2025
China West Normal University, Nanchong, China.
Introduction: Time compression of instructional videos has received attention from scholars around the world. From existing empirical studies, a wide range of scholars have not yet reached a consensus on whether acceleration promotes video learning.
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Front Psychol
August 2025
College of Physical Education, Yangzhou University, Yangzhou, Jiangsu, China.
Background: Under high-pressure situations, such as crucial games, some athletes often underperform. This is the case even for exceptional athletes in critical moments of competition. Athletes often experience performance anxiety, which creates attentional errors and underperformance.
View Article and Find Full Text PDFJ Eval Clin Pract
September 2025
Academic Unit of Population and Lifespan Sciences, School of Medicine, Nottingham City Hospital Campus, University of Nottingham, Clinical Sciences Building, Nottingham, UK.
Background: Artificial intelligence (AI) is increasingly applied across healthcare and public health, with evidence of benefits including enhanced diagnostics, predictive modelling, operational efficiency, medical education, and disease surveillance.However, potential harms - such as algorithmic bias, unsafe recommendations, misinformation, privacy risks, and sycophantic reinforcement - pose challenges to safe implementation.Far less attention has been directed to the public health threats posed by artificial general intelligence (AGI), a hypothetical form of AI with human-level or greater cognitive capacities.
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