The incentive sensitization theory suggests that repeated exposure to rewarding substances or food shapes neural circuits to create an attentional bias towards these stimuli. There is ongoing debate about whether attentional capture by such stimuli is an early automatic process or a later stage in the processing cascade. Event-related brain potentials (ERPs) provide a means to pinpoint the timing and location of attentional capture. ERPs were recorded from 28 normal weight healthy women as they attended to the left or right hemifield of a visual display while fixating a central point. Stimuli comprised bars presented left and right of the fixation point simultaneously with the task being to respond to slightly smaller bars on the attended side by button press. The bars appeared superimposed on task-irrelevant distractor stimuli (either food pictures or pictures of non-food objects). The bilateral stimuli elicited a positivity that was largest as posterior sites contralateral to the attended hemifield between 75 and 250 ms. Critically, this contralateral attention effect was enhanced by food distractors on the attended side and diminished by food distractors on the unattended side, demonstrating signs of attention capture by food stimuli as early as 80 ms poststimulus.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1016/j.bbr.2025.115514 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Protein-ligand interaction prediction based on heterogeneity maps and data enhancement.
J Biomol Struct Dyn
March 2025
School of Mechatronic Engineering and automation, Shanghai University, Shanghai, China.
Prediction of protein-ligand interactions is critical for drug discovery and repositioning. Traditional prediction methods are computationally intensive and limited in modeling structural changes. In contrast, data-driven deep learning methods significantly reduce computational costs and offer a more efficient approach for drug discovery.
View Article and Find Full Text PDFInterpretation of mutations (DNM) and genetic counseling for sporadic hearing loss based on family trio-based sequencing.
Yi Chuan
March 2025
Senior Department of Otolaryngology-Head & Neck Surgery, the Sixth Medical Center of PLA General Hospital, Beijing 100048，China.
mutations (DNMs) are significant genetic factors contributing to sporadic hearing loss (HL) and complex HL syndromes. To analyze the genetic counseling characteristics and interpretation of pathogenic DNMs for sporadic HL, we retrospectively analyze the clinical information of probands and their parents from 410 sporadic HL core pedigrees enrolled in the "Chinese Deafness Genome Project (CDGP)" between October 2015 and October 2023. We apply family trio-based genome sequencing (targeted gene capture and high throughput sequencing, mitochondrial genome sequencing, and copy number variants analysis) and validate the samples of their unaffected-parents.
View Article and Find Full Text PDFEnhancing short-term algal bloom forecasting through an anti-mimicking hybrid deep learning method.
J Environ Manage
March 2025
State Key Laboratory of Marine Environmental Science / National Observation and Research Station for the Taiwan Strait Marine Ecosystem (T-SMART) / Fujian Provincial Key Laboratory for Coastal Ecology and Environmental Studies / College of the Environment and Ecology, Xiamen University, Xiamen, 361102, China.
Accurately predicting algal blooms remains a critical challenge due to their dynamic and non-stationary nature, compounded by high-frequency fluctuations and noise in monitoring data. Additionally, a common issue in time-series forecasting is data replication, where models tend to replicate historical patterns rather than capturing true future variations, leading to inaccurate forecasts during abrupt changes. To address these challenges, we developed a hybrid deep learning model (TAB) that integrates a Temporal Convolutional Network (TCN), an attention mechanism, and Bidirectional Long Short-Term Memory (BiLSTM) network.
View Article and Find Full Text PDFGreen bonds and gold: A new financial-environmental relationship.
J Environ Manage
March 2025
MBS School of Business, 2300, Avenue des Moulins, Cedex 4, 34185, Montpellier, France. Electronic address:
In the transition to a low carbon economy the green bonds play an eminent role. On the other hand, gold has attracted a lot of attention in energy economics literature. In this study, we examine the relationship of corporate green bonds with gold, an issue that has attracted very little attention in the relative literature.
View Article and Find Full Text PDFFusionformer: A Novel Adversarial Transformer Utilizing Fusion Attention for Multivariate Anomaly Detection.
IEEE Trans Neural Netw Learn Syst
March 2025
Multivariate time series forecasting (MTSF) is of significant importance in the enhancement and optimization of real-world applications. The task of MTSF poses substantial challenges due to the unpredictability of temporal patterns and the complexity in modeling the influence of all nonpredictive sequences on the target sequence at different time stages. Recent research has demonstrated the potential held by the Transformer algorithm to augment long-term forecasting capability.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!