Development of Chinese food picture library for inducing food cravings.

Cue-induced food cravings are strong desires directed toward specific foods, usually ones with high caloric content, and can lead to overeating. However, although food cravings vary according to individual preferences for specific high-calorie food subtypes, a structured library of food craving-inducing pictures including multiple categories of high-calorie foods does not yet exist. Here, we developed and validated a picture library of Chinese foods (PLCF) consisting of five subtypes of high-calorie foods (i.e., sweets, starches, salty foods, fatty foods, and sugary drinks) to allow for more nuanced future investigations in food craving research, particularly in Chinese cultural contexts. We collected 100 food images representing these five subtypes, with four food items per subtype depicted in five high-resolution photographs each. We recruited 241 individuals with overweight or obesity to rate the food pictures based on craving, familiarity, valence, and arousal dimensions. Of these participants, 213 reported the severity of problematic eating behaviors as a clinical characteristic. Under the condition of mixing multiple subtypes of high-calorie foods, we did not observe significant differences in craving ratings for high- and low-calorie food images (p tukey > 0.05). Then, we compared each subtype of high-calorie food images to low-calorie ones, and found craving ratings were greater for the images of salty foods and sugary drinks (ps < 0.05). Furthermore, we conducted a subgroup analysis of individuals according to whether they did or did not meet the criteria for food addiction (FA) and found that greater cravings induced by the images of high-calorie food subtypes (i.e., salty foods and sugary drinks) only appeared in the subgroup that met the FA criteria. The results show that the PLCF is practical for investigating food cravings.

How Impulsiveness Influences Obesity: The Mediating Effect of Resting-State Brain Activity in the dlPFC.

Impulsiveness is a stable personal characteristic that contributes to obesity and may interact with it. Specifically, obesity is caused by unrestrained impulse eating that is not consciously controlled and leads to a hormonal imbalance that also can impair impulse control. However, the mechanism of this relationship is unclear. In our study, 35 obese individuals (body mass index, BMI > 28) were recruited and matched with 31 healthy controls (BMI < 24) in age and education level. All the participants underwent a resting-state fMRI and completed the Barratt Impulsiveness Scale-11. The results showed that patients with obesity had a significantly lower fractional amplitude of low-frequency fluctuations (fALFF) in the bilateral dorsolateral prefrontal cortex (dlPFC) and higher fALFF in the left fusiform cortex. In addition, non-planning impulsiveness was positively correlated with BMI. Importantly, we found that the right dlPFC completely mediated the relationship between non-planning impulsiveness and BMI. Our findings suggest that impulsivity is statistically more likely to precede obesity than to precede impulsivity and contributes to obesity by downregulating spontaneous activity in the dlPFC. This suggests that the dlPFC, which is associated with executive control, may be able a potential target for treating obesity.

Efficacy of MP-3 microperimeter biofeedback fixation training for low vision rehabilitation in patients with maculopathy.

BACKGROUND: To evaluate the efficacy of MP-3 microperimeter biofeedback fixation training (MBFT) in vision rehabilitation of low-vision patients affected by macular disease with central vision loss. METHODS: Seventeen eyes (7 age-related macular degeneration, 10 myopic maculopathy) of 17 patients were included in this prospective, interventional study. The preferred retinal locus was determined by comprehensive ophthalmoscopic fundus evaluation including fundus photography, autofluorescence, optical coherence tomography, and microperimetry. The rehabilitation consisted of three 10-min sessions per eye to be performed twice per week for 20 consecutive weeks using the MP-3 microperimeter. Best corrected visual acuity (BCVA), reading speed, mean central sensitivity, the percentages of fixation points within specified regions, bivariate contour ellipse area (BCEA) and the 25-item National Eye Institute visual function questionnaire (NEI-VFQ-25) were recorded pre- and post-training. RESULTS: The final BCVA, reading speed and mean central sensitivity all showed significant improvements after rehabilitation (P <  0.0001, P = 0.0013, and P = 0.0002, respectively). The percentages of fixation points located within 2° and 4° diameter circles both significantly increased after training (P = 0.0008 and P = 0.0007, respectively). The BCEA encompassing 68.2, 95.4, 99.6% of fixation points were all significantly decreased after training (P = 0.0038, P = 0.0022, and P = 0.0021, respectively). The NEI-VFQ-25 scores were significantly increased at the end of the rehabilitation training (P <  0.0001). CONCLUSION: Rehabilitation with MP-3 MBFT is a user-friendly therapeutic option for improving visual function, fixation stability, and quality of life in advanced macular disease. TRIAL REGISTRATION: The prospective study was registered with the Chinese Clinical Trial Registry ( http://www.chictr.org.cn/ ). TRIAL REGISTRATION NUMBER: ChiCTR2000029586 . Date of registration: 05/02/2020.

Pictures Library of Smoking Cravings: Development and Verification of Smokers and Non-smokers.

Background: The cue-induced craving by addiction related materials is commonly employed in addiction research; however, no existing standardized picture database based on the expectation model of craving has been developed. We prepared and validated a Pictures Library of Smoking Cravings (PLSC) in this study. Methods: We captured pictures 366 smoking and 406 control pictures (matched in content). We selected 109 smoking pictures and 115 control pictures and asked participants to provide ratings of craving, familiarity, valence, and arousal induced in them. Participants were divided into three groups: non-smokers (n = 211), light smokers (n = 504), and heavy smokers (n = 101). Results: The results showed that smoking pictures evoked a greater craving, familiarity, and arousal than control pictures in smokers (ps < 0.01). In addition, craving caused by smoking pictures was positively associated with the Fagerström test for nicotine dependence score in dependent smokers. Conclusions: Overall, the contemporary results showed that PLSC is effective and can be used in smoking-related studies.

The Corticospinal Excitability Can Be Predicted by Spontaneous Electroencephalography Oscillations.

Transcranial magnetic stimulation (TMS) has a wide range of clinical applications, and there is growing interest in neural oscillations and corticospinal excitability determined by TMS. Previous studies have shown that corticospinal excitability is influenced by fluctuations of brain oscillations in the sensorimotor region, but it is unclear whether brain network activity modulates corticospinal excitability. Here, we addressed this question by recording electroencephalography (EEG) and TMS measurements in 32 healthy individuals. The resting motor threshold (RMT) and active motor threshold (AMT) were determined as markers of corticospinal excitability. The least absolute shrinkage and selection operator (LASSO) was used to identify significant EEG metrics and then correlation analysis was performed. The analysis revealed that alpha2 power in the sensorimotor region was inversely correlated with RMT and AMT. Innovatively, graph theory was used to construct a brain network, and the relationship between the brain network and corticospinal excitability was explored. It was found that the global efficiency in the theta band was positively correlated with RMT. Additionally, the global efficiency in the alpha2 band was negatively correlated with RMT and AMT. These findings indicated that corticospinal excitability can be modulated by the power spectrum in sensorimotor regions and the global efficiency of functional networks. EEG network analysis can provide a useful supplement for studying the association between EEG oscillations and corticospinal excitability.

Short intracortical facilitation associates with motor-inhibitory control.

The ability of motor-inhibitory control is important in daily life. Inhibitory control deficits are commonly observed in psychiatric conditions with enhanced impulsivity. The physiological mechanisms underlying the inhibitory control deficits are not well elucidated. We systematically investigated the relationship between resting-state intracortical inhibition or facilitation and inhibitory control (indicated by stop signal reaction time, SSRT) to determine whether reduced intracortical inhibition or increased intracortical facilitation was related to the poorer inhibitory control. Thirty-three healthy subjects (age: 21.46 ± 1.40 years) participated in this study. We used paired-pulse transcranial magnetic stimulation to induce short intracortical inhibition, intracortical facilitation, long intracortical inhibition, and short intracortical facilitation at rest. SSRT was derived from stop signal task. We performed all measurements in two repeat sessions conducted two weeks apart. A negative correlation between short intracortical inhibition and SSRT was only observed in session 1; however, the correlation did not persist after controlling for short intracortical facilitation. Positive correlation between short intracortical facilitation and SSRT was observed in both sessions, indicating that individuals with greater resting-state short intracortical facilitation tend to have less efficient stopping performance. Our results help explain the inconsistency with respect to the relationship between short intracortical inhibition and SSRT in the existing literature. Short intracortical facilitation may be used as a potential physiological biomarker for motor-inhibitory control, which may have clinical implications for disorders associated with inhibitory control deficits.