Noninvasive brain stimulations modulated brain modular interactions to ameliorate working memory in community-dwelling older adults.

Non-invasive brain stimulations have drawn attention in remediating memory decline in older adults. However, it remains unclear regarding the cognitive and neural mechanisms underpinning the neurostimulation effects on memory rehabilitation. We evaluated the intervention effects of 2-weeks of neurostimulations (high-definition transcranial direct current stimulation, HD-tDCS, and electroacupuncture, EA versus controls, CN) on brain activities and functional connectivity during a working memory task in normally cognitive older adults (age 60+, n = 60). Results showed that HD-tDCS and EA significantly improved the cognitive performance, potentiated the brain activities of overlapping neural substrates (i.e. hippocampus, dlPFC, and lingual gyrus) associated with explicit and implicit memory, and modulated the nodal topological properties and brain modular interactions manifesting as increased intramodular connection of the limbic-system dominated network, decreased intramodular connection of default-mode-like network, as well as stronger intermodular connection between frontal-dominated network and limbic-system-dominated network. Predictive model further identified the neuro-behavioral association between modular connections and working memory. This preliminary study provides evidence that noninvasive neurostimulations can improve older adults' working memory through potentiating the brain activity of working memory-related areas and mediating the modular interactions of related brain networks. These findings have important implication for remediating older adults' working memory and cognitive declines.

Sex-based differences in fairness norm compliance and neural circuitry.

Human behavior often aligns with fairness norms, either voluntarily or under external pressure, like sanctions. Prior research has identified distinct neural activation patterns associated with voluntary and sanction-based compliance or non-compliance with fairness norms. However, an investigation gap exists into potential neural connectivity patterns and sex-based differences. To address this, we conducted a study using a monetary allocation game and functional magnetic resonance imaging to examine how neural activity and connectivity differ between sexes across three norm compliance conditions: voluntary, sanction-based, and voluntary post-sanctions. Fifty-five adults (27 females) participated, revealing that punishment influenced decisions, leading to strategic calculations and reduced generosity in voluntary compliance post-sanctions. Moreover, there were sex-based differences in neural activation and connectivity across the different compliance conditions. Specifically, the connectivity between the right dorsolateral prefrontal cortex and right dorsal anterior insular appeared to mediate intuitive preferences, with variations across norm compliance conditions and sexes. These findings imply potential sex-based differences in intuitive motivation for diverse norm compliance conditions. Our insights contribute to a better understanding of the neural pathways involved in fairness norm compliance and clarify sex-based differences, offering implications for future investigations into psychiatric and neurological disorders characterized by atypical socialization and mentalizing.

Sex modulated the relationship between trait approach motivation and decision-making.

It has been observed that one's Behavioral Approach System (BAS) can have an effect on decision-making under uncertainty, although the results have been mixed. To discern the underlying neural substrates, we hypothesize that sex may explain the conflicting results. To test this idea, a large sample of participants was studied using resting state fMRI, utilizing fractional Amplitude of Low Frequency Fluctuations (fALFF) and Resting-State Functional Connectivity (rsFC) techniques. The results of the Iowa Gambling Task (IGT) revealed an interaction between sex and BAS, particularly in the last 60 trials (decision-making under risk). Males with high BAS showed poorer performance than those with low BAS. fALFF analysis showed a significant interaction between BAS group and sex in the left superior occipital gyrus, as well as the functional connectivity between this region and the left ventrolateral prefrontal cortex. Additionally, this functional connectivity was further positively correlated with male performance in the IGT, particularly in the decision-making under risk stage. Furthermore, it was found that the functional connectivity between left ventrolateral prefrontal cortex and left superior occipital gyrus could mediate the relationship between BAS and decision-making in males, particularly in the decision-making under risk stage. These results suggest possible sex-based differences in decision-making, providing an explanation for the inconsistent results found in prior research. Since the research was carried out exclusively with Chinese university students, it is essential to conduct further studies to investigate whether the findings can be generalized.

Choice overload interferes with early processing and necessitates late compensation: Evidence from electroencephalogram.

Having a multitude of choices can be advantageous, yet an abundance of options can be detrimental to the decision-making process. Based on existing research, the present study combined electroencephalogram and self-reported methodologies to investigate the neural mechanisms underlying the phenomenon of choice overload. Behavioural data suggested that an increase in the number of options led to negative evaluations and avoidance of choice tendencies, even in the absence of time pressure. Event-related potential results indicated that the large choice set interfered with the early visual process, as evidenced by the small P1 amplitude, and failed to attract more attentional resources in the early stage, as evidenced by the small amplitude of P2 and N2. However, the LPC amplitude was increased in the late stage, suggesting greater investment of attentional resources and higher emotional arousal. Multivariate pattern analysis revealed that the difference between small and large choice set began at around 120 ms, and the early and late stages were characterised by opposite activation patterns. This suggested that too many options interfered with early processing and necessitate continued processing at a later stage. In summary, both behavioural and event-related potential (ERP) results confirm the choice overload effect, and it was observed that individuals tend to subjectively exaggerate the choice overload effect.

Neural basis of reward expectancy inducing proactive aggression.

Proactive aggression refers to deliberate and unprovoked behavior, typically motivated by personal gain or expected reward. Reward expectancy is generally recognized as a critical factor that may influence proactive aggression, but its neural mechanisms remain unknown. We conducted a task-based functional magnetic resonance imaging (fMRI) experiment to investigate the relationship between reward expectancy and proactive aggression. 37 participants (20 females, mean age = 20.8 ± 1.42, age range = 18-23 years) completed a reward-harm task. In the experiment, reward valence expectancy and reward possibility expectancy were manipulated respectively by varying amounts (low: 0.5-1.5 yuan; high: 10.5-11.5 yuan) and possibilities (low: 10%-30%; high: 70%-90%) of money that participants could obtain by choosing to aggress. Participants received fMRI scans throughout the experiment. Brain activation regions associated with reward expectancy mainly involve the middle frontal gyrus, lingual gyrus, inferior temporal gyrus, anterior cuneus, caudate nucleus, inferior frontal gyrus, cingulate gyrus, anterior central gyrus, and posterior central gyrus. Associations between brain activation and reward expectancy in the left insula, left middle frontal gyrus, left thalamus, and right middle frontal gyrus were found to be related to proactive aggression. Furthermore, the brain activation regions primarily involved in proactive aggression induced by reward expectancy were the insula, inferior frontal gyrus, inferior temporal gyrus, pallidum, and caudate nucleus. Under conditions of high reward expectancy, participants engage in more proactive aggressive behavior. Reward expectancy involves the activation of reward- and social-cognition-related brain regions, and these associations are instrumental in proactive aggressive decisions.

Sequence-based design and construction of synthetic nanobody library.

Nanobody (Nb), the smallest antibody fragments known to bind antigens, is now widely applied to various studies, including protein structure analysis, bioassay, diagnosis, and biomedicine. The traditional approach to generating specific nanobodies involves animal immunization which is time-consuming and expensive. As the understanding of the antibody repertoire accumulation, the synthetic library, which is devoid of animals, has attracted attention widely in recent years. Here, we describe a synthetic phage display library (S-Library), designed based on the systematic analysis of the next-generation sequencing (NGS) of nanobody repertoire. The library consists of a single highly conserved scaffold (IGHV3S65*01-IGHJ4*01) and complementary determining regions of constrained diversity. The S-Library containing 2.19 × 108 independent clones was constructed by the one-step assembly and rapid electro-transformation. The S-Library was screened against various targets (Nb G8, fusion protein of Nb G8 and green fluorescent protein, bovine serum albumin, ovalbumin, and acetylcholinesterase). In comparison, a naïve library (N-Library) from the source of 13 healthy animals was constructed and screened against the same targets as the S-Library. Binders were isolated from both S-Library and N-Library. The dynamic affinity was evaluated by the biolayer interferometry. The data confirms that the feature of the Nb repertoire is conducive to reducing the complexity of library design, thus allowing the S-Library to be built on conventional reagents and primers.

How distinct functional insular subdivisions mediate interacting neurocognitive systems.

Recent neurocognitive models propose that the insula serves as a hub of interoceptive awareness system, modulating 2 interplaying neurocognitive systems: The posterior insula (PI) receives and integrates various interoceptive signals; these signals are then transmitted to the anterior insula for processing higher-order representations into awareness, where the dorsal anterior insula (dAI) modulates the prefrontal self-control system and the ventral anterior insula (vAI) modulates the amygdala (AMG)-striatal reward-seeking circuit. We sought to test this view using a multimodal approach. We first used a resting-state functional magnetic resonance imaging (fMRI) approach with a sample of 120 undergraduate students. Then, we unpacked the neuro-cognitive association between insular connectivity and cognitive performance during an Iowa gambling fMRI task. Lastly, an independent Open Southwest University Longitudinal Imaging Multimodal dataset was used to validate the results. Findings suggested that the dAI was predominantly connected to the prefrontal regions; the vAI was primarily connected to the AMG-ventral-striatum system; and the PI was mainly connected to the visceral-sensorimotor system. Moreover, cognitive scores were positively correlated with FC between dAI and the self-control process of ventrolateral prefrontal cortex and were negatively correlated with FC between vAI and the reward-seeking process of orbitofrontal cortex and subgenual anterior cingulate cortex. The findings highlight the roles of our theorized subinsular functionality in the overall operation of the neural cognitive systems.

Gender-specific resting-state rDMPFC-centric functional connectivity underpinnings of intertemporal choice.

Although studies have observed gender differences in intertemporal choice, the neural bases of these differences require further research. The current study used resting state functional connectivity (rsFC) to explore the gender-specific neural basis of intertemporal choice in three independent samples (n1 = 86, n2 = 297, n3 = 172). Behaviorally, three samples (S1, S2, and S3) consistently demonstrated that men had larger delay discounting rate (log k) than women. Then, whole-brain functional connectivity analyses were performed for different genders in S2 and S3 using the right dorsomedial prefrontal cortex (rDMPFC) as a region of interest. By subtracting the common rsFC patterns of different genders, we identified gender-specific log k-related rsFC patterns with significant gender differences in S2. This was verified in an independent sample (S3). Specifically, in women, log k was found to be positively correlated with the rsFC between rDMPFC and anterior cingulate cortex/right orbitofrontal cortex. In contrast, in men, log k was negatively correlated with rsFC between rDMPFC and left orbitofrontal cortex/right precuneus. These gender differences were confirmed by slope tests. The findings highlight how gender may differ when engaging in intertemporal choice. They improve the understanding of gender differences in decision impulsivity and its underlying neural bases.

Being bold wisely: neural substrates underlying ability to exploit risk.

Nothing ventured, nothing gained. To succeed one must take risks, and more importantly, take risks wisely, which depends on individual ability to exploit risk. Here, we explore neural substrates for the ability to exploit risk by using voxel-based morphometry (VBM). First, we carried out structural magnetic resonance imaging and measured individual risk-taking propensity and corresponding earnings by administrating the Balloon Analogue Risk Task in 1,389 participants. Behavior analysis revealed an inverted-U-shaped relation between risk-taking propensity and earnings, that earnings initially increased and then decreased as risk-taking propensity increased. Then individual ability to exploit risk was estimated by calculating the difference between individual actual earnings and the average earnings of the group at the same level of risk-taking propensity. VBM analysis revealed that individual ability to exploit risk was positively correlated with the gray matter volumes of three clusters located in the right orbitofrontal cortex, left dorsolateral prefrontal cortex (dlPFC), and right dlPFC, respectively. These findings highlight the neural substrates for the ability to exploit risk and implicate that precise valuation, adaptive learning, and self-control may underpin the ability to exploit risk, which expand our understanding of the ability to exploit risk and its neural substrates.

Risk of insomnia during COVID-19: effects of depression and brain functional connectivity.

Normal sleepers may be at risk for insomnia during COVID-19. Identifying psychological factors and neural markers that predict their insomnia risk, as well as investigating possible courses of insomnia development, could lead to more precise targeted interventions for insomnia during similar public health emergencies. Insomnia severity index of 306 participants before and during COVID-19 were employed to determine the development of insomnia, while pre-COVID-19 psychometric and resting-state fMRI data were used to explore corresponding psychological and neural markers of insomnia development. Normal sleepers as a group reported a significant increase in insomnia symptoms after COVID-19 outbreak (F = 4.618, P = 0.0102, df = 2, 609.9). Depression was found to significantly contribute to worse insomnia (ß = 0.066, P = 0.024). Subsequent analysis found that functional connectivity between the precentral gyrus and middle/inferior temporal gyrus mediated the association between pre-COVID-19 depression and insomnia symptoms during COVID-19. Cluster analysis identified that postoutbreak insomnia symptoms followed 3 courses (lessened, slightly worsened, and developed into mild insomnia), and pre-COVID-19 depression symptoms and functional connectivities predicted these courses. Timely identification and treatment of at-risk individuals may help avoid the development of insomnia in the face of future health-care emergencies, such as those arising from COVID-19 variants.

Multivariate resting-state functional connectomes predict and characterize obesity phenotypes.

The univariate obesity-brain associations have been extensively explored, while little is known about the multivariate associations between obesity and resting-state functional connectivity. We therefore utilized machine learning and resting-state functional connectivity to develop and validate predictive models of 4 obesity phenotypes (i.e. body fat percentage, body mass index, waist circumference, and waist-height ratio) in 3 large neuroimaging datasets (n = 2,992). Preliminary evidence suggested that the resting-state functional connectomes effectively predicted obesity/weight status defined by each obesity phenotype with good generalizability to longitudinal and independent datasets. However, the differences between resting-state functional connectivity patterns characterizing different obesity phenotypes indicated that the obesity-brain associations varied according to the type of measure of obesity. The shared structure among resting-state functional connectivity patterns revealed reproducible neuroimaging biomarkers of obesity, primarily comprising the connectomes within the visual cortex and between the visual cortex and inferior parietal lobule, visual cortex and orbital gyrus, and amygdala and orbital gyrus, which further suggested that the dysfunctions in the perception, attention and value encoding of visual information (e.g. visual food cues) and abnormalities in the reward circuit may act as crucial neurobiological bases of obesity. The recruitment of multiple obesity phenotypes is indispensable in future studies seeking reproducible obesity-brain associations.

Increased ventral anterior insular connectivity to sports betting availability indexes problem gambling.

With the advent of digital technologies, online sports betting is spurring a fast-growing expansion. In this study, we examined how sports betting availability modulates the brain connectivity of frequent sports bettors with [problem bettors (PB)] or without [non-problem bettors (NPB)] problematic sports betting. We conducted functional connectivity analyses centred on the ventral anterior insular cortex (vAI), a brain region playing a key role in the dynamic interplay between reward-based processes. We re-analysed a dataset on sports betting availability undertaken in PB (n = 30) and NPB (n = 35). Across all participants, we observed that sports betting availability elicited positive vAI coupling with extended clusters of brain activation (encompassing the putamen, cerebellum, occipital, temporal, precentral and central operculum regions) and negative vAI coupling with the orbitofrontal cortex. Between-group analyses showed increased positive vAI coupling in the PB group, as compared with the NPB group, in the left lateral occipital cortex, extending to the left inferior frontal gyrus, the anterior cingulate gyrus and the right frontal pole. Taken together, these results are in line with the central assumptions of triadic models of addictions, which posit that the insular cortex plays a pivotal role in promoting the drive and motivation to get a reward by 'hijacking' goal-oriented processes toward addiction-related cues. Taken together, these findings showed that vAI functional connectivity is sensitive not only to gambling availability but also to the status of problematic sport betting.

Altered executive control network and default model network topology are linked to acute electronic cigarette use: A resting-state fNIRS study.

In recent years, electronic cigarettes (e-cigs) have gained popularity as stylish, safe, and effective smoking cessation aids, leading to widespread consumer acceptance. Although previous research has explored the acute effects of combustible cigarettes or nicotine replacement therapy on brain functional activities, studies on e-cigs have been limited. Using fNIRS, we conducted graph theory analysis on the resting-state functional connectivity of 61 male abstinent smokers both before and after vaping e-cigs. And we performed Pearson correlation analysis to investigate the relationship between alterations in network metrics and changes in craving. E-cig use resulted in increased degree centrality, nodal efficiency, and local efficiency within the executive control network (ECN), while causing a decrease in these properties within the default model network (DMN). These alterations were found to be correlated with reductions in craving, indicating a relationship between differing network topologies in the ECN and DMN and decreased craving. These findings suggest that the impact of e-cig usage on network topologies observed in male smokers resembles the effects observed with traditional cigarettes and other forms of nicotine delivery, providing valuable insights into their addictive potential and effectiveness as aids for smoking cessation.

Comparison of percutaneous nephrolithotomy and flexible ureterorenoscopy in the treatment of single upper ureteral calculi measuring 1 to 2 centimeters: a retrospective study.

PURPOSE: To compare the efficacy and safety of micropercutaneous nephrolithotomy (MPCNL) and flexible ureteroscopy (FURS) in the treatment of single upper ureteral calculi measuring 1 to 2 centimeters. METHODS: This study is a retrospective analysis that combines a review of medical records with an outcomes management database. A total of 163 patients who underwent MPCNL and 137 patients who had FURS were identified between January 2017 and December 2021. Demographic data, operation time, hospitalization time, stone-free rate, and complication rate were collected and analyzed. RESULTS: Preoperative general data of sex, age, BMI, serum creatinine, time of stone existence, stone hardness, stone diameter, preoperative hydronephrosis, and preoperative infection of the MPCNL group have no statistically significant difference with that of the FURS group. All MPCNL or FURS operations in both groups were successfully completed without any instances of reoperation or conversion to another surgical procedure. Patients who underwent MPCNL had a considerably reduced operation time (49.6 vs. 72.4 min; P<0.001), but a higher duration of hospitalization (9.1 vs. 3.9 days; P<0.001) compared to those who underwent FURS. The stone-free rate in the MPCNL group was superior to that of the FURS group, with a percentage of 90.8% compared to 71.5% (P<0.001). There was no statistically significant disparity in the rate of complications between the two groups (13.5% vs. 15.3%; P = 0.741). CONCLUSION: Both MPCNL and FURS are viable and secure surgical choices for individuals with solitary upper ureteral calculi measuring 1 to 2 cm. The FURS procedure resulted in a shorter duration of hospitalization compared to MPCNL. However, it had a comparatively lower rate of successfully removing the stones and required a longer duration for the operation.There were no substantial disparities observed in the complication rate between the two groups.FURS is the preferable option for treating uncomplicated upper ureteral calculi, whereas MPCNL is the preferable option for treating complicated upper ureteral calculi.Prior to making treatment options, it is crucial to take into account the expertise of surgeons, the quality of the equipment, and the preferences of the patient. TRIAL REGISTRATION: No.

Distributed attribute representation in the superior parietal lobe during probabilistic decision-making.

Several studies have examined the neural substrates of probabilistic decision-making, but few have systematically investigated the neural representations of the two objective attributes of probabilistic rewards, that is, the reward amount and the probability. Specifically, whether there are common or distinct neural activity patterns to represent the objective attributes and their association with the neural representation of the subjective valuation remains largely underexplored. We conducted two studies (nStudy1 = 34, nStudy2 = 41) to uncover distributed neural representations of the objective attributes and subjective value as well as their association with individual probability discounting rates. The amount and probability were independently manipulated to better capture brain signals sensitive to these two attributes and were presented simultaneously in Study 1 and successively in Study 2. Both univariate and multivariate pattern analyses showed that the brain activities in the superior parietal lobule (SPL), including the postcentral gyrus, were modulated by the amount of rewards and probability in both studies. Further, representational similarity analysis revealed a similar neural representation between these two objective attributes and between the attribute and valuation. Moreover, the SPL tracked the subjective value integrated by the hyperbolic function. Probability-related brain activations in the inferior parietal lobule were associated with the variability in individual discounting rates. These findings provide novel insights into a similar neural representation of the two attributes during probabilistic decision-making and perhaps support the common neural coding of stimulus objective properties and subjective value in the field of probabilistic discounting.

Connectome-based prediction of eating disorder-associated symptomatology.

BACKGROUND: Despite increasing knowledge on the neuroimaging patterns of eating disorder (ED) symptoms in non-clinical populations, studies using whole-brain machine learning to identify connectome-based neuromarkers of ED symptomatology are absent. This study examined the association of connectivity within and between large-scale functional networks with specific symptomatic behaviors and cognitions using connectome-based predictive modeling (CPM). METHODS: CPM with ten-fold cross-validation was carried out to probe functional networks that were predictive of ED-associated symptomatology, including body image concerns, binge eating, and compensatory behaviors, within the discovery sample of 660 participants. The predictive ability of the identified networks was validated using an independent sample of 821 participants. RESULTS: The connectivity predictive of body image concerns was identified within and between networks implicated in cognitive control (frontoparietal and medial frontal), reward sensitivity (subcortical), and visual perception (visual). Crucially, the set of connections in the positive network related to body image concerns identified in one sample was generalized to predict body image concerns in an independent sample, suggesting the replicability of this effect. CONCLUSIONS: These findings point to the feasibility of using the functional connectome to predict ED symptomatology in the general population and provide the first evidence that functional interplay among distributed networks predicts body shape/weight concerns.

Predisposing Variations in Fear-Related Brain Networks Prospectively Predict Fearful Feelings during the 2019 Coronavirus (COVID-19) Pandemic.

The novel coronavirus (COVID-19) pandemic has led to a surge in mental distress and fear-related disorders, including posttraumatic stress disorder (PTSD). Fear-related disorders are characterized by dysregulations in fear and the associated neural pathways. In the present study, we examined whether individual variations in the fear neural connectome can predict fear-related symptoms during the COVID-19 pandemic. Using machine learning algorithms and back-propagation artificial neural network (BP-ANN) deep learning algorithms, we demonstrated that the intrinsic neural connectome before the COVID-19 pandemic could predict who would develop high fear-related symptoms at the peak of the COVID-19 pandemic in China (Accuracy rate = 75.00%, Sensitivity rate = 65.83%, Specificity rate = 84.17%). More importantly, prediction models could accurately predict the level of fear-related symptoms during the COVID-19 pandemic by using the prepandemic connectome state, in which the functional connectivity of lvmPFC (left ventromedial prefrontal cortex)-rdlPFC (right dorsolateral), rdACC (right dorsal anterior cingulate cortex)-left insula, lAMY (left amygdala)-lHip (left hippocampus) and lAMY-lsgACC (left subgenual cingulate cortex) was contributed to the robust prediction. The current study capitalized on prepandemic data of the neural connectome of fear to predict participants who would develop high fear-related symptoms in COVID-19 pandemic, suggesting that individual variations in the intrinsic organization of the fear circuits represent a neurofunctional marker that renders subjects vulnerable to experience high levels of fear during the COVID-19 pandemic.

Maladaptive changes in delay discounting in males during the COVID-19 pandemic: the predictive role of functional connectome.

The Coronavirus disease of 2019 (COVID-19) and measures to curb it created population-level changes in male-dominant impulsive and risky behaviors such as violent crimes and gambling. One possible explanation for this is that the pandemic has been stressful, and males, more so than females, tend to respond to stress by altering their focus on immediate versus delayed rewards, as reflected in their delay discounting rates. Delay discounting rates from healthy undergraduate students were collected twice during the pandemic. Discounting rates of males (n=190) but not of females (n=493) increased during the pandemic. Using machine learning, we show that prepandemic functional connectome predict increased discounting rates in males (n=88). Moreover, considering that delay discounting is associated with multiple psychiatric disorders, we found the same neural pattern that predicted increased discounting rates in this study, in secondary datasets of patients with major depression and schizophrenia. The findings point to sex-based differences in maladaptive delay discounting under real-world stress events, and to connectome-based neuromarkers of such effects. They can explain why there was a population-level increase in several impulsive and risky behaviors during the pandemic and point to intriguing questions about the shared underlying mechanisms of stress responses, psychiatric disorders and delay discounting.

Brain modular connectivity interactions can predict proactive inhibition in smokers when facing smoking cues.

Proactive inhibition is a critical ability for smokers who seek to moderate or quit smoking. It allows them to pre-emptively refrain from seeking and using nicotine products, especially when facing salient smoking cues in daily life. Nevertheless, there is limited knowledge on the impact of salient cues on behavioural and neural aspects of proactive inhibition, especially in smokers with nicotine withdrawal. Here, we seek to bridge this gap. To this end, we recruited 26 smokers to complete a stop-signal anticipant task (SSAT) in two separate sessions: once in the neutral cue condition and once in the smoking cue condition. We used graph-based modularity analysis to identify the modular structures of proactive inhibition-related network during the SSAT and further investigated how the interactions within and between these modules could be modulated by different proactive inhibition demands and salient smoking cues. Findings pointed to three stable brain modules involved in the dynamical processes of proactive inhibition: the sensorimotor network (SMN), cognitive control network (CCN) and default-mode network (DMN). With the increase in demands, functional connectivity increased within the SMN, CCN and between SMN-CCN and decreased within the DMN and between SMN-DMN and CCN-DMN. Salient smoking cues disturbed the effective dynamic interactions of brain modules. The profiles for those functional interactions successfully predicted the behavioural performance of proactive inhibition in abstinent smokers. These findings advance our understanding of the neural mechanisms of proactive inhibition from a large-scale network perspective. They can shed light on developing specific interventions for abstinent smokers.

Neural differences of food-specific inhibitory control in people with healthy vs higher BMI.

Consistent with the idea that deficits in inhibition limit resistance to tempting, tasty, high-calorie foods, and might result in a higher BMI, we test whether people with higher BMIs (BMI >25 kg/m2) present inefficient inhibitory control over food-related responses. To unpack this association, we also examine individual differences in the neural mechanisms of food inhibitory control in healthy vs higher BMI individuals. We test these aspects with a sample of 109 participants (49 with higher BMI and 60 with healthy BMI) and the food stop-signal task, which was used to examine individuals' inhibitory control. Results demonstrated that people with higher BMI had significantly poorer food inhibitory control than healthy BMI individuals. fMRI results showed that, in both Go (Go_food vs Go_nature) and Stop conditions (Stop_food vs Stop_nature), compared to healthy BMI individuals, individuals with higher BMI had lower activation in the superior frontal gyrus, precuneus, precentral gyrus, and supramarginal gyrus in the food stimulus condition. Moreover, ROI analysis results showed that under the Stop_food condition, the activation in the inferior frontal gyrus in the higher BMI group was significantly negatively correlated with inhibitory control abilities. These results suggest that people with a higher BMI have limited ability to inhibit food impulsions, and that the prefrontal regions and parietal cortex may contribute to the progression of inhibitory control limitations in relation to food.