Localization of epileptogenic zone based on time-varying effective networks.

Surgical resection of the epileptogenic zone (EZ) is an effective method for treating drug-resistant epilepsy. At present, the accuracy of EZ localization needs to be further improved. The characteristics of graph theory based on partial directed coherence networks have been applied to the localization of EZ, but the application of network control theory to effective networks to locate EZ is rarely reported. In this study, the method of partial directed coherence analysis was utilized to construct the time-varying effective brain networks of stereo-electroencephalography (SEEG) signals from 20 seizures in 12 patients. Combined with graph theory and network control theory, the differences in network characteristics between epileptogenic and non-epileptogenic zones during seizures were analyzed. We also used dung beetle optimized support vector machine classification model to evaluate the localization effect of EZ based on brain network characteristics of graph theory and controllability. The results showed that the classification of the average controllability feature was the best, and the area under the receiver operating characteristic (ROC) curve (AUC) was 0.9505, which is 1.32 % and 1.97 % higher than the traditional methods. The AUC value increased to 0.9607 after integrating the average controllability with other features. This study proved the effectiveness of controllability characteristic in identifying the EZ and provided a theoretical basis for the clinical application of network controllability in the EZ.

Linked patterns of symptoms and cognitive covariation with functional brain controllability in major depressive disorder.

BACKGROUND: Controllability analysis is an approach developed for evaluating the ability of a brain region to modulate function in other regions, which has been found to be altered in major depressive disorder (MDD). Both depressive symptoms and cognitive impairments are prominent features of MDD, but the case-control differences of controllability between MDD and controls can not fully interpret the contribution of both clinical symptoms and cognition to brain controllability and linked patterns among them in MDD. METHODS: Sparse canonical correlation analysis was used to investigate the associations between resting-state functional brain controllability at the network level and clinical symptoms and cognition in 99 first-episode medication-naïve patients with MDD. FINDINGS: Average controllability was significantly correlated with clinical features. The average controllability of the dorsal attention network (DAN) and visual network had the highest correlations with clinical variables. Among clinical variables, depressed mood, suicidal ideation and behaviour, impaired work and activities, and gastrointestinal symptoms were significantly negatively associated with average controllability, and reduced cognitive flexibility was associated with reduced average controllability. INTERPRETATION: These findings highlight the importance of brain regions in modulating activity across brain networks in MDD, given their associations with symptoms and cognitive impairments observed in our study. Disrupted control of brain reconfiguration of DAN and visual network during their state transitions may represent a core brain mechanism for the behavioural impairments observed in MDD. FUNDING: National Natural Science Foundation of China (82001795 and 82027808), National Key R&D Program (2022YFC2009900), and Sichuan Science and Technology Program (2024NSFSC0653).

The perceived controllability of negatively-valenced episodic future thinking modulates delay discounting.

Intertemporal decision-making is important for both economy and physical health. Nevertheless, in daily life, individuals tend to prefer immediate and smaller rewards to delayed and larger rewards, which is known as delay discounting (DD). Episodic future thinking (EFT) has been proven to influence DD. However, there is still no inconsistent conclusion on the effect of negative EFT on DD. Considering the perceived controllability of negative EFT may address the issue (Controllability refers to the extent to which progress and result of an event could be controlled by ourselves). In the current study, we manipulated EFT conditions (baseline, neutral EFT, negative-controllable EFT and negative-uncontrollable EFT), delayed time (i.e. 1 week, 1 month, 3 months, 6 months, 1 year and 3 years) and reward magnitude (small, large). We mainly found that when experiencing negative-uncontrollable EFT compared to negative-controllable EFT in the delayed time of 6 months with large rewards, individuals chose more delayed rewards, suggesting that negative-uncontrollable EFT effectively reduced DD under conditions of both large-magnitude reward and longer delayed time. The current study provides new insight for healthy groups on optimising EFT. In that case, individuals are able to gain long-term benefits in financial management and healthcare.

Bimetallic Photo-Activated and Steerable Janus Micromotors as Active Microcleaners for Wastewater.

Photoactive colloidal motors whose motion can be controlled and even programed via external magnetic fields have significant potential in practical applications extending from biomedical fields to environmental remediation. Herein, we report a "three in one" strategy in a Co/Zn-TPM (3-trimethoxysilyl propyl methacrylate) bimetallic Janus colloidal micromotor (BMT-micromotor) which can be controlled by an optical field, chemical fuel, and magnetic field. The speed of the micromotors can be tuned by light intensity and with the concentration of the chemical fuel of H2O2, while it could be steered and programed through magnetic field due to the presence of Co in the bimetallic part. Finally, the BMT-micromotors were employed to effectively remove rubidium metal ions and organic dyes (methylene blue and rhodamine b). Benefited of excellent mobility, multiple active sites, and hierarchical morphology, the micromotors exhibit excellent adsorption capacity of 103 mg·g-1 to Rb metal ions and high photodegradation efficiency toward organic dyes in the presence of a lower concentration of H2O2. The experimental characterizations and DFT calculations confirmed the strong interaction of Rb metal ions on the surface of BMT-micromotors and the excellent decomposition of H2O2 which enhanced the photodegradation process. We expect the combination of light and fuel sensitivity with magnetic controllability to unlock an excess of opportunities for the application of BMT-micromotors in water treatments.

Perceived controllability of group membership does not moderate individuating information effects in implicit person perception.

Although the effects of counterstereotypic individuating information (i.e., information specific to individual members of stereotyped groups that disconfirms the group stereotype) on biases in explicit person perception are well-established, research shows mixed effects of such information on implicit person perception. The present research tested the overarching hypothesis that, when social group membership is perceived to be under an individual's control, diagnostic individuating information would have lesser effects on implicit person perception than it would when social group membership is perceived not to be under an individual's control. This hypothesis was tested in the domain of implicit attitudinal and stereotype-relevant judgments of individuals who belonged to existing social groups and individuals who belonged to novel social groups. We found that individuating information consistently shifted scores on implicit measures among targets belonging to existing social groups, but not in a theoretically predicted direction among targets belonging to novel social groups. Controllability of group membership did not moderate such effects. Results of implicit and explicit measures were mostly consistent when targets belonged to existing social groups, but mostly inconsistent when targets belonged to novel social groups.

Evidence for a role of the basolateral amygdala in regulating regional metabolism in the stressed brain.

The brain regulates every physiological process in the body, including metabolism. Studies investigating brain metabolism have shown that stress can alter major metabolic processes, and that these processes can vary between regions. However, no study has investigated how metabolic pathways may be altered by stressor perception, or whether stress-responsive brain regions can also regulate metabolism. The basolateral amygdala (BLA), a region important for stress and fear, has reciprocal connections to regions responsible for metabolic regulation. In this study, we investigated how BLA influences regional metabolic profiles within the hippocampus (HPC) and medial prefrontal cortex (mPFC), regions involved in regulating the stress response and stress perception, using optogenetics in male C57BL/6 mice during footshock presentation in a yoked shuttlebox paradigm based on controllable (ES) and uncontrollable (IS) stress. RNA extracted from HPC and mPFC were loaded into NanoString® Mouse Neuroinflammation Panels, which also provides a broad view of metabolic processes, for compilation of gene expression profiles. Results showed differential regulation of carbohydrate and lipid metabolism, and insulin signaling gene expression pathways in HPC and mPFC following ES and IS, and that these differences were altered in response to optogenetic excitation or inhibition of the BLA. These findings demonstrate for the first time that individual brain regions can utilize metabolites in a way that are unique to their needs and function in response to a stressor, and that vary based on stressor controllability and influence by BLA.

From Connectivity to Controllability: Unraveling the Brain Biomarkers of Major Depressive Disorder.

Major Depressive Disorder (MDD) is a significant neurological condition associated with aberrations in brain functional networks. Traditional studies have predominantly analyzed these from a network topology perspective. However, given the brain's dynamic and complex nature, exploring its mechanisms from a network control standpoint provides a fresh and insightful framework. This research investigates the integration of network controllability and machine learning to pinpoint essential biomarkers for MDD using functional magnetic resonance imaging (fMRI) data. By employing network controllability methods, we identify crucial brain regions that are instrumental in facilitating transitions between brain states. These regions demonstrate the brain's ability to navigate various functional states, emphasizing the utility of network controllability metrics as potential biomarkers. Furthermore, these metrics elucidate the complex dynamics of MDD and support the development of precision medicine strategies that incorporate machine learning to improve the precision of diagnostics and the efficacy of treatments. This study underscores the value of merging machine learning with network neuroscience to craft personalized interventions that align with the unique pathological profiles of individuals, ultimately enhancing the management and treatment of MDD.

Controllability on impulsive systems with delays in both input and impulse and its applications to multi-agent networks.

This paper investigates the controllability of impulsive systems with input delay and impulse delay and its applications in multi-agent networks. We adopt the geometric and algebraic analytical tools to establish some easily verified controllability conditions for the considered system model. First, the analytic solution of the considered system is established on every impulsive interval by using ordinary differential equation theory. Then, according to the solution derived, some sufficient complete controllability criteria are developed to reveal the role of the Gramian matrices in different subintervals. By introducing a row matrix of different kinds of Gramian matrices, a complete controllability condition that is proved to be necessary and sufficient is further obtained. By using the relevant geometric matrix theory, the derived algebraic controllability condition is then converted to a geometric one. On other hand, we introduce a multi-agent network with delayed input and impulse and investigate its controllability. By resorting to graph theory and matrix theory, several factors affecting the controllability of the considered multi-agent networks are investigated, such as the topology structure, the inner coupling matrix, and the dynamics of each agent. Finally, two numerical examples are worked out to verify the derived controllability criteria.

Weiner's Attribution-Emotion-Action Model: Uncovering the Mediating Role of Self-Blame and the Moderating Effect of the Helper's Responsibility for the Help Recipient's Behavior.

Seven preregistered experimental studies investigated a potential mediator (self-blame) and moderator (the perceived responsibility of the helper for the help recipient's behavior) of Weiner's attribution-emotion-action model. When participants considered a nonchild close other experiencing depression, higher perceived controllability was related to lower sympathy, which correlated with less willingness to provide support; however, among parents considering their child experiencing depression, perceived controllability was either positively associated with sympathy (study 1) or did not influence sympathy (study 2). Offering an explanation, studies 3a/3b indicated a significantly weaker relationship between controllability and responsibility attributions when the target of help was the participant's child. Study 4 investigated the underlying mechanism. Parents experienced self-blame when the cause was controllable, which lowered the association between controllability and responsibility attributions. Studies 5 and 6 revealed this pattern was not specific to the parent-child relationship but occurred whenever the potential helper felt responsible for the help recipient's behavior.

Versatile Prepolymer Platform for Controlled Tailoring of Quantum Dot Surface Properties.

Quantum dots (QDs) hold immense promise for bioimaging, yet technical challenges in surface engineering limit their wider scientific use. We introduce poly(pentafluorophenyl acrylate) (PPFPA) as a user-friendly prepolymer platform for creating precisely controlled multidentate polymeric ligands for QD surface engineering, accessible to researchers without extensive synthetic expertise. PPFPA combines the benefits of both bottom-up and prepolymer approaches, offering minimal susceptibility to hydrolysis and side reactions for controlled chemical composition, along with simple synthetic procedures using commercially available reagents. Live cell imaging experiments highlighted a significant reduction in nonspecific binding when employing PPFPA, owing to its minimal hydrolysis, in contrast to ligands synthesized by using a conventional prepolymer prone to uncontrolled hydrolysis. This observation underscores the distinct advantage of our prepolymer system. Leveraging PPFPA, we synthesized biomolecule-conjugated QDs and performed QD-based immunofluorescence to detect a cytosolic protein. To effectively label cytosolic targets in such a dense and complex environment, probes must exhibit minimal nonspecific binding and be compact. As a result, QD-immunofluorescence has focused primarily on cell surface targets. By creating compact QD-F(ab')2, we sensitively detected alpha-tubulin with a ∼50-fold higher signal-to-noise ratio compared to organic dye-based labeling. PPFPA represents a versatile and accessible platform for tailoring QD surfaces, offering a pathway to realize the full potential of colloidal QDs in various scientific applications.

Emotion malleability beliefs matter in emotion regulation: a comprehensive review and meta-analysis.

Individuals' beliefs about the malleability of emotions have been theorised to play a role in their psychological distress by influencing emotion regulation processes, such as the use of emotion regulation strategies. We conducted a meta-analysis to test this idea across studies with a focus on the relationships between emotion malleability beliefs and five distinct emotion regulation strategies: cognitive reappraisal, suppression, avoidance, rumination, and acceptance. Further, using two-stage meta-analytic structural equation modelling (TSSEM), we examined whether the emotion regulation strategies mediate the cross-sectional relationship between emotion malleability beliefs and psychological distress across studies. Thirty-seven studies were included in the meta-analyses and 55 cross-sectional studies were included in the TSSEM. Results demonstrated that, across studies, emotion malleability beliefs were significantly associated with greater use of putatively helpful strategies (particularly with cognitive reappraisal) and less use of putatively unhelpful strategies (particularly with avoidance). The use of cognitive reappraisal and avoidance partially mediated the relationship between emotion malleability beliefs and psychological distress. These results highlight the importance of considering beliefs about the malleability of emotions in the context of emotion regulation. These findings suggest the potential role of emotion malleability beliefs in interventions for individuals with emotion regulation-related difficulties and psychological distress.

The impact of input node placement in the controllability of structural brain networks.

Network controllability refers to the ability to steer the state of a network towards a target state by driving certain nodes, known as input nodes. This concept can be applied to brain networks for studying brain function and its relation to the structure, which has numerous practical applications. Brain network controllability involves using external signals such as electrical stimulation to drive specific brain regions and navigate the neurophysiological activity level of the brain around the state space. Although controllability is mainly theoretical, the energy required for control is critical in real-world implementations. With a focus on the structural brain networks, this study explores the impact of white matter fiber architecture on the control energy in brain networks using the theory of how input node placement affects the LCC (the longest distance between inputs and other network nodes). Initially, we use a single input node as it is theoretically possible to control brain networks with just one input. We show that highly connected brain regions that lead to lower LCCs are more energy-efficient as a single input node. However, there may still be a need for a significant amount of control energy with one input, and achieving controllability with less energy could be of interest. We identify the minimum number of input nodes required to control brain networks with smaller LCCs, demonstrating that reducing the LCC can significantly decrease the control energy in brain networks. Our results show that relying solely on highly connected nodes is not effective in controlling brain networks with lower energy by using multiple inputs because of densely interconnected brain network hubs. Instead, a combination of low and high-degree nodes is necessary.

Functional brain network controllability dysfunction in Alzheimer's disease and its relationship with cognition and gene expression profiling.

Objective. In recent studies, network control theory has been applied to clarify transitions between brain states, emphasizing the significance of assessing the controllability of brain networks in facilitating transitions from one state to another. Despite these advancements, the potential alterations in functional network controllability associated with Alzheimer's disease (AD), along with the underlying genetic mechanisms responsible for these alterations, remain unclear.Approach. We conducted a comparative analysis of functional network controllability measures between patients with AD (n= 64) and matched normal controls (NCs,n= 64). We investigated the association between altered controllability measures and cognitive function in AD. Additionally, we conducted correlation analyses in conjunction with the Allen Human Brain Atlas to identify genes whose expression was correlated with changes in functional network controllability in AD, followed by a set of analyses on the functional features of the identified genes.Main results. In comparison to NCs, patients with AD exhibited a reduction in average controllability, predominantly within the default mode network (DMN) (63% of parcellations), and an increase in average controllability within the limbic (LIM) network (33% of parcellations). Conversely, AD patients displayed a decrease in modal controllability within the LIM network (27% of parcellations) and an increase in modal controllability within the DMN (80% of parcellations). In AD patients, a significant positive correlation was found between the average controllability of the salience network and the mini-mental state examination scores. The changes in controllability measures exhibited spatial correlation with transcriptome profiles. The significant genes identified exhibited enrichment in neurobiologically relevant pathways and demonstrated preferential expression in various tissues, cell types, and developmental periods.Significance. Our findings have the potential to offer new insights into the genetic mechanisms underlying alterations in the controllability of functional networks in AD. Additionally, these results offered perspectives for a deeper understanding of the pathogenesis and the development of therapeutic strategies for AD.

Aberrant neural computation of social controllability in nicotine-dependent humans.

Social controllability, defined as the ability to exert influence when interacting with others, is crucial for optimal decision-making. Inability to do so might contribute to maladaptive behaviors such as drug use, which often takes place in social settings. Here, we examined nicotine-dependent humans using fMRI, as they made choices that could influence the proposals from simulated partners. Computational modeling revealed that smokers under-estimated the influence of their actions and self-reported a reduced sense of control, compared to non-smokers. These findings were replicated in a large independent sample of participants recruited online. Neurally, smokers showed reduced tracking of forward projected choice values in the ventromedial prefrontal cortex, and impaired computation of social prediction errors in the midbrain. These results demonstrate that smokers were less accurate in estimating their personal influence when the social environment calls for control, providing a neurocomputational account for the social cognitive deficits in this population.

Emotion Controllability Beliefs and Young People's Anxiety and Depression Symptoms: A Systematic Review.

Emotion regulation is a powerful predictor of youth mental health and a crucial ingredient of interventions. A growing body of evidence indicates that the beliefs individuals hold about the extent to which emotions are controllable (emotion controllability beliefs) influence both the degree and the ways in which they regulate emotions. A systematic review was conducted that investigated the associations between emotion controllability beliefs and youth anxiety and depression symptoms. The search identified 21 peer-reviewed publications that met the inclusion criteria. Believing that emotions are relatively controllable was associated with fewer anxiety and depression symptoms, in part because these beliefs were associated with more frequent use of adaptive emotion regulation strategies. These findings support theoretical models linking emotion controllability beliefs with anxiety and depression symptoms via emotion regulation strategies that target emotional experience, like reappraisal. Taken together, the review findings demonstrate that emotion controllability beliefs matter for youth mental health. Understanding emotion controllability beliefs is of prime importance for basic science and practice, as it will advance understanding of mental health and provide additional targets for managing symptoms of anxiety and depression in young people.

Should We Really Be Afraid of "Weakness"? Applying the Insights of Attribution Theory.

It is widely assumed that the term "weakness" has negative psychological effects and should be replaced by "area for improvement." The present study is the first to examine the matter experimentally. It was hypothesised that effects of "weakness" (vs. "area for improvement") are most pronounced in those with low perceived self-efficacy in the relevant domain. Two experiments were conducted in the domain of self-regulation. In those with low perceived self-efficacy for self-regulation (PSESR), "weakness" apparently had a negative indirect effect on improvement expectancy by increasing the perceived stability (Experiment 1) or lowering the perceived controllability (Experiment 2) of the problem. Moreover, at low levels of PSESR in Experiment 2, estimated indirect effects of "weakness" on perceived value of improvement were both positive and negative. However, gender apparently moderated those effects. "Weakness" apparently lowered perceived controllability in both males and females but in women the negative effect was more pronounced when PSESR was low. In addition, "weakness" apparently increased perceived internality in males with low PSESR. Compared to "area for improvement," "weakness" may indeed have some (negative) psychological effects in people with low perceived self-efficacy in the relevant domain. Given the ubiquity of these terms in evaluative contexts and the widespread fears of the term "weakness," more experimental research needs to be conducted.

Facets of Suicidal Ideation.

According to SAMHSA (2023), approximately 16,600,000 American adults and teens reported having serious thoughts of suicide in 2022. While suicide prevention has primarily focused on suicide deaths and attempts, we contend that suicidal ideation (SI) deserves more in-depth investigation and should be an essential intervention target on its own. In support of this point, we provide three examples of ways to improve specificity in understanding of SI through the study of controllability of SI, the language used to assess SI, and measuring SI in real time. We also consider qualitative work on the content of SI, its treatment, and definitional considerations. We thus call for an increased general focus on SI within research, clinical care, and policy.

Consumer brand and category switching behaviors after food safety incidents: Factors and mechanisms.

The excessive mold found in Three Squirrels' nuts and the clenbuterol abuse of Shuanghui are two infamous food safety incidents in China. We adopted push-pull-mooring theory to conduct a model and examined the factors influencing consumer short-term or long-term brand-switching or category-switching behaviors following the two food safety incidents. We employed multinomial logistic regression and structural equation modeling as tools to analyze 1027 valid questionnaires. The results, for the first time, revealed that perceived risk, alternative selectivity, alternative attractiveness, controllability attribution, and habits were key push, pull and mooring factors influencing Chinese consumers' brand and category switching from food brands under food safety crisis, and most importantly, that their influential paths differed greatly under the two food safety incidents, suggesting a different influential mechanism across two product categories (i.e., utilitarian food and hedonic food). These findings throw light on the predictors and mechanisms that affect consumer brand and category switching from food brands under food safety crisis and help associated food businesses develop more targeted and powerful crisis management and public relations strategies.

The control patterns of affective processing and cognitive reappraisal: insights from brain controllability analysis.

Perceiving and modulating emotions is vital for cognitive function and is often impaired in neuropsychiatric conditions. Current tools for evaluating emotional dysregulation suffer from subjectivity and lack of precision, especially when it comes to understanding emotion from a regulatory or control-based perspective. To address these limitations, this study leverages an advanced methodology known as functional brain controllability analysis. We simultaneously recorded electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) data from 17 healthy subjects engaged in emotion processing and regulation tasks. We then employed a novel EEG/fMRI integration technique to reconstruct cortical activity in a high spatiotemporal resolution manner. Subsequently, we conducted functional brain controllability analysis to explore the neural network control patterns underlying different emotion conditions. Our findings demonstrated that the dorsolateral and ventrolateral prefrontal cortex exhibited increased controllability during the processing and regulation of negative emotions compared to processing of neutral emotion. Besides, the anterior cingulate cortex was notably more active in managing negative emotion than in either controlling neutral emotion or regulating negative emotion. Finally, the posterior parietal cortex emerged as a central network controller for the regulation of negative emotion. This study offers valuable insights into the cortical control mechanisms that support emotion perception and regulation.

Polarization-dependent photoinduced metal-insulator transitions in manganites.

In correlated oxides, collaborative manipulation on light intensity, wavelength, pulse duration and polarization has yielded many exotic discoveries, such as phase transitions and novel quantum states. In view of potential optoelectronic applications, tailoring long-lived static properties by light-induced effects is highly desirable. So far, the polarization state of light has rarely been reported as a control parameter for this purpose. Here, we report polarization-dependent metal-to-insulator transition (MIT) in phase-separated manganite thin films, introducing a new degree of freedom to control static MIT. Specifically, we observed giant photoinduced resistance jumps with striking features: (1) a single resistance jump occurs upon a linearly polarized light incident with a chosen polarization angle, and a second resistance jump occurs when the polarization angle changes; (2) the amplitude of the second resistance jump depends sensitively on the actual change of the polarization angles. Linear transmittance measurements reveal that the origin of the above phenomena is closely related to the coexistence of anisotropic micro-domains. Our results represent a first step to utilize light polarization as an active knob to manipulate static phase transitions, pointing towards new pathways for nonvolatile optoelectronic devices and sensors.