Aversive System Research Articles

자살 위기개입 상담사들의 실천 경험에 대한 질적 메타분석

Objectives This qualitative meta-analysis explored the practice experiences of suicide crisis intervention counselors and aimed to identify an action agenda. Methods The researchers used the CASP tool to select seven qualitative studies for analysis, which were then analyzed using the grounded theory synthesis method proposed by Eaves(2001). The purpose is to reanalyze qualitative research results with similar topics and identify the most important core themes to develop high-level core categories. Results The categories identified were “Client Avoidance,” “Practice Failure Zone,” “Struggling Without Support,” “Drifting Crisis Management Interventions,” “Counselor-Client Mutual Empowerment,” “Foundations for Deeper Client Understanding,” “Practicing as an Inclusionist,” and “Overcoming Limitations and Growing.” The core category found was “The client and counselor in the limited situation encouraged each other and grew as counselors by overcoming the limited situation through mutual growth.” Conclusions Based on the study findings, the researchers discussed the need for a manual for suicide crisis intervention, creating a safe environment for clients, establishing an aversive system for suicide crisis intervention, and providing ongoing education for counselors.

An Intelligent Crow Search Optimization and Bi-GRU for Forest Fire Detection System Using Internet of Things

Natural ecosystems have been facing a major threat due to deforestation and forest fires for the past decade. These environmental challenges have led to significant biodiversity loss, disruption of natural habitats, and adverse effects on climate change. The integration of Artificial Intelligence (AI) and Optimization techniques has made a revolutionary impact in disaster management, offering new avenues for early detection and prevention strategies. Therefore, to prevent the outbreak of a forest fire, an efficient forest fire diagnosis and aversion system is needed. To address this problem, an IoT-based Artificial Intelligence (AI) technique for forest fire detection has been proposed. This system leverages the Internet of Things (IoT) to collect real-time data from various sensors deployed in forest areas, providing continuous monitoring and early warning capabilities. Several researchers have contributed different techniques to predict forest fires at various remote locations, highlighting the importance of innovative approaches in this field. The proposed work involves object detection, which is facilitated by EfficientDet, a state-of-the-art object detection model known for its accuracy and efficiency. EfficientDet enables the system to accurately identify potential fire outbreaks by analyzing visual data from the sensors. To facilitate efficient detection at the outbreak of forest fires, a bi-directional gated recurrent neural network (Bi-GRU-NN) is needed. This neural network architecture is capable of processing sequential data from multiple directions, enhancing the system’s ability to predict the spread and intensity of fires. Crow Search Optimization (CSO) and fractional calculus are used to create an optimal solution in the proposed crow search fractional calculus optimization (CSFCO) algorithm for deep learning. CSO is inspired by the intelligent foraging behavior of crows, and when combined with fractional calculus, it provides a robust optimization framework that improves the accuracy and efficiency of the AI model. Experimental analysis shows that the proposed technique outperformed the other existing traditional approaches with an accuracy of 99.32% and an error rate of 0.12%. These results demonstrate the effectiveness of the integrated AI and optimization techniques in enhancing forest fire detection and prevention. The high accuracy and low error rate underscore the potential of this system to be a valuable tool in mitigating the risks associated with forest fires, ultimately contributing to the preservation of natural ecosystems.

Modulating reward and aversion: Insights into addiction from the paraventricular nucleus.

Drug addiction, characterized by compulsive drug use and high relapse rates, arises from complex interactions between reward and aversion systems in the brain. The paraventricular nucleus (PVN), located in the anterior hypothalamus, serves as a neuroendocrine center and is a key component of the hypothalamic-pituitary-adrenal axis. This review aimed to explore how the PVN impacts reward and aversion in drug addiction through stress responses and emotional regulation and to evaluate the potential of PVN as a therapeutic target for drug addiction. We review the current literature, focusing on three main neuron types in the PVN-corticotropin-releasing factor, oxytocin, and arginine vasopressin neurons-as well as other related neurons, to understand their roles in modulating addiction. Existing studies highlight the PVN as a key mediator in addiction, playing a dual role in reward and aversion systems. These findings are crucial for understanding addiction mechanisms and developing targeted therapies. The role of PVN in stress response and emotional regulation suggests its potential as a therapeutic target in drug addiction, offering new insights for addiction treatment.

Flexible microelectrode array probe for simultaneous detection of neural discharge and dopamine in striatum of mice aversion system

Simultaneous detection of spike firing and neurotransmitters in mice is conducive to further understanding the mechanism of innate fear induced by aversive stimuli. As the key brain region of the dopamine aversion system, the synchronous changes of neural discharge and neurotransmitter concentration in the striatum under innate fear are less studied. This paper proposed a fabrication method for dual-mode high-sensitive flexible microelectrode array (MEA) probe based on Parylene. The microelectrode sites were modified with platinum black nanoparticles and conductive polymer PEDOT, which can realize single neuron action potential recording and dopamine concentration detection. The electrode sensitivity for dopamine detection can reach 162.3 pA/μM. We used this flexible MEA probe to simultaneously real-time detect electrophysiology activities and dopamine in the striatum of awake mice under aversive stimulation. The results showed that after fear, with the decrease of the mean activity of mice behavior, the action potential firing rate, local field potential (LFP) power in low-frequency (0–30 Hz), and dopamine concentration in the striatum of mice decreased synchronously. The spike firing rate decreased by about 32 %, and the dopamine concentration decreased by about 23.5 %. Our electrodes provide a powerful tool for multimodal neural information detection and our research provides new evidence for striatum involvement in the dopamine aversion system.

Neural circuits provide insights into reward and aversion.

Maladaptive changes in the neural circuits associated with reward and aversion result in some common symptoms, such as drug addiction, anxiety, and depression. Historically, the study of these circuits has been hampered by technical limitations. In recent years, however, much progress has been made in understanding the neural mechanisms of reward and aversion owing to the development of technologies such as cell type-specific electrophysiology, neuronal tracing, and behavioral manipulation based on optogenetics. The aim of this paper is to summarize the latest findings on the mechanisms of the neural circuits associated with reward and aversion in a review of previous studies with a focus on the ventral tegmental area (VTA), nucleus accumbens (NAc), and basal forebrain (BF). These findings may inform efforts to prevent and treat mental illnesses associated with dysfunctions of the brain's reward and aversion system.

Does Sequence Matter?

Abstract: This study examined the role of motivation in processing sequentially coactive content (i.e., positive leading to negative or the reverse). A motivational inhibition hypothesis was proposed to predict the processing of sequentially coactive content as a function of changes in arousing content. Results provided evidence in support of the mutual inhibitory effects between the appetitive and aversive systems during sequential coactivation and further revealed the role of change in arousing content in resource allocation during different patterns of motivational inhibition. Theoretically, this study extended previous work in offering a clarification on the boundary conditions governing the effect of proposed motivational inhibition when processing sequentially coactive content.

Financial Risk Avoidance Based on the Sensor Network and Edge Computing

In order to improve the effect of financial risk aversion, this paper studies the financial risk aversion system combined with the edge computing method of the sensor network and proposes a sensor data anomaly detection algorithm based on the offset distance. Moreover, this paper divides the sensor data into several sliding windows according to the time series, analyzes the offset between the data object and other data in the sliding window by calculating the offset distance, and uses the abnormal level to indicate the possibility of data abnormality. In addition, this paper analyzes the single-layer linear network model for the data with high abnormal level and constructs a financial risk aversion model based on the edge computing of the sensor network. The simulation test results show that the financial risk aversion model based on sensor network and edge computing proposed in this paper meets the actual needs of financial risk analysis.

Emotional Assessment in Spanish Youths With Antisocial Behavior.

Impaired emotional capacity in antisocial populations is a well-known reality. Taking the dimensional approach to the study of emotion, emotions are perceived as a disposition to action; they emerge from arousal of the appetitive or aversive system, and result in subjective, behavioral, and physiological responses that are modulated by the dimensions of valence, arousal, and dominance. This study uses the International Affective Picture System (IAPS) to study the interaction between the type of picture presented (pleasant, neutral, or unpleasant) and group (adolescents under custody in juvenile justice centers, adolescents under non-custodial measures, and secondary school students) in the emotional assessment of these dimensions. The interaction between the study variables was statistically significant. Statistically significant differences were found between the three types of pictures presented, in the ratings of unpleasant pictures between the custody group and the group of secondary students in regular schooling in valence, and in the ratings of unpleasant, neutral, and pleasant pictures in arousal, between the custody group and all groups. Discriminant analyses of each affective dimension indicate that the unpleasant pictures with violent and/or aggressive content tend to be in the functions that most differentiate the antisocial groups.

Self Psychology and Aggression — Reflections on Aversive Experience, Culture, and Building Developmental Capabilities

ABSTRACT From the beginning, self psychology has been criticized for failing to adequately address aggression. This critique is explored beginning with Heinz Kohut’s position on aggression and then moving to discuss Joseph Lichtenberg’s proposals concerning aggression and aversiveness, the aversive motivational system. In a number of clinical vignettes, the process of developing new, adaptive developmental capacities in the aversive motivational system are described. Additionally, a focus on diversity, culture, and bias which spontaneously became activated between the analytic partners is included.

Low frequency deep brain stimulation in the inferior colliculus ameliorates haloperidol-induced catalepsy and reduces anxiety in rats.

Deep brain stimulation (DBS) of the colliculus inferior (IC) improves haloperidol-induced catalepsy and induces paradoxal kinesia in rats. Since the IC is part of the brain aversive system, DBS of this structure has long been related to aversive behavior in rats limiting its clinical use. This study aimed to improve intracollicular DBS parameters in order to avoid anxiogenic side effects while preserving motor improvements in rats. Catalepsy was induced by systemic haloperidol (0.5mg/kg) and after 60 min the bar test was performed during which a given rat received continuous (5 min, with or without pre-stimulation) or intermittent (5 x 1 min) DBS (30Hz, 200–600μA, pulse width 100μs). Only continuous DBS with pre-stimulation reduced catalepsy time. The rats were also submitted to the elevated plus maze (EPM) test and received either continuous stimulation with or without pre-stimulation, or sham treatment. Only rats receiving continuous DBS with pre-stimulation increased the time spent and the number of entries into the open arms of the EPM suggesting an anxiolytic effect. The present intracollicular DBS parameters induced motor improvements without any evidence of aversive behavior, pointing to the IC as an alternative DBS target to induce paradoxical kinesia improving motor deficits in parkinsonian patients.

196-LB: Synergetic and Distinct Roles in the Control of Food Intake and Energy Balance for Subpopulations of NTS Neurons

To understand hindbrain pathways involved in the control of food intake, we initially defined markers for distinct subsets of nucleus tractus solitarius (NTS) neurons that respond to food intake, including those that express calcitonin receptor (Calcr), leptin receptor (LepRb), or cholecystokinin (CCK). While the chemogenetic activation of each of these NTS populations decreased short- and long-term food intake and body weight, only CCKNTS cells activated aversive CGRP-containing neurons of the parabrachial nucleus (CGRPPBN cells) and promoted a conditioned taste aversion. Indeed, the combined activation of CalcrNTS+LepRbNTS (LCNTS) cells provoked a stronger and more durable suppression of food intake and body weight than any single population but failed to promote aversive responses. Thus, while CCKNTS cells provoke aversive anorexia, CalcrNTS and LepRbNTS cells cooperatively suppress food intake without engaging aversive systems. To understand the roles for these NTS neurons in the physiologic control of food intake and energy balance, we chronically silenced them and examined food intake and energy balance. We found that silencing any single NTS population not only interfered with the response to gut peptide-mimetics, but also increased food intake and body weight, and that high-calorie food accentuated this effect. Additionally, simultaneously silencing multiple populations further increased food intake and body weight, promoting greater adiposity. These findings not only reveal the importance of both aversive and non-aversive brainstem circuits for the control of long-term energy balance, but also identify multiple synergistic hindbrain circuits that non-aversively suppress feeding. These non-aversive systems represent ideal targets for the potential treatment of obesity and associated metabolic diseases. Disclosure W.C. Cheng: None. E. Ndoka: None. B. Maerz: None. K.J. Roelofs: None. C.J. Rhodes: Employee; Self; AstraZeneca. R.J. Seeley: Consultant; Self; Ionis Pharmaceuticals, Inc., Kintai, Kintai, Novo Nordisk A/S, Sanofi, Scohia Pharma Inc. Research Support; Self; AstraZeneca, Novo Nordisk A/S, Pfizer Inc. Stock/Shareholder; Self; Redesign Health. D.A. Sandoval: Research Support; Self; MedImmune, Novo Nordisk A/S. D. Olson: Research Support; Self; MedImmune, Inc, Novo Nordisk A/S. M.G. Myers: Research Support; Self; AstraZeneca, Novo Nordisk Inc. Funding American Diabetes Association (1-16-PDF-021 to W.C.C.)

Calcitonin Receptor Neurons in the Mouse Nucleus Tractus Solitarius Control Energy Balance via the Non-aversive Suppression of Feeding

SummaryTo understand hindbrain pathways involved in the control of food intake, we examined roles for calcitonin receptor (CALCR)-containing neurons in the NTS. Ablation of NTS Calcr abrogated the long-term suppression of food intake, but not aversive responses, by CALCR agonists. Similarly, activating CalcrNTS neurons decreased food intake and body weight but (unlike neighboring CckNTS cells) failed to promote aversion, revealing that CalcrNTS neurons mediate a non-aversive suppression of food intake. While both CalcrNTS and CckNTS neurons decreased feeding via projections to the PBN, CckNTS cells activated aversive CGRPPBN cells while CalcrNTS cells activated distinct non-CGRP PBN cells. Hence, CalcrNTS cells suppress feeding via non-aversive, non-CGRP PBN targets. Additionally, silencing CalcrNTS cells blunted food intake suppression by gut peptides and nutrients, increasing food intake and promoting obesity. Hence, CalcrNTS neurons define a hindbrain system that participates in physiological energy balance and suppresses food intake without activating aversive systems.

SECURING NETWORK THROUGH HONEYPOT AND ITS IMPLEMENTATION

PCs and data innovation (IT) reformed the world and developing day by day. Computer systems empower us to speak with remote PC system and access assets successfully and productively. Yet, these systems are not verify it's inclined to interruption, dangers and assaults. Presently a days ventures use Intrusion identification framework (IDS) and Intrusion aversion framework (IPS) to screen the framework or a system for assaults, interruption or threats& keep the framework or system from such vulnerabilities. Anyway IDS/IPS is over the top expensive and complex to be executed on your IT frameworks. It isn't feasible for little scale enterprises to actualize such systems, thus a model of cutting edge imitation based innovation called honeypot is proposed as an answer for little scale ventures. Today honeypot is broadly utilized by such ventures close to that honeypot is likewise valuable for huge scale enterprises in improving their interruption and aversion systems. But customarily honeypot is seen as trickiness system & not as an interruption location or avoidance innovation additionally a large portion of the honeypot is worked for Linux/Unix based working frameworks on account of the way that these working frameworks are publicly released systems. Most of the time honeypots are utilized in the virtualized condition and they normally invigorate counterfeit framework to catch organize bundles which are utilized later to analyze them disconnected for any dangers and intrusions. This paper proposes new structure &methodology that actualizes IDS and IPS inside the honeypot with real time arrange parcel catching &intrusions recognition alongside implanted firewall for interruption prevention, which make the proposed honeypot more successful and effective than existing honeypots. The objective of this paper is to propose and structure a convenient java based continuous bundle catching with interruption identification and prevention honeypot for windows based working framework. This honeypot is planned remembering Research honeypots however it very well may be utilized in virtualized condition moreover.

Social status and demographic effects of the kappa opioid receptor: a PET imaging study with a novel agonist radiotracer in healthy volunteers.

Kappa opioid receptors (KORs) have been characterized as an aversive system in the brain and implicated in social behavior in preclinical models. This work investigated the effect of social status on the KOR system in humans using positron emission tomography (PET) imaging with the novel KOR agonist radiotracer [11C]EKAP. Eighteen healthy participants (mean age 41.2 ± 9.3) completed the Barratt Simplified Measure of Social Status (BSMSS), an MRI and an [11C]EKAP PET scan on the High Resolution Research Tomograph. Arterial blood sampling and metabolite analysis were conducted to obtain the input function. Regions of interest were based upon an MR template and included the reward/aversion areas of the brain. The multilinear analysis-1 (MA1) method was applied to the regional time-activity curves (TACs) to calculate [11C]EKAP regional volume of distribution (VT). Mixed models and Pearson correlation coefficients were used for body mass index (BMI), gender and age, with age being dropped in subsequent analyses because of nonsignificance. An overall effect of primary ROIs (F7, 112 7.43, p < 0.0001), BSMSS score (F1, 13 7.45, p = 0.02), BMI (F1, 13 23.5, p < 0.001), and gender (F1, 13 23.75, p < 0.001), but not age (F1, 13 1.12, p = 0.35) was observed. Regional [11C]EKAP VT and BSMSS were found to be negatively correlated in the amygdala (r = -0.69, p < 0.01), anterior cingulate cortex (r = -0.56, p = 0.02), caudate (r = -0.66, p < 0.01), frontal cortex (r = -0.52, p = 0.04), hippocampus (r = -0.60, p = 0.01), pallidum (r = -0.59, p = 0.02), putamen (r = -0.62, p = 0.01), and ventral striatum (r = -0.66, p < 0.01). In secondary (non-reward) regions, correlations of [11C]EKAP VT and BSMSS were nonsignificant with the exception of the insula. There was an inverse correlation between social status and KOR levels that was largely specific to the reward/aversion (e.g., saliency) areas of the brain. This finding suggests the KOR system may act as a mediator for the negative effects of social behaviors in humans.

Modeling Emotions Associated With Novelty at Variable Uncertainty Levels: A Bayesian Approach.

Acceptance of novelty depends on the receiver's emotional state. This paper proposes a novel mathematical model for predicting emotions elicited by the novelty of an event under different conditions. It models two emotion dimensions, arousal and valence, and considers different uncertainty levels. A state transition from before experiencing an event to afterwards is assumed, and a Bayesian model estimates a posterior distribution as being proportional to the product of a prior distribution and a likelihood function. Our model uses Kullback-Leibler divergence of the posterior from the prior, which we termed information gain, to represent arousal levels because it corresponds to surprise, a high-arousal emotion, upon experiencing a novel event. Based on Berlyne's hedonic function, we formalized valence as a summation of reward and aversion systems that are modeled as sigmoid functions of information gain. We derived information gain as a function of prediction errors (i.e., differences between the mean of the posterior and the peak likelihood), uncertainty (i.e., variance of the prior that is proportional to prior entropy), and noise (i.e., variance of the likelihood function). This functional model predicted an interaction effect of prediction errors and uncertainty on information gain, which we termed the arousal crossover effect. This effect means that the greater the uncertainty, the greater the information gain for a small prediction error. However, for large prediction errors, greater uncertainty means a smaller information gain. To verify this effect, we conducted an experiment with participants who watched short videos in which different percussion instruments were played. We varied uncertainty levels by using familiar and unfamiliar instruments, and we varied prediction error magnitudes by including congruent or incongruent percussive sounds in the videos. Event-related potential P300 amplitudes and subjective reports of surprise in response to the percussive sounds were used as measures of arousal levels, and the findings supported the hypothesized arousal crossover effect. The concordance between our model's predictions and our experimental results suggests that Bayesian information gain can be decomposed into uncertainty and prediction errors and is a valid measure of emotional arousal. Our model's predictions of arousal may help identify positively accepted novelty.

Disgust sensitivity is associated with heightened risk perception

Disgust is a versatile emotion that is not only elicited by threats to one’s physical health but that has also recently been linked to social and especially moral concerns. Building on the hypothesis that disgust can be seen as part of a broader loss aversion system, four studies demonstrate that disgust sensitivity is linked to heightened risk perception. A preliminary study and Study 1 established a moderate correlation of disgust sensitivity with risk perception. Studies 2 and 3 confirmed the effect while controlling for potential affective influences, including current mood, or trait anxiety, respectively. Importantly, we find that the correlation is also independent of gender and age, and that disgust sensitivity is associated with a broad range of risk domains, including recreational, social, ethical, financial, and health and safety risks. Therefore, disgust may be part of a general risk aversion mechanism aimed at guiding behavior in uncertain situations.

Sensory ecology of ostariophysan alarm substances.

Chemical communication of predation risk has evolved multiple times in fish species, with conspecific alarm substance (CAS) being the most well understood mechanism. CAS is released after epithelial damage, usually when prey fish are captured by a predator and elicits neurobehavioural adjustments in conspecifics which increase the probability of avoiding predation. As such, CAS is a partial predator stimulus, eliciting risk assessment-like and avoidance behaviours and disrupting the predation sequence. The present paper reviews the distribution and putative composition of CAS in fish and presents a model for the neural processing of these structures by the olfactory and the brain aversive systems. Applications of CAS in the behavioural neurosciences and neuropharmacology are also presented, exploiting the potential of model fish [e.g., zebrafish Danio rerio, guppies Poecilia reticulata, minnows Phoxinus phoxinus) in neurobehavioural research.

Understanding the role of dopamine in conditioned and unconditioned fear.

Pharmacological and molecular imaging studies in anxiety disorders have primarily focused on the serotonin system. In the meantime, dopamine has been known as the neurotransmitter of reward for 60 years, particularly for its action in the nervous terminals of the mesocorticolimbic system. Interest in the mediation by dopamine of the well-known brain aversion system has grown recently, particularly given recent evidence obtained on the role of D2 dopamine receptors in unconditioned fear. However, it has been established that excitation of the mesocorticolimbic pathway, originating from dopaminergic (DA) neurons from the ventral tegmental area (VTA), is relevant for the development of anxiety. Among the forebrain regions innervated by this pathway, the amygdala is an essential component of the neural circuitry of conditioned fear. Current findings indicate that the dopamine D2 receptor-signaling pathway connecting the VTA to the basolateral amygdala modulates fear and anxiety, whereas neural circuits in the midbrain tectum underlie the expression of innate fear. The A13 nucleus of the zona incerta is proposed as the origin of these DA neurons projecting to caudal structures of the brain aversion system. In this article we review data obtained in studies showing that DA receptor-mediated mechanisms on ascending or descending DA pathways play opposing roles in fear/anxiety processes. Dopamine appears to mediate conditioned fear by acting at rostral levels of the brain and regulate unconditioned fear at the midbrain level.

Obstructing the cascade: motivational system coactivation dampening defensive reactions to threat and disgust

ABSTRACTThis study uses the limited capacity model of motivated mediated message processing (LC4MP; Lang, 2006) as a framework to study coactivation of fundamental motivational systems elicited by common message features in antismoking public service announcements (PSAs): the appetitive system (elicited by smoking cues) and aversive system (elicited by perceived threat and disgust). Specific predictions were made for smoking cues’ ability to provide cognitive resources for message encoding when simultaneous message elements are so highly aversive they begin to deplete resources (i.e., during a defensive cascade). The results showed that greater resources were expended on encoding headlines as indicated by increased attention (i.e., gaze duration and frequency of fixation) and better free recall, but not noncue pictorial elements when smoking cues were present in PSAs high in perceived disgust. Although the inclusion of smoking cues was effective in highly aversive PSAs, results indicated that the inclusion of smoking cues reduced attention and free recall for moderately and low-aversive PSAs. Theoretical advances include the use of motivational coactivation to reduce defensive reactions and the differential allocation impact on text versus visual message elements. Applied implications highlight the importance of formative production research to ensure aversive activation is high enough to offset urges associated with smoking cues.

Smart Devices Threats, Vulnerabilities and Malware Detection Approaches: A Survey

In recent times, malware detection mechanism systems of mobile smart devices are getting growing concentration from researchers. With the quick expansion of malwares found in mobile devices, preventing the secrecy of mobile users is incredibly imperative and necessary. Intrusion detection systems are programming devices that consequently assemble information, dissect it and recognize such occurrences. These systems advanced to intrusion aversion systems (IPS) including extra counteractive action capacities. In Intrusion detection systems, accuracy rate plays a significant role in measuring the effectiveness of an approach. One of the motivations of this study is to increase the true positive as well as reducing the false-positive rates beyond other studies.