Cognitive Systems Research Articles

Implementation of automated cognitive testing systems for socially housed rhesus (Macaca mulatta) and squirrel (Saimiri spp.) monkeys: Age differences in learning.

Utilizing Automated Cognitive Testing Systems (ACTS) with group-housed nonhuman primates offers a number of advantages over manual testing and computerized testing of singly housed subjects. To date, ACTS usage has been limited to great apes or African monkeys. Here, we detail what we have learned while implementing ACTS with socially housed squirrel monkeys and rhesus macaques and provide information about the training process. In addition, we examined the effects of age on learning acquisition. We found age differences in learning for both squirrel monkeys and rhesus monkeys. Older monkeys were not as proficient as younger monkeys on learning to use the touch screens (squirrel monkeys only), discrimination learning (rhesus monkeys only; note: squirrel monkeys were not trained to criterion on this task), and recognition learning (both species). Overall, ACTS provide a number of advantages for studying cognition in socially living nonhuman primates and can be used to further investigate cognitive decline whether related to natural aging processes or disease pathology. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Harmonising humans and technology: Exploring the dynamics of cognitive production, artificial intelligence and social communication in cybernetic systems

Agile cognitive production systems mark a manufacturing paradigm shift, propelled by the demand for accelerated product development and the adoption of digitalised production systems across extensive supply networks. Cognitive manufacturing emphasises the role of technology and automation in the learning and adaptation process. These systems independently analyse data, make real-time adjustments and optimise processes, sometimes minimising the need for human intervention. Based on a conceptual framework that draws on the diversity of living systems and cognitive processes, cybernetics provides a solid theoretical background. It explores the intricate connections between cognition, self-organising systems and the challenges arising from the autonomy of such systems. The concept of "cognition" in "agile cognitive systems" moves away from the conventional understanding of purely technical processes and towards human thought processes. This departure fosters a dynamic exchange where individual thoughts resonate in social communication. Addressing the role of artificial intelligence (AI), the article emphasises examining computers from a social science standpoint, exploring the relationship between computers and mental systems, capturing human faculties such as cognition, utterance, and understanding. The integration of AI into computer-mediated communication leads to the question how AI-equipped computers intersect with societal intelligence notions. The inherent intransparency of AI, often viewed as a black box, prompts queries about the potential black-box nature of an autonomously controlled AI factory or supply chain. In this hypothetical scenario, the idea of the supply chain as a communication network is challenged, emphasising the importance of human involvement. Research on human-centric cognitive production emphasises explainable AI and human-in-the-loop. This orientation goes beyond the technical dimensions and incorporates social science considerations, which emphasises the holistic nature of current research. In essence, research in the field of cognitive production is a comprehensive exploration of the complex interplay between human cognition, artificial intelligence and the evolving landscape of modern production systems.

Analysis of delays in medium access control devices in cognitive radio systems with correlation of time intervals in request flows

This article is about the development of a method for analyzing the average waiting time of a request in a queue with correlated inter-arrival and service times. The ON-OFF process is often used to model the primary user channel occupancy in different questions related to cognitive radio, such as resource allocation, medium access control protocols, spectrum handoff and others. It is assumed that the time intervals of the ON- and OFF- periods are not correlated. More realistic models of primary user activity require the presence of correlation not only between consequent periods, but also the presence of correlation between channel occupancy and other quantities interpreted as service time in models based on queuing systems. As a result, here is proposed a variant of constructing the probability density function of a random variable which is the difference between the service time of the i-th request and the time interval between the moments of arriving of the i-th and (i-1)-th requests with correlated inter-arrival and service times. Solution based on the use of a two-dimensional characteristic function, so in this case it is possible to more purposefully specify the components of the statistical connection of previously described sequences. These components are the cumulants of the described distribution. For a queuing system with hyperexponential distribution of inter-arrival and service intervals, an analytical expression for the average waiting time of a request in a queue is found.

Cortical and subcortical substrates of working memory in the right hemisphere: A connectome-based lesion-symptom mapping study

Working Memory (WM) is a cognitive system whose crucial role is to temporarily hold and manipulate information. Early studies suggest that verbal WM is typically associated with left hemisphere (LH) brain regions, while the processing of visuospatial information in WM more specifically depends on the right hemisphere (RH). However, recent evidence suggests a more complex network involving both hemispheres' prefrontal and posterior parietal cortices in these processes. Unfortunately, previous lesion studies often examined only one modality (either verbal, or visuospatial) or one hemisphere, which limits the possible conclusions regarding non-lateralized hemispheric involvement. Using connectome-based lesion-symptom mapping on a large sample of patients with left (LBD) and right (RBD) focal brain damage, we examined whether gray matter damage and white matter disconnections predict deficits of WM updating in an N-back task. Patients were examined with two WM tasks that differed regarding modality (verbal, spatial) and cognitive load (1-back, 2-back). Behavioral outcomes indicated that RBD patients showed significant deficits in WM updating, regardless of task modality or load. This observation was supported by whole-brain voxel-based analysis, revealing associations between WM deficits and gray matter clusters in the RH. Specifically, damage to the right lateral frontal cortex including the brain region homologous to Broca's area was associated with verbal WM deficits, while damage to the right inferior parietal lobe and posterior temporal cortex predicted spatial WM deficits. Additionally, white matter analyses identified severely impacted tracts in the RH, predicting deficits in both verbal and spatial WM. Our findings suggest that the mental manipulation of both verbal and visuospatial information in WM updating relies on the integrity of the RH, irrespective of the specific type of information held in mind.

Understanding the relationships among adolescents’ internet dependence, reward, cognitive control processing, and learning burnout: a network perspective in China

Alterations in the reward and cognitive control systems are commonly observed among adolescents with internet dependence (ID), and this impairment is often accompanied by social dysfunctions, such as academic burnout. However, the intercorrelations among ID, reward, cognitive control processing, and learning burnout remain unclear. We recruited 1074 Chinese adolescents to investigate the complex interrelationships among these variables using network analysis. The resulting network revealed patterns that connected ID to the behavioral inhibition/activation system (BIS/BAS), self-control, and learning burnout; these results exhibited reasonable stability and test–retest consistency. Throughout the network, the node of BAS-drive was the critical influencing factor, and the node of self-control was the protection factor. In addition, several symptoms of learning burnout and ID were positively associated with sensitivity to punishment. As revealed by the network comparison test, the network constructed among internet dependent (ID) group differed from the network constructed among internet nondependent (IND) group not only in the edges between BIS and learning burnout but also in terms of the edges associated with learning burnout. In conclusion, this study provides insights into the complex mechanisms underlying ID among adolescents from the perspective of the network relationships between core influencing factors and negative consequences. It validates the dual-system model of risky behavior among adolescents and offers a foundation for early warning and interventions for ID in this context.

A smart system for student performance assessment (SPA)

The proposed smart system for Student Performance Assessment (SPA) is a system that evaluates students' knowledge and skill attainment in a specific course by measuring their achievements of the Course Learning Outcomes (CLOs). The instructor defines the aspects, weights, and rating scale used by SPA to analyze each course. The system calculates the average of students' marks in each learning outcome and compares them with the CLO targets and scores to determine the effectiveness of the teaching and learning methods used. The system uses facts and rules extracted from the course syllabus and Bloom's Taxonomy to build its knowledge base. This paper presents the development of the SPA inference engine, which is used to find CLO targets based on the course level. The inference engine uses efficient procedures and a prediction process to determine the correct target and score, providing a reliable and understandable methodology for reasoning about the information in the knowledge base and formulating conclusions. SPA is a highly responsive and intelligent system that can be a valuable tool for measuring students' achievements. Its characteristics include high performance, reliability, and intelligibility, and its combination of cognitive systems and cognitive theory has led to remarkable progress in measuring student performance. Limitations include dependency on accurate course content and initial setup time, potential bias in CLO weight assignments, challenges in integrating SPA with existing institutional databases, the need for continuous updates to the knowledge base to reflect curriculum changes, and potential resistance from educators to adopt new technologies. Future improvements could involve adaptive learning integrations, enhanced user interfaces, and broader applicability across diverse educational settings.

Functional connectivity of the pediatric brain.

This review highlights the importance of functional connectivity in pediatric neuroscience, focusing on its role in understanding neurodevelopment and potential applications in clinical practice. It discusses various techniques for analyzing brain connectivity and their implications for clinical interventions in neurodevelopmental disorders. The principles and applications of independent component analysis and seed-based connectivity analysis in pediatric brain studies are outlined. Additionally, the use of graph analysis to enhance understanding of network organization and topology is reviewed, providing a comprehensive overview of connectivity methods across developmental stages, from fetuses to adolescents. Findings from the reviewed studies reveal that functional connectivity research has uncovered significant insights into the early formation of brain circuits in fetuses and neonates, particularly the prenatal origins of cognitive and sensory systems. Longitudinal research across childhood and adolescence demonstrates dynamic changes in brain connectivity, identifying critical periods of development and maturation that are essential for understanding neurodevelopmental trajectories and disorders. Functional connectivity methods are crucial for advancing pediatric neuroscience. Techniques such as independent component analysis, seed-based connectivity analysis, and graph analysis offer valuable perspectives on brain development, creating new opportunities for early diagnosis and targeted interventions in neurodevelopmental disorders, thereby paving the way for personalized therapeutic strategies.

The impact of anger on intertemporal decision-making in individuals with internet addiction: an fNIRS study.

Intertemporal decision-making is the choice between an immediate smaller reward (SS) and a delayed larger reward (LL). Intertemporal decision-making depends on the interaction of the cognitive and emotional systems, and the latter is particularly vital. According to the Appraisal Tendency Frame (ATF) theory, anger influences intertemporal decision-making by increasing an individual's sense of certainty and control. This study examined whether anger affects intertemporal decision-making in individuals with internet addiction (IA) in this manner and investigated its neural mechanisms. Nineteen individuals with IA and 20 healthy controls were recruited. All subjects performed the Monetary choice task under anger and neutral emotions while functional near-infrared spectroscopy (fNIRS) equipment simultaneously recorded the hemodynamics in the prefrontal cortex (PFC). Individuals with IA showed a more considerable delay discount and lower brain activations in the orbitofrontal cortex (OFC) and left dorsolateral prefrontal cortex (L-dlPFC) compared to HC. Moreover, individuals with IA made more LL choices in the angry condition than in the neutral emotion, yet there was no difference in HC. The brain activation in L-dlPFC of individuals with IA tends to increase in the angry condition compared to the neutral condition. These findings revealed that impairment of intertemporal decision-making in individuals with individuals with IA might be related to the dysfunction of OFC and L-dlPFC. Our work also provided initial footing for the applicability of the appraisal tendency frame theory to individuals with IA, and L-dlPFC might play a role in the effects of anger on intertemporal decision-making.

Exploring Cognitive Skills and Academic Outcomes of Poverty-Affected English Language Learners in Indian Primary Schools

This study investigates the cognitive performance of primary school children in India who are English Language Learners (ELL) and live in poverty. Cognitive performance was assessed using the Das-Naglieri Cognitive Assessment System (CAS2 was not constructed). There is a scarcity of studies on participants who are both ELL and live in poverty, and many such children are often found to be intellectually deficient. This study examines the performance in PASS measures (Planning, Attention, Simultaneous, Successive) and their correlation with academic achievement, particularly in reading and mathematics. We assessed the performance of 80 primary school students residing in slum areas (mean age: 9.8 years), matched in age and grade with 70 regular school students from areas outside the slum (mean age: 9.11 years). It was hypothesized that ELL regular school students would exhibit average Das-Naglieri CAS scores as per established American norms.

Childhood Trauma Questionnaire-based child maltreatment profiles to predict efficacy of the Cognitive Behavioral Analysis System of Psychotherapy versus non-specific psychotherapy in adults with early-onset chronic depression: cluster analysis of data from a randomised controlled trial

Child maltreatment is a broadly confirmed risk factor for mental and physical illness. Some psychological treatments specifically target mental health conditions associated with child maltreatment. For example, the Cognitive Behavioral Analysis System of Psychotherapy (CBASP) focuses on maladaptive interpersonal behaviours in chronic depression. However, how the assessment of child maltreatment could inform personalised treatment is unclear. We used data from a previously published clinical trial to investigate whether a pre-established child maltreatment clustering approach predicts differential outcomes after CBASP versus non-specific supportive psychotherapy in patients with early-onset chronic depression. We did a cluster analysis of data from a previous randomised controlled trial of unmedicated adult outpatients with early-onset chronic depression who were treated at eight university clinics and psychological institutes in Germany with 32 sessions of CBASP or non-specific supportive psychotherapy. Participants were eligible for the original trial if they were aged 18-65 years; had major depressive disorder (MDD) with an early onset and duration of at least 2 years, current MDD superimposed on a pre-existing dysthymic disorder, or recurrent MDD with incomplete remission between episodes as defined by DSM-IV; and had a score of at least 20 points on the 24-item Hamilton Rating Scale for Depression (HRSD-24). Participants were included in the current study if they had completed the short form of the Childhood Trauma Questionnaire (CTQ) at trial baseline. We used an agglomerative hierarchical clustering approach to derive child maltreatment clusters from individual patterns across the five domains of the CTQ. We used linear mixed models to investigate whether clustering could predict differential clinical outcomes (change in symptom severity on the HRSD-24) up to 2 years after treatment onset. People with lived experience were involved in the current study. 253 patients (129 [51%] treated with CBASP and 124 [49%] with supportive psychotherapy) had complete CTQ records and were included in the analysis. 169 (67%) participants were women, 84 (33%) were men, and the mean age was 45·9 years (SD 11·7). We identified seven child maltreatment clusters and found significant differences in treatment effects of CBASP and supportive psychotherapy between the clusters (F(6,948·76)=2·47; p=0·023); differences were maintained over the 2-year follow-up. CBASP was superior in distinct clusters of co-occurring child maltreatment: predominant emotional neglect (change in β -6·02 [95% CI -11·9 to -0·13]; Cohen's d=-0·98 [95% CI -1·94 to -0·02]; p=0·045), predominant emotional neglect and abuse (-6·39 [-10·22 to -2·56]; -1·04 [-1·67 to -0·42]; p=0·0011), and emotional neglect and emotional and physical abuse (-9·41 [-15·91 to -2·91]; -1·54 [-2·6 to -0·47]; p=0·0046). CTQ-based cluster analysis can facilitate identification of patients with early-onset chronic depression who would specifically benefit from CBASP. Child maltreatment clusters could be implemented in clinical assessments and serve to develop and personalise trauma-informed care in mental health. The German Research Foundation and the German Federal Ministry of Education and Research.

The association between selenium status and global and attention-specific cognition in very old adults in the Newcastle 85+ Study: cross-sectional and longitudinal analyses

BackgroundSelenium has potential safeguarding properties against cognitive decline, because of its role in protecting DNA, proteins, and lipids in the brain from oxidative damage. However, acute and chronic overexposure to selenium can be neurotoxic. ObjectiveThe aim of this analysis was to explore the association between selenium status [serum selenium and selenoprotein P (SELENOP) concentrations and glutathione peroxidase 3 (GPx3) activity] and cognitive function in 85-y olds living in Northeast England at baseline and ≤5 y of follow-up. MethodsGlobal cognitive performance was assessed in 755 participants from the Newcastle 85+ study using the standardized Mini-Mental State Examination and attention-specific cognition was assessed using composite scores derived from the Cognitive Drug Research System. Serum selenium, SELENOP, and GPx3 activity were measured at baseline by total reflection X-ray fluorescence, enzyme-linked immunosorbent assay, and coupled-enzyme reaction, respectively. Regression analyses explored linear and nonlinear associations between continuous values and tertiles of selenium status biomarkers, respectively, and cognitive function at baseline. Generalized linear mixed models explored associations between continuous values and tertiles of selenium status biomarkers, and global cognitive decline over 5 y, and attention-specific cognitive decline over 3 y. ResultsOver 3 and 5 y, none of the selenium biomarkers were associated with the rate of cognitive decline. At baseline, in fully adjusted models, higher serum selenium was nonlinearly associated with global cognition (β = 0.05 ± 0.01, P = 0.387 linear, β = 0.04 ± 0.01, P = 0.002 nonlinear). SELENOP and GPx3 activity were not associated with any cognitive outcomes. ConclusionsThere were no associations between selenium status and cognitive decline. However, serum selenium, but not SELENOP or GPx3 activity, was positively associated nonlinearly with global cognition at baseline. Furthermore, these associations were not evident during follow-up, potentially because of residual confounding and reverse causation.

Stable construction and analysis of MDD modular networks based on multi-center EEG data

BackgroundThe modular structure can reflect the activity pattern of the brain, and exploring it may help us understand the pathogenesis of major depressive disorder (MDD). However, little is known about how to build a stable modular structure in MDD patients and how modules are separated and integrated. MethodWe used four independent resting state Electroencephalography (EEG) datasets. Different coupling methods, window lengths, and optimized community detection algorithms were used to find a reliable and robust modular structure, and the module differences of MDD were analyzed from the perspectives of global module attributes and local topology in multiple frequency bands. ResultsThe combination of the Phase Lag Index (PLI) and the Louvain algorithm can achieve better results and can achieve stability at smaller window lengths. Compared with Healthy Controls (HC), MDD had higher Modularity (Q) values and the number of modules in low-frequency bands. In addition, MDD showed significant structural changes in the frontal and parietal-occipital lobes, which were confirmed by further correlation analysis. ConclusionOur results provided a reliable validation of the modular structure construction method in MDD patients and contributed strong evidence for the changes in emotional cognition and visual system function in MDD patients from a new perspective. These results would afford valuable insights for further exploration of the pathogenesis of MDD.

On Meter and the Social Dynamics of Cueing in Bill Monroe’s “Muleskinner Blues”

“Muleskinner Blues,” the signature song of bluegrass patriarch Bill Monroe, is at once central to the bluegrass canon and yet metrically enigmatic, featuring a flexible timing structure that fluctuated wildly between performances. This article engages in a longitudinal study of 165 performances of “Muleskinner Blues” across Bill Monroe’s career to explore how the musicians that rotated through his band, the Blue Grass Boys, cognitively grappled with the song’s flexible structure. Through a series of analytical vignettes, I will detail the distributed cognitive system that drives performances of “Muleskinner Blues,” giving special attention to musical cues as tools for calling collective attention to structurally important moments of action. Additionally, I show how the song’s flexible meter was weaponized by Monroe in acts of musical hazing, antagonizing his musicians in the high-stakes environment of a live performance. Through these analyses, I show how the song’s peculiar meter centered Monroe musically, structurally, and socially, transforming “Muleskinner Blues” into a potent vehicle for the masculine ideology of the father of bluegrass music.

Structural covariation between cerebellum and neocortex intrinsic structural covariation links cerebellum subregions to the cerebral cortex.

The human cerebellum is increasingly recognized to be involved in nonmotor and higher-order cognitive functions. Yet, its ties with the entire cerebral cortex have not been holistically studied in a whole brain exploration with a unified analytical framework. Here, we characterized dissociable cortical-cerebellar structural covariation patterns based on regional gray matter volume (GMV) across the brain in n = 38,527 UK Biobank participants. Our results invigorate previous observations in that important shares of cortical-cerebellar structural covariation are described as 1) a dissociation between the higher-level cognitive system and lower-level sensorimotor system and 2) an anticorrelation between the visual-attention system and advanced associative networks within the cerebellum. We also discovered a novel pattern of ipsilateral, rather than contralateral, cerebral-cerebellar associations. Furthermore, phenome-wide association assays revealed key phenotypes, including cognitive phenotypes, lifestyle, physical properties, and blood assays, associated with each decomposed covariation pattern, helping to understand their real-world implications. This systems neuroscience view paves the way for future studies to explore the implications of these structural covariations, potentially illuminating new pathways in our understanding of neurological and cognitive disorders.NEW & NOTEWORTHY Cerebellum's association with the entire cerebral cortex has not been holistically studied in a unified way. Here, we conjointly characterize the population-level cortical-cerebellar structural covariation patterns leveraging ∼40,000 UK Biobank participants whole brain structural scans and ∼1,000 phenotypes. We revitalize the previous hypothesis of an anticorrelation between the visual-attention system and advanced associative networks within the cerebellum. We also discovered a novel ipsilateral cerebral-cerebellar associations. Phenome-wide association (PheWAS) revealed real-world implications of the structural covariation patterns.

Management of Sports and Recreation Centers in Karanganyar District Through Knowledge Based Worker-Based Sports Human Resources Development

This research aims to explore innovation in management through the development of knowledge-based sports human resources in the sports and recreation center of Karanganyar Regency. The main focus of this study is on the development of knowledge-based sports human resources (knowledge-based workers). In the corporate context, the development of sports human resources should involve several important aspects, including participation in training, mandatory learning, training to improve skills relevant to various modern positions, as well as providing a broad career path and competency development. In addition, performance and competency assessment as well as effective communication in providing feedback are also an integral part of this process. Knowledge-based development is considered a fundamental requirement for achieving sustainable competitive advantage. This underlines the important role of professional intellect in creating value and profits for sports and recreation centers to face business competition. The concept of professional intellect is implemented at four levels, namely cognitive knowledge (professional intellect), skill improvement (advanced skills), system understanding (system understanding), and self-motivated creativity (self-motivated creativity)

Differential Impact of WM Load on Attention in Young Adults Versus Children and Adolescents.

Background: This study aimed to examine how concurrent working memory (WM) loads affect selective attention, and to explore developmental differences between young adults and children/adolescents aged 10 to 14 years. Methods: We employed a modified Stroop task with verbal or spatial WM loads to assess their impact on attention. Results: In adults, we found increased Stroop effects when WM load overlapped with target processing and decreased Stroop effects when WM load overlapped with distractor processing. Conversely, in children/adolescents, WM loads did not significantly impact target or distractor processing, indicating no change in Stroop effects under dual-task conditions. Interestingly, results from the correlational analyses revealed that as participants' ages increase, the interference effect under the WM load that shares resources with distractor processing in the attention task decreases. Conclusions: Our findings suggest that the interaction between attention and WM differs across developmental stages. While adults showed distinctive effects of concurrent WM loads on attention processing depending on the cognitive resources utilized, children/adolescents failed to show the interaction between the two cognitive systems. Furthermore, a significant relationship between age and the effects of WM load on attention was observed, providing insights into the development of the interaction between WM and attention.

Cognitive Capacities as Functional Natural Kinds.

In this paper, we articulate a functional approach to cognitive capacities. It is a restricted functionalism for various reasons, but especially because it does not claim that all cognitive (and/or mental) entities and processes are functional in the sense of a systemic capacities approach. One of the central aims of a cognitive theory consists in providing explanations of behavioral phenomena of (human and non-human) animals, and of the phenomena that are involved in those explanations. We accept that part of what lies at the heart of these explanations are certain functional entities -we call them "cognitive functional systems" -which in our view stand for most of the cognitive capacities of an organism; that is, systems that are individuated primarily by the main cognitive functions they undertake. Additionally, in the paper, we go into further detail concerning these functional systems, their internal organization, the nature of their causal interactions, etc. We also argue that some of these classes of cognitive functional systems (i.e., cognitive capacities) can be construed as "natural kinds" whenever their kinds of functional organizations are understood as kinds of hierarchically ordered classes of information processing events that are related among each other in regular (often complex) ways.

Deep Learning model based on CNN using Keras and TensorFlow to determine real time melting point of chemical substances

Deep learning is a subset of machine learning that uses artificial neural networks inspired by human cognitive systems. Although this is a newly approach recently it became very popular and effective. In many applications deep learning become most successful approach where machine learning has been successful at certain rates. In the succession of these the proposed deep learning model is suitable for melting point detection apparatus which determine melting point of chemical substances this apparatus generally used in pharmaceutical and chemical industries. Proposed deep learning model classify images of chemical’s state (Solid or Liquid) by deep neural network (DNN) it consists of TensorFlow framework, libraries like Keras and activation function like ReLu, sigmoid, MaxPool and Flatten to determine melting point of chemical substances. The proposed model enables to TensorFlow architecture, which can determine the melting point of chemicals in real time on a single board computer. This use python as a programming language, TensorFlow framework and keras library. The input image data mainly focuses on chemical’s state, there are 2 categories of chemical’s state either solid or liquid. The Deep Neural Network (DNN) chosen as the best practice for the training process because it provides high accuracy. The results discussed in terms of the image classification accuracy in percentage. The images from two class label gets maximum accuracy is 99.72% and maximum validation accuracy is 99.37% same as liquid’s image and the average value of accuracy 84.17% or higher after certain epochs.

Sex differences in distributed error-related neural activation in problem-drinking young adults

BackgroundDetecting and responding to errors is central to goal-directed behavior and cognitive control and is thought to be supported by a network of structures that includes the anterior cingulate cortex and anterior insula. Sex differences in the maturational timing of cognitive control systems create differential periods of vulnerability for psychiatric conditions, such as substance use disorders. MethodsWe examined sex differences in error-related activation across an array of distributed brain regions during a Go/No-Go task in young adults with problem alcohol use (N=69; 34 females; M=19.4 years). Regions of interest previously linked to error-related activation, including anterior cingulate cortex, insula, and frontoparietal structures, were selected in a term-based meta-analysis. Individual differences in their responses to false alarm (FA) inhibitory errors relative to “go” trials (FA>GO) and correct rejections (FA>CR) were indexed using multivariate summary measures derived from principal components analysis. ResultsFA>GO and FA>CR activation both revealed a first component that explained the majority of the variance across error-associated regions and displayed the strongest loadings on salience network structures. Compared to females, males exhibited significantly higher levels of the FA>GO component but not the FA>CR component. ConclusionsMales exhibit greater salience network activation in response to inhibitory errors, which could be attributed to sex differences in error-monitoring processes or to other functions (e.g., novelty detection). The findings are relevant for the further characterization of sex differences in cognitive control and may have implications for understanding individual differences in those at risk for substance use or other cognitive control disorders.

Control your emotions: evidence for a shared mechanism of cognitive and emotional control

ABSTRACT The current investigation examined the bidirectional effects of cognitive control and emotional control and the overlap between these two systems in regulating emotions. Based on recent neural and cognitive findings, we hypothesised that two control systems largely overlap as control recruited for one system (either emotional or cognitive) can be used by the other system. In two experiments, participants completed novel versions of either the Stroop task (Experiment 1) or the Flanker task (Experiment 2) in which the emotional and cognitive control systems were actively manipulated into either a high or low emotional-load condition (achieved by varying the proportions of negative-valence emotional cues) and a high and a low cognitive control condition (achieved through varying the proportion of conflict-laden trials). In both experiments, participants’ performance was impaired when both emotional and cognitive control were low, but significantly and similarly improved when one of the two control mechanisms were activated – the emotional or the cognitive. In Experiment 2, performance was further improved when both systems were activated. Our results give further support for a more integrative notion of control in which the two systems (emotional and cognitive control) not only influence each other, but rather extensively overlap.