Identifying the cognitive state can help educators understand the evolving thought processes of learners, and it is important in promoting the development of higher-order thinking skills (HOTS). Cognitive neuroscience research identifies cognitive states by designing experimental tasks and recording electroencephalography (EEG) signals during task performance. However, most of the previous studies primarily concentrated on extracting features from individual channels in single-type tasks, ignoring the interconnection across channels. In this study, three learning activities (i.e., video watching activity, keyword extracting activity, and essay creating activity) were designed based on a revised Bloom's taxonomy and the Interactive-Constructive-Active-Passive framework and used with 31 college students. The EEG signals were recorded when they were engaged in these activities. First, whole-brain network temporal dynamics were characterized by EEG microstate sequence analysis. Such dynamic changes rely on learning activity and corresponding functional brain systems. Subsequently, phase locking value was used to construct synchrony-based functional brain networks. The network characteristics were extracted to be inputted into different machine learning classifiers: Support Vector Machine, K-Nearest Neighbour, Random Forest, and eXtreme Gradient Boosting (XGBoost). XGBoost showed superior performance in the classification of cognitive states, with an accuracy of 88.07%. Furthermore, SHapley Additive exPlanations (SHAP) was adopted to reveal the connections between different brain regions that contributed to the classification of cognitive state. SHAP analysis reveals that the connections in the frontal, temporal, and central regions are most important for the high cognitive state. Collectively, this study may provide further evidence for educators to design cognitive-guided instructional activities to enhance learners' HOTS.

Neuroimaging studies on prosocial decision-making frequently employ a costly giving paradigm, whereas there is a lack of consensus on the broader differences underlying various altruistic giving tasks. This study explores the neural substrates of altruistic giving through an ALE meta-analysis of 65 fMRI studies with 2803 participants. Altruistic giving tasks were categorized into Dictator Game (DG), Charitable Donation (CD), and Pain versus Gain (PvsG). The meta-analysis identified consistent activation in core brain regions, including the ventromedial prefrontal cortex (vmPFC), anterior cingulate cortex (ACC), and insula, which are involved in value computation, conflict monitoring, and emotional processing. Task-specific analyses revealed that the DG task activated the right dorsomedial prefrontal cortex (dmPFC) and presupplementary motor area (pre-SMA), indicating cognitive control of fairness. The CD task showed significant activation in the nucleus accumbens (NAcc) and the second visual cortex, reflecting socio-cognitive evaluation based on context and stimuli. The PvsG task uniquely activated the vmPFC and orbitofrontal cortex (OFC), suggesting rapid moral-emotional trade-offs under urgency. These findings indicate that altruistic giving is context-dependent, shaped by specific task demands. Future research should integrate computational modeling with neuroscientific data and explore individual differences and real-world applications.

Memory is a reconstructive and continuous process that enables existing information to be modified in response to a changing environment. Being able to dynamically update outdated memories is critical to an organism's survival. Memory modifications have been extensively studied in both rodents and humans, and prior work has revealed many regional, cellular, neurotransmitter, and subcellular molecular mechanisms underlying this process. However, these diverse bodies of literature have not yet been fully integrated into a comprehensive cross-species review. Integrating the finding across rodent and human work is important for furthering our understanding of memory modifications and the underlying neural mechanisms that support memory modification in both species. Here, we discuss advances in our understanding of adaptive and maladaptive memory modifications in terms of both underlying mechanisms (regional, cellular, and molecular) and behavioral outcomes. By emphasizing findings from both humans and rodents, the two major model systems in which memory modifications have been studied, we are able to highlight converging mechanisms and point to open questions in the field. Specifically, we discuss the major findings from several memory paradigms including declarative, aversive and procedural memory designs and highlight paradigms and models that have been readily translated between rodent and human models. Ultimately, this review identifies key parallels underlying memory updating across species, paradigms, tasks, and models.

Postoperative short-term attentional and executive dysfunctions are common after brain tumor resection, significantly impacting patients' quality of life and functional recovery. This longitudinal cross-sectional study investigated whether presurgical functional dynamics of key brain networks supporting executive functioning could predict postoperative neuropsychological outcomes, providing insights into temporary deficits and recovery trajectories.

Twenty-two patients with gliomas underwent resting-state fMRI scans before and three-months after surgery, along with neuropsychological assessments conducted before, one week and three months after surgery. Co-activation pattern analysis (CAPs) characterized functional dynamic properties of executive networks, including the Fronto-parietal (FPN). Temporal network properties - stability, integration, and centrality- were examined longitudinally. Descriptive and predictive multivariate analysis explored associations between network dynamics and cognitive functioning.

Immediate post-surgical attentional deficits were associated with pre-surgical FPN properties, revealing dynamic activation patterns predictive of short-term deficits. These temporal properties not only predicted the severity and persistence of early deficits, but also offered valuable insights in the longitudinal progression of attentional performance otherwise neglected. Importantly, by three months post-surgery, neuropsychological profiles and network dynamics returned to pre-surgical baseline, highlighting the transient nature of the deficits beyond treatment strategies.

Our study demonstrates that presurgical dynamic properties of intrinsic executive networks alone can predict short-term postoperative neuropsychological outcomes. This predictive ability offers critical value for patients, families and clinical teams by emphasizing the temporary nature of the deficits and enabling early, personalized interventions. These findings emphasize the potential for using intrinsic brain activity dynamics as a tool for guiding postoperative recovery planning and alleviating concerns about temporary postoperative cognitive impairments.

Smartphones have become integral to daily life, and their overuse can lead to various maladaptive behaviors and decision-making patterns. This study investigated the neural and computational mechanisms underlying smartphone addiction, focusing on its impact on loss-aversion decision-making. We combined computational models, such as the Drift Diffusion Model, with a novel analytic approach, intersubject representational similarity analysis (IS-RSA). Behavioral results showed that higher smartphone addiction symptom (SAS) scores were correlated with reduced loss-aversion (lnλ), while the drift rate was positively associated with SAS. Furthermore, the drift rate mediated the relationship between SAS and lnλ. Neuroimaging analyses revealed that SAS was associated with increased gain-related activity in the occipital pole (OP) but decreased activity in the precuneus and middle frontal gyrus. Additionally, reduced activity was observed in the angular gyrus and superior temporal gyrus during loss processing. IS-RSA further identified brain activation patterns in the default mode network, frontoparietal network, visual network, and sensorimotor network, which corresponded to intersubject variations in SAS, particularly during gain processing but not during loss processing. These patterns were also observed when gains and losses were processed simultaneously. Mediation analyses indicated that brain activation strengths in the OP, precuneus, and MFG during gain processing mediated the relationship between SAS and lnλ and drift rate. Similar mediation effects were observed for intersubject variations in SAS and computational process patterns (eg decision threshold, drift rate, and nondecision time) within these networks. These findings provide novel insights into the neural and computational mechanisms of loss aversion in smartphone addiction, with implications for understanding cognitive biases and informing interventions for addictive behaviors.

This was an exploratory study designed to examine the alterations in neuromagnetic networks within brain regions involved in cognitive functions in children with self-limited epilepsy with centrotemporal spikes (SeLECTS). Additionally, it sought to explore the relationship between these neural network differences and cognitive impairment.

Magnetoencephalography (MEG) data were collected from 63 drug-naïve children diagnosed with SeLECTS and 30 healthy controls (HC). Functional connectivity (FC) across 26 cognitive-related brain regions, as defined by Desikan-Killiany, was assessed using corrected amplitude envelope correlation (AEC-c) analysis. The cognitive function of the children was evaluated using the fourth edition of the Wechsler Intelligence Scale for Children (WISC-IV). Spearman's correlation analysis was then performed to assess the relationship between AEC-c values and WISC-IV indices.

Children with SeLECTS showed reduced FC in the delta band between the left rostral middle frontal (rMFG.L) and the left rostral anterior cingulate (rACC.L), as well as in the gamma2 band between the left superior frontal (SFG.L) and the rACC on both sides, compared to HC (p < 0.05). On the other hand, several FC networks were enhanced, including those between the left rMFG and the right rACC, the left rMFG and the left caudal middle frontal (CMF.L), and between the right caudal middle frontal (CMF.R) and the right supramarginal (SMG.R), specifically in the gamma1 band (p < 0.05). A correlation analysis revealed a positive association between the AEC-c values between the left rMFG and the right rACC and the Verbal Comprehension Index (VCI) scores (R = 0.4228, p < 0.05).

The findings of this study revealed that children with SeLECTS exhibited significant differences in the FC networks in brain regions associated with cognition, especially within the delta and gamma frequency bands, when compared to HC. We also found that these differences in FC networks are significantly correlated with verbal comprehension ability, which may contribute to the understanding of the mechanisms underlying the weaknesses in cognitive function in children with SeLECTS. Furthermore, our findings may provide hypotheses for future work dedicated to further exploring the mechanisms associated with brain network alterations in cognitive impairment in children with SeLECTS.

Based on magnetoencephalography technology (MEG), this study found that there were significant differences in cognitive-related neuromagnetic networks in children with SeLECTS compared with HC, which were significantly correlated with relevant indicators in the Wechsler Scale. This finding suggested that differences in the neuromagnetic network may serve as imaging markers to predict changes in cognitive function in children with SeLECTS.

Transcranial magnetic stimulation (TMS) applies electromagnetic pulses to stimulate cortical neurons. The antidepressant effect of the repetitive application of TMS (rTMS) was first shown nearly three decades ago. The therapeutic potential of TMS has been extensively investigated, mostly in treatment-resistant depression (TRD). Studies have extensively evaluated stimulation parameters, treatment schedules, methods to localize the stimulation target, and different magnetic coil designs engineered for desired stimulation breadth and depth. Several of these stimulation protocols and coils/devices have received U.S. Food and Drug Administration (FDA) clearance for application in TRD and other neuropsychiatric disorders, such as obsessive-compulsive disorder. Some stimulation protocols, while not FDA-cleared, have substantial clinical trial-derived evidence to support their safety and antidepressant efficacy. The proliferation of rTMS translational and clinical research has resulted in the field's advancement. This clinician-oriented review contains an overview of fundamental TMS principles, physiological effects, and studies of rTMS in TRD. Also discussed are two innovations that are increasingly applied in the clinic: theta burst stimulation and accelerated scheduling. A synthesis of the key clinical considerations given to patient assessment and safety, treatment setup, and the minimization and management of adverse effects is provided.

Executive function (EF) is crucial for goal-directed behavior and predicts overall wellbeing, academic and interpersonal success. Intrinsic (i.e., non-evoked) resting state functional connectivity (rsFC) during naturalistic paradigms offers insight into neural mechanisms underlying EF. However, few studies have explored EF-rsFC associations using functional near-infrared spectroscopy (fNIRS) across age groups. This cross-sectional study validates a naturalistic viewing paradigm (Inscapes) using fNIRS and examines the link between rsFC in the prefrontal cortex (PFC) and EF in children ages 4-5 and in young adults ages 18-22. Adults were presented with two rsFC paradigms in a counterbalanced within-subjects design: a traditional static crosshair and Inscapes. Representational similarity analysis revealed robustly similar rsFC patterns between the crosshair and Inscapes conditions, and both were associated with EF (Stroop performance). Children were presented with Inscapes to assess rsFC, and exhibited high compliance using fNIRS. Importantly, rsFC assessed with Inscapes in children was associated with EF (Stroop-like Day-Night Task performance). Age-related differences showed intrinsic functional connections within the PFC strengthening over development. This study uses child-friendly, noninvasive optical neuroimaging and a publicly available rsFC paradigm to elucidate the role of the PFC in EF development, illuminating practical methodological approaches to study the developmental trajectory and neural underpinnings of EF.

Deficits in Executive Function (EF) and Theory of Mind (ToM) are common and significant in attention deficit hyperactivity disorder (ADHD), impacting self-regulation and social interaction. The nature of ToM deficits is believed to be partially associated with preexisting deficits in other core cognitive domains of ADHD, such as EF, which are essential for making mental inferences, especially complex ones. Evaluating these associations at a meta-analytic level is relevant.

To conduct a systematic literature review followed by a meta-analysis to identify potential associations between EF and ToM among individuals with ADHD and their healthy counterparts, considering different developmental stages.

A systematic review was conducted in seven different databases. The methodological quality of the studies was assessed using the Newcastle-Ottawa Scale. The meta-analytic measurement was estimated with the correlation coefficient as the outcome. Due to the presence of heterogeneity, a random-effects model was adopted. Independent meta-analyses were conducted for different EF subdomains and ADHD and healthy control groups. Subgroup analyses were performed to examine the influence of age on the outcome of interest.

Fifteen studies were analyzed. Moderate associations were found when comparing EF and ToM between individuals with ADHD (0.20-0.38) and healthy subjects (0.02-0.40). No significant differences were found between child and adult samples (p > 0.20).

The association between EF and ToM was significant, with a moderate effect size, although no significant differences were found according to age, the presence of ADHD, or EF subdomains. Future research is suggested to expand the age groups and overcome the methodological limitations indicated in this review.

Genetics and experience are known to mold our cognitive development. Yet, the interactions between genetics and brain mechanisms that support learning and flexible behavior in the adult human brain remain largely unknown. Here, we test the link between brain-wide gene expression and macroscopic neuroimaging phenotypes of brain plasticity that support our ability to improve perceptual decisions with training. We demonstrate that gene expression links to learning-dependent changes in spatial variations of cortical microstructure and functional connectivity in visual and fronto-parietal networks that are known to be involved in perceptual decisions. Further, we show that brain stimulation in visual cortex during training boosts learning and alters functional connections, rather than microstructure organization, within and between these networks. Our results reveal neurogenetic phenotypes of plasticity in perceptual decision networks, providing insights into the interplay of genetic expression and macroscopic mechanisms of structural and functional plasticity for learning and flexible behavior.

Functional near-infrared spectroscopy (fNIRS) offers a portable, cost-effective alternative to functional magnetic resonance imaging (fMRI) for noninvasively measuring neural activity. However, fNIRS measurements are limited to cortical regions near the scalp, missing important medial and deeper brain areas. We introduce a predictive model that maps prefrontal fNIRS signals to whole-brain fMRI activity during movie-watching. By aligning neural responses to a common audiovisual stimulus, our approach leverages shared dynamics across imaging modalities to map fNIRS signals to broader neural activity patterns. We scanned participants with fNIRS and utilized a publicly available fMRI dataset of participants watching the same TV episode. The model was trained on the first half of the episode and tested on a held-out participant watching the second half to assess cross-individual and cross-stimulus generalizability. The model significantly predicted fMRI time courses in 66 out of 122 brain regions, including areas otherwise inaccessible to fNIRS. It also replicated intersubject functional connectivity patterns and retained semantic information about the movie content. The model generalized to an independent dataset from a different TV series, suggesting it captures robust cross-modal mappings across stimuli. Our publicly available models enable researchers to infer broader neural dynamics from localized fNIRS data during naturalistic tasks.

Controlling action and thought requires the capacity to stop mental processes. Over the past two decades, evidence has grown that a domain-general inhibitory control mechanism supported by the right lateral prefrontal cortex achieves these functions. However, current views of the neural mechanisms of inhibitory control derive largely from research into the stopping of action. Whereas action stopping is a convenient empirical model, it does not invoke thought inhibition and cannot be used to identify the unique features of this process. Here, we review research that addresses how organisms stop a key process that drives thoughts: memory retrieval. This work has shown that retrieval stopping shares right dorsolateral and ventrolateral prefrontal mechanisms with action stopping, consistent with a domain-general inhibitory control mechanism, but also recruits a distinct fronto-temporal pathway that determines the success of mental control. As part of this pathway, GABAergic inhibition within the hippocampus influences the efficacy of prefrontal control over thought. These unique elements of mental control suggest that hippocampal disinhibition is a transdiagnostic factor underlying intrusive thinking, linking the fronto-temporal control pathway to preclinical models of psychiatric disorders and fear extinction. We suggest that retrieval-stopping deficits may underlie the intrusive thinking that is common across many psychiatric disorders.

Medulloblastoma is the most prevalent malignant brain tumour in children. Although contemporary comprehensive anticancer therapy has been shown to result in favourable survival and relapse outcomes, the long-term toxic effects on cognitive and motor function remain a concern. This study aims to investigate the long-term neurotoxic effects on cognitive function in paediatric medulloblastoma survivors.

Data from 70 patients (Mage = 12.7 ± 2.94 years, 40% female) in remission treated according to the HIT protocol who underwent comprehensive neuropsychological assessment were analyzed. General linear models (GLMs) were constructed to assess the contribution of remission duration, chemotherapy type, and radiation dose to variability in cognitive performance on the CANTAB and DTKI tests.

GLM revealed that remission > 4 years was associated with poorer processing speed, attention, and executive functions: cognitive flexibility, inhibitory control, planning, and working memory compared to participants with shorter remission. Induction therapy with methotrexate had more pronounced long-term negative effects on processing speed. However, no significant effects were observed across different radiation doses.

Remission duration emerged as a more significant predictor of a poor neurocognitive outcome than chemotherapy type or radiation dose, that is, the longer the remission, the more pronounced the neurocognitive impairment becomes. This highlights the need for continued monitoring and the development of targeted rehabilitation interventions for paediatric medulloblastoma survivors.

Dysregulation of brain state is common following traumatic brain injury (TBI), contributing to long-term difficulties in important life pursuits, spanning school, work, and beyond. Brain state dysregulation makes it difficult to effectively organize and direct cognition and behavior to accomplish any number of goals, resulting instead in difficult-to-understand combinations of neurocognitive and emotional symptoms: distractibility, forgetfulness, poor follow-through, irritability, reduced frustration tolerance, and becoming easily overwhelmed. Given underlying heterogeneity with neurocognitive-emotional symptoms, it may be highly efficient to train use of state regulation skills (SRS) as a generalizable approach to facilitate processing of neurocognitive demands encountered along individual goal pathways. In this report, we present an innovative system of guided experiential skill learning of goal-directed SRS - one that rationally integrates experiential digital technology designed to practice applying and integrating SRS directly into goal-based functional challenges with therapist-led training to maximize skill learning, transfer, and generalization. Moreover, we designed this system specifically to bridge important gaps that interfere with skill learning when individuals are remote from therapists. To advance the integration of technology into rehabilitation neuroscience, we present this communication as a hybrid of intervention design (introducing principles and features), "user experiences" (sharing vignettes informative of the value of technology integration into the learning process), and a controlled, proof-of-principle pilot intervention study for a small cohort of individuals (n = 18) with chronic TBI (assessing the plausibility of strengthening goal-directed functioning, as indexed by performance on neurocognitive assessment tasks and complex functional tasks, as well as ratings of personal life functioning). Data suggest that a technology-augmented remote guided experiential learning approach may bridge important gaps in skill learning to help individuals improve goal-directed functioning. This line of work will inform further advances in remote neuro-cognitive rehabilitation.

Salience network functional integration with the central executive network and the default mode network at rest has been shown to predict real-life self-control. It has been proposed that a network interaction index reflecting stronger functional integration of the salience network with the central executive network and reduced functional connectivity of the salience network with the default mode network represents a trait neural correlate of successful self-control exertion. Here, we attempted to replicate this result using data from our own study where 121 participants completed an fMRI self-control task comprising real-life scenarios and data from a second study (N = 79) retrieved from OpenNeuro (dataset ID: ds002643) where participants completed an fMRI food choice task. We could not replicate the proposed role of salience network resting-state functional connectivity in self-controlled decision-making in either of those data sets. Instead, we found evidence for the exact opposite effect, specifically a negative association between self-control performance and the network interaction index. The role of analysis pipelines, appropriate network ROIs, and the measurement of self-control are discussed in the context of our findings.

Disorders of consciousness (DoC) are characterized by a broad decline in background excitatory synaptic activity and varying levels of cerebral network disruption. Repetitive transcranial magnetic stimulation (rTMS), a neuromodulatory technique, is anticipated to assist the recovery of consciousness. Nonetheless, ongoing debates persist regarding its effectiveness, in light of the inconsistent results of recent research.

The purpose of this study is to investigate the efficacy of rTMS in promoting recovery of consciousness in patients with DoC and to probe its impact on activity of cerebral functional networks.

Forty-eight patients with DoC were included in this randomized controlled trial (Chinese Clinical Trial Registry: ChiCTR2100044930). Twenty-four patients in the control group accepted conventional therapy. Another 24 patients in the rTMS group received extra rTMS over the dorsolateral prefrontal cortex (DLPFC) once per workday during a 4-week intervention phase. Primary outcome was the proportion of patients emerging improvement on level of consciousness (LOC) based on coma recovery scale- revised (CRS-R) at the end of intervention. Furthermore, other behavioral scales such as the clinical global impression-improvement (CGI-I) and resting state-electroencephalography (rs-EEG) microstate were employed as secondary outcomes. Different microstates served as tools to detect the activity of respective corresponding resting state cerebral functional networks.

In comparison to the control group, the rTMS group exhibited a higher proportion of patients emerging improvement on LOC at post-intervention, with a risk ratio of 3.06 (95 % CI 1.54 to 6.09, P = 0.001). The distribution of patients with each grade of CGI-I across the groups also implied a trend that favored the rTMS group (common odds ratio:0.20, 95 % CI 0.065 to 0.63, P = 0.006). With respect to microstate E, the rTMS group had a significantly reduced global explained variance (GEV) was observed in the rTMS group (Z = -2.61, Pbonf = 0.027).

High-frequency rTMS over the DLPFC could promote recovery of consciousness in patients with DoC. It might get involved in modulating the balance among cerebral functional networks and facilitating consciousness recovery.

Sleep disturbances are common non-motor symptoms of Parkinson's disease (PD), negatively affecting daily functioning, exacerbating motor symptoms, and contributing to cognitive impairment. However, the underlying neurobiological mechanisms are not well understood. This study utilized resting-state and task-based functional near-infrared spectroscopy (fNIRS) to explore how sleep disturbances affect brain function in PD patients at the neural level.

Sixty PD patients were recruited, including 30 with sleep disturbances and 30 without. Resting-state fNIRS and clinical assessments were used to analyze spontaneous brain activity and functional connectivity. We also examined the mediating role of brain activity in the relationship between sleep disturbances and motor symptoms. The verbal fluency test (VFT) was employed to investigate changes in brain mechanisms related to executive function in patients with sleep disturbances.

Resting-state analysis revealed significantly increased fractional amplitude of low-frequency fluctuations (fALFF) in the medial prefrontal cortex (mPFC) in PD patients with sleep disturbances. fALFF values were negatively correlated with sleep quality and positively with motor symptom severity. Mediation analysis indicated that spontaneous neural activity in the mPFC partially mediated the relationship between sleep disturbances and motor symptoms. Task-based analysis showed reduced activation in the mPFC and orbitofrontal cortex (OFC) during the VFT in patients with sleep disturbances, indicating impaired executive function.

Sleep disturbances in PD could be associated with exacerbated motor symptoms and may impair executive function by affecting spontaneous and task-related neural activity in the mPFC. These findings highlight mPFC dysfunction as a potential biomarker for targeted therapies.

A fundamental tradeoff exists between speed and accuracy when performing a decision (speed-accuracy tradeoff, SAT). Metacognition allows for the adjustment, monitoring, and evaluation of one's own decisions and strategies. While these aspects of cognition are central to human behavioural performance, their respective causal neural underpinnings are not well understood. Here, we used transcranial direct current stimulation (tDCS) to investigate the causal roles of the prefrontal cortex (PFC), superior medial frontal cortex (SMFC), and posterior parietal cortex (PPC) in the SAT and metacognition. Subjects received active or sham tDCS before completing a perceptual task with explicit SAT cues and reported confidence in their decisions. We fit the linear ballistic accumulator model to behavioural data to extract latent decision variables and used confidence judgments to compute two common indices of metacognition: meta-d' and m-ratio. Stimulation influenced performance on the perceptual task but there was no meaningful evidence for an effect on metacognition. Specifically, PFC stimulation reduced subjects' response caution, especially when accuracy was emphasised; SMFC stimulation decreased response caution and increased the discriminability between choices; and PPC stimulation increased both response caution and discriminability. These results show that the impact of tDCS on the SAT critically depends on the frontoparietal region stimulated. In addition, there was little to no evidence of any effect of tDCS on metacognition, hinting at potential differences in the neural circuitry supporting aspects of object-level computation and meta-level processing. In sum, our findings provide further evidence that tDCS can alter decision making and strategic processes in the human brain.

Published results of our Phase I safety and feasibility trial of accelerated intermittent theta burst stimulation (a-iTBS) in mild cognitive impairment (MCI) due to Alzheimer's disease showed a large effect-size improvement in cognition.

Further demonstrate target engagement by identifying whether changes in local and network-level functional connectivity relate to the observed cognitive improvement.

Eighteen patients with MCI received 3-day a-iTBS (8 sessions/day) to the left dorsolateral prefrontal cortex at Beam F3 (14,400 total pulses) and completed MRI and cognitive testing at pre- and post-treatment. Based on electric field models, we selected 3 stimulated target regions of interest (ROIs) which belonged to the frontoparietal (FPN), default mode (DMN), and ventral attention (VAT) networks (3 target networks). Metrics of resting-state functional connectivity were computed at the ROI level (within-network degree: number of connections) and network level (segregation: strength of connectivity within-network relative to other networks). We correlated changes in cognition and connectivity of the target ROIs and networks; off-target ROI (primary visual) and networks served as negative controls.

Improvements in cognition were associated with connectivity changes in the target ROIs and networks, but not in off-target negative controls. Positive associations were observed for degree of the l-DMN and segregation of target networks overall, with significant effects for DMN and VAT.

Cognitive improvement following a-iTBS in MCI may be attributable to local and network-level reconfigurations in functional connectivity. These findings will inform larger trials designed to further evaluate the neural mechanisms of a-iTBS for cognition in MCI.

The substantial personal, societal, and economic impacts of opioid addiction drive research investigating how opioid addiction affects the brain, and whether therapies attenuate addiction-related metrics of brain function. Evaluating the connectivity between brain regions is a useful approach to characterise the effects of opioid addiction on the brain. This work is a systematic narrative review of studies investigating the effect of abstinence or interventions on connectivity in people who are dependent on heroin (HD) and healthy controls (HC). We found that HD typically showed weaker connectivity than HC between three functional networks: the Executive Control Network, Default Mode Network, and the Salience Network. Abstinence and Transcranial Magnetic Stimulation (TMS) both attenuated differences in connectivity between HD and HC, often by strengthening connectivity in HD. We observed that increased connectivity due to abstinence or TMS consistently related to decreased craving/risk of relapse. Using these findings, we present an "urge and action framework" relating therapeutic factors contributing to craving/relapse, connectivity results, and neurobiological models of HD. To inform future research, we critically assessed the impact of study design and analysis methods on study results. We conclude that the weaker between-network connectivity in HD and HC and its relationship to craving/relapse merits further exploration as a biomarker and target for therapeutic interventions.

Despite recent studies suggesting an important association of hoarder disorder (HD) and attention-deficit/hyperactive disorder (ADHD), no neuroimaging study has investigated the differences between patients with HD comorbid with ADHD and those without ADHD. This study investigated the regional spontaneous activity and functional connectivity in HD, focusing on the comorbidity with ADHD. Resting-state functional magnetic resonance imaging (MRI) data were obtained from 24 patients with HD and 31 healthy individuals. We investigated the group differences using the fractional amplitude of low-frequency fluctuation (fALFF). The altered regions in the fALFF were used as seeds in a functional connectivity analysis where we conducted group comparisons among the three groups: healthy controls (HCs), HD with ADHD (HD +ADHD), and HD without ADHD (HD -ADHD). Compared to HCs, patients with HD had a reduced fALFF in the right inferior frontal gyrus (IFG). Functional connectivity analysis revealed that patients with HD + ADHD had reduced functional connectivity between the IFG and dorsolateral prefrontal cortex (DLPFC) compared to HCs, while the HD -ADHD group was intermediate level between HD +ADHD and HCs groups. In conclusion, patients with HD have altered spontaneous activity of the IFG. Additionally, patients with HD + ADHD had significantly reduced functional connectivity between the IFG and the DLPFC. Our findings suggest the potential need to distinguish between subgroups of HD+ADHD to identify novel neurobiological models of HD that could guide future therapeutic strategies.

Recent advances in neuroimaging modeling highlight the importance of accounting for subgroup heterogeneity in population-based neuroscience research through various investigations in large scale neuroimaging data collection. To integrate survey methodology with neuroscience research, we present an imaging data analysis and yield population generalizability with screened subsets of data. The Adolescent Brain Cognitive Development (ABCD) Study has enrolled a large cohort of participants to reflect the individual variation of the U.S. population in adolescent development. To ensure population representation, the ABCD Study has released the base weights. We estimated the associations between brain activities and cognitive performance using the functional Magnetic Resonance Imaging (fMRI) data from the ABCD Study's N-Back working memory task. Notably, the imaging subsample exhibits differences from the baseline cohort in key child characteristics and such discrepancies cannot be addressed simply by applying the ABCD base weights. We developed new population weights specific to the subsample and included the adjusted weights in the image-on-scalar regression model. We validated the approach through synthetic simulations and applications to fMRI data from the ABCD Study. Our findings demonstrate that population weighting adjustments effectively capture active brain areas associated with cognition, enhancing the validity and generalizability of population neuroscience research.

Rumination is a known risk factor for depression relapse. Understanding its neurobiological mechanisms during depression remission can inform strategies to prevent relapse, yet the temporal dynamics of brain networks during rumination in remitted depression remain unclear. Here, we collected rumination induction fMRI data from 42 patients with remitted depression and 41 healthy controls (HCs). Using an energy landscape approach, we investigated the temporal dynamics of brain networks during rumination. The appearance frequency (AF) and transition frequency (TF) metrics were defined to quantify the dynamic properties of brain states. Patients during remission showed higher levels of rumination than HCs. Both groups exhibited four brain states during rumination, which consisted of complementary network group activation (states 1 and 2, states 3 and 4). In patients, the AFs of and reciprocal TFs between states 1 and 2 during rumination were significantly increased, while AFs of states 3 and 4 and reciprocal TFs involving states 1-3, 1-4, 2-3, and 2-4 were decreased, both when compared to HCs and relative to patients themselves during distraction. Moreover, we found that for patients, the AF of state 1 was negatively correlated with rumination levels and marginally positively associated with attention, while the AF of state 2 was negatively associated with performance on attention tasks. Our study revealed altered dynamic characteristics of brain states composed of network groups during rumination in remitted depression. Additionally, the findings suggest that heightened self-focus linked to rumination may impair the brain's ability to efficiently allocate attentional resources.

This study aims to assess the therapeutic effects of intermittent theta burst stimulation (iTBS) targeting the bilateral dorsomedial prefrontal cortex (DMPFC) on negative symptoms in patients with schizophrenia, utilizing functional near-infrared spectroscopy for evaluation.

Thirty-five schizophrenia patients with negative symptoms and moderate to severe cognitive impairment were randomly assigned to a treatment group (n = 18) or a control group (n = 17). The treatment group received iTBS via bilateral DMPFC. Negative symptoms, cognitive function, emotional state, and social function were assessed using Positive and Negative Syndrome Scale (PANSS), Scale for the Assessment of Negative Symptoms (SANS), Montreal Cognitive Assessment (MoCA), Calgary Depression Scale for Schizophrenia (CDSS), and Social Dysfunction Screening Questionnaire (SDSS) scales at pretreatment, posttreatment, and follow-up at 4, 8, and 12 weeks. Brain activation in regions of interest (ROIs) was evaluated through verbal fluency tasks.

Prior to treatment there was no significant difference in the two groups. After 20 iTBS sessions, a significant difference was observed in SANS total score, its related subscales, PANSS total score, and PANSS-negative symptoms (all P < 0.05). The group-by-time interaction showed statistical significance, indicating improvements in negative symptoms and related dimensions over time, with therapeutic effects persisting for at least 8 weeks posttreatment. Prior to treatment, there were no significant differences in activation across all ROIs between the two groups. Posttreatment, the activation of right inferior frontal gyrus (t = 2.19, P = 0.036) and right frontal eye field (t = 2.14, P = 0.04) in the treatment group was significantly higher than in the control group.

iTBS stimulation of bilateral DMPFC demonstrates therapeutic effects in improving negative symptoms in schizophrenia patients, and this treatment approach has the potential to enhance activation within the prefrontal cortex.

Cognitive flexibility, the capacity to adapt behaviors in response to changing environments, is impaired across mental illnesses, including depression, anxiety, addiction, and obsessive-compulsive disorder. Cortico-striatal-cortical circuits are integral to cognition and goal-directed behavior and disruptions in these circuits are linked to cognitive inflexibility in mental illnesses. We review evidence that neurostimulation of these circuits can improve cognitive flexibility and ameliorate symptoms, and that this may be a mechanism of action of current clinical therapies. Further, we discuss how animal models can offer insights into the mechanisms underlying cognitive flexibility and effects of neurostimulation. We review research from animal studies that may, if translated, yield better approaches to modulating flexibility. Future research should focus on refining definitions of cognitive flexibility, improving detection of impaired flexibility, and developing new methods for optimizing neurostimulation parameters. This could enhance neurostimulation therapies through more personalized treatments that leverage cognitive flexibility to improve patient outcomes.

Proliferation of the term "emotion dysregulation" in child psychopathology parallels the growing interest in processes that influence negative emotional reactivity. While it commonly refers to a clinical phenotype where intense anger leads to behavioral dyscontrol, the term implies etiology because anything that is dysregulated requires an impaired regulatory mechanism. Many cognitive, affective, behavioral, neural, and social processes have been studied to improve understanding of emotion dysregulation. Nevertheless, the defective regulatory mechanism that might underlie it remains unclear. This systematic review of research on processes that affect emotion dysregulation endeavors to develop an integrative framework for the wide variety of factors investigated. It seeks to ascertain which, if any, constitutes an impaired regulatory mechanism. Based on this review, we propose a framework organizing emotion-relevant processes into categories pertaining to stimulus processing, response selection and control, emotion generation, closed- or open-loop feedback-based regulation, and experiential influences. Our review finds scant evidence for closed-loop (automatic) mechanisms to downregulate anger arousal rapidly. Open-loop (deliberate) regulatory strategies seem effective for low-to-moderate arousal. More extensive evidence supports roles for aspects of stimulus processing (sensory sensitivity, salience, appraisal, threat processing, and reward expectancy). Response control functions, such as inhibitory control, show robust associations with emotion dysregulation. Processes relating to emotion generation highlight aberrant features in autonomic, endocrine, reward functioning, and tonic mood states. A large literature on adverse childhood experiences and family interactions shows the unique and joint effects of interpersonal with child-level risks. We conclude that the defective closed-loop regulatory mechanisms that emotion dysregulation implies require further specification. Integrating research on emotion-relevant mechanisms along an axis from input factors through emotion generation to corrective feedback may promote research on (a) heterogeneity in pathogenesis, (b) interrelationships between these factors, and (c) the derivation of better-targeted treatments that address specific pathogenic processes of affected youth.

This study aimed to explore the brain activity characteristics of individuals with Internet Gaming Disorder (IGD) during mobile gameplay, focusing on neural responses to positive and negative game events. The findings may enhance our understanding of the neural mechanisms underlying IGD.

Functional near-infrared spectroscopy (fNIRS) was employed to measure hemodynamic responses (HbO/HbR) in the prefrontal cortex of both IGD participants and recreational gaming users (RGU), during solo and multiplayer mobile gameplay.

In solo mode, IGD participants exhibited stronger activation in the dorsolateral prefrontal cortex (dLPFC), frontopolar area (FPA), orbitofrontal cortex (OFC) in response to positive events compared to RGU. Negative events led to reduced activation in the FPA among IGD participants. In multiplayer mode, IGD participants displayed lower activation in the dLPFC and ventrolateral prefrontal cortex (vLPFC), although overall brain response trends to positive and negative events were similar between IGD and RGU.

This study suggests that individuals with IGD exhibit heightened sensitivity to rewards and diminished sensitivity to losses, along with potential impairments in the executive control network. These results contribute to a better understanding of the neural mechanisms of IGD and offer insights for developing targeted interventions aimed at addressing abnormal reward and loss processing.

Creativity, characterized by the pursuit of uniqueness and novelty, highlights the importance of individual variability, which have been a key focus in cognitive and behavioral research on creativity. However, most studies on the neural basis of creativity have primarily focused on consistent patterns of brain activity across individuals, with little attention to the variability in brain function. In this study, inter-subject representational similarity analysis was employed to investigate the relationship between inter-individual variability in resting-state functional connectivity and creative ability. The results revealed significant positive correlations between individual variability in functional connectivity maps of multiple brain regions, including the superior frontal gyrus, orbital gyrus, precuneus, cingulate gyrus, and lateral occipital cortex, and variability in creative ability. Notably, both intra-network variability within the default mode network (DMN) and visual network, as well as inter-network variability among the DMN, visual, sensorimotor, dorsal attention, and fronto-parietal networks, were linked to the variability in creative ability. The variations in functional connectivity patterns effectively distinguished individuals with high creative ability from those with lower ability. By examining creativity from the perspective of individual variability, this study provides new insights into the neural mechanisms underlying creativity.

This study investigates the neural underpinnings of cognitive control deficits in attention-deficit/hyperactivity disorder (ADHD), focusing on trial-level variability of neural coding. Using fMRI, we apply a computational approach to single-trial neural decoding on a cued stop-signal task, probing proactive and reactive control within the dual control model. Reactive control involves suppressing an automatic response when interference is detected, and proactive control involves implementing preparatory strategies based on prior information. In contrast to typically developing children (TD), children with ADHD show disrupted neural coding during both proactive and reactive control, characterized by increased temporal variability and diminished spatial stability in neural responses in salience and frontal-parietal network regions. This variability correlates with fluctuating task performance and ADHD symptoms. Additionally, children with ADHD exhibit more heterogeneous neural response patterns across individuals compared to TD children. Our findings underscore the significance of modeling trial-wise neural variability in understanding cognitive control deficits in ADHD.

Advancements in biomedical imaging technologies over the past few decades have made it increasingly possible to measure the long-term effects of exercise on the central nervous system. This study aims to compare the brain morphology and functional connectivity of wrestlers and handball players, exploring sport-specific neural adaptations.

Here, we examined 26 elite male athletes (13 wrestlers and 13 handball players) using anatomical and resting-state functional magnetic resonance imaging (fMRI) measurements. Connectivity maps are derived using the seed-based correlation analysis of resting-state fMRI, while voxel-based morphometry (VBM) is employed to identify anatomical differences. Additionally, the cortical thickness and global volumetric values of the segmented images are examined to determine the distinctions between elite wrestlers and handball players using non-parametric statistical tests.

Wrestlers exhibited greater grey matter volume (GMV) in the right middle temporal gyrus, left middle frontal gyrus, and right posterior cingulate gyrus (uncorr., p < 0.001). On the other hand, wrestlers showed increased functional connectivity in the left superior temporal gyrus, left parahippocampal gyrus, the left anterior orbital gyrus, and right superior frontal gyrus-medial frontal region (P(FWE) < 0.05). In addition, wrestlers showed greater cortical thickness in several brain regions.

The increased GMV, cortical thickness, and functional connectivity observed in wrestlers highlight the presence of sport-specific neural adaptations. While this research provides valuable insights into the neuroplastic effects of various athletic disciplines, further studies involving additional sports and control groups are needed for a more comprehensive understanding.

Studies have shown that inhibitory control is supported by frontal cortex and small-world brain networks. However, it remains unclear how regulating the topology changes the inhibitory control. We investigated the effects of small-worldness upregulation training on resting-state networks via fNIRS neurofeedback training, which will contribute to a deeper insight of inhibitory control.

A five-day training session was used to regulate the small-worldness of the frontal cortex, and the color-word Stroop task was tested before and after training. Fifty healthy adults were recruited and randomly assigned to the sham feedback group (sham group), or intermittent fNIRS-based brain network feedback group (fNIRS-NF group). On the basis of the exclusion of incomplete data, 45 valid data sets were retained and analyzed (sham: 21, fNIRS-NF: 24).

Training increased resting-state small-worldness and improved Stroop task performance, with a significant correlation between these changes (r = -0.32, p = 0.032). The fNIRS-NF group exhibited reduced hemodynamic activation (βvalue decreased, indicating lower cognitive load) during posttest and follow-up. Notably, the right dorsolateral prefrontal cortex (dlPFC) showed greater intra-regional connectivity increases than the left dlPFC, suggesting asymmetric plasticity.

Intermittent fNIRS neurofeedback effectively modulates resting-state small-world networks and enhances inhibitory control, with effects sustained for at least one week. These findings highlight small-worldness as a novel target for cognitive interventions.

People with bipolar disorder (BD) present with mood instability resulting from more frequent and intense emotions in response to environmental conditions relative to healthy subjects. The aim of this study was to investigate the time course of emotion regulation strategies, distraction, and reappraisal in euthymic BD patients (i.e., normal mood range) using electroencephalography (EEG). Fourteen BD patients and 13 matched healthy controls took part in an experiment constituting three conditions, i.e., a passive viewing of positive, negative, and neutral pictures, and two regulation conditions, one with a reappraisal strategy and the other with a distraction strategy. Critically, the ERP results indicated that during passive viewing, the Late Positive Potential (LPP) was larger in BD patients compared with healthy controls, but only for neutral pictures. During emotion regulation, LPP amplitude was reduced in distraction conditions compared with viewing ones, especially for negative emotions in both patients and controls. Importantly, LPP was reduced in reappraisal conditions compared with passive viewing in an early time window for negative emotions and in a later time window for positive emotions in controls but not in patients. Our findings showed that the temporal dynamics of emotion regulation by reappraisal are faster for negative than for positive emotions in controls but not in BD patients.

General anesthesia, pivotal for surgical procedures, requires precise depth monitoring to mitigate risks ranging from intraoperative awareness to postoperative cognitive impairments. Traditional assessment methods, relying on physiological indicators or behavioral responses, fall short of accurately capturing the nuanced states of unconsciousness. This study introduces a machine learning-based approach to decode anesthesia depth, leveraging EEG data across different anesthesia states induced by propofol and esketamine in rats. Our findings demonstrate the model's robust predictive accuracy, underscored by a novel intra-subject dataset partitioning and a 5-fold cross-validation method. The research diverges from conventional monitoring by utilizing anesthetic infusion rates as objective indicators of anesthesia states, highlighting distinct EEG patterns and enhancing prediction accuracy. Moreover, the model's ability to generalize across individuals suggests its potential for broad clinical application, distinguishing between anesthetic agents and their depths. Despite relying on rat EEG data, which poses questions about real-world applicability, our approach marks a significant advance in anesthesia monitoring.

To elucidate the neurobiological basis of cognition, which is dynamic and evolving, various methods have emerged to characterise time-varying functional connectivity (FC) and track the temporal evolution of functional networks. However, given a selection of regions, many of these methods are based on modelling all possible pairwise connections, diluting a potential focus of interest on individual connections. This is the case with the hidden Markov model (HMM), which relies on region-by-region covariance matrices across all pairs of selected regions, assuming that fluctuations in FC occur across all investigated connections; that is, that all connections are locked to the same temporal pattern. To address this limitation, we introduce Targeted Time-Varying FC (T-TVFC), a variant of the HMM that explicitly models the temporal fluctuations between two sets of regions in a targeted fashion, rather than across the entire connectivity matrix. In this study, we apply T-TVFC to both simulated and real-world data. Specifically, we investigate thalamocortical connectivity, hypothesising distinct temporal signatures compared to corticocortical networks. Given the thalamus's role as a critical hub, thalamocortical connections might contain unique information about cognitive processing that could be overlooked in a coarser representation. We tested these hypotheses on high-field functional magnetic resonance data from 60 participants engaged in a reasoning task with varying complexity levels. Our findings demonstrate that the time-varying interactions captured by T-TVFC contain task-related information not detected by more traditional decompositions.

Estrogen exposure during menstrual years has been associated with late-life neuroprotection. We explored the presence of an age-sensitive menarche window for cognition in old age and the impact of socioeconomic status and education. We compared neuropsychological performance of 1082 older women [MeanAGE = 72.69 (5.48)] with menarche in childhood, early-, mid-, and late-adolescence and dementia prevalence, severity, and type, including the effects of education and socioeconomic status. Adjusting for covariates, menarche at 11-14 years of age was associated with better memory, executive and global cognitive functioning in old age, and stronger positive effects of education and socioeconomic status on cognition than those with menarche at 15-17 years. We found a critical age window for the neuroprotective effects of estrogens during early adolescence, putting women with later menarche at higher risk for cognitive decline. Effects of socioeconomic status and education in adulthood should be a focus of future research.

Overload represents a significant challenge for pilots in flight, with a substantial impact on flight safety. Currently, the primary method of protection is the utilization of inflatable anti-G suit to address instances where blood is concentrated in the lower extremities. The inflatable air pressure of the anti-G suit varies in response to different overload conditions, which in turn affects the pilot's sensory and brain loads. However, this change has not yet been fully explored. To investigate the neural effects of pressure from the anti-G suit under different degrees of overload, this paper employs a pressurized simulation methodology. The subjects' brain state changes during the simulation are measured through electroencephalogram (EEG), and comparative calculations are performed using microstate and functional connectivity. The final results demonstrate that varying inflation levels of the bladder anti-G suit can influence the microstate and functional connectivity. The Duration, Coverage, Occurrence, and transition probability (TP) characteristics of microstate C demonstrated significant variance across three distinct levels of overload. The mean increase in Phase Locking Value (PLV) for overload 3 relative to the absence of overload was 13.8%, and the number of channel synchronizations underwent a transition from 7 to 62.

Cortical Layer 1 (L1) acts as a critical relay for processing long-range inputs. GABAergic inhibitory interneurons (INs) in this layer (Layer 1 interneurons [L1INs]) function as inhibitory gates, regulating these inputs and modulating the activity of deeper cortical layers. However, their characteristics and circuits in the medial prefrontal cortex (mPFC) remain poorly understood. Using biocytin labeling, we identified three distinct morphological types of mPFC L1INs: neurogliaform cells (NGCs), elongated NGCs (eNGCs), and single-bouquet cell-like (SBC-like) cells. Whole-cell recordings revealed distinct firing patterns across these subtypes: NGCs and eNGCs predominantly exhibited late-spiking (LS) patterns, and SBC-like cells displayed a higher prevalence of non-LS (NLS) patterns. We observed both electrical and chemical connections among mPFC L1INs. Optogenetic activation of NDNF+ L1INs demonstrated broad inhibitory effects on deeper layer neurons. The strength of inhibition on pyramidal neurons (PyNs) and INs displayed layer-specific preference. These findings highlight the functional diversity of L1INs in modulating mPFC circuits and suggest their potential role in supporting higher order cognitive functions.

Self-judgment is a trans-diagnostic symptom among various psychological disorders, therefore can be a therapeutic target for many common psychiatric conditions. Self-judgment often arises among those who experienced childhood maltreatment, which increases the risk for developing comorbid psychiatric disorders that are resistant to traditional pharmacological and psychological interventions. Understanding the neural correlates of the therapeutic effect of behavioral interventions for reducing self-judgment is key for developing and refining evidence-based intervention programs. This single arm pilot study (N = 24) explored the neural correlates of reduction in self-judgment after an eight-week mindful self-compassion (MSC) intervention program for a sample of adult patients with either anxiety or depressive disorders, with 83 % having more than one diagnoses. The results demonstrated significant reduction of self-judgment after the intervention (p < 0.001, d = -1.04) along with increased self-compassion (p < 0.001, d =1.20); in particular, participants with above median score on the Childhood Trauma Questionnaire had significantly more improvement than those with below median scores (p < 0.05). Resting state fMRI was used to study neural correlates and showed that reduced self-judgment was associated with increased posterior cingulate cortex functional connectivity with dorsal lateral prefrontal cortex, inferior frontal gyrus, and dorsal medial prefrontal cortex, accompanied by reduced posterior cingulate cortex functional connectivity with the amygdala-hippocampal complex. These findings suggest reduced self-judgment after MSC training was substantiated by reduced fear circuitry influences on self-referential processes along with enhanced frontal regulation from the executive network and language network.

In some cases, when we are making decisions, the available choices can appear to be equivalent. When this happens, our choices appear not to be constrained by external factors and, instead, we can believe to be selecting "randomly." Furthermore, randomness is sometimes even explicitly required by task conditions such as in random sequence generation tasks. This is a challenging task that involves the coordination of multiple cognitive processes, which can include the inhibition of habitual choice patterns and monitoring of the running choice sequence. It has been shown that random choices are strongly influenced by the way they are instructed. This raises the question whether the brain mechanisms underlying random selection also differ between different task instructions. To assess this, we measured brain activity while participants were engaging in three different variations of a sequence generation task: On the basis of previous work, participants were instructed to either (1) "generate a random sequence of choices," (2) "simulate a fair coin toss," or (3) "choose freely." Our results reveal a consistent frontoparietal activation pattern that is shared across all tasks. Specifically, increased activity was observed in bilateral inferior and right middle frontal gyrus, left pre-SMA, bilateral inferior parietal lobules, and portions of anterior insular cortex in both hemispheres. Activity in the mental coin toss condition was higher in right dorsolateral prefrontal cortex, left (pre-) SMA, a portion of right inferior frontal gyrus, bilateral superior parietal lobules, and bilateral anterior insula. In addition, our multivariate analysis revealed a distinct region in the right frontal pole to be predictive of the outcome of choices, but only when randomness was explicitly instructed. These results emphasize that different randomization tasks involve both shared and unique neural mechanisms. Thus, even seemingly similar randomization behavior can be produced by different neural pathways.

Arousal refers to changes in brain-body state underpinning motivated behavior but lacks a proper definition and taxonomy. Neuroscience and psychology textbooks offer surprisingly different views on what arousal is, from a global brain-wide modulation of neuronal activity to a multidimensional construct, with specific brain-body patterns tuned to a given situation. The huge number of scientific articles mentioning arousal (~50,000) highlights the importance of the concept but also explains why such a vast literature has never been systematically reviewed so far. Here, we leverage the tools of natural language processing to probe the nature of arousal in a data-driven, comprehensive manner. We show that arousal comes in seven varieties: cognitive, emotional, physiological, sexual, related to stress disorders, to sleep, or to sleep disorders. We then ask whether domain-general arousal exists at the cortical level, and run meta-analyses of the brain imaging literature to reveal that all varieties of arousal, except arousal in sleep disorders for lack of data, converge onto a cortical network composed of the presupplementary motor area and the left and right dorsal anterior insula. More precisely, we find that activity in dysgranular insular area 7 (Jülich atlas), the region with the highest convergence across varieties of arousal, is also specifically associated with arousal. The domain-general arousal network might trigger the reorganization of large-scale brain networks-a global mechanism-resulting in a context-specific configuration-in line with the multidimensional view. Future taxonomies of arousal refining the alignment between concepts and data should include domain-general arousal as a central component.

Executive functions, the set of cognitive control processes that facilitate adaptive thoughts and actions, are composed primarily of three distinct yet interrelated cognitive components: Inhibition, Shifting, and Updating. While prior research has examined the nature of different components as well as their inter-relationships, fewer studies examined whole-brain connectivity to predict individual differences for the three cognitive components and associated tasks. Here, using the Connectome-based Predictive Modelling (CPM) approach and open-access data from the Human Connectome Project, we built brain network models to successfully predict individual performance differences on the Flanker task, the Dimensional Change Card Sort task, and the 2-back task, each putatively corresponding to Inhibition, Shifting, and Updating. We focused on grayordinate fMRI data collected during the 2-back tasks after confirming superior predictive performance over resting-state and volumetric data. High cross-task prediction accuracy as well as joint recruitment of canonical networks, such as the frontoparietal and default-mode networks, suggest the existence of a common executive function factor. To investigate the relationships among the three executive function components, we developed new measures to disentangle their shared and unique aspects. Our analysis confirmed that a shared executive function component can be predicted from functional connectivity patterns densely located around the frontoparietal, default-mode and dorsal attention networks. The Updating-specific component showed significant cross-prediction with the general executive function factor, suggesting a relatively stronger role than the other components. In contrast, the Shifting-specific and Inhibition-specific components exhibited lower cross-prediction performance, indicating more distinct and specialized roles. Given the limitation that individual behavioral measures do not purely reflect the intended cognitive constructs, our study demonstrates a novel approach to infer common and specific components of executive function.