The role of PFC networks in cognitive control and executive function

Multi-level cognitive state classification of learners using complex brain networks and interpretable machine learning

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.

The influence of tDCS on the speed-accuracy tradeoff and metacognitive decision making

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.

Differences in fMRI-based connectivity during abstinence or interventions between heroin-dependent individuals and healthy controls

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.

Spontaneous activity and functional connectivity in patients with hoarding disorder comorbid with attention-deficit/hyperactive disorder

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.

Treating Depression With Repetitive Transcranial Magnetic Stimulation: A Clinician's Guide

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.

Population-weighted Image-on-scalar Regression Analyses of Large Scale Neuroimaging Data

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.

Accelerated iTBS-Induced Changes in Resting-State Functional Connectivity Correspond with Cognitive Improvement in Amnestic MCI

BACKGROUND

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.

OBJECTIVE

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

METHODS

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 for the target ROIs and networks; off-target ROI (primary visual) and networks serve as negative controls.

RESULTS

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.

CONCLUSION

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 relationship between neuromagnetic networks and cognitive impairment in self-limited epilepsy with centrotemporal spikes

OBJECTIVE

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.

METHODS

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.

RESULTS

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).

SIGNIFICANCE

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.

PLAIN LANGUAGE SUMMARY

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.

Altered brain network dynamics during rumination in remitted depression

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.

Intermittent theta burst stimulation for negative symptoms in schizophrenia patients with moderate to severe cognitive impairment: A randomized controlled trial

AIMS

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.

METHODS

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.

RESULTS

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.

CONCLUSIONS

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.

Neurostimulation to Improve Cognitive Flexibility

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.

Annual Research Review: What processes are dysregulated among emotionally dysregulated youth? - a systematic review

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.

Prefrontal cortex responses to game rewards and losses in individuals with Internet Gaming Disorder: Insights from fNIRS during mobile gameplay

Aims

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.

Methods

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.

Results

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.

Conclusions

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.

Beyond the uniform creative brain: Inter-individual variability in functional connectivity correlates with creativity

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.

Differences in Anatomical Structures and Resting-State Brain Networks Between Elite Wrestlers and Handball Athletes

BACKGROUND/OBJECTIVES

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.

METHODS

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.

RESULTS

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.

CONCLUSIONS

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.

The emergent property of inhibitory control: implications of intermittent network-based fNIRS neurofeedback training

Background

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.

Methods

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).

Results

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.

Conclusion

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.

Impaired Regulation of Emotion in Bipolar I Disorder: Behavioral and Neurophysiological Signatures

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.

Accurate Machine Learning-based Monitoring of Anesthesia Depth with EEG Recording

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.

Targeted Time-Varying Functional Connectivity

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.

Neural impact of anti-G suits on pilots: Analyzing microstates and functional connectivity

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.

Critical menarche age for late-life dementia and the role of education and socioeconomic status

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.

Neural correlates of reduction in self-judgment after mindful self-compassion training: A pilot study with resting state fMRI

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.

Neural Correlates of Different Randomization Tasks

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.

Evidence for domain-general arousal from semantic and neuroimaging meta-analyses reconciles opposing views on arousal

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.

Connectome-based Predictive Models of General and Specific Executive Functions

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.

Emergent Aspects of the Integration of Sensory and Motor Functions

This article delves into the intricate mechanisms underlying sensory integration in the executive control of movement, encompassing ideomotor activity, predictive capabilities, and motor control systems. It examines the interplay between motor and sensory functions, highlighting the role of the cortical and subcortical regions of the central nervous system in enhancing environmental interaction. The acquisition of motor skills, procedural memory, and the representation of actions in the brain are discussed emphasizing the significance of mental imagery and training in motor function. The development of this aspect of sensorimotor integration control can help to advance our understanding of the interactions between executive motor control, cortical mechanisms, and consciousness. Bridging theoretical insights with practical applications, it sets the stage for future innovations in clinical rehabilitation, assistive technology, and education. The ongoing exploration of these domains promises to uncover new pathways for enhancing human capability and well-being.

The hemispheric differences in prefrontal function of Internet game disorder and non-Internet game disorder: an activation likelihood estimation meta-analysis

This study explored the differences in brain activation between individuals with and without Internet gaming disorder (IGD) through activation likelihood estimation analysis. In total, 39 studies were included based on the inclusion and exclusion criteria by searching the literature in the PubMed and Web of Science databases, as well as reading other reviews. The analysis revealed that the activated brain regions in IGD were the right inferior frontal gyrus, left cingulate gyrus, and left lentiform nucleus. In comparison, the activated brain regions in non-IGD were the left middle frontal, left inferior frontal, left anterior cingulate, left precentral, and right precentral gyri. The results of the present study on differences in activation further confirm existing theoretical hypotheses. Future studies should explore hemispheric differences in prefrontal brain function between IGD and non-IGD.

Altered Dynamic Brain Functional Network Connectivity Related to Visual Network in Spinal Cord Injury

Visual feedback training (VFT) plays an important role in the motor rehabilitation of patients with spinal cord injury (SCI). However, the neural mechanisms are unclear. We aimed to investigate the changes in dynamic functional network connectivity (FNC) related to visual networks (VN) in patients with SCI and to reveal the neural mechanism of VFT promoting motor function rehabilitation. Dynamic FNC and the sliding window method were performed in 18 complete SCI (CSCI), 16 patients with incomplete SCI (ISCI), and 42 healthy controls (HCs). Then, k-mean clustering was implemented to identify discrete FNC states, and temporal properties were computed. The correlations between these dynamic features and neurological parameters in all patients with SCI were calculated. The majority of aberrant FNC was manifested between VN and executive control network (ECN). In addition, compared with HCs, temporal metrics derived from state transition vectors were decreased in patients with CSCI including the mean dwell time and the fraction of time spent in state 3. Furthermore, the disrupted FNC between salience network and ECN in state 2 and the number of transitions were all positively correlated with neurological scores in patients with SCI. Our findings indicated that SCI could result in VN-related FNC alterations, revealing the possible mechanism for VFT in rehabilitation of patients with SCI and increasing the training efficacy and promoting rehabilitation for SCI.

Enhancing task fMRI individual difference research with neural signatures

Task-based functional magnetic resonance imaging (tb-fMRI) has advanced our understanding of brain-behavior relationships. Standard tb-fMRI analyses suffer from limited reliability and low effect sizes, and machine learning (ML) approaches often require thousands of subjects, restricting their ability to inform how brain function may arise from and contribute to individual differences. Using data from 9,024 early adolescents, we derived a classifier ('neural signature') distinguishing between high and low working memory loads in an emotional n-back fMRI task, which captures individual differences in the separability of activation to the two task conditions. Signature predictions were more reliable and had stronger associations with task performance, cognition, and psychopathology than standard estimates of regional brain activation. Further, the signature was more sensitive to psychopathology associations and required a smaller training sample (N=320) than standard ML approaches. Neural signatures hold tremendous promise for enhancing the informativeness of tb-fMRI individual differences research and revitalizing its use.

The unity/diversity framework of executive functions: behavioral and neural evidence in older adults

Executive functions (EFs), encompassing inhibition, shifting, and updating as three fundamental subdomains, are typically characterized by a unity/diversity construct. However, given the dedifferentiation trend observed in aging, it remains controversial whether the construct of EFs in older adults becomes unidimensional or maintains unity/diversity. This study aims to explore and validate the construct of EFs in older adults. At the behavioral level, we conducted confirmatory factor analysis on data from 222 older adults who completed six tasks specifically targeting inhibition, shifting, and updating. One unidimensional model and six unity/diversity models of EFs were evaluated. Our results indicated that the EFs of older adults demonstrated greater congruence with the unity/diversity construct. At neural level, thirty older adults completed three thematically consistent fMRI tasks, targeting three subdomains of EFs respectively. Multivariate pattern analysis showed that rostromedial prefrontal cortex robustly showed similar neural representation across different tasks (unity). Meanwhile, the three EF domains were encoded by distinct global neural representation and the lateral prefrontal cortex play a crucial role in classification (diversity). These findings underscore the unity/diversity framework of EFs in older adults and offer important insights for designing interventions aimed at improving EFs in this population.

Symptom-based depression subtypes: brain dynamic specificity and its association with gene expression profiles

At least 227 combinations of symptoms meet the criteria for Major Depressive Disorder (MDD). However, in clinical practice, patients consistently present symptoms in a regular rather than random manner, and the neural basis underlying the MDD subtypes remains unclear. To help clarify the neural basis, patients with MDD were clustered by symptom combinations to investigate the neural underpinning of each subtype using functional resonance imaging (fMRI). Four symptom-based subtypes of MDD were identified using latent profile analysis according to the clinical scales. Subsequently, brain dynamics were evaluated using fMRI, and the dysregulations in attention and limbic network were observed among the subtypes. Correlation between brain dynamics and symptom combinations was then assessed via canonical correlation analysis (CCA). The brain-symptom correlation was higher when evaluated in subtypes (r = 0.77 to 0.92) compared to the entire group (r = 0.5). The loading weight in CCA showed that dynamics in transmodal networks contributed the most to the correlation in the subtypes characterized by typical depression symptoms, whereas unimodal networks contributed the most to subtypes characterized by anxiety and insomnia. Finally, gene expression underlying the CCA model, along with its biological encoding process, performed using a postmortem gene expression atlas revealed distinct gene enrichments for different subtypes. These findings highlight that distinct symptom clusters in MDD have specific neural correlates, providing insights into depression's heterogeneous diagnosis and precision medicine opportunities.

The effect of transcranial direct current stimulation and inhibitory control training on depression and anxiety among post-stroke individuals

BACKGROUND

Recent research has highlighted the role of fronto-parietal brain networks and cognitive control in mood disorders. Transcranial direct current stimulation (tDCS) and computer-based cognitive training are used in post-stroke rehabilitation. This study examined the combined effects ofof computer-based inhibitory control training (ICCT) and anodal tDCS on post-stroke depression and anxiety.

METHODS

Thirty-five participants were randomly assigned to one of three groups: active tDCS treatment (A), sham tDCS treatment with ICCT (T), or active tDCS with ICCT (AT), for a duration of ten days. Primary outcome measures included the Beck Depression Inventory (BDI), Hamilton Depression Rating Scale (HAM-D), and Spielberger's State-Trait Anxiety Inventory (STAI-S/T). Statistical analysis was performed using a Mixed-model Analysis of Variance, with supplementary Bayesian analysis.

RESULTS

The AT group showed a significant improvement in BDI scores (p < .001), whereas no significant effects were observed on the HAM-D, STAI-T, or STAI-S scales.

CONCLUSIONS

The combination of tDCS and ICCT reduced depressive symptoms as measured by the BDI; while no significant effects were found with either treatment alone. Further research is needed to explore the mechanisms behind the synergistic effects in the treatment of post-stroke mood disorders.

Resting-state functional connectivity between the frontoparietal network and the default mode network is aberrantly increased in ankylosing spondylitis

Lower back pain comprises the majority of the disease burden of patients with ankylosing spondylitis (AS), while the alterations of the large-scale brain networks could be implicated in the neuropathophysiology of pain. The frontoparietal network (FPN) is known as a pain modulation hub, with key nodes dorsolateral prefrontal cortex (dlPFC) and ventrolateral prefrontal cortex (vlPFC) participating in the pain modulation and reappraisal process. In this study, we adopted the analytical approaches of independent component analysis (ICA) and seed-based correlation analysis (SCA) to examine the resting-state functional connectivity (rsFC) of the large-scale brain networks, notably FPN, between 82 AS patients and 61 healthy controls (HCs). We also investigated the correlation between the rsFC and the clinical measures of AS patients. Both ICA and SCA consistently showed that the rsFC between FPN and mPFC, a key node of the default mode network (DMN), was significantly increased in AS. In addition, SCA also identified a cluster at the right posterior lobe of cerebellum which exhibited increased rsFC with the posterior cingulate cortex, and the right lateral prefrontal cortex also showed increased rsFC with the right dlPFC. Correlation analysis showed that the rsFC between mPFC and the left anterior prefrontal cortex was significantly correlated with C-reactive protein in AS. The increased FPN-DMN connectivity could contribute to the neuropathophysiology of lower back pain in AS, with potential association with faulty pain modulation and reappraisal mechanisms facilitated by the FPN.

Age-related differences in eye blink-related neural activity and functional connectivity during driving

Driving is a complex task that requires effective neural processing and coordination, which degrade with aging. Previous studies suggest that age-related changes in cognitive and motor functions can influence driving performance. Herein, we investigated age-related differences and differences between reactive and proactive driving in blink behavior-related potentials, and source-level functional connectivity. Seventy-six subjects participated in two experiments with reactive (19 young, 28 older) and proactive (16 young, 13 older) driving scenarios, consisting of a lane-keeping task with either varying levels of crosswind or curve road, respectively. While blink rate analysis revealed no significant age or driving condition effects, blink duration was notably longer in younger participants. Also, significant age effects were observed in blink-related potentials, mainly in the frontal N2 and occipital P0 and P2 components, with higher amplitudes in younger participants, signifying more efficient neural processing. The parietal N2 component showed significant age and interaction effects, with older individuals showing higher amplitudes in reactive conditions, potentially due to increased cognitive effort and attentional demands. Furthermore, functional connectivity analysis revealed that aging most significantly affects the visual network in the beta band. More specifically, younger participants showed an increase in the clustering coefficient and degrees of the networks, reflecting more robust neural network integration. This pattern of higher connectivity measures in younger participants was also observed in the default mode, control, and limbic networks. Conversely, the dorsal attention network in the theta band showed an increased degree and clustering coefficient in older adults, which could indicate a compensatory mechanism for maintaining cognitive demands. This study highlights the impact of aging on neural activity and connectivity characteristics during driving and emphasizes the requirement of age-tailored interventions, aimed to improve driving safety.

Sleep deprivation impairs spatial cognitive processing and Alters brain connectivity in table tennis athletes

Spatial cognitive ability is critical for table tennis athletes to achieve excellent competitive performance, and sleep may be an important factor influencing this ability. This study investigated the impact of 36h sleep deprivation on the spatial cognitive processing of 20 s-level table tennis athletes, using event-related potentials and functional connectivity analysis to assess changes in cognitive resource allocation and inter-regional brain coordination before and after sleep deprivation. The results showed that sleep deprivation significantly prolonged reaction time and led to a decrease in P3 amplitude, reflecting a reduction in participants' attentional resource allocation and cognitive processing capacity. Functional connectivity analysis further revealed that β frequency band functional connectivity between the frontal and occipital regions significantly decreased after sleep deprivation, indicating reduced brain efficiency in processing spatial information. After 36 h of SD, the spatial cognitive ability of table tennis athletes was impaired. SD not only led to a reduction in the allocation of attentional resources and cognitive processing capabilities in these athletes, but also weakened functional connectivity between the frontal and occipital lobes of the brain.

Cytoarchitectonic gradients of laminar degeneration in behavioural variant frontotemporal dementia

Behavioural variant frontotemporal dementia (bvFTD) is a clinical syndrome caused primarily by either tau (bvFTD-tau) or transactive response DNA-binding protein of 43 kDa (TDP-43) (bvFTD-TDP) proteinopathies. We previously found that lower cortical layers and dorsolateral regions accumulate greater tau than TDP-43 pathology; however, the patterns of laminar neurodegeneration across diverse cytoarchitecture in bvFTD are understudied. We hypothesized that bvFTD-tau and bvFTD-TDP have distinct laminar distributions of pyramidal neurodegeneration along cortical gradients, a topological order of cytoarchitectonic subregions based on increasing pyramidal density and laminar differentiation. Here, we tested this hypothesis in a frontal cortical gradient consisting of five cytoarchitectonic types (i.e. periallocortex, agranular mesocortex, dysgranular mesocortex, eulaminate-I isocortex and eulaminate-II isocortex) spanning the anterior cingulate, paracingulate, orbitofrontal and mid-frontal gyri in bvFTD-tau (n = 27), bvFTD-TDP (n = 47) and healthy controls (n = 32). We immunostained all tissue for total neurons (NeuN; neuronal-nuclear protein) and pyramidal neurons (SMI32; non-phosphorylated neurofilament) and digitally quantified NeuN-immunoreactivity (ir) and SMI32-ir in supragranular II-III, infragranular V-VI and all I-VI layers in each cytoarchitectonic type. We used linear mixed-effects models adjusted for demographic and biological variables to compare SMI32-ir between groups and examine relationships with the cortical gradient, long-range pathways and clinical symptoms. We found regional and laminar distributions of SMI32-ir expected for healthy controls, validating our measures within the cortical gradient framework. The SMI32-ir loss was relatively uniform along the cortical gradient in bvFTD-TDP, whereas SMI32-ir decreased progressively along the cortical gradient of bvFTD-tau and included greater SMI32-ir loss in supragranular eulaminate-II isocortex in bvFTD-tau versus bvFTD-TDP (P = 0.039). Using a ratio of SMI32-ir to model known long-range connectivity between infragranular mesocortex and supragranular isocortex, we found a larger laminar ratio in bvFTD-tau versus bvFTD-TDP (P = 0.019), suggesting that select long-projecting pathways might contribute to isocortical-predominant degeneration in bvFTD-tau. In cytoarchitectonic types with the highest NeuN-ir, we found lower SMI32-ir in bvFTD-tau versus bvFTD-TDP (P = 0.047), suggesting that pyramidal neurodegeneration might occur earlier in bvFTD-tau. Lastly, we found that reduced SMI32-ir was related to behavioural severity and frontal-mediated letter fluency, not temporal-mediated confrontation naming, demonstrating the clinical relevance and specificity of frontal pyramidal neurodegeneration to bvFTD-related symptoms. Our data suggest that loss of neurofilament-rich pyramidal neurons is a clinically relevant feature of bvFTD that worsens selectively along a frontal cortical gradient in bvFTD-tau, not bvFTD-TDP. Therefore, tau-mediated degeneration might preferentially involve pyramidal-rich layers that connect more distant cytoarchitectonic types. Moreover, the hierarchical arrangement of cytoarchitecture along cortical gradients might be an important neuroanatomical framework for identifying which types of cells and pathways are involved differentially between proteinopathies.

The power of music: impact on EEG signals

INTRODUCTION

Music is known to impact attentional state without conscious awareness. Listening to music encourages the brain to secrete neurotransmitters improving cognition and emotion.

AIM OF WORK

Analysis of QEEG band width while listening to two music types, identifying different cortical areas activated and which genre has a similar effect to relaxed EEG.

METHODS

This is a cross-section interventional analytic study including 76 normal subjects, 55 of them are females (72.37%). Participants listened to 10 min of a single audio track during EEG recording, consisting of (1 min of silence, 3 min of Egyptian folk music, 3 min of silence, then 3 min of Egyptian instrumental classic music (without any lyrics). We analyzed QEEG bands at each brain region during different tracks. The power ratio index (PRI) was calculated for each region, and then the interhemispheric difference was compared.

RESULTS

The participants' ages ranged from 15 to 26 with a mean 16.73 ± 2.37 years. PRI showed a significant increase in the frontal and occipital regions during listening to folk music compared to the silent epoch, where p < 0.001 and p = 0.023, respectively. In the frontal and temporal regions, the classic music epoch evoked the highest PRI interhemispheric difference compared to the folk music epoch, where p = 0.004 and p < 0.001, respectively.

CONCLUSION

Egyptian folk music has significantly slowed the brain rhythm, particularly in the frontal region, compared to classic music, supporting the hypothesis of a momentary reduction of cognitive capacities by the noise. Classic music was evidently associated with a relaxed state EEG.

Neural mechanisms underlying cognitive impairment in depression and cognitive benefits of exercise intervention

Depression is associated with functional brain impairments, although comprehensive studies remain limited. This study reviews neural mechanisms underlying cognitive impairment in depression and identifies associated activation abnormalities in brain regions. The study also explores the underlying neural processes of cognitive benefits of exercise intervention for depression. Executive function impairments, including working memory, inhibitory control and cognitive flexibility are associated with frontal cortex and anterior cingulate areas, especially dorsolateral prefrontal cortex. Depression is associated with certain neural impairments of reward processing, especially orbitofrontal cortex, prefrontal cortex, nucleus accumbens and other striatal regions. Depressed patients exhibit decreased activity in the hippocampus during memory function. Physical exercise has been found to enhance memory function, executive function, and reward processing in depression patients by increasing functional brain regions and the brain-derived neurotrophic factor (BDNF) as a nutritional factor also plays a key role in exercise intervention. The study documents neurophysiological mechanisms behind exercise intervention's improved functions. In summary, the study provides insights into neural mechanisms underlying cognitive impairments in depression and the effectiveness of exercise as a treatment.

Intermittent theta burst stimulation for negative symptoms in schizophrenia patients with mild cognitive impairment: a randomized controlled trail

Background

This study aims to evaluate the intervention effect of intermittent Theta burst stimulation (iTBS) on bilateral dorsomedial prefrontal cortex (DMPFC) for negative symptoms in schizophrenia using functional near-infrared spectroscopy (fNIRS) to confirm the therapeutic significance of DMPFC in treating negative symptoms and provide new evidence for schizophrenia treatment and research.

Method

Thirty-nine schizophrenia patients with negative symptoms and mild cognitive impairment were randomly divided into a treatment group (n=20) and a control group (n=19). The treatment group received iTBS in bilateral DMPFC. The control group received the sham treatment. Negative symptoms, cognitive function, emotional state, and social function were assessed at pre-treatment, post-treatment, 4-, 8-, and 12-week follow-ups. Brain activation in regions of interest (ROIs) was evaluated through verbal fluency tasks. Changes in scale scores were analyzed by repeated measures ANOVA.

Result

After 20 sessions of iTBS, the Scale for the Assessment of Negative Symptoms (SANS) total and sub-scale scores significantly improved in the treatment group, with statistically significant differences. SANS scores differed significantly between pre- and post-treatment in both groups, with post-treatment scores markedly lower than pre-treatment and better efficacy in the treatment group. However, there was no significant difference in cognitive function, emotional state, and social function. ROIs did not differ significantly between groups before intervention. After treatment, prefrontal cortex activation was significantly higher in the treatment group than in controls, with a statistically significant difference. Regarding functional connectivity, the small-world properties Sigma and Gamma were enhanced.

Conclusion

iTBS on bilateral DMPFC can effectively alleviate negative symptoms and enhance prefrontal cortex activation and the small-world properties in patients of schizophrenia.

Neural Variability and Cognitive Control in Individuals With Opioid Use Disorder

Importance

Opioid use disorder (OUD) impacts millions of people worldwide. Prior studies investigating its underpinning neural mechanisms have not often considered how brain signals evolve over time, so it remains unclear whether brain dynamics are altered in OUD and have subsequent behavioral implications.

Objective

To characterize brain dynamic alterations and their association with cognitive control in individuals with OUD.

Design, Setting, and Participants

This case-control study collected functional magnetic resonance imaging (fMRI) data from individuals with OUD and healthy control (HC) participants. The study was performed at an academic research center and an outpatient clinic from August 2019 to May 2024.

Exposure

Individuals with OUD were all recently stabilized on medications for OUD (<24 weeks).

Main Outcomes and Measures

Recurring brain states supporting different cognitive processes were first identified in an independent sample with 390 participants. A multivariate computational framework extended these brain states to the current dataset to assess their moment-to-moment engagement within each individual. Resting-state and naturalistic fMRI investigated whether brain dynamic alterations were consistently observed in OUD. Using a drug cue paradigm in participants with OUD, the association between cognitive control and brain dynamics during exposure to opioid-related information was studied. Variations in continuous brain state engagement (ie, state engagement variability [SEV]) were extracted during resting-state, naturalistic, and drug-cue paradigms. Stroop assessed cognitive control.

Results

Overall, 99 HC participants (54 [54.5%] female; mean [SD] age, 31.71 [12.16] years) and 76 individuals with OUD (31 [40.8%] female; mean [SD] age, 39.37 [10.47] years) were included. Compared with HC participants, individuals with OUD demonstrated consistent SEV alterations during resting-state (99 HC participants; 71 individuals with OUD; F4,161 = 6.83; P < .001) and naturalistic (96 HC participants; 76 individuals with OUD; F4,163 = 9.93; P < .001) fMRI. Decreased cognitive control was associated with lower SEV during the rest period of a drug cue paradigm among 70 participants with OUD. For example, lower incongruent accuracy scores were associated with decreased transition SEV (ρ58 = 0.34; P = .008).

Conclusions and Relevance

In this case-control study of brain dynamics in OUD, individuals with OUD experienced greater difficulty in effectively engaging various brain states to meet changing demands. Decreased cognitive control during the rest period of a drug cue paradigm suggests that these individuals had an impaired ability to disengage from opioid-related information. The current study introduces novel information that may serve as groundwork to strengthen cognitive control and reduce opioid-related preoccupation in OUD.

Exploring the links among brain iron accumulation, cognitive performance, and dietary intake in older adults: A longitudinal MRI study

This study evaluated longitudinal brain iron accumulation in older adults, its association with cognition, and the role of specific nutrients in mitigating iron accumulation. MRI-based, quantitative susceptibility mapping estimates of brain iron concentration were acquired from seventy-two healthy older adults (47 women, ages 60-86) at a baseline timepoint (TP1) and a follow-up timepoint (TP2) 2.5-3.0 years later. Dietary intake was evaluated at baseline using a validated questionnaire. Cognitive performance was assessed at TP2 using the uniform data set (Version 3) neuropsychological tests of episodic memory (MEM) and executive function (EF). Voxel-wise, linear mixed-effects models, adjusted for longitudinal gray matter volume alterations, age, and several non-dietary lifestyle factors revealed brain iron accumulation in multiple subcortical and cortical brain regions, which was negatively associated with both MEM and EF performance at T2. However, consumption of specific dietary nutrients at TP1 was associated with reduced brain iron accumulation. Our study provides a map of brain regions showing iron accumulation in older adults over a short 2.5-year follow-up and indicates that certain dietary nutrients may slow brain iron accumulation.

Alexithymia: Toward an Experimental, Processual Affective Science with Effective Interventions

Alexithymia is a multi-dimensional personality trait involving difficulty identifying feelings, difficulty describing feelings, and an externally oriented thinking style. Poor fantasy life is debated as another facet. For over 50 years, the alexithymia literature has examined how alexithymia-related disturbances in perceiving and expressing feelings contribute to mental and physical disorders. We review the current understanding of alexithymia-including its definition, etiology, measurement, and vulnerabilities for both mental and physical illness-and its treatment. We emphasize the importance of further experimental and processual affective science research that (a) emphasizes facet-level analysis toward an understanding of the nuanced bases of alexithymia effects on neural, cognitive, and behavioral processes; (b) distinguishes between emotion deficits and emotion over-responding, including when over-responding is functional; and (c) clarifies when and how impairments occur for neutral and positively valenced information or contexts. Taken as a whole, a clarification of these issues will provide clear directions for effective and tailored alexithymia interventions.

Computational Modeling of the Prefrontal-Cingulate Cortex to Investigate the Role of Coupling Relationships for Balancing Emotion and Cognition

Within the prefrontal-cingulate cortex, abnormalities in coupling between neuronal networks can disturb the emotion-cognition interactions, contributing to the development of mental disorders such as depression. Despite this understanding, the neural circuit mechanisms underlying this phenomenon remain elusive. In this study, we present a biophysical computational model encompassing three crucial regions, including the dorsolateral prefrontal cortex, subgenual anterior cingulate cortex, and ventromedial prefrontal cortex. The objective is to investigate the role of coupling relationships within the prefrontal-cingulate cortex networks in balancing emotions and cognitive processes. The numerical results confirm that coupled weights play a crucial role in the balance of emotional cognitive networks. Furthermore, our model predicts the pathogenic mechanism of depression resulting from abnormalities in the subgenual cortex, and network functionality was restored through intervention in the dorsolateral prefrontal cortex. This study utilizes computational modeling techniques to provide an insight explanation for the diagnosis and treatment of depression.

Representation of Anticipated Rewards and Punishments in the Human Brain

Subjective value is a core concept in neuroeconomics, serving as the basis for decision making. Despite the extensive literature on the neural encoding of subjective reward value in humans, the neural representation of punishment value remains relatively understudied. This review synthesizes current knowledge on the neural representation of reward value, including methodologies, involved brain regions, and the concept of a common currency representation of diverse reward types in decision-making and learning processes. We then critically examine existing research on the neural representation of punishment value, highlighting conceptual and methodological challenges in human studies and insights gained from animal research. Finally, we explore how individual differences in reward and punishment processing may be linked to various mental illnesses, with a focus on stress-related psychopathologies. This review advocates for the integration of both rewards and punishments within value-based decision-making and learning frameworks, leveraging insights from cross-species studies and utilizing ecological gamified paradigms to reflect real-life scenarios.

Reconfiguration of brain network dynamics in bipolar disorder: a hidden Markov model approach

Bipolar disorder (BD) is a neuropsychiatric disorder characterized by severe disturbance and fluctuation in mood. Dynamic functional connectivity (dFC) has the potential to more accurately capture the evolving processes of emotion and cognition in BD. Nevertheless, prior investigations of dFC typically centered on larger time scales, limiting the sensitivity to transient changes. This study employed hidden Markov model (HMM) analysis to delve deeper into the moment-to-moment temporal patterns of brain activity in BD. We utilized resting-state functional magnetic resonance imaging (rs-fMRI) data from 43 BD patients and 51 controls to evaluate the altered dynamic spatiotemporal architecture of the whole-brain network and identify unique activation patterns in BD. Additionally, we investigated the relationship between altered brain dynamics and structural disruption through the ridge regression (RR) algorithm. The results demonstrated that BD spent less time in a hyperconnected state with higher network efficiency and lower segregation. Conversely, BD spent more time in anticorrelated states featuring overall negative correlations, particularly among pairs of default mode network (DMN) and sensorimotor network (SMN), DMN and insular-opercular ventral attention networks (ION), subcortical network (SCN) and SMN, as well as SCN and ION. Interestingly, the hypoactivation of the cognitive control network in BD may be associated with the structural disruption primarily situated in the frontal and parietal lobes. This study investigated the dynamic mechanisms of brain network dysfunction in BD and offered fresh perspectives for exploring the physiological foundation of altered brain dynamics.

Error monitoring and response inhibition in adolescents with bipolar disorders: An ERP study

Cognitive control develops throughout adolescence, a high-risk period for bipolar disorders (BD) onset. Despite neurobehavioral abnormalities in adults with BD, there is minimal research investigating deviations in cognitive control in adolescents with BD. Cognitive control involves numerous processes. Identifying the specific neural abnormalities in adolescent BD could provide precise targets for novel interventions that improve illness outcomes. The present study administered a Go/No-Go (GNG) task to 98 adolescents (44 BD; 54 controls) to activate response inhibition and error processes and recorded EEG for event-related potentials (ERPs) analysis. Stimulus-locked N2 and P3 (response inhibition) and response-locked error-related negativity (ERN; early error detection) and error positivity (Pe; conscious error detection) were analyzed. Adolescents with BD had attenuated Pe mean amplitudes following failed inhibition trials. There were no group differences in other ERP amplitudes, including N2, P3, and ERN. The pattern of findings implicates conscious error detection impairment in adolescents with BD, without support for deficits in more automatic, earlier error detection. Impaired conscious error detection in adolescents with BD may be an early expression of BD pathophysiology and a possible intervention target for cognitive rehabilitation. Further studies are needed to examine Pe in BD across the lifetime.

Deciphering network dysregulations and temporo-spatial dynamics in disorders of consciousness: insights from minimum spanning tree analysis

Objectives

The neural mechanism associated with impaired consciousness is not fully clear. We aim to explore the association between static and dynamic minimum spanning tree (MST) characteristics and neural mechanism underlying impaired consciousness.

Methods

MSTs were constructed based on full-length functional magnetic resonance imaging (fMRI) signals and fMRI signal segments within each time window. Global and local measures of static MSTs, as well as spatio-temporal interaction characteristics of dynamic MSTs were investigated.

Results

A disruption or an alteration in the functional connectivity, the decreased average coupling strength and the reorganization of hub nodes were observed in patients with minimally conscious state (MCS) and patients with vegetative state (VS). The analysis of global and local measures quantitatively supported altered static functional connectivity patterns and revealed a slower information transmission efficiency in both patient groups. From a dynamic perspective, the spatial distribution of hub nodes exhibited relative stability over time in both normal and patient populations. The increased temporal variability in multiple brain regions within resting-state networks associated with consciousness was detected in MCS patients and VS patients, especially thalamus. As well, the increased spatial variability in multiple brain regions within these resting-state networks was detected in MCS patients and VS patients. In addition, local measure and spatio-temporal variability analysis indicated that the differences in network structure between two groups of patients were mainly in frontoparietal network and auditory network.

Conclusion

Our findings suggest that altered static and dynamic MST characteristics may shed some light on neural mechanism underlying impaired consciousness.

Striatal stimulation enhances cognitive control and evidence processing in rodents and humans

Brain disorders, in particular mental disorders, might be effectively treated by direct electrical brain stimulation, but clinical progress requires understanding of therapeutic mechanisms. Animal models have not helped, because there are no direct animal models of mental illness. Here, we propose a potential path past this roadblock, by leveraging a common ingredient of most mental disorders: impaired cognitive control. We previously showed that deep brain stimulation (DBS) improves cognitive control in humans. We now reverse translate that result using a set-shifting task in rats. DBS-like stimulation of the midstriatum improved reaction times without affecting accuracy, mirroring our human findings. Impulsivity, motivation, locomotor, and learning effects were ruled out through companion tasks and model-based analyses. To identify the specific cognitive processes affected, we applied reinforcement learning drift-diffusion modeling. This approach revealed that DBS-like stimulation enhanced evidence accumulation rates and lowered decision thresholds, improving domain-general cognitive control. Reanalysis of prior human data showed that the same mechanism applies in humans. This reverse/forward translational model could have near-term implications for clinical DBS practice and future trial design.

Altered default-mode and frontal-parietal network pattern underlie adaptiveness of emotion regulation flexibility following task-switch training

Emotion regulation flexibility (ERF) refers to one's ability to respond flexibly in complex environments. Adaptiveness of ERF has been associated with cognitive flexibility, which can be improved by task-switching training. However, the impact of task-switching training on ERF and its underlying neural mechanisms remain unclear. To address this issue, we examined the effects of training on individuals' adaptiveness of ERF by assessing altered brain network patterns. Two groups of participants completed behavioral experiments and resting-state fMRI before and after training. Behavioral results showed higher adaptiveness scores and network analysis observed a higher number of connectivity edges, in the training group compared to the control group. Moreover, we found decreased connectivity strength within the default mode network (DMN) and increased connectivity strength within the frontoparietal network (FPN) in the training group. Furthermore, the task-switch training also led to decreased DMN-FPN interconnectivity, which was significantly correlated to increased adaptiveness of ERF scores. These findings suggest that the adaptiveness of ERF can be supported by altered patterns with the brain network through task-switch training, especially the increased network segregation between the DMN and FPN.