Deception is a complex behavior that requires greater cognitive effort than truth-telling, with brain states dynamically adapting to external stimuli and cognitive demands. Investigating these brain states provides valuable insights into the brain's temporal and spatial dynamics. In this study, we designed an experiment paradigm to efficiently simulate lying and constructed a temporal network of brain states. We applied the Louvain community clustering algorithm to identify characteristic brain states associated with lie-telling, inverse-telling, and truth-telling. Our analysis revealed six representative brain states with unique spatial characteristics. Notably, two distinct states-termed truth-preferred and lie-preferred-exhibited significant differences in fractional occupancy and average dwelling time. The truth-preferred state showed higher occupancy and dwelling time during truth-telling, while the lie-preferred state demonstrated these characteristics during lie-telling. Using the average z-score BOLD signals of these two states, we applied generalized linear models with elastic net regularization, achieving a classification accuracy of 88.46%, with a sensitivity of 92.31% and a specificity of 84.62% in distinguishing deception from truth-telling. These findings revealed representative brain states for lie-telling, inverse-telling, and truth-telling, highlighting two states specifically associated with truthful and deceptive behaviors. The spatial characteristics and dynamic attributes of these brain states indicate their potential as biomarkers of cognitive engagement in deception.

The online version contains supplementary material available at 10.1007/s11571-025-10222-4.

Youth antisocial behavior strongly associates with conduct problems (CP) and callous-unemotional (CU) traits. While CP has links to broad cognitive impairments, CU traits have specific links with cognitive control and affective theory of mind (ToM) difficulties. Evidence suggests cognitive control limitations impact affective processing in ToM amongst youth with elevated CU traits. Here we sought to improve on those initial findings by leveraging a randomized dual-task (within-trial) design to replicate and extend prior findings.

In this double-blind, randomized controlled trial, 85 participants (47 % female) were stratified by sex and CU trait severity. The study employed a ToM task with cognitive, affective, and physical conditions, combined with an inhibitory processing task to tax cognitive control. Participants completed single and dual-task trials, counterbalanced to test within-subject effects. Primary hypotheses were tested with both CP and CU traits in the same model using repeated measure mixed effects to examine changes in accuracy and reaction time.

CU traits were uniquely associated with greater impairments in affective ToM under dual-task conditions, reflecting increased difficulty integrating affective information when cognitive demands were increased. CP associated with lower single ToM performance but no change during dual-task trials. Notably, participants resilient to dual-task effects reported fewer antisocial behaviors, even with elevated CU traits.

While appropriately powered for study aims, the sample was underpowered to detect any potential primary and secondary variant interactions on study outcomes.

These findings support a CU trait specific cognitive-affective interaction as a mechanism critical for understanding youth antisocial behavior.

Test anxiety is positively correlated with trait anxiety. However, the precise relationship between the two is not clear. Are they two independent constructs that share a high degree of comorbidity, or the same construct manifesting in different situations (e.g., test anxiety as a special type of trait anxiety)?

The present study employed two advanced analysis tools (latent profile analysis and network analysis) to evaluate the connectivity pattern between test anxiety and trait anxiety in a sample of adolescent students (N = 475, Mean age = 13.49).

The latent profile analysis revealed that all participants could be classified into three groups (low-risk, moderate-risk, and high-risk) based on their scores on two scales measuring test anxiety and trait anxiety, indicating a high degree of comorbidity between test and trait anxiety. The network analysis found that test anxiety and trait anxiety formed two relatively distinct communities, suggesting that they are two independent structures.

Together, this study provides a novel insight into the structural relationship between test anxiety and trait anxiety, indicating that while they are distinct constructs, they frequently coexist. The clinical implications for our understanding of the etiology, diagnosis and treatment of test and trait anxiety are discussed.

Adolescence is a pivotal phase marked by heightened vulnerability to the onset of psychiatric disorders. However, there are few transdiagnostic studies of dynamic brain networks across major psychiatric disorders during this phase.

We collected resting-state functional MRI data from 189 adolescent patients (61 with bipolar disorder, 73 with major depressive disorder, and 55 with schizophrenia) and 181 healthy adolescents. Functional networks were constructed using a state-of-art edge-centric dynamic functional connectivity (DFC) approach.

Four DFC states were identified for the healthy adolescents that were related to different behavioral and cognitive terms. Disorder-related alterations were observed in two states involving motor and somatosensory processing and one state involving various cognitive functions. Regardless of the state, the three patient groups exhibited lower FC that were mainly involved in edges between different functional subsystems and were predominantly linked to regions in the somatomotor network. The patients with major depressive disorder additionally showed increased FC that were primarily linked to default mode regions. Graph-based network analysis revealed different patterns of disrupted small-world organization and altered nodal degree in the disorders in a state-dependent manner. The nodal degree alterations were correlated with the concentration of various neurotransmitters. Intriguingly, the noradrenaline concentration was engaged in the nodal degree alterations in each patient group. Finally, decreased FC involving regions in the somatomotor network showed significant correlations with clinical variables in the major depressive disorder patients.

These findings may help understand the developmental pathways associated with the heightened vulnerability to major psychiatric disorders during adolescence.

Cognitive inhibition is key to cognitive control in healthy and psychiatric conditions. Bipolar Disorder (BD) individuals display a range of inhibitory deficits and high levels of impulsivity across all stages of the disease, including euthymia.

We tested how the inhibition of heuristics in favor of analytical strategies influences the elaboration of sentences with logical quantifiers by means of a sentence-picture matching task in which the processing of quantified sentences containing the logical universal and particular quantifiers was required. Behavioral and brain oscillatory responses were assessed employing EEG recordings.

In Experiment 1, in a group of healthy volunteers, we demonstrated how the presence of a universal quantifier generates an inhibition, characterized by a high cognitive load, which is resolved at the expense of a poorer behavioral performance compared to a lower cognitive load and neutral control task. In Experiment 2, comparing healthy adults and BD patients, EEG time-frequency analysis showed a different modulation of the theta frequency band localized centrally in the medial frontal areas and representative of the different degrees of cognitive control between groups.

Electrophysiological description should be interpreted with caution in light of the high signal-to-noise ratio determined by the complexity of the task.

Even in euthymia, BD limited availability of resources for cognitive inhibition impacts the functionality of a fronto-parietal cortical network, responsible for cognitive control, and orchestrated by the activity of frontal areas synchronized in theta and beta frequency.

Major Depressive Disorder (MDD) and Bipolar Disorder (BD) exhibit overlapping depressive symptoms, complicating their differentiation in clinical practice. Traditional neuroimaging studies have focused on specific regions of interest, but few have employed whole-brain analyses like regional homogeneity (ReHo). This study aims to differentiate MDD from BD by identifying key brain regions with abnormal ReHo and using advanced machine learning techniques to improve diagnostic accuracy.

A total of 63 BD patients, 65 MDD patients, and 70 healthy controls were recruited from the Shanghai Mental Health Center. Resting-state functional MRI (rs-fMRI) was used to analyze ReHo across the brain. We applied Support Vector Machine (SVM) and SVM-Recursive Feature Elimination (SVM-RFE), a robust machine learning model known for its high precision in feature selection and classification, to identify critical brain regions that could serve as biomarkers for distinguishing BD from MDD. SVM-RFE allows for the recursive removal of non-informative features, enhancing the model's ability to accurately classify patients. Correlations between ReHo values and clinical scores were also evaluated.

ReHo analysis revealed significant differences in several brain regions. The study results revealed that, compared to healthy controls, both BD and MDD patients exhibited reduced ReHo in the superior parietal gyrus. Additionally, MDD patients showed decreased ReHo values in the Right Lenticular nucleus, putamen (PUT.R), Right Angular gyrus (ANG.R), and Left Superior occipital gyrus (SOG.L). Compared to the MDD group, BD patients exhibited increased ReHo values in the Left Inferior occipital gyrus (IOG.L). In BD patients only, the reduction in ReHo values in the right superior parietal gyrus and the right angular gyrus was positively correlated with Hamilton Depression Scale (HAMD) scores. SVM-RFE identified the IOG.L, SOG.L, and PUT.R as the most critical features, achieving an area under the curve (AUC) of 0.872, with high sensitivity and specificity in distinguishing BD from MDD.

This study demonstrates that BD and MDD patients exhibit distinct patterns of regional brain activity, particularly in the occipital and parietal regions. The combination of ReHo analysis and SVM-RFE provides a powerful approach for identifying potential biomarkers, with the left inferior occipital gyrus, left superior occipital gyrus, and right putamen emerging as key differentiating regions. These findings offer valuable insights for improving the diagnostic accuracy between BD and MDD, contributing to more targeted treatment strategies.

Anhedonia is a core symptom of major depressive disorder (MDD), which has been shown to be associated with abnormalities in cortical morphology. However, the correlation between cortical thickness (CT) changes with anhedonia in MDD and gene expression remains unclear.

We investigated the link between brain-wide gene expression and CT correlates of anhedonia in individuals with MDD, using 7 Tesla neuroimaging and a publicly available transcriptomic dataset. The interest-activity score was used to evaluation MDD with high anhedonia (HA) and low anhedonia (LA). Nineteen patients with HA, nineteen patients with LA, and twenty healthy controls (HC) were enrolled. We investigated CT alterations of anhedonia subgroups relative to HC and related cortical gene expression, enrichment and specific cell types. We further used Neurosynth and von Economo-Koskinas atlas to assess the meta-analytic cognitive functions and cytoarchitectural variation associated with anhedonia-related cortical changes.

Both patient subgroups exhibited widespread CT reduction, with HA manifesting more pronounced changes. Gene expression related to anhedonia had significant spatial correlations with CT differences. Transcriptional signatures related to anhedonia-associated cortical thinning were connected to mitochondrial dysfunction and enriched in adipogenesis, oxidative phosphorylation, mTORC1 signaling pathways, involving neurons, astrocytes, and oligodendrocytes. These CT alterations were significantly correlated with meta-analytic terms involving somatosensory processing and pain perception. HA had reduced CT within the somatomotor and ventral attention networks, and in agranular cortical regions.

These include measuring anhedonia using interest-activity score and employing a cross-sectional design.

This study sheds light on the molecular basis underlying gene expression associated with anhedonia in MDD, suggesting directions for targeted therapeutic interventions.

Hypertensive retinopathy (HR) is known to have effects on the brain's function. This neuroimaging investigation aimed to evaluate alterations in functional network connectivity and the topological properties of brain networks in in patients with HR.

The study involved twenty patients with HR and forty-one healthy controls (HC), all of whom underwent resting-state functional MRI scans. Independent component analysis and graph theory analysis were calculated to identify functional connectivity and topological property abnormalities between the two groups.

Compared to HC, patients with HR demonstrated increased internetwork functional connectivity. Furthermore, these patients showed increased intranetwork functional connectivity within the right precuneus of the default mode network. Graph theory analysis revealed that both groups demonstrated a small-world topology. However, significant differences were observed in global and regional network metrics in HR patients compared to HC.

These findings highlight the alterations in functional connectivity and topological properties of brain networks in patients with HR, offering valuable insights into the potential neural mechanisms underlying their condition.

Cognitive interference resolution (CIR) is the process of maintaining goal-directed focus despite the presence of distractions. While CIR has been extensively studied through localized activation analyses, its network-level dynamics remain underexplored with sufficient methodological diversity. In this study, we investigated the task-modulated intrinsic connectivity networks (ICNs) and their dynamic interactions with detailed subnetwork segmentation during CIR using fMRI data from 27 healthy adults performing the Multi-Source Interference Task (MSIT). We applied high-order group independent component analysis (ICA) to extract ICN subcomponents, followed by task-modulated component identification and dynamic functional connectivity analysis to examine network interactions. Our results reveal that the dorsal attention network (DAN) and cognitive control network (CCN) show increased activation and connectivity, while the default mode network (DMN) and limbic network exhibit decreased activation and connectivity. Additionally, the visual and cerebellum networks emerge as key intermediaries in CIR, as DAN and CCN strengthen their connectivity with these networks rather than directly interacting with each other. Furthermore, network reconfiguration patterns suggest functional segregation within the somatomotor network and CCN, indicating specialized subcomponent contributions. These findings provide a granular understanding of ICN activations and dynamic inter-network communication during CIR, offering new insights into the flexible reorganization of brain networks in response to cognitive interference.

Bullying and cyberbullying are serious public health concerns that involve more roles beyond the bully and the victim (pro-bullies, defenders, bystanders). However, students often perceive the phenomena as dyadic.

The purpose was to examine students' perceptions of different roles when observing bullying and cyberbullying scenes combining implicit (attention by using the eye-tracker) and explicit (verbal reports) measures.

We included 50 Italian students (aged 10-11).

Students watched 12 drawings of different types of bullying and cyberbullying while their gaze was tracked, and subsequently described each drawing verbally. We ran repeated measure ANOVAs to compare attentional indexes (fixation count, visit count and total fixation duration) in observing roles and Cochran's Q test to evaluate differences in the verbal identification of roles.

Overall, the victim and bully were the most observed and identified roles in every type of bullying and cyberbullying scenario. Concerning the other roles, a discrepancy was observed between the implicit and explicit measures since although it was greatly identified, the pro-bully received less attention, and while the bystander received great attention, it was mentioned less. Finally, the defender was more observed and identified in physical bullying and cyberbullying.

Our study points out for the first time the dyadic perception of the phenomena among adolescents using implicit and explicit measures and sheds light on differences among the roles in different forms of bullying. Further research including the eye-tracker would be worthwhile given the possibility of exploring the phenomena from different perspectives.

To identify reliable electroencephalography (EEG) biomarkers for attention deficit/hyperactivity disorder (ADHD) by investigating anomalous functional connectivity patterns and their clinical relevance.

Resting-state EEG data were collected from 74 children aged 6-12 (33 unmedicated ADHD; 41 typically developing). Functional connectivity was quantified using the imaginary part of coherency (ICOH). Machine learning (ML)-based support vector machine (SVM) modeling, regression, and mediation analyses linked connectivity features to symptom severity and diagnostic classification.

Children with ADHD exhibited beta (β) band hypo-connectivity in frontal regions (Fp2-F4, Fp1-Cz, F7-Cz) and theta (θ) band hyper-connectivity in left parietal-central networks (C3-P7, P3-P7, etc.). An SVM classifier achieved an average area under the curve of 0.89 using three connectivity features. Left parietal θ band hyper-connectivity (C3-P7) correlated with both inattention and hyperactivity/impulsivity and mediated their interrelationship.

ADHD is characterized by disrupted frontoparietal connectivity, with θ band hyper-connectivity in sensory-integration networks potentially compensating for impaired frontal regulation.

These findings highlight C3-P7 θ band connectivity as both a diagnostic and mechanistic biomarker, providing novel target for neurofeedback therapies and enhancing the differential diagnosis in neurodevelopmental disorders.

Automatic approaches to gaming-related cues are key factors in internet gaming disorder (IGD). Approach bias modification (ApBM) has been shown to reduce addictive behaviors, but its neurobiological effects remain poorly understood. This study examined changes in brain activities in the 'natural' state in IGD patients after ApBM.

Fifty-five (of 61) IGD patients were randomly assigned to the approach-avoidance task (AAT, n = 30) and sham-AAT (n = 25) groups. Participants completed the pre-test, five real/sham ApBM sessions, and the post-test. In the pre-and post-tests, fMRI data were collected while viewing gaming and neutral videos. Inter-subject correlation (ISC) and functional connectivity (FC) analyses were conducted to explore the ApBM-related changes.

ANOVA of behavioral data revealed that ApBM significantly decreased the approach bias and addiction scores. The ISC analyses revealed increased synchronization in the paracentral lobule, precuneus, and insula regions in the ATT group after ApBM. Additionally, decreased FC was observed between the insula and superior frontal gyrus, precuneus, and orbitofrontal cortex in the AAT group.

Preliminary findings suggest that ApBM may be effective in reducing automatic approach tendencies toward gaming cues, highlighting its potential as an intervention strategy. However, it is important to note that the neurobiological evidence in this study only provides a possible association, and the results should be interpreted with caution. Future research is needed to further examine the clinical efficacy of ApBM in IGD, whether as a stand-alone treatment or as an adjunct to formal therapy.

Humans can rapidly memorize numerous images, which is surprising considering the limited visual sampling of each image. To enhance the probability of recognition, it is crucial to focus on previously sampled locations most likely to support memory. How does the visuomotor system achieve this? To study this, we analyzed the eye movements of a group of neurotypical observers while they performed a natural scene memorization task. Using comprehensive gaze analysis and computational modeling, we show that observers traded off visual exploration for exploiting information at the most memorable scene locations with repeated viewing. Furthermore, both the explore-exploit trade-off and gaze consistency predicted accurate recognition memory. Finally, false alarms were predicted by confusion of the incoming visual information at fixated locations with previously sampled information from other images. Together, our findings shed light on the symbiotic relationship between attention and memory in facilitating accurate natural scene memory.

Regional neural response and network properties have traditionally been studied separately. However, growing evidence suggests a close interplay between regional activity and inter-regional connectivity. This study aimed to examine the relationship between global functional connectivity and regional spontaneous activity, termed the global-to-local relationship.

Resting-state fMRI data were parcellated using MOSI (modular analysis and similarity measurements), enabling multi-resolution functional partitioning. For each parcellated cluster, the mean amplitude of low-frequency fluctuations (node power) and its average functional connectivity with the remaining cortex (node strength) were computed. Correlation analyses assessed their relationship. A supplementary analysis was conducted on EEG data (1-30 Hz).

A significant negative correlation between node strength and regional power was observed in MRI datasets. One-sample t-tests confirmed robustness across different MOSI resolutions, with individual P values at the level 10-4 to 10-5. The negative relationship was also found in EEG data but was restricted to delta (1-4 Hz) and theta (4-8 Hz) bands.

This study introduces two key novel aspects. First, it applies MOSI to the entire cortex, enhancing the comprehensiveness of network analysis. Second, it examines the global influence on regional neural activity, rather than limiting the focus to a specific network.

A robust negative relationship between node strength and node power was consistently observed across both MRI and EEG datasets, particularly in lower frequency bands (up to 8 Hz). These findings suggest a framework for investigating how global connectivity shapes regional neural activity, with inhibitory coupling as a potential underlying mechanism.

Excessive use of short-video platforms not only impairs decision-making processes but also predisposes individuals to addictive behaviors. This study investigated the relationship between short-video addiction (SVA) symptoms and loss aversion (LA), delving into the underlying computational and neural mechanisms using the drift diffusion model (DDM) and the inter-subject representational similarity analysis (IS-RSA). Behavioral analyses revealed a significant negative correlation between SVA symptoms and the LA coefficient (lnλ). Additionally, the DDM-based drift rate (v) was found to mediate this relationship. Neuroimaging analyses further indicated that SVA symptoms were negatively associated with gain-related activity in the right precuneus, while positively correlating with loss-related activity in the right cerebellum and left postcentral gyrus. Notably, precuneus activation during gain processing mediated the relationship between SVA symptoms and both lnλ and drift rate. IS-RSA revealed that inter-subject variations in SVA symptoms were significantly associated with distinct activation patterns related to gain processing in the frontoparietal network (e.g., frontal pole, inferior frontal gyrus, and supramarginal gyrus) and motor network (e.g., precentral), as well as loss-related activation patterns in the motor networks (e.g., postcentral and pre-supplementary motor area). Similar patterns emerged when examining simultaneous gain and loss-related activation patterns. Mediation analyses further demonstrated that functional activation patterns in the motor network mediated the relationships between inter-subject variations in SVA symptoms and both loss-aversion and psychological processing patterns (e.g., decision threshold, drift rate, and non-decision time). These findings provide novel insights into the cognitive and neural mechanisms underlying the influence of SVA symptoms on loss aversion, and suggest the critical roles of evidence accumulation speed and specific brain activation patterns-particularly within the cognitive control and motor network-in shaping decision-making biases associated with addiction.

Amblyopia has effects on vision that extend from the processing of low-level visual features to higher level functions such as visual attention. In this narrative review, we focus on the impact of amblyopia on visual attention. A structured literature search revealed 28 articles reporting comparisons between amblyopia and normal vision control groups for a variety of visual attention tasks. Several of these articles also included neuroimaging measures. A review of these articles suggested that amblyopia does not affect behavioral performance of tasks with a low attentional load, such as cuing tasks, but deficits emerge for tasks with high demands on visual attention such as multiple object tracking. Deficits are not limited to the amblyopic eye but are also evident under fellow eye and binocular viewing conditions suggesting that abnormal early binocular visual experience can fundamentally alter the development of visual attention. Overall, the current literature suggests that amblyopia is associated with reduced visual attention resources. We raise the possibility that this attention resource deficit may be partially associated with an attentional demand for suppression of the amblyopic eye.

Previous research suggests that unexpected (deviant) sounds negatively affect reading performance by inhibiting saccadic planning, which models of reading agree takes place simultaneous to parafoveal processing. This study examined the effect of deviant sounds on foveal and parafoveal processing. Participants read single sentences in quiet, standard (repeated sounds), or deviant sound conditions (a new sound within a repeated sound sequence). Sounds were presented with a variable delay coincident with the onset of fixations on target words during a period when saccadic programming and parafoveal processing occurred. We used the moving window paradigm to manipulate the amount of information readers could extract from the parafovea (the entire sentence or a 13-character window of text). Global, sentence-level analyses showed typical disruption to reading by the window, and under quiet conditions similar effects were observed at the target and post-target word in the local analyses. Standard and deviant sounds also produced clear distraction effects of differing magnitudes at the target and post-target words, though at both regions, these effects were qualified by interactions. Effects at the target word suggested that with sounds, readers engaged in less effective parafoveal processing than under quiet. Similar patterns of effects due to standard and deviant sounds, each with a different time course, occurred at the post-target word. We conclude that distraction via auditory deviation causes disruption to parafoveal processing during reading, with such effects being modulated by the degree to which a sound's characteristics are more or less unique.

We aimed to establish if the electrophysiological activity resulting from the direct stimulation of the intraparietal sulcus and eliciting visual percepts is hemispheric-specific.

We tested nineteen participants. Each received 360 TMS pulses at phosphene threshold intensity over right and left IPS while recording EEG. After each pulse, participants had to report if they had seen a phosphene.

Parietal phosphene perception is associated with hemispheric-specific activations: phosphenes elicited by left TMS involve central and frontal electrodes at about 30 ms, and frontal, central and parieto-occipital electrodes from 120 to 250 ms; phosphenes elicited by right parietal TMS involve parietal and centro-parietal electrodes at about 60 ms, and frontal, central and parietal electrodes from 150 to 250 ms. Correlated Component Analysis shows that primary visual areas are not activated when phosphenes are produced by TMS over IPS.

Our results show that direct stimulation of IPS gives rise to sustained patterns of activity specific to the stimulated hemisphere. Moreover, elicited parietal phosphenes are associated with evoked activity specific to the stimulated hemisphere and located outside early visual processing areas.

This study highlights hemispheric differences in the electrophysiological dynamics related to parietal phosphenes, and shows that the dorsal pathway can give rise to visual conscious percepts.

This study aimed to investigate the functional alterations in the resting-state brain networks of flight trainees using the independent component analysis (ICA) method. A total of 33 flight trainees and 33 general college students were recruited. Resting-state fMRI data were collected using a 3.0 T MRI scanner. ICA was employed to extract resting-state brain network components, followed by statistical analyses. Fourteen physiologically independent components were identified during the ICA process and classified into nine networks. The flight trainees exhibited significantly increased activation in the right calcarine fissure within the ventral attention network (FWE corrected, P < 0.05). Moreover, the region of interest values of the differential brain region in flight trainees showed a significant positive correlation with the correct rate of the Berg Card Sorting Test (BCST) and a significant negative correlation with the BCST perseverative error (P < 0.05 for both). The significant activation of the right calcarine fissure of flight trainees may be associated with the high attentional demands of flight tasks. Flight trainees demonstrated superior executive function and attention allocation abilities, providing evidence of adaptive functional adjustments in the brain caused by professional activities.

Language can be processed with varying levels of attentional involvement; consequently, the interplay between the language and attentional systems in the brain has been extensively studied in spoken languages. However, in signed languages (SLs), this interplay is less well understood. Here, we use Constructed Action (CA) - a meaning-making strategy based on enactment - as a window into the attentional mechanisms recruited in signed language comprehension. We explored the attentional processing of CA by identifying the sequence of processes involved and in which stage CA and its types might be processed differently. Finally, we investigated the associations between the brain mechanisms of CA detection and their behavioral manifestations, as well as with components of attention of the Attention Network Test (ANT). We also measured the electrophysiological correlates of performance on an oddball CA detection task in deaf and hearing L1 signers. We found that processes involved in all signers' active detection of CA involved automatic (indexed by N1 and P2) and attention-based processes (indexed by N2s and P3s). N2 posterior bilateral were also more negative for tokens of overt CA than for PT-only signs, while P3a was more positive for all types of CA than for PT. No significant results were found regarding the ANT. We conclude that specific attentional involvement in CA detection is triggered by the increasing enacting elements and saliency involved in CA. This study yielded new insights into the functional interaction between the neural mechanisms underlying attentional control and those mediating CA processing in SL.

This meta-analysis examines the challenge of capturing brain activity in real-world and laboratory settings by integrating naturalistic neuroimaging and experimental data with behavioral measures to explore the predictive role of intersubject correlation (ISC) in attention. Using databases such as Web of Science and PubMed, we conducted a comprehensive search from January 2000 to July 2024. Our meta-analysis of 14 studies and 27 effect sizes reveals a significant positive correlation between ISC and attention (r = 0.65, p < 0.001), demonstrating that ISC serves as a reliable neural marker for attentional engagement under various experimental conditions. By incorporating naturalistic stimuli such as video clips and controlled laboratory tasks, we provide insights into the application of ISC to predict attention in ecologically-valid contexts. Moreover, our addition of behavioral data further enhances the understanding of how neural synchronization reflects attentional states. Our results underscore the potential of utilizing ISC to develop personalized assessments and interventions in educational and cognitive settings.

Recent evidence indicates that the intraparietal sulcus (IPS) may play a causal role in action stopping, potentially representing a novel neuromodulation target for inhibitory control dysfunctions. Here, we leverage intracranial recordings in human subjects to establish the timing and directionality of information flow between IPS and prefrontal and cingulate regions during action stopping. Prior to successful inhibition, information flows primarily from the inferior frontal gyrus (IFG), a critical inhibitory control node, to IPS. In contrast, during stopping errors the communication between IPS and IFG is lacking, and IPS is engaged by posterior cingulate cortex, an area outside of the classical inhibition network and typically associated with default mode. Anterior cingulate and orbitofrontal cortex also display performance-dependent connectivity with IPS. Our functional connectivity results provide direct electrophysiological evidence that IPS is recruited by frontal and anterior cingulate areas to support action plan monitoring and updating, and by posterior cingulate during control failures.

Background/Objectives: Visuomotor integration relies on synchronized proprioceptive and visual feedback during visually guided locomotion. How the human brain processes unimodal or asynchronous multimodal inputs during locomotion is unclear. Methods: Using high-density mobile electroencephalography (EEG) and motion capture in a virtual reality environment, we investigated electrocortical responses during altered treadmill gait speeds (0.5 and 1.5 m/s) and visual flow speeds (0.5×, 1×, and 1.5× gait speed) among 13 healthy human subjects. Experimental conditions included passive viewing of a moving virtual environment, walking in a stationary virtual environment, and walking in a moving environment with synchronous and asynchronous visual flow. Results: At faster gait speed, we identified reduced premotor, sensorimotor, and visual electrocortical beta-band spectral power (13-30 Hz) and greater premotor cortex theta power (4-8 Hz). At faster visual flow speeds, we identified reduced sensorimotor electrocortical beta-band spectral power, reduced alpha (8-13 Hz) and beta power, and greater gamma-band power (30-50 Hz) from the visual cortex. During visual flow and gait speed mismatches, sensorimotor and parietal alpha- and beta-band electrocortical spectral power decreased at faster gait speed. During treadmill walking at 1.5 m/s, parietal electrocortical spectral power increased when visual flow exceeded gait speed. Conclusions: Electrical brain dynamics during human gait identified distinct neural circuits for integrating kinesthetic and visual information during visuomotor conflicts, gated by the parietal cortex.

BackgroundAnxiety often exacerbates freezing of gait (FOG) in people with Parkinson's (PwP). Anxiety-related attentional processes and associated processing inefficiencies, like conscious movement processing (CMP) and ruminations, can substantially impact movement control. However, their impact on FOG remains largely unexplored.ObjectiveTo validate an adapted 10-item (1-5 Likert scale) Gait-Specific Attentional Profile (G-SAP) in PwP and assess if adapted G-SAP-subscales (Physiological Arousal, CMP, Rumination, and Processing Inefficiencies) are associated with self-reported FOG frequency.MethodsWe recruited 440 PwP (Mage = 65.5 ± 8.7; 5.8 ± 5.0 years since diagnosis) across the UK. Participants completed the adapted G-SAP and questionnaires on demographics, medical background, and FOG frequency. We assessed adapted G-SAP's internal consistency, structural validity, and subscale scores associations with FOG frequency.ResultsThe adapted G-SAP showed acceptable internal consistency (α≥0.66) and acceptable/good model fit (comparative fit index = 0.976). Physiological Arousal and CMP subscale scores presented weaker correlations for PwP with FOG (PwP + FOG, r = 0.52) compared to PwP without FOG (PwP-FOG, r = 0.77; p = 0.006). Higher Rumination (OR: 1.323, 95%CI: [1.214-1.440]) and Physiological Arousal (OR: 1.195, 95%CI:[1.037-1.377]) were significantly associated with higher FOG frequency, controlling for age, time since diagnosis and balance/gait problems.ConclusionsThe adapted G-SAP is reliable and convenient to measure and identify potentially maladaptive anxiety-related attentional processes that may impact FOG. Results suggest that PwP who experience more worrisome thoughts and greater physiological arousal in daily life are likelier to freeze. Compared to PwP-FOG, for PwP + FOG high physiological arousal was associated with reduced goal-directed focus of attention. Future research will determine if this is a causal risk factor.

Sleep deprivation (SD) impairs cognitive functions like attention and reaction speed, though some individuals exhibit a trait-like resilience to these effects. To explore the neurobiological basis of this resilience, we quantified cognitive performance using the Percentage Reaction Speed Change (PRSC) from the psychomotor vigilance test (PVT). We then examined the relationship between PRSC and ventral tegmental area (VTA) functional connectivity during 28 h of SD.

Forty-four healthy adults (21 females; age = 25.4 ± 5.6 years) underwent a resting-state functional MRI (rs-fMRI) to examine whole-brain VTA connectivity. Within the same week, participants completed a 28-hour SD protocol, during which PVT performance was measured. We examined the association between VTA connectivity and PRSC, with a focus on connections to the Primary Visual Cortex (V1) and Supplementary and Cingulate Eye Field (SCEF).

Greater VTA connectivity with the V1 and SCEF was associated with higher PRSC, suggesting that stronger VTA connectivity to these visual processing and cognitive control regions supports cognitive resilience to SD.

The VTA contributes to cognitive resilience during sleep deprivation through its connectivity with visual and cognitive control regions. These findings provide insight into neural mechanisms that help preserve cognitive performance under SD.

Hemispheric lateralization is linked to potential cognitive advantages. It is considered a driving force behind the generation of human intelligence. However, establishing quantitative links between the degree of lateralization and intelligence in humans remains elusive. In this study, we propose a framework that utilizes the functional aligned multidimensional representation space derived from hemispheric functional gradients to compute between-hemisphere distances within this space. Applying this framework to a large cohort (N = 777), we identified high functional divergence across the two hemispheres within the frontoparietal network. We found that both global divergence between the cerebral hemispheres and regional divergence within the multiple demand network were positively associated with fluid composite score and partially mediated the relationship between brain size and individual differences in fluid intelligence. Together, these findings deepen our understanding of hemispheric lateralization as a fundamental organizational principle of the human brain, providing empirical evidence for its role in supporting fluid intelligence.

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.

Subcortical arousal systems are known to play a key role in controlling sustained changes in attention and conscious awareness. Recent studies indicate that these systems have a major influence on short-term dynamic modulation of visual attention, but their role across sensory modalities is not fully understood. In this study, we investigated shared subcortical arousal systems across sensory modalities during transient changes in attention using block and event-related fMRI paradigms. We analyzed massive publicly available fMRI datasets collected while 1561 participants performed visual, auditory, tactile, and taste perception tasks. Our analyses revealed a shared circuit of subcortical arousal systems exhibiting early transient increases in activity in midbrain reticular formation and central thalamus across perceptual modalities, as well as less consistent increases in pons, hypothalamus, basal forebrain, and basal ganglia. Identifying these networks is critical for understanding mechanisms of normal attention and consciousness and may help facilitate subcortical targeting for therapeutic neuromodulation.

The vestibular system, one of the earliest sensory systems in vertebrates, is crucial for encoding head and trunk movements. Research in stroke patients with spatial attention deficits and studies manipulating vestibular signals in healthy individuals suggest that the vestibular system is also involved in orienting visuospatial attention. However, the specific interactions between vestibular and attentional systems and the consequences of vestibular pathologies on attentional functions are still poorly understood. In this study, we investigated the impact of vestibular disorders on the orienting of automatic (exogenous) and voluntary (endogenous) attention in patients (N = 16) with acute (AVS), episodic (EVS) or chronic (CVS) vestibular syndromes, who were compared to a control group (N = 16) of age-matched healthy participants. The two groups were assessed using endogenous and exogenous versions of the Posner cueing task. Cognitive functioning and anxiety were evaluated with the Montreal Cognitive Assessment (MoCA) and the Beck Anxiety Inventory (BAI), respectively. Vestibular patients exhibited selective impairments in maintaining voluntary attention in the endogenous task, particularly those with EVS and CVS, compared to the controls. In addition, vestibular alterations influenced the automatic right-lateralized attention system, as evidenced by a reduced rightward attentional bias in the exogenous task in vestibular patients. Anxiety, aging, or the overall cognitive function did not influence the observed attention deficits. The evidence that vestibular disorders differentially affect voluntary and automatic orienting of visuospatial attention has relevant implications for the assessment and treatment of patients with vestibular disorders, the rehabilitation of stroke patients with spatial attention deficits, and space research.

Physically salient stimuli are potent influences on behavior, but their negative impacts can be reduced in the presence of explicit goal-related cues. Here, we investigated whether goal-related cues associated with value are capable of insulating information from task-irrelevant abrupt onsets during two stages of information processing. Abrupt onsets were shown either after attention-directing cues and before a target (Experiment 1) or after a target that is to be remembered for later report (Experiment 2). The cues indicated the value associated with upcoming target locations, and they were either different in value, indicating that one was more valuable than the other, or equal in value. In both experiments, subjects were instructed to report the target that would earn them the most points (Experiment 1) or money (Experiment 2). In Experiment 1, performance suffered with equal cues, suggesting that orienting to multiple locations increases susceptibility to distraction from physically salient stimuli. In Experiment 2, the same pattern did not appear for abrupt onsets during the retention period; instead, the impact of the physically salient stimulus was dependent upon working memory capacity. The differential impact of abrupt onsets prior to (Experiment 1) and after (Experiment 2) encoding of value-related target locations suggest that physically salient task-irrelevant stimuli influence value-related information processing differently during orienting and maintenance.

Goal-directed visual attention is a fundamental cognitive process that demonstrates the brain's remarkable ability to prioritize visual information relevant to specific tasks or objectives. Despite its importance, there is a lack of comprehensive datasets to investigate the underlying neural mechanisms. Here, we present a large naturalistic visual search dataset in which rhesus macaques searched for targets among natural stimuli based on object categories using voluntary eye movements. The stimulus set included 40 images per category across four categories: faces, houses, flowers, and hands. We recorded activity from 6871 units in area V4, 8641 units in the inferior temporal cortex (IT), 5622 units in the orbital frontal cortex (OFC), and 9916 units in the lateral prefrontal cortex (LPFC). These units exhibited diverse receptive fields and selectivity for visual categories. Together, our extensive dataset provides a rich neuronal population across multiple brain areas, enabling a comprehensive analysis of the neural processes underlying goal-directed visual attention.

It is well understood that attentional selection is required to deploy visual attention to relevant objects within displays during visual search tasks. Interactive search, an extension of visual search, refers to tasks wherein an individual must manipulate items within their environment to uncover obscured information whilst searching for a target object. Here, we conducted two independent interactive search experiments where participants were asked to interact with virtual cubes to locate a target T shape embedded onto the side of one of the cubes. Our goal here was to investigate the drivers of attentional selection within interactive searches. To do so, we manipulated the effort required to rotate cubes (Experiment 1) and the quantity of shapes attached to the cubes (Experiment 2). Our findings suggest that the perceived effort required to interact with an object is an extremely strong driver of attentional selection within interactive search behaviors. Here, targets may be slower to be detected when that target is obscured within or by an object that conveys, in some shape or form, greater difficulty to examine compared with other objects. These findings provide an exciting first step towards understanding the factors that influence selection during interactive searches. Data and experimental code for all experiments in this study can be accessed online via this web address: https://osf.io/2zyvf/?view_only=ae4f4f2c36ab4e6aae5da3e99fb81988 . Experiments were not preregistered.

This pilot study explored the combined impact of arousal reappraisal intervention and transcranial direct current stimulation (tDCS) targeting the left dorsolateral prefrontal cortex (PFC) on state anxiety, challenge and threat appraisals, and performance under high pressure in esport contexts. Arousal reappraisal has previously been shown to enable individuals to interpret physiological arousal more constructively, while tDCS has demonstrated potential to increase the efficacy of psychological interventions.

A fully repeated measures study design was employed where participants experienced four different experimental interventions: tDCS with arousal reappraisal, tDCS with active control, sham stimulation with arousal reappraisal, and sham stimulation with active control.

Seventeen male Counter-Strike competitors participated in the study. Each participant received all four experimental intervention conditions, with measurements taken of state anxiety, challenge and threat appraisals, and esport performance under pressure.

The findings tentatively suggest that arousal reappraisal effectively reduces cognitive anxiety, promotes favourable challenge appraisals versus threat, and enhances esports performance. This effect appeared more pronounced when arousal reappraisal was combined with anodal tDCS.

Combining arousal reappraisal and tDCS may be a promising intervention for esports competitors facing performance pressure. The synergistic effects of these interventions warrant further investigation in larger samples.

The present study examined whether spatial processing in the unimpaired cognitive system is influenced by attentional load during multitasking. More specifically, it tested the hypothesis that high attentional load would induce spatial processing asymmetries in the form of a rightward attentional bias. We conducted two separate experiments on healthy adults (n = 101 and n = 98) by using web-based data collections. We capitalized on a condition of perceptual uncertainty to investigate the presence of these spatial asymmetries which cannot be easily detected under regular perceptual conditions. More specifically, we employed a primary audiovisual integration task, which involved presenting stimuli capable of eliciting the sound-induced flash illusion (i.e., task-relevant flashes accompanied by an incongruent number of sounds) on either the left or right side of the screen. This task enabled us to investigate audiovisual integration, but also indirectly provided an opportunity to sensitively explore spatial processing within a highly complex context. In Experiment 1, attentional load was increased by presenting stimuli to be retained before the audiovisual integration task (i.e., "offline" attentional load manipulation). Differently, in Experiment 2, attentional load was increased by having participants to perform visual discrimination during the audiovisual integration task (i.e., "online" attentional load manipulation). Attentional load was increased in a different way within each experiment to test the idea that more demanding tasks, albeit of different nature, would have similarly modulated performance. In both experiments, we replicated the increase of sound-induced flash illusion under high attentional load, which challenges the notion of an early and pre-attentive onset of the illusion. However, this effect was identical for left- and right-sided flashes, which speaks against the existence of load-induced spatial processing asymmetries in the unimpaired cognitive system. Given that both experiments yielded similar results, quantitative aspects of attentional engagement rather than the nature of the attentional resources involved seem to play a critical role.

Acute carbon monoxide poisoning (ACOP) is a significant contributor to acute poisoning incidents worldwide, with numerous patients suffering from cognitive impairment. Growing evidence indicates that patients with ACOP exhibit both disrupted functional connectivity and corpus callosum (CC) degeneration. Nevertheless, how interhemispheric connectivity is altered in ACOP and how such alterations relate to cognitive deficits remain largely unexplored. In this study, multimodal magnetic resonance imaging was performed on 30 patients with ACOP and 28 healthy controls (HC), and their cognitive functions were evaluated. Group differences in the voxel-mirrored homotopic connectivity (VMHC) index and CC white matter microstructure were analyzed. Furthermore, mediation analysis was conducted to elucidate the interrelationships among CC integrity, interhemispheric connectivity, and cognitive impairment. Compared to HC, patients with ACOP exhibited reduced VMHC values in the middle frontal gyrus, inferior parietal lobule, precentral gyrus, and temporal regions, along with decreased fractional anisotropy values in the subregions of the CC, including the genu, body, and splenium. Partial correlation analyses showed that VMHC in the inferior parietal lobule positively correlated with Glasgow Coma Scale scores. In addition, VMHC in both the inferior parietal lobule and the middle temporal gyrus positively correlated with Montreal Cognitive Assessment-Basic scores. Mediation analysis indicated that changes in interhemispheric connectivity played a crucial role in mediating the effect of CC integrity on cognitive impairment. Together, these findings may offer novel insights into the neurobiological mechanisms underlying ACOP.

Dual-task (DT) training, which involves the simultaneous execution of cognitive and motor tasks, has been shown to influence task performance and cortical activation, yet evidence on the effects of DT training and cortical activation for complex postural control tasks remains limited. This study investigated the immediate and retention effects of a one-week DT training program on DT learning, performance in DT and single-task conditions, and activation in bilateral prefrontal (PFC) and vestibular cortices in healthy young adults. Eighteen individuals (age = 22.39 ± 1.73 years) participated in the study. The DT paradigm involved a dynamic stability platform (motor task) paired with either a simple or complex auditory reaction time (RT) task (cognitive). Participants completed 20-25 minutes of DT training (18 trials/day) across five consecutive days. DT performance was measured by the duration participants maintained the stability platform within 3 degrees of the horizontal while responding to auditory stimuli. Single-task motor and cognitive performances were also assessed. Cortical activation in the PFC and vestibular cortices was measured using functional near infrared spectroscopy (fNIRS), tracking changes in oxygenated hemoglobin (HbO) concentrations. Pre-training, post-training, and one-week follow-up testing was conducted. The results demonstrate that DT training significantly improves and retains DT performance, likely due to a reduction in cognitive-motor interference. Additionally, DT training led to decreased activation in the bilateral PFC and vestibular cortices, specifically for complex DT condition, suggesting enhanced attentional resource allocation and optimized vestibular input processing, indicative of neural efficiency. Notably, these training effects also transferred to single-task cognitive and motor performances, with corresponding reductions in PFC and vestibular cortex activation, despite the lack of direct training on these tasks. This study advances our understanding of the neural mechanisms underlying DT training and underscores the critical role of practice in optimizing cognitive-motor efficiency.

Emerging research suggests the brain operates as a "prediction machine," continuously anticipating sensory, motor, and cognitive outcomes. Central to this capability is the brain's spontaneous activity-ongoing internal processes independent of external stimuli. Neuroimaging and computational studies support that this activity is integral to maintaining and refining mental models of our environment, body, and behaviors, akin to generative models in computation. During rest, spontaneous activity expands the variability of potential representations, enhancing the accuracy and adaptability of these models. When performing tasks, internal models direct brain regions to anticipate sensory and motor states, optimizing performance. This review synthesizes evidence from various species, from C. elegans to humans, highlighting three key aspects of spontaneous brain activity's role in prediction: the similarity between spontaneous and task-related activity, the encoding of behavioral and interoceptive priors, and the high metabolic cost of this activity, underscoring prediction as a fundamental function of brains across species.

Attention plays a vital part in the cognitive process, where different kinds of attention are associated with separate brain mechanisms. The objective of this research was to investigate the patterns of brain activation and functional connectivity in middle-aged and elderly individuals, while they were engaged in various attentional tasks, with the intention of establishing a reference foundation for the clinical treatment of attention disorders.

A total of 44 healthy middle-aged and elderly persons (47.1% women) aged over 40 were enrolled in this study. The digital cancellation test (DCT), the paced auditory serial addition test (PASAT), the Stroop colour-word test, and the trail making test (TMT) are, respectively, associated with four types of attention tasks: sustained attention, divided attention, selective attention, and attention shifting. Functional near-infrared spectroscopic imaging was employed to measure the concentration of brain oxyhaemoglobin in the subjects, while they were performing these four attention tasks.

In this study, we found distinct activation patterns in brain areas, such as BA-3, BA-4, BA-6, and others. Functional connectivity analysis revealed that the frontal and right parietal lobes consistently showed higher density and strength of connections across tasks, with the PASAT task exhibiting the highest number of connections exceeding the threshold. Notably, the DCT task demonstrated significant correlations in oxygen fluctuations among several brain regions, while the TMT-B task highlighted strong functional connectivity within the bilateral frontal and parietal lobes.

This research provides evidence that middle-aged and elderly people have different brain activation and functional connectivity patterns in different attentional tasks, suggesting individualized treatment for attention disorder patients based on impairment type and location.

This study has been registered through the Chinese Clinical Trial Registry (ChiCTR2400087755).

The hierarchy and segregation of community-based brain networks can be characterized by functional connectome gradient (FCG). Whether the cortical FCG was disrupted and could even be reversed after prolonged abstinence in substance use disorders (SUDs) remained unclear. Less is known about the underlying genetic basis.

We utilized three independent datasets (n = 247) to investigate cortical FCG dysfunction and recovery after prolonged abstinence in methamphetamine use disorder (MUD) (n = 131), and validated in heroin use disorder (HUD) (n = 36). Furthermore, magnetic resonance spectroscopy (MRS) was employed to test the relationship between the glutamate in the ventral tegmental area (VTA) and cortical FCG. Postmortem gene expression was utilized to assess the transcriptional profiles related to cortical FCG alterations. Support vector regression (SVR) model based on the baseline cortical FCG was built to predict craving changes after long-term abstinence.

MUD and HUD individuals exhibited similar cortical FCG dysfunction and recovery at global and network levels, mainly in dorsal and ventral attentions network (DAN and VAN), frontoparietal network (FPN) and default mode network (DMN). The glutamate levels in VTA were correlated with the gradient distance between FPN and limbic network (LIM). The transcriptional profiles explained variance of the altered gradient pattern, with the most related genes enriched in synaptic signaling. Baseline cortical FCG significantly predicted craving changes after long-term abstinence.

We provided novel insights into the understanding of SUD as treatable health conditions from cortical FCG changes, which could be considered as the potential biomarkers of craving changes after prolonged abstinence for SUDs.

We developed an experimental approach to compare how attentional orienting facilitates retrieval from spatial working memory (WM) and long-term memory (LTM), and how selective attention within these two memory types impacts incoming sensory information processing. In three experiments with healthy young adults, retrospective attention cues prioritize an item represented in WM or LTM. Participants then retrieve a memory item or perform a perceptual task. The retrocue is informative for the retrieval task but not for the perceptual task. We show that attentional orienting benefits performance for both WM and LTM, with stronger effects for WM. Eye-tracking reveals significant gaze shifts and microsaccades correlated with attention in WM, but no statistically significant gaze biases were found for LTM. Visual discrimination of unrelated visual stimuli is consistently improved for items matching attended WM locations. Similar effects occur at LTM locations but less consistently. The findings suggest at least partly dissociable attention-orienting processes for different memory types. Although our conclusions are necessarily constrained to the type of WM and LTM representations relevant to our task, they suggest that, under certain conditions, attentional prioritization in LTM can operate independently from WM. Future research should explore whether similar dissociations extend to non-spatial or more complex forms of LTM.

Brain functional dedifferentiation, marked by reduced specificity of brain activity or greater similarity of functional connectivity (FC) among networks, is a hallmark of aging. Traditionally, task functional magnetic resonance imaging studies have explored functional dedifferentiation within specific cognitive domains, while FC-based approaches have focused on regional connectivity patterns. Here, we leverage the principal functional gradient to provide a macro-scale and integrative perspective on functional dedifferentiation in aging, offering a novel framework for understanding its relationship with aging, cognition, and disease. We utilized brain images and clinical data from the UK Biobank, comprising 23,578 participants aged 44-82. Linear regression was employed to assess relationships between the network dedifferentiation along the principal functional gradient and age, and cognitive performance across six domains in a normal aging population. We tested interactions between age, sex, and education to assess their influence on age-related dedifferentiation. Logistic regression was applied to classify stroke in participants with stroke and matched normal aging participants. Our findings revealed a reduced principal functional gradient range with age, indicating reduced FC variability of all brain regions. At the network level, the dedifferentiation between the frontoparietal and other networks was strongly linked to aging and cognitive performance. Males exhibited faster dedifferentiation than females across multiple networks. The somatomotor network was most affected by stroke-related dedifferentiation. Validation via covariate-matched subgroups confirmed the robustness of these findings. This research provides macro-scale insights into age-related brain functional changes, highlighting dedifferentiation along the principal gradient as a network-sensitive indicator of aging and the development of stroke.

Neural markers of visual function in age-related macular degeneration (AMD) allow clinicians and researchers to directly evaluate the functional changes in visual processing which occur as a result of the progressive loss of afferent input from the macula. Unfortunately, few protocols exist that elicit such neural markers, and most of these are poorly adapted to AMD. Here, we propose a novel method of embedding frequency tags into full color and motion videos by periodically manipulating the contrast of visual information of different spatial frequencies at different temporal frequencies. These videos elicit steady-state visual evoked potentials (SSVEPS) in viewers which, when measured using electrophysiological neuroimaging methods, independently represent the responses of populations of neurons tuned to the tagged spatial frequencies. We used electroencephalography (EEG) to record the SSVEPs of 15 AMD patients and 16 age-matched healthy controls watching a 6-min series of natural scene videos filtered with this spatial frequency tagging method. Compared with healthy controls, AMD patients showed a lower SSVEP to high spatial frequency information, and a stronger response to the low spatial frequency information in the video set. The ratio of the SSVEP to lower relative to higher spatial frequency information was strongly predictive of both visual acuity and contrast sensitivity, and the topographic distributions of these responses suggested retinotopic reorganization of the neural response to spatial frequency information.

Nowadays, breast cancer is a leading cause of cancer-related mortality among women globally. Approximately 10% to 15% of breast cancer patients fail to undergo timely screening, resulting in a missed opportunity for optimal treatment. Computer-aided diagnosis (CAD) systems have been used successfully in breast cancer diagnosis. Nevertheless, current systems have encountered difficulties in achieving a high degree of accuracy, with the majority of research efforts focusing on the binary classification that distinguishes benign from malignant. Different subtypes of breast cancer require different targeted therapeutic approaches. Therefore, the precise classification of the breast cancer subtype has a major impact on treatment decisions. To improve the accuracy of breast cancer multi-classification, a novel Attention-based Mask Reconstruction Module (AMRM) is proposed to improve the performance of the model. AMRM extracts features from breast cancer histopathological images through the attention module and then performs mask reconstruction to generate reconstructed features. These reconstructed features were used in a multi-classification task to accurately classify histopathological images of breast cancer. AMRM enables the network to effectively identify background and foreground in histopathological images, reduce background interference, improve adaptability to background changes, align the features extracted by the model with the pathologist's expectations, and improve classification accuracy. Results from experiments conducted on the BreakHis dataset show that the inclusion of AMRM resulted in a significant improvement in multi-classification accuracy for the AlexNet, VGG11, ResNet-50 and Data-efficient Image Transformer (DeiT) models, reaching 88.48%, 93.40%, 96.49% and 94.10% respectively. Compared to the baseline model, accuracy increased by 8.28%, 2.11%, 1.27% and 1.26% respectively, demonstrating a significant improvement.