Neural Mechanisms Research Articles

Abnormal percent amplitude of fluctuation in patients with lifelong premature ejaculation is associated with neurotransmitter profiles.

Identifying additional imaging biomarkers of lifelong premature ejaculation (LPE) may provide valuable insights into understanding the underlying neural mechanisms of this disorder. Forty-six LPE patients and thirty-five healthy controls (HCs) were enrolled in this study. The Percent Amplitude of Fluctuation (PerAF) method was used to assess differences in brain function in LPE patients compared to HCs during the resting-state. Receiver operating characteristic (ROC) analysis was used to investigate the potential biomarkers based on the imaging findings. Correlation analysis was then applied to examine the relationships between the neuroimaging findings and clinical symptoms. We also investigated whether PerAF alterations in LPE patients were associated with specific neurotransmitter systems. Compared to HCs, LPE patients showed increased PerAF in the middle cingulate cortex (MCC), supramarginal gyrus, Rolandic operculum, parahippocampus/hippocampus (ParaHIPP/HIPP) as well as insula; and decreased PerAF in the precuneus, inferior temporal cortex plus occipital cortex. The MCC and ParaHIPP/HIPP exhibited higher classification performance on ROC analysis. Positive correlations were found between the Premature Ejaculation Diagnostic Tool score and PerAF in the insula, and the International Index of Erectile Function score and PerAF in the precuneus. Additionally, altered PerAF in LPE patients correlated significantly with the spatial distribution of dopamine, acetylcholine and epinephrine pathways. Our findings indicate that LPE patients have PerAF-related changes in certain brain regions associated with visual, sensory and/or emotional processing, and reveal that the abnormal control of ejaculatory function may be related to the combined dysregulation of neurotransmitter systems in LPE patients.

Impact of age-related hearing loss on decompensation of left DLPFC during speech perception in noise: a combined EEG-fNIRS study.

Understanding speech-in-noise is a significant challenge for individuals with age-related hearing loss (ARHL). Evidence suggests that increased activity in the frontal cortex compensates for impaired speech perception in healthy aging older adults. However, whether older adults with ARHL still show preserved compensatory function and the specific neural regulatory mechanisms underlying such compensation remains largely unclear. Here, by utilizing a synchronized EEG-fNIRS test, we investigated the neural oscillatory characteristics of the theta band and synchronous hemodynamic changes in the frontal cortex during a speech recognition task in noise. The study included healthy older adults (n = 26, aged 65.4 ± 2.8), those with mild hearing loss (n = 26, aged 66.3 ± 3.8), and those with moderate to severe hearing loss (n = 26, aged 67.5 ± 3.7). Results showed that, relative to healthy older adults, older adults with ARHL exhibited lower activation and weakened theta band neural oscillations in the left dorsolateral prefrontal cortex (DLPFC) under noisy conditions, and this decreased activity correlated with high-frequency hearing loss. Meanwhile, we found that the connectivity of the frontoparietal network was significantly reduced, which might depress the top-down articulatory prediction function affecting speech recognition performance in ARHL older adults. The results suggested that healthy aging older adults might exhibit compensatory attentional resource recruitment through a top-down auditory-motor integration mechanism. In comparison, older adults with ARHL reflected decompensation of the left DLPFC involving the frontoparietal integration network during speech recognition tasks in noise.

The mediation role of gray matter volume in the relationship between childhood maltreatment and psychological resilience in adolescents with first-episode major depressive disorder

Previous studies have revealed morphologic alterations in patients with major depressive disorder (MDD) with experiences of childhood trauma. However, the underlying neural mechanisms remain largely unknown. This study aims to explore the brain structural changes and their possible mediation role in the relationship between childhood maltreatment and psychological resilience in drug-naïve adolescents with first-episode MDD. A total of 57 adolescents with first-episode MDD and 36 healthy controls (HCs) completed the T1-weighted magnetic resonance imaging scan. The adverse childhood experiences and current psychological resilience were assessed using the Childhood Trauma Questionnaire-Short Form and the Connor Davidson Resilience Scale, respectively. The voxel-based morphometry approach was applied to examine changes in the gray matter volume (GMV). Compared with the HCs, adolescents with MDD had significantly reduced GMV volumes in the left fusiform gyrus, right orbitofrontal gyrus, right superior temporal gyrus, right calcarine cortex, right middle frontal gyrus, left angular gyrus, right precuneus, right posterior cingulate gyrus, and right posterior central gyrus, as well as significantly increased GMV volumes in the left lenticular putamen and right lenticular pallidum. The GMV of the right calcarine cortex was found to be negatively correlated with the severity of emotional abuse and positively correlated with the level of psychological resilience. Moreover, the GMV of the right calcarine cortex might partially mediate the relationship between childhood maltreatment and psychological resilience. The present study provided further evidence for structural impairments in adolescents with MDD. Our findings also confirmed the important role of depression-related GMV changes in childhood growth experiences and psychological resilience characteristics during adolescent brain maturation.

Functional connectivity density of brain in children with primary nocturnal enuresis: results from a resting-state fMRI study.

Primary nocturnal enuresis (PNE) is a disease characterized by involuntary urination during sleep after the age of five, causing inconvenience and psychological burden to children and their families. The onset of PNE is related to many factors, and in recent years, delayed central nervous system maturation has been considered one of the important causes of PNE. Previous studies have demonstrated functional changes in multiple brain regions in children with PNE. However, these studies either focused on changes in local brain regions or the functional connection (FC) between specific brain regions, and there is currently a lack of research on the whole brain FC in children with PNE. This study analyzed functional connectivity density (FCD) across the entire brain based on voxels and comprehensively evaluated the global FCD (gFCD), local FCD (lFCD), and long-range FCD (lrFCD). Decreased gFCD and lFCD were found in the left temporal lobe and the right posterior cerebellum in the children with PNE compared with the HC. The FCD values in these regions were negatively correlated with the scores of hyperactivity/impulsivity in the children with PNE. This study may help to reveal the neural mechanisms underlying the onset of PNE in children from a new perspective.

Behavioral and Neurophysiological Signatures of Cognitive Control in Humans and Rats.

Deficits in cognitive control are implicated in numerous neuropsychiatric disorders. However, relevant pharmacological treatments are limited, likely due to weak translational validity of applicable preclinical models used. Neural indices derived from electroencephalography (EEG) may prove useful in comparing and translating the effects of cognition-enhancing drugs between species. In the current study, we aimed to extend our previous cross-species results by examining if methylphenidate (MPH) modulates behavioral and neural indices of cognitive control in independent cohorts of humans and rats. We measured continuous EEG data from healthy adults (n=25; 14 female) and Long Evans rats (n=22; 8 female) and compared both stimulus- and response-locked event-related potentials (ERPs) and spectral power measures across species, and their MPH-related moderation following treatment with vehicle (placebo) or one of two doses of MPH. Across both species, linear mixed effects modeling confirmed the expected Flanker interference effect on behavior (e.g., accuracy) and response-related ERPs. Unexpectedly, in contrast to past work, we did not observe any task-related effects on the spectral power of rodents. Moreover, MPH generally did not modulate cognitive control of either species, although some species-specific patterns offer insight for future research. Collectively, these findings in independent human and rodent subjects replicate some of our previously reported behavioral and neurophysiological patterns partly consistent with the notion that similar neural mechanisms may regulate cognitive control in both species. Nonetheless, these results showcase an approach to accelerate translation using a coordinated between-species platform to evaluate pro-cognitive treatments.

Sex- and age-dependent impacts of nicotine and ethanol binge drinking on the brain: Insights from preclinical research.

Electronic cigarette use among adolescents is a growing concern, not only due to the high incidence of co-use with other substances, such as alcohol, but also due to the fact brain is still maturing during this period. Combined exposure to alcohol and nicotine leads to plastic adaptation of crucial circuits in the brain, which can contribute to the development of addiction. It is well established that nicotine exposure can facilitate alcohol binge drinking, and vice-versa, in a sex-, age- and exposure-dependent manner. Nonetheless, the central mechanisms underlying the synergistic relationship between these two substances and the emergence of differential behavioural traits dependent on these factors remain underexplored. Preclinical studies continue to provide valuable insights into such mechanisms. Here, we discuss recent preclinical findings that report behavioural changes characteristic of addiction following nicotine consumption, primarily in models of vaping and alcohol use; and insights into the neural mechanisms impacted by intake of these two substances, with a focus on the adolescent brain.

Rapid modulation in music supports attention in listeners with attentional difficulties

Background music is widely used to sustain attention, but little is known about what musical properties aid attention. This may be due to inter-individual variability in neural responses to music. Here we find that music with amplitude modulations added at specific rates can sustain attention differentially for those with varying levels of attentional difficulty. We first tested the hypothesis that music with strong amplitude modulation would improve sustained attention, and found it did so when it occurred early in the experiment. Rapid modulations in music elicited greater activity in attentional networks in fMRI, as well as greater stimulus-brain coupling in EEG. Finally, to test the idea that specific modulation properties would differentially affect listeners based on their level of attentional difficulty, we parametrically manipulated the depth and rate of amplitude modulations inserted in otherwise-identical music, and found that beta-range modulations helped more than other modulation ranges for participants with more ADHD symptoms. Results suggest the possibility of an oscillation-based neural mechanism for targeted music to support improved cognitive performance.

Alterations of regional brain activity and corresponding brain circuits in drug-naïve adolescents with nonsuicidal self-injury

Nonsuicidal self-injury (NSSI) is one of the major public health problems endangering adolescents. However, the neural mechanisms of NSSI is still unclear. The purpose of this study was to explore regional brain activity and corresponding brain circuits in drug-naïve adolescents with NSSI using amplitude of low-frequency fluctuations (ALFF) combined with functional connectivity (FC) analysis. Thirty-two drug-naïve adolescents with NSSI (NSSI group) and 29 healthy controls matched for sex, age, and level of education (HC group) were enrolled in this study. ALFF and seed-based FC analyses were used to examine the alterations in regional brain activity and corresponding brain circuits. The correlation between ALFF or FC values of aberrant brain regions and clinical characteristics were detected by Pearson correlation analysis. The NSSI group showed increased ALFF in the left inferior and middle occipital gyri, lingual gyrus, and fusiform gyrus; additionally, decreased ALFF in the right medial cingulate gyrus, left anterior cingulate gyrus, and left medial superior frontal gyrus compared to those in the HC group. With the left inferior occipital gyrus as seed, the NSSI group showed increased FC between the left inferior occipital gyrus and the bilateral superior parietal gyrus, right inferior parietal angular gyrus, right inferior frontal gyrus of the insular region, and left precuneus relative to that the HC group. With the left anterior cingulate gyrus as seed, the NSSI group showed increased FC between the left anterior cingulate gyrus and right dorsolateral superior frontal gyrus. With the left lingual gyrus as seed, the NSSI group showed increased FC between the left lingual gyrus and right middle frontal gyrus, and decreased FC between the left lingual gyrus and the left superior temporal gyrus, right supplementary motor area, and left rolandic operculum. With the left fusiform gyrus as seed, the NSSI group showed increased FC between the left fusiform gyrus and left middle and inferior temporal gyrus, and decreased FC between the left fusiform gyrus and the bilateral postcentral gyrus, right precentral gyrus, right lingual gyrus, and left inferior parietal angular gyrus. Moreover, the FC value between the left fusiform gyrus and left inferior temporal gyrus was positively correlated with suicidal ideations score. This study highlights alterations in regional brain activity and corresponding brain circuits in brain regions related to visual and emotional regulation functions in drug-naïve adolescents with NSSI. These findings may facilitate better understand the underlying neural mechanisms of NSSI in adolescents.

Functional excitation-inhibition ratio for social anxiety analysis and severity assessment

IntroductionSocial anxiety disorder (SAD) is a prevalent psychiatric condition characterized by an intense fear of and avoidance of social situations. Traditional assessment methods for SAD primarily rely on subjective self-report questionnaires and clinical interviews, which can be prone to biases and inaccuracies. This study aims to explore the functional excitation-inhibition (fEI) ratio derived from EEG data as a potential objective biomarker for assessing SAD severity. MethodsResting-state EEG data were collected from 20 control subjects and 60 individuals with varying degrees of SAD severity (mild, moderate, and severe). The fEI ratio was estimated across different EEG bands and analyzed, focusing on differences between control subjects and SAD groups. ResultsSignificantly higher fEI ratios were observed in the alpha and low beta EEG bands in individuals with SAD compared to controls, especially within the prefrontal cortex. Additionally, a positive correlation was found between the fEI ratio and the severity of social anxiety symptoms across SAD severity levels. DiscussionThe findings indicate that the fEI ratio in the alpha and low beta bands may serve as a promising biomarker for assessing SAD severity. These results contribute to a deeper understanding of the neural mechanisms underlying social anxiety, offering a potentially more objective approach to SAD assessment compared to traditional methods.

Transitive inference as probabilistic preference learning.

Transitive inference (TI) is a cognitive task that assesses an organism's ability to infer novel relations between items based on previously acquired knowledge. TI is known for exhibiting various behavioral and neural signatures, such as the serial position effect (SPE), symbolic distance effect (SDE), and the brain's capacity to maintain and merge separate ranking models. We propose a novel framework that casts TI as a probabilistic preference learning task, using one-parameter Mallows models. We present a series of simulations that highlight the effectiveness of our novel approach. We show that the Mallows ranking model natively reproduces SDE and SPE. Furthermore, extending the model using Bayesian selection showcases its capacity to generate and merge ranking hypotheses as pairs with connecting symbols. Finally, we employ neural networks to replicate Mallows models, demonstrating how this framework aligns with observed prefrontal neural activity during TI. Our innovative approach sheds new light on the nature of TI, emphasizing the potential of probabilistic preference learning for unraveling its underlying neural mechanisms.

Intuitive Innovation: Unconventional Modeling and Systems Neurology

This review explores how intuitive processes drive innovation, which we define as novel ideas, inventions, or artistic creations that cannot be logically derived from existing knowledge or sensory data. Although intuitive processes are not yet fully recognized as a formal area of scientific research, this paper examines current approaches to their study and modeling. It highlights the necessity of integrating unconventional modeling methods with neuroscience to gain deeper insights into these processes. Key experimental studies investigating extrasensory abilities—such as remote viewing, precognition, and telepathy—are reviewed, emphasizing their potential relevance to innovation. We propose that combining these unconventional modeling approaches with insights from systems neurology can provide new perspectives on the neural mechanisms underpinning intuition and creativity. This review emphasizes the critical need for further research into intuitive processes to address complex global challenges. It calls for a more open, interdisciplinary approach to scientific inquiry, promoting the exploration of unconventional forms of knowledge generation and their neural correlates.

Characteristics of Functional Connections and Topographical Properties Distinguished the Healthy State and Obsessive-Compulsive Disorder

Background: Obsessive-compulsive disorder (OCD) is characterized by alterations in brain connectivity, particularly within the default mode network (DMN) and the salience network (SN). Investigating these connectivity differences can provide a deeper understanding of the neural mechanisms underlying OCD. Methods: This cross-sectional study involved 58 patients diagnosed with OCD and 38 healthy control subjects, totaling 96 participants. Resting-state functional MRI (fMRI) data were acquired and analyzed using the CONN toolbox to examine functional connectivity within intrinsic resting-state networks. Graph theory metrics were applied to evaluate node connections and the overall network topology. Clinical symptoms were assessed using the Yale-Brown Obsessive-Compulsive Scale (Y-BOCS), and their correlations with connectivity patterns and graph-theory parameters were analyzed. Results: The OCD patients and healthy controls were matched in terms of age, gender, marital status, socioeconomic status, and handedness. However, OCD patients had significantly worse general health, quality of life, and higher levels of depression and anxiety. Network analyses revealed altered whole-brain connectivity in OCD patients, particularly within the DMN and the frontoparietal network. The most significant between-group connectivity differences were observed between the posterior parietal cortex (PPC) and the precuneus. Disruptions in the DMN, specifically altered connectivity between the medial prefrontal cortex and posterior cingulate cortex, and changes in the SN involving the anterior insula and anterior cingulate cortex, were significantly correlated with the severity of OCD symptoms. Conclusions: The findings suggest that OCD is associated with distinct alterations in DMN connectivity, which may play a critical role in the disorder's pathophysiology. These disruptions offer potential targets for therapeutic intervention. Further research is needed to explore these connectivity changes in larger cohorts and at various stages of OCD to better understand their clinical significance.

Decoding and modifying dynamic attentional bias in gaming disorder.

With the spread of smartphones and computer games, concerns have escalated regarding the rising prevalence of gaming disorder. Patients often display attentional biases, unconsciously turning their attention towards gaming-related stimuli. However, attempts to discover and ameliorate these attentional deficits have yielded inconsistent outcomes, potentially due to the dynamic nature of attentional bias. This study investigated neural mechanisms underlying attentional bias state by combining neuroimaging (functional magnetic resonance imaging -fMRI) with an approach-avoidance task tailored to an individual's gaming preference. We conducted a multivariate pattern analysis of endogenous brain activity in 21 participants with probable gaming disorder. Our analyses revealed that activity patterns in the insula tracked temporal attentional bias states specific to gaming stimuli. A broad network of frontal and parietal regions instead appeared to predict a general temporal attentional bias state. Finally, we conducted a proof-of-concept study for 'just-in-time' attentional bias training through fMRI-decoded neurofeedback of insula activity patterns, named decoded attentional bias training (DecABT). Our preliminary results suggest that DecABT may help to decrease the attractiveness of gaming stimuli via a insula- and precuneus-based neural mechanism. This work provides new evidence for the insula as an endogenous regulator of attentional bias states in gaming disorder and a starting point to develop novel, individualized therapeutic approaches to treat addiction.This article is part of the theme issue 'Neurofeedback: new territories and neurocognitive mechanisms of endogenous neuromodulation'.

Neuroimaging Findings for the Overnight Consolidation of Learned Non-native Speech Sounds

Abstract Research over the past two decades has documented the importance of sleep to language learning. Sleep has been suggested to play a role in establishing new speech representations as well; however, the neural mechanisms corresponding to sleep-mediated effects on speech perception behavior are unknown. In this study, we trained monolingual English-speaking adults to perceive differences between the Hindi dental vs. retroflex speech contrast in the evening. We examined the blood oxygen level dependent signal using functional magnetic resonance imaging during perceptual tasks on both the trained talker and on an untrained talker shortly after training, and again the next morning. We also employed diffusion tensor imaging to determine if individual differences in white matter structure could predict variability in overnight consolidation. We found greater activity in cortical regions associated with language processing (e.g., left insula) on the second day. Fractional anisotropy values in the anterior thalamic radiation and the uncinate fasciculus was associated with the magnitude of overnight change in perceptual behavior on the generalization (untrained) talker, after controlling for differences in sleep duration and initial learning. Our findings suggest that speech-perceptual information is subject to an overnight transfer of information to the cortex. Moreover, neural structure appears to be linked to individual differences in efficiency of overnight consolidation.

Anticipatory and evoked visual cortical dynamics of voluntary temporal attention.

We can often anticipate the precise moment when a stimulus will be relevant for our behavioral goals. Voluntary temporal attention, the prioritization of sensory information at task-relevant time points, enhances visual perception. However, the neural mechanisms of voluntary temporal attention have not been isolated from those of temporal expectation, which reflects timing predictability rather than relevance. Here we use time-resolved steady-state visual evoked responses (SSVER) to investigate how temporal attention dynamically modulates visual activity when temporal expectation is controlled. We recorded magnetoencephalography while participants directed temporal attention to one of two sequential grating targets with predictable timing. Meanwhile, a co-localized SSVER probe continuously tracked visual cortical modulations both before and after the target stimuli. We find that in the pre-target period, the SSVER gradually ramps up as the targets approach, reflecting temporal expectation. Furthermore, we find a low-frequency modulation of the SSVER, which shifts approximately half a cycle in phase according to which target is attended. In the post-target period, temporal attention to the first target transiently modulates the SSVER shortly after target onset. Thus, temporal attention dynamically modulates visual cortical responses via both periodic pre-target and transient post-target mechanisms to prioritize sensory information at precise moments.

Mechanisms of brain self-regulation: psychological factors, mechanistic models and neural substrates.

While neurofeedback represents a promising tool for neuroscience and a brain self-regulation approach to psychological rehabilitation, the field faces several problems and challenges. Current research has shown great variability and even failure among human participants in learning to self-regulate target features of brain activity with neurofeedback. A better understanding of cognitive mechanisms, psychological factors and neural substrates underlying self-regulation might help improve neurofeedback's scientific and clinical practices. This article reviews the current understanding of the neural mechanisms of brain self-regulation by drawing on findings from human and animal studies in neurofeedback, brain-computer/machine interfaces and neuroprosthetics. In this article, we look closer at the following topics: cognitive processes and psychophysiological factors affecting self-regulation, theoretical models and neural substrates underlying self-regulation, and finally, we provide an outlook on the outstanding gaps in knowledge and technical challenges. This article is part of the theme issue 'Neurofeedback: new territories and neurocognitive mechanisms of endogenous neuromodulation'.

Time courses of brain plasticity underpinning visual motion perceptual learning

Visual perceptual learning (VPL) refers to a long-term improvement of visual task performance through training or experience, reflecting brain plasticity even in adults. In human subjects, VPL has been mostly studied using functional magnetic resonance imaging (fMRI). However, due to the low temporal resolution of fMRI, how VPL affects the time course of visual information processing is largely unknown. To address this issue, we trained human subjects to perform a visual motion direction discrimination task. Their behavioral performance and magnetoencephalography (MEG) signals responding to the motion stimuli were measured before, immediately after, and two weeks after training. Training induced a long-lasting behavioral improvement for the trained direction. Based on the MEG signals from occipital sensors, we found that, for the trained motion direction, VPL increased the motion direction decoding accuracy, reduced the motion direction decoding latency, enhanced the direction-selective channel response, and narrowed the tuning profile. Following the MEG source reconstruction, we showed that VPL enhanced the cortical response in early visual cortex (EVC) and strengthened the feedforward connection from EVC to V3A. These VPL-induced neural changes co-occurred in 160–230 ms after stimulus onset. Complementary to previous fMRI findings on VPL, this study provides a comprehensive description on the neural mechanisms of visual motion perceptual learning from a temporal perspective and reveals how VPL shapes the time course of visual motion processing in the adult human brain.

Increased understanding of complex neuronal circuits in the cerebellar cortex

The prevailing belief has been that the fundamental structures of cerebellar neuronal circuits, consisting of a few major neuron types, are simple and well understood. Given that the cerebellum has long been known to be crucial for motor behaviors, these simple yet organized circuit structures seemed beneficial for theoretical studies proposing neural mechanisms underlying cerebellar motor functions and learning. On the other hand, experimental studies using advanced techniques have revealed numerous structural properties that were not traditionally defined. These include subdivided neuronal types and their circuit structures, feedback pathways from output Purkinje cells, and the multidimensional organization of neuronal interactions. With the recent recognition of the cerebellar involvement in non-motor functions, it is possible that these newly identified structural properties, which are potentially capable of generating greater complexity than previously recognized, are associated with increased information capacity. This, in turn, could contribute to the wide range of cerebellar functions. However, it remains largely unknown how such structural properties contribute to cerebellar neural computations through the regulation of neuronal activity or synaptic transmissions. To promote further research into cerebellar circuit structures and their functional significance, we aim to summarize the newly identified structural properties of the cerebellar cortex and discuss future research directions concerning cerebellar circuit structures and their potential functions.

Mechanisms of Social Attachment Between Children and Pet Dogs.

An increasing body of evidence indicates that owning a pet dog is associated with improvements in child health and well-being. Importantly, the degree of the social bond between child and dog may mediate the beneficial outcomes of dog ownership. The formation of social bonds is an intrinsically dyadic, interactive process where each interactor's behavior influences the other's behavior. For this reason, it is critical to evaluate the biological mechanisms of attachment in both children and their pet dogs as a socially bonded pair. Here, we review the physical, mental, and emotional outcomes that are associated with pet dog ownership or interaction in children. We then discuss the evidence that suggests that the strength of a social bond between a child and their pet dog matters for maximizing the beneficial outcomes associated with pet dog ownership, such as possible stress-buffering effects. We review the existing literature on the neural and endocrinological mechanisms of social attachment for inter-species social bonds that form between human children and dogs, situating this emerging knowledge within the context of the mechanisms of intra-species bonds in mammals. Finally, we highlight the remaining open questions and point toward directions for future research.

Large-scale structural covariance networks changes relate to executive function deficit in betel quid-dependent chewers.

Previous studies demonstrate deficits in executive function for betel quid-dependent (BQD) patients. Large-scale structural covariance network (SCN) based on gray matter (GM) morphometry may be able to explore the neural mechanism of executive dysfunction in BQD individuals. This study aims to identify spatial covariance patterns of GM volume and to investigate their association with executive dysfunction in BQD individuals. Sixty-four BQD individuals and 48 sex- and age-matched healthy controls (HCs) underwent T1-weighted structural MRI examination and executive function assessments, including the Backward Digit Span (BDS) test and Stroop Color and Word (SCW) test. Seventy SCNs based on GM volume covariance patterns were defined using independent component analysis. An SCN-based classifier was constructed to differentiate between BQD and HC individuals. Receiver operating characteristic (ROC) curves were applied to evaluate the performance of the SCN-based classifier. Linear regression analyses were performed to investigate the association between SCN network indices and executive function indices. Six SCNs had higher classifications for differentiating between BQD and HC individuals. The area under the ROC curve of the SCN-based classifier was 0.812 in the training set and 0.771 in the testing set. Furthermore, linear regression analyses demonstrated that the network indices in the thalamus were associated with BDS scores adjusted for age, sex, and education. Large-scale SCNs could provide potential imaging markers for differentiating BQD and HC groups. The loss of network index in the thalamus was associated with working memory, indicating that SCNs could reveal executive dysfunction in BQD individuals.