Large-scale brain networks and psychopathology: a unifying triple network model

Resting-state functional connectivity abnormalities in subjective cognitive decline: A 7T MRI study

Resting-state functional connectivity (FC) MRI is sensitive to brain changes in Alzheimer's disease in preclinical stages, however studies in persons with subjective cognitive decline (SCD) have reported conflicting findings, and no study is available at 7T MRI. In this study, we investigated FC alterations in sixty-six participants recruited at the Geneva Memory Center (24 controls, 14 SCD, 28 cognitively impaired [CI]). Participants were classified as SCD if they reported cognitive complaints without objective cognitive deficits, and underwent 7T fMRI to assess FC in canonical brain networks and their association with cognitive/clinical features. SCD showed normal cognition, a trend for higher depressive symptoms, and normal AD biomarkers. Compared to the other two groups, SCD showed higher FC in frontal default mode network (DMN) and insular and superior temporal nodes of ventral attention network (VAN). Higher FC in the DMN and VAN was associated with worse cognition but not depression, suggesting that hyper-connectivity in these networks may be a signature of age-related cognitive decline in SCD at low risk of developing AD.

Orbitofrontal cortex hypergyrification in hallucinating schizophrenia patients: Surface ratio as a promising brain biomarker

The study of brain gyrification may provide useful information on the cytoarchitecture and connectivity of the brain. One of the methods that have been developed to estimate brain gyrification, known as surface ratio (SR), has not yet been studied in schizophrenia. Here we aimed to assess whether SR could provide new insights on the brain structure of schizophrenia patients and the severity of symptoms. We also computed a more established brain gyrification measure, namely absolute mean curvature (AMC). We analyzed 63 magnetic resonance images, 25 from schizophrenia patients with treatment-resistant auditory verbal hallucinations (SCH-H), 18 from schizophrenia patients without hallucinations (SCH-NH), and 20 from healthy controls (HC). The SR measure revealed that SCH-H patients had a more folded orbitofrontal cortex than SCH-NH patients and HC. Gyrification in this region was also negatively associated with positive symptoms, specifically with the delusions and conceptual disorganization items, only in the SCH-H group. Regarding the AMC measure, we identified two areas where HC showed more gyrification than SCH-H patients, but no relationships arose with symptoms. The hypergyrification of the orbitofrontal cortex displayed by SCH-H patients, as captured by the SR measure, suggests aberrant and/or excessive wiring in these patients, which in turn could give rise to auditory verbal hallucinations. Alternatively, we comment on potential compensatory mechanisms that may better explain the negative association between orbitofrontal gyrification and positive symptomatology. The SR measure captured the most relevant differences and associations, making it a promising biomarker in schizophrenia.

Advances in brain and religion studies: a review and synthesis of recent representative studies

We review and synthesize recent religion and brain studies and find that at a broad network neuroscience level, religious/spiritual experiences (RSEs) appear to depend crucially upon interactions between the default mode network (DMN), the frontoparietal network (FPN), and the salience network (SN). We see this general result as broadly consistent with Menon's et al. "Triple Network or Tripartite Model" (TPM) of neuropsychiatric function/dysfunction. A TPM cycling model is here offered to account for details of neural bases of an array of RSE phenomena including ecstatic seizures, neuroimaging of religious participants, psychedelically induced mystical states and perceptions of supernatural agents. To adequately account for SA perceptions, however, recent evidence suggests that REM sleep and dreaming mechanisms likely play a role. Future research should examine neurodevelopmental mechanisms of acquired SA perceptions as well as societal-level effects such as brain mediated religious beliefs of in-group cohesion and out-group hostility.

Functional connectivity profiles in remitted depression and their relation to ruminative thinking

The triple network model suggests that dysfunction in three major brain networks - the default mode network (DMN), central executive network (CEN), and salience network (SN) - might contribute to cognitive impairments in various psychiatric disorders, including major depressive disorder (MDD). While hyperconnectivity in the DMN, hypoconnectivity in the CEN, and abnormal SN connectivity have been observed in acutely depressed patients, evidence for network alterations during remission is limited. Further, there are few studies examining connectivity in people in remission from MDD (rMDD) during emotional processing tasks, including during affective cognition (i.e., tasks that encompass affective processing in the context of cognitive processes, such as inhibition). To address these literature gaps, this study compared functional connectivity (FC) between resting and task conditions, specifically during the emotional Stroop (eStroop) task, as well as between rMDD and healthy volunteers (HVs), within and between nodes of the three networks. We also explored how FC relates to rumination in the rMDD group, given that rumination tends to persist in rMDD and involves affective and cognitive networks. We unexpectedly found greater FC during the task vs. rest condition within the DMN, and decreased FC during the task vs. rest conditions within the CEN and SN across the groups. Greater FC during the task vs. rest condition between DMN and SN nodes, as well as between CEN and SN nodes were also observed. These effects were more pronounced in the rMDD group as per our exploratory analyses. Additionally, the rMDD vs. HV group showed higher FC between DMN-CEN nodes, regardless of condition. Higher hopeless rumination scores were associated with decreased resting FC within the DMN, while higher active problem-solving scores were associated with increased task FC within the DMN in the rMDD group. These findings suggest that tasks engaging affective cognition processes influence FC within and among the three networks, with this effect more pronounced in the rMDD group. This might indicate potential protective and compensatory mechanisms in rMDD and expands our understanding of large-scale intrinsic network connectivity alterations during remission from depression. However, given the limited sample and the exploratory nature of some of our analyses, replication is necessary.

Altered Blood Oxygen Level-Dependent Signal Stability in the Brain of Patients with Major Depressive Disorder Undergoing Resting-State Functional Magnetic Resonance Imaging

INTRODUCTION

Major depressive disorder (MDD) is a common, relapse-prone psychiatric disorder with unknown pathogenesis. Previous studies on resting-state functional magnetic resonance imaging of MDD have mostly focused on the spontaneous activity of blood oxygen level-dependent (BOLD) signals; however, a few studies have investigated BOLD signal stability.

METHODS

We conducted a resting-state functional study in 42 patients with MDD and 42 healthy controls (HC) matched for age and sex. This included the BOLD signal stability, resting-state functional connectivity (RSFC) analysis, correlation analysis, and support vector machine (SVM) analysis.

RESULTS

The BOLD signal stability of the left fusiform gyrus, right inferior temporal gyrus, right temporal pole superior temporal gyrus, and left thalamus was significantly lower in the MDD group compared to the HC group. Further RSFC analysis revealed that the connectivity between right inferior temporal gyrus and both left inferior temporal gyrus and left supramarginal gyrus was significantly reduced in the MDD group. Additionally, the RSFC levels of left thalamus and right thalamus were decreased. Combining BOLD signal stability and RSFC, the SVM-based classification model achieved an accuracy of 80.95% (sensitivity: 78.57%; specificity: 83.33%; receiver-operating characteristic area under the curve: 0.8793).

CONCLUSION

The integration of the BOLD signal stability index and RSFC index demonstrates a robust capability to differentiate between individuals with MDD and HC subjects. We tentatively believe that a combination of the BOLD signal stability index and RSFC can be used to diagnose MDD.

Disentangling the Neural Circuits of Arousal and Anxiety-Like Behavior

Anxiety disorders are prevalent and debilitating conditions characterized by excessive concern and fear, affecting thoughts, behaviors, and sensations. A critical component of anxiety is arousal, a complex process involving alertness regulation and stimulus salience modulation. While arousal is adaptive in normal circumstances, dysregulation can lead to hypoarousal or hyperarousal, affecting response selection and threat perception. This chapter reviews challenges in studying arousal in preclinical anxiety models, emphasizing the need for multicomponent measurement and analysis. Novel methodologies integrating physiological measurement with activity tracking of neurons with single-cell resolution in awake animals are discussed, with emphasis in current challenges. Understanding these mechanisms is crucial for developing effective treatments for anxiety disorders.

A multi-regional human brain atlas of chromatin accessibility and gene expression facilitates promoter-isoform resolution genetic fine-mapping

Brain region- and cell-specific transcriptomic and epigenomic features are associated with heritability for neuropsychiatric traits, but a systematic view, considering cortical and subcortical regions, is lacking. Here, we provide an atlas of chromatin accessibility and gene expression profiles in neuronal and non-neuronal nuclei across 25 distinct human cortical and subcortical brain regions from 6 neurotypical controls. We identified extensive gene expression and chromatin accessibility differences across brain regions, including variation in alternative promoter-isoform usage and enhancer-promoter interactions. Genes with distinct promoter-isoform usage across brain regions were strongly enriched for neuropsychiatric disease risk variants. Moreover, we built enhancer-promoter interactions at promoter-isoform resolution across different brain regions and highlighted the contribution of brain region-specific and promoter-isoform-specific regulation to neuropsychiatric disorders. Including promoter-isoform resolution uncovers additional distal elements implicated in the heritability of diseases, thereby increasing the power to fine-map risk genes. Our results provide a valuable resource for studying molecular regulation across multiple regions of the human brain and underscore the importance of considering isoform information in gene regulation.

Negative BOLD Responses Surpass Positive Responses in Task Specificity, Reflecting Neural Reconfigurations Better Than Functional Connectivity

Objective

To investigate whether the Negative BOLD Response (NBR) is more task-specific than the Positive BOLD Response (PBR) during cognitive tasks and to determine whether task-evoked activity reflects brain reconfigurations during different tasks better than functional connectivity.

Methods

Functional Magnetic Resonance Imaging (fMRI) data were collected from 214 participants under 50 years old (152 in Dataset 1 and 62 in Dataset 2) performing twelve cognitive tasks spanning vocabulary, speed of processing, fluid reasoning, and memory domains. Data analysis included subject-level and group-level analyses, focusing on comparing the spatial patterns and task specificity of NBR and PBR through similarity measures using Dice coefficients. Additionally, functional connectivity was assessed using the Multi-session Hierarchical Bayesian Model (MS-HBM) to evaluate its sensitivity to task-induced brain reconfigurations compared to task-evoked activity.

Results

NBR demonstrated significantly greater task specificity compared to PBR across all cognitive tasks, with lower mean Dice coefficients for NBR maps (mean: 0.44, SD: 0.13) than for PBR maps (mean: 0.67, SD: 0.09; t(65) = 18.38, p < 0.001). Functional connectivity analyses indicated that the default mode network (DMN) remained stable across tasks, suggesting that task-evoked activity reflects task-specific brain reconfigurations better than functional connectivity.

Conclusion

The findings confirm that NBR is inherently more task-specific than PBR and that task-evoked activity provides a more sensitive measure of task-specific neural reconfigurations than functional connectivity. This enhances our understanding of the neural mechanisms underlying cognitive processes and highlights the importance of considering NBR in cognitive neuroscience research.

Macro-scale patterns in functional connectivity associated with ongoing thought patterns and dispositional traits

Complex macro-scale patterns of brain activity that emerge during periods of wakeful rest provide insight into the organisation of neural function, how these differentiate individuals based on their traits, and the neural basis of different types of self-generated thoughts. Although brain activity during wakeful rest is valuable for understanding important features of human cognition, its unconstrained nature makes it difficult to disentangle neural features related to personality traits from those related to the thoughts occurring at rest. Our study builds on recent perspectives from work on ongoing conscious thought that highlight the interactions between three brain networks - ventral and dorsal attention networks, as well as the default mode network. We combined measures of personality with state-of-the-art indices of ongoing thoughts at rest and brain imaging analysis and explored whether this 'tri-partite' view can provide a framework within which to understand the contribution of states and traits to observed patterns of neural activity at rest. To capture macro-scale relationships between different brain systems, we calculated cortical gradients to describe brain organisation in a low-dimensional space. Our analysis established that for more introverted individuals, regions of the ventral attention network were functionally more aligned to regions of the somatomotor system and the default mode network. At the same time, a pattern of detailed self-generated thought was associated with a decoupling of regions of dorsal attention from regions in the default mode network. Our study, therefore, establishes that interactions between attention systems and the default mode network are important influences on ongoing thought at rest and highlights the value of integrating contemporary perspectives on conscious experience when understanding patterns of brain activity at rest.

Resting state functional connectivity in adolescents with substance use disorder and their unaffected siblings

We aimed to examine resting-state functional connectivity (rsFC) in adolescents with substance use disorder (SUD) and their unaffected biological siblings (SIB), relative to typically-developing controls (TDC) in order to identify alterations in functional network organization that may be associated with the familial risk for SUD. Resting-state functional magnetic resonance imaging analysis included 20 adolescents with SUD, 20 SIB, and 18 TDC. Network-based analysis revealed that adolescents with SUD had significantly both weaker and higher rsFC compared to TDC mainly within the default-mode network (DMN) and between the DMN, fronto-parietal (FPN) and salience networks. In addition, adolescents with SUD showed lower rsFC between the visual network and other functional networks. Although the SIB group did not differ from TDC in the whole brain analysis, they showed lower rsFC within DMN and also between the visual network and other large-scale networks as well as higher rsFC between DMN and FPN compared to TDC in connections found to be abnormal in SUD group. Our results suggest that lower rsFC within DMN and higher rsFC between the DMN with FPN which were evident both in SUD and in SIB groups, and might be related to the familial predisposition for SUD.

Electrophysiological dynamics of salience, default mode, and frontoparietal networks during episodic memory formation and recall revealed through multi-experiment iEEG replication

Dynamic interactions between large-scale brain networks underpin human cognitive processes, but their electrophysiological mechanisms remain elusive. The triple network model, encompassing the salience network (SN), default mode network (DMN), and frontoparietal network (FPN), provides a framework for understanding these interactions. We analyzed intracranial electroencephalography (EEG) recordings from 177 participants across four diverse episodic memory experiments, each involving encoding as well as recall phases. Phase transfer entropy analysis revealed consistently higher directed information flow from the anterior insula (AI), a key SN node, to both DMN and FPN nodes. This directed influence was significantly stronger during memory tasks compared to resting state, highlighting the AI's task-specific role in coordinating large-scale network interactions. This pattern persisted across externally driven memory encoding and internally governed free recall. Control analyses using the inferior frontal gyrus (IFG) showed an inverse pattern, with DMN and FPN exerting higher influence on IFG, underscoring the AI's unique role. We observed task-specific suppression of high-gamma power in the posterior cingulate cortex/precuneus node of the DMN during memory encoding, but not recall. Crucially, these results were replicated across all four experiments spanning verbal and spatial memory domains with high Bayes replication factors. Our findings advance understanding of how coordinated neural network interactions support memory processes, highlighting the AI's critical role in orchestrating large-scale brain network dynamics during both memory encoding and retrieval. By elucidating the electrophysiological basis of triple network interactions in episodic memory, our study provides insights into neural circuit dynamics underlying memory function and offer a framework for investigating network disruptions in memory-related disorders.

Reconfiguration of Functional Brain Network Organization and Dynamics With Changing Cognitive Demands in Children With Attention-Deficit/Hyperactivity Disorder

BACKGROUND

The pathophysiology of attention-deficit/hyperactivity disorder (ADHD) is characterized by atypical brain network organization and dynamics. Although functional brain networks adaptively reconfigure across cognitive contexts, previous studies have largely focused on network dysfunction during the resting state. In this preliminary study, we examined how functional brain network organization and dynamics flexibly reconfigure across rest and 2 cognitive control tasks with different cognitive demands in 30 children with ADHD and 36 typically developing children (ages 8-12 years).

METHODS

We leveraged graph theoretical analyses to interrogate the segregation (modularity, within-module degree) and integration (global efficiency, node dissociation index) of frontoparietal, cingulo-opercular/salience, default mode, somatomotor, and visual networks. We also conducted edge time series analyses to quantify connectivity dynamics within and between these networks.

RESULTS

Across resting and task-based states, children with ADHD demonstrated significantly lower whole-graph modularity and a greater node dissociation index between default mode and visual networks. Furthermore, a significant task-by-diagnosis interaction was observed for frontoparietal network within-module degree, which decreased from rest to task in children with ADHD but increased in typically developing children. Finally, children with ADHD displayed significantly more dynamic connectivity within and across cingulo-opercular/salience, default mode, and somatomotor networks, especially during task performance. Exploratory analyses revealed associations between network dynamics, cognitive performance, and ADHD symptoms.

CONCLUSIONS

By integrating static and dynamic network analyses across changing cognitive demands, this study provides novel insight into how context-specific, context-general, and timescale-dependent network connectivity is altered in children with ADHD. Our findings highlight the involvement and clinical relevance of both association and sensory/motor systems in ADHD.

Functional Connectivity Alterations in Cocaine Use Disorder: Insights from the Triple Network Model and the Addictions Neuroclinical Assessment Framework

Cocaine use disorder (CUD) disrupts functional connectivity within key brain networks, specifically the default mode network (DMN), salience network (SN), and central executive network (CEN). While the triple network model has been proposed to explain various psychiatric disorders, its applicability to CUD requires further exploration. In the present study, we built machine learning classifiers based on different combinations of DMN/SN/CEN to distinguish cocaine-use disorder (CUD) subjects from healthy control (HC) subjects. Among them, the combination of the SN and the CEN results in a remarkably high accuracy of 73.4% (sensitivity/specificity: 69.6%/78.6%, AUC: 0.78), outperforming the model based on the full triple network. This supports the hypothesis that during the binge/intoxication stage of addiction, the SN and the CEN play a more critical role than the DMN, consistent with the Addictions Neuroclinical Assessment (ANA) framework. Functional connectivity analysis revealed decreased connectivity within the DMN and the SN and increased connectivity within the CEN in CUD patients, suggesting that alterations in these networks could serve as biomarkers for addiction severity.

Mother-child closeness and adolescent structural neural networks: a prospective longitudinal study of low-income families

Mother-child closeness, a mutually trusting and affectionate bond, is an important factor in shaping positive youth development. However, little is known about the neural pathways through which mother-child closeness is related to brain organization. Utilizing a longitudinal sample primarily from low-income families (N = 181; 76% African American youth and 54% female), this study investigated the associations between mother-child closeness at ages 9 and 15 years and structural connectivity organization (network integration, robustness, and segregation) at age 15 years. The assessment of mother-child closeness included perspectives from both mother and child. The results revealed that greater mother-child closeness is linked with increased global efficiency and transitivity, but not with modularity. Specifically, both the mother's and child's reports of closeness at age 15 years predicted network metrics, but report at age 9 years did not. Our findings suggest that mother-child closeness is associated with neural white matter organization, as adolescents who experienced greater mother-child closeness displayed topological properties indicative of more integrated and robust structural networks.

Assessing the causal role of the structural connectome in temporomandibular disorders: A Mendelian randomization study

OBJECTIVE

We examined the relationships between the structural connectome and temporomandibular disorders (TMDs).

METHODS

Bidirectional Mendelian randomization analyses were conducted using Genome-wide association studies data on the structural connectome and TMDs.

RESULTS

Positive associations with TMD risk were found for white matter structural connectivity from the left hemisphere limbic network to putamen, left hemisphere salience_ventral attention network to caudate, right hemisphere visual network to thalamus, and right hemisphere salience_ventral attention network to right hemisphere control network, while negative associations were observed for connectivity from the left hemisphere control and somatomotor networks to pallidum, left hemisphere somatomotor network to right hemisphere dorsal attention network, and right hemisphere somatomotor network to hippocampus (p< 0.05). In TMD patients, connectivity from the Left-hemisphere visual network to putamen was reduced, whereas connectivity from the Left-hemisphere limbic network to left-hemisphere control network was increased (p< 0.05).

CONCLUSION

Our findings provide insights into the TMD pathogenesis.

Predicting Clinical Improvement in Early Psychosis Using Circuit-Based Resting-State Functional Magnetic Resonance Imaging

BACKGROUND AND HYPOTHESIS

Identifying biomarkers that predict treatment response in early psychosis (EP) is a priority for psychiatry research. Previous work suggests that resting-state connectivity biomarkers may have promise as predictive measures, although prior results vary considerably in direction and magnitude. Here, we evaluated the relationship between intrinsic functional connectivity of the attention, default mode, and salience resting-state networks and 12-month clinical improvement in EP.

STUDY DESIGN

Fifty-eight individuals with EP (less than 2 years from illness onset, 35 males, average age 20 years) had baseline and follow-up clinical data and were included in the final sample. Of these, 30 EPs showed greater than 20% improvement in Brief Psychiatric Rating Scale (BPRS) total score at follow-up and were classified as "Improvers."

STUDY RESULTS

The overall logistic regression predicting Improver status was significant (χ2 = 23.66, Nagelkerke's R2 = 0.45, P < .001, with 85% concordance). Significant individual predictors of Improver status included higher default mode within-network connectivity, higher attention-default mode between-network connectivity, and higher attention-salience between-network connectivity. Including baseline BPRS as a predictor increased model significance and concordance to 92%, and the model was not significantly influenced by the dose of antipsychotic medication (chlorpromazine equivalents). Linear regression models predicting percent change in BPRS were also significant.

CONCLUSIONS

Overall, these results suggest that resting-state functional magnetic resonance imaging connectivity may serve as a useful biomarker of clinical outcomes in recent-onset psychosis.

Attention Network Dysfunctions in Lewy Body Dementia and Alzheimer's Disease

Background: Attention deficits are notable in Lewy body dementia (LBD) and in Alzheimer's disease (AD). In this study, we combined functional magnetic resonance imaging (fMRI) and electroencephalograph (EEG) to detect neural correlates of attention dysfunctions in LBD and AD. Methods: We recruited 33 patients with LBD, 15 patients with AD and 19 elderly healthy controls. The participants performed the modified Attention Network Task (ANT) to investigate the attention dysfunctions. Results: We found that LBD had alerting attention deficits and AD showed apparent orienting attention dysfunctions, while LBD and AD maintained relatively normal executive/conflict attention. Based on source-level EEG analyses, LBD had frontal-central deficits for alerting attention while AD showed inferior frontal and precentral impairments for orienting attention. In addition, the insular and inferior frontal areas were hyper-activated in LBD and AD for executive/conflict attention. Apart from these areas, LBD showed activity in the complementary temporal-central-occipital network for the modified ANT task. Furthermore, the oscillational sources for the ANT effects indicated that the alpha and theta bands were partly impaired in dementia patients. Conclusions: In summary, using source-localised EEG, we found that attention dysfunctions in LBD and AD engaged different neural networks.

Neuroplastic Responses to Chiropractic Care: Broad Impacts on Pain, Mood, Sleep, and Quality of Life

OBJECTIVES

This study aimed to elucidate the mechanisms of chiropractic care using resting electroencephalography (EEG), somatosensory evoked potentials (SEPs), clinical health assessments (Fitbit), and Patient-reported Outcomes Measurement Information System (PROMIS-29).

METHODS

Seventy-six people with chronic low back pain (mean age ± SD: 45 ± 11 years, 33 female) were randomised into control (n = 38) and chiropractic (n = 38) groups. EEG and SEPs were collected pre and post the first intervention and post 4 weeks of intervention. PROMIS-29 was measured pre and post 4 weeks. Fitbit data were recorded continuously.

RESULTS

Spectral analysis of resting EEG showed a significant increase in Theta, Alpha and Beta, and a significant decrease in Delta power in the chiropractic group post intervention. Source localisation revealed a significant increase in Alpha activity within the Default Mode Network (DMN) post intervention and post 4 weeks. A significant decrease in N30 SEP peak amplitude post intervention and post 4 weeks was found in the chiropractic group. Source localisation demonstrated significant changes in Alpha and Beta power within the DMN post-intervention and post 4 weeks. Significant improvements in light sleep stage were observed in the chiropractic group along with enhanced overall quality of life post 4 weeks, including significant reductions in anxiety, depression, fatigue, and pain.

CONCLUSIONS

These findings indicate that many health benefits of chiropractic care are due to altered brain activity.

The Algorithmic Agent Perspective and Computational Neuropsychiatry: From Etiology to Advanced Therapy in Major Depressive Disorder

Major Depressive Disorder (MDD) is a complex, heterogeneous condition affecting millions worldwide. Computational neuropsychiatry offers potential breakthroughs through the mechanistic modeling of this disorder. Using the Kolmogorov theory (KT) of consciousness, we developed a foundational model where algorithmic agents interact with the world to maximize an Objective Function evaluating affective valence. Depression, defined in this context by a state of persistently low valence, may arise from various factors-including inaccurate world models (cognitive biases), a dysfunctional Objective Function (anhedonia, anxiety), deficient planning (executive deficits), or unfavorable environments. Integrating algorithmic, dynamical systems, and neurobiological concepts, we map the agent model to brain circuits and functional networks, framing potential etiological routes and linking with depression biotypes. Finally, we explore how brain stimulation, psychotherapy, and plasticity-enhancing compounds such as psychedelics can synergistically repair neural circuits and optimize therapies using personalized computational models.

Thalamocortical dysrhythmia and reward deficiency syndrome as uncertainty disorders

A common anatomical core has been described for psychiatric disorders, consisting of the dorsal anterior cingulate cortex (dACC) and anterior insula, processing uncertainty. A common neurophysiological core has been described for other brain related disorders, called thalamocortical dysrhythmia (TCD), consisting of persistent cross-frequency coupling between low and high frequencies. And a common genetic core has been described for yet another set of hypodopaminergic pathologies called reward deficiency syndromes (RDS). Considering that some RDS have the neurophysiological features of TCD, it can be hypothesized that TCD and RDS have a common anatomical core, yet a differentiating associated neurophysiological mechanism. The EEGs of 683 subjects are analysed in source space for both differences and conjunction between TCD and healthy controls, RDS and healthy controls, and between TCD and RDS. A balance between current densities of the pregenual anterior cingulate cortex (pgACC) extending into the ventromedial prefrontal cortex (vmPFC) and dACC is calculated as well. TCD and RDS share a common anatomical and neurophysiological core, consisting of beta activity in the dACC and theta activity in dACC extending into precuneus and dorsolateral prefrontal cortex. TCD and RDS differ in pgACC/vmPFC activity and demonstrate an opposite balance between pgACC/vmPFC and dACC. Based on the Bayesian brain model TCD and RDS can be defined as uncertainty disorders in which the pgACC/vmPFC and dACC have an opposite balance, possibly explained by an inverted-U curve profile of both pgACC/vmPFC and dACC.

Functional imaging derived ADHD biotypes based on deep clustering: a study on personalized medication therapy guidance

Background

Attention deficit hyperactivity disorder (ADHD) is one prevalent neurodevelopmental disorder with childhood onset, however, there is no clear correspondence established between clinical ADHD subtypes and primary medications. Identifying objective and reliable neuroimaging markers for categorizing ADHD biotypes may lead to more individualized, biotype-guided treatment.

Methods

Here we proposed a graph convolution network for biological subtype detection (GCN-BSD) using both functional network connectivity (FNC) and non-imaging phenotypic data for ADHD biotype. We applied GCN-BSD to ADHD patients from the ABCD study as the discovery dataset and a validation ADHD dataset with longitudinal medication treatment from Peking University Sixth Hospital.

Findings

We identified two biotypes based on 1069 ADHD patients selected from Adolescent Brain and Cognitive Development (ABCD) study, which were validated on independent ADHD adolescents undergoing longitudinal medication treatment (n = 130). Interestingly, in addition to differences in cognitive performance and hyperactivity/impulsivity symptoms, biotype 1 demonstrated a significantly better recovery rate in psychosomatic problems score (p < 0.05, baseline symptom score adjusted) when treated with methylphenidate than with atomoxetine.

Interpretation

Our results suggested that such an imaging-driven, biotype-guided approaches hold promise for facilitating personalized treatment of ADHD and exploring possible boundaries through innovative deep learning algorithms to improve medication treatment effectiveness.

Funding

Science and Technology Innovation 2030 Major Projects, the National Natural Science Foundation of China, the Startup Funds for Talents at Beijing Normal University, China Postdoctoral Science Foundation, and the National Institutes of Health.

Salience network segregation mediates the effect of tau pathology on mild behavioral impairment

INTRODUCTION

A recently developed mild behavioral impairment (MBI) diagnostic framework standardizes the early characterization of neuropsychiatric symptoms in older adults. However, the joint contributions of Alzheimer's disease (AD) pathology and brain function to MBI remain unclear.

METHODS

We test a novel model assessing direct relationships between AD biomarker status and MBI symptoms, as well as mediated effects through segregation of the salience and default-mode networks, using data from 128 participants with diagnosis of amnestic mild cognitive impairment or mild dementia-AD type.

RESULTS

We identified a mediated effect of tau positivity on MBI through functional segregation of the salience network from the other high-level, association networks. There were no direct effects of AD biomarkers status on MBI.

DISCUSSION

Our findings suggest that tau pathology contributes to MBI primarily by disrupting salience network function and emphasize the role of the salience network in mediating relationships between neuropathological changes and behavioral manifestations.

HIGHLIGHTS

Network segregation mediates Alzheimer's disease (AD) pathology impact on mild behavioral impairment (MBI). The salience network is pivotal in linking tau pathology and MBI. This study used path analysis with AD biomarkers and network integrity. The study evaluated the roles of salience, default mode, and frontoparietal networks. This is the first study to integrate MBI with AD biomarkers and network functionality.

Breakthroughs and challenges for generating brain network-based biomarkers of treatment response in depression

Treatment outcomes widely vary for individuals diagnosed with major depressive disorder, implicating a need for deeper understanding of the biological mechanisms conferring a greater likelihood of response to a particular treatment. Our improved understanding of intrinsic brain networks underlying depression psychopathology via magnetic resonance imaging and other neuroimaging modalities has helped reveal novel and potentially clinically meaningful biological markers of response. And while we have made considerable progress in identifying such biomarkers over the last decade, particularly with larger, multisite trials, there are significant methodological and practical obstacles that need to be overcome to translate these markers into the clinic. The aim of this review is to review current literature on brain network structural and functional biomarkers of treatment response or selection in depression, with a specific focus on recent large, multisite trials reporting predictive accuracy of candidate biomarkers. Regarding pharmaco- and psychotherapy, we discuss candidate biomarkers, reporting that while we have identified candidate biomarkers of response to a single intervention, we need more trials that distinguish biomarkers between first-line treatments. Further, we discuss the ways prognostic neuroimaging may help to improve treatment outcomes to neuromodulation-based therapies, such as transcranial magnetic stimulation and deep brain stimulation. Lastly, we highlight obstacles and technical developments that may help to address the knowledge gaps in this area of research. Ultimately, integrating neuroimaging-derived biomarkers into clinical practice holds promise for enhancing treatment outcomes and advancing precision psychiatry strategies for depression management. By elucidating the neural predictors of treatment response and selection, we can move towards more individualized and effective depression interventions, ultimately improving patient outcomes and quality of life.

Aesthetic processing in neurodiverse populations

Neurodiversity is a perspective on cognition which suggests a non-pathological view of individual cognitive differences. Aesthetics research on neurodivergent brains has generally been limited to neuropsychological cases. Although this research has been integral to establishing the neurological correlates of aesthetic experience, it is crucial to expand this paradigm to more psychologically complex disorders. We offer a review of research on aesthetic preference in neurodivergent brains beyond neuropsychological cases: across populations with psychotic disorder, anhedonia and depression, anxiety disorder, and autism. We identify stable patterns of aesthetic bias in these populations, relate these biases to symptoms at perceptual, emotional, and evaluative levels of cognition, review relevant neurological correlates, and connect this evidence to current neuroaesthetics theory. Critically, we synthesize the reviewed evidence and discuss its relevance for three brain networks regularly implicated in aesthetic processing: the mesocorticolimbic reward circuit, frontolimbic connections, and the default mode network. Finally, we propose that broadening the subject populations for neuroaesthetics research to include neurodiverse populations is instrumental for yielding new insights into aesthetic processing in the brain.

A systematic review of the effect and mechanism of Daoyin therapy on improving mild cognitive impairment in older adults

BACKGROUND

Age-related cognitive decline is a pervasive problem in the aging population. Daoyin therapy is a mind-body movement characteristic of traditional Chinese medicine (TCM). Increasing evidence has reported its usefulness in improving cognitive function among different populations. However, there is no systematic review to assess the effect and mechanism of Daoyin therapy on mild cognitive dysfunction (MCI) in older adults.

OBJECTIVE

To systematically review the evidence on the effect and mechanism of Daoyin therapy on MCI in older adults.

RESULTS

Taichi, Baduanjin, and Yijinjing can improve cognitive function. Qigong and Wuqinxi can enhance the physical and cognitive functions related to balance, muscle strength, physical endurance, postural control, and flexibility. Taichi, Baduanjin, and Wuqinxi can improve the cognitive function of older adults and alleviate the symptoms associated with MCI through multiple mechanisms. The underlying mechanisms include activating the expression of signals and changing their connections in different brain regions, increasing brain capacity, and regulating brain-derived neurotropic and inflammatory factors.

CONCLUSION

In summary, the existing evidence from RCTs suggests that traditional Daoyin therapy, such as Taichi, Baduanjin, and Wuqinxi, is a promising strategy that can improve cognitive function and delay the onset of dementia in older adults with MCI by altering structural and neural activities and modulating other factors.

Default mode network-associated intrinsic connectivity relates to individual learnability differences in errorless and trial-and-error learning

The intrinsic functional network architecture accounts for task-evoked brain activity changes and variabilities in cognitive performance. Relationships between the intrinsic functional network architecture and task performance or learning ability have been previously reported. However, the relationships between learning benefits and the characteristics of intrinsic functional network architecture for different types of learning methods remain unclear. In this study, we used graph theoretical analysis to examine the relationships between intrinsic functional network connectivity and learning benefits in two well-known learning methods in the field of cognitive rehabilitation-errorless learning (EL learning) and trial-and-error learning (T&E learning). We focused on the default mode network (DMN) as a task-relevant network, which can differentiate between EL and T&E learning and was found to be more important for T&E learning in a previous study. Participants performed a color-name association task with both learning methods. The graph metrics used were within-network connectivity and efficiency for the DMN. Within-DMN connectivity and DMN efficiency showed a significantly weak positive correlation with T&E scores but not with EL scores. These findings show that the intrinsic integration strength within the DMN relates to individuals' learnability through the T&E method.

Resolving Heterogeneity in Posttraumatic Stress Disorder Using Individualized Structural Covariance Network Analysis

The heterogeneity of posttraumatic stress disorder (PTSD) is an obstacle to both understanding and therapy, and this has prompted a search for internally homogeneous neuroradiological subgroups within the broad clinical diagnosis. We set out to do this using the individual differential structural covariance network (IDSCN). We constructed cortical thickness-based IDSCN using T1-weighted images of 89 individuals with PTSD (mean age 42.8 years, 60 female) and 89 demographically matched trauma-exposed non-PTSD (TENP) controls (mean age 43.1 years, 63 female). The IDSCN metric quantifies how the structural covariance edges in a patient differ from those in the controls. We examined the structural diversity of PTSD and variation among subtypes using a hierarchical clustering analysis. PTSD patients exhibited notable diversity in distinct structural covariance edges but mainly affecting three networks: default mode, ventral attention, and sensorimotor. These changes predicted individual PTSD symptom severity. We identified two neuroanatomical subtypes: the one with higher PTSD symptom severity showed lower structural covariance edges in the frontal cortex and between frontal, parietal, and occipital cortex-regions that are functionally implicated in selective attention, response selection, and learning tasks. Thus, deviations in structural covariance in large-scale networks are common in PTSD but fall into two subtypes. This work sheds light on the neurobiological mechanisms underlying the clinical heterogeneity and may aid in personalized diagnosis and therapeutic interventions.

Modulation of Posterior Default Mode Network Activity During Interoceptive Attention and Relation to Mindfulness

Background

Interoceptive attention to internal sensory signals, such as the breath, is fundamental to mindfulness. However, interoceptive attention can be difficult to study, with many studies relying on subjective and retrospective measures. Response consistency is an established method for evaluating variability of attention on exteroceptive attention tasks, but it has rarely been applied to interoceptive attention tasks.

Methods

In this study, we measured consistency of response times on a breath-monitoring task with simultaneous electroencephalography in individuals across the life span (15-91 years of age, N = 324).

Results

We found that consistency on the breath-monitoring task was positively correlated with attentive performance on an exteroceptive inhibitory control task. Electroencephalography source reconstruction showed that on-task alpha band (8-12 Hz) activity was greater than that measured at rest. Low-consistency/longer breath responses were associated with elevated brain activity compared with high-consistency responses, particularly in posterior default mode network (pDMN) brain regions. pDMN activity was inversely linked with functional connectivity to the frontoparietal network and the cingulo-opercular network on task but not at rest, suggesting a role for these frontal networks in on-task regulation of pDMN activity. pDMN activity within the precuneus region was greater in participants who reported low subjective mindfulness and was adaptively modulated by task difficulty in an independent experiment.

Conclusions

Elevated pDMN alpha activity serves as an objective neural marker for low-consistency responding during interoceptive breath attention, scales with task difficulty, and is associated with low subjective mindfulness.

Food insecurity and adolescent impulsivity: The mediating role of functional connectivity in the context of family flexibility

Adolescent food insecurity is a salient adversity hypothesized to affect neural systems associated with increased impulsive behavior. Family environments shape how adverse experiences influence development. In this study, hypotheses were tested regarding the conjoint effects of food insecurity and family flexibility on impulsivity via alterations in connectivity between regions within the salience and central executive networks. Such alterations are reflected in resting-state functional connectivity (rsFC) metrics between the anterior insula (AI) and the middle frontal gyrus (MFG). Hypotheses were tested in a longitudinal moderated mediation model with two waves of data from 142 adolescents (Time 1 [T1] Mage = 12.89, SD = 0.85; Time 2 [T2] Mage = 15.01, SD = 1.07). Data on past-year household food insecurity, family flexibility, and rsFC were obtained at T1. Impulsivity was self-reported by the adolescent at T1 and T2. Findings revealed that high T1 left-to-left rsFC between the AI and MFG was associated with increased impulsivity at T2. The interaction of family flexibility and food insecurity was associated with AI and MFG rsFC. In the context of low family flexibility, food insecurity was linked to high levels of AI and MFG rsFC. Conversely, in the context of optimal family flexibility, food insecurity was associated with low levels of AI and MFG rsFC. Conditional indirect analysis suggests that the links among food insecurity, rsFC, and impulsive behavior depend on family flexibility. RESEARCH HIGHLIGHTS: Adolescent food insecurity was associated with anterior insula and middle frontal gyrus connectivity only at certain levels of family flexibility. High family flexibility attenuated the link between food insecurity and neural connectivity, while low levels of family flexibility increased this risk. High left anterior insula and left middle frontal gyrus connectivity was associated with increased impulsivity 1 year later.

Comparing mouse and human cingulate cortex organization using functional connectivity

The subdivisions of the extended cingulate cortex of the human brain are implicated in a number of high-level behaviors and affected by a range of neuropsychiatric disorders. Its anatomy, function, and response to therapeutics are often studied using non-human animals, including the mouse. However, the similarity of human and mouse frontal cortex, including cingulate areas, is still not fully understood. Some accounts emphasize resemblances between mouse cingulate cortex and human cingulate cortex while others emphasize similarities with human granular prefrontal cortex. We use comparative neuroimaging to study the connectivity of the cingulate cortex in the mouse and human, allowing comparisons between mouse 'gold standard' tracer and imaging data, and, in addition, comparison between the mouse and the human using comparable imaging data. We find overall similarities in organization of the cingulate between species, including anterior and midcingulate areas and a retrosplenial area. However, human cingulate contains subareas with a more fine-grained organization than is apparent in the mouse and it has connections to prefrontal areas not present in the mouse. Results such as these help formally address between-species brain organization and aim to improve the translation from preclinical to human results.

Altered brain function in treatment-resistant depression patients: A resting-state functional magnetic resonance imaging study

BACKGROUND

It has been established that there are functional changes in the brain of treatment-resistant depression (TRD) patients, but previous studies of functional connectivity (FC) usually involved selection of regions of interest based on accumulated a priori knowledge of the disorder. In this study, we combine amplitude of low-frequency fluctuation (ALFF) and FC; this approach, based on the abnormal ALFF, may provide some insights into the neural basis of the disease in terms of fMRI signals of low-frequency fluctuations.

METHODS

A total of 16 TRD patients, who visited the Qingdao Mental Health Center, Shandong Province, China between March 2023 and January 2024, along with 16 normal subjects, were enrolled into this study for functional imaging. In this study, we first explored the ALFF changes of TRD patients at a baseline resting state. Second, we selected the regions that were significantly changed in the ALFF as seeds and calculated the regional activity and functional connectivity (FC) of these regions using a seed-based approach. We also calculated correlations between the percent change in the PDQ-5D scores and ALFF values in brain regions with differing activity for TRD patients.

RESULTS

During the baseline resting state, by using the ALFF, we found a significantly decreased or increased ALFF in the TRD patients relative to the controls. These regions were located in the left/right postcentral gyrus (PoCG.L/PoCG.R), right cuneus(CUN.R). We found that the ALFF values of the right hippocampus (HIP.R) in the TRD group were negatively correlated with the PDQ-5D score. Then, we selected these brain regions as seeds to investigate the FC changes in brains of TRD patients. We found abnormal functional connectivity in left/right middle frontal gyrus(MFG.L/MFG.R), the right Inferior frontal gyrus, opercular part (IFGoperc.R), the left/right Anterior cingulate and paracingulate gyri (ACC.L/ACC.R), the right supramarginal gyrus (SMG.R), and the right Calcarine fissure and surrounding cortex (CAL.R).

CONCLUSION

We found a larger range of altered brain regions in TRD patients compared to healthy controls, especially in the central executive network (CEN), salience network (SN) and default mode network (DMN).

Opposing effects of pre-encoding stress on neural substrates of item and emotional contextual source memory retrieval

Although the mediating role of the stress hormone systems in memory for single- especially emotional- events is well-stablished, less is known about the influence of stress on memory for associated contextual information (source memory). Here, we investigated the impact of acute stress on the neural underpinnings of emotional contextual source memory. Participants underwent a stress or a control manipulation before they encoded objects paired with pleasant, neutral, or unpleasant backgrounds. One week later, item and contextual source memory were tested. Acute stress modulated the neural signature of item and contextual source memory in an opposite fashion: stressed participants showed larger activation in the precuneus and the medial prefrontal cortex (mPFC) during the retrieval of items, while the retrieval of contextual unpleasant information was associated with lower activation in the angular gyrus (AG) and mPFC. Furthermore, as revealed by cross-region representational similarity analyses, stress also reduced the memory reinstatement of the previously encoded visual cortex representations of object/unpleasant background pairings in the AG and mPFC. These results suggest that pre-encoding stress induction increases the activity of memory-related regions for single items but reduces the activity of these regions during the retrieval of contextual unpleasant information. Our findings provide new insights into the dissociative effects of stress on item and contextual source memory which could have clinical relevance for stress-related disorders.

Sex differences in trajectories of cortical development in autistic children from 2-13 years of age

Previous studies have reported alterations in cortical thickness in autism. However, few have included enough autistic females to determine if there are sex specific differences in cortical structure in autism. This longitudinal study aimed to investigate autistic sex differences in cortical thickness and trajectory of cortical thinning across childhood. Participants included 290 autistic (88 females) and 139 nonautistic (60 females) individuals assessed at up to 4 timepoints spanning ~2-13 years of age (918 total MRI timepoints). Estimates of cortical thickness in early and late childhood as well as the trajectory of cortical thinning were modeled using spatiotemporal linear mixed effects models of age-by-sex-by-diagnosis. Additionally, the spatial correspondence between cortical maps of sex-by-diagnosis differences and neurotypical sex differences were evaluated. Relative to their nonautistic peers, autistic females had more extensive cortical differences than autistic males. These differences involved multiple functional networks, and were mainly characterized by thicker cortex at ~3 years of age and faster cortical thinning in autistic females. Cortical regions in which autistic alterations were different between the sexes significantly overlapped with regions that differed by sex in neurotypical development. Autistic females and males demonstrated some shared differences in cortical thickness and rate of cortical thinning across childhood relative to their nonautistic peers, however these areas were relatively small compared to the widespread differences observed across the sexes. These results support evidence of sex-specific neurobiology in autism and suggest that processes that regulate sex differentiation in the neurotypical brain contribute to sex differences in the etiology of autism.

Early differences in lassitude predicts outcomes in Stanford Neuromodulation Therapy for difficult to treat depression

Stanford Neuromodulation Therapy (SNT), has recently shown rapid efficacy in difficult to treat (DTT) depression. We conducted an exploratory analysis of individual symptom improvements during treatment, correlated with fMRI, to investigate this rapid improvement in 23 DTT participants from an SNT RCT (12 active, 11 sham). Montgomery-Åsberg Depression Rating Scale item 7 (Lassitude) was the earliest to show improvements between active and sham, as early as treatment day 2. Lassitude score at treatment day 3 was predictive of response at 4 weeks post-treatment and response immediately after treatment. Participants with lower lassitude scores at treatment day 3 had different patterns of sgACC functional connectivity compared to participants with higher scores in both baseline and post-treatment minus baseline analyses. Further work will aim to first replicate these preliminary findings, and then to extend these findings and examine how SNT may affect lassitude and behavioral activation early in treatment.

Combination of magnetoencephalographic and clinical features to identify atypical self-limited epilepsy with centrotemporal spikes

INTRODUCTION

Our aim was to use magnetoencephalography (MEG) and clinical features to early identify self-limited epilepsy with centrotemporal spikes (SeLECTS) patients who evolve into atypical SeLECTS (AS).

METHODS

The baseline clinical and MEG data of 28 AS and 33 typical SeLECTS (TS) patients were collected. Based on the triple-network model, MEG analysis included power spectral density representing spectral power and corrected amplitude envelope correlation representing functional connectivity (FC). Based on the clinical and MEG features of AS patients, the linear support vector machine (SVM) classifier was used to construct the prediction model.

RESULTS

The spectral power transferred from the alpha band to the delta band in the bilateral posterior cingulate cortex, and the inactivation of the beta band in both the right anterior cingulate cortex and left middle frontal gyrus were distinctive features of the AS group. The FC network in the AS group was characterized by attenuated intrinsic FC within the salience network in the alpha band, as well as attenuated FC interactions between the salience network and both the default mode network and central executive network in the beta band. The prediction model that integrated MEG and clinical features had a high prediction efficiency, with an accuracy of 0.80 and an AUC of 0.84.

CONCLUSION

The triple-network model of early AS patients has band-dependent MEG alterations. These MEG features combined with clinical features can efficiently predict AS at an early stage.

Functional brain networks in clinical high-risk for bipolar disorder and psychosis

Abnormal connectivity in the brain has been linked to the pathophysiology of severe mental illnesses, including bipolar disorder and schizophrenia. The current study aimed to investigate large-scale functional networks and global network metrics in clinical high-risk for bipolardisorder (CHR-BD, n = 25), clinical high-risk for psychosis (CHR-P, n = 30), and healthy controls (HCs, n = 19). Help-seeking youth at CHR-BD and CHR-P were recruited from the early intervention program at Dokuz Eylul University, Izmir, Turkey. Resting-state functional magnetic resonance imaging scans were obtained from youth at CHR-BD, CHR-P, and HCs. Graph theoretical analysis and network-based statistics were employed to construct and examine the topological features of the whole-brain metrics and large-scale functional networks. Connectivity was increased (i) between the visual and default mode, (ii) between the visual and salience, (iii) between the visual and cingulo-opercular networks, and decreased (i) within the default mode and (ii) between the default mode and fronto-parietal networks in the CHR-P compared to HCs. Decreased global efficiency was found in CHR-P compared to CHR-BD. Functional networks were not different between CHR-BD and HCs. Global efficiency was negatively correlated with subthreshold positive symptoms and thought disorder in the high-risk groups. The current results suggest disrupted networks in CHR-P compared to HCs and CHR-BD. Moreover, transdiagnostic psychosis features are linked to functional brain networks in the at-risk groups. However, given the small, medicated sample, results are exploratory and hypothesis-generating.

Long-term cognitive training enhances fluid cognition and brain connectivity in individuals with MCI

Amnestic mild cognitive impairment (aMCI) is a risk factor for Alzheimer's disease (AD). Multi-domain cognitive training (CT) may slow cognitive decline and delay AD onset. However, most work involves short interventions, targeting single cognitive domains or lacking active controls. We conducted a single-blind randomized controlled trial to investigate the effect of a 6-month, multi-domain CT on Fluid Cognition, functional connectivity in memory and executive functioning networks (primary outcomes), and white matter microstructural properties (secondary outcome) in aMCI. Sixty participants were randomly assigned to either a multi-domain CT or crossword training (CW) group, and thirty-four participants completed the intervention. We found a significant group-by-time interaction in Fluid Cognition (p = 0.007, F (1,28) = 8.26, Cohen's d = 0.38, 95% confidence interval [CI]: 2.45-14.4), with 90% of CT patients showing post-intervention improvements (p < 0.01, Cohen's d = 0.7). The CT group also showed better post-intervention Fluid Cognition than healthy controls (HCs, N = 45, p = 0.045). Functional connectivity analyses showed a significant group-by-time interaction (Cohen's d ≥ 0.8) in the dorsolateral prefrontal cortex (DLPFC) and inferior parietal cortex (IPC) networks. Specifically, CT displayed post-intervention increases whereas CW displayed decreases in functional connectivity. Moreover, increased connectivity strength between the left DLPFC and medial PFC was associated with improved Fluid Cognition. At a microstructural level, we observed a decline in fiber density (FD) for both groups, but the CT group declined less steeply (1.3 vs. 2%). The slower decline in FD for the CT group in several tracts, including the cingulum-hippocampus tract, was associated with better working memory. Finally, we identified regions in cognitive control and memory networks for which baseline functional connectivity and microstructural properties were associated with changes in Fluid Cognition. Long-term, multi-domain CT improves cognitive functioning and functional connectivity and delays structural brain decline in aMCI (ClinicalTrials.gov number: NCT03883308).

Structural brain network organization in children with prenatal alcohol exposure

INTRODUCTION

There is growing evidence suggesting that children with prenatal alcohol exposure (PAE) struggle with cognitively demanding tasks, such as learning, attention, and language. Complex structural network analyses can provide insight into the neurobiological underpinnings of these functions, as they may be sensitive for characterizing the effects of PAE on the brain. However, investigations on how PAE affects brain networks are limited. We aim to compare diffusion magnetic resonance imaging (MRI) tractography-based structural networks between children with low-to-moderate PAE in trimester 1 only (T1) or throughout all trimesters (T1-T3) with those without alcohol exposure prenatally.

METHODS

Our cohort included three groups of children aged 6 to 8 years: 1) no PAE (n = 24), 2) low-to-moderate PAE during T1 only (n = 30), 3) low-to-moderate PAE throughout T1-T3 (n = 36). Structural networks were constructed using the multi-shell multi-tissue constrained spherical deconvolution tractography technique. Quantitative group-wise analyses were conducted at three levels: (a) at the whole-brain network level, using both network-based statistical analyses and network centrality; and then using network centrality at (b) the modular level, and (c) per-region level, including the regions identified as brain hubs.

RESULTS

Compared with the no PAE group, widespread brain network alterations were observed in the PAE T1-T3 group using network-based statistics, but no alterations were observed for the PAE T1 group. Network alterations were also detected at the module level in the PAE T1-T3 compared with the no PAE group, with lower eigenvector centrality in the module that closely represented the right cortico-basal ganglia-thalamo-cortical network. No significant group differences were found in network centrality at the per-region level, including the hub regions.

CONCLUSIONS

This study demonstrated that low-to-moderate PAE throughout pregnancy may alter brain structural connectivity, which may explain the neurodevelopmental deficits associated with PAE. It is possible that timing and duration of alcohol exposure are crucial, as PAE in T1 only did not appear to alter brain structural connectivity.

Structural alterations in a rumination-related network in patients with major depressive disorder

Rumination is a common symptom in major depressive disorder (MDD). Previous work has connected individual differences in rumination to structural properties in various brain regions. Some of these, such as the dorsolateral prefrontal cortex (dlPFC), have also been highlighted as being altered in MDD, suggesting a connection between structural changes and ruminative symptoms. Although informative, such localised relations have limitations in the context of a network view of the brain. To further investigate rumination-related structural changes in depression, and to situate these within potential functional networks, we acquired T1-weighted structural MRI data from patients with MDD (n = 32) and controls (n = 69). Rumination was measured with the Rumination Response Scale. Surface-based, whole-brain analysis of cortical grey-matter identified group differences in the dlPFC that were, however, not related to rumination. Instead, rumination was correlated with grey-matter properties in the right precuneus. Using normative functional connectivity analysis on an independent sample (n = 100), we show these two regions to be interconnected. Further developing a network-based perspective, it was shown that the rumination-related precuneus region is connected with networks associated with processes such as executive function, autobiographical memory, and visual perception. Notably, these processes have been connected to rumination. These results suggest that rumination in depression may be linked to focal structural changes. The effects of these focal changes on rumination may then be connected to their influence on distributed functional networks.

Resting state network changes induced by experimental inaudible infrasound exposure and associations with self-reported noise sensitivity and annoyance

The effects of prolonged infrasound (IS) exposure on brain function and behavior are largely unknown, with only one prior study investigating functional connectivity (FC) changes. In a long-term randomized-controlled trial, 38 participants were exposed to inaudible airborne IS (6 Hz, 80-90 dB) or sham devices for four weeks (8 h/night). We assessed FC changes in resting-state networks (auditory, default mode (DMN), sensorimotor (SMN), and executive control (ECN)), and explored IS 'sensitivity' as a predictor of identified significant FC changes. We also examined correlations between somatic symptoms and FC. IS exposure led to decreased FC in the right precuneus (DMN) and increased FC in the Vermis IV and V (SMN). In the ECN, we observed increased FC in the right frontal middle gyrus (BA8) and the right inferior parietal lobe, and decreased FC in another region of the right frontal middle gyrus. Changes in the ECN (right inferior parietal lobe) were negatively associated with self-reported annoyance from IS/low-frequency noise. A significant negative association was found between FC changes in the DMN (right precuneus) and somatic symptoms. Our study is the first to investigate prolonged IS exposure effects on brain FC, revealing changes in the vDMN, SMN, and ECN, but not in the auditory network. Future studies should assess annoyance and sensitivity markers, fine-grained measures of somatic symptoms, and stratify samples by sensitivity to uncover individual differences in response to IS.

Shedding Light on the Aftermath: Childhood Maltreatment's Role in Modifying the Association Between Recent Life Stress and Resting-State Network Connectivity

Childhood maltreatment has been demonstrated to impact brain development. However, whether childhood maltreatment can influence the effects of recent stress on brain networks remains unclear. This study aimed to investigate whether childhood maltreatment moderates the longitudinal relationship between recent life stress and within- and between-network connectivity in key brain networks, including the anterior salience (ASN), central executive (CEN), default mode (DMN), and emotional regulation network (ERN). A cohort of 172 individuals from the Neuroscience in Psychiatry Network (NSPN) underwent MRI scans at two specific time points and undertook evaluations of childhood maltreatment and recent life stress. The results showed that childhood abuse moderated the association of recent life stress with the within-network connectivity of ASN and ERN but not DMN and CEN. Furthermore, recent life stress significantly interacted with childhood abuse to be associated with the between-network connectivity of ASN-DMN, ASN-CEN, ASN-ERN, DMN-ERN and CEN-ERN. Overall, among youth exposed to higher degrees of childhood abuse, greater recent life stress was longitudinally associated with increased network connectivity. Understanding these interactions can provide valuable insights for developing prevention strategies and interventions aimed at mitigating the lasting impact of childhood maltreatment on brain development and overall well-being.

The alterations of repetitive transcranial magnetic stimulation on the energy landscape of resting-state networks differ across the human cortex

Repetitive transcranial magnetic stimulation (rTMS) is a promising intervention tool for the noninvasive modulation of brain activity and behavior in neuroscience research and clinical settings. However, the resting-state dynamic evolution of large-scale functional brain networks following rTMS has rarely been investigated. Here, using resting-state fMRI images collected from 23 healthy individuals before (baseline) and after 1 Hz rTMS of the left frontal (FRO) and occipital (OCC) lobes, we examined the different effects of rTMS on brain dynamics across the human cortex. By fitting a pairwise maximum entropy model (pMEM), we constructed an energy landscape for the baseline and poststimulus conditions by fitting a pMEM. We defined dominant brain states (local minima) in the energy landscape with synergistic activation and deactivation patterns of large-scale functional networks. We calculated state dynamics including appearance probability, transitions and duration. The results showed that 1 Hz rTMS induced increased and decreased state probability, transitions and duration when delivered to the FRO and OCC targets, respectively. Most importantly, the shortest path and minimum cost between dominant brain states were altered after stimulation. The absolute sum of the costs from the source states to the destinations was lower after OCC stimulation than after FRO stimulation. In conclusion, our study characterized the dynamic trajectory of state transitions in the energy landscape and suggested that local rTMS can induce significant dynamic perturbation involving stimulated and distant functional networks, which aligns with the modern view of the dynamic and complex brain. Our results suggest low-dimensional mapping of rTMS-induced brain adaption, which will contribute to a broader and more effective application of rTMS in clinical settings.

The interplay between insomnia symptoms and Alzheimer's disease across three main brain networks

STUDY OBJECTIVES

Insomnia symptoms are prevalent along the trajectory of Alzheimer's disease (AD), but the neurobiological underpinning of their interaction is poorly understood. Here, we assessed structural and functional brain measures within and between the default mode network (DMN), salience network, and central executive network (CEN).

METHODS

We selected 320 participants from the ADNI database and divided them by their diagnosis: cognitively normal (CN), Mild Cognitive Impairment (MCI), and AD, with and without self-reported insomnia symptoms. We measured the gray matter volume (GMV), structural covariance (SC), degrees centrality (DC), and functional connectivity (FC), testing the effect and interaction of insomnia symptoms and diagnosis on each index. Subsequently, we performed a within-group linear regression across each network and ROI. Finally, we correlated observed abnormalities with changes in cognitive and affective scores.

RESULTS

Insomnia symptoms were associated with FC alterations across all groups. The AD group also demonstrated an interaction between insomnia and diagnosis. Within-group analyses revealed that in CN and MCI, insomnia symptoms were characterized by within-network hyperconnectivity, while in AD, within- and between-network hypoconnectivity was ubiquitous. SC and GMV alterations were nonsignificant in the presence of insomnia symptoms, and DC indices only showed network-level alterations in the CEN of AD individuals. Abnormal FC within and between DMN and CEN hubs was additionally associated with reduced cognitive function across all groups, and increased depressive symptoms in AD.

CONCLUSIONS

We conclude that patients with clinical AD present with a unique pattern of insomnia-related functional alterations, highlighting the profound interaction between both conditions.

White matter alterations associated with chronic cannabis use disorder: a structural network and fixel-based analysis

Cannabis use disorder (CUD) is associated with adverse mental health effects, as well as social and cognitive impairment. Given prevalence rates of CUD are increasing, there is considerable efforts, and need, to identify prognostic markers which may aid in minimising any harm associated with this condition. Previous neuroimaging studies have revealed changes in white matter (WM) organization in people with CUD, though, the findings are mixed. In this study, we applied MRI-based analysis techniques that offer complimentary mechanistic insights, i.e., a connectome approach and fixel-based analysis (FBA) to investigate properties of individual WM fibre populations and their microstructure across the entire brain, providing a highly sensitive approach to detect subtle changes and overcome limitations of previous diffusion models. We compared 56 individuals with CUD (median age 25 years) to a sample of 38 healthy individuals (median age 31.5 years). Compared to controls, those with CUD had significantly increased structural connectivity strength (FDR corrected) across 9 edges between the right parietal cortex and several cortical and subcortical regions, including left orbitofrontal, left temporal pole, and left hippocampus and putamen. Utilizing FBA, WM density was significantly higher in those with CUD (FWE-corrected) across the splenium of the corpus callosum, and lower in the bilateral cingulum and right cerebellum. We observed significant correlation between cannabis use over the past month and connectivity strength of the frontoparietal edge, and between age of regular use and WM density of the bilateral cingulum and right cerebellum. Our findings enhance the understanding of WM architecture alterations associated with CUD.

How the arts heal: a review of the neural mechanisms behind the therapeutic effects of creative arts on mental and physical health

Background

The creative arts have long been known for their therapeutic potential. These modalities, which include dance, painting, and music, among others, appear to be effective in enhancing emotional expression and alleviating adverse physiological and psychological effects. Engagement in creative arts can be pursued as a personal hobby, in a classroom setting, or through a formal therapeutic intervention with a qualified therapist. Engagement can be active (i.e., creating) or passive (i.e., viewing, listening). Regardless of the modality and manner of engagement, the mechanisms explaining the therapeutic efficacy of creative arts remain poorly understood.

Objective

This study aims to systematically review research investigating the neurological mechanisms activated during active or passive engagement in creative arts, with a specific emphasis on the roles of the medial prefrontal cortex (mPFC) and the amygdala in emotional regulation (ER) and creative behaviors. The review seeks to provide preliminary evidence for the possible existence of common neural mechanisms underlying both phenomena, which could inform the development of targeted therapeutic interventions leveraging creative arts for ER.

Methods

A systematic review was conducted following the Cochrane Collaboration guideline and PRISMA standards to identify studies examining the neurological mechanisms underlying creative activities.

Results

A total of six out of 85 records meet the inclusion criteria, with all being basic research studies. Preliminary findings suggest that active and passive engagement with creative arts consistently activate neural circuits implicated in adaptive emotional regulation, including the mPFC and amygdala. These activations mirror the neural pathways engaged in effective ER strategies, suggesting the possible existence of shared mechanisms between creative expression and emotional processing.

Conclusion

The evidence underscores the potential of creative arts as a complementary therapeutic strategy alongside conventional care and other evidence-based mind-body modalities. By elucidating the shared neural mechanisms between creative arts engagement and ER, this review contributes to the theoretical and practical understanding of the role of creative arts in mental health. Future research is recommended to further explore these neural correlations and their implications for therapeutic practice.

REM sleep remains paradoxical: sub-states determined by thalamo-cortical and cortico-cortical functional connectivity

During paradoxical sleep (PS, aka REM sleep) the cerebral cortex displays rapid electroencephalographic activity similar to that of wakefulness, whereas in the posterior associative thalamus, rapid activity is interrupted by frequent periods of slow-wave (delta) oscillations at 2-3 Hz, thereby dissociating the intrinsic frequency in thalamus and cortex. Here we studied the functional consequences of such a dissociation using intrathalamic and intracortical recordings in 21 epileptic patients, applying coherence analysis to examine changes in functional connectivity between the posterior thalamus (mainly medial pulvinar) and six cortical functional networks, and also between each cortical network with respect to the others. Periods of slow-wave thalamic activity ('delta PS') were more prevalent than phases of 'rapid PS,' and the delta/rapid thalamic alternance did not overlap with the classical tonic/phasic dichotomy based on rapid eye movements. Thalamo-cortical and cortico-cortical functional connectivity significantly decreased during delta PS, relative to both rapid PS periods and to wakefulness. The fact that delta thalamic activity and low thalamo-cortical binding coincided with a suppression of cortico-cortical connectivity supports a crucial role for the posterior associative thalamus, and particularly the medial pulvinar, in ensuring trans-thalamic communication between distant cortical areas. Disruption of such a trans-thalamic communication during delta PS compromises the functional binding between cortical areas, and consequently might contribute to the alteration of perceptual experiences commonly reported during dreams. KEY POINTS: During paradoxical, or REM, sleep (PS), rapid thalamic activity is interrupted by frequent periods of slow delta waves at 2-3 Hz. During these periods of thalamic delta activity there was a drastic drop of functional connectivity between associative thalamus and cortex, and also among different cortical networks. The delta/rapid alternance did not overlap with the classically defined 'tonic/phasic' periods and therefore suggests a distinct dichotomy of functional states in PS. Recurrent decrease in thalamo-cortical and cortico-cortical functional connectivity during PS may compromise the spatio-temporal binding between cortical areas, which in turn could hinder the formation of coherent mental content during dreams.

Enhanced diversity on connector hubs following sleep deprivation: Evidence from diffusion and functional magnetic resonance imaging

Sleep deprivation has been demonstrated to exert widespread and intricate impacts on the brain network. The human brain network is a modular network composed of interconnected nodes. This network consists of provincial hubs and connector hubs, with provincial hubs having diverse connectivities within their own modules, while connector hubs distribute their connectivities across different modules. The latter is crucial for integrating information from various modules and ensuring the normal functioning of the modular brain. However, there has been a lack of systematic investigation into the impact of sleep deprivation on brain connector hubs. In this study, we utilized functional connectivity from resting-state functional magnetic resonance imaging, as well as structural connectivity from diffusion-weighted imaging, to systematically explore the variation of connector hub properties in the cerebral cortex after one night of sleep deprivation. The normalized participation coefficients (PCnorm) were utilized to identify connector hubs. In both the functional and structural networks, connector hubs exhibited a significant increase in average PCnorm, indicating the diversity enhancement of the connector hub following sleep deprivation. This enhancement is associated with increased network cost, reduced modularity, and decreased small-worldness, but enhanced global efficiency. This may potentially signify a compensatory mechanism within the brain following sleep deprivation. The significantly affected connector hubs were primarily observed in both the Control Network and Salience Network. We believe that the observed results reflect the increasing demand on the brain to invest more effort at preventing performance deterioration after sleep loss, in exchange for increased communication efficiency, especially involving systems responsible for neural resource allocation and cognitive control. These results have been replicated in an independent dataset. In conclusion, this study has enhanced our understanding of the compensatory mechanism in the brain response to sleep deprivation. This compensation is characterized by an enhancement in the connector hubs responsible for inter-modular communication, especially those related to neural resource and cognitive control. As a result, this compensation comes with a higher network cost but leads to an improvement in global communication efficiency, akin to a more random-like network manner.

Robust and replicable functional brain signatures of 22q11.2 deletion syndrome and associated psychosis: a deep neural network-based multi-cohort study

A major genetic risk factor for psychosis is 22q11.2 deletion (22q11.2DS). However, robust and replicable functional brain signatures of 22q11.2DS and 22q11.2DS-associated psychosis remain elusive due to small sample sizes and a focus on small single-site cohorts. Here, we identify functional brain signatures of 22q11.2DS and 22q11.2DS-associated psychosis, and their links with idiopathic early psychosis, using one of the largest multi-cohort data to date. We obtained multi-cohort clinical phenotypic and task-free fMRI data from 856 participants (101 22q11.2DS, 120 idiopathic early psychosis, 101 idiopathic autism, 123 idiopathic ADHD, and 411 healthy controls) in a case-control design. A novel spatiotemporal deep neural network (stDNN)-based analysis was applied to the multi-cohort data to identify functional brain signatures of 22q11.2DS and 22q11.2DS-associated psychosis. Next, stDNN was used to test the hypothesis that the functional brain signatures of 22q11.2DS-associated psychosis overlap with idiopathic early psychosis but not with autism and ADHD. stDNN-derived brain signatures distinguished 22q11.2DS from controls, and 22q11.2DS-associated psychosis with very high accuracies (86-94%) in the primary cohort and two fully independent cohorts without additional training. Robust distinguishing features of 22q11.2DS-associated psychosis emerged in the anterior insula node of the salience network and the striatum node of the dopaminergic reward pathway. These features also distinguished individuals with idiopathic early psychosis from controls, but not idiopathic autism or ADHD. Our results reveal that individuals with 22q11.2DS exhibit a highly distinct functional brain organization compared to controls. Additionally, the brain signatures of 22q11.2DS-associated psychosis overlap with those of idiopathic early psychosis in the salience network and dopaminergic reward pathway, providing substantial empirical support for the theoretical aberrant salience-based model of psychosis. Collectively, our findings, replicated across multiple independent cohorts, advance the understanding of 22q11.2DS and associated psychosis, underscoring the value of 22q11.2DS as a genetic model for probing the neurobiological underpinnings of psychosis and its progression.

Integrating dynamic psychophysiological indices across time and contexts: Elucidating mechanisms, risk markers, and intervention targets

Why should researchers measure psychophysiological processes repeatedly over time? The study of psychophysiology inherently involves sampling biological processes as they manifest over time. The most common approach is to use a brief sample to make conclusions about how individuals or groups differ. Although these types of between-subject comparisons have utility for understanding individual and group differences, many of the important conceptual questions in the field involve processes that are dynamic, varying within individuals over time. Using examples from the literature on affect regulation, this conceptual review contrasts three types of study designs: the classic single-observation design and the aggregated and temporally linked repeated observation designs, which have great promise for measuring variables that fluctuate dynamically over time. Importantly, these designs can be integrated to elucidate research questions about risk (when and for whom will the likelihood of an unwanted outcome occurring increase?), mechanisms (how and why does a change in psychophysiology contribute to a change in another process of interest?), and interventions (how and when should interventions take place to modify an outcome?). Researchers are encouraged to implement intensive sampling in their research, which can be conducted in traditional laboratory settings (e.g., fMRI, event-related brain potentials, and heart rate variability) and in ecologically valid contexts in everyday life using ambulatory assessment.

Neuroimaging of posttraumatic stress disorder in adults and youth: progress over the last decade on three leading questions of the field

Almost three decades have passed since the first posttraumatic stress disorder (PTSD) neuroimaging study was published. Since then, the field of clinical neuroscience has made advancements in understanding the neural correlates of PTSD to create more efficacious treatment strategies. While gold-standard psychotherapy options are available, many patients do not respond to them, prematurely drop out, or never initiate treatment. Therefore, elucidating the neurobiological mechanisms that define the disorder can help guide clinician decision-making and develop individualized mechanisms-based treatment options. To this end, this narrative review highlights progress made in the last decade in adult and youth samples on three outstanding questions in PTSD research: (1) Which neural alterations serve as predisposing (pre-exposure) risk factors for PTSD development, and which are acquired (post-exposure) alterations? (2) Which neural alterations can predict treatment outcomes and define clinical improvement? and (3) Can neuroimaging measures be used to define brain-based biotypes of PTSD? While the studies highlighted in this review have made progress in answering the three questions, the field still has much to do before implementing these findings into clinical practice. Overall, to better answer these questions, we suggest that future neuroimaging studies of PTSD should (A) utilize prospective longitudinal designs, collecting brain measures before experiencing trauma and at multiple follow-up time points post-trauma, taking advantage of multi-site collaborations/consortiums; (B) collect two scans to explore changes in brain alterations from pre-to-post treatment and compare changes in neural activation between treatment groups, including longitudinal follow up assessments; and (C) replicate brain-based biotypes of PTSD. By synthesizing recent findings, this narrative review will pave the way for personalized treatment approaches grounded in neurobiological evidence.