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Brain gray matter (GM) reductions have been reported after breast cancer chemotherapy, typically in small and/or cross-sectional cohorts, most commonly using voxel-based morphometry (VBM). There has been little examination of approaches such as deformation-based morphometry (DBM), machine-learning-based brain aging metrics, or the relationship of clinical and demographic risk factors to GM reduction. This international data pooling study begins to address these questions. Participants included breast cancer patients treated with (CT+, n = 183) and without (CT-, n = 155) chemotherapy and noncancer controls (NC, n = 145), scanned pre- and post-chemotherapy or comparable intervals. VBM and DBM examined GM volume. Estimated brain aging was compared to chronological aging. Correlation analyses examined associations between VBM, DBM, and brain age, and between neuroimaging outcomes, baseline age, and time since chemotherapy completion. CT+ showed longitudinal GM volume reductions, primarily in frontal regions, with a broader spatial extent on DBM than VBM. CT- showed smaller clusters of GM reduction using both methods. Predicted brain aging was significantly greater in CT+ than NC, and older baseline age correlated with greater brain aging. Time since chemotherapy negatively correlated with brain aging and annual GM loss. This large-scale data pooling analysis confirmed findings of frontal lobe GM reduction after breast cancer chemotherapy. Milder changes were evident in patients not receiving chemotherapy. CT+ also demonstrated premature brain aging relative to NC, particularly at older age, but showed evidence for at least partial GM recovery over time. When validated in future studies, such knowledge could assist in weighing the risks and benefits of treatment strategies., (© 2023. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Neural dysfunction and cognitive complaints are associated with chemotherapy for breast cancer although trajectory and contributory factors remain unclear. We prospectively examined neurocognition using fMRI and self-reported cognitive, physical and psychological symptoms in women treated with adjuvant chemotherapy over one year. Patients treated with (n = 28) or without (n = 34) chemotherapy for localized breast cancer and healthy controls (n = 30) performed a Verbal Working Memory Task (VWMT) during fMRI and provided self-reports at baseline (pre-adjuvant treatment), five- (M5) and 12-months (M12). Repeated measures ANOVA and multivariable regression determined change over time and possible predictors (e.g., hemoglobin, physical symptoms, worry) of VWMT performance, fMRI activity in the frontoparietal executive network, and cognitive complaints at M12. Trajectories of change in VWMT performance for chemotherapy and healthy control groups differed significantly with the chemotherapy group performing worse at M12. Chemotherapy patients had persistently higher spatial variance (neural inefficiency) in executive network fMRI-activation than both other groups from baseline to M12. Cognitive complaints were similar among groups over time. At M12, VWMT performance and executive network spatial variance were each independently predicted by chemotherapy treatment and their respective baseline values, while cognitive complaints were predicted by baseline level, physical symptoms and worry. Executive network inefficiency and neurocognitive performance deficits pre-adjuvant treatment predict cognitive dysfunction one-year post-baseline, particularly in chemotherapy-treated patients. Persistent cognitive complaints are linked with physical symptom severity and worry regardless of treatment. Pre-chemotherapy interventions should target both neurocognitive deficits and symptom burden to improve cognitive outcomes for breast cancer survivors.

Visual attention problems have been reported in association with prenatal alcohol exposure (PAE). With related behavioral data documented in literature, further investigation of this PAE effect would benefit from integrating functional and anatomical imaging data to ascertain its neurobiological basis. The current study investigated the possible functional and anatomical bases for the PAE-related visual sustained attention deficit. Functional magnetic resonance imaging (fMRI) data were collected while the subjects performed a sustained visual attention task. High resolution, three dimensional anatomical images were also collected for morphometric evaluation. In the alcohol-affected subjects, we observed a significant white and gray matter volume reduction in the occipital-temporal area. Meanwhile, their fMRI activations in the same region resided more superiorly than that of the controls resulting in reduced activation in the ventral occipital-temporal area. The location of this PAE functional abnormality approximately matches that of the significant structural reduction. In addition to the well documented corpus callosum abnormalities observed in PAE subjects, the present results reveal a teratogenic effect on the occipital-temporal area. Furthermore, as the occipital-temporal area plays an important role in visual attention, the current observation suggests a neurobiological underpinning for the PAE related deficit in sustained visual attention.

Disrupted whole-brain resting-state functional connectivity (RSFC) of the posterior cingulate (PCC) has been highlighted to associate with cognitive and affective dysfunction in major depressive disorder (MDD). However, prior findings showed certain inconsistency about the RSFC of the PCC in MDD. This study aims to investigate the aberrant RSFC of the PCC in MDD using anisotropic effect-size version of seed-based d mapping (AES-SDM). Web of Science and PubMed were searched for studies investigating PCC-based RSFC in MDD. A total of 17 studies, involving 804 patients and 724 healthy controls (HCs), fit our selection criteria. Additionally, to seek for the link between functional and structural differences, we did a meta-analysis on the studies in conjunction with voxel-based morphology (VBM) analysis. The PCC showed higher RSFC with the left middle temporal gyrus (MTG) and the right middle frontal gyrus (MFG), and lower RSFC with the left superior frontal gyrus (SFG) and the left precuneus in patients with MDD than HCs. Moreover, the meta-regression analysis revealed a negative correlation between the FC alteration of the right MFG with the PCC and depression severity. Notably, the left MTG and the left MFG demonstrated gray matter deviations in conjunction analysis. Our results indicated that the aberrant RSFC between the PCC and brain regions sub-serving cognitive control and emotional regulation in patients with MDD. And such functional alterations may have structural basis. These findings may underlie the mechanisms of deficits in cognitive control and emotional regulation of MDD., (© 2022. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Our study investigated the associations between the clinical benefits of telehealth-delivered cognitive behavioral therapy for insomnia (tele-CBT-I) and the salience network in fibromyalgia (FM). Thirty-five FM patients with comorbid insomnia were recruited and assigned into two groups: the tele-CBT-I group (n = 17) or the treatment-as-usual (TAU) group (n = 18). At baseline and post-treatment, clinical status was assessed using standardized scales, including the Insomnia Severity Index (ISI), Brief Pain Inventory, Numeric Pain Rating scale, Beck Depression Intervention version II, Beck Anxiety Intervention, Situational Fatigue Scale, and Fibromyalgia Impact Questionnaires. Resting-state functional magnetic resonance imaging was collected. We compared within- and between-group differences in clinical changes and functional connectivity (FC) of the salience network. A factor analysis of significant FCs was performed. Correlation analyses between clinical symptoms and salience FCs were conducted. The tele-CBT-I group showed sleep quality improvements after treatment that were greater than those in the TAU group (p-value = 0.038). After treatment, tele-CBT-I decreased FCs of cortical regions and increased FCs of subcortical regions compared to the TAU group. Additionally, factor analysis grouped the significant FCs into cortical factors and subcortical factors. The cortical factor value, representing the involvement of specific cortical regions of the salience network by the factor analysis, was significantly associated with ISI scores in the tele-CBT-I group (p-value = 0.0002). In conclusion, tele-CBT-I might be an adjuvant approach to improve sleep quality and normalize cortical and subcortical functions of the salience network in FM patients with comorbid insomnia., (© 2024. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Increasing evidence has shown that the resting state brain connectivity of default mode network (DMN) which are important for social cognition are disrupted in autism spectrum disorder (ASD). However, previous neuroimaging studies did not present consistent results. Therefore, we performed a meta-analysis of resting-state functional connectivity (rsFC) studies of DMN in the individuals with ASD and healthy controls (HCs) to provide a new perspective for investigating the pathophysiology of ASD. We carried out a search using the terms: ("ASD" OR "Autism") AND ("resting state" OR "rest") AND ("DMN" OR "default mode network") in PubMed, Web of Science and Embase to identify the researches published before January 2020. Ten resting state datasets including 203 patients and 208 HCs were included. Anisotropic Effect Size version of Signed Differential Mapping (AES-SDM) method was applied to identify group differences. In comparison with the HCs, the patients with ASD showed increased connectivity in cerebellum, right middle temporal gyrus, superior occipital gyrus, right supramarginal gyrus, supplementary motor area and putamen. Decreased connectivity was discovered in some nodes of DMN, such as medial prefrontal cortex, precuneus and angular gyrus. These results may help us to further clarify the neurobiological mechanisms in patients with ASD., (© 2021. The Author(s), under exclusive licence to Springer Science+Business Media, LLC part of Springer Nature.)

Neuroimaging studies have demonstrated that autism spectrum disorder (ASD) is accompanied by abnormal functional and structural features in specific brain regions of the default mode network (DMN). However, little is known about the alterations of the topological organization and the functional connectivity (FC) of the DMN in ASD patients. Thirty-seven ASD patients and 38 healthy control (HC) participants underwent a resting-state functional magnetic resonance imaging scan. Twenty DMN subregions were specifically selected to construct the DMN architecture. We applied graph theory approaches to the topological configuration and compare the FC patterns of the DMN. We then examined the relationships between the neuroimaging measures of the DMN and clinical characteristics in patients with ASD. The current study revealed that both the ASD and HC participants showed a small-world regimen in the DMN; however there were no significant differences in global network measures. Compared with the HC group, the ASD group exhibited significantly decreased nodal centralities in the bilateral anterior medial prefrontal cortex and increased nodal centralities in the right lateral temporal cortex and the right retrosplenial cortex. Patients with ASD displayed significantly reduced and increased FC within the DMN. Our findings demonstrated that ASD patients showed a pattern of disrupted FC metrics and nodal network metrics in the DMN, which could be a potential biomarker for objective ASD diagnoses and for the level of autism spectrum traits. HIGHLIGHTS: We used graph theoretical approaches and functional connectivity (FC) to investigate the topological configuration and FC patterns of the DMN in ASD. The current study revealed that both ASD and HC participants exhibited small-world regimes in the DMN, however there were no significant differences in global network measures. The ASD group showed abnormal nodal centralities in the bilateral aMPFC, the right LTC and the Rsp of the DMN, and ASD was characterized by altered FC patterns, including decreased and increased FC within the DMN.

Aberrant intrinsic brain networks are consistently observed in individuals with autism spectrum disorder. However, studies examining the strength of functional connectivity across brain regions have yielded conflicting results. Therefore, this study aimed to investigate the functional connectivity of the resting brain in children with low-functioning autism, including during the early developmental stages. We explored the functional connectivity of 43 children with autism spectrum disorder and 54 children with typical development aged 2 to 12 years using resting-state functional magnetic resonance imaging data. We used independent component analysis to classify the brain regions into six intrinsic networks and analyzed the functional connectivity within each network. Moreover, we analyzed the relationship between functional connectivity and clinical scores. In children with autism, the under-connectivities were observed within several brain networks, including the cognitive control, default mode, visual, and somatomotor networks. In contrast, we found over-connectivities between the subcortical, visual, and somatomotor networks in children with autism compared with children with typical development. Moderate effect sizes were observed in entire networks (Cohen's d = 0.43-0.77). These network alterations were significantly correlated with clinical scores such as the communication sub-score (r = - 0.442, p = 0.045) and the calibrated severity score (r = - 0.435, p = 0.049) of the Autism Diagnostic Observation Schedule. These opposing results observed based on the brain areas suggest that aberrant neurodevelopment proceeds in various ways depending on the functional brain regions in individuals with autism spectrum disorder., (© 2024. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Objectives: The alterations in cerebellar activity that occur in vascular mild cognitive impairment remain largely unexplored. This study aimed to investigate potential associations between abnormal cerebellar functional connectivity (FC) and changes in cognitive function by examining intracerebellar and cerebellar-cerebral FC., Methods: MRI data were collected from seventy-two patients with vascular mild cognitive impairment (VMCI), comprising 38 patients with small vessel mild cognitive impairment (SVMCI) and 34 with poststroke mild cognitive impairment (PSMCI), and from 43 demographically matched healthy controls (HCs). Changes in FC between subregions within the cerebellum and from each cerebellar subregion to the selected cerebral seed points in VMCI patients were calculated, and the association of these changes with cognitive function was examined., Results: Compared with HCs, we found that VMCI patients had 11 cerebellar subregions showing significant differences (mainly decreases) in FC with brain regions in the default-mode network (DMN), sensory-motor network (SMN), and frontoparietal network (FPN). In the intracerebellar FC analysis, 47 (8%) cerebellar connections had significant intergroup differences, mainly a reduced magnitude of FC in VMCI patients. In the correlation analysis, higher Montreal Cognitive Assessment (MoCA) scores were correlated with stronger intracerebellar FC (left crus II-right lobule VI, left crus II-right lobule VIIb) and cerebellar-cerebral FC (right lobule X-left precuneus, vermal lobule IX-right inferior parietal lobule) in both the SVMCI and PSMCI groups., Conclusion: These findings suggest prominent intracerebellar and cerebellar-cerebral FC abnormalities in VMCI patients, contributing evidence for a possible role of the cerebellum in cognitive processes., (© 2023. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

We sought to identify baseline (pre-treatment) neural markers associated with treatment response in major depressive disorder (MDD), specific to treatment type, Cognitive Behavioral Therapy (CBT) or pharmacotherapy (selective serotonin reuptake inhibitors; SSRI). We conducted a meta-analysis of functional magnetic resonance imaging (fMRI) studies to identify neural prognostic indicators of response to CBT or SSRI. To verify the regions derived from literature, the meta-analytic regions were used to predict clinical change in a verification sample of participants with MDD who received either CBT (n = 60) or an SSRI (n = 19) as part of prior clinical trials. The meta-analysis consisted of 21 fMRI studies that used emotion-related tasks. It yielded prognostic regions of the perigenual (meta pgACC) and subgenual anterior cingulate cortex (meta sgACC), associated with SSRI and CBT response, respectively. When applying the meta-analytic regions to predict treatment response in the verification sample, reactivity of the meta pgACC was prognostic for SSRI response, yet the effect direction was opposite of most prior studies. Meta sgACC reactivity failed to be prognostic for CBT response. Results confirm the prognostic potential of neural reactivity of ACC subregions in MDD but further research is necessary for clinical translation., (© 2023. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Although childhood maltreatment confers a high risk for the development of major depressive disorder, the neurobiological mechanisms underlying this connection remain unknown. The present study sought to identify the specific resting-state networks associated with childhood maltreatment. We recruited major depressive disorder patients with and without a history of childhood maltreatment (n = 31 and n = 30, respectively) and healthy subjects (n = 80). We used independent component analysis to compute inter- and intra- network connectivity. We found that individuals with major depressive disorder and childhood maltreatment could be characterized by the following network disconnectivity model relative to healthy subjects: (i) decreased intra-network connectivity in the left frontoparietal network and increased intra-network connectivity in the right frontoparietal network, (ii) decreased inter-network connectivity in the posterior default mode network-auditory network, posterior default mode network-limbic system, posterior default mode network-anterior default mode network, auditory network-medial visual network, lateral visual network - medial visual network, medial visual network-sensorimotor network, medial visual network - anterior default mode network, occipital pole visual network-dorsal attention network, and posterior default mode network-anterior default mode network, and (iii) increased inter-network connectivity in the sensorimotor network-ventral attention network, and dorsal attention network-ventral attention network. Moreover, we found significant correlations between the severity of childhood maltreatment and the intra-network connectivity of the frontoparietal network. Our study demonstrated that childhood maltreatment is integrally associated with aberrant network architecture in patients with major depressive disorder., (© 2022. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

The goal of this study was to determine the presence or absence of persistent functional impairments in specific brain regions in breast cancer patients during the recovery period after chemotherapy. We calculated degree centrality (DC) and explored the correlation between brain changes and cognitive scores in 29 female patients with breast cancer who had completed chemotherapy within 1-6 years (C + group) and in 28 age-matched patients with breast cancer who did not receive chemotherapy (C- group). All patients underwent rs-fMRI and cognitive testing. Differences in brain functional activity were explored using DC parameters. Correlations between brain features and cognitive scores were analyzed via correlation analysis. Compared with the C- group, the C + group obtained significantly lower motor and cognitive subscores on the Fatigue Scale for Motor and Cognitive Functions and four subscale scores of the Functional Assessment of Cancer Therapy-Cognitive Function (P < 0.05). Furthermore, the C + group exhibited a significantly higher DC z-score (zDC) in the right superior temporal gyrus and left postcentral gyrus (P < 0.01, FWE-corrected), and a lower zDC in the left caudate nucleus (P < 0.01, FWE-corrected). We found a positive correlation between digit symbol test (DST) scores and zDC values in the right superior temporal gyrus (r = 0.709, P < 0.001), and a negative correlation between DST scores and zDC values in the right angular gyrus (r = -0.784, P < 0.001) and left superior parietal gyrus (r = -0.739, P < 0.001). Chemotherapy can cause abnormal brain activity and cognitive decline in patients with breast cancer, and these effects are likely to persist. DC can be used as an imaging marker for chemotherapy-related cognitive impairment after chemotherapy in breast cancer patients., (© 2022. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Resting state low-frequency brain activity may aid in our understanding of the mechanisms of aging-related cognitive decline. Our purpose was to explore the characteristics of the amplitude of low-frequency fluctuations (ALFF) in different frequency bands of fMRI to better understand cognitive aging. Thirty-seven cognitively normal older individuals underwent a battery of neuropsychological tests and MRI scans at baseline and four years later. ALFF from five different frequency bands (typical band, slow-5, slow-4, slow-3, and slow-2) were calculated and analyzed. A two-way ANOVA was used to explore the interaction effects in voxel-wise whole brain ALFF of the time and frequency bands. Paired-sample t-test was used to explore within-group changes over four years. Partial correlation analysis was performed to assess associations between the altered ALFF and cognitive function. Significant interaction effects of time × frequency were distributed over inferior frontal gyrus, superior frontal gyrus, right rolandic operculum, left thalamus, and right putamen. Significant ALFF reductions in all five frequency bands were mainly found in the right hemisphere and the posterior cerebellum; whereas localization of the significantly increased ALFF were mainly found in the cerebellum at typical band, slow-5 and slow-4 bands, and left hemisphere and the cerebellum at slow-3, slow-2 bands. In addition, ALFF changes showed frequency-specific correlations with changes in cognition. These results suggest that changes of local brain activity in cognitively normal aging should be investigated in multiple frequency bands. The association between ALFF changes and cognitive function can potentially aid better understanding of the mechanisms underlying normal cognitive aging., (© 2022. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Attention is a basic human function underlying every other cognitive process. It is demonstrated in the functional Magnetic Resonance Imaging literature that frontoparietal networks are involved with attentive performance while default mode networks are involved with inattentive performance. Yet, it is still not clear whether similar results would be found with functional Near-Infrared Spectroscopy. The goal of our study was to investigate differences in hemodynamic activity measured by functional Near-Infrared Spectroscopy between fast and slow responses on a simple sustained attention task both before and after stimulus onset. Thirty healthy adults took part in the study. Our results have shown differences between fast and slow responses only on channels over medial frontal cortex and inferior parietal cortex (p < 0,05). These differences were observed both before and after stimulus presentation. It is discussed that functional Near-Infrared Spectroscopy is a good tool to investigate the frontoparietal network and its relationship with performance in attention tasks; it could be used to further investigate other approaches on attention, such as the dual network model of cognitive control and brain states views based on complex systems analysis; and finally, it could be used to investigate attention in naturalistic settings., (© 2021. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Functional magnetic resonance imaging (fMRI) has been used to study the influence of opioids on neural circuitry implicated in opioid use disorder, such as the cortico-striatal-thalamo-cortical (CSTC) circuit. Given the increase in fentanyl-related deaths, this study was conducted to characterize the effects of fentanyl on patterns of brain activation in awake nonhuman primates. Four squirrel monkeys were acclimated to awake scanning procedures conducted at 9.4 Tesla. Subsequently, test sessions were conducted in which a dose of fentanyl that reliably maintains intravenous (IV) self-administration behavior in monkeys, 1 μg/kg, was administered and the effects on patterns of brain activity were assessed using: (1) a pharmacological regressor to elucidate fentanyl-induced patterns of neural activity, and (2) seed-based approaches targeting bilateral anterior cingulate, thalamus, or nucleus accumbens (NAc) to determine alterations in CSTC functional connectivity. Results showed a functional inhibition of BOLD signal in brain regions that mediate behavioral effects of opioid agonists, such as cingulate cortex, striatum and midbrain. Functional connectivity between each of the seed regions and areas involved in motoric, sensory and cognition-related behavior generally decreased. In contrast, NAc functional connectivity with other striatal regions increased. These results indicate that fentanyl produces changes within CSTC circuitry that may reflect key features of opioid use disorder (e.g. persistent drug-taking/seeking) and thereby contribute to long-term disruptions in behavior and addiction. They also indicate that fMRI in alert nonhuman primates can detect drug-induced changes in neural circuits and, in turn, may be useful for investigating the effectiveness of medications to reverse drug-induced dysregulation., (© 2022. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Electroconvulsive therapy (ECT), a rapidly acting and effective treatment for major depressive disorder (MDD), is frequently accompanied by cognitive impairment. Recent studies have documented that ECT reorganizes dysregulated inter/intra- connected cerebral networks, including the affective network, the cognitive control network(CCN) and default mode network (DMN).Moreover, cerebellum is thought to play an important role in emotion regulation and cognitive processing. However, little is known about the relationship between cerebro-cerebellar connectivity alterations following ECT and antidepressant effects or cognitive impairment. We performed seed-based resting-state functional connectivity (RSFC) analyses in 28 MDD patients receiving ECT and 20 healthy controls to identify cerebro-cerebellar connectivity differences related to MDD and changes induced by ECT. Six seed regions (three per hemisphere) in the cerebrum were selected for RSFC, corresponding to the affective network, CCN and DMN, to establish cerebro-cerebellar functional connectivity with cerebellum. MDD patients showed increased RSFC between left sgACC and left cerebellar lobule VI after ECT. Ggranger causality analyses (GCA) identified the causal interaction is from left cerebellar lobule VI to left sgACC. Furthermore, increased effective connectivity from left cerebellar lobule VI to left sgACC exhibited positively correlated with the change in verbal fluency test (VFT) score following ECT (r = 0.433, p = 0.039). Our findings indicate that the enhanced cerebro-cerebellar functional connectivity from left lobule VI to left sgACC may ameliorate cognitive impairment induced by ECT. This study identifies a potential neural pathway for mitigation of cognitive impairment following ECT.

Machine learning methods have been widely used for early diagnosis of Alzheimer's disease (AD) via functional connectivity networks (FCNs) analysis from neuroimaging data. The conventional low-order FCNs are obtained by time-series correlation of the whole brain based on resting-state functional magnetic resonance imaging (R-fMRI). However, FCNs overlook inter-region interactions, which limits application to brain disease diagnosis. To overcome this drawback, we develop a novel framework to exploit the high-level dynamic interactions among brain regions for early AD diagnosis. Specifically, a sliding window approach is employed to generate some R-fMRI sub-series. The correlations among these sub-series are then used to construct a series of dynamic FCNs. High-order FCNs based on the topographical similarity between each pair of the dynamic FCNs are then constructed. Afterward, a local weight clustering method is used to extract effective features of the network, and the least absolute shrinkage and selection operation method is chosen for feature selection. A support vector machine is employed for classification, and the dynamic high-order network approach is evaluated on the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset. Our experimental results demonstrate that the proposed approach not only achieves promising results for AD classification, but also successfully recognizes disease-related biomarkers.