Structural covariance of the neostriatum with regional gray matter volumes

Neural basis underlying the association between thought control ability and happiness: The moderating role of the amygdala

Thought control ability (TCA) plays an important role in individuals' health and happiness. Previous studies demonstrated that TCA was closely conceptually associated with happiness. However, empirical research supporting this relationship was limited. In addition, the neural basis underlying TCA and how this neural basis influences the relationship between TCA and happiness remain unexplored. In the present study, the voxel-based morphometry (VBM) method was adopted to investigate the neuroanatomical basis of TCA in 314 healthy subjects. The behavioral results revealed a significant positive association between TCA and happiness. On the neural level, there was a significant negative correlation between TCA and the gray matter density (GMD) of the bilateral amygdala. Split-half validation analysis revealed similar results, further confirming the stability of the VBM analysis findings. Furthermore, gray matter covariance network and graph theoretical analyses showed positive association between TCA and both the node degree and node strength of the amygdala. Moderation analysis revealed that the GMD of the amygdala moderated the relationship between TCA and happiness. Specifically, the positive association between TCA and self-perceived happiness was stronger in subjects with a lower GMD of the amygdala. The present study indicated the neural basis underlying the association between TCA and happiness and offered a method of improving individual well-being.

Structural covariance predictors of clinical improvement at 2-year follow-up in first-episode psychosis

The relationship between structural brain alterations and prediction of clinical improvement in first-episode psychosis (FEP) has been scarcely studied. We investigated whether structural covariance, a well-established approach to identify abnormal patterns of volumetric correlation across distant brain regions, which allows incorporating network-level information to structural assessments, is associated with longitudinal clinical course. We assessed a sample of 74 individuals from a multicenter study. Magnetic resonance imaging scans were acquired at baseline, and clinical assessments at baseline and at a 2-year follow-up. Participants were split in two groups as a function of their clinical improvement after 2 years (i.e., ≥ < 40% reduction in psychotic symptom severity, (n = 29, n = 45)). We performed a seed-based approach and focused our analyses on 3 cortical and 4 subcortical regions of interest to identify alterations in cortical and cortico-subcortical networks. Improvers presented an increased correlation between the volumes of the right posterior cingulate cortex (PCC) and the left precentral gyrus, and between the left PCC and the left middle occipital gyrus. They also showed an increased correlation between right posterior hippocampus and left angular gyrus volumes. Our study provides a novel mean to identify structural correlates of clinical improvement in FEP, describing clinically-relevant anatomical differences in terms of large-scale brain networks, which is better aligned with prevailing neurobiological models of psychosis. The results involve brain regions considered to participate in the multisensory processing of bodily signals and the construction of bodily self-consciousness, which resonates with recent theoretical accounts in psychosis research.

Obesity status and obesity-associated gut dysbiosis effects on hypothalamic structural covariance

BACKGROUND

Functional connectivity alterations in the lateral and medial hypothalamic networks have been associated with the development and maintenance of obesity, but the possible impact on the structural properties of these networks remains largely unexplored. Also, obesity-related gut dysbiosis may delineate specific hypothalamic alterations within obese conditions. We aim to assess the effects of obesity, and obesity and gut-dysbiosis on the structural covariance differences in hypothalamic networks, executive functioning, and depressive symptoms.

METHODS

Medial (MH) and lateral (LH) hypothalamic structural covariance alterations were identified in 57 subjects with obesity compared to 47 subjects without obesity. Gut dysbiosis in the subjects with obesity was defined by the presence of high (n = 28) and low (n = 29) values in a BMI-associated microbial signature, and posthoc comparisons between these groups were used as a proxy to explore the role of obesity-related gut dysbiosis on the hypothalamic measurements, executive function, and depressive symptoms.

RESULTS

Structural covariance alterations between the MH and the striatum, lateral prefrontal, cingulate, insula, and temporal cortices are congruent with previously functional connectivity disruptions in obesity conditions. MH structural covariance decreases encompassed postcentral parietal cortices in the subjects with obesity and gut-dysbiosis, but increases with subcortical nuclei involved in the coding food-related hedonic information in the subjects with obesity without gut-dysbiosis. Alterations for the structural covariance of the LH in the subjects with obesity and gut-dysbiosis encompassed increases with frontolimbic networks, but decreases with the lateral orbitofrontal cortex in the subjects with obesity without gut-dysbiosis. Subjects with obesity and gut dysbiosis showed higher executive dysfunction and depressive symptoms.

CONCLUSIONS

Obesity-related gut dysbiosis is linked to specific structural covariance alterations in hypothalamic networks relevant to the integration of somatic-visceral information, and emotion regulation.

Hidden brain iron content in sickle cell disease: impact on neurocognitive functions

Children with sickle cell disease (SCD) are at a high risk for neurocognitive impairment. We aim to quantitatively measure cerebral tissue R2* to investigate the brain iron deposition in children and young adults with SCD in comparison to beta thalassemia major (BTM) and healthy controls and evaluate its impact on neurocognitive functions in patients with SCD. Thirty-two SCD, fifteen BTM, and eleven controls were recruited. Multi-echo fast-gradient echo sequence brain MRI was performed, and brain R2* values of both caudate and thalamic regions were calculated. SCD patients were examined for the neurocognitive functions. SCD had high iron overload 0.30 ± 0.12 mg/kg/day. 68.9% of SCD had under-threshold IQ, 12.5% had moderate to severe anxiety, and 60.8% had depression. There were no differences between SCD, BTM, and controls in brain MRI except that left thalamus R2* higher in BTM than both SCD and controls (p = 0.032). Mean right caudate R2* was higher in female than male (p = 0.044). No significant association between brain R2* and LIC or heart R2* values in SCD. Left caudate R2* directly correlate with age and HbS%, and negatively correlate with HbA% while right thalamus R2* negatively correlate with transfusion index and among SCD patients.Conclusion: Neurocognitive dysfunction in SCD could not be explained solely by brain iron overload. What is Known: • Children with sickle cell disease are at great risk of brain damage due to their irregularly shaped red blood cells that can interrupt blood flow to the brain. • There are a number of factors that have negative brain effects that result in learning difficulties, and this not only due to increase brain iron content. What is New: • Assessment of quantitative brain iron content using MRI R2* in children and young adults with SCD in comparison to beta thalassemia major and healthy controls. • Impact of brain iron content on neurocognitive functions of children and young adults with SCD.

Magnetic Resonance Imaging-Based Structural Covariance Changes of the Striatum in Lifelong Premature Ejaculation Patients

BACKGROUND

The striatum has been reported to be implicated in various neurological diseases, including lifelong premature ejaculation (LPE). Altered striatum-related functional connectivity was investigated in LPE patients in previous studies; however, structural abnormalities in the striatum have been less studied in LPE.

PURPOSE

To identify the gray matter volume (GMV) and structural covariance patterns of the striatum between LPE patients and healthy controls (HCs).

STUDY TYPE

Prospective.

SUBJECTS

Forty-three LPE patients and 31 male HCs.

FIELD STRENGTH/SEQUENCE

3.0 T magnetic resonance imaging (MRI) scanner; T1-weighted imaging using a spoiled gradient recalled echo sequence.

ASSESSMENT

Preprocessing of structural MRI data and the striatum-seeded GMV computation were conducted using SPM12.

STATISTICAL TESTS

Two sample t-test was used to compare differences in GMV of the striatum between patients and HCs. Regions showing altered between-group GMV were considered as seeds for structural covariance analysis in two groups. Additionally, correlations between GMV findings and clinical features were assessed with age and total intracranial volume (TIV) as covariates and with age, TIV, anxiety, and depression scores as covariates in the patient group, P < 0.05 was considered statistically significant.

RESULTS

Compared to HCs, LPE patients had significantly decreased GMV in four regions located in the bilateral caudate and putamen. Distinct striatum-based structural covariance patterns in the two groups were mainly related to the thalamus, amygdala, insula, anterior cingulate cortex, middle cingulate cortex, medial prefrontal cortex, primary motor cortex, and precuneus/cuneus. LPE patients showed that GMV in the bilateral caudate negatively correlated with the premature ejaculation diagnostic tool (PEDT) scores (r = -0.369, r = -0.377, respectively).

DATA CONCLUSION

Our findings indicated that LPE patients had altered GMV and structural covariance patterns in the striatum compared to HCs. The correlations between abnormal GMV and PEDT were also shown in the present findings. These findings may contribute to enhancing the understanding of the pathophysiology of LPE.

LEVEL OF EVIDENCE

1 TECHNICAL EFFICACY: Stage 3.

Regional brain volume predicts response to methylphenidate treatment in individuals with ADHD

BACKGROUND

Despite the effectiveness of methylphenidate for treating ADHD, up to 30% of individuals with ADHD show poor responses to methylphenidate. Neuroimaging biomarkers to predict medication responses remain elusive. This study characterized neuroanatomical features that differentiated between clinically good and poor methylphenidate responders with ADHD.

METHODS

Using a naturalistic observation design selected from a larger cohort, we included 79 drug-naive individuals (aged 6-42 years) with ADHD without major psychiatric comorbidity, who had acceptable baseline structural MRI data quality. Based on a retrospective chart review, we defined responders by individuals' responses to at least one-month treatment with methylphenidate. A nonparametric mass-univariate voxel-based morphometric analysis was used to compare regional gray matter volume differences between good and poor responders. A multivariate pattern recognition based on the support vector machine was further implemented to identify neuroanatomical indicators to predict an individual's response.

RESULTS

63 and 16 individuals were classified in the good and poor responder group, respectively. Using the small-volume correction procedure based on the hypothesis-driven striatal and default-mode network masks, poor responders had smaller regional volumes of the left putamen as well as larger precuneus volumes compared to good responders at baseline. The machine learning approach identified that volumetric information among these two regions alongside the left frontoparietal regions, occipital lobes, and posterior/inferior cerebellum could predict clinical responses to methylphenidate in individuals with ADHD.

CONCLUSION

Our results suggest regional striatal and precuneus gray matter volumes play a critical role in mediating treatment responses in individuals with ADHD.

Disturbed neurovascular coupling in hemodialysis patients

Background

Altered cerebral blood flow (CBF) and amplitude of low-frequency fluctuation (ALFF) have been reported in hemodialysis patients. However, neurovascular coupling impairments, which provide a novel insight into the human brain, have not been reported in hemodialysis patients.

Methods

We combined arterial spin labeling (ASL) and blood oxygen level dependent (BOLD) techniques to investigate neurovascular coupling alterations and its relationships with demographic and clinical data in 46 hemodialysis patients and 47 healthy controls. To explore regional neuronal activity, ALFF was obtained from resting-state functional MRI. To measure cerebral vascular response, CBF was calculated from ASL. The across-voxel CBF-ALFF correlations for global neurovascular coupling and CBF/ALFF ratio for regional neurovascular coupling were compared between hemodialysis patients and healthy controls. Two-sample t-tests were used to compare the intergroup differences in CBF and ALFF. Multiple comparisons were corrected using a voxel-wise false discovery rate (FDR) method (P < 0.05).

Results

All hemodialysis patients and healthy controls showed significant across-voxel correlations between CBF and ALFF. Hemodialysis patients showed a significantly reduced global CBF-ALFF coupling (P = 0.0011) compared to healthy controls at the voxel-level. Of note, decreased CBF/ALFF ratio was exclusively located in the bilateral amygdala involved in emotional regulation and cognitive processing in hemodialysis patients. In hemodialysis patients, the decreased CBF (right olfactory cortex, anterior cingulate gyrus and bilateral insula) and ALFF (bilateral precuneus and superior frontal gyrus) were mainly located in the default mode network and salience network-related regions as well as increased CBF in the bilateral thalamus.

Conclusions

These novel findings reveal that disrupted neurovascular coupling may be a potential neural mechanism in hemodialysis patients.

Brain structural covariance networks in obsessive-compulsive disorder: a graph analysis from the ENIGMA Consortium

Brain structural covariance networks reflect covariation in morphology of different brain areas and are thought to reflect common trajectories in brain development and maturation. Large-scale investigation of structural covariance networks in obsessive-compulsive disorder (OCD) may provide clues to the pathophysiology of this neurodevelopmental disorder. Using T1-weighted MRI scans acquired from 1616 individuals with OCD and 1463 healthy controls across 37 datasets participating in the ENIGMA-OCD Working Group, we calculated intra-individual brain structural covariance networks (using the bilaterally-averaged values of 33 cortical surface areas, 33 cortical thickness values, and six subcortical volumes), in which edge weights were proportional to the similarity between two brain morphological features in terms of deviation from healthy controls (i.e. z-score transformed). Global networks were characterized using measures of network segregation (clustering and modularity), network integration (global efficiency), and their balance (small-worldness), and their community membership was assessed. Hub profiling of regional networks was undertaken using measures of betweenness, closeness, and eigenvector centrality. Individually calculated network measures were integrated across the 37 datasets using a meta-analytical approach. These network measures were summated across the network density range of K = 0.10-0.25 per participant, and were integrated across the 37 datasets using a meta-analytical approach. Compared with healthy controls, at a global level, the structural covariance networks of OCD showed lower clustering (P < 0.0001), lower modularity (P < 0.0001), and lower small-worldness (P = 0.017). Detection of community membership emphasized lower network segregation in OCD compared to healthy controls. At the regional level, there were lower (rank-transformed) centrality values in OCD for volume of caudate nucleus and thalamus, and surface area of paracentral cortex, indicative of altered distribution of brain hubs. Centrality of cingulate and orbito-frontal as well as other brain areas was associated with OCD illness duration, suggesting greater involvement of these brain areas with illness chronicity. In summary, the findings of this study, the largest brain structural covariance study of OCD to date, point to a less segregated organization of structural covariance networks in OCD, and reorganization of brain hubs. The segregation findings suggest a possible signature of altered brain morphometry in OCD, while the hub findings point to OCD-related alterations in trajectories of brain development and maturation, particularly in cingulate and orbitofrontal regions.

Smaller subcortical volume in Parkinson patients with rapid eye movement sleep behavior disorder

Parkinson disease (PD) patients with rapid eye movement (REM) sleep behavior disorder (RBD) have worse motor symptoms and non-motor symptoms than patients without RBD. The aim of this study was to examine underlying differences in brain structure from a network perspective. Baseline data were obtained from Parkinson's Progression Markers Initiative (PPMI) participants. We divided PD patients and healthy controls (HC) into RBD positive and RBD negative using a cutoff score of ≥5 on the RBD screening questionnaire. HC with probable RBD were excluded. We first carried out a region-of-interest analysis of structural MRIs using voxel-based morphometry to study volumetric differences for the putamen, thalamus and hippocampus in a cross-sectional design. Additionally, an exploratory whole-brain analysis was performed. To study group differences from a network perspective, we then performed a 'seed-based' analysis of structural covariance, using the bilateral dorsal-caudal putamen, mediodorsal thalamus and anterior hippocampus as seed regions. The volume of the right putamen was smaller in PD patients with RBD. RBD symptom severity correlated negatively with volume of the right putamen, left hippocampus and left thalamus. We did not find any differences in structural covariance between PD patients with and without RBD. Presence of RBD and severity of RBD symptoms in PD are associated with smaller volumes of the putamen, thalamus and hippocampus.

Anxiety in Parkinson's disease is associated with reduced structural covariance of the striatum

BACKGROUND

Anxiety is highly prevalent in Parkinson's disease (PD) and has great negative impact on quality of life. Functional and structural neuroimaging studies have contributed to our understanding of the symptomatology of PD but still little is known about the pathophysiology of PD-related anxiety.

METHODS

We used seed-based structural covariance analysis to study the anatomical network correlates of anxiety in PD. Structural covariance analysis is based on the statistical correlation between regional brain volumes measured on T1-weighted magnetic resonance images. We investigated the association between anxiety symptoms, as measured by the Beck Anxiety Inventory (BAI), and seed-to-whole-brain structural covariance networks in 115 patients with idiopathic PD using five bilateral seeds: basolateral amygdala, centromedial-superficial amygdala, dorsal caudate nucleus, dorsal-caudal putamen, and nucleus accumbens.

RESULTS

Severity of anxiety correlated negatively with structural covariance between the left striatal sub-regions and the contralateral caudate nucleus. Moreover, severity of anxiety was associated with reduced structural covariance between the right dorsal caudate nucleus and ipsilateral ventrolateral prefrontal cortex and between the left nucleus accumbens and ipsilateral dorsolateral prefrontal cortex. Structural covariance of the amygdalar seeds did not correlate with anxiety.

CONCLUSIONS

We interpret these findings as a reduced interhemispheric cooperation between the left and right striatum and reduced prefrontal-striatal connectivity, possibly related to impaired 'top-down' regulation of emotions. These findings shed more light on the pathophysiology of PD-related anxiety LIMITATIONS: This study did not include PD patients with an anxiety disorder.

Altered amygdala-related structural covariance and resting-state functional connectivity in end-stage renal disease patients

Depression and cognitive control deficits were frequently reported in concurrent end-stage renal disease (ESRD) patients. Neuroimaging studies indicated depression could be a risk factor for cognitive control deficits, and amygdala-related circuitry may play a critical role in this abnormal interaction. To investigate the potential relationship between depressive symptoms and cognitive control reduction in ESRD patients, T1-weighted and resting fMRI images were obtained in 29 ESRD patients and 29 healthy controls. Voxel-based morphometry (VBM), structural covariance (SC) analysis based on grey matter volume (GMV), and functional connectivity (FC) analysis were adopted. All subjects performed the Beck Depression Inventory (BDI) assessment and Stroop test. The patients also underwent blood biochemistry tests (urea, creatinine, phosphate, Ca2⁺, hematocrit, cystatin, hemoglobin). Compared with controls, GMV reductions were found mainly in the anterior cingulate cortex (ACC) and bilateral amygdala, and decreased SC was found between the amygdala and ACC in ESRD patients. This indicated that structural changes in the amygdala may be related to the GMV alterations in the ACC. Additionally, decreased FC between the amygdala and ACC was revealed in ESRD patients. Negative correlation was found between the FC of the amygdala-ACC and reaction delay during the Stroop test, but this correlation disappeared after controlling BDI. Stepwise regression analysis showed that the low level of hemoglobin was contributed to the reduced FC of the amygdala-ACC in ESRD patients. Our results demonstrated the abnormal interaction between depressive mood and cognitive control deficits in ESRD patients.

Altered brain structure in women with premenstrual syndrome

BACKGROUND

Functional brain abnormalities have been noted in premenstrual syndrome (PMS). However, the brain structural alterations related to PMS remain unclear. This study aimed to identify possible abnormalities in gray matter (GM) volumes and structural covariance patterns among PMS patients.

METHODS

Structural magnetic resonance imaging data were obtained from 20 PMS patients and 20 healthy controls. Voxel-based morphometry (VBM) analysis was applied to examine GM volumes changes between the two groups. Receiver operating characteristic (ROC) curve was used to investigate the most reliable biomarker for distinguishing PMS patients from health controls based on the intergroup differences. Correlation analysis was then performed to assess relationships between the daily rating of severity of problems (DRSP) and abnormal brain regions. Finally, the regions identified from VBM analysis were served as seeds to characterize the whole-brain structural covariance patterns.

RESULTS

Compared with healthy controls, PMS patients showed increased GM volumes in the precuneus/posterior cingulate cortex (precuneus/PCC) and thalamus, and decreased GM volumes in the insula. The precuneus/PCC exhibited the highest classification power by ROC analysis and positively correlated with the DRSP. Moreover, different patterns of structural covariance in the two groups were mainly located in the dorsolateral prefrontal cortex, anterior cingulate cortex, angular gyrus and hippocampus.

LIMITATIONS

This study is limited by a small sample and narrow age range of participants.

CONCLUSIONS

Our findings may provide preliminary evidence for brain morphology alterations in PMS patients and contribute to a better understanding of the pathophysiology of PMS.

How neuroscience can inform the study of individual differences in cognitive abilities

Theories of human mental abilities should be consistent with what is known in neuroscience. Currently, tests of human mental abilities are modeled by cognitive constructs such as attention, working memory, and speed of information processing. These constructs are in turn related to a single general ability. However, brains are very complex systems and whether most of the variability between the operations of different brains can be ascribed to a single factor is questionable. Research in neuroscience suggests that psychological processes such as perception, attention, decision, and executive control are emergent properties of interacting distributed networks. The modules that make up these networks use similar computational processes that involve multiple forms of neural plasticity, each having different time constants. Accordingly, these networks might best be characterized in terms of the information they process rather than in terms of abstract psychological processes such as working memory and executive control.

Metabolic Covariant Network in Relation to Nigrostriatal Degeneration in Carbon Monoxide Intoxication-Related Parkinsonism

Presence of parkinsonian features after carbon monoxide (CO) intoxication is well known and the severity was found to relate to the pre-synaptic dopaminergic deficits. There is no systemic study to analyse the functional network involved in CO-related Parkinsonism. Forty-five CO-related parkinsonism patients and 25 aged-matched controls completed the 3D T1-weighted imaging and (18)F-fluoro-2-deoxyglucose positron emission tomography (FDG-PET). Voxel-based morphometry (VBM) was performed to assess the structural and functional brain differences between the patients and controls. Spatial covariant networks responsible for distinguishing patients and controls were constructed using independent component analysis. For validation, the pre-synaptic dopaminergic functional network was established by regression model using striatal TRODAT-1 SPECT as the independent variable. The clinical significance of both networks was determined by correlation with the Unified Parkinson's Disease Rating Scale (UPDRS). Compared with controls, the spatial covariant signals of FDG-PET were significantly lower in the medial and lateral frontal, caudate nucleus, dorsomedial prefrontal areas, and temporal-parietal regions while the spatial intensities correlated significantly with UPDRS total scores. The functional network that correlated with striatum pre-synaptic dopaminergic uptakes included the midbrain, thalamus, caudate, lateral frontal cortex, ventral striatum, ventral, or dorsal anterior cingulate cortex. Both networks overlapped considerably and the topographies reflected structural damage pattern. Our study provides evidence that glucose metabolism in CO-parkinsonism patients pertains to an organized covariant pattern in the cortical regions that is spatially coherent with the cortical map of pre-synaptic dopamine deficits. As the fronto-temporal, striatum, and temporal-parietal areas were involved, the unique metabolic covariant network suggests a different pathophysiology in CO-related parkinsonism.

Structural covariance of neostriatal and limbic regions in patients with obsessive-compulsive disorder

BACKGROUND

Frontostriatal and frontoamygdalar connectivity alterations in patients with obsessive-compulsive disorder (OCD) have been typically described in functional neuroimaging studies. However, structural covariance, or volumetric correlations across distant brain regions, also provides network-level information. Altered structural covariance has been described in patients with different psychiatric disorders, including OCD, but to our knowledge, alterations within frontostriatal and frontoamygdalar circuits have not been explored.

METHODS

We performed a mega-analysis pooling structural MRI scans from the Obsessive-compulsive Brain Imaging Consortium and assessed whole-brain voxel-wise structural covariance of 4 striatal regions (dorsal and ventral caudate nucleus, and dorsal-caudal and ventral-rostral putamen) and 2 amygdalar nuclei (basolateral and centromedial-superficial). Images were preprocessed with the standard pipeline of voxel-based morphometry studies using Statistical Parametric Mapping software.

RESULTS

Our analyses involved 329 patients with OCD and 316 healthy controls. Patients showed increased structural covariance between the left ventral-rostral putamen and the left inferior frontal gyrus/frontal operculum region. This finding had a significant interaction with age; the association held only in the subgroup of older participants. Patients with OCD also showed increased structural covariance between the right centromedial-superficial amygdala and the ventromedial prefrontal cortex.

LIMITATIONS

This was a cross-sectional study. Because this is a multisite data set analysis, participant recruitment and image acquisition were performed in different centres. Most patients were taking medication, and treatment protocols differed across centres.

CONCLUSION

Our results provide evidence for structural network-level alterations in patients with OCD involving 2 frontosubcortical circuits of relevance for the disorder and indicate that structural covariance contributes to fully characterizing brain alterations in patients with psychiatric disorders.

Large-scale brain network abnormalities in Huntington's disease revealed by structural covariance

Huntington's disease (HD) is a progressive neurodegenerative disorder that can be diagnosed with certainty decades before symptom onset. Studies using structural MRI have identified grey matter (GM) loss predominantly in the striatum, but also involving various cortical areas. So far, voxel-based morphometric studies have examined each brain region in isolation and are thus unable to assess the changes in the interrelation of brain regions. Here, we examined the structural covariance in GM volumes in pre-specified motor, working memory, cognitive flexibility, and social-affective networks in 99 patients with manifest HD (mHD), 106 presymptomatic gene mutation carriers (pre-HD), and 108 healthy controls (HC). After correction for global differences in brain volume, we found that increased GM volume in one region was associated with increased GM volume in another. When statistically comparing the groups, no differences between HC and pre-HD were observed, but increased positive correlations were evident for mHD, relative to pre-HD and HC. These findings could be explained by a HD-related neuronal loss heterogeneously affecting the examined network at the pre-HD stage, which starts to dominate structural covariance globally at the manifest stage. Follow-up analyses identified structural connections between frontoparietal motor regions to be linearly modified by disease burden score (DBS). Moderator effects of disease load burden became significant at a DBS level typically associated with the onset of unequivocal HD motor signs. Together with existing findings from functional connectivity analyses, our data indicates a critical role of these frontoparietal regions for the onset of HD motor signs.

Discrete alterations of brain network structural covariance in individuals at ultra-high risk for psychosis

BACKGROUND

Investigation of aberrant large-scale brain networks offers novel insight into the role these networks play in diverse psychiatric disorders such as schizophrenia. Although studies report altered functional brain connectivity in participants at ultra-high risk (UHR) for psychosis, it is unclear whether these alterations extend to structural brain networks.

METHODS

Whole-brain structural covariance patterns of 133 participants at UHR for psychosis (51 of whom subsequently developed psychosis) and 65 healthy control (HC) subjects were studied. Following data preprocessing (using VBM8 toolbox), the mean signal in seed regions relating to specific networks (visual, auditory, motor, speech, semantic, executive control, salience, and default-mode) were extracted, and voxel-wise analyses of covariance were conducted to compare the association between whole-brain signal and each seed region for UHR and HC individuals. The UHR participants who transitioned to psychosis were compared with the UHR participants who did not.

RESULTS

Significantly reduced structural covariance was observed in the UHR sample compared with the HC sample for the default-mode network, and increased covariance was observed for the motor and executive control networks. When the UHR participants who transitioned to psychosis were compared with the UHR participants who did not, aberrant structural covariance was observed in the salience, executive control, auditory, and motor networks.

CONCLUSIONS

Whole-brain structural covariance analyses revealed subtle changes of connectivity of the default-mode, executive control, salience, motor, and auditory networks in UHR individuals for psychosis. Although we found significant differences, these are small changes and tend to reflect largely intact structural networks.

Abnormalities of structural covariance networks in drug-naïve boys with attention deficit hyperactivity disorder

The aim of this study is to investigate whether the anatomical organization of large-scale brain systems would change in ADHD patients compared to healthy controls. We utilized a structural covariance network (SCN) mapping approach to investigate large-scale networks in 30 drug-naïve ADHD boys and 30 gender- and age-matched controls. The regions showing significant between-group differences in gray matter (GM) volume were defined as seed regions of interest. Then, the SCNs derived from these seeds were statistically compared between ADHD and controls. Significant regional GM volume decreases (P<0.05, corrected) were observed in the right insula and the right orbito-frontal cortex (OFC) in ADHD relative to controls. Both SCNs derived from these two seeds showed more localized topology in ADHD group. Furthermore, significantly decreased structural connectivity were found between insula and right hippocampus, bilateral olfactory cortex, and between OFC and bilateral caudate nucleus (P<0.05, corrected) in ADHD group. Significantly increased association was observed between insula and left middle temporal gyrus (P<0.05, corrected) in ADHD group. Taken together, our results reveal abnormal regional brain anatomy as well as aberrant structural covariance networks in ADHD, supporting previous findings of dysfunction in distributed network organization in patients with ADHD.

¹⁸F-FP-(+)-DTBZ positron emission tomography detection of monoaminergic deficient network in patients with carbon monoxide related parkinsonism

BACKGROUND AND PURPOSE

Although parkinsonism after carbon monoxide (CO) intoxication is well known, neurotransmitter deficient networks that are responsible for the severity of parkinsonism have rarely been systemically evaluated.

METHODS

Eighteen patients with CO-related parkinsonism and nine age- and sex-matched controls were enrolled for detailed neurological examinations, three-dimensional T1-weighted images, diffusion tensor imaging and (18)F-9-fluoropropyl-(+)-dihydrotetrabenzazine ((18)F-FP-(+)-DTBZ) positron emission tomography (PET). The structural analysis included voxel-based morphometry to assess grey matter atrophy and tract-based spatial statistics related to white matter involvement. For presynaptic monoaminergic assessment, volume of interest analysis in six subcortical regions and non-parametric voxel-wise comparison were performed on PET images with estimation of registration parameters from magnetic resonance images. All the imaging modalities were compared between the patients and controls. For the patients, a regression model for correlation with cognitive behaviour and Unified Parkinson's Disease Rating Scale (UPDRS) score was used.

RESULTS

In the patients, monoaminergic deficit networks were found in the caudate, anterior putamen, anterior insular, thalamus and anterior cingulate cortex. The UPDRS revealed significant correlations with the prefrontal white matter fractional anisotropy values and with the (18)F-FP-(+)-DTBZ uptake values in the caudate nucleus, insular, medial prefrontal and dorsomedial thalamus. The neuropsychiatric inventory score correlated with the (18)F-FP-(+)-DTBZ uptake values in the anterior cingulate cortex and dorsolateral prefrontal cortex.

CONCLUSIONS

Our study demonstrated monoaminergic deficits and white matter damage networks in CO-related parkinsonism that determined the severity of parkinsonism or behaviour changes. As the substantia nigra was spared, the monoaminergic topography of involvement suggests a different pathophysiology in CO-related parkinsonism.

Structural covariance networks of striatum subdivision in patients with Parkinson's disease

Parkinson's disease (PD) is a neurodegenerative disorder associated with the striatum. Previous studies indicated that subdivisions of the striatum with distinct functional connectivity profiles contribute to different pathogeneses in PD. Segregated structural covariance (SC) pattern between the striatum and neocortex observed in healthy subjects, however, remain unknown in PD. The purpose of this study is to map and compare the subregional striatal SC network organization between 30 healthy controls and 48 PD patients and to investigate their association with the disease severity. The striatal SC network was statistically inferred by correlating the mean gray matter (GM) volume of six striatal subdivisions (including the bilateral dorsal caudate, superior ventral striatum, inferior ventral striatum, dorsal caudal putamen, dorsal rostral putamen, and ventral rostral putamen) with the entire neocortical GM volume in voxel-wise manner. The PD patients revealed marked atrophy in the striatum, cerebellum, and extra-striatum neocortices. As predicted, segregated striatal SC network patterns were observed in both groups. This suggests that in PD, pathological processes occurring in the striatum affect the same striato-cortical networks that covary with the striatum in healthy brains. The PD patients further demonstrated atypical striatal SC patterns between the caudate, parahippocampus temporal cortices, and cerebellum, which corresponded to dopaminergic associated network. The areas with significant group differences in SC were further associated with disease severity. Our findings support previous studies indicating that PD is associated with altered striato-cortical networks, and suggest that structural changes in the striatum may result in a cascade of alterations in multiple neocortices.

A selective involvement of putamen functional connectivity in youth with internet gaming disorder

Brain cortico-striatal circuits have consistently been implicated in the pathology of addiction related disorders. We applied a reliable seed-based analysis of the resting-state brain activity to comprehensively delineate the subdivisions of striatal functional connectivity implicated in internet gaming disorder. Among twelve right-handed male adolescents with internet gaming disorder and 11 right-handed and gender-matched healthy controls, we examined group differences in the functional connectivity of dorsal and ventral subdivisions of the caudate nucleus and putamen, as well as the association of these connectivity indices with behavioral measures of internet use. Adolescents with internet gaming disorder showed significantly reduced dorsal putamen functional connectivity with the posterior insula-parietal operculum. More time spent playing online games predicted significantly greater functional connectivity between the dorsal putamen and bilateral primary somatosensory cortices in adolescents with internet gaming disorder, and significantly lower functional connectivity between the dorsal putamen and bilateral sensorimotor cortices in healthy controls. The dorsal putamen functional connectivity was significantly and specifically different in adolescents with internet gaming disorder. The findings suggest a possible biomarker of internet gaming disorder.

Associations between age and gray matter volume in anatomical brain networks in middle-aged to older adults

Aging is associated with cognitive decline, diminished brain function, regional brain atrophy, and disrupted structural and functional brain connectivity. Understanding brain networks in aging is essential, as brain function depends on large-scale distributed networks. Little is known of structural covariance networks to study inter-regional gray matter anatomical associations in aging. Here, we investigate anatomical brain networks based on structural covariance of gray matter volume among 370 middle-aged to older adults of 45-85 years. For each of 370 subjects, we acquired a T1-weighted anatomical MRI scan. After segmentation of structural MRI scans, nine anatomical networks were defined based on structural covariance of gray matter volume among subjects. We analyzed associations between age and gray matter volume in anatomical networks using linear regression analyses. Age was negatively associated with gray matter volume in four anatomical networks (P < 0.001, corrected): a subcortical network, sensorimotor network, posterior cingulate network, and an anterior cingulate network. Age was not significantly associated with gray matter volume in five networks: temporal network, auditory network, and three cerebellar networks. These results were independent of gender and white matter hyperintensities. Gray matter volume decreases with age in networks containing subcortical structures, sensorimotor structures, posterior, and anterior cingulate cortices. Gray matter volume in temporal, auditory, and cerebellar networks remains relatively unaffected with advancing age.

Characterizing structural association alterations within brain networks in normal aging using Gaussian Bayesian networks

Recent multivariate neuroimaging studies have revealed aging-related alterations in brain structural networks. However, the sensory/motor networks such as the auditory, visual and motor networks, have obtained much less attention in normal aging research. In this study, we used Gaussian Bayesian networks (BN), an approach investigating possible inter-regional directed relationship, to characterize aging effects on structural associations between core brain regions within each of these structural sensory/motor networks using volumetric MRI data. We then further examined the discriminability of BN models for the young (N = 109; mean age =22.73 years, range 20-28) and old (N = 82; mean age =74.37 years, range 60-90) groups. The results of the BN modeling demonstrated that structural associations exist between two homotopic brain regions from the left and right hemispheres in each of the three networks. In particular, compared with the young group, the old group had significant connection reductions in each of the three networks and lesser connection numbers in the visual network. Moreover, it was found that the aging-related BN models could distinguish the young and old individuals with 90.05, 73.82, and 88.48% accuracy for the auditory, visual, and motor networks, respectively. Our findings suggest that BN models can be used to investigate the normal aging process with reliable statistical power. Moreover, these differences in structural inter-regional interactions may help elucidate the neuronal mechanism of anatomical changes in normal aging.

Memory performance and affect: are there gender differences in community-residing older adults?

After age 65, the incidence of episodic memory decline in males is greater than in females. We explored the influence of anxiety and depression on objective and subjective memory performance in a diverse sample of community-residing older adults. The study was a secondary analysis of data on three samples of adults from two states, Ohio and Texas: a community sample (n = 177); a retirement community sample (n = 97); and the SeniorWISE Study (n = 265). The sample of 529 adults was 74% female, the average age was 76.58 years (range = 59-100 years), and educational attainment was 13.12 years (±3.68); 68% were Caucasian, and 17% had depressive symptoms. We found no memory performance differences by gender. Males and females were similarly classified into the four memory performance groups, with almost half of each gender in the poor memory category. Even though males had greater years of education, they used fewer compensatory memory strategies. The observed gender differences in memory were subjective evaluations, specifically metamemory. Age was not a significant predictor of cognition or memory performance, nor did males have greater memory impairment than females.

Altered structural covariance of the striatum in functional dyspepsia patients

BACKGROUND

Functional dyspepsia (FD) is thought to be involved in dysregulation within the brain-gut axis. Recently, altered striatum activation has been reported in patients with FD. However, the gray matter (GM) volumes in the striatum and structural covariance patterns of this area are rarely explored. The purpose of this study was to examine the GM volumes and structural covariance patterns of the striatum between FD patients and healthy controls (HCs).

METHODS

T1-weighted magnetic resonance images were obtained from 44 FD patients and 39 HCs. Voxel-based morphometry (VBM) analysis was adopted to examine the GM volumes in the two groups. The caudate- or putamen-related regions identified from VBM analysis were then used as seeds to map the whole brain voxel-wise structural covariance patterns. Finally, a correlation analysis was used to investigate the effects of FD symptoms on the striatum.

KEY RESULTS

The results showed increased GM volumes in the bilateral putamen and right caudate. Compared with the structural covariance patterns of the HCs, the FD-related differences were mainly located in the amygdala, hippocampus/parahippocampus (HIPP/paraHIPP), thalamus, lingual gyrus, and cerebellum. And significant positive correlations were found between the volumes in the striatum and the FD duration in the patients.

CONCLUSIONS & INFERENCES

These findings provided preliminary evidence for GM changes in the striatum and different structural covariance patterns in patients with FD. The current results might expand our understanding of the pathophysiology of FD.

Aging Influence on Gray Matter Structural Associations within the Default Mode Network Utilizing Bayesian Network Modeling

Recent neuroimaging studies have revealed normal aging-related alterations in functional and structural brain networks such as the default mode network (DMN). However, less is understood about specific brain structural dependencies or interactions between brain regions within the DMN in the normal aging process. In this study, using Bayesian network (BN) modeling, we analyzed gray matter volume data from 109 young and 82 old subjects to characterize the influence of aging on associations between core brain regions within the DMN. Furthermore, we investigated the discriminability of the aging-associated BN models for the young and old groups. Compared to their young counterparts, the old subjects showed significant reductions in connections from right inferior temporal cortex (ITC) to medial prefrontal cortex (mPFC), right hippocampus (HP) to right ITC, and mPFC to posterior cingulate cortex and increases in connections from left HP to mPFC and right inferior parietal cortex to right ITC. Moreover, the classification results showed that the aging-related BN models could predict group membership with 88.48% accuracy, 88.07% sensitivity, and 89.02% specificity. Our findings suggest that structural associations within the DMN may be affected by normal aging and provide crucial information about aging effects on brain structural networks.

Strategic lacunes and their relationship to cognitive impairment in cerebral small vessel disease

Objectives

Lacunes are an important disease feature of cerebral small vessel disease (SVD) but their relationship to cognitive impairment is not fully understood. To investigate this we determined (1) the relationship between lacune count and total lacune volume with cognition, (2) the spatial distribution of lacunes and the cognitive impact of lacune location, and (3) the whole brain anatomical covariance associated with these strategically located regions of lacune damage.

Methods

One hundred and twenty one patients with symptomatic lacunar stroke and radiological leukoaraiosis were recruited and multimodal MRI and neuropsychological data acquired. Lacunes were mapped semi-automatically and their volume calculated. Lacune location was automatically determined by projection onto atlases, including an atlas which segments the thalamus based on its connectivity to the cortex. Lacune locations were correlated with neuropsychological results. Voxel based morphometry was used to create anatomical covariance maps for these ‘strategic’ regions.

Results

Lacune number and lacune volume were positively associated with worse executive function (number p < 0.001; volume p < 0.001) and processing speed (number p < 0.001; volume p < 0.001). Thalamic lacunes, particularly those in regions with connectivity to the prefrontal cortex, were associated with impaired processing speed (Bonferroni corrected p = 0.016). Regions of associated anatomical covariance included the medial prefrontal, orbitofrontal, anterior insular cortex and the striatum.

Conclusion

Lacunes are important predictors of cognitive impairment in SVD. We highlight the importance of spatial distribution, particularly of anteromedial thalamic lacunes which are associated with impaired information processing speed and may mediate cognitive impairment via disruption of connectivity to the prefrontal cortex.

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Lacunes are a predictor of cognitive impairment in cerebral small vessel disease

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Lacunes in the anteromedial thalamus are associated with impaired processing speed

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This region was identified to have connectivity to the prefrontal cortex

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We validate this finding with the help of a structural covariance analysis

Brain tissue properties differentiate between motor and limbic basal ganglia circuits

Despite advances in understanding basic organizational principles of the human basal ganglia, accurate in vivo assessment of their anatomical properties is essential to improve early diagnosis in disorders with corticosubcortical pathology and optimize target planning in deep brain stimulation. Main goal of this study was the detailed topological characterization of limbic, associative, and motor subdivisions of the subthalamic nucleus (STN) in relation to corresponding corticosubcortical circuits. To this aim, we used magnetic resonance imaging and investigated independently anatomical connectivity via white matter tracts next to brain tissue properties. On the basis of probabilistic diffusion tractography we identified STN subregions with predominantly motor, associative, and limbic connectivity. We then computed for each of the nonoverlapping STN subregions the covariance between local brain tissue properties and the rest of the brain using high‐resolution maps of magnetization transfer (MT) saturation and longitudinal (R1) and transverse relaxation rate (R2*). The demonstrated spatial distribution pattern of covariance between brain tissue properties linked to myelin (R1 and MT) and iron (R2*) content clearly segregates between motor and limbic basal ganglia circuits. We interpret the demonstrated covariance pattern as evidence for shared tissue properties within a functional circuit, which is closely linked to its function. Our findings open new possibilities for investigation of changes in the established covariance pattern aiming at accurate diagnosis of basal ganglia disorders and prediction of treatment outcome. Hum Brain Mapp 35:5083–5092, 2014. © 2014 The Authors. Human Brain Mapping Published by Wiley Periodicals, Inc.

Irritable bowel syndrome in female patients is associated with alterations in structural brain networks

Alterations in gray matter (GM) density/volume and cortical thickness (CT) have been demonstrated in small and heterogeneous samples of subjects with differing chronic pain syndromes, including irritable bowel syndrome (IBS). Aggregating across 7 structural neuroimaging studies conducted at University of California, Los Angeles, Los Angeles, CA, USA, between August 2006 and April 2011, we examined group differences in regional GM volume in 201 predominantly premenopausal female subjects (82 IBS, mean age: 32±10 SD, 119 healthy controls [HCs], 30±10 SD). Applying graph theoretical methods and controlling for total brain volume, global and regional properties of large-scale structural brain networks were compared between the group with IBS and the HC group. Relative to HCs, the IBS group had lower volumes in the bilateral superior frontal gyrus, bilateral insula, bilateral amygdala, bilateral hippocampus, bilateral middle orbital frontal gyrus, left cingulate, left gyrus rectus, brainstem, and left putamen. Higher volume was found in the left postcentral gyrus. Group differences were no longer significant for most regions when controlling for the Early Trauma Inventory global score, with the exception of the right amygdala and the left postcentral gyrus. No group differences were found for measures of global and local network organization. Compared to HCs, in patients with IBS, the right cingulate gyrus and right thalamus were identified as being significantly more critical for information flow. Regions involved in endogenous pain modulation and central sensory amplification were identified as network hubs in IBS. Overall, evidence for central alterations in patients with IBS was found in the form of regional GM volume differences and altered global and regional properties of brain volumetric networks.

Imaging structural co-variance between human brain regions

Brain structure varies between people in a markedly organized fashion. Communities of brain regions co-vary in their morphological properties. For example, cortical thickness in one region influences the thickness of structurally and functionally connected regions. Such networks of structural co-variance partially recapitulate the functional networks of healthy individuals and the foci of grey matter loss in neurodegenerative disease. This architecture is genetically heritable, is associated with behavioural and cognitive abilities and is changed systematically across the lifespan. The biological meaning of this structural co-variance remains controversial, but it appears to reflect developmental coordination or synchronized maturation between areas of the brain. This Review discusses the state of current research into brain structural co-variance, its underlying mechanisms and its potential value in the understanding of various neurological and psychiatric conditions.

Age-related changes in brain structural covariance networks

Previous neuroimaging studies have suggested that cerebral changes over normal aging are not simply characterized by regional alterations, but rather by the reorganization of cortical connectivity patterns. The investigation of structural covariance networks (SCNs) using voxel-based morphometry is an advanced approach to examining the pattern of covariance in gray matter (GM) volumes among different regions of the human cortex. To date, how the organization of critical SCNs change during normal aging remains largely unknown. In this study, we used an SCN mapping approach to investigate eight large-scale networks in 240 healthy participants aged 18-89 years. These participants were subdivided into young (18-23 years), middle aged (30-58 years), and older (61-89 years) subjects. Eight seed regions were chosen from widely reported functional intrinsic connectivity networks. The voxels showing significant positive associations with these seed regions were used to describe the topological organization of an SCN. All of these networks exhibited non-linear patterns in their spatial extent that were associated with normal aging. These networks, except the primary motor network, had a distributed topology in young participants, a sharply localized topology in middle aged participants, and were relatively stable in older participants. The structural covariance derived using the primary motor cortex was limited to the ipsilateral motor regions in the young and older participants, but included contralateral homologous regions in the middle aged participants. In addition, there were significant between-group differences in the structural networks associated with language-related speech and semantics processing, executive control, and the default-mode network (DMN). Taken together, the results of this study demonstrate age-related changes in the topological organization of SCNs, and provide insights into normal aging of the human brain.