Structural Magnetic Resonance Imaging Scans Research Articles

Gyrification in relation to cortical thickness in the congenitally blind.

Greater cortical gyrification (GY) is linked with enhanced cognitive abilities and is also negatively related to cortical thickness (CT). Individuals who are congenitally blind (CB) exhibits remarkable functional brain plasticity which enables them to perform certain non-visual and cognitive tasks with supranormal abilities. For instance, extensive training using touch and audition enables CB people to develop impressive skills and there is evidence linking these skills to cross-modal activations of primary visual areas. There is a cascade of anatomical, morphometric and functional-connectivity changes in non-visual structures, volumetric reductions in several components of the visual system, and CT is also increased in CB. No study to date has explored GY changes in this population, and no study has explored how variations in CT are related to GY changes in CB. T1-weighted 3D structural magnetic resonance imaging scans were acquired to examine the effects of congenital visual deprivation in cortical structures in a healthy sample of 11 CB individuals (6 male) and 16 age-matched sighted controls (SC) (10 male). In this report, we show for the first time an increase in GY in several brain areas of CB individuals compared to SC, and a negative relationship between GY and CT in the CB brain in several different cortical areas. We discuss the implications of our findings and the contributions of developmental factors and synaptogenesis to the relationship between CT and GY in CB individuals compared to SC. F.

Relations of gray matter volume to dimensional measures of cognition and affect in mood disorders.

Understanding the relationship between brain measurements and behavioral performance is an important step in developing approaches for early identification of any psychiatric difficulties and interventions to modify these challenges. Conventional methods to identify associations between regional brain volume and behavioral measures are not optimized, either in scale, scope, or specificity. To find meaningful associations between brain and behavior with greater sensitivity and precision, we applied data-driven factor analytic models to identify and extract individual differences in latent cognitive functions embedded across several computerized cognitive tasks. Furthermore, we simultaneously utilized a keyword-based neuroimaging meta-analytic tool (i.e., NeuroSynth), restricted atlas-parcel matching, and factor-analytic models to narrow down the scope of search and to further aggregate gray matter volume (GMV) data into empirical clusters. We recruited an early adult community cross-sectional sample (Total n=177, age 18-30) that consisted of individuals with no history of any mood disorder (healthy controls, n=44), those with remitted major depressive disorder (rMDD, n=104), and those with a diagnosis of bipolar disorder currently in euthymic state (eBP, n=29). Study participants underwent structural magnetic resonance imaging (MRI) scans and separately completed behavioral testing using computerized measures. Factor-analyzing five computerized tasks used to assess aspects of cognitive and affective processing resulted in seven latent dimensions: (a) Emotional Memory, (b) Interference Resolution, (c) Reward Sensitivity, (d) Complex Inhibitory Control, (e) Facial Emotion Sensitivity, (f) Sustained attention, and (g)Simple Impulsivity/Response Style. These seven dimensions were then labeled with specific keywords which were used to create neuroanatomical maps using NeuroSynth. These masks were further subdivided into GMV clusters. Using regression, we identified GMV clusters that were predictive of individual differences across each of the aforementioned seven cognitive dimensions. We demonstrate that a dimensional approach consistent with core principles of RDoC can be utilized to identify structural variability predictive of critical dimensions of human behavior.

Brain Age Prediction: A Comparison between Machine Learning Models Using Brain Morphometric Data.

Brain structural morphology varies over the aging trajectory, and the prediction of a person’s age using brain morphological features can help the detection of an abnormal aging process. Neuroimaging-based brain age is widely used to quantify an individual’s brain health as deviation from a normative brain aging trajectory. Machine learning approaches are expanding the potential for accurate brain age prediction but are challenging due to the great variety of machine learning algorithms. Here, we aimed to compare the performance of the machine learning models used to estimate brain age using brain morphological measures derived from structural magnetic resonance imaging scans. We evaluated 27 machine learning models, applied to three independent datasets from the Human Connectome Project (HCP, n = 1113, age range 22–37), the Cambridge Centre for Ageing and Neuroscience (Cam-CAN, n = 601, age range 18–88), and the Information eXtraction from Images (IXI, n = 567, age range 19–86). Performance was assessed within each sample using cross-validation and an unseen test set. The models achieved mean absolute errors of 2.75–3.12, 7.08–10.50, and 8.04–9.86 years, as well as Pearson’s correlation coefficients of 0.11–0.42, 0.64–0.85, and 0.63–0.79 between predicted brain age and chronological age for the HCP, Cam-CAN, and IXI samples, respectively. We found a substantial difference in performance between models trained on the same data type, indicating that the choice of model yields considerable variation in brain-predicted age. Furthermore, in three datasets, regularized linear regression algorithms achieved similar performance to nonlinear and ensemble algorithms. Our results suggest that regularized linear algorithms are as effective as nonlinear and ensemble algorithms for brain age prediction, while significantly reducing computational costs. Our findings can serve as a starting point and quantitative reference for future efforts at improving brain age prediction using machine learning models applied to brain morphometric data.

Naturalistic Sleep Patterns are Linked to Global Structural Brain Aging in Adolescence

PurposeWe examined whether interindividual differences in naturalistic sleep patterns correlate with any deviations from typical brain aging. MethodsOur sample consisted of 251 participants without current psychiatric diagnoses (9–25 years; mean [standard deviation] = 17.4 ± 4.52 yr; 58% female) drawn from the Neuroimaging and Pediatric Sleep Databank. Participants completed a T1-weighted structural magnetic resonance imaging scan and 5–7 days of wrist actigraphy to assess naturalistic sleep patterns (duration, timing, continuity, and regularity). We estimated brain age from extracted structural magnetic resonance imaging indices and calculated brain age gap (estimated brain age–chronological age). Robust regressions tested cross-sectional associations between brain age gap and sleep patterns. Exploratory models investigated moderating effects of age and biological gender and, in a subset of the sample, links between sleep, brain age gap, and depression severity (Patient-Reported Outcomes Measurement Information System Depression). ResultsLater sleep timing (midsleep) was associated with more advanced brain aging (larger brain age gap), β = 0.1575, puncorr = .0042, pfdr = .0167. Exploratory models suggested that this effect may be driven by males, although the interaction of gender and brain age gap did not survive multiple comparison correction (β = 0.2459, puncorr = .0336, pfdr = .1061). Sleep duration, continuity, and regularity were not significantly associated with brain age gap. Age did not moderate any brain age gap–sleep relationships. In this psychiatrically healthy sample, depression severity was also not associated with brain age gap or sleep. DiscussionLater midsleep may be one behavioral cause or correlate of more advanced brain aging, particularly among males. Future studies should examine whether advanced brain aging and individual differences in sleep precede the onset of suboptimal cognitive-emotional outcomes in adolescents.

Maternal warmth is associated with network segregation across late childhood: A longitudinal neuroimaging study.

The negative impact of adverse experiences in childhood on neurodevelopment is well documented. Less attention however has been given to the impact of variations in “normative” parenting behaviors. The influence of these parenting behaviors is likely to be marked during periods of rapid brain reorganization, such as late childhood. The aim of the current study was to investigate associations between normative parenting behaviors and the development of structural brain networks across late childhood. Data were collected from a longitudinal sample of 114 mother-child dyads (54% female children, M age 8.41 years, SD = 0.32 years), recruited from low socioeconomic areas of Melbourne, Australia. At the first assessment parenting behaviors were coded from two lab-based interaction tasks and structural magnetic resonance imaging (MRI) scans of the children were performed. At the second assessment, approximately 18 months later (M age 9.97 years, SD = 0.37 years) MRI scans were repeated. Cortical thickness (CT) was extracted from T1-weighted images using FreeSurfer. Structural covariance (SC) networks were constructed from partial correlations of CT estimates between brain regions and estimates of network efficiency and modularity were obtained for each time point. The change in these network measures, from Time 1 to Time 2, was also calculated. At Time 2, less positive maternal affective behavior was associated with higher modularity (more segregated networks), while negative maternal affective behavior was not related. No support was found for an association between local or global efficacy and maternal affective behaviors at Time 2. Similarly, no support was demonstrated for associations between maternal affective behaviors and change in network efficiency and modularity, from Time 1 to Time 2. These results indicate that normative variations in parenting may influence the development of structural brain networks in late childhood and extend current knowledge about environmental influences on structural connectivity in a developmental context.

Functional connectivity of limbic system and prefrontal cortex years after pre-eclampsia: 7-Tesla functional magnetic resonance imaging study.

Pre-eclampsia is a vascular complication of pregnancy, associated with a long-term risk of cerebrovascular and mental disorders. We explored whether formerly pre-eclamptic women exhibit differences in functional brain organization, especially in regions that may explain the commonly reported emotional symptoms and cognitive complaints even years after the pregnancy. Formerly pre-eclamptic women and control women with a history of normotensive pregnancy underwent structural and functional 7-Tesla magnetic resonance imaging scans. Using graph theoretical analysis, the efficiency and clustering coefficient of the functional brain network were investigated. The study included local analysis focusing on particular brain structures, such as the limbic system and the prefrontal cortex, and global analysis of the whole cerebrum. Univariable and multivariable linear regression was used to investigate the relationship between brain network-related graph measures and the group (formerly pre-eclamptic or control). A total of 17 control parous women and 55 women with a history of pre-eclampsia were recruited. The time intervals between the index pregnancy and recruitment were 8.0 and 5.6 years for the two groups, respectively. Compared with control women, formerly pre-eclamptic women had higher local efficiency in the prefrontal cortex (P = 0.048) and anterior cingulate cortex (P = 0.03) but lower local efficiency and local clustering coefficient in the amygdala (P = 0.004 and P = 0.02, respectively) and parahippocampal cortex (P = 0.007 and P = 0.008, respectively). No differences were found in the global functional brain organization. Compared to controls with a history of normotensive pregnancy, formerly pre-eclamptic women displayed a different local functional brain organization. These differences in functional connectivity, especially in the limbic regions and the prefrontal cortex, are in line with the psychological and cognitive complaints reported commonly by women with a history of pre-eclampsia. © 2022 The Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology.

Functional connectivity and structural changes of thalamic subregions in episodic migraine

BackgroundThe thalamus plays a crucial role in transmitting nociceptive information to various cortical regions involving migraine-related allodynia and photophobia. Abnormal structural and functional alterations related to the thalamus have been well established. However, it is unknown whether the brain structure and function of the thalamic subregions are differentially affected in this disorder. In this study, we aimed to clarify this issue by comparing the structure and function of 16 thalamic subregions between patients with episodic migraine (EM) and healthy controls (HCs).MethodsTwenty-seven patients with EM and 30 sex-, age- and education-matched HCs underwent resting-state functional and structural magnetic resonance imaging scans. Functional connectivity (rsFC), grey matter volume (GMV), and diffusion tensor imaging (DTI) parameters of each subregion of the thalamus were calculated and compared between the two groups. Furthermore, correlation analyses between neuroimaging changes and clinical features were performed in this study.ResultsFirst, compared with HCs, patients with EM exhibited decreased rsFC between the anterior-medial-posterior subregions of the thalamus and brain regions mainly involved in the medial system of the pain processing pathway and default mode network (DMN). Second, for the whole thalamus and each of its subregions, there were no significant differences in GMV between patients with EM and HCs (P > 0.05, Bonferroni corrected). Third, there was no significant difference in DTI parameters between the two groups (P > 0.05). Finally, decreased rsFC was closely related to scores on the Hamilton Rating Scale for Anxiety (HAMA) and Big Five Inventory (BFI) scales.ConclusionSelective functional hypoconnectivity in the thalamic subregions provides neuroimaging evidence supporting the important role of thalamocortical pathway dysfunction in episodic migraine, specifically, that it may modulate emotion and different personality traits in migraine patients.

Incidental neuroimaging findings in South African adult research participants with and without neuropsychiatric disorders

There is a lack of comparative data on the occurrence and clinical significance of incidental neuroimaging findings (IFs) in adult research participants with neuropsychiatric disorders and healthy controls. We investigated and compared the frequency, clinical significance and predictors of IFs on structural brain magnetic resonance imaging (MRI) scans of research participants between the ages of 18–78 years living in Cape Town, South Africa. Our sample (N = 295) included individuals with posttraumatic stress disorder (n = 122) or Parkinson's disease (n = 21), and healthy controls (n = 152). T1 ME-MPRAGE weighted structural MRI scans were acquired and subsequently reviewed for IFs by radiologists. A neurologist reviewed radiological reports and categorised IFs according to their estimated clinical significance. IFs were observed on the scans of 95 (32%) participants but most IFs were either judged to be clinically non-significant (49%) or of unknown clinical significance (32%). Eighteen participants (6%) had clinically significant findings that required referral for further clinical management. Age was a significant predictor of having an IF, whereas a diagnosis of Parkinson's disease was a significant predictor of having a clinically significant IF.

Case studies in neuroscience: reversible signatures of edema following electric and piezoelectric craniotomy drilling in macaques.

In vivo electrophysiology requires direct access to brain tissue, necessitating the development and refinement of surgical procedures and techniques that promote the health and well-being of animal subjects. Here, we report a series of findings noted on structural magnetic resonance imaging (MRI) scans in monkeys with MRI-compatible implants following small craniotomies that provide access for intracranial electrophysiology. We found distinct brain regions exhibiting hyperintensities in T2-weighted scans that were prominent underneath the sites at which craniotomies had been performed. We interpreted these hyperintensities as edema of the neural tissue and found that they were predominantly present following electric and piezoelectric drilling, but not when manual, hand-operated drills were used. Furthermore, the anomalies subsided within 2-3 wk following surgery. Our report highlights the utility of MRI-compatible implants that promote clinical examination of the animal's brain, sometimes revealing findings that may go unnoticed when incompatible implants are used. We show replicable differences in outcome when using electric versus mechanical devices, both ubiquitous in the field. If electric drills are used, our report cautions against electrophysiological recordings from tissue directly underneath the craniotomy for the first 2-3 wk following the procedure due to putative edema.NEW & NOTEWORTHY Close examination of structural MRI in eight nonhuman primates following craniotomy surgeries for intracranial electrophysiology highlights a prevalence of hyperintensities on T2-weighted scans following surgeries conducted using electric and piezoelectric drills, but not when using mechanical, hand-operated drills. We interpret these anomalies as edema of neural tissue that resolved 2-3 wk postsurgery. This finding is especially of interest as electrophysiological recordings from compromised tissue may directly influence the integrity of collected data immediately following surgery.

Neuronavigation maximizes accuracy and precision in TMS positioning: Evidence from 11,230 distance, angle, and electric field modeling measurements

BackgroundResearchers and clinicians have traditionally relied on elastic caps with markings to reposition the transcranial magnetic stimulation (TMS) coil between trains and sessions. Newer neuronavigation technology co-registers the patient's head and structural magnetic resonance imaging (MRI) scan, providing the researcher with real-time feedback about how to adjust the coil to be on-target. However, there has been no head to head comparison of accuracy and precision across treatment sessions. Objective/Hypothesis: In this two-part study, we compared elastic cap and neuronavigation targeting methodologies on distance, angle, and electric field (E-field) magnitude values. MethodsIn 42 participants receiving up to 50 total accelerated rTMS sessions in 5 days, we compared cap and neuronavigation targeting approaches in 3408 distance and 6816 angle measurements. In Experiment 1, TMS administrators saved an on-target neuronavigation location at Beam F3, which served as the landmark for all other measurements. Next, the operators placed the TMS coil based on cap markings or neuronavigation software to measure the distance and angle differences from the on-target sample. In Experiment 2, we saved each XYZ coordinate of the TMS coil from cap and neuronavigation targeting in 12 participants to compare the E-field magnitude differences at the cortical prefrontal target in 1106 cap and neuronavigation models. ResultsCap targeting was significantly off-target for distance, placing the coil an average of 10.66 mm off-target (Standard error of the mean; SEM = 0.19 mm) compared to 0.3 mm (SEM = 0.03 mm) for neuronavigation (p < 0.0001). Cap targeting also significantly deviated for angles off-target, averaging 7.79 roll/pitch degrees (SEM = 1.07°) off-target and 5.99 yaw degrees (SEM = 0.12°) off-target; in comparison, neuronavigation targeting positioned the coil 0.34 roll/pitch degrees (SEM = 0.01°) and 0.22 yaw (SEM = 0.004°) off-target (both p < 0.0001). Further analyses revealed that there were significant inter-operator differences on distance and angle positioning for F3 (all p < 0.05), but not neuronavigation. Lastly, cap targeting resulted in significantly lower E-fields at the intended prefrontal cortical target, with equivalent E-fields as 110.7% motor threshold (MT; range = 58.3–127.4%) stimulation vs. 119.9% MT (range = 115–123.3%) from neuronavigated targeting with 120% MT stimulation applied (p < 0.001). ConclusionsCap-based targeting is an inherent source of target variability compared to neuronavigation. Additionally, cap-based coil placement is more prone to differences across operators. Off-target coil placement secondary to cap-based measurements results in significantly lower amounts of stimulation reaching the cortical target, with some individuals receiving only 48.6% of the intended on-target E-field. Neuronavigation technology enables more precise and accurate TMS positioning, resulting in the intended stimulation intensities at the targeted cortical level.

An application of non-dominated sorting genetic algorithm for reversible data hiding based on histogram shifting in neuroimages

This paper presents an application of multi-objective non-dominated sorting genetic algorithm with a modified chromosome encoding for histogram shifting-based multiple reversible data hiding scheme in neuroimages which aims to minimize distortion and maximize capacity. The modified chromosomes encoding scheme is designed according to the zero-bin characteristic of the intensity histogram of the structural magnetic resonance imaging scans of human brain. The experiments of this study is designed to assess the effect of non-dominated sorting for multi-objective optimization compared to Euclidian distance, the convenience of modified chromosome encoding scheme for medical images compared to non-medical images. The performance of the proposed method has been measured in terms of the peak signal-to-noise ratio (PSNR) for image quality and the bits per pixel (bpp) for capacity assessments. The experimental results show that the proposed method is better than its counterparts.

Neuroanatomical subtypes of schizophrenia and relationship with illness duration and deficit status

BackgroundThe heterogeneity of schizophrenia (SCZ) regarding psychopathology, illness trajectory and their inter-relationships with underlying neural substrates remain incompletely understood. In a bid to reduce illness heterogeneity using neural substrates, our study aimed to replicate the findings of an earlier study by Chand et al. (2020). We employed brain structural measures for subtyping SCZ patients, and evaluate each subtype's relationship with clinical features such as illness duration, psychotic psychopathology, and additionally deficit status. MethodsOverall, 240 subjects (160 SCZ patients, 80 healthy controls) were recruited for this study. The participants underwent brain structural magnetic resonance imaging scans and clinical rating using the Positive and Negative Syndrome Scale. Neuroanatomical subtypes of SCZ were identified using “Heterogeneity through discriminative analysis” (HYDRA), a clustering technique which accounted for relevant covariates and the inter-group normalized percentage changes in brain volume were also calculated. ResultsAs replicated, two neuroanatomical subtypes (SG-1 and SG-2) were found amongst our patients with SCZ. The subtype SG-1 was associated with enlargements in the third and lateral ventricles, volume increase in the basal ganglia (putamen, caudate, pallidum), longer illness duration, and deficit status. The subtype SG-2 was associated with reductions of cortical and subcortical structures (hippocampus, thalamus, basal ganglia). ConclusionsThese replicated findings have clinical implications in the early intervention, response monitoring, and prognostication of SCZ. Future studies may adopt a multi-modal neuroimaging approach to enhance insights into the neurobiological composition of relevant subtypes.

The instant impact of a single hemodialysis session on brain morphological measurements in patients with end-stage renal disease.

ObjectiveTo investigate the instant impact of hemodialysis (HD) on the cerebral morphological measurements of patients with end-stage renal disease (ESRD).Materials and methodsTwenty-five patients undergoing maintenance HD and twenty-eight age-, sex-, and education-matched healthy control (HC) were included. The HD group and HC group had 3D high-resolution structural magnetic resonance imaging (MRI) scans twice and once, respectively. Both groups underwent neuropsychologic tests. The morphological measurements of structural MRI were measured using CAT12 and these measures were compared among three groups. The relationship between morphological measures and clinical parameters and neuropsychological tests were investigated through multiple regression analysis.ResultsCompared to the HC group, the cortical thickness before HD significantly decreased in the bilateral temporal lobe and significantly decreased in the left superior temporal gyrus after HD. The cortical thickness significantly increased in the bilateral temporal lobe, frontal lobe and occipital lobe after HD compared to before HD. The sulcus depth in the bilateral insula, frontal lobe, and parietal lobe after HD significantly increased compared to before HD. No significant differences in sulcus depth between HD and HC were detected. After HD, the cortical thickness of the right parsopercularis was positively correlated with the number connection test-A. Cortical thickness in multiple regions were positively correlated with blood flow velocity and cortical thickness in the left parahippocampal gyrus was negatively correlated with ultrafiltration volume. Patients showed better performance in the digit symbol test and line tracing test after HD compared to before HD, but there were no significant differences in the comparison of neuropsychologic tests between patients and HC.ConclusionThe instant morphological changes were captured during a single hemodialysis in HD patients. There was an association between these instant changes in the brain and clinical parameters and neuropsychologic tests. This work implied the instant impact of a single hemodialysis impact on the brain in HD patients.

Altered local gyrification index and corresponding resting-state functional connectivity in individuals with high test anxiety

Previous studies have reported that test anxiety is closely related to unreasonable cognitive patterns and maladaptive emotional responses. However, its underlying brain structural and functional basis has not been thoroughly studied. This study aimed to evaluate the potential difference in local gyration index (LGI) and corresponding resting-state functional connectivity (RSFC) in individuals with high test anxiety (HTA) compared with low test anxiety (LTA). Twenty-six individuals with HTA and 28 individuals with LTA underwent T1-weighted structural and resting-state functional magnetic resonance imaging scans. Using FreeSurfer software, we contrasted the LGI between the HTA and LTA groups using a surface-based general linear model to map group contrasts on a vertex-by-vertex basis. By selecting the cortical regions with significant differences in the LGI analysis as the regions of interest, the seed-based RSFC analysis was further carried out using the Resting-State fMRI Data Analysis Toolkit to examine the differences in the functional connectivity of these cortical regions with the whole brain between the two groups. The results showed that the LGI in several cortical regions of the executive control network (ECN) and the right lateral occipital gyrus was lower in the HTA group than in the LTA group. Furthermore, compared with the LTA group, the HTA group exhibited abnormal RSFC within the ECN, between the ECN and the visual network, and between the ECN and the sensorimotor network. Our findings might provide preliminary evidence for brain morphology and functional alterations in individuals with HTA and contribute to a better understanding of the pathophysiology of TA.

Dorsal bed nucleus of stria terminalis in depressed and nondepressed temporal lobe epilepsy patients.

Temporal lobe epilepsy (TLE) and depression are common comorbid disorders whose underlying shared neural network has yet to be determined. Although animal studies demonstrate a role for the dorsal bed nucleus of the stria terminalis (dBNST) in both seizures and depression, and human clinical studies demonstrate a therapeutic effect of stimulating this region on treatment-resistant depression, the role of the dBNST in depressed and nondepressed TLE patients is still unclear. Here, we tested the hypothesis that this structure is morphologically abnormal in these epilepsy patients, with an increased abnormality in TLE patients with comorbid depression. In this case-controlled study, 3-T structural magnetic resonance imaging scans were obtained from TLE patients with no depression (TLEonly), TLE patients with depression (TLEdep), and healthy control (HC) subjects. TLE subjects were recruited from the Yale University Comprehensive Epilepsy Center, diagnosed with the International League Against Epilepsy 2014 Diagnostic Guidelines, and confirmed by video-electroencephalography. Diagnosis of major depressive disorder was confirmed by a trained neuropsychologist through a Mini International Neuropsychiatric Interview based on the Diagnostic and Statistical Manual of Mental Disorders, 4th edition. The dBNST was delineated manually by reliable raters using Bioimage Suite software. The number of patients and subjects included 35 TLEonly patients, 20 TLEdep patients, and 102 HC subjects. Both TLEonly and TLEdep patients had higher dBNST volumes compared to HC subjects, unilaterally in the left hemisphere in the TLEonly patients (p= .003) and bilaterally in the TLEdep patients (p< .0001). Furthermore, the TLEdep patients had a higher dBNST volume than the TLEonly patients in the right hemisphere (p= .02). Here, we demonstrate an abnormality of the dBNST in TLE patients, both without depression (left enlargement) and with depression (bilateral enlargement). Our results demonstrate this region to underlie TLE both with and without depression, implicating it as a target in treating the comorbidity between these two disorders.

Neuroanatomical Correlates of Emotion-Related Impulsivity

BackgroundEmotion-related impulsivity (ERI) refers to chronically poor self-control during periods of strong emotion. ERI robustly predicts psychiatric disorders and related problems, yet its neuroanatomical correlates are largely unknown. We tested whether local brain morphometry in targeted brain regions that integrate emotion and control could explain ERI severity. MethodsOne hundred twenty-two adults (ages 18–55 years) with internalizing or externalizing psychopathology completed a structural magnetic resonance imaging (MRI) scan, the Three-Factor Impulsivity Index, and the Structured Clinical Interview for DSM-5. The Three-Factor Impulsivity Index measures two types of ERI and a third type of impulsivity not linked to emotion. Cortical reconstruction yielded cortical thickness and local gyrification measurements. We evaluated whether morphometry in the orbitofrontal cortex (OFC), insula, amygdala, and nucleus accumbens was associated with ERI severity. Hypotheses and analyses were preregistered. ResultsLower cortical gyrification in the right lateral OFC was associated with high ERI severity in a full, preregistered model. Separate examinations of local gyrification and cortical thickness also showed a positive association between gyrification in the left lateral OFC and ERI. An integrated measure of hemispheric imbalance in lateral OFC gyrification (right < left) correlated with ERI severity. These findings were specific to ERI and did not appear with non–emotion-related impulsivity. ConclusionsLocal gyrification in the lateral OFC is associated with ERI severity. The current findings fit with existing theories of OFC function, strengthen the connections between the transdiagnostic literature in psychiatry and neuroscience, and may guide future treatment development.

The hypertrophic amygdala shape associated with anxiety in patients with primary dysmenorrhea during pain-free phase: insight from surface-based shape analysis

BackgroundPrimary dysmenorrhea (PDM) is highly associated with mood symptoms. However, the neuropathology of these comorbidities is unclear. In the present study, we aimed to investigate the structural changes in the amygdala of patients with PDM during the pain-free phase using a surface-based shape analysis.MethodsForty-three PDM patients and forty healthy controls were recruited in the study, and all participants underwent structural magnetic resonance imaging scans during their periovulatory phase. FMRIB’s Integrated Registration and Segmentation Tool (FIRST) was employed to assess the subcortical volumetric and surface alterations in patients with PDM. Moreover, correlation and mediation analyses were used to detect the clinical significance of the subcortical morphometry alteration.ResultsPDM patients showed hypertrophic alteration of the amygdala in the left superficial nuclei and right basolateral and superficial nuclei but not for the whole amygdala volume. The hypertrophic amygdala was associated with disease duration, pain severity and anxiety symptoms during the menstrual period. Furthermore, the hypertrophic left amygdala could mediate the association between disease duration and anxiety severity.ConclusionsThe results of the current study demonstrated that the localized amygdala shape hypertrophy was present in PDM patients even in the pain-free phase. In addition, the mediator role of the hypertrophic amygdala indicates the potential target of amygdala for anxiety treatment in PDM treatment in the pain-free phase.

Study on the changes of Structural Covariance Network in post-traumatic stress disorder.

The topological properties of functional brain networks in post-traumatic stress disorder (PTSD) have been thoroughly examined, whereas the topology of structural covariance networks has been researched much less. Based on graph theoretical approaches, we investigated the topological architecture of structural covariance networks among PTSD, trauma-exposed controls (TEC), and healthy controls (HC) by constructing covariance networks driven by inter-regional correlations of cortical thickness. Structural magnetic resonance imaging (sMRI) scans and clinical scales were performed on 27 PTSD, 33 TEC, and 29 HC subjects. Group-level structural covariance networks were established using pearson correlations of cortical thickness between 68 brain areas, and the graph theory method was utilized to study the global and nodal properties. PTSD and HC subjects did not differ at the global level. When PTSD subjects were compared to TEC subjects, they had significantly higher clustering coefficient (p = .014) and local efficiency (p = .031). Nodes having different nodal centralities between groups did not pass the false-discovery rate correction at the node level. According to the structural brain network topological characteristics discovered in this study, PTSD manifests differently compared to the TEC group. In the PTSD group, the SCN keeps the small-world characteristics, but the degree of functional separation is enhanced. The TEC group's reduced small worldness and the tendency for brain network randomization could be signs of trauma recovery.

Visual task-related functional and structural magnetic resonance imaging for the objective quantitation of visual function in patients with advanced retinitis pigmentosa.

PurposeThe objective quantitation of visual function in patients with advanced retinitis pigmentosa (RP) presents a difficult challenge due to the weak visual function of these patients. This study utilized magnetic resonance imaging (MRI) to assess the function and structure of the visual cortex (VC) in patients with RP and quantitatively categorize them.Materials and MethodsTwenty-three patients with RP and ten healthy controls (HCs) were enrolled for MRI examinations. The patients were divided into form perception (FP) and no form perception (NFP) groups. Participants underwent structural MRI scans, and two visual task functional MRI scans were performed using stimuli, including white flash and black and white checkerboard patterns. Eight regions of interest (ROIs) were studied. In structural MRI, the gray matter volume (GMV) was compared in the ROIs. In the two visual tasks, the response intensity and functional connectivity (FC) of ROIs were also compared separately. Correlation analysis was performed to explore the correlations between the structural and functional parameters.ResultsIn the structural analysis, the GMV in Brodmann areas 17, 18, and 19 of the FP and NFP groups was significantly lower than that of HCs. Regarding the functional data, the response intensity in the VC of both the FP and NFP groups was significantly lower than that in HCs. The response in Brodmann areas 17, 18, and 19 obtained using the pattern stimulus was significantly lower in the NFP group than in the FP group. For the FC comparison, the FP and NFP groups exhibited significantly lower values in several pathways than the HCs, and FC in the ipsilateral V1–contralateral V1 pathway in the flash task was significantly lower in the NFP group than in the FP group. A positive correlation between response intensity and GMV was observed in Brodmann areas 17, 18, and 19 in both flash and pattern visual tasks.ConclusionMagnetic resonance imaging was an effective tool to objectively and quantitatively evaluate the visual function of patients with advanced RP. Response intensity and FC were effective parameters to distinguish FP and NFP patients. A positive correlation between response intensity and GMV was observed in the VC.

Causal Structural Covariance Network Suggesting Structural Alterations Progression in Type 2 Diabetes Patients.

Background and PurposeAccording to reports, type 2 diabetes (T2D) is a progressive disease. However, no known research has examined the progressive brain structural changes associated with T2D. The purpose of this study was to determine whether T2D patients exhibit progressive brain structural alterations and, if so, how the alterations progress.Materials and MethodsStructural magnetic resonance imaging scans were collected for 81 T2D patients and 48 sex-and age-matched healthy controls (HCs). Voxel-based morphometry (VBM) and causal structural covariance network (CaSCN) analyses were applied to investigate gray matter volume (GMV) alterations and the likely chronological processes underlying them in T2D. Two sample t-tests were performed to compare group differences, and the differences were corrected using Gaussian random field (GRF) correction (voxel-level p < 0.001, cluster-level p < 0.01).ResultsOur findings demonstrated that GMV alterations progressed in T2D patients as disease duration increased. In the early stages of the disease, the right temporal pole of T2D patients had GMV atrophy. As the diseases duration prolonged, the limbic system, cerebellum, subcortical structures, parietal cortex, frontal cortex, and occipital cortex progressively exhibited GMV alterations. The patients also exhibited a GMV alterations sequence exerting from the right temporal pole to the limbic-cerebellum-striatal-cortical network areas.ConclusionOur results indicate that the progressive GMV alterations of T2D patients manifested a limbic-cerebellum-striatal-cortical sequence. These findings may contribute to a better understanding of the progression and an improvement of current diagnosis and intervention strategies for T2D.