Most recent paper
Aberrant modular segregation of brain networks in female patients with bulimia nervosa
Int J Eat Disord. 2023 Mar 23. doi: 10.1002/eat.23939. Online ahead of print.
OBJECTIVE: Bulimia nervosa (BN) is an eating disorder associated with the dysfunction of intrinsic brain networks. However, whether the network disruptions in BN patients manifest as dysconnectivity or imbalances of network modular segregation remains unclear.
METHOD: We collected data from 41 women with BN and 41 matched healthy control (HC) women. We performed graph theory analysis based on resting-state functional magnetic resonance imaging (RS-fMRI) data; then, we computed the participation coefficient (PC) among brain modules to characterize the modular segregation for the BN and HC groups. The number of intra- and inter-modular connections was calculated to explain the PC changes. Additionally, we examined the potential associations of the measures mentioned above with clinical variables within the BN group.
RESULTS: Compared with the HC group, the BN group showed significantly decreased PC in the fronto-parietal network (FPN), cingulo-opercular network (CON), and cerebellum (Cere). Additionally, the number of intra-modular connections of the default mode network (DMN) and the number of the inter-modular connections between the DMN and CON, FPN and Cere, and CON and Cere in the BN group were lower than those in the HC group. The nodal level analysis showed that the BN group had a decreased PC of the anterior prefrontal cortex (aPFC), dorsal frontal cortex (dFC), inferior parietal lobule (IPL), thalamus, and angular gyrus. Further, these metrics were significantly correlated with clinical variables in the BN group.
DISCUSSION: These findings may provide novel insights to capture atypical topologies associated with pathophysiology mechanisms and clinical symptoms underlying BN.
PMID:36951235 | DOI:10.1002/eat.23939
Altered topological properties of functional brain networks in patients with first episode, late-life depression before and after antidepressant treatment
Front Aging Neurosci. 2023 Mar 6;15:1107320. doi: 10.3389/fnagi.2023.1107320. eCollection 2023.
OBJECTIVES: To preliminarily explore the functional activity and information integration of the brains under resting state based on graph theory in patients with first-episode, late-life depression (LLD) before and after antidepressant treatment.
METHODS: A total of 50 patients with first-episode LLD and 40 non-depressed controls (NCs) were recruited for the present research. Participants underwent the RBANS test, the 17-item Hamilton depression rating scale (HAMD-17) test, and resting-state functional MRI scans (rs-fMRI). The RBANS test consists of 12 sub-tests that contribute to a total score and index scores across the five domains: immediate memory, visuospatial/constructional, language, attention, and delayed memory. Escitalopram or sertraline was adopted for treating depression, and the dosage of the drug was adjusted by the experienced psychiatrists. Of the 50 LLD patients, 27 cases who completed 6-month follow-ups and 27 NCs matched with age, sex, and education level were included for the final statistical analysis.
RESULTS: There were significant differences in RBANS total score, immediate memory, visuospatial/constructional, language, attention, and delayed memory between LLD baseline group and NCs group (P < 0.05). Considering the global attribute indicators, the clustering coefficient of global indicators was lower in the LLD baseline group than in the NCs group, and the small-world attribute of functional brain networks existed in all three groups. The degree centrality and node efficiency of some brains were lower in the LLD baseline group than in the NCs group. After 6 months of antidepressant therapy, the scores of HAMD-17, immediate memory, language, and delayed memory in the LLD follow-up group were higher than those in the LLD baseline group. Compared with the LLD baseline group, the degree centrality and node efficiency of some brains in the cognitive control network were decreased in the LLD follow-up group.
CONCLUSIONS: The ability to integrate and divide labor of functional brain networks declines in LLD patients and linked with the depression severity. After the relief of depressive symptoms, the small-world attribute of functional brain networks in LLD patients persists. However, the information transmission efficiency and centrality of some brain regions continue to decline over time, perhaps related to their progressive cognitive impairment.
PMID:36949772 | PMC:PMC10025486 | DOI:10.3389/fnagi.2023.1107320
Frequency-Specific Alterations of Spontaneous Brain Activity in First-Episode Drug-Naïve Schizophrenia
Sichuan Da Xue Xue Bao Yi Xue Ban. 2023 Mar;54(2):281-286. doi: 10.12182/20230360103.
OBJECTIVE: To investigate frequency-specific alterations of spontaneous brain activity in first-episode drug-naïve schizophrenia (SZ) patients and the associations with clinical symptoms.
METHODS: We collected the resting-state functional MRI (rs-fMRI) data from 84 first-episode drug-naïve SZ patients and 94 healthy controls (HCs) and calculated the amplitude of low-frequency fluctuations (ALFF) and regional homogeneity (ReHo) of four frequency bands, including slow-2, slow-3, slow-4, and slow-5. Two-sample t-tests were used to evaluate the intergroup differences in ALFF and ReHo, while partial correlation analyses were conducted to explore the associations between abnormal ALFF and ReHo and the severity of clinical symptoms in the SZ group.
RESULTS: Compared with HCs, the SZ group showed reduced ALFF in superior cerebellum and cerebellar vermis across slow-2, slow-3, and slow-4 bands, while increased ALFF was found in left superior temporal gyrus, middle temporal gyrus, and superior temporal pole at slow-4 band. Moreover, reduced ReHo was observed in the right precentral and postcentral gyri at slow-3 band in the SZ group. Additionally, the ALFF of left superior temporal gyrus, middle temporal gyrus, and superior temporal pole in slow-4 band showed a trend of positive correlation with the excited factor score of Positive and Negative Syndrome Scale (PANSS) in the SZ group.
CONCLUSION: Our results suggest that local alterations of spontaneous brain activity were frequency-specific in first-episode drug-naïve SZ patients.
PMID:36949686 | DOI:10.12182/20230360103
PTSD and comorbid MDD is associated with activation of the right frontoparietal network
Psychiatry Res Neuroimaging. 2023 Mar 17;331:111630. doi: 10.1016/j.pscychresns.2023.111630. Online ahead of print.
There is growing evidence of abnormalities in intrinsic functional connectivity (FC) in posttraumatic stress disorder (PTSD) and major depressive disorder (MDD). However, there has been less work on the commonly occurring co-presentation of PTSD and MDD. Characterising intrinsic FC abnormalities in this clinical population is important for understanding how they may contribute towards impairments underpinned by different networks. Participants were mothers enroled in the Drakenstein Child Health Study from Western Cape, South Africa. Mothers between 18 and 50 years of age were recruited and divided into 4 groups: PTSD, MDD, PTSD with MDD, and healthy controls. Participants underwent resting-state fMRI at the 18-month postpartum time point. Functional connectivity within and between higher order cognitive control networks, including the salience, dorsal attention, frontoparietal, and default mode networks were compared across the 4 groups. PTSD with comorbid MDD was associated with greater intrinsic FC within the R FPAR, relative to controls and the mono-diagnostic groups. Intrinsic FC differences were observed within the default mode network for the MDD group. No group differences in connectivity between networks were observed. Differential intrinsic connectivity in participants with comorbidity are consistent with evidence that such individuals have more severe illness and require more robust intervention.
PMID:36947943 | DOI:10.1016/j.pscychresns.2023.111630
Active Inference, Epistemic Value, and Uncertainty in Conceptual Disorganization in First-Episode Schizophrenia
Schizophr Bull. 2023 Mar 22;49(Supplement_2):S115-S124. doi: 10.1093/schbul/sbac125.
BACKGROUND AND HYPOTHESIS: Active inference has become an influential concept in psychopathology. We apply active inference to investigate conceptual disorganization in first-episode schizophrenia. We conceptualize speech production as a decision-making process affected by the latent "conceptual organization"-as a special case of uncertainty about the causes of sensory information. Uncertainty is both minimized via speech production-in which function words index conceptual organization in terms of analytic thinking-and tracked by a domain-general salience network. We hypothesize that analytic thinking depends on conceptual organization. Therefore, conceptual disorganization in schizophrenia would be both indexed by low conceptual organization and reflected in the effective connectivity within the salience network.
STUDY DESIGN: With 1-minute speech samples from a picture description task and resting state fMRI from 30 patients and 30 healthy subjects, we employed dynamic causal and probabilistic graphical models to investigate if the effective connectivity of the salience network underwrites conceptual organization.
STUDY RESULTS: Low analytic thinking scores index low conceptual organization which affects diagnostic status. The influence of the anterior insula on the anterior cingulate cortex and the self-inhibition within the anterior cingulate cortex are elevated given low conceptual organization (ie, conceptual disorganization).
CONCLUSIONS: Conceptual organization, a construct that explains formal thought disorder, can be modeled in an active inference framework and studied in relation to putative neural substrates of disrupted language in schizophrenia. This provides a critical advance to move away from rating-scale scores to deeper constructs in the pursuit of the pathophysiology of formal thought disorder.
PMID:36946528 | DOI:10.1093/schbul/sbac125
Creative thinking and brain network development in schoolchildren
Dev Sci. 2023 Mar 21:e13389. doi: 10.1111/desc.13389. Online ahead of print.
Fostering creative minds has always been a premise to ensure adaptation to new challenges of human civilization. While some alternative educational settings (i.e., Montessori) were shown to nurture creative skills, it is unknown how they impact underlying brain mechanisms across the school years. This study assessed creative thinking and resting-state functional connectivity via fMRI in 75 children (4-18 y.o.) enrolled either in Montessori or traditional schools. We found that pedagogy significantly influenced creative performance and underlying brain networks. Replicating past work, Montessori-schooled children showed higher scores on creative thinking tests. Using static functional connectivity analysis, we found that Montessori-schooled children showed decreased within-network functional connectivity of the salience network. Moreover, using dynamic functional connectivity, we found that traditionally-schooled children spent more time in a brain state characterized by high intra-default mode network connectivity. These findings suggest that pedagogy may influence brain networks relevant to creative thinking-particularly the default and salience networks. Further research is needed, like a longitudinal study, to verify these results given the implications for educational practitioners. RESEARCH HIGHLIGHTS: Most executive jobs are prospected to be obsolete within several decades, so creative skills are seen as essential for the near future. School experience has been shown to play a role in creativity development, however, the underlying brain mechanisms remained under-investigated yet. Seventy-five 4-18 years-old children, from Montessori or traditional schools, performed a creativity task at the behavioral level, and a 6-min resting-state MR scan. We uniquely report preliminary evidence for the impact of pedagogy on functional brain networks.
PMID:36942648 | DOI:10.1111/desc.13389
Altered functional connectivity of the default mode and frontal control networks in patients with insomnia
CNS Neurosci Ther. 2023 Mar 21. doi: 10.1111/cns.14183. Online ahead of print.
AIMS: The purpose of this study was to investigate the association between spontaneous regional activity and brain functional connectivity, which maybe can distinguish insomnia while being responsive to repetitive transcranial magnetic stimulation (rTMS) treatment effects in insomnia patients.
METHODS: Using resting-state functional magnetic resonance imaging data from 38 chronic insomnia patients and 36 healthy volunteers, we compared the amplitude of low-frequency fluctuations (ALFF) between the two groups. Of all the patients with insomnia, 20 received rTMS for 4 weeks, while 18 patients received a 4-week pseudo-stimulation intervention. Seed-based resting-state functional connectivity (RSFC) analysis was conducted from regions with significantly different ALFF values, and the association between RSFC value and Pittsburgh Sleep Quality Index score was determined.
RESULTS: Our results revealed that insomnia patients presented a significantly higher ALFF value in the posterior cingulate cortex (PCC), whereas a significantly lower ALFF value was observed in the superior parietal lobule (SPL). Moreover, significantly reduced RSFC was detected from both PCC to prefrontal cortex connections, as well as from left SPL to frontal pole connections. In addition, RSFC from frontal pole to left SPL negatively predicted sleep quality (PSQI) and treatment response in patients' group.
CONCLUSION: Our findings suggest that disrupted frontoparietal network connectivity may be a biomarker for insomnia in middle-aged adults, reinforcing the potential of rTMS targeting the frontal lobes. Monitoring pretreatment RSFC could offer greater insight into how rTMS treatments are responded to by insomniacs.
PMID:36942498 | DOI:10.1111/cns.14183
Spontaneous changes in brain network centrality in patients with pathological myopia: A voxel-wise degree centrality analysis
CNS Neurosci Ther. 2023 Mar 21. doi: 10.1111/cns.14168. Online ahead of print.
BACKGROUND: Myopia has become a worldwide problem that endangers public health and adds a serious socioeconomic burden. Current research has focused on the pathogenesis and manifestations of pathological myopia (PM). However, few studies have been conducted on the spontaneous activity of the patient's brain.
PURPOSE: To study the potential brain network activity in patients with PM by the degree centrality (DC) method.
MATERIALS AND METHODS: This experiment included 15 PM patients and 15 healthy controls (HCs). Every participant experienced a resting-state functional magnetic resonance imaging (rs-fMRI) scan. Receiver operating characteristic (ROC) curve analysis was used to distinguish between PM patients and HCs. Correlation analysis was used to explore the relationships between mean DC values and clinical performance in different brain regions.
RESULTS: It showed that patients with PM had lower DC values in the right fusiform gyrus (FR) and right cingulate (CAR). The ROC curve was used to indicate the accuracy of the correlation. It showed that in PM group, left best corrected visual acuity (BCVA-L) and right best corrected visual acuity (BCVA-R) were negatively correlated with the DC value of FR.
CONCLUSION: The occurrence of PM is mainly related to the abnormal activity of the fusiform and cingulum. DC value might be used as a biological marker of abnormal brain activity in PM patients.
PMID:36942490 | DOI:10.1111/cns.14168
Functional magnetic resonance imaging of headache: Issues, best-practices, and new directions, a narrative review
Headache. 2023 Mar;63(3):309-321. doi: 10.1111/head.14487.
OBJECTIVE: To ensure readers are informed consumers of functional magnetic resonance imaging (fMRI) research in headache, to outline ongoing challenges in this area of research, and to describe potential considerations when asked to collaborate on fMRI research in headache, as well as to suggest future directions for improvement in the field.
BACKGROUND: Functional MRI has played a key role in understanding headache pathophysiology, and mapping networks involved with headache-related brain activity have the potential to identify intervention targets. Some investigators have also begun to explore its use for diagnosis.
METHODS/RESULTS: The manuscript is a narrative review of the current best practices in fMRI in headache research, including guidelines on transparency and reproducibility. It also contains an outline of the fundamentals of MRI theory, task-related study design, resting-state functional connectivity, relevant statistics and power analysis, image preprocessing, and other considerations essential to the field.
CONCLUSION: Best practices to increase reproducibility include methods transparency, eliminating error, using a priori hypotheses and power calculations, using standardized instruments and diagnostic criteria, and developing large-scale, publicly available datasets.
PMID:36942411 | DOI:10.1111/head.14487
Electrocorticographic Activation Patterns of Electroencephalographic Microstates
Brain Topogr. 2023 Mar 20. doi: 10.1007/s10548-023-00952-1. Online ahead of print.
Electroencephalography (EEG) microstates are short successive periods of stable scalp field potentials representing spontaneous activation of brain resting-state networks. EEG microstates are assumed to mediate local activity patterns. To test this hypothesis, we correlated momentary global EEG microstate dynamics with the local temporo-spectral evolution of electrocorticography (ECoG) and stereotactic EEG (SEEG) depth electrode recordings. We hypothesized that these correlations involve the gamma band. We also hypothesized that the anatomical locations of these correlations would converge with those of previous studies using either combined functional magnetic resonance imaging (fMRI)-EEG or EEG source localization. We analyzed resting-state data (5 min) of simultaneous noninvasive scalp EEG and invasive ECoG and SEEG recordings of two participants. Data were recorded during the presurgical evaluation of pharmacoresistant epilepsy using subdural and intracranial electrodes. After standard preprocessing, we fitted a set of normative microstate template maps to the scalp EEG data. Using covariance mapping with EEG microstate timelines and ECoG/SEEG temporo-spectral evolutions as inputs, we identified systematic changes in the activation of ECoG/SEEG local field potentials in different frequency bands (theta, alpha, beta, and high-gamma) based on the presence of particular microstate classes. We found significant covariation of ECoG/SEEG spectral amplitudes with microstate timelines in all four frequency bands (p = 0.001, permutation test). The covariance patterns of the ECoG/SEEG electrodes during the different microstates of both participants were similar. To our knowledge, this is the first study to demonstrate distinct activation/deactivation patterns of frequency-domain ECoG local field potentials associated with simultaneous EEG microstates.
PMID:36939988 | DOI:10.1007/s10548-023-00952-1
Correction to: Brain function in children with obstructive sleep apnea: a resting-state fMRI study
Sleep. 2023 Mar 20:zsac299. doi: 10.1093/sleep/zsac299. Online ahead of print.
PMID:36938602 | DOI:10.1093/sleep/zsac299
Incorporating multi-stage diagnosis status to mine associations between genetic risk variants and the multi-modality phenotype network in major depressive disorder
Front Psychiatry. 2023 Mar 2;14:1139451. doi: 10.3389/fpsyt.2023.1139451. eCollection 2023.
Depression (major depressive disorder, MDD) is a common and serious medical illness. Globally, it is estimated that 5% of adults suffer from depression. Recently, imaging genetics receives growing attention and become a powerful strategy for discoverying the associations between genetic variants (e.g., single-nucleotide polymorphisms, SNPs) and multi-modality brain imaging data. However, most of the existing MDD imaging genetic research studies conducted by clinicians usually utilize simple statistical analysis methods and only consider single-modality brain imaging, which are limited in the deeper discovery of the mechanistic understanding of MDD. It is therefore imperative to utilize a powerful and efficient technology to fully explore associations between genetic variants and multi-modality brain imaging. In this study, we developed a novel imaging genetic association framework to mine the multi-modality phenotype network between genetic risk variants and multi-stage diagnosis status. Specifically, the multi-modality phenotype network consists of voxel node features and connectivity edge features from structural magnetic resonance imaging (sMRI) and resting-state functional magnetic resonance imaging (rs-fMRI). Thereafter, an association model based on multi-task learning strategy was adopted to fully explore the relationship between the MDD risk SNP and the multi-modality phenotype network. The multi-stage diagnosis status was introduced to further mine the relation among the multiple modalities of different subjects. A multi-modality brain imaging data and genotype data were collected by us from two hospitals. The experimental results not only demonstrate the effectiveness of our proposed method but also identify some consistent and stable brain regions of interest (ROIs) biomarkers from the node and edge features of multi-modality phenotype network. Moreover, four new and potential risk SNPs associated with MDD were discovered.
PMID:36937715 | PMC:PMC10017727 | DOI:10.3389/fpsyt.2023.1139451
Resting-state abnormalities in functional connectivity of the default mode network in migraine: A meta-analysis
Front Neurosci. 2023 Mar 1;17:1136790. doi: 10.3389/fnins.2023.1136790. eCollection 2023.
Migraine-a disabling neurological disorder, imposes a tremendous burden on societies. To reduce the economic and health toll of the disease, insight into its pathophysiological mechanism is key to improving treatment and prevention. Resting-state functional magnetic resonance imaging (rs-fMRI) studies suggest abnormal functional connectivity (FC) within the default mode network (DMN) in migraine patients. This implies that DMN connectivity change may represent a biomarker for migraine. However, the FC abnormalities appear inconsistent which hinders our understanding of the potential neuropathology. Therefore, we performed a meta-analysis of the FC within the DMN in migraine patients in the resting state to identify the common FC abnormalities. With efficient search and selection strategies, nine studies (published before July, 2022) were retrieved, containing 204 migraine patients and 199 healthy subjects. We meta-analyzed the data using the Anisotropic Effect Size version of Signed Differential Mapping (AES-SDM) method. Compared with healthy subjects, migraine patients showed increased connectivity in the right calcarine gyrus, left inferior occipital gyrus, left postcentral gyrus, right cerebellum, right parahippocampal gyrus, and right posterior cingulate gyrus, while decreased connectivity in the right postcentral gyrus, left superior frontal gyrus, right superior occipital gyrus, right orbital inferior frontal gyrus, left middle occipital gyrus, left middle frontal gyrus and left inferior frontal gyrus. These results provide a new perspective for the study of the pathophysiology of migraine and facilitate a more targeted treatment of migraine in the future.
PMID:36937687 | PMC:PMC10014826 | DOI:10.3389/fnins.2023.1136790
The Effects of Propofol Anaesthesia on Molecular-enriched Networks During Resting-state and Naturalistic Listening
Neuroimage. 2023 Mar 17:120018. doi: 10.1016/j.neuroimage.2023.120018. Online ahead of print.
Placing a patient in a state of anaesthesia is crucial for modern surgical practice. However, the mechanisms by which anaesthetic drugs, such as propofol, impart their effects on consciousness remain poorly understood. Propofol potentiates GABAergic transmission, which purportedly has direct actions on cortex as well as indirect actions via ascending neuromodulatory systems. Functional imaging studies to date have been limited in their ability to unravel how these effects on neurotransmission impact the system-level dynamics of the brain. Here, we leveraged advances in multi-modal imaging, Receptor-Enriched Analysis of functional Connectivity by Targets (REACT), to investigate how different levels of propofol-induced sedation alter neurotransmission-related functional connectivity (FC), both at rest and when individuals are exposed to naturalistic auditory listening. Propofol increased GABA-A- and noradrenaline transporter-enriched FC within occipital and somatosensory regions respectively. Additionally, during auditory stimulation, the network related to the dopamine transporter showed reduced FC within bilateral regions of temporal and mid/posterior cingulate cortices, with the right temporal cluster showing an interaction between auditory stimulation and level of consciousness. In bringing together these micro- and macro-scale systems, we provide support for both direct GABAergic and indirect noradrenergic and dopaminergic-related network changes under propofol sedation. Further, we delineate a cognition-related reconfiguration of the dopaminergic network, highlighting the utility of REACT to explore the molecular substrates of consciousness and cognition.
PMID:36935083 | DOI:10.1016/j.neuroimage.2023.120018
Abnormal thalamic functional connectivity correlates with cardiorespiratory fitness and physical activity in progressive multiple sclerosis
J Neurol. 2023 Mar 18. doi: 10.1007/s00415-023-11664-8. Online ahead of print.
BACKGROUND: Altered thalamic volumes and resting state (RS) functional connectivity (FC) might be associated with physical activity (PA) and cardiorespiratory fitness (CRF) in people with progressive multiple sclerosis (PMS).
OBJECTIVES: To assess thalamic structural and functional alterations and investigate their correlations with PA/CRF levels in people with PMS.
METHODS: Seven-day accelerometry and cardiopulmonary exercise testing were used to assess PA/CRF levels in 91 persons with PMS. They underwent 3.0 T structural and RS fMRI acquisition with 37 age/sex-matched healthy controls (HC). Between-group comparisons of MRI measures and their correlations with PA/CRF variables were assessed.
RESULTS: PMS people had lower volumes compared to HC (all p < 0.001). At corrected threshold, PMS showed decreased intra- and inter-thalamic RS FC, and increased RS FC between the thalamus and the hippocampus, bilaterally. At uncorrected threshold, decreased thalamic RS FC with caudate nucleus, cerebellum and anterior cingulate cortex (ACC), as well as increased thalamic RS FC with occipital regions, were also detected. Lower CRF, measured as peak oxygen consumption (VO2peak), correlated with lower white matter volume (r = 0.31, p = 0.03). Moreover, lower levels of light PA correlated with increased thalamic RS FC with the right hippocampus (r = - 0.3, p = 0.05).
DISCUSSION: People with PMS showed widespread brain atrophy, as well as pronounced intra-thalamic and thalamo-hippocampal RS FC abnormalities. White matter atrophy correlated with CRF, while increased thalamo-hippocampal RS FC was associated to worse PA levels. Thalamic RS FC might be used to monitor physical impairment and efficacy of rehabilitative and disease-modifying treatments in future studies.
PMID:36933030 | DOI:10.1007/s00415-023-11664-8
Altered Functional Connectivity Strength in Distinct Brain Networks of Children With Early-Onset Schizophrenia
J Magn Reson Imaging. 2023 Mar 17. doi: 10.1002/jmri.28682. Online ahead of print.
BACKGROUND: Schizophrenia is regarded as a brain network or connectome disorder that is associated with neurodevelopment. Children with early-onset schizophrenia (EOS) provide an opportunity to evaluate the neuropathology of schizophrenia at a very early stage without potential confounding factors. But dysfunction in brain networks of schizophrenia is inconsistent.
PURPOSE: To identify abnormal functional connectivity (FC) in EOS patients and relationships with clinical symptoms, we aimed to reveal neuroimaging phenotypes of EOS.
STUDY TYPE: Prospective, cross-sectional.
POPULATION: Twenty-six female/22 male patients (age:14.3 ± 3.45 years) with first-episode EOS, 27 female/22 male age- and gender-matched healthy controls (HC) (age:14.1 ± 4.32).
FIELD STRENGTH/SEQUENCE: 3-T, resting-state (rs) gradient-echo echo-planar imaging and three-dimensional magnetization-prepared rapid gradient-echo imaging.
ASSESSMENT: Intelligence quotient (IQ) was measured by the Wechsler Intelligence Scale-Fourth edition for Children (WISC-IV). The clinical symptoms were evaluated by the Positive and Negative Syndrome Scale (PANSS). FC strength (FCS) from rs functional MRI (rsfMRI) was used to investigate functional integrity of global brain regions. In addition, associations between regionally altered FCS and clinical symptoms in EOS patients were examined.
STATISTICAL TESTS: Two-sample t-test controlling for sample size, diagnostic method, brain volume algorithm, and age of the subjects, Bonferroni correction, Pearson's correlation analysis. A P-value <0.05 with a minimum cluster size of 50 voxels was considered statistically significant.
RESULTS: Compared with HC, EOS patients had significantly lower total IQ scores (IQ:91.5 ± 16.1), increased FCS in the bilateral precuneus, left dorsolateral prefrontal cortex, left thalamus, and left parahippocampus (paraHIP), and decreased FCS in the right cerebellum posterior lobe and right superior temporal gyrus. The PANSS total score of EOS patients (PANSS total score:74.30 ± 7.23) was found to be positively correlated to FCS in the left paraHIP (r = 0.45).
DATA CONCLUSION: Our study revealed that disrupted FC of brain hubs illustrate multiple abnormalities in brain networks in EOS patients.
EVIDENCE LEVEL: 1 TECHNICAL EFFICACY STAGE: 2.
PMID:36932678 | DOI:10.1002/jmri.28682
Connectivity profile of middle inferior parietal cortex confirms the hypothesis about modulating cortical areas
Neuroscience. 2023 Mar 15:S0306-4522(23)00126-4. doi: 10.1016/j.neuroscience.2023.03.010. Online ahead of print.
According to the correlated transmitter-receptor based structure of the inferior parietal cortex (IPC), this brain area is divided into three clusters, namely, the caudal, the middle and the rostral. Nevertheless, in associating different cognitive functions to the IPC, previous studies considered this part of the cortex as a whole and thus inconsistent results have been reported. Using multiband EPI, we investigated the connectivity profile of the middle IPC while forty-five participants performed a task requiring cognitive control. The middle IPC demonstrated functional associations which do not have similarities to a contributing part in the frontoparietal network, in processing cognitive control. At the same time, this cortical area showed negative functional connectivity with both the precuneus cortex, which is resting- state related, and brain areas related to general cognitive functions. That is, the functions of the middle IPC are not accommodated by the traditional categorization of different brain areas i.e. resting state-related or task-related networks and this advanced our hypothesis about modulating cortical areas. Such brain areas are characterized by their negative functional connectivity with parts of the cortex involved in task performance, proportional to the difficulty of the task; yet, their functional associations are inconsistent with the resting state-related cortical areas.
PMID:36931424 | DOI:10.1016/j.neuroscience.2023.03.010
Characterization of regional differences in resting-state fMRI with a data-driven network model of brain dynamics
Sci Adv. 2023 Mar 15;9(11):eabq7547. doi: 10.1126/sciadv.abq7547. Epub 2023 Mar 17.
Model-based data analysis of whole-brain dynamics links the observed data to model parameters in a network of neural masses. Recently, studies focused on the role of regional variance of model parameters. Such analyses however necessarily depend on the properties of preselected neural mass model. We introduce a method to infer from the functional data both the neural mass model representing the regional dynamics and the region- and subject-specific parameters while respecting the known network structure. We apply the method to human resting-state fMRI. We find that the underlying dynamics can be described as noisy fluctuations around a single fixed point. The method reliably discovers three regional parameters with clear and distinct role in the dynamics, one of which is strongly correlated with the first principal component of the gene expression spatial map. The present approach opens a novel way to the analysis of resting-state fMRI with possible applications for understanding the brain dynamics during aging or neurodegeneration.
PMID:36930710 | DOI:10.1126/sciadv.abq7547
A spectral sampling algorithm in dynamic causal modelling for resting-state fMRI
Hum Brain Mapp. 2023 Mar 16. doi: 10.1002/hbm.26256. Online ahead of print.
Resting-state functional magnetic resonance imaging (rs-fMRI) is widely utilized to study the directed influences among neural populations which were called effective connectivity (EC), and the spectral dynamic causal modelling (spDCM) is the state-of-the-art framework to identify them. However, spDCM used variational Laplace to approximate the posterior density by maximizing the free energy, which might underestimate the variability of posterior density and get locked to the local minima. A spectral sampling algorithm (SS-DCM) was proposed to improve the estimation accuracy of the dynamic causal model for rs-fMRI. In SS-DCM, a naïve Bayesian model was constructed in the spectral domain, which described the probabilistic relationship between the sampled parameters and cross spectra of the observed blood oxygen level-dependent signals, and the parameters were sampled using randomly walked Markov Chain Monto Carlo scheme. The root mean square errors of the estimation of EC and hemodynamic parameters of SS-DCM, spDCM and generalized filter scheme were compared in the synthetic data, and SS-DCM was the most accurate and stable. A comparative evaluation using empirical rs-fMRI data was performed to study the EC pattern of the default mode network and compare the accuracy of classification between typically developed subjects and inattentive attention deficit and hyperactivity disorder patients. The results showed high consistency of positivity and negativity of EC between spDCM and SS-DCM, and SS-DCM also provided higher classification accuracy. It is highlighted that SS-DCM improves the accuracy of the estimation of EC and provides accurate information of discrepancies between diseased and healthy subjects using rs-fMRI.
PMID:36929686 | DOI:10.1002/hbm.26256
Using in silico perturbational approach to identify critical areas in schizophrenia
Cereb Cortex. 2023 Mar 16:bhad067. doi: 10.1093/cercor/bhad067. Online ahead of print.
Schizophrenia is a debilitating neuropsychiatric disorder whose underlying correlates remain unclear despite decades of neuroimaging investigation. One contentious topic concerns the role of global signal (GS) fluctuations and how they affect more focal functional changes. Moreover, it has been difficult to pinpoint causal mechanisms of circuit disruption. Here, we analyzed resting-state fMRI data from 47 schizophrenia patients and 118 age-matched healthy controls and used dynamical analyses to investigate how global fluctuations and other functional metastable states are affected by this disorder. We found that brain dynamics in the schizophrenia group were characterized by an increased probability of globally coherent states and reduced recurrence of a substate dominated by coupled activity in the default mode and limbic networks. We then used the in silico perturbation of a whole-brain model to identify critical areas involved in the disease. Perturbing a set of temporo-parietal sensory and associative areas in a model of the healthy brain reproduced global pathological dynamics. Healthy brain dynamics were instead restored by perturbing a set of medial fronto-temporal and cingulate regions in the model of pathology. These results highlight the relevance of GS alterations in schizophrenia and identify a set of vulnerable areas involved in determining a shift in brain state.
PMID:36929009 | DOI:10.1093/cercor/bhad067