Most recent paper

Brain-wide neural co-activations in resting human

Tue, 07/12/2022 - 18:00

Neuroimage. 2022 Jul 9:119461. doi: 10.1016/j.neuroimage.2022.119461. Online ahead of print.

ABSTRACT

Spontaneous neural activity in human as assessed with resting-state functional magnetic resonance imaging (fMRI) exhibits brain-wide coordinated patterns in the frequency of <0.1 Hz. However, understanding of fast brain-wide networks at the timescales of neuronal events (milliseconds to sub-seconds) and their spatial, spectral, and transitional characteristics remain limited due to the temporal constraints of hemodynamic signals. With milli-second resolution and whole-head coverage, scalp-based electroencephalography (EEG) provides a unique window into brain-wide networks with neuronal-timescale dynamics, shedding light on the organizing principles of brain functions. Using the state-of-the-art signal processing techniques, we reconstructed cortical neural tomography from resting-state EEG and extracted component-based co-activation patterns (cCAPs). These cCAPs revealed brain-wide intrinsic networks and their dynamics, indicating the configuration/reconfiguration of resting human brains into recurring and transitional functional states, which are featured with the prominent spatial phenomena of global patterns and anti-state pairs of co-(de)activations. Rich oscillational structures across a wide frequency band (i.e., 0.6 Hz, 5 Hz, and 10 Hz) were embedded in the nonstationary dynamics of these functional states. We further identified a superstructure that regulated between-state immediate and long-range transitions involving the entire set of identified cCAPs and governed a significant aspect of brain-wide network dynamics. These findings demonstrated how resting-state EEG data can be functionally decomposed using cCAPs to reveal rich dynamic structures of brain-wide human neural activations.

PMID:35820583 | DOI:10.1016/j.neuroimage.2022.119461

Cerebellum-cingulo-opercular network connectivity strengthens in adolescence and supports attention efficiency only in childhood

Tue, 07/12/2022 - 18:00

Dev Cogn Neurosci. 2022 Jun 25;56:101129. doi: 10.1016/j.dcn.2022.101129. Online ahead of print.

ABSTRACT

Posterior cerebellar lobules are active during executive function (EF) tasks and are functionally connected to EF-associated cortical networks such as the fronto-parietal network (FPN) and cingulo-opercular network (CON). Despite evidence that EF and cerebello-cortical connectivity develop on a similar time scale, developmental relationships between EFs and cerebello-cortical connectivity have not been directly investigated. We therefore examined relationships between cerebello-cortical connectivity and EF performance in a typically developing sample ages 8 - 21. Resting-state functional connectivity between posterior cerebellum and FPN (middle frontal gyrus, posterior parietal lobules)/CON (anterior cingulate, insula) was computed using independent components analysis. Using conditional process models, we tested the hypothesis that cerebellum - PFC connectivity would mediate the relationship between FPN/CON and EF, and that cerebello-cortical connectivity, and connectivity - EF relationships, would become stronger with increasing age. Cerebellum - CON connectivity strengthened with age, but a relationship between cerebellum - anterior cingulate cortex (ACC) connectivity and attention efficiency was significant only in younger children. Results suggest that during childhood, the posterior cerebellum and ACC may support sustained and executive attention, though age has a stronger effect on EF. These findings may help to guide further studies of executive dysfunction in neurodevelopmental disorders.

PMID:35820341 | DOI:10.1016/j.dcn.2022.101129

Communities and Cliques in Functional Brain Network Using Multiscale Consensus Approach

Tue, 07/12/2022 - 18:00

IEEE Trans Neural Syst Rehabil Eng. 2022 Jul 12;PP. doi: 10.1109/TNSRE.2022.3190390. Online ahead of print.

ABSTRACT

The modular organization of the functional brain connectome implies its functional segregation. Correlation matrices extracted from fMRI data are used as adjacency matrices of the connectome, i.e., the functional connectivity network (FCN). The modular organization of FCN is widely solved using node-community detection methods, albeit with a requirement of edge filtering, mostly. However, network sparsification potentially leads to the loss of correlation information. With no ideal threshold values for edge filtering in literature, there is growing interest in finding communities in the complete weighted network. To address this requirement, we propose the use of exploratory factor analysis (EFA), thus, exploiting the semantics of the correlation matrix. In our recent work on using EFA for FCN analysis, we have proposed a novel consensus-based algorithm using a multiscale approach, where the number of factors nF is treated as the scale. The consensus procedure is employed for transforming the network before performing community detection. Here, we propose a novel extension to our multiscale EFA for finding relevant cliques. We use an ensemble of experiments and extensive quantitative analysis of its outcomes to identify the optimal set of scales for efficient node-partitioning. We perform case studies of datasets of FCN of the human brain at resting state, with different sizes and parcellation atlases (AAL, Schaefer). Our results of consensus communities and cliques correspond to relevant brain activity in its resting state, thus showing the effectiveness of consensus-based multiscale EFA.

PMID:35820016 | DOI:10.1109/TNSRE.2022.3190390

The cerebellum is involved in motor improvements after repetitive transcranial magnetic stimulation in Parkinson's disease patients

Mon, 07/11/2022 - 18:00

Neuroscience. 2022 Jul 8:S0306-4522(22)00347-5. doi: 10.1016/j.neuroscience.2022.07.004. Online ahead of print.

ABSTRACT

Accumulating evidence indicates that repetitive transcranial magnetic stimulation (rTMS) ameliorates motor symptoms in patients with Parkinson's disease (PD); however, patients' responses to rTMS are different. Here, we aimed to explore neural activity changes in patients with PD exhibiting different responses to high-frequency rTMS treatments using functional magnetic resonance imaging (fMRI). We treated 24 patients with PD using 10-session rTMS (10 Hz) over the supplementary motor area (SMA) for 10 days. Resting-state functional magnetic resonance imaging (rs-fMRI), the Unified Parkinson's Disease Rating Scale Part III (UPDRS-III) and other neuropsychological scales were performed at the baseline and endpoint of rTMS treatment. The changes in the fractional amplitude of low-frequency fluctuation (fALFF) were calculated. Significant improvements were observed in motor symptoms, especially in the sub-symptoms of bradykinesia. All the participants were subsequently stratified into responders and non-responders according to the UPDRS-III reduction. We identified increased fALFF values in the left Crus II of the cerebellar hemisphere and bilateral thalamus as responsive signs to rTMS. Furthermore, the motor response to rTMS over the SMA, measured by the reduction in UPDRS-III and bradykinesia scores, was positively associated with increased fALFF values in the left Crus2 of cerebellar hemisphere, left lobule VIIB of cerebellar hemisphere, right lobule VI of the cerebellar hemisphere, and the right postcentral gyrus. These findings provide evidence for the involvement of cerebellar activity in the motor response to rTMS treatment.

PMID:35817220 | DOI:10.1016/j.neuroscience.2022.07.004

Altered Regional Homogeneity in Patients With Congenital Blindness: A Resting-State Functional Magnetic Resonance Imaging Study

Mon, 07/11/2022 - 18:00

Front Psychiatry. 2022 Jun 22;13:925412. doi: 10.3389/fpsyt.2022.925412. eCollection 2022.

ABSTRACT

In patients with congenital blindness (CB), the lack of any visual experience may affect brain development resulting in functional, structural, or even psychological changes. Few studies to date have addressed or focused on the synchronicity of regional brain activity in patients with CB. Our study aimed to investigate regional brain activity in patients with CB in a resting state and try to explain the possible causes and effects of any anomalies. Twenty-three CB patients and 23 healthy control (HC) volunteers agreed to undergo resting state functional magnetic resonance imaging (fMRI) scans. After the fMRI data were preprocessed, regional homogeneity (ReHo) analysis was conducted to assess the differences in brain activity synchronicity between the two groups. Receiver operating characteristic (ROC) curve analysis was used to explore whether the brain areas with statistically significant ReHo differences have diagnostic and identification values for CB. All CB patients were also required to complete the Hospital Anxiety and Depression Scale (HADS) to evaluate their anxiety and depression levels. The results showed that in CB patients mean ReHo values were significantly lower than in HCs in the right orbital part of the middle frontal gyrus (MFGorb), bilateral middle occipital gyrus (MOG), and the right dorsolateral superior frontal gyrus (SFGdl), but significantly higher in the left paracentral lobule (PCL), right insula and bilateral thalamus. The ReHo value of MFGorb showed a negative linear correlation with both the anxiety score and the depression score of the HADS. ROC curve analysis revealed that the mean ReHo values which differed significantly between the groups have excellent diagnostic accuracy for CB (especially in the left PCL and right SFGdl regions). Patients with CB show abnormalities of ReHo values in several specific brain regions, suggesting potential regional structural changes, functional reorganization, or even psychological effects in these patients. FMRI ReHo analysis may find use as an objective method to confirm CB for medical or legal purposes.

PMID:35815017 | PMC:PMC9256957 | DOI:10.3389/fpsyt.2022.925412

Abnormal Functional Connectivity Between Cerebral Hemispheres in Patients With High Myopia: A Resting FMRI Study Based on Voxel-Mirrored Homotopic Connectivity

Mon, 07/11/2022 - 18:00

Front Hum Neurosci. 2022 Jun 23;16:910846. doi: 10.3389/fnhum.2022.910846. eCollection 2022.

ABSTRACT

PURPOSE: To study the changes in functional connections between the left and right hemispheres of patients with high myopia (HM) and healthy controls (HCs) by resting functional magnetic resonance imaging (fMRI) based on voxel-mirrored homotopic connectivity (VMHC). To study the changes in resting-state functional connectivity (rsFC) between the left and right hemispheres of patients with HM and healthy controls (HCS) at rest by using resting functional magnetic resonance imaging (fMRI) based on voxel-mirror homotopy connectivity (VMHC).

PATIENTS AND METHODS: A total of 89 patients with HM (41 men and 48 women) and 59 HCs (24 men and 35 women) were collected and matched according to gender, age, and education level. The VMHC method was used to evaluate the changes in rsFC between cerebral hemispheres, and a correlation analysis was carried out to understand the differences in brain functional activities between the patients with HM and the HCs.

RESULTS: Compared with the HCs, the VMHC values of the putamen and fusiform in the HM group were significantly lower (voxel-level p < 0.01, Gaussian random field correction cluster level p < 0.05).

CONCLUSION: This study preliminarily confirmed the destruction of interhemispheric functional connection in some brain regions of the patients with HM and provided effective information for clarifying the neural mechanism of patients with HM.

PMID:35814958 | PMC:PMC9259881 | DOI:10.3389/fnhum.2022.910846

Aberrant Modulations of Neurocognitive Network Dynamics in Migraine Comorbid With Tinnitus

Mon, 07/11/2022 - 18:00

Front Aging Neurosci. 2022 Jun 22;14:913191. doi: 10.3389/fnagi.2022.913191. eCollection 2022.

ABSTRACT

PURPOSE: The possible relationship between migraine and tinnitus still remains elusive although migraine is often accompanied by chronic tinnitus. Several neuroimaging studies have reinforced the cognitive network abnormality in migraine and probably as well as tinnitus. The present work aims to investigate the dynamic neurocognitive network alterations of migraine comorbid with tinnitus.

MATERIALS AND METHODS: Participants included migraine patients (n = 32), tinnitus patients (n = 20), migraine with tinnitus (n = 27), and healthy controls (n = 47), matched for age and gender. Resting-state functional magnetic resonance imaging (rs-fMRI) with independent component analysis (ICA), sliding window cross-correlation, and clustering state analysis was used to detect the dynamic functional network connectivity (dFNC) of each group. Correlation analyses illustrated the association between clinical symptoms and abnormal dFNC in migraine as well as tinnitus.

RESULTS: Compared with healthy controls, migraine patients exhibited decreased cerebellar network and visual network (CN-VN) connectivity in State 2; migraine with tinnitus patients showed not only decreased CN-VN connectivity in State 2 but also decreased cerebellar network and executive control network (CN-ECN) connectivity in State 2 and increased cerebellar network and somatomotor network (SMN-VN) connectivity in State 1. The abnormal cerebellum dFNC with the executive control network (CN-ECN) was negatively correlated with headache frequency of migraine (rho = -0.776, p = 0.005).

CONCLUSION: Brain network characteristics of migraine with tinnitus patients may indicate different mechanisms for migraine and tinnitus. Our results demonstrated a transient pathologic state with atypical cerebellar-cortical connectivity in migraine with tinnitus patients, which might be used to identify the neuro-pathophysiological mechanisms in migraine accompanied by tinnitus.

PMID:35813956 | PMC:PMC9257523 | DOI:10.3389/fnagi.2022.913191

Functional Connectivity of the Chemosenses: A Review

Mon, 07/11/2022 - 18:00

Front Syst Neurosci. 2022 Jun 22;16:865929. doi: 10.3389/fnsys.2022.865929. eCollection 2022.

ABSTRACT

Functional connectivity approaches have long been used in cognitive neuroscience to establish pathways of communication between and among brain regions. However, the use of these analyses to better understand how the brain processes chemosensory information remains nascent. In this review, we conduct a literature search of all functional connectivity papers of olfaction, gustation, and chemesthesis, with 103 articles discovered in total. These publications largely use approaches of seed-based functional connectivity and psychophysiological interactions, as well as effective connectivity approaches such as Granger Causality, Dynamic Causal Modeling, and Structural Equation Modeling. Regardless of modality, studies largely focus on elucidating neural correlates of stimulus qualities such as identity, pleasantness, and intensity, with task-based paradigms most frequently implemented. We call for further "model free" or data-driven approaches in predictive modeling to craft brain-behavior relationships that are free from a priori hypotheses and not solely based on potentially irreproducible literature. Moreover, we note a relative dearth of resting-state literature, which could be used to better understand chemosensory networks with less influence from motion artifacts induced via gustatory or olfactory paradigms. Finally, we note a lack of genomics data, which could clarify individual and heritable differences in chemosensory perception.

PMID:35813269 | PMC:PMC9257046 | DOI:10.3389/fnsys.2022.865929

Altered Intrinsic Brain Activity in Patients With Toothache Using the Percent Amplitude of a Fluctuation Method: A Resting-State fMRI Study

Mon, 07/11/2022 - 18:00

Front Neurol. 2022 Jun 23;13:934501. doi: 10.3389/fneur.2022.934501. eCollection 2022.

ABSTRACT

OBJECTIVE: The percent amplitude of fluctuation (PerAF) technique was utilized to evaluate the neural functions of specific cerebrum areas in patients with toothache (TA).

PATIENTS AND METHODS: An aggregation of 18 patients with TA (eight males and 10 females) were included in the study. We also recruited 18 healthy controls (HCs; eight men and 10 women) aligned for sex and age. Resting functional magnetic resonance imaging (rs-fMRI) scans were obtained. Then, we utilized the PerAF method and a support vector machine (SVM) to analyze the image data and measure neural abnormalities in related cerebrum areas. Receiver operating characteristic (ROC) curve analysis was utilized to appraise the two data sets.

RESULTS: The PerAF signals in the right dorsolateral superior frontal gyrus (RDSFG) and the right posterior central gyrus (RPCG) of TA sufferers were lower than HC signals. These results may reveal neural dysfunctions in relevant cerebrum regions. The AUC values of PerAF in the two areas were 0.979 in the RDSFG and 0.979 in the RPCG. The SVM results suggested that PerAF could be utilized to distinguish the TA group from HCs with a sensitivity of 75.00%, a specificity of 66.67%, and an accuracy of 70.83%.

CONCLUSION: Patients with TA had marked differences in PerAF values in some regions of the cerebrum. Changes in PerAF values represented distinctions in blood oxygen level dependent semaphore intensity, which reflected the overactivity or inactivation of some cerebrum areas in those suffering from TA. At the same time, we analyzed the PerAF values of TAs with ROC curve, which can be helpful for the diagnosis of TA severity and subsequent treatment. Our results may help to elucidate the pathological mechanism of TA.

PMID:35812119 | PMC:PMC9259968 | DOI:10.3389/fneur.2022.934501

Functional Significance of Human Resting-State Networks Hubs Identified Using MEG During the Transition From Childhood to Adulthood

Mon, 07/11/2022 - 18:00

Front Neurol. 2022 Jun 23;13:814940. doi: 10.3389/fneur.2022.814940. eCollection 2022.

ABSTRACT

Cortical hubs identified within resting-state networks (RSNs), areas of the cortex that have a higher-than-average number of connections, are known to be critical to typical cognitive functioning and are often implicated in disorders leading to abnormal cognitive functioning. Functionally defined cortical hubs are also known to change with age in the developing, maturing brain, mostly based on studies carried out using fMRI. We have recently used magnetoencephalography (MEG) to study the maturation trajectories of RSNs and their hubs from age 7 to 29 in 131 healthy participants with high temporal resolution. We found that maturation trajectories diverge as a function of the underlying cortical rhythm. Specifically, we found the beta band (13-30 Hz)-mediated RSNs became more locally efficient with maturation, i.e., more organized into clusters and connected with nearby regions, while gamma (31-80 Hz)-mediated RSNs became more globally efficient with maturation, i.e., prioritizing faster signal transmission between distant cortical regions. We also found that different sets of hubs were associated with each of these networks. To better understand the functional significance of this divergence, we wanted to examine the cortical functions associated with the identified hubs that grew or shrunk with maturation within each of these networks. To that end, we analyzed the results of the prior study using Neurosynth, a platform for large-scale, automated synthesis of fMRI data that links brain coordinates with their probabilistically associated terms. By mapping the Neurosynth terms associated with each of these hubs, we found that maturing hubs identified in the gamma band RSNs were more likely to be associated with bottom-up processes while maturing hubs identified in the beta band RSNs were more likely to be associated with top-down functions. The results were consistent with the idea that beta band-mediated networks preferentially support the maturation of top-down processing, while the gamma band-mediated networks preferentially support the maturation of bottom-up processing.

PMID:35812111 | PMC:PMC9259855 | DOI:10.3389/fneur.2022.814940

Altered Long- and Short-Range Functional Connectivity Density in Patients With Thyroid-Associated Ophthalmopathy: A Resting-State fMRI Study

Mon, 07/11/2022 - 18:00

Front Neurol. 2022 Jun 23;13:902912. doi: 10.3389/fneur.2022.902912. eCollection 2022.

ABSTRACT

BACKGROUND AND PURPOSE: Although previous neuroimaging studies have demonstrated emotion- and psychology-associated brain abnormalities in patients with thyroid-associated ophthalmopathy (TAO), the changes of brain functional connectivity in TAO were seldom focused. We aimed to investigate interregional and intraregional functional interactions in patients with TAO by using resting-state functional MRI (rs-fMRI) with long- and short-range functional connectivity density (FCD) analysis.

METHODS: Thirty patients with TAO and 30 well-matched healthy controls (HCs) were recruited in our study. Long- and short-range FCD values were calculated and compared between the two groups. Correlations between long- and short-range FCD values and clinical indicators were analyzed.

RESULTS: Compared with HCs, patients with showed both increased long- and short-range FCDs in the left middle frontal gyrus (MFG), orbital part of superior frontal gyrus (ORBsup), and dorsolateral part of superior frontal gyrus (SFGdor); meanwhile, both decreased long- and short-range FCDs in bilateral postcentral gyrus (PoCG), left superior parietal gyrus (SPG), and inferior parietal (IPL). In addition, patients with TAO showed increased short-range FCD in the right SFGdor, bilateral medial part of superior frontal gyrus (SFGmed), left orbital part of middle frontal gyrus (ORBmid), and orbital part of inferior frontal gyrus (ORBinf), as well as decreased short-range FCD in the right supplementary motor area (SMA) and the left paracentral lobule (PCL) than HCs. Moreover, the short-range value in the left SFGdor showed a negative correlation with Montreal Cognitive Assessment (MoCA) score (r = -0.501, p = 0.005).

CONCLUSION: Our findings complemented the functional neural mechanism of TAO, and provided potential neuroimaging markers for assessing the psychiatric, visual, and emotional disturbances in patients with TAO.

PMID:35812093 | PMC:PMC9259934 | DOI:10.3389/fneur.2022.902912

Brain Responses to Food Choices and Decisions Depend on Individual Hedonic Profiles and Eating Habits in Healthy Young Women

Mon, 07/11/2022 - 18:00

Front Nutr. 2022 Jun 24;9:920170. doi: 10.3389/fnut.2022.920170. eCollection 2022.

ABSTRACT

The way different food consumption habits in healthy normal-weight individuals can shape their emotional and cognitive relationship with food and further disease susceptibility has been poorly investigated. Documenting the individual consumption of Western-type foods (i.e., high-calorie, sweet, fatty, and/or salty) in relation to psychological traits and brain responses to food-related situations can shed light on the early neurocognitive susceptibility to further diseases and disorders. We aimed to explore the relationship between eating habits, psychological components of eating, and brain responses as measured by blood oxygen level-dependent functional magnetic resonance imaging (fMRI) during a cognitive food choice task and using functional connectivity (FC) during resting-state fMRI (rsfMRI) in a population of 50 healthy normal-weight young women. A Food Consumption Frequency Questionnaire (FCFQ) was used to classify them on the basis of their eating habits and preferences by principal component analysis (PCA). Based on the PCA, we defined two eating habit profiles, namely, prudent-type consumers (PTc, N = 25) and Western-type consumers (WTc, N = 25), i.e., low and high consumers of western diet (WD) foods, respectively. The first two PCA dimensions, PCA1 and PCA2, were associated with different psychological components of eating and brain responses in regions involved in reward and motivation (striatum), hedonic evaluation (orbitofrontal cortex, OFC), decision conflict (anterior cingulate cortex, ACC), and cognitive control of eating (prefrontal cortex). PCA1 was inversely correlated with the FC between the right nucleus accumbens and the left lateral OFC, while PCA2 was inversely correlated with the FC between the right insula and the ACC. Our results suggest that, among a healthy population, distinct eating profiles can be detected, with specific correlates in the psychological components of eating behavior, which are also related to a modulation in the reward and motivation system during food choices. We could detect different patterns in brain functioning at rest, with reduced connectivity between the reward system and the frontal brain region in Western-type food consumers, which might be considered as an initial change toward ongoing modified cortico-striatal control.

PMID:35811938 | PMC:PMC9263555 | DOI:10.3389/fnut.2022.920170

Resting-state neural signal variability in women with depressive disorders

Sun, 07/10/2022 - 18:00

Behav Brain Res. 2022 Jul 7:113999. doi: 10.1016/j.bbr.2022.113999. Online ahead of print.

ABSTRACT

Aberrant activity and connectivity in default mode (DMN), frontoparietal (FPN), and salience (SN) network regions is well-documented in depression. Recent neuroimaging research suggests that altered variability in the blood oxygen level-dependent (BOLD) signal may disrupt normal network integration and be an important novel predictor of psychopathology. However, no studies have yet determined the relationship between resting-state BOLD signal variability and depressive disorders nor applied BOLD signal variability features to the classification of depression history using machine learning (ML). We collected resting-state fMRI data for 79 women with different depression histories: no history, past history, and current depressive disorder. We tested voxelwise differences in BOLD signal variability related to depression group and severity. We also investigated whether BOLD signal variability of DMN, FPN, and SN regions could predict depression history group using a supervised random forest ML model. Results indicated that individuals with any history of depression had significantly decreased BOLD signal variability in the left and right cerebellum and right parietal cortex (pFWE <.05). Furthermore, greater depression severity was also associated with reduced BOLD signal variability in the cerebellum. A random forest model classified participant depression history with 74% accuracy, with the ventral anterior cingulate cortex of the DMN as the most important variable in the model. These findings provide novel support for resting-state BOLD signal variability as a marker of neural dysfunction in depression and implicate decreased neural signal variability in the pathophysiology of depression.

PMID:35811000 | DOI:10.1016/j.bbr.2022.113999

The effect of long-term methadone maintenance treatment on coupling among three large-scale brain networks in male heroin-dependent individuals: A resting-state fMRI study

Sun, 07/10/2022 - 18:00

Drug Alcohol Depend. 2022 Jun 30;238:109549. doi: 10.1016/j.drugalcdep.2022.109549. Online ahead of print.

ABSTRACT

PURPOSE: Methadone maintenance treatment (MMT) is considered as an effective and mainstream therapy for heroin dependence. However, whether long-term MMT would improve the coupling among the three core large-scale brain networks (salience, default mode, and executive control) and its relationship with the craving for heroin is unknown.

METHODS: Forty-four male heroin-dependent individuals during long-term MMT, 27 male heroin-dependent individuals after short-term detoxification/abstinence (SA), and 26 demographically matched healthy controls (HC) underwent resting-state functional magnetic resonance imaging. We analyzed the difference in coupling among the salience, default mode, and executive control networks among the three groups and examined how the coupling among these large-scale networks was associated with craving before and after drug-cue exposure.

RESULTS: Compared with the SA group, the MMT group showed lower craving before and after cue exposure and stronger connectivity between the dorsal anterior cingulate cortex (a key node of the salience network) and key regions of the bilateral executive control network, including the bilateral dorsolateral prefrontal cortex, posterior parietal cortex, and dorsomedial prefrontal cortex. Among the heroin-dependent individuals, the functional connectivity was negatively correlated with the craving before and after heroin-cue exposure.

CONCLUSION: Our findings suggest that long-term MMT could increase the coupling between the salience and bilateral executive control networks and decrease craving for heroin. These findings contribute to the understanding of the neural mechanism of MMT, from the perspective of large-scale brain networks.

PMID:35810622 | DOI:10.1016/j.drugalcdep.2022.109549

Structural connections between the noradrenergic and cholinergic system shape the dynamics of functional brain networks

Sat, 07/09/2022 - 18:00

Neuroimage. 2022 Jul 6:119455. doi: 10.1016/j.neuroimage.2022.119455. Online ahead of print.

ABSTRACT

Complex cognitive abilities are thought to arise from the ability of the brain to adaptively reconfigure its internal network structure as a function of task demands. Recent work has suggested that this inherent flexibility may in part be conferred by the widespread projections of the ascending arousal systems. While the different components of the ascending arousal system are often studied in isolation, there are anatomical connections between neuromodulatory hubs that we hypothesize are crucial for mediating key features of adaptive network dynamics, such as the balance between integration and segregation. To test this hypothesis, we estimated the strength of structural connectivity between key hubs of the noradrenergic and cholinergic arousal systems (the locus coeruleus [LC] and nucleus basalis of Meynert [nbM], respectively). We then asked whether the strength of structural LC and nbM inter-connectivity was related to individual differences in the emergent, dynamical signatures of functional integration measured from resting state fMRI data, such as network and attractor topography. We observed a significant positive relationship between the strength of white-matter connections between the LC and nbM and the extent of network-level integration following BOLD signal peaks in LC relative to nbM activity. In addition, individuals with denser white-matter streamlines interconnecting neuromodulatory hubs also demonstrated a heightened ability to shift to novel brain states. These results suggest that individuals with stronger structural connectivity between the noradrenergic and cholinergic systems have a greater capacity to mediate the flexible network dynamics required to support complex, adaptive behaviour. Furthermore, our results highlight the underlying static features of the neuromodulatory hubs can impose some constraints on the dynamic features of the brain.

PMID:35809888 | DOI:10.1016/j.neuroimage.2022.119455

Altered Dynamic Amplitude of Low-frequency Fluctuations in Patients with Postpartum Depression

Sat, 07/09/2022 - 18:00

Behav Brain Res. 2022 Jul 6:113980. doi: 10.1016/j.bbr.2022.113980. Online ahead of print.

ABSTRACT

BACKGROUND: Postpartum depression (PPD) is a common mood disorder with increasing incidence year by year. However, the dynamic changes in local neural activity of patients with PPD remain unclear. In this study, we utilized the dynamic amplitude of low-frequency fluctuation (dALFF) method to investigate the abnormal temporal variability of local neural activity and its potential correlation with clinical severity in PPD.

METHODS: Twenty-four patients with PPD and nineteen healthy primiparous mothers controls (HCs) matched for age, education level and body mass index were examined by resting-state functional magnetic resonance imaging (rs-fMRI). A sliding-window method was used to assess the dALFF, and a k-means clustering method was used to identify dALFF states. Two-sample t-test was used to compare the differences of dALFF variability and state metrics between PPD and HCs. Pearson correlation analysis was used to analyze the relationship between dALFF variability, states metrics and clinical severity.

RESULTS: (1) Patients with PPD had lower variance of dALFF than HCs in the cognitive control network, cerebellar network and sensorimotor network. (2) Four dALFF states were identified, and patients with PPD spent more time on state 2 than the other three states. The number of transitions between the four dALFF states increased in the patients compared with that in HCs. (3) Multiple dALFF states were found to be correlated with the severity of depression. The variance of dALFF in the right middle frontal gyrus was negatively correlated with the Edinburgh postnatal depression scale score.

CONCLUSION: This study provides new insights into the brain dysfunction of PPD from the perspective of dynamic local brain activity, highlighting the important role of dALFF variability in understanding the neurophysiological mechanisms of PPD.

PMID:35809693 | DOI:10.1016/j.bbr.2022.113980

Cognitive Challenges Are Better in Distinguishing Binge From Nonbinge Drinkers: An Exploratory Deep-Learning Study of fMRI Data of Multiple Behavioral Tasks and Resting State

Sat, 07/09/2022 - 18:00

J Magn Reson Imaging. 2022 Jul 9. doi: 10.1002/jmri.28336. Online ahead of print.

ABSTRACT

BACKGROUND: Studies have identified imaging markers of binge drinking. Functional connectivity during both task challenges and resting state was shown to distinguish binge and nonbinge drinkers. However, no studies have compared the efficacy of task and resting data in the classification.

HYPOTHESIS: Task outperforms resting-state functional magnetic resonance imaging (fMRI) data in the differentiation of binge and nonbinge drinkers. We tested the hypothesis via multiple deep learning algorithms.

STUDY TYPE: Cross-sectional; retrospective.

POPULATION: A total of 149 binge (107 men) and 151 demographically matched, nonbinge (92 men) drinkers curated from the Human Connectome Project, with 80% randomly selected for model development and 20% for validation/test.

FIELD STRENGTH/SEQUENCE: A 3 T; fMRI with a blood oxygen level-dependent (BOLD) gradient-echo echo-planar sequence.

ASSESSMENT: FMRI data of resting state and seven behavioral tasks were acquired. Graph convolutional network (GCN), long short-term memory, convolutional, and recurrent neural network models were built to distinguish bingers and nonbingers using connectivity matrices of 8, 116, and 268 regions of interest (ROI). Nodal metrics including betweenness centrality, degree centrality, clustering coefficient, efficiency, local efficiency, and shortest path length were calculated from the GCN model.

STATISTICAL TESTS: Model performance was quantified by the area under the curve (AUC) in receiver operating characteristic analysis. A P value < 0.05 was considered statistically significant.

RESULTS: Task outperformed resting data in classification by approximately 8% by AUC in the test set. Across models and ROI sets, the gambling, motor, language and working memory tasks, each with AUC of 0.614, 0.612, 0.605, and 0.603, performed better than resting data (AUC = 0.548). Models with 116 ROIs (AUC = 0.602) consistently outperformed those with 8 ROIs (AUC = 0.569). Task data performed best with GCN (AUC = 0.619). Nodal metrics of left supplementary motor area and right cuneus showed significant group main effect across tasks.

CONCLUSION: Neural responses to cognitive challenges relative to resting state better characterize binge drinking. The performance of different network models may depend on behavioral tasks and the number of ROIs.

EVIDENCE LEVEL: 3 TECHNICAL EFFICACY: Stage 2.

PMID:35808911 | DOI:10.1002/jmri.28336

Study protocol: a comprehensive multi-method neuroimaging approach to disentangle developmental effects and individual differences in second language learning

Fri, 07/08/2022 - 18:00

BMC Psychol. 2022 Jul 8;10(1):169. doi: 10.1186/s40359-022-00873-x.

ABSTRACT

BACKGROUND: While it is well established that second language (L2) learning success changes with age and across individuals, the underlying neural mechanisms responsible for this developmental shift and these individual differences are largely unknown. We will study the behavioral and neural factors that subserve new grammar and word learning in a large cross-sectional developmental sample. This study falls under the NWO (Nederlandse Organisatie voor Wetenschappelijk Onderzoek [Dutch Research Council]) Language in Interaction consortium (website: https://www.languageininteraction.nl/ ).

METHODS: We will sample 360 healthy individuals across a broad age range between 8 and 25 years. In this paper, we describe the study design and protocol, which involves multiple study visits covering a comprehensive behavioral battery and extensive magnetic resonance imaging (MRI) protocols. On the basis of these measures, we will create behavioral and neural fingerprints that capture age-based and individual variability in new language learning. The behavioral fingerprint will be based on first and second language proficiency, memory systems, and executive functioning. We will map the neural fingerprint for each participant using the following MRI modalities: T1-weighted, diffusion-weighted, resting-state functional MRI, and multiple functional-MRI paradigms. With respect to the functional MRI measures, half of the sample will learn grammatical features and half will learn words of a new language. Combining all individual fingerprints allows us to explore the neural maturation effects on grammar and word learning.

DISCUSSION: This will be one of the largest neuroimaging studies to date that investigates the developmental shift in L2 learning covering preadolescence to adulthood. Our comprehensive approach of combining behavioral and neuroimaging data will contribute to the understanding of the mechanisms influencing this developmental shift and individual differences in new language learning. We aim to answer: (I) do these fingerprints differ according to age and can these explain the age-related differences observed in new language learning? And (II) which aspects of the behavioral and neural fingerprints explain individual differences (across and within ages) in grammar and word learning? The results of this study provide a unique opportunity to understand how the development of brain structure and function influence new language learning success.

PMID:35804430 | DOI:10.1186/s40359-022-00873-x

Lag-Optimized Blood Oxygenation Level Dependent Cerebrovascular Reactivity Estimates Derived From Breathing Task Data Have a Stronger Relationship With Baseline Cerebral Blood Flow

Fri, 07/08/2022 - 18:00

Front Neurosci. 2022 Jun 15;16:910025. doi: 10.3389/fnins.2022.910025. eCollection 2022.

ABSTRACT

Cerebrovascular reactivity (CVR), an important indicator of cerebrovascular health, is commonly studied with the Blood Oxygenation Level Dependent functional MRI (BOLD-fMRI) response to a vasoactive stimulus. Theoretical and empirical evidence suggests that baseline cerebral blood flow (CBF) modulates BOLD signal amplitude and may influence BOLD-CVR estimates. We address how acquisition and modeling choices affect the relationship between baseline cerebral blood flow (bCBF) and BOLD-CVR: whether BOLD-CVR is modeled with the inclusion of a breathing task, and whether BOLD-CVR amplitudes are optimized for hemodynamic lag effects. We assessed between-subject correlations of average GM values and within-subject spatial correlations across cortical regions. Our results suggest that a breathing task addition to a resting-state acquisition, alongside lag-optimization within BOLD-CVR modeling, can improve BOLD-CVR correlations with bCBF, both between- and within-subjects, likely because these CVR estimates are more physiologically accurate. We report positive correlations between bCBF and BOLD-CVR, both between- and within-subjects. The physiological explanation of this positive correlation is unclear; research with larger samples and tightly controlled vasoactive stimuli is needed. Insights into what drives variability in BOLD-CVR measurements and related measurements of cerebrovascular function are particularly relevant when interpreting results in populations with altered vascular and/or metabolic baselines or impaired cerebrovascular reserve.

PMID:35801183 | PMC:PMC9254683 | DOI:10.3389/fnins.2022.910025

fMRI Findings in Cortical Brain Networks Interactions in Migraine Following Repetitive Transcranial Magnetic Stimulation

Fri, 07/08/2022 - 18:00

Front Neurol. 2022 Jun 21;13:915346. doi: 10.3389/fneur.2022.915346. eCollection 2022.

ABSTRACT

BACKGROUND: Repetitive transcranial magnetic stimulation (rTMS) is one of the high-potential non-pharmacological methods for migraine treatment. The purpose of this study is to define the neuroimaging markers associated with rTMS therapy in patients with migraine based on data from functional MRI (fMRI).

MATERIALS AND METHODS: A total of 19 patients with episodic migraine without aura underwent a 5-day course of rTMS of the fronto-temporo-parietal junction bilaterally, at 10 Hz frequency and 60% of motor threshold response of 900 pulses. Resting-state functional MRI (1.5 T) and a battery of tests were carried out for each patient to clarify their diagnosis, qualitative and quantitative characteristics of pain, and associated affective symptoms. Changes in functional connectivity (FC) in the brain's neural networks before and after the treatment were identified through independent components analysis.

RESULTS: Over the course of therapy, we observed an increase in FC of the default mode network within it, with pain system components and with structures of the visual network. We also noted a decrease in FC of the salience network with sensorimotor and visual networks, as well as an increase in FC of the visual network. Besides, we identified 5 patients who did not have a positive response to one rTMS course after the first week of treatment according to the clinical scales results, presumably because of an increasing trend of depressive symptoms and neuroimaging criteria for depressive disorder.

CONCLUSIONS: Our results show that a 5-day course of rTMS significantly alters the connectivity of brain networks associated with pain and antinociceptive brain systems in about 70% of cases, which may shed light on the neural mechanisms underlying migraine treatment with rTMS.

PMID:35800086 | PMC:PMC9253380 | DOI:10.3389/fneur.2022.915346