New resting-state fMRI related studies at PubMed

Subscribe to New resting-state fMRI related studies at PubMed feed New resting-state fMRI related studies at PubMed
NCBI: db=pubmed; Term=resting state fMRI
Updated: 2 hours 55 min ago

Initial Evidence for Brain Plasticity Following a Digital Therapeutic Intervention for Depression.

Sat, 05/23/2020 - 15:00
Related Articles

Initial Evidence for Brain Plasticity Following a Digital Therapeutic Intervention for Depression.

Chronic Stress (Thousand Oaks). 2019 Jan-Dec;3:2470547019877880

Authors: Hoch MM, Doucet GE, Moser DA, Hee Lee W, Collins KA, Huryk KM, DeWilde KE, Fleysher L, Iosifescu DV, Murrough JW, Charney DS, Frangou S, Iacoviello BM

Abstract
Background: Digital therapeutics such as cognitive-emotional training have begun to show promise for the treatment of major depressive disorder. Available clinical trial data suggest that monotherapy with cognitive-emotional training using the Emotional Faces Memory Task is beneficial in reducing depressive symptoms in patients with major depressive disorder. The aim of this study was to investigate whether Emotional Faces Memory Task training for major depressive disorder is associated with changes in brain connectivity and whether changes in connectivity parameters are related to symptomatic improvement.
Methods: Fourteen major depressive disorder patients received Emotional Faces Memory Task training as monotherapy over a six-week period. Patients were scanned at baseline and posttreatment to identify changes in resting-state functional connectivity and effective connectivity during emotional working memory processing.
Results: Compared to baseline, patients showed posttreatment reduced connectivity within resting-state networks involved in self-referential and salience processing and greater integration across the functional connectome at rest. Moreover, we observed a posttreatment increase in the Emotional Faces Memory Task-induced modulation of connectivity between cortical control and limbic brain regions, which was associated with clinical improvement.
Discussion: These findings provide initial evidence that cognitive-emotional training may be associated with changes in short-term plasticity of brain networks implicated in major depressive disorder.
Conclusion: Our findings pave the way for the principled design of large clinical and neuroimaging studies.

PMID: 32440602 [PubMed]

Back to the Basics: Resting State Functional Connectivity of the Reticular Activation System in PTSD and its Dissociative Subtype.

Sat, 05/23/2020 - 15:00
Related Articles

Back to the Basics: Resting State Functional Connectivity of the Reticular Activation System in PTSD and its Dissociative Subtype.

Chronic Stress (Thousand Oaks). 2019 Jan-Dec;3:2470547019873663

Authors: Thome J, Densmore M, Koppe G, Terpou B, Théberge J, McKinnon MC, Lanius RA

Abstract
Background: Brainstem and midbrain neuronal circuits that control innate, reflexive responses and arousal are increasingly recognized as central to the neurobiological framework of post-traumatic stress disorder (PTSD). The reticular activation system represents a fundamental neuronal circuit that plays a critical role not only in generating arousal but also in coordinating innate, reflexive responding. Accordingly, the present investigation aims to characterize the resting state functional connectivity of the reticular activation system in PTSD and its dissociative subtype.
Methods: We investigated patterns of resting state functional connectivity of a central node of the reticular activation system, namely, the pedunculopontine nuclei, among individuals with PTSD (n = 77), its dissociative subtype (PTSD+DS; n = 48), and healthy controls (n = 51).
Results: Participants with PTSD and PTSD+DS were characterized by within-group pedunculopontine nuclei resting state functional connectivity to brain regions involved in innate threat processing and arousal modulation (i.e., midbrain, amygdala, ventromedial prefrontal cortex). Critically, this pattern was most pronounced in individuals with PTSD+DS, as compared to both control and PTSD groups. As compared to participants with PTSD and controls, individuals with PTSD+DS showed enhanced pedunculopontine nuclei resting state functional connectivity to the amygdala and the parahippocampal gyrus as well as to the anterior cingulate and the ventromedial prefrontal cortex. No group differences emerged between PTSD and control groups. In individuals with PTSD+DS, state derealization/depersonalization was associated with reduced resting state functional connectivity between the left pedunculopontine nuclei and the anterior nucleus of the thalamus. Altered connectivity in these regions may restrict the thalamo-cortical transmission necessary to integrate internal and external signals at a cortical level and underlie, in part, experiences of depersonalization and derealization.
Conclusions: The present findings extend the current neurobiological model of PTSD and provide emerging evidence for the need to incorporate brainstem structures, including the reticular activation system, into current conceptualizations of PTSD and its dissociative subtype.

PMID: 32440600 [PubMed]

Functional and Structural Changes in Postherpetic Neuralgia Brain Before and Six Months After Pain Relieving.

Sat, 05/23/2020 - 15:00
Related Articles

Functional and Structural Changes in Postherpetic Neuralgia Brain Before and Six Months After Pain Relieving.

J Pain Res. 2020;13:909-918

Authors: Zhang Y, Cao S, Yuan J, Song G, Yu T, Liang X

Abstract
Objective: Multimodal magnetic resonance imaging (MRI) was used to detect whether 6 months after pain relieving, the structural and functional abnormalities in the brain of postherpetic neuralgia (PHN) patients are changeable.
Methods: Fifteen successfully treated PHN patients were enrolled; the brain activity and structural abnormalities were detected and compared before and 6 months after treatment. The functional parameters were evaluated with resting-state functional MRI technique, i.e., the regional homogeneity (ReHo) and fractional amplitude of low-frequency fluctuation (fALFF). Structural changes were detected with voxel-based morphometry (VBM) and diffusion kurtosis imaging (DKI).
Results: Six months after pain relieving, PHN brain showed different ReHo and fALFF values in the frontal lobe, caudate, supramarginal gyrus, anterior cingulate cortex (ACC), cuneus, middle temporal gyrus, and cerebellum. In addition, VBM intensity in the cerebellum increased; DKI values decreased in the thalamus and increased in the temporal lobe after successful treatment.
Conclusion: Six months after pain relieving, functional and structural changes exist in PHN brain. Changes in some differential areas in PHN brain, such as ACC, frontal lobe, thalamus, and temporal lobe indicate that the central plasticity may be reversible after chronic pain relieving.

PMID: 32440196 [PubMed]

Resting-State Brain Activity for Early Prediction Outcome in Postanoxic Patients in a Coma with Indeterminate Clinical Prognosis.

Sat, 05/23/2020 - 15:00
Related Articles

Resting-State Brain Activity for Early Prediction Outcome in Postanoxic Patients in a Coma with Indeterminate Clinical Prognosis.

AJNR Am J Neuroradiol. 2020 May 21;:

Authors: Pugin D, Hofmeister J, Gasche Y, Vulliemoz S, Lövblad KO, Van De Ville D, Haller S

Abstract
BACKGROUND AND PURPOSE: Early outcome prediction of postanoxic patients in a coma after cardiac arrest proves challenging. Current prognostication relies on multimodal testing, using clinical examination, electrophysiologic testing, biomarkers, and structural MR imaging. While this multimodal prognostication is accurate for predicting poor outcome (ie, death), it is not sensitive enough to identify good outcome (ie, consciousness recovery), thus leaving many patients with indeterminate prognosis. We specifically assessed whether resting-state fMRI provides prognostic information, notably in postanoxic patients in a coma with indeterminate prognosis early after cardiac arrest, specifically for good outcome.
MATERIALS AND METHODS: We used resting-state fMRI in a prospective study to compare whole-brain functional connectivity between patients with good and poor outcomes, implementing support vector machine learning. Then, we automatically predicted coma outcome using resting-state fMRI and also compared the prediction based on resting-state fMRI with the outcome prediction based on DWI.
RESULTS: Of 17 eligible patients who completed the study procedure (among 351 patients screened), 9 regained consciousness and 8 remained comatose. We found higher functional connectivity in patients recovering consciousness, with greater changes occurring within and between the occipitoparietal and temporofrontal regions. Coma outcome prognostication based on resting-state fMRI machine learning was very accurate, notably for identifying patients with good outcome (accuracy, 94.4%; area under the receiver operating curve, 0.94). Outcome predictors using resting-state fMRI performed significantly better (P < .05) than DWI (accuracy, 60.0%; area under the receiver operating curve, 0.63).
CONCLUSIONS: Indeterminate prognosis might lead to major clinical uncertainty and significant variations in life-sustaining treatments. Resting-state fMRI might bridge the gap left in early prognostication of postanoxic patients in a coma by identifying those with both good and poor outcomes.

PMID: 32439642 [PubMed - as supplied by publisher]

Impaired mesocorticolimbic connectivity underlies increased mechanical pain sensitivity in chronic low back pain.

Sat, 05/23/2020 - 15:00
Related Articles

Impaired mesocorticolimbic connectivity underlies increased mechanical pain sensitivity in chronic low back pain.

Neuroimage. 2020 May 18;:116969

Authors: Yu S, Li W, Shen W, Edwards RR, Gollub RL, Wilson G, Park J, Ortiz A, Cao J, Gerber J, Mawla I, Chan ST, Lee J, Wasan AD, Napadow V, Kaptchuk TJ, Rosen B, Kong J

Abstract
Chronic low back pain (cLBP) is a prevalent disorder. A growing body of evidence linking the pathology of the reward network to chronic pain suggests that pain sensitization may contribute to cLBP chronification via disruptions of mesocortical and mesolimbic circuits in the reward system. Resting-state (RS) functional magnetic resonance imaging (fMRI) data was acquired from 90 patients with cLBP and 74 matched pain-free controls (HCs) at baseline and after a manipulation for back pain intensification. The ventral tegmental area (VTA) was chosen as a seed region to perform RS functional connectivity (FC) analysis. Baseline rsFC of both the mesocortical (between the VTA and bilateral rostral anterior cingulate cortex (rACC) / and medial prefrontal cortex (mPFC)) and mesolimbic (between the VTA and bilateral hippocampus/parahippocampus) pathways was reduced in patients with cLBP (vs. HCs). In addition, patients exhibiting higher back pain intensity (compared to the relatively lower back pain intensity condition) also showed increases in both mesocortical and mesolimbic connectivity, implicating these pathways in pain downregulation in cLBP. Mediation analysis further isolated the mesolimbic (VTA-hippocampus/ parahippocampus) dysconnectivity as a neural mechanism mediating the association between mechanical pain sensitivity (indexed by P40 pressure) and cLBP severity. In sum, the current study demonstrates deficient mesocorticolimbic connectivity in cLBP, with the mesolimbic dysconnectivity potentially mediating the contribution of pain sensitization to pain chronification. These reward network dysfunctions and purportedly, dopaminergic dysregulations, may help us to identify key brain targets of neuromodulation in the treatment of cLBP.

PMID: 32439536 [PubMed - as supplied by publisher]

Disrupted interhemispheric coordination with unaffected lateralization of global eigenvector centrality characterizes hemiparkinsonism.

Sat, 05/23/2020 - 15:00
Related Articles

Disrupted interhemispheric coordination with unaffected lateralization of global eigenvector centrality characterizes hemiparkinsonism.

Brain Res. 2020 May 18;:146888

Authors: Wu J, Guo T, Zhou C, Gao T, Guan X, Xuan M, Gu Q, Huang P, Song Z, Xu X, Zhang M

Abstract
OBJECTIVE: The motor dysfunctions always affect hemi-body first in Parkinson's disease (PD). However, the interhemispheric relationships in patients with only unilateral motor impairment were barely known to date. We aimed to investigate the interhemispheric functions using resting-state functional Magnetic resonance imaging (RS-fMRI) for further understanding the pathogenesis of PD.
METHODS: Forty-three unilateral-symptomatic PD patients (UPD, Hoehn-Yahr staging scale, H-Y: 1-1.5), and 54 age-, gender-, education-matched normal controls (NC) were recruited. All subjects underwent MRI scanning and clinical evaluations. The interhemispheric coordination (Voxel-Mirrored Homotopic Connectivity, VMHC) and hemispheric dominance pattern (laterality index of eigenvector centrality mapping, LI-ECM) were calculated. Afterwards, correlation analyses and receiver operating characteristic (ROC) curve analysis were employed.
RESULTS: Compared with NC, UPD group showed significantly decreased VMHC in bilateral sensorimotor regions which was negatively correlated with the motor score. Furthermore, at the cut-off homotopic connectivity of 0.604, statistically significant ability of VMHC to discriminate UPD from NC with area under ROC curve (AUC) = 0.759, p < 0.001; specificity = 74.4%; sensitivity = 68.5% was observed. No difference was detected in UPD patients as for ECM and LI-ECM.
CONCLUSIONS: The disrupted interhemispheric coordination in bilateral sensorimotor regions may have significant implications for elucidating the mechanisms underlying the hemiparkinsonism and enabling the uncovering of complex mechanisms of PD.

PMID: 32439342 [PubMed - as supplied by publisher]

Toward Task Connectomics: Examining Whole-Brain Task Modulated Connectivity in Different Task Domains.

Sat, 05/23/2020 - 15:00
Related Articles

Toward Task Connectomics: Examining Whole-Brain Task Modulated Connectivity in Different Task Domains.

Cereb Cortex. 2019 04 01;29(4):1572-1583

Authors: Di X, Biswal BB

Abstract
Human brain anatomical and resting-state functional connectivity have been comprehensively portrayed using MRI, which are termed anatomical and functional connectomes. A systematic examination of tasks modulated whole brain functional connectivity, which we term as task connectome, is still lacking. We analyzed 6 block-designed and 1 event-related designed functional MRI data, and examined whole-brain task modulated connectivity in various task domains, including emotion, reward, language, relation, social cognition, working memory, and inhibition. By using psychophysiological interaction between pairs of regions from the whole brain, we identified statistically significant task modulated connectivity in 4 tasks between their experimental and respective control conditions. Task modulated connectivity was found not only between regions that were activated during the task but also regions that were not activated or deactivated, suggesting a broader involvement of brain regions in a task than indicated by simple regional activations. Decreased functional connectivity was observed in all the 4 tasks and sometimes reduced connectivity was even between regions that were both activated during the task. This suggests that brain regions that are activated together do not necessarily work together. The current study demonstrates the comprehensive task connectomes of 4 tasks, and suggested complex relationships between regional activations and connectivity changes.

PMID: 29931116 [PubMed - indexed for MEDLINE]

Functional Segregation of the Right Inferior Frontal Gyrus: Evidence From Coactivation-Based Parcellation.

Sat, 05/23/2020 - 15:00
Related Articles

Functional Segregation of the Right Inferior Frontal Gyrus: Evidence From Coactivation-Based Parcellation.

Cereb Cortex. 2019 04 01;29(4):1532-1546

Authors: Hartwigsen G, Neef NE, Camilleri JA, Margulies DS, Eickhoff SB

Abstract
Previous studies helped unraveling the functional architecture of the human cerebral cortex. However, a comprehensive functional segregation of right lateral prefrontal cortex is missing. Here, we delineated cortical clusters in right area 44 and 45 based on their task-constrained whole-brain activation patterns across neuroimaging experiments obtained from a large database. We identified 5 clusters that differed with respect to their coactivation patterns, which were consistent with resting-state functional connectivity patterns of an independent dataset. Two clusters in the posterior inferior frontal gyrus (IFG) were functionally associated with action inhibition and execution, while two anterior clusters were related to reasoning and social cognitive processes. A fifth cluster was associated with spatial attention. Strikingly, the functional organization of the right IFG can thus be characterized by a posterior-to-anterior axis with action-related functions on the posterior and cognition-related functions on the anterior end. We observed further subdivisions along a dorsal-to-ventral axis in posterior IFG between action execution and inhibition, and in anterior IFG between reasoning and social cognition. The different clusters were integrated in distinct large-scale networks for various cognitive processes. These results provide evidence for a general organization of cognitive processes along axes spanning from more automatic to more complex cognitive processes.

PMID: 29912435 [PubMed - indexed for MEDLINE]

Inter-individual differences in resting-state functional connectivity are linked to interval timing in irregular contexts.

Fri, 05/22/2020 - 13:40

Inter-individual differences in resting-state functional connectivity are linked to interval timing in irregular contexts.

Cortex. 2020 Apr 08;128:254-269

Authors: Teghil A, Di Vita A, D'Antonio F, Boccia M

Abstract
Behavioral evidence suggests that different mechanisms mediate duration perception depending on whether regular or irregular cues for time estimation are provided, and that individual differences in interoceptive processing may affect duration perception only in the latter case. However, no study has addressed brain correlates of this proposed distinction. Here participants performed a duration reproduction task in two conditions: with unevenly spaced stimuli during time estimation/reproduction (irregular), with regularly spaced stimuli provided during the same task (regular). They also underwent resting-state fMRI to assess regional functional connectivity, in order to link individual differences in behavioral performance to variations in patterns of intrinsic brain oscillations. Resting-state functional connectivity of the right precentral gyrus with the ipsilateral insula and putamen was predicted by duration reproduction performance selectively in the irregular condition. The connectivity of the right posterior insula, within a network modulated by participants' degree of interoceptive awareness, correlated positively with performance in the irregular condition only. Findings support the distinction between brain networks involved in duration processing with or without regular cues, and the hypothesis that the multimodal integration of interoceptive and exteroceptive cues is specifically involved in the latter.

PMID: 32438031 [PubMed - as supplied by publisher]

Association between functional and structural connectivity of the corticostriatal network in people with schizophrenia and unaffected first-degree relatives.

Fri, 05/22/2020 - 13:40

Association between functional and structural connectivity of the corticostriatal network in people with schizophrenia and unaffected first-degree relatives.

J Psychiatry Neurosci. 2020 May 20;45(4):190015

Authors: Li P, Jing RX, Zhao RJ, Shi L, Sun HQ, Ding Z, Lin X, Lu L, Fan Y

Abstract
Background: Dysfunction of the corticostriatal network has been implicated in the pathophysiology of schizophrenia, but findings are inconsistent within and across imaging modalities. We used multimodal neuroimaging to analyze functional and structural connectivity in the corticostriatal network in people with schizophrenia and unaffected first-degree relatives.
Methods: We collected resting-state functional magnetic resonance imaging and diffusion tensor imaging scans from people with schizophrenia (n = 47), relatives (n = 30) and controls (n = 49). We compared seed-based functional and structural connectivity across groups within striatal subdivisions defined a priori.
Results: Compared with controls, people with schizophrenia had altered connectivity between the subdivisions and brain regions in the frontal and temporal cortices and thalamus; relatives showed different connectivity between the subdivisions and the right anterior cingulate cortex (ACC) and the left precuneus. Post-hoc t tests revealed that people with schizophrenia had decreased functional connectivity in the ventral loop (ventral striatum-right ACC) and dorsal loop (executive striatum-right ACC and sensorimotor striatum-right ACC), accompanied by decreased structural connectivity; relatives had reduced functional connectivity in the ventral loop and the dorsal loop (right executive striatum-right ACC) and no significant difference in structural connectivity compared with the other groups. Functional connectivity among people with schizophrenia in the bilateral ventral striatum-right ACC was correlated with positive symptom severity.
Limitations: The number of relatives included was moderate. Striatal subdivisions were defined based on a relatively low threshold, and structural connectivity was measured based on fractional anisotropy alone.
Conclusion: Our findings provide insight into the role of hypoconnectivity of the ventral corticostriatal system in people with schizophrenia.

PMID: 32436671 [PubMed - as supplied by publisher]

Increased striatal functional connectivity is associated with improved smoking cessation outcomes: A preliminary study.

Fri, 05/22/2020 - 13:40

Increased striatal functional connectivity is associated with improved smoking cessation outcomes: A preliminary study.

Addict Biol. 2020 May 21;:e12919

Authors: Wang C, Huang P, Shen Z, Qian W, Wang S, Jiaerken Y, Luo X, Li K, Zeng Q, Zhou C, Yang Y, Zhang M

Abstract
The striatum is the critical area of reward processing and has been repeatedly linked to nicotine addiction. However, it remains unclear whether different smoking cessation outcomes (relapse or not) are associated with different functional connectivity changes of the striatum during smoking cessation treatment. A total of 30 treatment-seeking smokers were recruited in the study and underwent magnetic resonance imaging (MRI) scans immediately before and after a 12-week treatment with varenicline. After the 12-week treatment with varenicline, 14 subjects relapsed to smoking (relapsers), whereas 16 not relapsed (nonrelapsers). Changes in resting-state functional connectivity (rsFC) across groups and visits were assessed using repeated measures analysis of covariance (ANCOVA). Significant interaction effects were detected: (1) between left nucleus accumbens (NAc) and left orbitofrontal cortex (OFC), insula, inferior frontal gyrus (IFG), and bilateral precuneus; (2) between right NAc and left insula, IFG, and bilateral dorsolateral prefrontal cortex (DLPFC); and (3) between bilateral putamen and left precuneus. Post hoc region-of-interest analyses in brain areas showing interaction effects indicated significantly decreased rsFC after treatment compared with before treatment in relapsers but opposite longitudinal changes in nonrelapers. These novel findings suggest that increased striatal rsFC is associated with improved smoking cessation outcomes. These striatal functional circuits may serve as potential therapeutic targets for more efficacious treatment of nicotine addiction.

PMID: 32436626 [PubMed - as supplied by publisher]

Resting State Functional Connectivity Is Associated With Motor Pathway Integrity and Upper-Limb Behavior in Chronic Stroke.

Fri, 05/22/2020 - 13:40

Resting State Functional Connectivity Is Associated With Motor Pathway Integrity and Upper-Limb Behavior in Chronic Stroke.

Neurorehabil Neural Repair. 2020 May 21;:1545968320921824

Authors: Hordacre B, Goldsworthy MR, Welsby E, Graetz L, Ballinger S, Hillier S

Abstract
Background. Resting state functional connectivity (RSFC) is a developmental priority for stroke recovery. Objective. To determine whether (1) RSFC differs between stroke survivors based on integrity of descending motor pathways; (2) RSFC is associated with upper-limb behavior in chronic stroke; and (3) the relationship between interhemispheric RSFC and upper-limb behavior differs based on descending motor pathway integrity. Methods. A total of 36 people with stroke (aged 64.4 ± 11.1 years, time since stroke 4.0 ± 2.8 years) and 25 healthy adults (aged 67.3 ± 6.7 years) participated in this study. RSFC was estimated from electroencephalography (EEG) recordings. Integrity of descending motor pathways was ascertained using transcranial magnetic stimulation to determine motor-evoked potential (MEP) status and magnetic resonance imaging to determine lesion overlap and fractional anisotropy of the corticospinal tract (CST). For stroke participants, upper-limb motor behavior was assessed using the Fugl-Meyer test, Action Research Arm Test and grip strength. Results. β-Frequency interhemispheric sensorimotor RSFC was greater for MEP+ stroke participants compared with MEP- (P = .020). There was a significant positive correlation between β RSFC and upper-limb behavior (P = .004) that appeared to be primarily driven by the MEP+ group. A hierarchical regression identified that the addition of β RSFC to measures of CST integrity explained greater variance in upper-limb behavior (R2 change = 0.13; P = .01). Conclusions. This study provides insight to understand the role of EEG-based measures of interhemispheric network activity in chronic stroke. Resting state interhemispheric connectivity was positively associated with upper-limb behavior for stroke survivors where residual integrity of descending motor pathways was maintained.

PMID: 32436426 [PubMed - as supplied by publisher]

Amygdala functional connectivity in the acute aftermath of trauma prospectively predicts severity of posttraumatic stress symptoms.

Fri, 05/22/2020 - 13:40

Amygdala functional connectivity in the acute aftermath of trauma prospectively predicts severity of posttraumatic stress symptoms.

Neurobiol Stress. 2020 May;12:100217

Authors: Belleau EL, Ehret LE, Hanson JL, Brasel KJ, Larson CL, deRoon-Cassini TA

Abstract
Understanding neural mechanisms that confer risk for posttraumatic stress disorder (PTSD) is critical for earlier intervention, yet longitudinal work has been sparse. The amygdala is part of a core network consistently implicated in PTSD symptomology. Most neural models of PTSD have focused on the amygdala's interactions with the dorsal anterior cingulate cortex, ventromedial prefrontal cortex, and hippocampus. However, an increasing number of studies have linked PTSD symptoms to aberrations in amygdala functional connections with other brain regions involved in emotional information processing, self-referential processing, somatosensory processing, visual processing, and motor control. In the current study, trauma-exposed individuals (N = 54) recruited from the emergency department completed a resting state fMRI scan as well as a script-driven trauma recall fMRI task scan two-weeks post-trauma along with demographic, PTSD, and other clinical symptom questionnaires two-weeks and six-months post-trauma. We examined whether amygdala-whole brain functional connectivity (FC) during rest and task could predict six-month post-trauma PTSD symptoms. More negative amygdala-cerebellum and amygdala-postcentral gyrus FC during rest as well as more negative amygdala-postcentral gyrus and amygdala-midcingulate cortex during recall of the trauma memory predicted six-month post-trauma PTSD after controlling for scanner type. Follow-up multiple regression sensitivity analyses controlling for several other relevant predictors of PTSD symptoms, revealed that amygdala-cerebellum FC during rest and amygdala-postcentral gyrus FC during trauma recall were particularly robust predictors of six-month PTSD symptoms. The results extend cross-sectional studies implicating abnormal FC of the amygdala with other brain regions involved in somatosensory processing, motor control, and emotional information processing in PTSD, to the prospective prediction of risk for chronic PTSD. This work may contribute to earlier identification of at-risk individuals and elucidate potential intervention targets.

PMID: 32435666 [PubMed]

Increased functional connectivity in gambling disorder correlates with behavioural and emotional dysregulation: Evidence of a role for the cerebellum.

Fri, 05/22/2020 - 13:40

Increased functional connectivity in gambling disorder correlates with behavioural and emotional dysregulation: Evidence of a role for the cerebellum.

Behav Brain Res. 2020 May 11;390:112668

Authors: Piccoli T, Maniaci G, Collura G, Gagliardo C, Brancato A, La Tona G, Gangitano M, La Cascia C, Picone F, Marrale M, Cannizzaro C

Abstract
Gambling disorder (GD) is a psychiatric disease that has been recently classified as a behavioural addiction. So far, a very few studies have investigated the alteration of functional connectivity in GD patients, thus the concrete interplay between relevant function-dependent circuitries in such disease has not been comprehensively assessed. The aim of this research was to investigate resting-state functional connectivity in GD patients, searching for a correlation with GD symptoms severity. GD patients were assessed for gambling behaviour, impulsivity, cognitive distortions, anxiety and depression, in comparison with healthy controls (HC). Afterwards, they were assessed for resting-state functional magnetic resonance imaging; functional connectivity was assessed through a data-driven approach, by using independent component analysis. The correlation between gambling severity and the strength of specific resting-state networks was also investigated. Our results show that GD patients displayed higher emotional and behavioural impairment than HC, together with an increased resting state functional connectivity in the network including anterior cingulate cortex, the caudate nucleus and nucleus accumbens, and within the cerebellum, in comparison with the control group. Moreover, a significant correlation between behavioural parameters and the strength of the resting-state cerebellar network was found. Overall, the functional alterations in brain connectivity involving the cerebellum observed in this study underpin the emotional and behavioural impairment recorded in GD patients. This evidence suggests the employment of novel neuromodulatory therapeutic approaches involving specific and salient targets such as the cerebellum in addictive disorders.

PMID: 32434751 [PubMed - as supplied by publisher]

Resting-State Functional Network Scale Effects and Statistical Significance-Based Feature Selection in Machine Learning Classification.

Fri, 05/22/2020 - 13:40
Related Articles

Resting-State Functional Network Scale Effects and Statistical Significance-Based Feature Selection in Machine Learning Classification.

Comput Math Methods Med. 2019;2019:9108108

Authors: Guo H, Li Y, Mensah GK, Xu Y, Chen J, Xiang J, Chen D

Abstract
In recent years, functional brain network topological features have been widely used as classification features. Previous studies have found that network node scale differences caused by different network parcellation definitions significantly affect the structure of the constructed network and its topological properties. However, we still do not know how network scale differences affect the classification accuracy, performance of classification features, and effectiveness of the feature selection strategy using P values in terms of the machine learning method. This study used five scale parcellations, involving 90, 256, 497, 1003, and 1501 nodes. Three local properties of resting-state functional brain networks were selected (degree, betweenness centrality, and nodal efficiency), and the support vector machine method was used to construct classifiers to identify patients with major depressive disorder. We analyzed the impact of the five scales on classification accuracy. In addition, the effectiveness and redundancy of features obtained by the different scale parcellations were compared. Finally, traditional statistical significance (P value) was verified as a feature selection criterion. The results showed that the feature effectiveness of different scales was similar; in other words, parcellation with more regions did not provide more effective discriminative features. Nevertheless, parcellation with more regions did provide a greater quantity of discriminative features, which led to an improvement in the accuracy of the classification. However, due to the close distance between brain regions, the redundancy of parcellation with more regions was also greater. The traditional P value feature selection strategy is feasible with different scales, but our analysis showed that the traditional P < 0.05 threshold was too strict for feature selection. This study provides an important reference for the selection of network scales when applying topological properties of brain networks to machine learning methods.

PMID: 31781290 [PubMed - indexed for MEDLINE]

Looking beyond the face area: lesion network mapping of prosopagnosia.

Fri, 05/22/2020 - 13:40
Related Articles

Looking beyond the face area: lesion network mapping of prosopagnosia.

Brain. 2019 12 01;142(12):3975-3990

Authors: Cohen AL, Soussand L, Corrow SL, Martinaud O, Barton JJS, Fox MD

Abstract
Damage to the right fusiform face area can disrupt the ability to recognize faces, a classic example of how damage to a specialized brain region can disrupt a specialized brain function. However, similar symptoms can arise from damage to other brain regions, and face recognition is now thought to depend on a distributed brain network. The extent of this network and which regions are critical for facial recognition remains unclear. Here, we derive this network empirically based on lesion locations causing clinically significant impairments in facial recognition. Cases of acquired prosopagnosia were identified through a systematic literature search and lesion locations were mapped to a common brain atlas. The network of brain regions connected to each lesion location was identified using resting state functional connectivity from healthy participants (n = 1000), a technique termed lesion network mapping. Lesion networks were overlapped to identify connections common to lesions causing prosopagnosia. Reproducibility was assessed using split-half replication. Specificity was assessed through comparison with non-specific control lesions (n = 135) and with control lesions associated with symptoms other than prosopagnosia (n = 155). Finally, we tested whether our facial recognition network derived from clinically evident cases of prosopagnosia could predict subclinical facial agnosia in an independent lesion cohort (n = 31). Our systematic literature search identified 44 lesions causing prosopagnosia, only 29 of which intersected the right fusiform face area. However, all 44 lesion locations fell within a single brain network defined by connectivity to the right fusiform face area. Less consistent connectivity was found to other face-selective regions. Surprisingly, all 44 lesion locations were also functionally connected, through negative correlation, with regions in the left frontal cortex. This connectivity pattern was highly reproducible and specific to lesions causing prosopagnosia. Positive connectivity to the right fusiform face area and negative connectivity to left frontal regions were independent predictors of prosopagnosia and predicted subclinical facial agnosia in an independent lesion cohort. We conclude that lesions causing prosopagnosia localize to a single functionally connected brain network defined by connectivity to the right fusiform face area and to left frontal regions. Implications of these findings for models of facial recognition deficits are discussed.

PMID: 31740940 [PubMed - indexed for MEDLINE]

Williams syndrome hemideletion and LIMK1 variation both affect dorsal stream functional connectivity.

Fri, 05/22/2020 - 13:40
Related Articles

Williams syndrome hemideletion and LIMK1 variation both affect dorsal stream functional connectivity.

Brain. 2019 12 01;142(12):3963-3974

Authors: Gregory MD, Mervis CB, Elliott ML, Kippenhan JS, Nash T, B Czarapata J, Prabhakaran R, Roe K, Eisenberg DP, Kohn PD, Berman KF

Abstract
Williams syndrome is a rare genetic disorder caused by hemizygous deletion of ∼1.6 Mb affecting 26 genes on chromosome 7 (7q11.23) and is clinically typified by two cognitive/behavioural hallmarks: marked visuospatial deficits relative to verbal and non-verbal reasoning abilities and hypersocial personality. Clear knowledge of the circumscribed set of genes that are affected in Williams syndrome, along with the well-characterized neurobehavioural phenotype, offers the potential to elucidate neurogenetic principles that may apply in genetically and clinically more complex settings. The intraparietal sulcus, in the dorsal visual processing stream, has been shown to be structurally and functionally altered in Williams syndrome, providing a target for investigating resting-state functional connectivity and effects of specific genes hemideleted in Williams syndrome. Here, we tested for effects of the LIMK1 gene, deleted in Williams syndrome and important for neuronal maturation and migration, on intraparietal sulcus functional connectivity. We first defined a target brain phenotype by comparing intraparietal sulcus resting functional connectivity in individuals with Williams syndrome, in whom LIMK1 is hemideleted, with typically developing children. Then in two separate cohorts from the general population, we asked whether intraparietal sulcus functional connectivity patterns similar to those found in Williams syndrome were associated with sequence variation of the LIMK1 gene. Four independent between-group comparisons of resting-state functional MRI data (total n = 510) were performed: (i) 20 children with Williams syndrome compared to 20 age- and sex-matched typically developing children; (ii) a discovery cohort of 99 healthy adults stratified by LIMK1 haplotype; (iii) a replication cohort of 32 healthy adults also stratified by LIMK1 haplotype; and (iv) 339 healthy adolescent children stratified by LIMK1 haplotype. For between-group analyses, differences in intraparietal sulcus resting-state functional connectivity were calculated comparing children with Williams syndrome to matched typically developing children and comparing LIMK1 haplotype groups in each of the three general population cohorts separately. Consistent with the visuospatial construction impairment and hypersocial personality that typify Williams syndrome, the Williams syndrome cohort exhibited opposite patterns of intraparietal sulcus functional connectivity with visual processing regions and social processing regions: decreased circuit function in the former and increased circuit function in the latter. All three general population groups also showed LIMK1 haplotype-related differences in intraparietal sulcus functional connectivity localized to the fusiform gyrus, a visual processing region also identified in the Williams syndrome-typically developing comparison. These results suggest a neurogenetic mechanism, in part involving LIMK1, that may bias neural circuit function in both the general population and individuals with Williams syndrome.

PMID: 31687737 [PubMed - indexed for MEDLINE]

Hypersynchronization in mild cognitive impairment: the 'X' model.

Fri, 05/22/2020 - 13:40
Related Articles

Hypersynchronization in mild cognitive impairment: the 'X' model.

Brain. 2019 12 01;142(12):3936-3950

Authors: Pusil S, López ME, Cuesta P, Bruña R, Pereda E, Maestú F

Abstract
Hypersynchronization has been proposed as a synaptic dysfunction biomarker in the Alzheimer's disease continuum, reflecting the alteration of the excitation/inhibition balance. While animal models have verified this idea extensively, there is still no clear evidence in humans. Here we test this hypothesis, evaluating the risk of conversion from mild cognitive impairment (MCI) to Alzheimer's disease in a longitudinal study. We compared the functional resting state eyes-closed magnetoencephalographic networks of 54 patients with MCI who were followed-up every 6 months. According to their clinical outcome, they were split into: (i) the 'progressive' MCI (n = 27) group; and (ii) the 'stable' MCI group (n = 27). They did not differ in gender or educational level. For all participants, two magnetoencephalographic recordings were acquired. Functional connectivity was evaluated using the phase locking value. To extract the functional connectivity network with significant changes between both magnetoencephalographic recordings, we evaluated the functional connectivity ratio, defined as functional connectivity post-/pre-condition, in a network-based statistical model with an ANCOVA test with age as covariate. Two significant networks were found in the theta and beta bands, involving fronto-temporal and fronto-occipital connections, and showing a diminished functional connectivity ratio in the progressive MCI group. These topologies were then evaluated at each condition showing that at baseline, patients with progressive MCI showed higher synchronization than patients with stable MCI, while in the post-condition this pattern was reversed. These results may be influenced by two main factors in the post-condition: the increased synchrony in the stable MCI patients and the network failure in the progressive MCI patients. These findings may be explained as an 'X' form model where the hypersynchrony predicts conversion, leading subsequently to a network breakdown in progressive MCI. Patients with stable MCI showed an opposite phenomenon, which could indicate that they were a step beyond in the Alzheimer's disease continuum. This model would be able to predict the risk for the conversion to dementia in MCI patients.

PMID: 31633176 [PubMed - indexed for MEDLINE]

The Protective Effects of Supportive Parenting on the Relationship Between Adolescent Poverty and Resting-State Functional Brain Connectivity During Adulthood.

Fri, 05/22/2020 - 13:40
Related Articles

The Protective Effects of Supportive Parenting on the Relationship Between Adolescent Poverty and Resting-State Functional Brain Connectivity During Adulthood.

Psychol Sci. 2019 07;30(7):1040-1049

Authors: Brody GH, Yu T, Nusslock R, Barton AW, Miller GE, Chen E, Holmes C, McCormick M, Sweet LH

Abstract
Children growing up in poverty are vulnerable to negative changes in the developing brain; however, these outcomes vary widely. We tested the hypothesis that receipt of supportive parenting would offset the association between living in poverty during adolescence and the connectivity of neural networks that support cognition and emotion regulation during young adulthood. In a sample of African American youths (N = 119) living in the rural South, poverty status and receipt of supportive parenting were assessed when youths were 11 to 13 and 16 to 18 years old. At age 25, resting-state functional connectivity of the central-executive and emotion-regulation neural networks was assessed using functional MRI. The results revealed that more years spent living in poverty presaged less connectivity in both neural networks among young adults who received low levels of supportive parenting but not among those who received high levels of such parenting.

PMID: 31088209 [PubMed - indexed for MEDLINE]

Acute and sub-acute stroke lesion segmentation from multimodal MRI.

Thu, 05/21/2020 - 12:40

Acute and sub-acute stroke lesion segmentation from multimodal MRI.

Comput Methods Programs Biomed. 2020 May 06;194:105521

Authors: Clèrigues A, Valverde S, Bernal J, Freixenet J, Oliver A, Lladó X

Abstract
BACKGROUND AND OBJECTIVE: Acute stroke lesion segmentation tasks are of great clinical interest as they can help doctors make better informed time-critical treatment decisions. Magnetic resonance imaging (MRI) is time demanding but can provide images that are considered the gold standard for diagnosis. Automated stroke lesion segmentation can provide with an estimate of the location and volume of the lesioned tissue, which can help in the clinical practice to better assess and evaluate the risks of each treatment.
METHODS: We propose a deep learning methodology for acute and sub-acute stroke lesion segmentation using multimodal MR imaging. We pre-process the data to facilitate learning features based on the symmetry of brain hemispheres. The issue of class imbalance is tackled using small patches with a balanced training patch sampling strategy and a dynamically weighted loss function. Moreover, a combination of whole patch predictions, using a U-Net based CNN architecture, and high degree of overlapping patches reduces the need for additional post-processing.
RESULTS: The proposed method is evaluated using two public datasets from the 2015 Ischemic Stroke Lesion Segmentation challenge (ISLES 2015). These involve the tasks of sub-acute stroke lesion segmentation (SISS) and acute stroke penumbra estimation (SPES) from multiple diffusion, perfusion and anatomical MRI modalities. The performance is compared against state-of-the-art methods with a blind online testing set evaluation on each of the challenges. At the time of submitting this manuscript, our approach is the first method in the online rankings for the SISS (DSC=0.59 ± 0.31) and SPES sub-tasks (DSC=0.84 ± 0.10). When compared with the rest of submitted strategies, we achieve top rank performance with a lower Hausdorff distance.
CONCLUSIONS: Better segmentation results are obtained by leveraging the anatomy and pathophysiology of acute stroke lesions and using a combined approach to minimize the effects of class imbalance. The same training procedure is used for both tasks, showing the proposed methodology can generalize well enough to deal with different unrelated tasks and imaging modalities without hyper-parameter tuning. In order to promote the reproducibility of our results, a public version of the proposed method has been released to the scientific community.

PMID: 32434099 [PubMed - as supplied by publisher]

Pages