New resting-state fMRI related studies at PubMed

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Aging and the wandering brain: Age-related differences in the neural correlates of stimulus-independent thoughts.

Wed, 10/16/2019 - 12:40
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Aging and the wandering brain: Age-related differences in the neural correlates of stimulus-independent thoughts.

PLoS One. 2019;14(10):e0223981

Authors: Maillet D, Beaty RE, Adnan A, Fox KCR, Turner GR, Spreng RN

Abstract
In recent years, several studies have indicated that healthy older adults exhibit a reduction in task-unrelated thoughts compared to young adults. However, much less is known regarding age-related differences in time spent engaging in stimulus-independent thoughts or in their neural correlates in the absence of an ongoing task. In the current study, we collected functional magnetic resonance imaging (fMRI) data while 29 young (mean age = 22y) and 22 older (mean age = 70y) adults underwent experience sampling in the absence of an ongoing task (i.e., at "rest"). Although both age groups reported spending a similar amount of time engaged in stimulus-independent thoughts, older adults rated their thoughts as more present-oriented (rather than atemporal) and more novel. Moreover, controlling for these age-related differences in content, we found that experiencing stimulus-independent thoughts was associated with increased posterior cingulate and left angular gyrus activation across age groups compared to exhibiting an external focus of attention. When experiencing stimulus-independent thoughts, younger adults engaged medial and left lateral prefrontal cortex as well as left superior temporal gyrus to a greater degree than older adults. Taken together, our results suggest that, in the absence of an ongoing task, although young and older adults spend a similar amount of time engaging in stimulus-independent thoughts, the content and neural correlates of these thoughts differ with age.

PMID: 31613920 [PubMed - in process]

Functional connectivity of the amygdala is linked to individual differences in emotional pain facilitation.

Wed, 10/16/2019 - 12:40
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Functional connectivity of the amygdala is linked to individual differences in emotional pain facilitation.

Pain. 2019 Oct 10;:

Authors: Gandhi W, Rosenek NR, Harrison R, Salomons TV

Abstract
The amygdala is central to emotional processing of sensory stimuli, including pain. Because recent findings suggest that individual differences in emotional processes play a part in the development of chronic pain, a better understanding of the individual patterns of functional connectivity that make individuals susceptible to emotionally modulated facilitation of pain is needed. We therefore investigated the neural correlates of individual differences in emotional pain facilitation using resting-state functional magnetic resonance imaging (rs-fMRI) with amygdala seed.Thirty-seven participants took part in 3 separate sessions, during which pain sensitivity was tested (session 1), participants underwent rs-fMRI (session 2), and emotional pain modulation was assessed (session 3). Amygdala served as seed for the rs-fMRI analysis and whole-brain voxelwise connectivity was tested. Pain modulatory scores were entered as regressor for the group analysis.Stronger connectivity of the amygdala to S1/M1, S2/operculum, and posterior parietal cortex at rest characterized individuals who showed greater pain facilitation by negative emotions. When comparing the amygdala networks associated with pain unpleasantness and with pain intensity modulation, most of the identified areas were equally related to either pain rating type; only amygdala connectivity to S1/M1 was found to predict pain intensity modulation specifically.We demonstrate that trait-like patterns of functional connectivity between amygdala and cortical regions involved in sensory and motor responses are associated with the individual amplitude of pain facilitation by negative emotional states. Our results are an early step towards improved understanding of the mechanisms that give rise to individual differences in emotional pain modulation.

PMID: 31613866 [PubMed - as supplied by publisher]

Altered Resting-State Functional Connectivity in Wernicke's Encephalopathy With Vestibular Impairment.

Wed, 10/16/2019 - 12:40
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Altered Resting-State Functional Connectivity in Wernicke's Encephalopathy With Vestibular Impairment.

Front Neurol. 2019;10:1035

Authors: Oh SY, Lee J, Kang JJ, Park YH, Kim KW, Lee JM, Kim JS, Dieterich M

Abstract
Objectives: To reveal the neural basis of Wernicke's encephalopathy (WE) with impaired vestibulo-ocular reflex (VOR), we evaluated resting-state functional connectivity (rs-fc) in the vestibular processing brain regions. Methods: Rs-fc between the vestibular regions and the rest of the brain were compared with neurotological features including the head-impulse tests (vHIT) and caloric responses in patients with WE (n = 5, mean age 53.4 ± 10 years) and healthy controls (n = 20, mean age 55.0 ± 9.2 years). Rs-fc analyses employed a region of interest (ROI)-based approach using regions selected a priori that participate in vestibular processing including the cerebellar vermis, insula, parietal operculum, and calcarine cortex. Results: The main neurologic findings for patients with WE were mental changes; gait ataxia; spontaneous and gaze-evoked nystagmus (GEN); and bilaterally positive HIT for the horizontal canals. Video HIT documented bilateral horizontal canal dysfunction with decreased gain and corrective saccades. Caloric irrigation and rotation chair testing revealed prominent bilateral horizontal canal paresis. Patients with WE also had decreased spatial memory, which substantially recovered after treatments. Functional connections at the predefined seed regions, including the insular cortex and parietal operculum, were attenuated in the WE group compared to healthy controls. Conclusions: WE is related to impaired VOR and visuospatial dysfunction, and fMRI documented changes in the rs-fc of multisensory vestibular processing regions including the insula, parietal operculum, and superior temporal gyrus, which participate in integration of vestibular perception.

PMID: 31611841 [PubMed]

Inconsistency in Abnormal Functional Connectivity Across Datasets of ADHD-200 in Children With Attention Deficit Hyperactivity Disorder.

Wed, 10/16/2019 - 12:40
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Inconsistency in Abnormal Functional Connectivity Across Datasets of ADHD-200 in Children With Attention Deficit Hyperactivity Disorder.

Front Psychiatry. 2019;10:692

Authors: Zhou ZW, Fang YT, Lan XQ, Sun L, Cao QJ, Wang YF, Luo H, Zang YF, Zhang H

Abstract
Many studies have shown abnormal functional connectivity in children with attention deficit hyperactivity disorder (ADHD) by using resting-state functional magnetic resonance imaging (rs-fMRI). However, few studies illustrated that to what extent these findings were consistent across different datasets. The present study aimed to assess the consistency of abnormal functional connectivity in children with ADHD across the four datasets from a public-assess rs-fMRI ADHD cohort, namely, ADHD-200. We employed the identical analysis process of previous studies and examined a few factors, including connectivity with the seed regions of the bilateral dorsal anterior cingulate cortex, bilateral inferior frontal gyrus, and bilateral middle frontal gyrus; connectivity between default mode network and executive control network; stringent and lenient statistical thresholds; and the ADHD subtypes. Our results revealed a high inconsistency of abnormal seed-based connectivity in children with ADHD across all datasets, even across three datasets from the same research site. This inconsistency could also be observed with a lenient statistical threshold. Besides, each dataset did not show abnormal connectivity between default mode network and executive control network for ADHD, albeit this abnormal connectivity between networks was intensively reported in previous studies. Importantly, the ADHD combined subtype showed greater consistency than did the inattention subtype. These findings provided methodological insights into the studies on spontaneous brain activity of ADHD, and the ADHD subtypes deserve more attention in future studies.

PMID: 31611824 [PubMed]

Neural Correlates of Facial Expression Recognition in Earthquake Witnesses.

Wed, 10/16/2019 - 12:40
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Neural Correlates of Facial Expression Recognition in Earthquake Witnesses.

Front Neurosci. 2019;13:1038

Authors: Pistoia F, Conson M, Quarantelli M, Panebianco L, Carolei A, Curcio G, Sacco S, Saporito G, Di Cesare E, Barile A, Masciocchi C, Splendiani A

Abstract
Major adverse events, like an earthquake, trigger different kinds of emotional dysfunctions or psychiatric disorders in the exposed subjects. Recent literature has also shown that exposure to natural disasters can increase threat detection. In particular, we previously found a selective enhancement in the ability to read emotional facial expressions in L'Aquila earthquake witnesses, suggesting hypervigilance to stimuli signaling a threat. In light of previous neuroimaging data showing that trauma exposure is related to derangement of resting-state brain activity, in the present study we investigated the neurofunctional changes related to the recognition of emotional faces in L'Aquila earthquake witnesses. Specifically, we tested the relationships between accuracy in recognizing facial expressions and activity of the visual network (VN) and of the default-mode network (DMN). Resting-state functional connectivity (FC) with the main hub of the VN (primary, ventral, right-dorsal, and left-dorsal visual cortices) and DMN (posterior cingulate/precuneus, medial prefrontal, and right and left inferior parietal cortices) was investigated through a seed-based functional magnetic resonance imaging (fMRI) analysis in both earthquake-exposed subjects and non-exposed persons who did not live in an earthquake-affected area. The results showed that, in earthquake-exposed subjects, there is a significant reduction in the correlation between accuracy in recognizing facial expressions and the FC of the dorsal seed of the VN with the right inferior occipito-temporal cortex and the left lateral temporal cortex, and of two parietal seeds of DMN, i.e., lower parietal and medial prefrontal cortex, with the precuneus bilaterally. These findings suggest that a functional modification of brain systems involved in detecting and interpreting emotional faces may represent the neurophysiological basis of the specific "emotional expertise" observed in the earthquake witnesses.

PMID: 31611769 [PubMed]

Neuron loss and dysfunctionality in hippocampus explain aircraft noise induced working memory impairment: a resting-state fMRI study on military pilots.

Wed, 10/16/2019 - 12:40
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Neuron loss and dysfunctionality in hippocampus explain aircraft noise induced working memory impairment: a resting-state fMRI study on military pilots.

Biosci Trends. 2019 Oct 11;:

Authors: Cheng H, Sun G, Li M, Yin M, Chen H

Abstract
Long-term aircraft noise exposure may cast a detrimental effect upon the working memory of military pilots, and the brain structural and functional bases of noise related cognitive impairment remains unclear. In this study, we enrolled 30 fighter jet pilots and 30 matched controls. The working memory performance of the subjects was measured with a neurobehavioral test battery including immediate verbal/visual memory and delayed verbal/visual memory tests. Structural MRI and resting-state functional magnetic resonance imaging (rs-fMRI) were utilized to quantify brain grey matter volumes (GMV), regional homogeneity (ReHo), amplitude of low-frequency fluctuation (ALFF) and fractional ALFF (fALFF) differences between the two groups. Furthermore, correlation analyses were performed to find the association between the neural imaging changes with individual neurobehavioral performance. The military pilots showed significantly lower accuracy in delayed verbal and visual memory tests in comparison to the controls, indicating a potential working memory deficit in this population. Structural MRI data and rs-fMRI data showed that the pilots displayed markedly decreased GMVs, ReHo and ALFF signals in the left hippocampus, suggesting neuron dysfunction of the hippocampus. Besides, ReHo and ALFF/fALFF analysis also revealed reduced ReHo in the left amygdala, left thalamus, left superior temporal gyrus and right superior/middle frontal gyrus, indicating disrupted local neural activity under chronic noise exposure. Furthermore, Spearman correlation analysis proved that the GMV and ReHo of left hippocampus were significantly associated with working memory accuracy. This study provided direct evidence of dysfunctional hippocampus serving as the structural and functional bases for neuropsychological impairment under aircraft noise exposure.

PMID: 31611544 [PubMed - as supplied by publisher]

Trait-like variants in human functional brain networks.

Wed, 10/16/2019 - 12:40
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Trait-like variants in human functional brain networks.

Proc Natl Acad Sci U S A. 2019 Oct 14;:

Authors: Seitzman BA, Gratton C, Laumann TO, Gordon EM, Adeyemo B, Dworetsky A, Kraus BT, Gilmore AW, Berg JJ, Ortega M, Nguyen A, Greene DJ, McDermott KB, Nelson SM, Lessov-Schlaggar CN, Schlaggar BL, Dosenbach NUF, Petersen SE

Abstract
Resting-state functional magnetic resonance imaging (fMRI) has provided converging descriptions of group-level functional brain organization. Recent work has revealed that functional networks identified in individuals contain local features that differ from the group-level description. We define these features as network variants. Building on these studies, we ask whether distributions of network variants reflect stable, trait-like differences in brain organization. Across several datasets of highly-sampled individuals we show that 1) variants are highly stable within individuals, 2) variants are found in characteristic locations and associate with characteristic functional networks across large groups, 3) task-evoked signals in variants demonstrate a link to functional variation, and 4) individuals cluster into subgroups on the basis of variant characteristics that are related to differences in behavior. These results suggest that distributions of network variants may reflect stable, trait-like, functionally relevant individual differences in functional brain organization.

PMID: 31611415 [PubMed - as supplied by publisher]

Affective forecasting in individuals with social anhedonia: The role of social components in anticipated emotion, prospection and neural activation.

Wed, 10/16/2019 - 12:40
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Affective forecasting in individuals with social anhedonia: The role of social components in anticipated emotion, prospection and neural activation.

Schizophr Res. 2019 Oct 11;:

Authors: Zhang RT, Yang ZY, Wang YM, Wang Y, Yang TX, Cheung EFC, Martin EA, Chan RCK

Abstract
BACKGROUND: Affective forecasting, or the ability to forecast emotional responses to future events, is essential to everyday life adaption. Previous research suggests that individuals with social anhedonia exhibit deficits in affective forecasting, but the pattern of these deficits and their neural correlates are not known.
METHODS: Individuals with social anhedonia (n = 40) and healthy controls (n = 46) completed a social affective forecasting task and underwent resting-state fMRI scanning.
RESULTS: Compared with healthy controls, social anhedonia individuals anticipated reduced pleasure especially in social conditions and their prospection contained less visualization, voice, taste, self-referential thoughts, other-referential thoughts and language communication. Moreover, anticipated pleasure (valence and arousal for positive events) was positively associated with effort level, especially in social conditions. The social anhedonia group also exhibited stronger functional connectivity between the retrosplenial cortex and the insula and reduced functional connectivity between the hippocampal formation and the parahippocampus. These altered functional connectivities were correlated with anticipated valence in social, but not non-social, conditions.
CONCLUSIONS: These findings suggest that individuals with social anhedonia anticipate less pleasure predominately in social conditions and impaired prospection may contribute to the reduced anticipated pleasure. Reduced anticipated pleasure may be a target to improve social motivation in social anhedonia individuals.

PMID: 31611042 [PubMed - as supplied by publisher]

Altered Cortico-Limbic Network Connectivity in Parkinsonian Depression: The Effect of Antidepressants.

Wed, 10/16/2019 - 12:40
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Altered Cortico-Limbic Network Connectivity in Parkinsonian Depression: The Effect of Antidepressants.

J Parkinsons Dis. 2018;8(3):429-440

Authors: Morgan HE, Ledbetter CR, Ferrier C, Zweig RM, Disbrow EA

Abstract
BACKGROUND: Depression is a common comorbidity of Parkinson's disease (PD); however, the impact of antidepressant status on cortical function in parkinsonian depression is not fully understood. While studies of resting state functional MRI in major depression have shown that antidepressant treatment affects cortical connectivity, data on connectivity and antidepressant status in PD is sparse.
OBJECTIVE: We tested the hypothesis that cortico-limbic network (CLN) resting state connectivity is abnormal in antidepressant-treated parkinsonian depression.
METHODS: Thirteen antidepressant-treated depressed PD and 47 non-depressed PD participants from the Parkinson's Progression Markers Initiative (PPMI) database were included. Data was collected using 3T Siemens TIM Trio MR scanners and analyzed using SPM and CONN functional connectivity toolbox. Volumetric analysis was also performed using BrainSuite.
RESULTS: We found decreased connectivity in the antidepressant-treated depressed PD group when compared to non-depressed PD between the left frontal operculum and bilateral insula, and also reduced connectivity between right orbitofrontal cortex and left temporal fusiform structures. Increased depression scores were associated with decreased insular-frontal opercular connectivity. No ROI volumetric differences were found between groups.
CONCLUSION: Given the relationship between depression scores and cortico-limbic connectivity in PD, the abnormal insular-frontal opercular hypoconnectivity in this cohort may be associated with persistent depressive symptoms or antidepressant effects.

PMID: 30124452 [PubMed - indexed for MEDLINE]

Neural predisposing factors of postoperative delirium in elderly patients with femoral neck fracture.

Wed, 10/16/2019 - 12:40
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Neural predisposing factors of postoperative delirium in elderly patients with femoral neck fracture.

Sci Rep. 2018 05 15;8(1):7602

Authors: Kyeong S, Shin JE, Yang KH, Lee WS, Chung TS, Kim JJ

Abstract
Elderly adults are more likely to develop delirium after major surgery, but there is limited knowledge of the vulnerability for postoperative delirium. In this study, we aimed to identify neural predisposing factors for postoperative delirium and develop a prediction model for estimating an individual's probability of postoperative delirium. Among 57 elderly participants with femoral neck fracture, 25 patients developed postoperative delirium and 32 patients did not. We preoperatively obtained data for clinical assessments, anatomical MRI, and resting-state functional MRI. Then we evaluated gray matter (GM) density, fractional anisotropy, and the amplitude of low-frequency fluctuation (ALFF), and conducted a group-level inference. The prediction models were developed to estimate an individual's probability using logistic regression. The group-level analysis revealed that neuroticism score, ALFF in the dorsolateral prefrontal cortex, and GM density in the caudate/suprachiasmatic nucleus were predisposing factors. The prediction model with these factors showed a correct classification rate of 86% using a leave-one-out cross-validation. The predicted probability computed from the logistic model was significantly correlated with delirium severity. These results suggest that the three components are the most important predisposing factors for postoperative delirium, and our prediction model may reflect the core pathophysiology in estimating the probability of postoperative delirium.

PMID: 29765105 [PubMed - indexed for MEDLINE]

Deep neural networks and kernel regression achieve comparable accuracies for functional connectivity prediction of behavior and demographics.

Tue, 10/15/2019 - 12:00
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Deep neural networks and kernel regression achieve comparable accuracies for functional connectivity prediction of behavior and demographics.

Neuroimage. 2019 Oct 11;:116276

Authors: He T, Kong R, Holmes AJ, Nguyen M, Sabuncu MR, Eickhoff SB, Bzdok D, Feng J, Thomas Yeo BT

Abstract
There is significant interest in the development and application of deep neural networks (DNNs) to neuroimaging data. A growing literature suggests that DNNs outperform their classical counterparts in a variety of neuroimaging applications, yet there are few direct comparisons of relative utility. Here, we compared the performance of three DNN architectures and a classical machine learning algorithm (kernel regression) in predicting individual phenotypes from whole-brain resting-state functional connectivity (RSFC) patterns. One of the DNNs was a generic fully-connected feedforward neural network, while the other two DNNs were recently published approaches specifically designed to exploit the structure of connectome data. By using a combined sample of almost 10,000 participants from the Human Connectome Project (HCP) and UK Biobank, we showed that the three DNNs and kernel regression achieved similar performance across a wide range of behavioral and demographic measures. Furthermore, the generic feedforward neural network exhibited similar performance to the two state-of-the-art connectome-specific DNNs. When predicting fluid intelligence in the UK Biobank, performance of all algorithms dramatically improved when sample size increased from 100 to 1000 subjects. Improvement was smaller, but still significant, when sample size increased from 1000 to 5000 subjects. Importantly, kernel regression was competitive across all sample sizes. Overall, our study suggests that kernel regression is as effective as DNNs for RSFC-based behavioral prediction, while incurring significantly lower computational costs. Therefore, kernel regression might serve as a useful baseline algorithm for future studies.

PMID: 31610298 [PubMed - as supplied by publisher]

Age effect on functional connectivity changes of right anterior insula after partial sleep deprivation.

Tue, 10/15/2019 - 12:00
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Age effect on functional connectivity changes of right anterior insula after partial sleep deprivation.

Neuroreport. 2019 Oct 11;:

Authors: Long Z, Cheng F

Abstract
Neuroimaging studies revealed that emotion and cognition dysfunction after sleep deprivation is associated with the disturbance of the salience network. However, the age effect on the functional connectivity changes of the network after sleep deprivation remains unclear. The current study investigated the functional connectivity changes of the right anterior insula after partial sleep deprivation in young and old adults by using resting-state functional magnetic resonance imaging. We found a significant age × deprivation interaction effect on the functional connectivity between the right ventral anterior insula and the right ventral lateral prefrontal cortex and between the right dorsal anterior insula and the right anterior temporoparietal junction and left medial prefrontal cortex. Post-hoc analysis indicated that only young adults showed reduced functional connectivity of the right anterior insula. The changes in the functional connectivity between the right anterior insula and the right ventral lateral prefrontal cortex and anterior temporoparietal junction were negatively correlated with the insomnia severity index. Results suggested that sleep deprivation affects the salience network of young and old adults differently and highlighted the crucial role of age in sleep deprivation-related studies.

PMID: 31609826 [PubMed - as supplied by publisher]

Mapping language with resting-state functional magnetic resonance imaging: A study on the functional profile of the language network.

Tue, 10/15/2019 - 12:00
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Mapping language with resting-state functional magnetic resonance imaging: A study on the functional profile of the language network.

Hum Brain Mapp. 2019 Oct 14;:

Authors: Branco P, Seixas D, Castro SL

Abstract
Resting-state functional magnetic resonance imaging (rsfMRI) is a promising technique for language mapping that does not require task-execution. This can be an advantage when language mapping is limited by poor task performance, as is common in clinical settings. Previous studies have shown that language maps extracted with rsfMRI spatially match their task-based homologs, but no study has yet demonstrated the direct participation of the rsfMRI language network in language processes. This demonstration is critically important because spatial similarity can be influenced by the overlap of domain-general regions that are recruited during task-execution. Furthermore, it is unclear which processes are captured by the language network: does it map rather low-level or high-level (e.g., syntactic and lexico-semantic) language processes? We first identified the rsfMRI language network and then investigated task-based responses within its regions when processing stimuli of increasing linguistic content: symbols, pseudowords, words, pseudosentences and sentences. The language network responded only to language stimuli (not to symbols), and higher linguistic content elicited larger brain responses. The left fronto-parietal, the default mode, and the dorsal attention networks were examined and yet none showed language involvement. These findings demonstrate for the first time that the language network extracted through rsfMRI is able to map language in the brain, including regions subtending higher-level syntactic and semantic processes.

PMID: 31609045 [PubMed - as supplied by publisher]

Imaging Functional Recovery Following Ischemic Stroke: Clinical and Preclinical fMRI Studies.

Tue, 10/15/2019 - 12:00
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Imaging Functional Recovery Following Ischemic Stroke: Clinical and Preclinical fMRI Studies.

J Neuroimaging. 2019 Oct 13;:

Authors: Crofts A, Kelly ME, Gibson CL

Abstract
Disability and effectiveness of physical therapy are highly variable following ischemic stroke due to different brain regions being affected. Functional magnetic resonance imaging (fMRI) studies of patients in the months and years following stroke have given some insight into how the brain recovers lost functions. Initially, new pathways are recruited to compensate for the lost region, showing as a brighter blood oxygen-level-dependent (BOLD) signal over a larger area during a task than in healthy controls. Subsequently, activity is reduced to baseline levels as pathways become more efficient, mimicking the process of learning typically seen during development. Preclinical models of ischemic stroke aim to enhance understanding of the biology underlying recovery following stroke. However, the pattern of recruitment and focusing seen in humans has not been observed in preclinical fMRI studies that are highly variable methodologically. Resting-state fMRI studies show more consistency; however, there are still confounding factors to address. Anesthesia and method of stroke induction are the two main sources of variability in preclinical studies; improvements here can reduce variability and increase the intensity and reproducibility of the BOLD response detected by fMRI. Differences in task or stimulus and differences in analysis method also present a source of variability. This review compares clinical and preclinical fMRI studies of recovery following stroke and focuses on how refinement of preclinical models and MRI methods may obtain more representative fMRI data in relation to human studies.

PMID: 31608550 [PubMed - as supplied by publisher]

Interaction of the Mechano-Electrical Feedback With Passive Mechanical Models on a 3D Rat Left Ventricle: A Computational Study.

Tue, 10/15/2019 - 12:00
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Interaction of the Mechano-Electrical Feedback With Passive Mechanical Models on a 3D Rat Left Ventricle: A Computational Study.

Front Physiol. 2019;10:1041

Authors: Du'o'ng MT, Holz D, Alkassar M, Dittrich S, Leyendecker S

Abstract
In this paper, we are investigating the interaction between different passive material models and the mechano-electrical feedback (MEF) in cardiac modeling. Various types of passive mechanical laws (nearly incompressible/compressible, polynomial/exponential-type, transversally isotropic/orthotropic material models) are integrated in a fully coupled electromechanical model in order to study their specific influence on the overall MEF behavior. Our computational model is based on a three-dimensional (3D) geometry of a healthy rat left ventricle reconstructed from magnetic resonance imaging (MRI). The electromechanically coupled problem is solved using a fully implicit finite element-based approach. The effects of different passive material models on the MEF are studied with the help of numerical examples. It turns out that there is a significant difference between the behavior of the MEF for compressible and incompressible material models. Numerical results for the incompressible models exhibit that a change in the electrophysiology can be observed such that the transmembrane potential (TP) is unable to reach the resting state in the repolarization phase, and this leads to non-zero relaxation deformations. The most significant and strongest effects of the MEF on the rat cardiac muscle response are observed for the exponential passive material law.

PMID: 31607936 [PubMed]

Disrupted Intraregional Brain Activity and Functional Connectivity in Unilateral Acute Tinnitus Patients With Hearing Loss.

Tue, 10/15/2019 - 12:00
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Disrupted Intraregional Brain Activity and Functional Connectivity in Unilateral Acute Tinnitus Patients With Hearing Loss.

Front Neurosci. 2019;13:1010

Authors: Zhou GP, Shi XY, Wei HL, Qu LJ, Yu YS, Zhou QQ, Yin X, Zhang H, Tao YJ

Abstract
Purpose: The present study combined fractional amplitude of low-frequency fluctuations (fALFF), regional homogeneity (ReHo), and functional connectivity (FC) to explore brain functional abnormalities in acute tinnitus patients (AT) with hearing loss.
Methods: We recruited twenty-eight AT patients and 31 healthy controls (HCs) and ran resting-state functional magnetic resonance imaging (fMRI) scans. fALFF, ReHo, and FC were conducted and compared between AT patients and HCs. After that, we calculated correlation analyses among abnormal fALFF, ReHo, FC, and clinical data in AT patients.
Results: Compared with HCs, AT showed increased fALFF values in the right inferior temporal gyrus (ITG). In contrast, significantly decreased ReHo values were observed in the cerebellar vermis, the right calcarine cortex, the right precuneus, the right supramarginal gyrus (SMG), and the right middle frontal gyrus (MFG). Based on the differences in the fALFF and ReHo maps, the latter of which we defined as region-of-interest (ROI) for FC analysis, the right ITG exhibited increased connectivity with the right precentral gyrus. In addition, the right MFG demonstrated decreased connectivity with both the bilateral anterior cingulate cortex (ACC) and the left precentral gyrus.
Conclusion: By combining ReHo, fALFF, and FC analyses, our work indicated that AT with hearing loss had abnormal intraregional neural activity and disrupted connectivity in several brain regions which mainly involving the non-auditory area, and these regions are major components of default mode network (DMN), attention network, visual network, and executive control network. These findings will help us enhance the understanding of the neuroimaging mechanism in tinnitus populations. Moreover, these abnormalities remind us that we should focus on the early stages of this hearing disease.

PMID: 31607851 [PubMed]

Spatial Dynamic Functional Connectivity Analysis Identifies Distinctive Biomarkers in Schizophrenia.

Tue, 10/15/2019 - 12:00
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Spatial Dynamic Functional Connectivity Analysis Identifies Distinctive Biomarkers in Schizophrenia.

Front Neurosci. 2019;13:1006

Authors: Bhinge S, Long Q, Calhoun VD, Adali T

Abstract
Dynamic functional network connectivity (dFNC) analysis is a widely-used to study associations between dynamic functional correlations and cognitive abilities. Traditional methods analyze time-varying association of different spatial networks while assuming that the spatial network itself is stationary. However, there has been very little work focused on voxelwise spatial variability. Exploiting the variability across both the temporal and spatial domains provide a more promising direction to obtain reliable dynamic functional patterns. However, methods for extracting time-varying spatio-temporal patterns from large-scale functional magnetic resonance imaging (fMRI) data present some challenges, such as degradation in performance with respect to increase in size of the data, estimation of the number of dynamic components, and the potential sensitivity of the resulting dFNCs to selection of the networks. In this work, we implement subsequent extraction of exemplars and dynamics using a constrained independent vector analysis, a data-driven method that efficiently estimates spatial and temporal dynamics from large-scale resting-state fMRI data. We explore the benefits of analyzing spatial dFNC (sdFNC) patterns over temporal dFNC (tdFNC) patterns in the context of differentiating healthy controls and patients with schizophrenia. Our results indicate that for resting-state fMRI data, sdFNC patterns were able to better classify patients and controls, and yield more distinguishing features compared with tdFNC patterns. We also estimate structured patterns of connectivity/states using sdFNC patterns, an area that has not been studied so far, and observe that sdFNC was able to successfully capture distinct information from healthy controls and patients with schizophrenia. In addition, sdFNC patterns were also able to identify functional patterns that associate with signs of paranoia and abnormalities in the patients group. We also observe that patients with schizophrenia tend to switch to or stay in a state corresponding to a hyperconnected brain network.

PMID: 31607848 [PubMed]

Resting-state functional brain networks in first-episode psychosis: A 12-month follow-up study.

Tue, 10/15/2019 - 12:00
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Resting-state functional brain networks in first-episode psychosis: A 12-month follow-up study.

Aust N Z J Psychiatry. 2018 09;52(9):864-875

Authors: Ganella EP, Seguin C, Pantelis C, Whittle S, Baune BT, Olver J, Amminger GP, McGorry PD, Cropley V, Zalesky A, Bartholomeusz CF

Abstract
INTRODUCTION: Schizophrenia is increasingly conceived as a disorder of brain network connectivity and organization. However, reports of network abnormalities during the early illness stage of psychosis are mixed. This study adopted a data-driven whole-brain approach to investigate functional connectivity and network architecture in a first-episode psychosis cohort relative to healthy controls and whether functional network properties changed abnormally over a 12-month period in first-episode psychosis.
METHODS: Resting-state functional connectivity was performed at two time points. At baseline, 29 first-episode psychosis individuals and 30 healthy controls were assessed, and at 12 months, 14 first-episode psychosis individuals and 20 healthy controls completed follow-up. Whole-brain resting-state functional connectivity networks were mapped for each individual and analyzed using graph theory to investigate whether network abnormalities associated with first-episode psychosis were evident and whether functional network properties changed abnormally over 12 months relative to controls.
RESULTS: This study found no evidence of abnormal resting-state functional connectivity or topology in first-episode psychosis individuals relative to healthy controls at baseline or at 12-months follow-up. Furthermore, longitudinal changes in network properties over a 12-month period did not significantly differ between first-episode psychosis individuals and healthy control. Network measures did not significantly correlate with symptomatology, duration of illness or antipsychotic medication.
CONCLUSIONS: This is the first study to show unaffected resting-state functional connectivity and topology in the early psychosis stage of illness. In light of previous literature, this suggests that a subgroup of first-episode psychosis individuals who have a neurotypical resting-state functional connectivity and topology may exist. Our preliminary longitudinal analyses indicate that there also does not appear to be deterioration in these network properties over a 12-month period. Future research in a larger sample is necessary to confirm our longitudinal findings.

PMID: 29806483 [PubMed - indexed for MEDLINE]

Altered Functional Brain Networks in Patients with Traumatic Anosmia: Resting-State Functional MRI Based on Graph Theoretical Analysis.

Mon, 10/14/2019 - 10:40
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Altered Functional Brain Networks in Patients with Traumatic Anosmia: Resting-State Functional MRI Based on Graph Theoretical Analysis.

Korean J Radiol. 2019 Nov;20(11):1536-1545

Authors: Park M, Chung J, Kim JK, Jeong Y, Moon WJ

Abstract
OBJECTIVE: Traumatic anosmia is a common disorder following head injury; however, little is known regarding its neural basis and influence on the functional networks. Therefore, we aimed to investigate the functional connectivity changes in patients with traumatic anosmia compared to healthy controls using resting-state functional magnetic resonance imaging (rs-fMRI).
MATERIALS AND METHODS: Sixteen patients with traumatic anosmia and 12 healthy controls underwent rs-fMRI. Differences in the connectivity of the olfactory and whole brain networks were compared between the two groups. Graph theoretical parameters, such as modularity and global efficiency of the whole brain or olfactory networks, were calculated and compared. Correlation analyses were performed between the parameters and disease severity.
RESULTS: Patients with traumatic anosmia showed decreased intra-network connectivity in the olfactory network (false discovery rate [FDR]-corrected p < 0.05) compared with that in healthy controls. Furthermore, the inter-network connectivity was increased in both the olfactory (FDR-corrected p < 0.05) and whole brain networks (degree-based statistic-corrected p < 0.05) in the anosmia group. The whole brain networks showed decreased modularity (p < 0.001) and increased global efficiency (p = 0.019) in patients with traumatic anosmia. The modularity and global efficiency were correlated with disease severity in patients with anosmia (p < 0.001 and p = 0.002, respectively).
CONCLUSION: Traumatic anosmia increased the inter-network connectivity observed with rs-fMRI in the olfactory and global brain functional networks. rs-fMRI parameters may serve as potential biomarkers for traumatic anosmia by revealing a more widespread functional damage than previously expected.

PMID: 31606958 [PubMed - in process]

Increased neural connectivity between the hypothalamus and cortical resting-state functional networks in chronic migraine.

Mon, 10/14/2019 - 10:40
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Increased neural connectivity between the hypothalamus and cortical resting-state functional networks in chronic migraine.

J Neurol. 2019 Oct 12;:

Authors: Coppola G, Di Renzo A, Petolicchio B, Tinelli E, Di Lorenzo C, Serrao M, Calistri V, Tardioli S, Cartocci G, Parisi V, Caramia F, Di Piero V, Pierelli F

Abstract
OBJECTIVE: The findings of resting-state functional MRI studies have suggested that abnormal functional integration between interconnected cortical networks characterises the brain of patients with migraine. The aim of this study was to investigate the functional connectivity between the hypothalamus, brainstem, considered as the migraine generator, and the following areas/networks that are reportedly involved in the pathophysiology of migraine: default mode network (DMN), executive control network, dorsal attention system, and primary and dorsoventral visual networks.
METHODS: Twenty patients with chronic migraine (CM) without medication overuse and 20 healthy controls (HCs) were prospectively recruited. All study participants underwent 3-T MRI scans using a 7.5-min resting-state protocol. Using a seed-based approach, we performed a ROI-to-ROI analysis selecting the hypothalamus as the seed.
RESULTS: Compared to HCs, patients with CM showed significantly increased neural connectivity between the hypothalamus and brain areas belonging to the DMN and dorsal visual network. We did not detect any connectivity abnormalities between the hypothalamus and the brainstem. The correlation analysis showed that the severity of the migraine headache was positively correlated with the connectivity strength of the hypothalamus and negatively with the connectivity strength of the medial prefrontal cortex, which belongs to the DMN.
CONCLUSION: These data provide evidence for hypothalamic involvement in large-scale reorganisation at the functional-network level in CM and in proportion with the perceived severity of the migraine pain.

PMID: 31606759 [PubMed - as supplied by publisher]

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