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

Wed, 10/16/2019 - 23:41
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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 - 23:41
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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 - 23:41
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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 - 23:41
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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 - 23:41
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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 - 23:41
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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]

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

Tue, 10/15/2019 - 23:39
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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]

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

Tue, 10/15/2019 - 23:39
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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 - 23:39
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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]

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

Tue, 10/15/2019 - 23:39
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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 - 23:39
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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]

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

Mon, 10/14/2019 - 23:38
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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 - 23:38
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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]

Lesion network mapping analysis identifies potential cause of post-operative depression in a case of cingulate low-grade glioma.

Mon, 10/14/2019 - 23:38
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Lesion network mapping analysis identifies potential cause of post-operative depression in a case of cingulate low-grade glioma.

World Neurosurg. 2019 Oct 10;:

Authors: Mansouri A, Boutet A, Elias G, Germann J, Yan H, Babu H, Lozano AM, Valiante T

Abstract
BACKGROUND: Depression following resection of diffuse low-grade gliomas (DLGG) has rarely been described. The location of the tumor or surgical route are among a multitude of potential causes. Lesion-network mapping (LNM), leveraging high quality resting-state fMRI data from large samples of healthy adults, has been used to explore the broader network connectivity for given lesions. However, LNM has not been applied to large intra-axial masses or surgical lesions. Here we utilized LNM to examine a potential cause of postoperative depression in a patient with a cingulate DLGG (Zones I-III).
CASE DESCRIPTION: This 34-year female underwent surgery for medically refractory seizures attributable to the lesion. A near-total resection was attained through a single-stage, trans-cortical route through the medial prefrontal cortex. Despite seizure-freedom and lack of tumor growth (42 months follow-up), she developed symptoms of major depressive disorder (MDD) soon after surgery that have persisted. To identify functional networks potentially engaged by the surgical corridor and tumor resection cavity, both were segmented separately and used as seeds for normative resting-state fMRI connectivity mapping. Then, to study depression specifically, networks associated with the tumor and surgical approach were compared to those associated with subgenual cingulate deep brain stimulation (DBS). The LNM results suggested that the surgical corridor, rather than the tumor, had greater overlap with DBS-based depression networks (32% vs 8%).
CONCLUSION: The early postoperative development of MDD following resection of a cingulate region tumor, though likely multi-factorial, should be considered and patients appropriately counselled preoperatively. Further validation of LNM as a viable methodology for correlating symptoms to lesion(s) could make it a valuable tool in selection of surgical approach and patient counseling.

PMID: 31606510 [PubMed - as supplied by publisher]

Resting-state brain entropy in right temporal lobe epilepsy and its relationship with alertness.

Sun, 10/13/2019 - 20:37
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Resting-state brain entropy in right temporal lobe epilepsy and its relationship with alertness.

Brain Behav. 2019 Oct 12;:e01446

Authors: Zhou M, Jiang W, Zhong D, Zheng J

Abstract
BACKGROUND: To date, no functional MRI (fMRI) studies have focused on brain entropy in right temporal lobe epilepsy (rTLE) patients. Here, we characterized brain entropy (BEN) alterations in patients with rTLE using resting-state functional MRI(rs-fMRI) and explored the relationship between BEN and alertness.
METHOD: Thirty-one rTLE patients and 33 controls underwent MRI scanning to investigate differences in BEN and resting-state functional connectivity (rs-FC) in regions of interest (ROIs) between patients and controls. Correlation analyses were performed to examine relationships between the BEN of each ROI and alertness reaction times (RTs) in rTLE patients.
RESULTS: Compared with controls, the BEN of rTLE patients was significantly increased in the right middle temporal gyrus, inferior temporal gyrus, and other regions of the left hemisphere and significantly decreased in the right middle frontal gyrus and left supplementary motor area (p < .05). The rs-FCs between the ROIs (at p < .01, with the left superior parietal lobule and right precentral gyrus defined as ROI1 and ROI2, respectively) and the whole brain showed an increasing trend in rTLE patients. In addition, the BEN of ROI2 was associated with the intrinsic alertness and phasic alertness RTs of patients with rTLE.
CONCLUSIONS: Our findings suggest that BEN is altered in patients with rTLE and that decreased BEN in the right precentral gyrus is positively related to intrinsic and phasic alertness; the abnormal FC in the brain regions with altered entropy suggests a reconstruction of brain functional connectivity. These findings suggest that BEN mapping may provide a useful tool for probing brain mechanisms related to TLE.

PMID: 31605452 [PubMed - as supplied by publisher]

Toward a Neural Model of the Openness-Psychoticism Dimension: Functional Connectivity in the Default and Frontoparietal Control Networks.

Sat, 10/12/2019 - 20:36
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Toward a Neural Model of the Openness-Psychoticism Dimension: Functional Connectivity in the Default and Frontoparietal Control Networks.

Schizophr Bull. 2019 Oct 11;:

Authors: Blain SD, Grazioplene RG, Ma Y, DeYoung CG

Abstract
Psychosis proneness has been linked to heightened Openness to Experience and to cognitive deficits. Openness and psychotic disorders are associated with the default and frontoparietal networks, and the latter network is also robustly associated with intelligence. We tested the hypothesis that functional connectivity of the default and frontoparietal networks is a neural correlate of the openness-psychoticism dimension. Participants in the Human Connectome Project (N = 1003) completed measures of psychoticism, openness, and intelligence. Resting state functional magnetic resonance imaging was used to identify intrinsic connectivity networks. Structural equation modeling revealed relations among personality, intelligence, and network coherence. Psychoticism, openness, and especially their shared variance were related positively to default network coherence and negatively to frontoparietal coherence. These associations remained after controlling for intelligence. Intelligence was positively related to frontoparietal coherence. Research suggests that psychoticism and openness are linked in part through their association with connectivity in networks involving experiential simulation and cognitive control. We propose a model of psychosis risk that highlights roles of the default and frontoparietal networks. Findings echo research on functional connectivity in psychosis patients, suggesting shared mechanisms across the personality-psychopathology continuum.

PMID: 31603227 [PubMed - as supplied by publisher]

Abnormal dynamic functional connectivity density in patients with generalized anxiety disorder.

Fri, 10/11/2019 - 20:34
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Abnormal dynamic functional connectivity density in patients with generalized anxiety disorder.

J Affect Disord. 2019 Oct 01;261:49-57

Authors: Chen Y, Cui Q, Xie A, Pang Y, Sheng W, Tang Q, Li D, Huang J, He Z, Wang Y, Chen H

Abstract
BACKGROUND: Numerous studies have revealed the abnormal static functional connectivity (FC) among different brain regions in patients with generalized anxiety disorder (GAD). However, little is known about the dynamic changes of FC in patients with GAD.
METHODS: This study investigated the whole-brain dynamic changes of FC in patients with GAD by combining global FC density (FCD) and sliding window correlation analyses. The standard deviation of dynamic FCD (dFCD) was calculated to evaluate its temporal variability along time. Support vector regression was then employed to predict the symptom severity of patients based on abnormal dynamic connectivity patterns.
RESULTS: The abnormal dFCD variability between 81 GAD patients and 80 healthy controls showed that the patients had higher dFCD variability in the bilateral dorsomedial prefrontal cortex (dmPFC) and left hippocampus while lower dFCD variability in the right postcentral gyrus. The abnormal dFCD variability of the left dmPFC is an important feature for anxiety prediction.
LIMITATIONS: The selection of sliding window length remains controversial, and most of our patients have been treated with medications. Future studies are expected to rule out the potential confounding effects from applying different parameters of the sliding window and recruiting large samples of medication-free patients.
CONCLUSION: The altered patterns of time-varying brain connectivity in the frontolimbic and sensorimotor areas may reflect abnormal dynamic neural communication between these regions and other regions of the brain, which may deepen our understanding of the disease.

PMID: 31600587 [PubMed - as supplied by publisher]

Task-evoked Negative BOLD Response and Functional Connectivity in the Default Mode Network are Representative of Two Overlapping but Separate Neurophysiological Processes.

Fri, 10/11/2019 - 20:34
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Task-evoked Negative BOLD Response and Functional Connectivity in the Default Mode Network are Representative of Two Overlapping but Separate Neurophysiological Processes.

Sci Rep. 2019 Oct 09;9(1):14473

Authors: Parker DB, Razlighi QR

Abstract
The topography of the default mode network (DMN) can be obtained with one of two different functional magnetic resonance imaging (fMRI) methods: either from the spontaneous but organized synchrony of the low-frequency fluctuations in resting-state fMRI (rs-fMRI), known as "functional connectivity", or from the consistent and robust deactivations in task-based fMRI (tb-fMRI), here referred to as the "negative BOLD response" (NBR). These two methods are fundamentally different, but their results are often used interchangeably to describe the brain's resting-state, baseline, or intrinsic activity. While the DMN was initially defined by consistent task-based decreases in blood flow in a set of specific brain regions using PET imaging, recently nearly all studies on the DMN employ functional connectivity in rs-fMRI. In this study, we first show the high level of spatial overlap between NBR and functional connectivity of the DMN extracted from the same tb-fMRI scan; then, we demonstrate that the NBR in putative DMN regions can be significantly altered without causing any change in their overlapping functional connectivity. Furthermore, we present evidence that in the DMN, the NBR is more closely related to task performance than the functional connectivity. We conclude that the NBR and functional connectivity of the DMN reflect two separate but overlapping neurophysiological processes, and thus should be differentiated in studies investigating brain-behavior relationships in both healthy and diseased populations. Our findings further raise the possibility that the macro-scale networks of the human brain might internally exhibit a hierarchical functional architecture.

PMID: 31597927 [PubMed - in process]

Using resting-state intrinsic network connectivity to identify suicide risk in mood disorders.

Fri, 10/11/2019 - 20:34
Related Articles

Using resting-state intrinsic network connectivity to identify suicide risk in mood disorders.

Psychol Med. 2019 Oct 10;:1-11

Authors: Stange JP, Jenkins LM, Pocius S, Kreutzer K, Bessette KL, DelDonno SR, Kling LR, Bhaumik R, Welsh RC, Keilp JG, Phan KL, Langenecker SA

Abstract
BACKGROUND: Little is known about the neural substrates of suicide risk in mood disorders. Improving the identification of biomarkers of suicide risk, as indicated by a history of suicide-related behavior (SB), could lead to more targeted treatments to reduce risk.
METHODS: Participants were 18 young adults with a mood disorder with a history of SB (as indicated by endorsing a past suicide attempt), 60 with a mood disorder with a history of suicidal ideation (SI) but not SB, 52 with a mood disorder with no history of SI or SB (MD), and 82 healthy comparison participants (HC). Resting-state functional connectivity within and between intrinsic neural networks, including cognitive control network (CCN), salience and emotion network (SEN), and default mode network (DMN), was compared between groups.
RESULTS: Several fronto-parietal regions (k > 57, p < 0.005) were identified in which individuals with SB demonstrated distinct patterns of connectivity within (in the CCN) and across networks (CCN-SEN and CCN-DMN). Connectivity with some of these same regions also distinguished the SB group when participants were re-scanned after 1-4 months. Extracted data defined SB group membership with good accuracy, sensitivity, and specificity (79-88%).
CONCLUSIONS: These results suggest that individuals with a history of SB in the context of mood disorders may show reliably distinct patterns of intrinsic network connectivity, even when compared to those with mood disorders without SB. Resting-state fMRI is a promising tool for identifying subtypes of patients with mood disorders who may be at risk for suicidal behavior.

PMID: 31597581 [PubMed - as supplied by publisher]

Learning to play badminton altered resting-state activity and functional connectivity of the cerebellar sub-regions in adults.

Wed, 10/02/2019 - 20:22

Learning to play badminton altered resting-state activity and functional connectivity of the cerebellar sub-regions in adults.

PLoS One. 2019;14(10):e0223234

Authors: Shao M, Lin H, Yin D, Li Y, Wang Y, Ma J, Yin J, Jin H

Abstract
Previous studies have shown that sport experts are different from novices in functions and structures of the cerebellar sub-regions and the functional connectivity (FC) associated with the cerebellum, suggesting the role of the cerebellum on motor skill learning (MSL). However, the manipulation of individuals with different motor skills fails to exclude the effects of innate talents. In addition, individuals with higher motor skills often start with the MSL in their young ages. It is still unclear whether the effects regarding the cerebellum would be shown at one's adult age. The present study was to directly alter individuals' motor skills to investigate whether MSL (taking learning to play badminton as an example) in adulthood influences resting-state activity in the cerebellum. To this end, young adults without ball training experience were recruited as participants and were assigned randomly into the experimental group and the control group. Participants in the experimental group were asked to attend a badminton training course for 12 weeks, while the control group did not regularly attend any ball sports during this period. Resting-state functional magnetic resonance imaging (fMRI) was recorded before and after the training. Results showed that compared to the control group, the experimental group had smaller amplitude of low-frequency fluctuation (ALFF) in right cerebellar hemispheric VI and left VIII after training. For the experimental group, right hemispheric VIII had a stronger FC with left hemispheric IV-V, cerebellar vermal IX, left middle cingulate gyrus and right hippocampus after training. Taken together, these findings suggested that MSL, at least learning to play badminton in adulthood, reduces resting-state activity in different sub-regions in the cerebellum but increases FC between sub-regions of the cerebellum as well as between sub-regions of the cerebellum and cerebral cortices (e.g., middle cingulate cortex and hippocampus).

PMID: 31574108 [PubMed - in process]