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Diminished Functional Connectivity on the Road to Child Sexual Abuse in Pedophilia.

4 hours 13 min ago

Diminished Functional Connectivity on the Road to Child Sexual Abuse in Pedophilia.

J Sex Med. 2015 Jan 23;

Authors: Kärgel C, Massau C, Weiß S, Walter M, Kruger TH, Schiffer B

Abstract
BACKGROUND: Pedophilia is a disorder recognized for its impairment to the individual and for the harm it may cause to others. However, the neurobiology of pedophilia and a possible propensity to sexually abuse children are not well understood. In this study, we thus aimed at providing new insights in how functional integration of brain regions may relate to pedophilia or child sexual abuse (CSA).
METHOD: By using functional magnetic resonance imaging (fMRI) technique, we compared functional connectivity at rest (RSFC) between pedophiles who engaged (P+CSA; N = 12) or did not engage (P-CSA; N = 14) in CSA and healthy controls (HCs; N = 14) within two networks: (i) the default mode network and (ii) the limbic network that has been linked to pedophilia before.
RESULTS: Pedophiles who engaged in CSA show diminished RSFC in both networks compared with HC and P-CSA. Most importantly, they showed diminished RSFC between the left amygdala and orbitofrontal as well as anterior prefrontal regions. Though significant age differences between groups could not be avoided, correlation control analysis did not provide evidence for the assumption that the RSFC effects were related to age differences.
CONCLUSION: We found significantly diminished RSFC in brain networks critically involved in widespread motivational and socio-emotional processes. These results extend existing models of the functional neuroanatomy of pedophilia and CSA as altered RSFC between these regions were related to CSA rather than pedophilia and thus may account for an increased propensity to engage in CSA in people suffering from pedophilia. Kärgel C, Massau C, Weiß S, Walter M, Kruger THC, and Schiffer B. Diminished functional connectivity on the road to child sexual abuse in pedophilia. J Sex Med **;**:**-**.

PMID: 25615561 [PubMed - as supplied by publisher]

A number-form area in the blind.

4 hours 13 min ago

A number-form area in the blind.

Nat Commun. 2015;6:6026

Authors: Abboud S, Maidenbaum S, Dehaene S, Amedi A

Abstract
Distinct preference for visual number symbols was recently discovered in the human right inferior temporal gyrus (rITG). It remains unclear how this preference emerges, what is the contribution of shape biases to its formation and whether visual processing underlies it. Here we use congenital blindness as a model for brain development without visual experience. During fMRI, we present blind subjects with shapes encoded using a novel visual-to-music sensory-substitution device (The EyeMusic). Greater activation is observed in the rITG when subjects process symbols as numbers compared with control tasks on the same symbols. Using resting-state fMRI in the blind and sighted, we further show that the areas with preference for numerals and letters exhibit distinct patterns of functional connectivity with quantity and language-processing areas, respectively. Our findings suggest that specificity in the ventral 'visual' stream can emerge independently of sensory modality and visual experience, under the influence of distinct connectivity patterns.

PMID: 25613599 [PubMed - in process]

Sex and disease-related alterations of anterior insula functional connectivity in chronic abdominal pain.

4 hours 13 min ago
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Sex and disease-related alterations of anterior insula functional connectivity in chronic abdominal pain.

J Neurosci. 2014 Oct 22;34(43):14252-9

Authors: Hong JY, Kilpatrick LA, Labus JS, Gupta A, Katibian D, Ashe-McNalley C, Stains J, Heendeniya N, Smith SR, Tillisch K, Naliboff B, Mayer EA

Abstract
Resting-state functional magnetic resonance imaging has been used to investigate intrinsic brain connectivity in healthy subjects and patients with chronic pain. Sex-related differences in the frequency power distribution within the human insula (INS), a brain region involved in the integration of interoceptive, affective, and cognitive influences, have been reported. Here we aimed to test sex and disease-related alterations in the intrinsic functional connectivity of the dorsal anterior INS. The anterior INS is engaged during goal-directed tasks and modulates the default mode and executive control networks. By comparing functional connectivity of the dorsal anterior INS in age-matched female and male healthy subjects and patients with irritable bowel syndrome (IBS), a common chronic abdominal pain condition, we show evidence for sex and disease-related alterations in the functional connectivity of this region: (1) male patients compared with female patients had increased positive connectivity of the dorsal anterior INS bilaterally with the medial prefrontal cortex (PFC) and dorsal posterior INS; (2) female patients compared with male patients had greater negative connectivity of the left dorsal anterior INS with the left precuneus; (3) disease-related differences in the connectivity between the bilateral dorsal anterior INS and the dorsal medial PFC were observed in female subjects; and (4) clinical characteristics were significantly correlated to the insular connectivity with the dorsal medial PFC in male IBS subjects and with the precuneus in female IBS subjects. These findings are consistent with the INS playing an important role in modulating the intrinsic functional connectivity of major networks in the resting brain and show that this role is influenced by sex and diagnosis.

PMID: 25339739 [PubMed - indexed for MEDLINE]

Reduced functional connectivity in the thalamo-insular subnetwork in patients with acute anorexia nervosa.

Sat, 01/24/2015 - 17:30

Reduced functional connectivity in the thalamo-insular subnetwork in patients with acute anorexia nervosa.

Hum Brain Mapp. 2015 Jan 22;

Authors: Ehrlich S, Lord AR, Geisler D, Borchardt V, Boehm I, Seidel M, Ritschel F, Schulze A, King JA, Weidner K, Roessner V, Walter M

Abstract
The neural underpinnings of anorexia nervosa (AN) are poorly understood. Results from existing functional brain imaging studies using disorder-relevant food- or body-stimuli have been heterogeneous and may be biased due to varying compliance or strategies of the participants. In this study, resting state functional connectivity imaging was used. To explore the distributed nature and complexity of brain function we characterized network patterns in patients with acute AN. Thirty-five unmedicated female acute AN patients and 35 closely matched healthy female participants underwent resting state functional magnetic resonance imaging. We used a network-based statistic (NBS) approach [Zalesky et al., 2010a] to identify differences between groups by isolating a network of interconnected nodes with a deviant connectivity pattern. Group comparison revealed a subnetwork of connections with decreased connectivity including the amygdala, thalamus, fusiform gyrus, putamen and the posterior insula as the central hub in the patient group. Results were not driven by changes in intranodal or global connectivity. No network could be identified where AN patients had increased coupling. Given the known involvement of the identified thalamo-insular subnetwork in interoception, decreased connectivity in AN patients in these nodes might reflect changes in the propagation of sensations that alert the organism to urgent homeostatic imbalances and pain-processes that are known to be severely disturbed in AN and might explain the striking discrepancy between patient's actual and perceived internal body state. Hum Brain Mapp, 2015. © 2014 Wiley Periodicals, Inc.

PMID: 25611053 [PubMed - as supplied by publisher]

Classification algorithms with multi-modal data fusion could accurately distinguish neuromyelitis optica from multiple sclerosis.

Sat, 01/24/2015 - 17:30

Classification algorithms with multi-modal data fusion could accurately distinguish neuromyelitis optica from multiple sclerosis.

Neuroimage Clin. 2015;7:306-314

Authors: Eshaghi A, Riyahi-Alam S, Saeedi R, Roostaei T, Nazeri A, Aghsaei A, Doosti R, Ganjgahi H, Bodini B, Shakourirad A, Pakravan M, Ghana'ati H, Firouznia K, Zarei M, Azimi AR, Sahraian MA

Abstract
Neuromyelitis optica (NMO) exhibits substantial similarities to multiple sclerosis (MS) in clinical manifestations and imaging results and has long been considered a variant of MS. With the advent of a specific biomarker in NMO, known as anti-aquaporin 4, this assumption has changed; however, the differential diagnosis remains challenging and it is still not clear whether a combination of neuroimaging and clinical data could be used to aid clinical decision-making. Computer-aided diagnosis is a rapidly evolving process that holds great promise to facilitate objective differential diagnoses of disorders that show similar presentations. In this study, we aimed to use a powerful method for multi-modal data fusion, known as a multi-kernel learning and performed automatic diagnosis of subjects. We included 30 patients with NMO, 25 patients with MS and 35 healthy volunteers and performed multi-modal imaging with T1-weighted high resolution scans, diffusion tensor imaging (DTI) and resting-state functional MRI (fMRI). In addition, subjects underwent clinical examinations and cognitive assessments. We included 18 a priori predictors from neuroimaging, clinical and cognitive measures in the initial model. We used 10-fold cross-validation to learn the importance of each modality, train and finally test the model performance. The mean accuracy in differentiating between MS and NMO was 88%, where visible white matter lesion load, normal appearing white matter (DTI) and functional connectivity had the most important contributions to the final classification. In a multi-class classification problem we distinguished between all of 3 groups (MS, NMO and healthy controls) with an average accuracy of 84%. In this classification, visible white matter lesion load, functional connectivity, and cognitive scores were the 3 most important modalities. Our work provides preliminary evidence that computational tools can be used to help make an objective differential diagnosis of NMO and MS.

PMID: 25610795 [PubMed - as supplied by publisher]

Cerebro-cerebellar connectivity is increased in primary lateral sclerosis.

Sat, 01/24/2015 - 17:30

Cerebro-cerebellar connectivity is increased in primary lateral sclerosis.

Neuroimage Clin. 2015;7:288-296

Authors: Meoded A, Morrissette AE, Katipally R, Schanz O, Gotts SJ, Floeter MK

Abstract
Increased functional connectivity in resting state networks was found in several studies of patients with motor neuron disorders, although diffusion tensor imaging studies consistently show loss of white matter integrity. To understand the relationship between structural connectivity and functional connectivity, we examined the structural connections between regions with altered functional connectivity in patients with primary lateral sclerosis (PLS), a long-lived motor neuron disease. Connectivity matrices were constructed from resting state fMRI in 16 PLS patients to identify areas of differing connectivity between patients and healthy controls. Probabilistic fiber tracking was used to examine structural connections between regions of differing connectivity. PLS patients had 12 regions with increased functional connectivity compared to controls, with a predominance of cerebro-cerebellar connections. Increased functional connectivity was strongest between the cerebellum and cortical motor areas and between the cerebellum and frontal and temporal cortex. Fiber tracking detected no difference in connections between regions with increased functional connectivity. We conclude that functional connectivity changes are not strongly based in structural connectivity. Increased functional connectivity may be caused by common inputs, or by reduced selectivity of cortical activation, which could result from loss of intracortical inhibition when cortical afferents are intact.

PMID: 25610792 [PubMed - as supplied by publisher]

Thalamic functional connectivity predicts seizure laterality in individual TLE patients: Application of a biomarker development strategy.

Sat, 01/24/2015 - 17:30

Thalamic functional connectivity predicts seizure laterality in individual TLE patients: Application of a biomarker development strategy.

Neuroimage Clin. 2015;7:273-280

Authors: Barron DS, Fox PT, Pardoe H, Lancaster J, Price LR, Blackmon K, Berry K, Cavazos JE, Kuzniecky R, Devinsky O, Thesen T

Abstract
Noninvasive markers of brain function could yield biomarkers in many neurological disorders. Disease models constrained by coordinate-based meta-analysis are likely to increase this yield. Here, we evaluate a thalamic model of temporal lobe epilepsy that we proposed in a coordinate-based meta-analysis and extended in a diffusion tractography study of an independent patient population. Specifically, we evaluated whether thalamic functional connectivity (resting-state fMRI-BOLD) with temporal lobe areas can predict seizure onset laterality, as established with intracranial EEG. Twenty-four lesional and non-lesional temporal lobe epilepsy patients were studied. No significant differences in functional connection strength in patient and control groups were observed with Mann-Whitney Tests (corrected for multiple comparisons). Notwithstanding the lack of group differences, individual patient difference scores (from control mean connection strength) successfully predicted seizure onset zone as shown in ROC curves: discriminant analysis (two-dimensional) predicted seizure onset zone with 85% sensitivity and 91% specificity; logistic regression (four-dimensional) achieved 86% sensitivity and 100% specificity. The strongest markers in both analyses were left thalamo-hippocampal and right thalamo-entorhinal cortex functional connection strength. Thus, this study shows that thalamic functional connections are sensitive and specific markers of seizure onset laterality in individual temporal lobe epilepsy patients. This study also advances an overall strategy for the programmatic development of neuroimaging biomarkers in clinical and genetic populations: a disease model informed by coordinate-based meta-analysis was used to anatomically constrain individual patient analyses.

PMID: 25610790 [PubMed - as supplied by publisher]

Evoked itch perception is associated with changes in functional brain connectivity.

Sat, 01/24/2015 - 17:30

Evoked itch perception is associated with changes in functional brain connectivity.

Neuroimage Clin. 2015;7:213-221

Authors: Desbordes G, Li A, Loggia ML, Kim J, Schalock PC, Lerner E, Tran TN, Ring J, Rosen BR, Kaptchuk TJ, Pfab F, Napadow V

Abstract
Chronic itch, a highly debilitating condition, has received relatively little attention in the neuroimaging literature. Recent studies suggest that brain regions supporting itch in chronic itch patients encompass sensorimotor and salience networks, and corticostriatal circuits involved in motor preparation for scratching. However, how these different brain areas interact with one another in the context of itch is still unknown. We acquired BOLD fMRI scans in 14 atopic dermatitis patients to investigate resting-state functional connectivity before and after allergen-induced itch exacerbated the clinical itch perception in these patients. A seed-based analysis revealed decreased functional connectivity from baseline resting state to the evoked-itch state between several itch-related brain regions, particularly the insular and cingulate cortices and basal ganglia, where decreased connectivity was significantly correlated with increased levels of perceived itch. In contrast, evoked itch increased connectivity between key nodes of the frontoparietal control network (superior parietal lobule and dorsolateral prefrontal cortex), where higher increase in connectivity was correlated with a lesser increase in perceived itch, suggesting that greater interaction between nodes of this executive attention network serves to limit itch sensation via enhanced top-down regulation. Overall, our results provide the first evidence of itch-dependent changes in functional connectivity across multiple brain regions.

PMID: 25610783 [PubMed - as supplied by publisher]

Distinct functional connectivity of limbic network in the washing type obsessive-compulsive disorder.

Sat, 01/24/2015 - 17:30
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Distinct functional connectivity of limbic network in the washing type obsessive-compulsive disorder.

Prog Neuropsychopharmacol Biol Psychiatry. 2014 Aug 4;53:149-55

Authors: Jhung K, Ku J, Kim SJ, Lee H, Kim KR, An SK, Kim SI, Yoon KJ, Lee E

Abstract
Neurobiological models of obsessive-compulsive disorder (OCD) emphasize disturbances of the corticostriatal circuit, but it remains unclear as to how these complex network dysfunctions correspond to heterogeneous OCD phenotypes. We aimed to investigate corticostriatal functional connectivity alterations distinct to OCD characterized predominantly by contamination/washing symptoms. Functional connectivity strengths of the striatal seed regions with remaining brain regions during the resting condition and the contamination symptom provocation condition were compared among 13 OCD patients with predominant contamination/washing symptoms (CON), 13 OCD patients without these symptoms (NCON), and 18 healthy controls. The CON group showed distinctively altered functional connectivity between the ventral striatum and the insula during both the resting and symptom-provoking conditions. Also, the connectivity strength between the ventral striatum and the insula significantly correlated with contamination/washing symptom severity. As common connectivity alterations of the whole OCD subjects, corticostriatal circuits involving the orbitofrontal and temporal cortices were again confirmed. To our knowledge, this is the first study that examined specific abnormalities in functional connectivity of contamination/washing symptom dimension OCD. The findings suggest limbic network dysfunctions to play a pivotal role in contamination/washing symptoms, possibly associated with emotionally salient error awareness. Our study sample allowed us to evaluate the corticostriatal network dysfunction underlying the contamination/washing symptom dimension, which leaves other major symptom dimensions to be explored in the future.

PMID: 24768985 [PubMed - indexed for MEDLINE]

Developmental changes in resting and functional cerebral blood flow and their relationship to the BOLD response.

Sat, 01/24/2015 - 17:30
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Developmental changes in resting and functional cerebral blood flow and their relationship to the BOLD response.

Hum Brain Mapp. 2014 Jul;35(7):3188-98

Authors: Moses P, DiNino M, Hernandez L, Liu TT

Abstract
Our understanding of cerebral blood flow (CBF) in the healthy developing brain has been limited due to the invasiveness of methods historically available for CBF measurement. Clinically based studies using radioactive tracers with children have focused on resting state CBF. Yet potential age-related changes in flow during stimulation may affect the blood oxygenation level dependent (BOLD) response used to investigate cognitive neurodevelopment. This study used noninvasive arterial spin labeling magnetic resonance imaging to compare resting state and stimulus-driven CBF between typically developing children 8 years of age, 12 years of age, and adults. Further, we acquired functional CBF and BOLD images simultaneously to examine their relationship during sensory stimulation. Analyses revealed age-related CBF differences during rest; the youngest group showed greater CBF than 12-year-olds or adults. During stimulation of the auditory cortex, younger children also showed a greater absolute increase in CBF than adults. However, the magnitude of CBF response above baseline was comparable between groups. Similarly, the amplitude of the BOLD response was stable across age. The combination of the 8 year olds' elevated CBF, both at rest and in response to stimulation, without elevation in the BOLD response suggests that additional physiological factors that also play a role in the BOLD effect, such as metabolic processes that are also elevated in this period, may offset the increased CBF in these children. Thus, CBF measurements reveal maturational differences in the hemodynamics underlying the BOLD effect in children despite the resemblance of the BOLD response between children and adults.

PMID: 24142547 [PubMed - indexed for MEDLINE]

Connectome-scale assessments of structural and functional connectivity in MCI.

Sat, 01/24/2015 - 17:30
Related Articles

Connectome-scale assessments of structural and functional connectivity in MCI.

Hum Brain Mapp. 2014 Jul;35(7):2911-23

Authors: Zhu D, Li K, Terry DP, Puente AN, Wang L, Shen D, Miller LS, Liu T

Abstract
Mild cognitive impairment (MCI) has received increasing attention not only because of its potential as a precursor for Alzheimer's disease but also as a predictor of conversion to other neurodegenerative diseases. Although MCI has been defined clinically, accurate and efficient diagnosis is still challenging. Although neuroimaging techniques hold promise, compared to commonly used biomarkers including amyloid plaques, tau protein levels and brain tissue atrophy, neuroimaging biomarkers are less well validated. In this article, we propose a connectomes-scale assessment of structural and functional connectivity in MCI via two independent multimodal DTI/fMRI datasets. We first used DTI-derived structural profiles to explore and tailor the most common and consistent landmarks, then applied them in a whole-brain functional connectivity analysis. The next step fused the results from two independent datasets together and resulted in a set of functional connectomes with the most differentiation power, hence named as "connectome signatures." Our results indicate that these "connectome signatures" have significantly high MCI-vs-controls classification accuracy, at more than 95%. Interestingly, through functional meta-analysis, we found that the majority of "connectome signatures" are mainly derived from the interactions among different functional networks, for example, cognition-perception and cognition-action domains, rather than from within a single network. Our work provides support for using functional "connectome signatures" as neuroimaging biomarkers of MCI.

PMID: 24123412 [PubMed - indexed for MEDLINE]

What has functional connectivity and chemical neuroimaging in fibromyalgia taught us about the mechanisms and management of 'centralized' pain?

Fri, 01/23/2015 - 15:30

What has functional connectivity and chemical neuroimaging in fibromyalgia taught us about the mechanisms and management of 'centralized' pain?

Arthritis Res Ther. 2014;16(5):425

Authors: Napadow V, Harris RE

Abstract
Research suggests that fibromyalgia is a central, widespread pain syndrome supported by a generalized disturbance in central nervous system pain processing. Over the past decades, multiple lines of research have identified the locus for many functional, chronic pain disorders to the central nervous system, and the brain. In recent years, brain neuroimaging techniques have heralded a revolution in our understanding of chronic pain, as they have allowed researchers to non-invasively (or minimally invasively) evaluate human patients suffering from various pain disorders. While many neuroimaging techniques have been developed, growing interest in two specific imaging modalities has led to significant contributions to chronic pain research. For instance, resting functional connectivity magnetic resonance imaging (fcMRI) is a recent adaptation of fMRI that examines intrinsic brain connectivity - defined as synchronous oscillations of the fMRI signal that occurs in the resting basal state. Proton magnetic resonance spectroscopy (1H-MRS) is a non-invasive magnetic resonance imaging technique that can quantify the concentration of multiple metabolites within the human brain. This review will outline recent applications of the complementary imaging techniques - fcMRI and 1H-MRS - to improve our understanding of fibromyalgia pathophysiology and how pharmacological and non-pharmacological therapies contribute to analgesia in these patients. A better understanding of the brain in chronic pain, with specific linkage as to which neural processes relate to spontaneous pain perception and hyperalgesia, will greatly improve our ability to develop novel therapeutics. Neuroimaging will play a growing role in the translational research approaches needed to make this a reality.

PMID: 25606591 [PubMed - in process]

Social network diversity and white matter microstructural integrity in humans.

Fri, 01/23/2015 - 15:30

Social network diversity and white matter microstructural integrity in humans.

Soc Cogn Affect Neurosci. 2015 Jan 19;

Authors: Molesworth T, Sheu LK, Cohen S, Gianaros PJ, Verstynen TD

Abstract
Diverse aspects of physical, affective, and cognitive health relate to social integration, reflecting engagement in social activities and identification with diverse roles within a social network. However, the mechanisms by which social integration interacts with the brain are unclear. In healthy adults (N=155) we tested the links between social integration and measures of white matter microstructure using diffusion tensor imaging. Across the brain, there was a predominantly positive association between a measure of white matter integrity, fractional anisotropy (FA), and social network diversity. This association was particularly strong in a region near the anterior corpus callosum and driven by a negative association with the radial component of the diffusion signal. This callosal region contained projections between bilateral prefrontal cortices, as well as cingulum and corticostriatal pathways. FA within this region was weakly associated with circulating levels of the inflammatory cytokine IL-6, but IL-6 did not mediate the social network and FA relationship. Finally, variation in FA indirectly mediated the relationship between social network diversity and intrinsic functional connectivity of medial corticostriatal pathways. These findings suggest that social integration relates to myelin integrity in humans, which may help explain the diverse aspects of health affected by social networks.

PMID: 25605966 [PubMed - as supplied by publisher]

Disease prediction based on functional connectomes using a scalable and spatially-informed support vector machine.

Fri, 01/23/2015 - 15:30
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Disease prediction based on functional connectomes using a scalable and spatially-informed support vector machine.

Neuroimage. 2014 Aug 1;96:183-202

Authors: Watanabe T, Kessler D, Scott C, Angstadt M, Sripada C

Abstract
Substantial evidence indicates that major psychiatric disorders are associated with distributed neural dysconnectivity, leading to a strong interest in using neuroimaging methods to accurately predict disorder status. In this work, we are specifically interested in a multivariate approach that uses features derived from whole-brain resting state functional connectomes. However, functional connectomes reside in a high dimensional space, which complicates model interpretation and introduces numerous statistical and computational challenges. Traditional feature selection techniques are used to reduce data dimensionality, but are blind to the spatial structure of the connectomes. We propose a regularization framework where the 6-D structure of the functional connectome (defined by pairs of points in 3-D space) is explicitly taken into account via the fused Lasso or the GraphNet regularizer. Our method only restricts the loss function to be convex and margin-based, allowing non-differentiable loss functions such as the hinge-loss to be used. Using the fused Lasso or GraphNet regularizer with the hinge-loss leads to a structured sparse support vector machine (SVM) with embedded feature selection. We introduce a novel efficient optimization algorithm based on the augmented Lagrangian and the classical alternating direction method, which can solve both fused Lasso and GraphNet regularized SVM with very little modification. We also demonstrate that the inner subproblems of the algorithm can be solved efficiently in analytic form by coupling the variable splitting strategy with a data augmentation scheme. Experiments on simulated data and resting state scans from a large schizophrenia dataset show that our proposed approach can identify predictive regions that are spatially contiguous in the 6-D "connectome space," offering an additional layer of interpretability that could provide new insights about various disease processes.

PMID: 24704268 [PubMed - indexed for MEDLINE]

Altered Spontaneous Brain Activity in Patients with Hemifacial Spasm: A Resting-State Functional MRI Study.

Thu, 01/22/2015 - 14:30

Altered Spontaneous Brain Activity in Patients with Hemifacial Spasm: A Resting-State Functional MRI Study.

PLoS One. 2015;10(1):e0116849

Authors: Tu Y, Wei Y, Sun K, Zhao W, Yu B

Abstract
Resting-state functional magnetic resonance imaging (fMRI) has been used to detect the alterations of spontaneous neuronal activity in various neurological and neuropsychiatric diseases, but rarely in hemifacial spasm (HFS), a nervous system disorder. We used resting-state fMRI with regional homogeneity (ReHo) analysis to investigate changes in spontaneous brain activity of patients with HFS and to determine the relationship of these functional changes with clinical features. Thirty patients with HFS and 33 age-, sex-, and education-matched healthy controls were included in this study. Compared with controls, HFS patients had significantly decreased ReHo values in left middle frontal gyrus (MFG), left medial cingulate cortex (MCC), left lingual gyrus, right superior temporal gyrus (STG) and right precuneus; and increased ReHo values in left precentral gyrus, anterior cingulate cortex (ACC), right brainstem, and right cerebellum. Furthermore, the mean ReHo value in brainstem showed a positive correlation with the spasm severity (r = 0.404, p = 0.027), and the mean ReHo value in MFG was inversely related with spasm severity in HFS group (r = -0.398, p = 0.028). This study reveals that HFS is associated with abnormal spontaneous brain activity in brain regions most involved in motor control and blinking movement. The disturbances of spontaneous brain activity reflected by ReHo measurements may provide insights into the neurological pathophysiology of HFS.

PMID: 25603126 [PubMed - as supplied by publisher]

Default mode network as a potential biomarker of chemotherapy-related brain injury.

Thu, 01/22/2015 - 14:30
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Default mode network as a potential biomarker of chemotherapy-related brain injury.

Neurobiol Aging. 2014 Sep;35 Suppl 2:S11-9

Authors: Kesler SR

Abstract
Chronic medical conditions and/or their treatments may interact with aging to alter or even accelerate brain senescence. Adult onset cancer, for example, is a disease associated with advanced aging and emerging evidence suggests a profile of subtle but diffuse brain injury following cancer chemotherapy. Breast cancer is currently the primary model for studying these "chemobrain" effects. Given the widespread changes to brain structure and function as well as the common impairment of integrated cognitive skills observed following breast cancer chemotherapy, it is likely that large-scale brain networks are involved. Default mode network (DMN) is a strong candidate considering its preferential vulnerability to aging and sensitivity to toxicity and disease states. Additionally, chemotherapy is associated with several physiological effects including increased inflammation and oxidative stress that are believed to elevate toxicity in the DMN. Biomarkers of DMN connectivity could aid in the development of treatments for chemotherapy-related cognitive decline.

PMID: 24913897 [PubMed - indexed for MEDLINE]

Large-scale Probabilistic Functional Modes from resting state fMRI.

Wed, 01/21/2015 - 13:00

Large-scale Probabilistic Functional Modes from resting state fMRI.

Neuroimage. 2015 Jan 15;

Authors: Harrison SJ, Woolrich MW, Robinson EC, Glasser MF, Beckmann CF, Jenkinson M, Smith SM

Abstract
It is well established that it is possible to observe spontaneous, highly structured, fluctuations in human brain activity from functional magnetic resonance imaging (fMRI) when the subject is 'at rest'. However, characterising this activity in an interpretable manner is still a very open problem. In this paper, we introduce a method for identifying modes of coherent activity from resting state fMRI (rfMRI) data. Our model characterises a mode as the outer product of a spatial map and a time course, constrained by the nature of both the between-subject variation and the effect of the hæmodynamic response function. This is presented as a probabilistic generative model within a variational framework that allows Bayesian inference, even on voxelwise rfMRI data. Furthermore, using this approach it becomes possible to infer distinct extended modes that are correlated with each other in space and time, a property which we believe is neuroscientifically desirable. We assess the performance of our model on both simulated data and high quality rfMRI data from the Human Connectome Project, and contrast its properties with those of both spatial and temporal independent component analysis (ICA). We show that our method is able to stably infer sets of modes with complex spatio-temporal interactions and spatial differences between subjects.

PMID: 25598050 [PubMed - as supplied by publisher]

Localized connectivity in depression: A meta-analysis of resting state functional imaging studies.

Wed, 01/21/2015 - 13:00

Localized connectivity in depression: A meta-analysis of resting state functional imaging studies.

Neurosci Biobehav Rev. 2015 Jan 15;

Authors: Iwabuchi SJ, Krishnadas R, Li C, Auer D, Radua J, Palaniyappan L

Abstract
IWABUCHI, S.J., R. Krishnadas, C. Li, D. Auer, J. Radua and L. Palaniyappan. Localized connectivity in depression: A meta-analysis of resting state functional imaging studies. NEUROSCI BIOBEHAV REV XX(X) XXX-XXX, 201X.-Resting-state fMRI studies investigating the pathophysiology of depression have identified prominent abnormalities in large-scale brain networks. However, it is unclear if localized dysfunction of specialized brain regions contribute to network-level abnormalities. We employed a meta-analytical procedure and reviewed studies conducted in China investigating changes in regional homogeneity (ReHo), a measure of localized intraregional connectivity, from resting-state fMRI in depression. Exploiting the statistical power gained from pooled analysis, we also investigated the effects of age, gender, illness duration and treatment on ReHo. The medial prefrontal cortex (MPFC) showed the most robust and reliable increase in ReHo in depression, with greater abnormality in medication-free patients with multiple episodes. Brain networks that relate to this region have been identified previously to show aberrant connectivity in depression, and we propose that the localized neuronal inefficiency of MPFC exists alongside wider network level disruptions involving this region.

PMID: 25597656 [PubMed - as supplied by publisher]

Increased interhemispheric functional connectivity in college students with non-clinical depressive symptoms in resting state.

Tue, 01/20/2015 - 18:30

Increased interhemispheric functional connectivity in college students with non-clinical depressive symptoms in resting state.

Neurosci Lett. 2015 Jan 14;

Authors: We XH, Ren JL, Liu WH, Yang RM, Xu XD, Liu J, Guo YM, Yu S, Lai LS, Xie YQ, Jiang XQ

Abstract
The underlying neural basis of non-clinical depressive symptoms (nCDSs) remains unclear. Interhemispheric functional connectivity has been suggested as one of the most robust characteristics of brain's intrinsic functional architecture. Here, we investigated the functional connectivity between homotopic points in the brain using the voxel-mirrored homotopic connectivity (VMHC) approach. We performed VMHC analysis on resting-state functional magnetic resonance imaging (rs-fMRI) data from 17 individuals with nCDSs and 20 healthy controls (HCs) who were enrolled from a sample of 1105 college students. We found increased VMHCs in the bilateral posterior cerebellum and fusiform gyrus in nCDSs subjects compared with HCs. Furthermore, receiver operating characteristic (ROC) curves indicated that VMHC values in the posterior cerebellum lobes could use to differente nCDSs from HCs [area under the curve (AUC), 0.756; p<0.01]. We suggest increased VMHCs indicate a possible compensatory mechanism involved in the pathophysiology of nCDSs. VMHC values of the posterior cerebellum lobes might serve as a reliable biomarker for identifying nCDSs.

PMID: 25596443 [PubMed - as supplied by publisher]

Attentional load modulates large-scale functional brain connectivity beyond the core attention networks.

Tue, 01/20/2015 - 18:30

Attentional load modulates large-scale functional brain connectivity beyond the core attention networks.

Neuroimage. 2015 Jan 13;

Authors: Alnæs D, Kaufmann T, Richard G, Duff EP, Sneve MH, Endestad T, Nordvik JE, Andreassen OA, Smith SM, Westlye LT

Abstract
In line with the notion of a continuously active and dynamic brain, functional networks identified during rest correspond with those revealed by task-fMRI. Characterizing the dynamic cross-talk between these network nodes is key to understanding the successful implementation of effortful cognitive processing in healthy individuals and its breakdown in a variety of conditions involving aberrant brain biology and cognitive dysfunction. We employed advanced network modeling on fMRI data collected during a task involving sustained attentive tracking of objects at two load levels and during rest. Using multivariate techniques, we demonstrate that attentional load levels can be significantly discriminated, and from a resting-state condition, the accuracy approaches 100%, by means of estimates of between-node functional connectivity. Several network edges were modulated during task engagement: The dorsal attention network increased connectivity with a visual node, while decreasing connectivity with motor and sensory nodes. Also, we observed a decoupling between left and right hemisphere dorsal visual streams. These results support the notion of dynamic network reconfigurations based on attentional effort. No simple correspondence between node signal amplitude change and node connectivity modulations was found, thus network modeling provides novel information beyond what is revealed by conventional task-fMRI analysis. The current decoding of attentional states confirms that edge connectivity contains highly predictive information about the mental state of the individual, and the approach shows promise for the utilization in clinical contexts.

PMID: 25595500 [PubMed - as supplied by publisher]