New resting-state fMRI related studies at PubMed

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Resting-state connectivity and executive functions after pediatric arterial ischemic stroke.

Wed, 11/22/2017 - 15:20

Resting-state connectivity and executive functions after pediatric arterial ischemic stroke.

Neuroimage Clin. 2018;17:359-367

Authors: Kornfeld S, Yuan R, Biswal BB, Grunt S, Kamal S, Delgado Rodríguez JA, Regényi M, Wiest R, Weisstanner C, Kiefer C, Steinlin M, Everts R

Abstract
Background: The aim of this study was to compare the relationship between core executive functions and frontoparietal network connections at rest between children who had suffered an arterial ischemic stroke and typically developing peers.
Methods: Children diagnosed with arterial ischemic stroke more than two years previously and typically developing controls were included. Executive function (EF) measures comprised inhibition (Go-NoGo task), fluency (category fluency task), processing speed (processing speed tasks), divided attention, working memory (letter-number sequencing), conceptual reasoning (matrices) and EF in everyday life (questionnaire). High-resolution T1-weighted magnetic resonance (MR) structural images and resting-state functional MR imaging were acquired. Independent component analysis was used to identify the frontoparietal network. Functional connections were obtained through correlation matrices; associations between cognitive measures and functional connections through Pearson's correlations.
Results: Twenty participants after stroke (7 females; mean age 16.0 years) and 22 controls (13 females; mean age 14.8 years) were examined. Patients and controls performed within the normal range in all executive tasks. Patients who had had a stroke performed significantly less well in tests of fluency, processing speed and conceptual reasoning than controls. Resting-state functional connectivity between the left and right inferior parietal lobe was significantly reduced in patients after pediatric stroke. Fluency, processing speed and perceptual reasoning correlated positively with the interhemispheric inferior parietal lobe connection in patients and controls.
Conclusion: Decreased interhemispheric connections after stroke in childhood may indicate a disruption of typical interhemispheric interactions relating to executive functions. The present results emphasize the relationship between functional organization of the brain at rest and cognitive processes.

PMID: 29159048 [PubMed - in process]

Identifying functional network changing patterns in individuals at clinical high-risk for psychosis and patients with early illness schizophrenia: A group ICA study.

Wed, 11/22/2017 - 15:20

Identifying functional network changing patterns in individuals at clinical high-risk for psychosis and patients with early illness schizophrenia: A group ICA study.

Neuroimage Clin. 2018;17:335-346

Authors: Du Y, Fryer SL, Lin D, Sui J, Yu Q, Chen J, Stuart B, Loewy RL, Calhoun VD, Mathalon DH

Abstract
Although individuals at clinical high risk (CHR) for psychosis exhibit a psychosis-risk syndrome involving attenuated forms of the positive symptoms typical of schizophrenia (SZ), it remains unclear whether their resting-state brain intrinsic functional networks (INs) show attenuated or qualitatively distinct patterns of functional dysconnectivity relative to SZ patients. Based on resting-state functional magnetic imaging data from 70 healthy controls (HCs), 53 CHR individuals (among which 41 subjects were antipsychotic medication-naive), and 58 early illness SZ (ESZ) patients (among which 53 patients took antipsychotic medication) within five years of illness onset, we estimated subject-specific INs using a novel group information guided independent component analysis (GIG-ICA) and investigated group differences in INs. We found that when compared to HCs, both CHR and ESZ groups showed significant differences, primarily in default mode, salience, auditory-related, visuospatial, sensory-motor, and parietal INs. Our findings suggest that widespread INs were diversely impacted. More than 25% of voxels in the identified significant discriminative regions (obtained using all 19 possible changing patterns excepting the no-difference pattern) from six of the 15 interrogated INs exhibited monotonically decreasing Z-scores (in INs) from the HC to CHR to ESZ, and the related regions included the left lingual gyrus of two vision-related networks, the right postcentral cortex of the visuospatial network, the left thalamus region of the salience network, the left calcarine region of the fronto-occipital network and fronto-parieto-occipital network. Compared to HCs and CHR individuals, ESZ patients showed both increasing and decreasing connectivity, mainly hypo-connectivity involving 15% of the altered voxels from four INs. The left supplementary motor area from the sensory-motor network and the right inferior occipital gyrus in the vision-related network showed a common abnormality in CHR and ESZ groups. Some brain regions also showed a CHR-unique alteration (primarily the CHR-increasing connectivity). In summary, CHR individuals generally showed intermediate connectivity between HCs and ESZ patients across multiple INs, suggesting that some dysconnectivity patterns evident in ESZ predate psychosis in attenuated form during the psychosis risk stage. Hence, these connectivity measures may serve as possible biomarkers to predict schizophrenia progression.

PMID: 29159045 [PubMed - in process]

Disruption of default mode network dynamics in acute and chronic pain states.

Wed, 11/22/2017 - 15:20

Disruption of default mode network dynamics in acute and chronic pain states.

Neuroimage Clin. 2018;17:222-231

Authors: Alshelh Z, Marciszewski KK, Akhter R, Di Pietro F, Mills EP, Vickers ER, Peck CC, Murray GM, Henderson LA

Abstract
It has been proposed that pain competes with other attention-demanding stimuli for cognitive resources, and many chronic pain patients display significant attention and mental flexibility deficits. These alterations may result from disruptions in the functioning of the default mode network (DMN) which plays a critical role in attention, memory, prospection and self-processing, and recent investigations have found alterations in DMN function in multiple chronic pain conditions. Whilst it has been proposed that these DMN alterations are a characteristic of pain that is chronic in nature, we recently reported altered oscillatory activity in the DMN during an acute, 5  minute noxious stimulus in healthy control subjects. We therefore hypothesize that altered DMN activity patterns will not be restricted to those in chronic pain but instead will also occur in healthy individuals during tonic noxious stimuli. We used functional magnetic resonance imaging to measure resting state infra-slow oscillatory activity and functional connectivity in patients with chronic orofacial pain at rest and in healthy controls during a 20-minute tonic pain stimulus. We found decreases in oscillatory activity in key regions of the DMN in patients with chronic pain, as well as in healthy controls during tonic pain in addition to changes in functional connectivity between the posterior cingulate cortex and areas of the DMN in both groups. The results show that similar alterations in DMN function occur in healthy individuals during acute noxious stimuli as well as in individuals with chronic pain. These DMN changes may reflect the presence of pain per se and may underlie alterations in attentional processes that occur in the presence of pain.

PMID: 29159039 [PubMed - in process]

Dynamic effective connectivity in resting state fMRI.

Wed, 11/22/2017 - 15:20

Dynamic effective connectivity in resting state fMRI.

Neuroimage. 2017 Nov 17;:

Authors: Park HJ, Friston K, Pae C, Park B, Razi A

Abstract
Context-sensitive and activity-dependent fluctuations in connectivity underlie functional integration in the brain and have been studied widely in terms of synaptic plasticity, learning and condition-specific (e.g., attentional) modulations of synaptic efficacy. This dynamic aspect of brain connectivity has recently attracted a lot of attention in the resting state fMRI community. To explain dynamic functional connectivity in terms of directed effective connectivity among brain regions, we introduce a novel method to identify dynamic effective connectivity using spectral dynamic causal modelling (spDCM). We used parametric empirical Bayes (PEB) to model fluctuations in directed coupling over consecutive windows of resting state fMRI time series. Hierarchical PEB can model random effects on connectivity parameters at the second (between-window) level given connectivity estimates from the first (within-window) level. In this work, we used a discrete cosine transform basis set or eigenvariates (i.e., expression of principal components) to model fluctuations in effective connectivity over windows. We evaluated the ensuing dynamic effective connectivity in terms of the consistency of baseline connectivity within default mode network (DMN), using the resting state fMRI from Human Connectome Project (HCP). To model group-level baseline and dynamic effective connectivity for DMN, we extended the PEB approach by conducting a multilevel PEB analysis of between-session and between-subject group effects. Model comparison clearly spoke to dynamic fluctuations in effective connectivity - and the dynamic functional connectivity these changes explain. Furthermore, baseline effective connectivity was consistent across independent sessions - and notably more consistent than estimates based upon conventional models. This work illustrates the advantage of hierarchical modelling with spDCM, in characterizing the dynamics of effective connectivity.

PMID: 29158202 [PubMed - as supplied by publisher]

Abnormal amplitude of low-frequency fluctuations associated with rapid-eye movement in chronic primary insomnia patients.

Wed, 11/22/2017 - 15:20
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Abnormal amplitude of low-frequency fluctuations associated with rapid-eye movement in chronic primary insomnia patients.

Oncotarget. 2017 Oct 17;8(49):84877-84888

Authors: Ran Q, Chen J, Li C, Wen L, Yue F, Shu T, Mi J, Wang G, Zhang L, Gao D, Zhang D

Abstract
Purpose: Chronic primary insomnia (CPI) is the most prevalent sleep disorder worldwide. CPI manifests as difficulties in sleep onset, maintaining sleep, prolonged sleep latency, and daytime impairment and is often accompanied by cognitive problems such as poor academic performance, poor attention, and decreased memory. The most popular explanation of insomnia is hyperarousal or increased activities of neurons. Rapid eye movement (REM) sleep detected by polysomnography (PSG) exhibits a positive relationship with brain homeostasis and can be helpful for optimally preparing an organism for emotional and social function. Limited work has been performed to explore brain function of insomnia patients in combination with PSG analysis.
Results: We observed increased ALFF within areas related to hyperarousal such as the midbrain and bilateral extra-nucleus, whereas decreased ALFF was observed within areas associated with memory and attention involving the parietal and occipital lobule and others. Furthermore, the altered ALFF was associated with the duration of insomnia, sleep efficiency, duration of REM, latency of RME and ratio of REM.
Materials and Methods: In this study, we recruited twenty-five CPI patients and twenty-five normal sleep (NS) volunteers as a control group to investigate the amplitude of low-frequency fluctuations (ALFF) and the correlation between those altered ALFF regions through resting-state fMRI and PSG data.
Conclusions: These findings suggest that hyperarousal reflected by ALFF abnormality within brain areas related to cognition and emotion in insomnia associated with REM sleep.

PMID: 29156690 [PubMed]

A comprehensive analysis of resting state fMRI measures to classify individual patients with Alzheimer's disease.

Tue, 11/21/2017 - 14:40

A comprehensive analysis of resting state fMRI measures to classify individual patients with Alzheimer's disease.

Neuroimage. 2017 Nov 14;:

Authors: de Vos F, Koini M, Schouten TM, Seiler S, van der Grond J, Lechner A, Schmidt R, de Rooij M, Rombouts SARB

Abstract
Alzheimer's disease (AD) patients show altered patterns of functional connectivity (FC) on resting state functional magnetic resonance imaging (RSfMRI) scans. It is yet unclear which RSfMRI measures are most informative for the individual classification of AD patients. We investigated this using RSfMRI scans from 77 AD patients (MMSE = 20.4 ± 4.5) and 173 controls (MMSE = 27.5 ± 1.8). We calculated i) FC matrices between resting state components as obtained with independent component analysis (ICA), ii) the dynamics of these FC matrices using a sliding window approach, iii) the graph properties (e.g., connection degree, and clustering coefficient) of the FC matrices, and iv) we distinguished five FC states and administered how long each subject resided in each of these five states. Furthermore, for each voxel we calculated v) FC with 10 resting state networks using dual regression, vi) FC with the hippocampus, vii) eigenvector centrality, and viii) the amplitude of low frequency fluctuations (ALFF). These eight measures were used separately as predictors in an elastic net logistic regression, and combined in a group lasso logistic regression model. We calculated the area under the receiver operating characteristic curve plots (AUC) to determine classification performance. The AUC values ranged between 0.51 and 0.84 and the highest were found for the FC matrices (0.82), FC dynamics (0.84) and ALFF (0.82). The combination of all measures resulted in an AUC of 0.85. We show that it is possible to obtain moderate to good AD classification using RSfMRI scans. FC matrices, FC dynamics and ALFF are most discriminative and the combination of all the resting state measures improves classification accuracy slightly.

PMID: 29155080 [PubMed - as supplied by publisher]

Brain functional connectivity in headache disorders: A narrative review of MRI investigations.

Tue, 11/21/2017 - 14:40

Brain functional connectivity in headache disorders: A narrative review of MRI investigations.

J Cereb Blood Flow Metab. 2017 Jan 01;:271678X17740794

Authors: Chong CD, Schwedt TJ, Hougaard A

Abstract
Resting-state functional magnetic resonance imaging (rs-fMRI) is used to interrogate the functional connectivity and network organization amongst brain regions. Functional connectivity is determined by measuring the extent of synchronization in the spontaneous fluctuations of blood oxygenation level dependent (BOLD) signal. Here, we review current rs-fMRI studies in headache disorders including migraine, trigeminal autonomic cephalalgias, and medication overuse headache. We discuss (1) brain network alterations that are shared amongst the different headache disorders and (2) network abnormalities distinct to each headache disorder. In order to focus the section on migraine, the headache disorder that has been most extensively studied, we chose to include articles that interrogated functional connectivity: (i) during the attack phase; (ii) in migraine patients with aura compared to migraine patients without aura; and (iii) of regions within limbic, sensory, motor, executive and default mode networks and those which participate in multisensory integration. The results of this review show that headache disorders are associated with atypical functional connectivity of regions associated with pain processing as well as atypical functional connectivity of multiple core resting state networks such as the salience, sensorimotor, executive, attention, limbic, visual, and default mode networks.

PMID: 29154684 [PubMed - as supplied by publisher]

SPARCL1 Accelerates Symptom Onset in Alzheimer's Disease and Influences Brain Structure and Function During Aging.

Tue, 11/21/2017 - 14:40

SPARCL1 Accelerates Symptom Onset in Alzheimer's Disease and Influences Brain Structure and Function During Aging.

J Alzheimers Dis. 2017 Nov 16;:

Authors: Seddighi S, Varma VR, An Y, Varma S, Beason-Held LL, Tanaka T, Kitner-Triolo MH, Kraut MA, Davatzikos C, Thambisetty M

Abstract
We recently reported that alpha-2 macroglobulin (A2M) is a biomarker of neuronal injury in Alzheimer's disease (AD) and identified a network of nine genes co-expressed with A2M in the brain. This network includes the gene encoding SPARCL1, a protein implicated in synaptic maintenance. Here, we examine whether SPARCL1 is associated with longitudinal changes in brain structure and function in older individuals at risk for AD in the Baltimore Longitudinal Study of Aging. Using data from the Gene-Tissue Expression Project, we first identified two single nucleotide polymorphisms (SNPs), rs9998212 and rs7695558, associated with lower brain SPARCL1 gene expression. We then analyzed longitudinal trajectories of cognitive performance in 591 participants who remained cognitively normal (average follow-up interval: 11.8 years) and 129 subjects who eventually developed MCI or AD (average follow-up interval: 9.4 years). Cognitively normal minor allele carriers of rs7695558 who developed incident AD showed accelerated memory loss prior to disease onset. Next, we compared longitudinal changes in brain volumes (MRI; n = 120 participants; follow-up = 6.4 years; 826 scans) and resting-state cerebral blood flow (rCBF; 15O-water PET; n = 81 participants; follow-up = 7.7 years; 664 scans) in cognitively normal participants. Cognitively normal minor allele carriers of rs9998212 showed accelerated atrophy in several global, lobar, and regional brain volumes. Minor allele carriers of both SNPs showed longitudinal changes in rCBF in several brain regions, including those vulnerable to AD pathology. Our findings suggest that SPARCL1 accelerates AD pathogenesis and thus link neuroinflammation with widespread changes in brain structure and function during aging.

PMID: 29154276 [PubMed - as supplied by publisher]

The dynamic characteristics of the anterior cingulate cortex in resting-state fMRI of patients with depression.

Tue, 11/21/2017 - 14:40

The dynamic characteristics of the anterior cingulate cortex in resting-state fMRI of patients with depression.

J Affect Disord. 2017 Nov 08;227:391-397

Authors: Zheng H, Li F, Bo Q, Li X, Yao L, Yao Z, Wang C, Wu X

Abstract
BACKGROUND: The anterior cingulate cortex (ACC) is part of the limbic system of the brain. It is a bridge between attentional and emotional processing, which is responsible for the integration of visceral, attentional, and affective information. Lesioning of the ACC, which produces striking changes, is used to treat major depression disorder (MDD). Moreover, the brain dynamically integrates and coordinates functions of its different subparts to realize its cognitive capability. Hence, the spatio-temporal community distribution of the ACC is necessary to completely understand MDD.
METHODS: First, community structure detection was used to reveal the community distribution of brain regions. Thereafter, the flexibility, i.e., the frequency of community assignment changes of the ACC in such a community, and the module allegiance matrix (MAM) between the ACC and other brain regions, were analyzed.
RESULTS: Our analysis demonstrated significant differences in the distribution of community assignment and flexibility of the ACC in MDD, compared to healthy controls (HC). The results also showed that the pairwise values of the MAMs between the ACC and the amygdala, insula, precuneus, and thalamus were significantly lower in patients with MDD compared to those in HC.
LIMITATIONS: The data collected is subject to patient-specific noise because (1) the medication effect varies from patient to patient, and (2) with most fMRI studies, the thoughts of the participants during imaging are difficult to control.
CONCLUSION: ACC exhibits abnormal flexibility in community structures in MDD. The pairwise abnormal entries in the MAM for the ACC with four other brain regions, i.e., amygdala, insula, precuneus, and thalamus, quantified the role played by the ACC in MDD.

PMID: 29154155 [PubMed - as supplied by publisher]

Decreased connectivity and increased BOLD complexity in the default mode network in individuals with chronic fatigue syndrome.

Tue, 11/21/2017 - 14:40

Decreased connectivity and increased BOLD complexity in the default mode network in individuals with chronic fatigue syndrome.

Brain Connect. 2017 Nov 20;:

Authors: Shan ZY, Finegan K, Bhuta S, Ireland T, Staines DR, Marshall-Gradisnik SM, Barnden LR

Abstract
The chronic fatigue syndrome / myalgic encephalomyelitis (CFS) is a debilitating disease with unknown pathophysiology and no diagnostic test. This study investigated the default mode network (DMN) in order to understand the pathophysiology of CFS and to identify potential biomarkers. Using functional MRI (fMRI) collected from 72 subjects (45 CFS and 27 controls) with a temporal resolution of 0.798s, we evaluated the default mode network using static functional connectivity (FC), dynamic functional connectivity (DFC) and DFC complexity, blood oxygenation level dependent (BOLD) activation maps and complexity of activity. General linear model (GLM) univariate analysis was used for inter group comparison to account for age and gender differences. Hierarchical regression analysis was used to test whether fMRI measures could be used to explain variances of health scores. BOLD signals in the posterior cingulate cortex (PCC), the driving hub in the DMN, were more complex in CFS in both resting state and task (P < 0.05). The FCs between medial prefrontal cortex (mPFC) and both inferior parietal lobules (IPLs) were weaker (P < 0.05) during resting state, while during task mPFC - left IPL and mPFC - PCC were weaker (P < 0.05). The DFCs between the DMN hubs were more complex in CFS (P < 0.05) during task. Each of these differences accounted for 7 - 11% variability of health scores. This study showed that DMN activity is more complex and less coordinated in CFS, suggesting brain network analysis could be potential used as a diagnostic biomarker for CFS.

PMID: 29152994 [PubMed - as supplied by publisher]

Reduced orbitofrontal-thalamic functional connectivity related to suicidal ideation in patients with major depressive disorder.

Sun, 11/19/2017 - 12:40
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Reduced orbitofrontal-thalamic functional connectivity related to suicidal ideation in patients with major depressive disorder.

Sci Rep. 2017 Nov 17;7(1):15772

Authors: Kim K, Kim SW, Myung W, Han CE, Fava M, Mischoulon D, Papakostas GI, Seo SW, Cho H, Seong JK, Jeon HJ

Abstract
Despite recent developments in neuroimaging, alterations of brain functional connectivity in major depressive disorder (MDD) patients with suicidal ideation are poorly understood. This study investigated specific changes of suicidal ideation in functional connectivity of MDD patients. Whole brain functional connectivity in 46 patients with MDD (23 with suicidal ideation and 23 without) and 36 age- and gender- matched healthy controls were compared using resting-state functional Magnetic Resonance Imaging (fMRI) analyzed with network-based statistics (NBS) and graph-theoretical methods. Decreased functional connectivity in a characterized sub-network was observed in patients with MDD and suicidal ideation (FDR-adjusted p < 0.05). The sub-network included the regions of the fronto-thalamic circuits in the left hemisphere. The network measures of the left superior frontal gyrus, pars orbitalis (r = -0.40, p = 0.009), left thalamus (r = -0.41, p = 0.009), and right thalamus (r = -0.51, p = -0.002) were shown, through graph theoretical analysis, to be significantly negatively correlated with severity of suicidal ideation. The reduced functional connectivity in left orbitofrontal-both thalamic regions with suicidal ideation in MDD were inversely proportional to the severity of suicidality independent from depression severity. These findings suggest problems with decision-making and information integration in MDD patients with suicidal ideation.

PMID: 29150619 [PubMed - in process]

Functional connectivity of the vigilant-attention network in children and adolescents with attention-deficit/hyperactivity disorder.

Sun, 11/19/2017 - 12:40
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Functional connectivity of the vigilant-attention network in children and adolescents with attention-deficit/hyperactivity disorder.

Brain Cogn. 2017 Nov 14;:

Authors: Zepf FD, Bubenzer-Busch S, Runions KC, Rao P, Wong JWY, Mahfouda S, Morandini HAE, Stewart RM, Moore JK, Biskup CS, Eickhoff SB, Fink GR, Langner R

Abstract
The ability to maintain attention to simple tasks (i.e., vigilant attention, VA) is often impaired in attention-deficit/hyperactivity disorder (ADHD), but the underlying pathophysiological mechanisms at the brain network level are not clear yet. We therefore investigated ADHD-related differences in resting-state functional connectivity within a meta-analytically defined brain network of 14 distinct regions subserving VA (comprising 91 connections in total), as well as the association of connectivity with markers of behavioural dysfunction in 17 children (age range: 9-14 years) with a diagnosis of ADHD and 21 age-matched neurotypical controls. Our analyses revealed selective, rather than global, differences in the intrinsic coupling between nodes of the VA-related brain network in children with ADHD, relative to controls. In particular, ADHD patients showed substantially diminished intrinsic coupling for 7 connections and increased coupling for 4 connections, with many differences involving connectivity with the anterior insula. Moreover, connectivity strength of several aberrant connections was found to be associated with core aspects of ADHD symptomatology, such as poor attention, difficulties with social functioning, and impaired cognitive control, attesting to the behavioural relevance of specific connectivity differences observed in the resting state.

PMID: 29150311 [PubMed - as supplied by publisher]

Resting-state fMRI in sleeping infants more closely resembles adult sleep than adult wakefulness.

Sat, 11/18/2017 - 11:40

Resting-state fMRI in sleeping infants more closely resembles adult sleep than adult wakefulness.

PLoS One. 2017;12(11):e0188122

Authors: Mitra A, Snyder AZ, Tagliazucchi E, Laufs H, Elison J, Emerson RW, Shen MD, Wolff JJ, Botteron KN, Dager S, Estes AM, Evans A, Gerig G, Hazlett HC, Paterson SJ, Schultz RT, Styner MA, Zwaigenbaum L, IBIS Network, Schlaggar BL, Piven J, Pruett JR, Raichle M

Abstract
Resting state functional magnetic resonance imaging (rs-fMRI) in infants enables important studies of functional brain organization early in human development. However, rs-fMRI in infants has universally been obtained during sleep to reduce participant motion artifact, raising the question of whether differences in functional organization between awake adults and sleeping infants that are commonly attributed to development may instead derive, at least in part, from sleep. This question is especially important as rs-fMRI differences in adult wake vs. sleep are well documented. To investigate this question, we compared functional connectivity and BOLD signal propagation patterns in 6, 12, and 24 month old sleeping infants with patterns in adult wakefulness and non-REM sleep. We find that important functional connectivity features seen during infant sleep closely resemble those seen during adult sleep, including reduced default mode network functional connectivity. However, we also find differences between infant and adult sleep, especially in thalamic BOLD signal propagation patterns. These findings highlight the importance of considering sleep state when drawing developmental inferences in infant rs-fMRI.

PMID: 29149191 [PubMed - in process]

GABA concentrations in the anterior temporal lobe predict human semantic processing.

Sat, 11/18/2017 - 11:40

GABA concentrations in the anterior temporal lobe predict human semantic processing.

Sci Rep. 2017 Nov 16;7(1):15748

Authors: Jung J, Williams SR, Sanaei Nezhad F, Lambon Ralph MA

Abstract
There is now considerable convergent evidence from multiple methodologies and clinical studies that the human anterior temporal lobe (ATL) is a semantic representational hub. However, the neurochemical nature of the ATL in the semantic processing remains unclear. The current study investigated the neurochemical mechanism underlying semantic processing in the ATL. We combined functional magnetic resonance imaging (fMRI) with resting-state magnetic resonance spectroscopy (MRS) to measure task-related blood-oxygen level-dependent (BOLD) signal changes during sematic processing and resting-state GABA concentrations in the ATL. Our combined fMRI and MRS investigation showed that the stronger ATL BOLD response induced by the semantic task, the lower GABA concentration in the same region. Moreover, individuals with higher GABA concentration in the ATL showed better semantic performance and stronger BOLD-related fluctuations in the semantic network. Our data demonstrated that the resting-state GABA concentration predicts neural changes in the human ATL and task performance during semantic processing. Our findings indicate that individuals with higher GABA may have a more efficient semantic processing leading to better task performance and imply that GABAergic neurochemical processes are potentially crucial to the neurobiological contribution of the ATL to semantic cognition.

PMID: 29146995 [PubMed - in process]

Causal Mapping of Emotion Networks in the Human Brain: Framework and Initial Findings.

Sat, 11/18/2017 - 11:40

Causal Mapping of Emotion Networks in the Human Brain: Framework and Initial Findings.

Neuropsychologia. 2017 Nov 13;:

Authors: Dubois J, Oya H, Tyszka JM, Howard M, Eberhardt F, Adolphs R

Abstract
Emotions involve many cortical and subcortical regions, prominently including the amygdala. It remains unknown how these multiple network components interact, and it remains unknown how they cause the behavioral, autonomic, and experiential effects of emotions. Here we describe a framework for combining a novel technique, concurrent electrical stimulation with fMRI (es-fMRI), together with a novel analysis, inferring causal structure from fMRI data (causal discovery). We outline a research program for investigating human emotion with these new tools, and provide initial findings from two large resting-state datasets as well as case studies in neurosurgical patients with electrical stimulation of the amygdala. The overarching goal is to use causal discovery methods on fMRI data to infer causal graphical models of how brain regions interact, and then to further constrain these models with direct stimulation of specific brain regions and concurrent fMRI. We conclude by discussing limitations and future extensions. The approach could yield anatomical hypotheses about brain connectivity, motivate rational strategies for treating mood disorders with deep brain stimulation, and could be extended to animal studies that use combined optogenetic fMRI.

PMID: 29146466 [PubMed - as supplied by publisher]

Spontaneous neural activity differences in posttraumatic stress disorder: A quantitative resting-state meta-analysis and fMRI validation.

Fri, 11/17/2017 - 16:40

Spontaneous neural activity differences in posttraumatic stress disorder: A quantitative resting-state meta-analysis and fMRI validation.

Hum Brain Mapp. 2017 Nov 15;:

Authors: Disner SG, Marquardt CA, Mueller BA, Burton PC, Sponheim SR

Abstract
Identifying the pathophysiology of posttraumatic stress disorder (PTSD) is a critical step toward reducing its debilitating impact. Spontaneous neural activity, measured at rest using various neuroimaging techniques (e.g., regional homogeneity [ReHo], amplitude of low frequency fluctuations [ALFF]), can provide insight about baseline neurobiological factors influencing sensory, cognitive, or behavioral processes associated with PTSD. The present study used activation likelihood estimation (ALE) to conduct the largest-to-date quantitative meta-analysis of spontaneous neural activity in PTSD, including 457 PTSD cases, 292 trauma-exposed controls (TECs), and 293 non-traumatized controls (NTCs) across 22 published studies. Five regions-of-interest (ROIs) were identified where activity differed between PTSD cases and controls: one when compared to all controls (left globus pallidus), two when compared to TECs (left inferior parietal lobule [IPL] and right lingual gyrus), and two when compared to NTCs (left amygdala and right caudate head). To corroborate these results, a second analysis was conducted using resting-state functional magnetic resonance imaging on an independent sample of 205 previously-deployed US military veterans. In this analysis, converging evidence from ReHo and ALFF showed that spontaneous neural activity in the left IPL alone was positively correlated with PTSD symptom severity. This result is consistent with theoretical accounts that link left IPL activity with PTSD-relevant processes such as processing of emotional stimuli (e.g., fearful faces) and the extent that attention is captured by salient autobiographical memories. By modeling the neurobiological correlates of PTSD, we can increase our understanding of this debilitating disorder and guide the development of future clinical innovations.

PMID: 29143411 [PubMed - as supplied by publisher]

Chronnectome fingerprinting: Identifying individuals and predicting higher cognitive functions using dynamic brain connectivity patterns.

Fri, 11/17/2017 - 16:40

Chronnectome fingerprinting: Identifying individuals and predicting higher cognitive functions using dynamic brain connectivity patterns.

Hum Brain Mapp. 2017 Nov 15;:

Authors: Liu J, Liao X, Xia M, He Y

Abstract
The human brain is a large, interacting dynamic network, and its architecture of coupling among brain regions varies across time (termed the "chronnectome"). However, very little is known about whether and how the dynamic properties of the chronnectome can characterize individual uniqueness, such as identifying individuals as a "fingerprint" of the brain. Here, we employed multiband resting-state functional magnetic resonance imaging data from the Human Connectome Project (N = 105) and a sliding time-window dynamic network analysis approach to systematically examine individual time-varying properties of the chronnectome. We revealed stable and remarkable individual variability in three dynamic characteristics of brain connectivity (i.e., strength, stability, and variability), which was mainly distributed in three higher order cognitive systems (i.e., default mode, dorsal attention, and fronto-parietal) and in two primary systems (i.e., visual and sensorimotor). Intriguingly, the spatial patterns of these dynamic characteristics of brain connectivity could successfully identify individuals with high accuracy and could further significantly predict individual higher cognitive performance (e.g., fluid intelligence and executive function), which was primarily contributed by the higher order cognitive systems. Together, our findings highlight that the chronnectome captures inherent functional dynamics of individual brain networks and provides implications for individualized characterization of health and disease.

PMID: 29143409 [PubMed - as supplied by publisher]

Hippocampal-caudate nucleus interactions support exceptional memory performance.

Thu, 11/16/2017 - 15:40
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Hippocampal-caudate nucleus interactions support exceptional memory performance.

Brain Struct Funct. 2017 Nov 14;:

Authors: Müller NCJ, Konrad BN, Kohn N, Muñoz-López M, Czisch M, Fernández G, Dresler M

Abstract
Participants of the annual World Memory Championships regularly demonstrate extraordinary memory feats, such as memorising the order of 52 playing cards in 20 s or 1000 binary digits in 5 min. On a cognitive level, memory athletes use well-known mnemonic strategies, such as the method of loci. However, whether these feats are enabled solely through the use of mnemonic strategies or whether they benefit additionally from optimised neural circuits is still not fully clarified. Investigating 23 leading memory athletes, we found volumes of their right hippocampus and caudate nucleus were stronger correlated with each other compared to matched controls; both these volumes positively correlated with their position in the memory sports world ranking. Furthermore, we observed larger volumes of the right anterior hippocampus in athletes. Complementing these structural findings, on a functional level, fMRI resting state connectivity of the anterior hippocampus to both the posterior hippocampus and caudate nucleus predicted the athletes rank. While a competitive interaction between hippocampus and caudate nucleus is often observed in normal memory function, our findings suggest that a hippocampal-caudate nucleus cooperation may enable exceptional memory performance. We speculate that this cooperation reflects an integration of the two memory systems at issue-enabling optimal combination of stimulus-response learning and map-based learning when using mnemonic strategies as for example the method of loci.

PMID: 29138923 [PubMed - as supplied by publisher]

Fusion of fMRI and non-imaging data for ADHD classification.

Thu, 11/16/2017 - 15:40
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Fusion of fMRI and non-imaging data for ADHD classification.

Comput Med Imaging Graph. 2017 Oct 19;:

Authors: Riaz A, Asad M, Alonso E, Slabaugh G

Abstract
Resting state fMRI has emerged as a popular neuroimaging method for automated recognition and classification of different brain disorders. Attention Deficit Hyperactivity Disorder (ADHD) is one of the most common brain disorders affecting young children, yet its underlying mechanism is not completely understood and its diagnosis is mainly dependent on behavior analysis. This paper addresses the problem of classification of ADHD based on resting state fMRI and proposes a machine learning framework with integration of non-imaging data with imaging data to investigate functional connectivity alterations between ADHD and control subjects (not diagnosed with ADHD). Our aim is to apply computational techniques to (1) automatically classify a subject as ADHD or control, (2) identify differences in functional connectivity of these two groups and (3) evaluate the importance of fusing non-imaging with imaging data for classification. In the first stage of our framework, we determine the functional connectivity of brain regions by grouping brain activity using clustering algorithms. Next, we employ Elastic Net based feature selection to select the most discriminant features from the dense functional brain network and integrate non-imaging data. Finally, a Support Vector Machine classifier is trained to classify ADHD subjects vs.
CONTROL: The proposed framework was evaluated on a public ADHD-200 dataset, and our results suggest that fusion of non-imaging data improves the performance of the framework. Classification results outperform the state-of-the-art on some subsets of the data.

PMID: 29137838 [PubMed - as supplied by publisher]

Altered resting-state functional activity in isolated pontine infarction patients with pathological laughing and crying.

Thu, 11/16/2017 - 15:40
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Altered resting-state functional activity in isolated pontine infarction patients with pathological laughing and crying.

Oncotarget. 2017 Oct 13;8(48):84529-84539

Authors: Liu T, Li J, Huang S, Li C, Zhao Z, Wen G, Chen F

Abstract
We used resting-state functional magnetic resonance imaging to investigate the global spontaneous neural activity involved in pathological laughing and crying after stroke. Twelve pathological laughing and crying patients with isolated pontine infarction were included, along with 12 age- and gender-matched acute isolated pontine infarction patients without pathological laughing and crying, and 12 age- and gender-matched healthy controls. We examined both the amplitude of low-frequency fluctuation and the regional homogeneity in order to comprehensively evaluate the intrinsic activity in patients with post-stroke pathological laughing and crying. In the post-stroke pathological laughing and crying group, changes in these measures were observed mainly in components of the default mode network (medial prefrontal cortex/anterior cingulate cortex, middle temporal gyrus, inferior temporal gyrus, superior frontal gyrus, middle frontal gyrus and inferior parietal lobule), sensorimotor network (supplementary motor area, precentral gyrus and paracentral lobule), affective network (medial prefrontal cortex/anterior cingulate cortex, parahippocampal gyrus, middle temporal gyrus and inferior temporal gyrus) and cerebellar lobes (cerebellum posterior lobe). We therefore speculate that when disinhibition of the volitional system is lost, increased activation of the emotional system causes pathological laughing and crying.

PMID: 29137445 [PubMed]

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