New resting-state fMRI related studies at PubMed

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Resting-state functional connectivity in the rat cervical spinal cord at 9.4 T.

Fri, 09/15/2017 - 15:00
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Resting-state functional connectivity in the rat cervical spinal cord at 9.4 T.

Magn Reson Med. 2017 Sep 14;:

Authors: Wu TL, Wang F, Mishra A, Wilson GH, Byun N, Chen LM, Gore JC

Abstract
PURPOSE: Numerous studies have adopted resting-state functional MRI methods to infer functional connectivity between cortical regions, but very few have translated them to the spinal cord, despite its critical role in the central nervous system. Resting-state functional connectivity between gray matter horns of the spinal cord has previously been shown to be detectable in humans and nonhuman primates, but it has not been reported previously in rodents.
METHODS: Resting-state functional MRI of the cervical spinal cord of live anesthetized rats was performed at 9.4 T. The quality of the functional images acquired was assessed, and quantitative analyses of functional connectivity in C4-C7 of the spinal cord were derived.
RESULTS: Robust gray matter horn-to-horn connectivity patterns were found that were statistically significant when compared with adjacent control regions. Specifically, dorsal-dorsal and ventral-ventral connectivity measurements were most prominent, while ipsilateral dorsal-ventral connectivity was also observed but to a lesser extent. Quantitative evaluation of reproducibility also revealed moderate robustness in the bilateral sensory and motor networks that was weaker in the dorsal-ventral connections.
CONCLUSIONS: This study reports the first evidence of resting-state functional circuits within gray matter in the rat spinal cord, and verifies their detectability using resting-state functional MRI at 9.4 T. Magn Reson Med, 2017. © 2017 International Society for Magnetic Resonance in Medicine.

PMID: 28905408 [PubMed - as supplied by publisher]

Distinct resting-state perfusion patterns underlie psychomotor retardation in unipolar vs. bipolar depression.

Fri, 09/15/2017 - 15:00
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Distinct resting-state perfusion patterns underlie psychomotor retardation in unipolar vs. bipolar depression.

Acta Psychiatr Scand. 2016 Oct;134(4):329-38

Authors: Cantisani A, Stegmayer K, Bracht T, Federspiel A, Wiest R, Horn H, Müller TJ, Schneider C, Höfle O, Strik W, Walther S

Abstract
OBJECTIVE: Psychomotor abnormalities characterize both unipolar (UP) depression and bipolar (BP) depression. We aimed to assess their neurobiological correlates in terms of motor activity (AL) and resting-state cerebral blood flow (rCBF) and investigate their association in BP, UP, and healthy controls (HC).
METHOD: We enrolled 42 depressed patients (22 BP, 20 UP) and 19 HC matched for age, gender, education, income. AL and rCBF were objectively assessed with the use of wrist actigraphy and arterial spin labeling. Group differences and the association of AL and rCBF were computed.
RESULTS: Activity level was significantly reduced in patients, but no difference was found between BP and UP. Increased perfusion was found in BP compared with UP and HC, in multiple brain areas. We found positive correlations of rCBF and AL in BP and UP, in different parts of the insula and frontal regions. Only BP showed a cluster in the left precentral gyrus. In HC, only inverse correlations of AL and rCBF were found.
CONCLUSION: The differences in rCBF and in the localization of the clusters of positive AL/rCBF correlations between BP and UP suggest that different neural impairments may underlie motor symptoms in the two disorders, but finally converge in phenotypically similar manifestations.

PMID: 27497085 [PubMed - indexed for MEDLINE]

Intra-regional and inter-regional abnormalities and cognitive control deficits in young adult smokers.

Fri, 09/15/2017 - 15:00
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Intra-regional and inter-regional abnormalities and cognitive control deficits in young adult smokers.

Brain Imaging Behav. 2016 Jun;10(2):506-16

Authors: Feng D, Yuan K, Li Y, Cai C, Yin J, Bi Y, Cheng J, Guan Y, Shi S, Yu D, Jin C, Lu X, Qin W, Tian J

Abstract
Tobacco use during later adolescence and young adulthood may cause serious neurophysiological changes; rationally, it is extremely important to study the relationship between brain dysfunction and behavioral performances in young adult smokers. Previous resting state studies investigated the neural mechanisms in smokers. Unfortunately, few studies focused on spontaneous activity differences between young adult smokers and nonsmokers from both intra-regional and inter-regional levels, less is known about the association between resting state abnormalities and behavioral deficits. Therefore, we used fractional amplitude of low frequency fluctuation (fALFF) and resting state functional connectivity (RSFC) to investigate the resting state spontaneous activity differences between young adult smokers and nonsmokers. A correlation analysis was carried out to assess the relationship between neuroimaging findings and clinical information (pack-years, cigarette dependence, age of onset and craving score) as well as cognitive control deficits measured by the Stroop task. Consistent with previous addiction findings, our results revealed the resting state abnormalities within frontostriatal circuits, i.e., enhanced spontaneous activity of the caudate and reduced functional strength between the caudate and anterior cingulate cortex (ACC) in young adult smokers. Moreover, the fALFF values of the caudate were correlated with craving and RSFC strength between the caudate and ACC was associated with the cognitive control impairments in young adult smokers. Our findings could lead to a better understanding of intrinsic functional architecture of baseline brain activity in young smokers by providing regional and brain circuit spontaneous neuronal activity properties as well as their association with cognitive control impairments.

PMID: 26164168 [PubMed - indexed for MEDLINE]

Alterations in default-mode network connectivity may be influenced by cerebrovascular changes within 1 week of sports related concussion in college varsity athletes: a pilot study.

Fri, 09/15/2017 - 15:00
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Alterations in default-mode network connectivity may be influenced by cerebrovascular changes within 1 week of sports related concussion in college varsity athletes: a pilot study.

Brain Imaging Behav. 2016 Jun;10(2):559-68

Authors: Militana AR, Donahue MJ, Sills AK, Solomon GS, Gregory AJ, Strother MK, Morgan VL

Abstract
The goal of this pilot study is to use complementary MRI strategies to quantify and relate cerebrovascular reactivity, resting cerebral blood flow and functional connectivity alterations in the first week following sports concussion in college varsity athletes. Seven college athletes (3F/4M, age = 19.7 ± 1.2 years) were imaged 3-6 days following a diagnosed sports related concussion and compared to eleven healthy controls with no history of concussion (5M/6F, 18-23 years, 7 athletes). Cerebrovascular reactivity and functional connectivity were measured using functional MRI during a hypercapnia challenge and via resting-state regional partial correlations, respectively. Resting cerebral blood flow was quantified using arterial spin labeling MRI methods. Group comparisons were made within and between 18 regions of interest. Cerebrovascular reactivity was increased after concussion when averaged across all regions of interest (p = 0.04), and within some default-mode network regions, the anterior cingulate and the right thalamus (p < 0.05) independently. The FC was increased in the concussed athletes within the default-mode network including the left and right hippocampus, precuneus and ventromedial prefrontal cortex (p < 0.01), with measures being linearly related to cerebrovascular reactivity in the hippocampus in the concussed athletes. Significant resting cerebral blood flow changes were not detected between the two groups. This study provides evidence for increased cerebrovascular reactivity and functional connectivity in the medial regions of the default-mode network within days of a single sports related concussion in college athletes. Our findings emphasize the utility of complementary cerebrovascular measures in the interpretation of alterations in functional connectivity following concussion.

PMID: 25972119 [PubMed - indexed for MEDLINE]

Analysis of correlation between white matter changes and functional responses in thalamic stroke: a DTI & EEG study.

Fri, 09/15/2017 - 15:00
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Analysis of correlation between white matter changes and functional responses in thalamic stroke: a DTI & EEG study.

Brain Imaging Behav. 2016 Jun;10(2):424-36

Authors: Duru AD, Duru DG, Yumerhodzha S, Bebek N

Abstract
Diffusion tensor imaging (DTI) allows in vivo structural brain mapping and detection of microstructural disruption of white matter (WM). One of the commonly used parameters for grading the anisotropic diffusivity in WM is fractional anisotropy (FA). FA value helps to quantify the directionality of the local tract bundle. Therefore, FA images are being used in voxelwise statistical analyses (VSA). The present study used Tract-Based Spatial Statistics (TBSS) of FA images across subjects, and computes the mean skeleton map to detect voxelwise knowledge of the tracts yielding to groupwise comparison. The skeleton image illustrates WM structure and shows any changes caused by brain damage. The microstructure of WM in thalamic stroke is investigated, and the VSA results of healthy control and thalamic stroke patients are reported. It has been shown that several skeleton regions were affected subject to the presence of thalamic stroke (FWE, p < 0.05). Furthermore the correlation of quantitative EEG (qEEG) scores and neurophysiological tests with the FA skeleton for the entire test group is also investigated. We compared measurements that are related to the same fibers across subjects, and discussed implications for VSA of WM in thalamic stroke cases, for the relationship between behavioral tests and FA skeletons, and for the correlation between the FA maps and qEEG scores.Results obtained through the regression analyses did not exceed the corrected statistical threshold values for multiple comparisons (uncorrected, p < 0.05). However, in the regression analysis of FA values and the theta band activity of EEG, cingulum bundle and corpus callosum were found to be related. These areas are parts of the Default Mode Network (DMN) where DMN is known to be involved in resting state EEG theta activity. The relation between the EEG alpha band power values and FA values of the skeleton was found to support the cortico-thalamocortical cycles for both subject groups. Further, the neurophysiological tests including Benton Face Recognition (BFR), Digit Span test (DST), Warrington Topographic Memory test (WTMT), California Verbal Learning test (CVLT) has been regressed with the FA skeleton maps for both subject groups. Our results corresponding to DST task were found to be similar with previously reported findings for working memory and episodic memory tasks. For the WTMT, FA values of the cingulum (right) that plays a role in memory process was found to be related with the behavioral responses. Splenium of corpus callosum was found to be correlated for both subject groups for the BFR.

PMID: 25957181 [PubMed - indexed for MEDLINE]

Correlation between brain circuit segregation and obesity.

Thu, 09/14/2017 - 13:40
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Correlation between brain circuit segregation and obesity.

Behav Brain Res. 2017 Sep 09;:

Authors: Chao HH, Liao YT, Chen VC, Li CJ, McIntyre RS, Lee Y, Weng JC

Abstract
Obesity is a major public health problem. Herein, we aim to identify the correlation between brain circuit segregation and obesity using multimodal functional magnetic resonance imaging (fMRI) techniques and analysis. Twenty obese patients (BMI=37.66±5.07) and 30 healthy controls (BMI=22.64±3.45) were compared using neuroimaging and assessed for symptoms of anxiety and depression using the Hospital Anxiety and Depression Scale (HADS). All participants underwent resting-state fMRI (rs-fMRI) and T1-weighted imaging using a 1.5T MRI. Multimodal MRI techniques and analyses were used to assess obese patients, including the functional connectivity (FC), amplitude of low-frequency fluctuations (ALFF), regional homogeneity (ReHo), graph theoretical analysis (GTA), and voxel-based morphometry (VBM). Correlations between brain circuit segregation and obesity were also calculated. In the VBM, obese patients showed altered gray matter volumes in the amygdala, thalamus and putamen. In the FC, the obesity group showed increased functional connectivity in the bilateral anterior cingulate cortex and decreased functional connectivity in the frontal gyrus of default mode network. The obesity group also exhibited altered ALFF and ReHo in the prefrontal cortex and precuneus. In the GTA, the obese patients showed a significant decrease in local segregation and a significant increase in global integration, suggesting a shift toward randomization in their functional networks. Our results may provide additional evidence for potential structural and functional imaging markers for clinical diagnosis and future research, and they may improve our understanding of the underlying pathophysiology of obesity.

PMID: 28899821 [PubMed - as supplied by publisher]

Neural and metabolic basis of dynamic resting state fMRI.

Thu, 09/14/2017 - 13:40
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Neural and metabolic basis of dynamic resting state fMRI.

Neuroimage. 2017 Sep 09;:

Authors: Thompson GJ

Abstract
Resting state fMRI (rsfMRI) as a technique showed much initial promise for use in psychiatric and neurological diseases where diagnosis and treatment were difficult. To realize this promise, many groups have moved towards examining "dynamic rsfMRI," which relies on the assumption that rsfMRI measurements on short time scales remain relevant to the underlying neural and metabolic activity. Many dynamic rsfMRI studies have demonstrated differences between clinical or behavioral groups beyond what static rsfMRI measured, suggesting a neurometabolic basis. Correlative studies combining dynamic rsfMRI and other physiological measurements have supported this. However, they also indicate multiple mechanisms and, if using correlation alone, it is difficult to separate cause and effect. Hypothesis-driven studies are needed, a few of which have begun to illuminate the underlying neurometabolic mechanisms that shape observed differences in dynamic rsfMRI. While the number of potential noise sources, potential actual neurometabolic sources, and methodological considerations can seem overwhelming, dynamic rsfMRI provides a rich opportunity in systems neuroscience. Even an incrementally better understanding of the neurometabolic basis of dynamic rsfMRI would expand rsfMRI's research and clinical utility, and the studies described herein take the first steps on that path forward.

PMID: 28899744 [PubMed - as supplied by publisher]

ICN_Atlas: Automated description and quantification of functional MRI activation patterns in the framework of intrinsic connectivity networks.

Thu, 09/14/2017 - 13:40
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ICN_Atlas: Automated description and quantification of functional MRI activation patterns in the framework of intrinsic connectivity networks.

Neuroimage. 2017 Sep 09;:

Authors: Kozák LR, van Graan LA, Chaudhary UJ, Szabó Á, Lemieux L

Abstract
Generally, the interpretation of functional MRI (fMRI) activation maps continues to rely on assessing their relationship to anatomical structures, mostly in a qualitative and often subjective way. Recently, the existence of persistent and stable brain networks of functional nature has been revealed; in particular these so-called intrinsic connectivity networks (ICNs) appear to link patterns of resting state and task-related state connectivity. These networks provide an opportunity of functionally-derived description and interpretation of fMRI maps, that may be especially important in cases where the maps are predominantly task-unrelated, such as studies of spontaneous brain activity e.g. in the case of seizure-related fMRI maps in epilepsy patients or sleep states. Here we present a new toolbox (ICN_Atlas) aimed at facilitating the interpretation of fMRI data in the context of ICN. More specifically, the new methodology was designed to describe fMRI maps in function-oriented, objective and quantitative way using a set of 15 metrics conceived to quantify the degree of 'engagement' of ICNs for any given fMRI-derived statistical map of interest. We demonstrate that the proposed framework provides a highly reliable quantification of fMRI activation maps using a publicly available longitudinal (test-retest) resting-state fMRI dataset. The utility of the ICN_Atlas is also illustrated on a parametric task-modulation fMRI dataset, and on a dataset of a patient who had repeated seizures during resting-state fMRI, confirmed on simultaneously recorded EEG. The proposed ICN_Atlas framework will be made freely available for download at https://www.nitrc.org and at http://incatlas.com for researchers to use in their fMRI investigations.

PMID: 28899742 [PubMed - as supplied by publisher]

Anti-fragmentation of resting-state fMRI connectivity networks with node-wise thresholding.

Thu, 09/14/2017 - 13:40
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Anti-fragmentation of resting-state fMRI connectivity networks with node-wise thresholding.

Brain Connect. 2017 Sep 13;

Authors: Hayasaka S

Abstract
fMRI-based functional connectivity networks are often constructed by thresholding a correlation matrix of nodal time courses. In a typical thresholding approach known as hard thresholding, a single threshold is applied to the entire correlation matrix to identify edges representing super-threshold correlations. However, hard thresholding is known to produce a network with uneven allocation of edges, resulting in a fragmented network with a large number of disconnected nodes. It is suggested that an alternative network thresholding approach, node-wise thresholding, is able to overcome these problems. To examine this, various network characteristics were compared between networks constructed by hard thresholding and node-wise thresholding, with publicly available resting-state fMRI data from 123 healthy young subjects. It was found that networks constructed with hard thresholding included a large number of disconnected nodes, while such network fragmentation was not observed in networks formed with node-wise thresholding. Moreover, in hard thresholding networks, fragmentized modular organization was observed, characterized by a large number of small modules. On the other hand, such modular fragmentation was not observed in node-wise thresholding networks, producing modules that were robust at any threshold and highly consistent across subjects. These results indicate that node-wise thresholding may lead to less fragmented networks. Moreover, node-wise thresholding enables robust characterization of network properties without much influence by the selection of a threshold.

PMID: 28899207 [PubMed - as supplied by publisher]

Disrupted Brain Network Hubs in Subtype-Specific Parkinson's Disease.

Wed, 09/13/2017 - 12:20

Disrupted Brain Network Hubs in Subtype-Specific Parkinson's Disease.

Eur Neurol. 2017 Aug 25;78(3-4):200-209

Authors: Ma LY, Chen XD, He Y, Ma HZ, Feng T

Abstract
BACKGROUND/AIMS: The topological organization of brain functional networks is impaired in Parkinson's disease (PD). However, the altered patterns of functional network hubs in different subtypes of PD are not completely understood.
METHODS: 3T resting-state functional MRI and voxel-based graph-theory analysis were employed to systematically investigate the intrinsic functional connectivity patterns of whole-brain networks. We enrolled 31 patients with PD (12 tremor dominant [TD] and 19 with postural instability/gait difficulty [PIGD]) and 22 matched healthy controls. Whole-brain voxel-wise functional networks were constructed by measuring the temporal correlations of each pair of brain voxels. Functional connectivity strength was calculated to explore the brain network hubs.
RESULTS: We found that both the TD and PIGD subtypes had comprehensive disrupted regions. These mainly involved the basal ganglia, cerebellum, superior temporal gyrus, pre- and postcentral gyri, inferior frontal gyrus, middle temporal gyrus, lingual gyrus, insula, and parahippocampal gyrus. Furthermore, the PIGD subgroup had more disrupted hubs in the cerebellum than the TD subgroup. These disruptions of hub connectivity were not correlated with the HY stage or disease duration.
CONCLUSION: Our results emphasize the subtype-specific PD-related degeneration of brain hubs, providing novel insights into the pathophysiological mechanisms of connectivity dysfunction in different PD subgroups.

PMID: 28898869 [PubMed - as supplied by publisher]

Distinct patterns of temporal and directional connectivity among intrinsic networks in the human brain.

Wed, 09/13/2017 - 12:20
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Distinct patterns of temporal and directional connectivity among intrinsic networks in the human brain.

J Neurosci. 2017 Sep 11;:

Authors: Shine JM, Kucyi A, Foster BL, Bickel S, Wang D, Liu H, Poldrack RA, Hsieh LT, Chun Hsiang J, Parvizi J

Abstract
To determine the spatiotemporal relationships among intrinsic networks of the human brain, we recruited seven neurosurgical patients (4 males; 3 females) who were implanted with intracranial depth electrodes. We first identified canonical resting state networks at the individual subject level using an iterative matching procedure on each subject's resting state fMRI data. We then introduced single electrical pulses to fMRI pre-identified nodes of the default (DN), frontoparietal (FPN) and salience networks (SN) while recording evoked responses in other recording sites within the same networks. We found bidirectional signal flow across the three networks, albeit with distinct patterns of evoked responses within different time windows. We used a data-driven clustering approach to show that stimulation of the FPN and SN evoked a rapid (<70 ms) response that was predominantly higher within the SN sites, whereas stimulation of the DN led to sustained responses in later time windows (85-200ms). Stimulations in the medial temporal lobe components of the DN evoked relatively late-effects (>130ms) in other nodes of the DN, as well as FPN and SN. Together, our results provide temporal information about the patterns of signal flow between intrinsic networks that provide insights into the spatiotemporal dynamics that are likely to constrain the architecture of the brain networks supporting human cognition and behavior.SIGNFICANCE STATEMENTDespite great progress in the functional neuroimaging of the human brain, we still don't know the precise set of rules that define the patterns of temporal organization between large-scale networks of the brain. In this study, we stimulated and then recorded electrical evoked potentials within and between three large-scale networks of the brain - the default (DN), frontoparietal (FPN) and salience networks (SN) - in 7 subjects undergoing invasive neurosurgery. Using a data-driven clustering approach, we observed distinct temporal and directional patterns between the three networks, with FPN and SN activity predominant in early windows, and DN stimulation affecting the network in later windows. These results provide important temporal information about the interactions between brain networks supporting human cognition and behavior.

PMID: 28893929 [PubMed - as supplied by publisher]

Resting state fMRI observations of baseline brain functional activities and connectivities in primary blepharospasm.

Wed, 09/13/2017 - 12:20
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Resting state fMRI observations of baseline brain functional activities and connectivities in primary blepharospasm.

Neurosci Lett. 2017 Sep 08;:

Authors: Ni MF, Huang XF, Miao YW, Liang ZH

Abstract
Primary blepharospasm (BPS) is a focal dystonia characterized by involuntary eyelid spasms and blinking. The pathophysiology of BPS remains unclear. Several functional and structural neuroimaging studies have demonstrated abnormalities of sensorimotor structures such as the sensorimotor cortex, the basal ganglia, the thalamus and the cerebellum in BPS patients. However, some of the results of these studies were inconsistent. In addition, the relationship between the motor and sensory structures in patients with BPS still needs to be investigated. Therefore, the purpose of this study was to investigate the abnormal alterations in both the intra-regional brain activities and inter-regional functional connectivities (FC) in patients with BPS using resting-state functional MRI(rs-fMRI) and to explore possible correlations between these rs-fMRI indices and clinical variables. The rs-fMRI images of the two groups of subjects (26 BPS patients and 26 healthy controls) were acquired using a 3.0T MRI scanner. The regional rs-fMRI indices, i.e., the fractional amplitude of the low-frequency fluctuation (fALFF) and the regional homogeneity (ReHo), were computed for all subjects. Then, two-sample t-tests were conducted to assess the significant differences between the two groups of subjects. To investigate the alterations in brain networks, cerebral regions with significant differences were used as regions of interest in the whole brain FC analysis. Compared to the control group, the BPS patients revealed significantly increased fALFF and ReHo values in the right caudate head. Significantly strengthened FC values were observed between the right caudate head and the left striatum and the right supplementary motor area in the BPS group. The fALFF and ReHo values in the right caudate head and the FC values between the right caudate head and the left striatum were positively correlated with the Jankovic Rating Scale sum score. In conclusion, this study indicated that BPS patients have both abnormal intra-regional spontaneous brain activities and inter-regional functional connectivities.

PMID: 28893588 [PubMed - as supplied by publisher]

Changes in resting-state brain networks after cognitive-behavioral therapy for chronic pain.

Wed, 09/13/2017 - 12:20
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Changes in resting-state brain networks after cognitive-behavioral therapy for chronic pain.

Psychol Med. 2017 Sep 12;:1-11

Authors: Yoshino A, Okamoto Y, Okada G, Takamura M, Ichikawa N, Shibasaki C, Yokoyama S, Doi M, Jinnin R, Yamashita H, Horikoshi M, Yamawaki S

Abstract
BACKGROUND: Cognitive-behavioral therapy (CBT) is thought to be useful for chronic pain, with the pathology of the latter being closely associated with cognitive-emotional components. However, there are few resting-state functional magnetic resonance imaging (R-fMRI) studies. We used the independent component analysis method to examine neural changes after CBT and to assess whether brain regions predict treatment response.
METHODS: We performed R-fMRI on a group of 29 chronic pain (somatoform pain disorder) patients and 30 age-matched healthy controls (T1). Patients were enrolled in a weekly 12-session group CBT (T2). We assessed selected regions of interest that exhibited differences in intrinsic connectivity network (ICN) connectivity strength between the patients and controls at T1, and compared T1 and T2. We also examined the correlations between treatment effects and rs-fMRI data.
RESULTS: Abnormal ICN connectivity of the orbitofrontal cortex (OFC) and inferior parietal lobule within the dorsal attention network (DAN) and of the paracentral lobule within the sensorimotor network in patients with chronic pain normalized after CBT. Higher ICN connectivity strength in the OFC indicated greater improvements in pain intensity. Furthermore, ICN connectivity strength in the dorsal posterior cingulate cortex (PCC) within the DAN at T1 was negatively correlated with CBT-related clinical improvements.
CONCLUSIONS: We conclude that the OFC is crucial for CBT-related improvement of pain intensity, and that the dorsal PCC activation at pretreatment also plays an important role in improvement of clinical symptoms via CBT.

PMID: 28893330 [PubMed - as supplied by publisher]

Depression in chronic ketamine users: Sex differences and neural bases.

Tue, 09/12/2017 - 11:00

Depression in chronic ketamine users: Sex differences and neural bases.

Psychiatry Res. 2017 Sep 05;269:1-8

Authors: Li CR, Zhang S, Hung CC, Chen CM, Duann JR, Lin CP, Lee TS

Abstract
Chronic ketamine use leads to cognitive and affective deficits including depression. Here, we examined sex differences and neural bases of depression in chronic ketamine users. Compared to non-drug using healthy controls (HC), ketamine-using females but not males showed increased depression score as assessed by the Center of Epidemiological Studies Depression Scale (CES-D). We evaluated resting state functional connectivity (rsFC) of the subgenual anterior cingulate cortex (sgACC), a prefrontal structure consistently implicated in the pathogenesis of depression. Compared to HC, ketamine users (KU) did not demonstrate significant changes in sgACC connectivities at a corrected threshold. However, in KU, a linear regression against CES-D score showed less sgACC connectivity to the orbitofrontal cortex (OFC) with increasing depression severity. Examined separately, male and female KU showed higher sgACC connectivity to bilateral superior temporal gyrus and dorsomedial prefrontal cortex (dmPFC), respectively, in correlation with depression. The linear correlation of sgACC-OFC and sgACC-dmPFC connectivity with depression was significantly different in slope between KU and HC. These findings highlighted changes in rsFC of the sgACC as associated with depression and sex differences in these changes in chronic ketamine users.

PMID: 28892733 [PubMed - as supplied by publisher]

Machine-learning Support to Individual Diagnosis of Mild Cognitive Impairment Using Multimodal MRI and Cognitive Assessments.

Tue, 09/12/2017 - 11:00

Machine-learning Support to Individual Diagnosis of Mild Cognitive Impairment Using Multimodal MRI and Cognitive Assessments.

Alzheimer Dis Assoc Disord. 2017 Sep 07;:

Authors: De Marco M, Beltrachini L, Biancardi A, Frangi AF, Venneri A

Abstract
BACKGROUND: Understanding whether the cognitive profile of a patient indicates mild cognitive impairment (MCI) or performance levels within normality is often a clinical challenge. The use of resting-state functional magnetic resonance imaging (RS-fMRI) and machine learning may represent valid aids in clinical settings for the identification of MCI patients.
METHODS: Machine-learning models were computed to test the classificatory accuracy of cognitive, volumetric [structural magnetic resonance imaging (sMRI)] and blood oxygen level dependent-connectivity (extracted from RS-fMRI) features, in single-modality and mixed classifiers.
RESULTS: The best and most significant classifier was the RS-fMRI+Cognitive mixed classifier (94% accuracy), whereas the worst performing was the sMRI classifier (∼80%). The mixed global (sMRI+RS-fMRI+Cognitive) had a slightly lower accuracy (∼90%), although not statistically different from the mixed RS-fMRI+Cognitive classifier. The most important cognitive features were indices of declarative memory and semantic processing. The crucial volumetric feature was the hippocampus. The RS-fMRI features selected by the algorithms were heavily based on the connectivity of mediotemporal, left temporal, and other neocortical regions.
CONCLUSION: Feature selection was profoundly driven by statistical independence. Some features showed no between-group differences, or showed a trend in either direction. This indicates that clinically relevant brain alterations typical of MCI might be subtle and not inferable from group analysis.

PMID: 28891818 [PubMed - as supplied by publisher]

Comparison of separation performance of independent component analysis algorithms for fMRI data.

Tue, 09/12/2017 - 11:00

Comparison of separation performance of independent component analysis algorithms for fMRI data.

J Integr Neurosci. 2017;16(2):157-175

Authors: Sariya YK, Anand RS

Abstract
Independent component analysis, a data-driven analysis method, has found significant applications in task-based as well as resting state fMRI studies. There are numbers of independent component analysis algorithms available, but only a few of them have been used frequently so far for fMRI images. With a view that algorithms that are overlooked may outperform the most opted, a comparative study is taken up in this paper to analyze their abilities for the purpose of synthesis of fMRI images. In this paper, ten independent component algorithms: Fast ICA, INFOMAX, SIMBEC, JADE, ERICA, EVD, RADICAL, ICA-EBM, ERBM, and COMBI are compared. Their separation abilities are adjudged on both, synthetic and real fMRI images. Performance to decompose synthetic fMRI images is being monitored on the basis of spatial correlation coefficients, time elapsed to extract independent components and the visual appearance of independent components. Ranking of their performances on task-based real fMRI images are based on the closeness of time courses of identified independent components with model time course and the closeness of spatial maps of components with spatial templates while their competencies for resting state fMRI data are analyzed by examining how distinctly they decompose the data into the most consistent resting state networks. Sum of mutual information between all the permutations of decomposed components of resting state fMRI data are also calculated.

PMID: 28891507 [PubMed - in process]

Association between resting-state brain network topological organization and creative ability: evidence from a multiple linear regression model.

Tue, 09/12/2017 - 11:00
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Association between resting-state brain network topological organization and creative ability: evidence from a multiple linear regression model.

Biol Psychol. 2017 Sep 07;:

Authors: Jiao B, Zhang D, Liang A, Liang B, Wang Z, Li J, Cai Y, Gao M, Gao Z, Chang S, Huang R, Liu M

Abstract
Previous studies have indicated a tight linkage between resting-state functional connectivity of the human brain and creative ability. This study aimed to further investigate the association between the topological organization of resting-state brain networks and creativity. Therefore, we acquired resting-state fMRI data from 22 high-creativity participants and 22 low-creativity participants (as determined by their Torrance Tests of Creative Thinking scores). We then constructed functional brain networks for each participant and assessed group differences in network topological properties before exploring the relationships between respective network topological properties and creative ability. We identified an optimized organization of intrinsic brain networks in both groups. However, compared with low-creativity participants, high-creativity participants exhibited increased global efficiency and substantially decreased path length, suggesting increased efficiency of information transmission across brain networks in creative individuals. Using a multiple linear regression model, we further demonstrated that regional functional integration properties (i.e., the betweenness centrality and global efficiency) of brain networks, particularly the default mode network (DMN) and sensorimotor network (SMN), significantly predicted the individual differences in creative ability. Furthermore, the associations between network regional properties and creative performance were creativity-level dependent, where the difference in the resource control component may be important in explaining individual difference in creative performance. These findings provide novel insights into the neural substrate of creativity and may facilitate objective identification of creative ability.

PMID: 28890001 [PubMed - as supplied by publisher]

A Multimodal Imaging- and Stimulation-based Method of Evaluating Connectivity-related Brain Excitability in Patients with Epilepsy.

Tue, 09/12/2017 - 11:00
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A Multimodal Imaging- and Stimulation-based Method of Evaluating Connectivity-related Brain Excitability in Patients with Epilepsy.

J Vis Exp. 2016 Nov 13;(117):

Authors: Shafi MM, Whitfield-Gabrieli S, Chu CJ, Pascual-Leone A, Chang BS

Abstract
Resting-state functional connectivity MRI (rs-fcMRI) is a technique that identifies connectivity between different brain regions based on correlations over time in the blood-oxygenation level dependent signal. rs-fcMRI has been applied extensively to identify abnormalities in brain connectivity in different neurologic and psychiatric diseases. However, the relationship among rs-fcMRI connectivity abnormalities, brain electrophysiology and disease state is unknown, in part because the causal significance of alterations in functional connectivity in disease pathophysiology has not been established. Transcranial Magnetic Stimulation (TMS) is a technique that uses electromagnetic induction to noninvasively produce focal changes in cortical activity. When combined with electroencephalography (EEG), TMS can be used to assess the brain's response to external perturbations. Here we provide a protocol for combining rs-fcMRI, TMS and EEG to assess the physiologic significance of alterations in functional connectivity in patients with neuropsychiatric disease. We provide representative results from a previously published study in which rs-fcMRI was used to identify regions with abnormal connectivity in patients with epilepsy due to a malformation of cortical development, periventricular nodular heterotopia (PNH). Stimulation in patients with epilepsy resulted in abnormal TMS-evoked EEG activity relative to stimulation of the same sites in matched healthy control patients, with an abnormal increase in the late component of the TMS-evoked potential, consistent with cortical hyperexcitability. This abnormality was specific to regions with abnormal resting-state functional connectivity. Electrical source analysis in a subject with previously recorded seizures demonstrated that the origin of the abnormal TMS-evoked activity co-localized with the seizure-onset zone, suggesting the presence of an epileptogenic circuit. These results demonstrate how rs-fcMRI, TMS and EEG can be utilized together to identify and understand the physiological significance of abnormal brain connectivity in human diseases.

PMID: 27911366 [PubMed - indexed for MEDLINE]

Mobilization of Medial and Lateral Frontal-Striatal Circuits in Cocaine Users and Controls: An Interleaved TMS/BOLD Functional Connectivity Study.

Tue, 09/12/2017 - 11:00
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Mobilization of Medial and Lateral Frontal-Striatal Circuits in Cocaine Users and Controls: An Interleaved TMS/BOLD Functional Connectivity Study.

Neuropsychopharmacology. 2016 Dec;41(13):3032-3041

Authors: Hanlon CA, Dowdle LT, Moss H, Canterberry M, George MS

Abstract
The integrity of frontal-striatal circuits is an area of great interest in substance dependence literature, particularly as the field begins to develop neural circuit-specific brain stimulation treatments for these individuals. Prior research indicates that frontal-striatal connectivity is disrupted in chronic cocaine users in a baseline (resting) state. It is unclear, however, if this is also true when these circuits are mobilized by an external source. In this study, we measured the functional and structural integrity of frontal-striatal circuitry involved in limbic arousal and executive control in 36 individuals-18 cocaine-dependent individuals with a history of failed quit attempts and 18 age-matched controls. This was achieved by applying a transcranial magnetic stimulation to the medial prefrontal cortex (Brodmann area 10) and the dorsolateral prefrontal cortex (lateral Brodmann 9) while participants rested in the MRI scanner (TMS/BOLD imaging). Relative to the controls, cocaine users had a lower ventral striatal BOLD response to MPFC stimulation. The dorsal striatal BOLD response to DLPFC stimulation however was not significantly different between the groups. Among controls, DLPFC stimulation led to a reciprocal attenuation of MPFC activity (BA 10), but this pattern did not exist in cocaine users. No relationship was found between regional diffusion metrics and functional activity. Considered together these data suggest that, when engaged, cocaine users can mobilize their executive control system similar to controls, but that the 'set point' for mobilizing their limbic arousal system has been elevated-an interpretation consistent with opponent process theories of addiction.

PMID: 27374278 [PubMed - indexed for MEDLINE]

A flexible graphical model for multi-modal parcellation of the cortex.

Mon, 09/11/2017 - 16:00

A flexible graphical model for multi-modal parcellation of the cortex.

Neuroimage. 2017 Sep 06;:

Authors: Parisot S, Glocker B, Ktena SI, Arslan S, Schirmer MD, Rueckert D

Abstract
Advances in neuroimaging have provided a tremendous amount of in-vivo information on the brain's organisation. Its anatomy and cortical organisation can be investigated from the point of view of several imaging modalities, many of which have been studied for mapping functionally specialised cortical areas. There is strong evidence that a single modality is not sufficient to fully identify the brain's cortical organisation. Combining multiple modalities in the same parcellation task has the potential to provide more accurate and robust subdivisions of the cortex. Nonetheless, existing brain parcellation methods are typically developed and tested on single modalities using a specific type of information. In this paper, we propose Graph-based Multi-modal Parcellation (GraMPa), an iterative framework designed to handle the large variety of available input modalities to tackle the multi-modal parcellation task. At each iteration, we compute a set of parcellations from different modalities and fuse them based on their local reliabilities. The fused parcellation is used to initialise the next iteration, forcing the parcellations to converge towards a set of mutually informed modality specific parcellations, where correspondences are established. We explore two different multi-modal configurations for group-wise parcellation using resting-state fMRI, diffusion MRI tractography, myelin maps and task fMRI. Quantitative and qualitative results on the Human Connectome Project database show that integrating multi-modal information yields a stronger agreement with well established atlases and more robust connectivity networks that provide a better representation of the population.

PMID: 28889005 [PubMed - as supplied by publisher]

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