Resting State Functional Connectivity Modulation and Sustained Changes after Real-Time fMRI Neurofeedback Training in Depression.
Brain Connect. 2014 Oct 20;
Authors: Yuan H, Young KD, Phillips R, Zotev V, Misaki M, Bodurka J
Amygdala hemodynamic responses to positive stimuli are attenuated in major depressive disorder (MDD) and normalize with remission. Real-time fMRI neurofeedback (rtfMRI-nf) training with the goal of upregulating amygdala activity during recall of happy autobiographical memories (AMs) has been suggested, and recently explored, as a novel therapeutic approach which resulted in improvement in self-reported mood in depressed subjects. In the present study we assessed the possibility of sustained brain changes as well as the neuromodulatory effects of rtfMRI-nf training of the amygdala during recall of positive AMs in MDD and matched healthy subjects. MDD and healthy subjects went through one visit of rtfMRI neurofeedback training. Subjects were assigned to receive active neurofeedback from the left amygdala or from a control region putatively not modulated by AM recall or emotion regulation, i.e. the left horizontal segment of the intraparietal sulcus. To assess lasting effects of neurofeedback in MDD, the resting state functional connectivity before and after rtfMRI-nf in 27 depressed subjects, as well as in 27 matched healthy subjects before rtfMRI-nf was measured. Results show that abnormal hypo-connectivity with left amygdala in MDD is reversed after rtfMRI-nf training by recalling positive AMs. Although such neuromodulatory changes are observed in both MDD groups receiving feedback from respective active and control brain regions, only in the active group are larger decreases of depression severity associated with larger increases of amygdala connectivity and a significant, positive correlation is found between the connectivity changes and the days after neurofeedback. Additionally, active neurofeedback training of the amygdala enhances connectivity with temporal cortical regions including the hippocampus. These results demonstrate lasting brain changes induced by amygdala rtfMRI-nf training and suggest the importance of reinforcement learning in rehabilitating emotion regulation in depression.
PMID: 25329241 [PubMed - as supplied by publisher]
Developmental Resting State Functional Connectivity for Clinicians.
Curr Behav Neurosci Rep. 2014 Sep 1;1(3):161-169
Authors: Hulvershorn LA, Cullen KR, Francis M, Westlund M
Resting state functional magnetic imaging (fMRI) is a novel means to examine functional brain networks. It allows investigators to identify functional networks defined by distinct, spontaneous signal fluctuations. Resting state functional connectivity (RSFC) studies examining child and adolescent psychiatric disorders are being published with increasing frequency, despite concerns about the impact of motion on findings. Here we review important RSFC findings on typical brain development and recent publications of child and adolescent psychiatric disorders. We close with a summary of the major findings and current strengths and limitations of RSFC studies.
PMID: 25328859 [PubMed - as supplied by publisher]
[Functional connectivity in ischemia stroke motor aphasia patients during resting state].
Zhonghua Yi Xue Za Zhi. 2014 Jul 15;94(27):2135-8
Authors: Wang W, Wang M, Liu H, Yuan B, Wang J, Li H, Zhou X, Wang X, Tao J, Li J
OBJECTIVE: To investigate the changes of Broca's area functional connectivity in ischemia stroke patients with motor aphasia during resting state using functional magnetic resonance imaging (fMRI).
METHODS: The functional connectivity of Broca's area was analyzed by observing the correlation between low frequency signal fluctuations in Broca's area and those in all brain regions.
RESULTS: In the normal controls group, there was multiple brain area positively correlated with Broca's area during resting state. The patients group compared with controls group, the functional connectivity between Broca's area and adjacent brain regions around its is most significant, and its controlateral brain area correlated with Broca's area reduced, but some cerebellum, occipital lobe, middle temporal gyrus and corpus callosum spenium correlated with Broca's area strengthened.
CONCLUSION: There is a wide range of motor function of language network during resting state. The right anterior cingulate gyrus, knee of corpus callosum and hemisphere play an important part in motor language function network. The enhancement functional connectivity between the adjacent brain regions surrounding Broca's area, the right cerebellum, occipital lobe, middle temporal gyrus and spenium of corpus callosum and Broca's area may be one compensatory mechanism remodeling for the language recover of ischemia stroke patients with motor aphasia.
PMID: 25327862 [PubMed - in process]
Functional connectivity density and balance in young patients with traumatic axonal injury.
Brain Connect. 2014 Oct 18;
Authors: Caeyenberghs K, Siugzdaite R, Drijkoningen D, Marinazzo D, Swinnen S
Background: Our previous study (Caeyenberghs et al., 2012) provided some evidence for the relationship between abnormal structural connectivity and poor balance performance in young traumatic axonal injury (TAI) patients. An enhanced understanding of the functional connectivity following TAI may allow for targeted treatments geared towards improving brain function and postural control. Methods: 12 patients with TAI and 28 normally developing children (aged 9-19 years) performed the Sensory Organisation Test (SOT) protocol of the EquiTest (Neurocom). All participants were scanned using resting state fMRI (rs-fMRI) series along with anatomical scans. We applied 'functional connectivity density mapping' (FCDM), a voxel-wise data-driven method that calculates individual functional connectivity maps to obtain both short-range and long-range FCD. Results: Findings revealed that the TAI group scored generally lower than the control group on the SOT, especially when proprioceptive feedback was compromised. Between-group maps noted significantly decreased long-range FCD in the TAI group in frontal and subcortical regions and significantly increased short-range FCD in frontal regions, left inferior parietal and cerebellar lobules. Moreover, lower balance levels in TAI patients were associated with a lower long-range FCD in left putamen and cerebellar vermis. Conclusion: These findings suggest that long-range connections may be more vulnerable to TAI than short-range connections. Moreover, higher values of short-range FCD may suggest adaptive mechanisms in the TAI group. Finally, this study supports the view that FCDM is a valuable tool for selectively predicting functional motor deficits in TAI patients.
PMID: 25327385 [PubMed - as supplied by publisher]
Lateralized Resting-state Functional Connectivity in the Task-positive and Task-negative Networks.
Brain Connect. 2014 Oct 18;
Authors: Kim E, Di X, Chen P, Biswal BB
Studies on functional brain lateralization using functional magnetic resonance imaging (fMRI) have generally focused on lateralization of local brain regions. We analyzed lateralization of functional connectivity using resting-state fMRI (N=87, right handed) and mapped left- and right- lateralized networks. We divided 402 equally spaced regions of interest (ROI) covering the entire gray matter into 358 task-positive and 44 task-negative ROIs. Lateralized functional connections were obtained using k-means clustering analysis. The right-lateralized functional connections were between the occipital and inferior/middle frontal regions among other connections, whereas the left-lateralized functional connections were among fusiform gyrus, inferior frontal and inferior/superior parietal regions. Within the task-negative network, the left-lateralized connections were mainly between the precuneus and medial prefrontal regions. Specific brain regions exhibited different left- or right-lateralized connections with other regions which suggest the importance of reporting lateralized connections over lateralized seed regions. The mean lateralization indices of the left- and right-lateralized connections were correlated, suggesting that the lateralization of connectivity may result from complementary processes between the lateralized networks. The potential functions of the lateralized networks were discussed.
PMID: 25327308 [PubMed - as supplied by publisher]
The relationship between eye movement and vision develops before birth.
Front Hum Neurosci. 2014;8:775
Authors: Schöpf V, Schlegl T, Jakab A, Kasprian G, Woitek R, Prayer D, Langs G
While the visuomotor system is known to develop rapidly after birth, studies have observed spontaneous activity in vertebrates in visually excitable cortical areas already before extrinsic stimuli are present. Resting state networks and fetal eye movements were observed independently in utero, but no functional brain activity coupled with visual stimuli could be detected using fetal fMRI. This study closes this gap and links in utero eye movement with corresponding functional networks. BOLD resting-state fMRI data were acquired from seven singleton fetuses between gestational weeks 30-36 with normal brain development. During the scan time, fetal eye movements were detected and tracked in the functional MRI data. We show that already in utero spontaneous fetal eye movements are linked to simultaneous networks in visual- and frontal cerebral areas. In our small but in terms of gestational age homogenous sample, evidence across the population suggests that the preparation of the human visuomotor system links visual and motor areas already prior to birth.
PMID: 25324764 [PubMed]
Increased resting state functional connectivity in the fronto-parietal and default mode network in anorexia nervosa.
Front Behav Neurosci. 2014;8:346
Authors: Boehm I, Geisler D, King JA, Ritschel F, Seidel M, Deza Araujo Y, Petermann J, Lohmeier H, Weiss J, Walter M, Roessner V, Ehrlich S
The etiology of anorexia nervosa (AN) is poorly understood. Results from functional brain imaging studies investigating the neural profile of AN using cognitive and emotional task paradigms are difficult to reconcile. Task-related imaging studies often require a high level of compliance and can only partially explore the distributed nature and complexity of brain function. In this study, resting state functional connectivity imaging was used to investigate well-characterized brain networks potentially relevant to understand the neural mechanisms underlying the symptomatology and etiology of AN. Resting state functional magnetic resonance imaging data was obtained from 35 unmedicated female acute AN patients and 35 closely matched healthy controls female participants (HC) and decomposed using spatial group independent component analyses (ICA). Using validated templates, we identified components covering the fronto-parietal "control" network, the default mode network (DMN), the salience network, the visual and the sensory-motor network. Group comparison revealed an increased functional connectivity between the angular gyrus and the other parts of the fronto-parietal network in patients with AN in comparison to HC. Connectivity of the angular gyrus was positively associated with self-reported persistence in HC. In the DMN, AN patients also showed an increased functional connectivity strength in the anterior insula in comparison to HC. Anterior insula connectivity was associated with self-reported problems with interoceptive awareness. This study, with one of the largest sample to date, shows that acute AN is associated with abnormal brain connectivity in two major resting state networks (RSN). The finding of an increased functional connectivity in the fronto-parietal network adds novel support for the notion of AN as a disorder of excessive cognitive control, whereas the elevated functional connectivity of the anterior insula with the DMN may reflect the high levels of self- and body-focused ruminations when AN patients are at rest.
PMID: 25324749 [PubMed]
Discriminative sparse connectivity patterns for classification of fMRI Data.
Med Image Comput Comput Assist Interv. 2014;17(Pt 3):193-200
Authors: Eavani H, Satterthwaite TD, Gur RE, Gur RC, Davatzikos C
Functional connectivity using resting-state fMRI has emerged as an important research tool for understanding normal brain function as well as changes occurring during brain development and in various brain disorders. Most prior work has examined changes in pairwise functional connectivity values using a multi-variate classification approach, such as Support Vector Machines (SVM). While it is powerful, SVMs produce a dense set of high-dimensional weight vectors as output, which are difficult to interpret, and require additional post-processing to relate to known functional networks. In this paper, we propose a joint framework that combines network identification and classification, resulting in a set of networks, or Sparse Connectivity Patterns (SCPs) which are functionally interpretable as well as highly discriminative of the two groups. Applied to a study of normal development classifying children vs. adults, the proposed method provided accuracy of 76%(AUC= 0.85), comparable to SVM (79%,AUC=0.87), but with dramatically fewer number of features (50 features vs. 34716 for the SVM). More importantly, this leads to a tremendous improvement in neuro-scientific interpretability, which is specially advantageous in such a study where the group differences are wide-spread throughout the brain. Highest-ranked discriminative SCPs reflect increases in long-range connectivity in adults between the frontal areas and posterior cingulate regions. In contrast, connectivity between the bilateral parahippocampal gyri was decreased in adults compared to children.
PMID: 25320799 [PubMed - in process]
Multiple-network classification of childhood autism using functional connectivity dynamics.
Med Image Comput Comput Assist Interv. 2014;17(Pt 3):177-84
Authors: Price T, Wee CY, Gao W, Shen D
Characterization of disease using stationary resting-state functional connectivity (FC) has provided important hallmarks of abnormal brain activation in many domains. Recent studies of resting-state functional magnetic resonance imaging (fMRI), however, suggest there is a considerable amount of additional knowledge to be gained by investigating the variability in FC over the course of a scan. While a few studies have begun to explore the properties of dynamic FC for characterizing disease, the analysis of dynamic FC over multiple networks at multiple time scales has yet to be fully examined. In this study, we combine dynamic connectivity features in a multi-network, multi-scale approach to evaluate the method's potential in better classifying childhood autism. Specifically, from a set of group-level intrinsic connectivity networks (ICNs), we use sliding window correlations to compute intra-network connectivity on the subject level. We derive dynamic FC features for all ICNs over a large range of window sizes and then use a multiple kernel support vector machine (MK-SVM) model to combine a subset of these features for classification. We compare the performance our multi-network, dynamic approach to the best results obtained from single-network dynamic FC features and those obtained from both single- and multi-network static FC features. Our experiments show that integrating multiple networks on different dynamic scales has a clear superiority over these existing methods.
PMID: 25320797 [PubMed - in process]
Large-scale brain network dynamics supporting adolescent cognitive control.
J Neurosci. 2014 Oct 15;34(42):14096-107
Authors: Dwyer DB, Harrison BJ, Yücel M, Whittle S, Zalesky A, Pantelis C, Allen NB, Fornito A
Adolescence is a time when the ability to engage cognitive control is linked to crucial life outcomes. Despite a historical focus on prefrontal cortex functioning, recent evidence suggests that differences between individuals may relate to interactions between distributed brain regions that collectively form a cognitive control network (CCN). Other research points to a spatially distinct and functionally antagonistic system-the default-mode network (DMN)-which typically deactivates during performance of control tasks. This literature implies that individual differences in cognitive control are determined either by activation or functional connectivity of CCN regions, deactivation or functional connectivity of DMN regions, or some combination of both. We tested between these possibilities using a multilevel fMRI characterization of CCN and DMN dynamics, measured during performance of a cognitive control task and during a task-free resting state, in 73 human adolescents. Better cognitive control performance was associated with (1) reduced activation of CCN regions, but not deactivation of the DMN; (2) variations in task-related, but not resting-state, functional connectivity within a distributed network involving both the CCN and DMN; (3) functional segregation of core elements of these two systems; and (4) task-dependent functional integration of a set of peripheral nodes into either one network or the other in response to prevailing stimulus conditions. These results indicate that individual differences in adolescent cognitive control are not solely attributable to the functioning of any single region or network, but are instead dependent on a dynamic and context-dependent interplay between the CCN and DMN.
PMID: 25319705 [PubMed - in process]
Resting-State Functional Connectivity Changes in Aging apoE4 and apoE-KO Mice.
J Neurosci. 2014 Oct 15;34(42):13963-75
Authors: Zerbi V, Wiesmann M, Emmerzaal TL, Jansen D, Van Beek M, Mutsaers MP, Beckmann CF, Heerschap A, Kiliaan AJ
It is well established that the cholesterol-transporter apolipoprotein ε (APOE) genotype is associated with the risk of developing neurodegenerative diseases. Recently, brain functional connectivity (FC) in apoE-ε4 carriers has been investigated by means of resting-state fMRI, showing a marked differentiation in several functional networks at different ages compared with carriers of other apoE isoforms. The causes of such hampered FC are not understood. We hypothesize that vascular function and synaptic repair processes, which are both impaired in carriers of ε4, are the major contributors to the loss of FC during aging. To test this hypothesis, we integrated several different MRI techniques with immunohistochemistry and investigated FC changes in relation with perfusion, diffusion, and synaptic density in apoE4 and apoE-knock-out (KO) mice at 12 (adult) and 18 months of age. Compared with wild-type mice, we detected FC deficits in both adult and old apoE4 and apoE-KO mice. In apoE4 mice, these changes occurred concomitant with increased mean diffusivity in the hippocampus, whereas perfusion deficits appear only later in life, together with reduced postsynaptic density levels. Instead, in apoE-KO mice FC deficits were mirrored by strongly reduced brain perfusion since adulthood. In conclusion, we provide new evidence for a relation between apoE and brain connectivity, possibly mediated by vascular risk factors and by the efficiency of APOE as synaptic modulator in the brain. Our results show that multimodal MR neuroimaging is an excellent tool to assess brain function and to investigate early neuropathology and aging effects in translational research.
PMID: 25319693 [PubMed - in process]
Case-control resting-state fMRI study of brain functioning among adolescents with first-episode major depressive disorder.
Shanghai Arch Psychiatry. 2014 Aug;26(4):207-15
Authors: Gong Y, Hao L, Zhang X, Zhou Y, Li J, Zhao Z, Jiang W, DU Y
BACKGROUND: Adolescent depression results in severe and protracted suffering for affected individuals and their family members, but the underlying mechanism of this disabling condition remains unclear.
OBJECTIVES: Compare resting-state brain functioning between first-episode, drug-naïve adolescents with major depressive disorder and matched controls.
METHODS: Fifteen adolescents with major depressive disorder and 16 controls underwent a resting-state fMRI scan performed using a 3T magnetic resonance scanner. The amplitude of low frequency fluctuation (ALFF) was used to assess resting-state brain function.
RESULTS: Adolescents with depression had higher mean (sd) scores on the Children Depression Inventory (CDI) than controls (22.13 [9.21] vs. 9.37 [5.65]). Compared with controls, adolescents with depression had higher ALFF in the posterior cingulate gyrus, left inferior temporal gyrus, right superior temporal gyrus, right insula, right parietal lobe, and right fusiform gyrus; they also exhibited lower ALFF in the bilateral cuneus, the left occipital lobe, and the left medial frontal lobe.
CONCLUSIONS: Adolescent depression is associated with significant changes in the functioning of several regions of the brain.
PMID: 25317007 [PubMed]
Are Epilepsy-Related fMRI Components Dependent on the Presence of Interictal Epileptic Discharges in Scalp EEG?
Brain Topogr. 2014 Oct 16;
Authors: van Houdt PJ, Ossenblok PP, Colon AJ, Hermans KH, Verdaasdonk RM, Boon PA, de Munck JC
Spatial independent component analysis (ICA) is increasingly being used to extract resting-state networks from fMRI data. Previous studies showed that ICA also reveals independent components (ICs) related to the seizure onset zone. However, it is currently unknown how these epileptic ICs depend on the presence of interictal epileptic discharges (IEDs) in the EEG. The goal of this study was to explore the relation between ICs obtained from fMRI epochs during the occurrence of IEDs in the EEG and those without IEDs. fMRI data sets with co-registered EEG were retrospectively selected of patients from whom the location of the epileptogenic zone was confirmed by outcome of surgery (n = 8). The fMRI data were split into two epochs: one with IEDs visible in scalp EEG and one without. Spatial ICA was applied to the fMRI data of each part separately. The maps of all resulting components were compared to the resection area and the EEG-fMRI correlation pattern by computing a spatial correlation coefficient to detect the epilepsy-related component. For all patients, except one, there was a remarkable resemblance between the epilepsy-related components selected during epochs with IEDs and those without IEDs. These findings suggest that epilepsy-related ICs are not dependent on the presence of IEDs in scalp EEG. Since these epileptic ICs showed partial overlap with resting-state networks of healthy volunteers (n = 10), our study supports the need for new ways to classify epileptic ICs.
PMID: 25315607 [PubMed - as supplied by publisher]
Phonemic Fluency and Brain Connectivity in Age-Related Macular Degeneration: A Pilot Study.
Brain Connect. 2014 Oct 14;
Authors: Whitson HE, Chou YH, Potter G, Diaz M, Chen NK, Lad E, Johnson M, Cousins S, Zhuang J, Madden D
Age-related macular degeneration (AMD), the leading cause of blindness in developed nations, has been associated with poor performance on tests of phonemic fluency. This pilot study sought to: 1) characterize the relationship between phonemic fluency and resting-state functional brain connectivity in AMD patients and 2) determine whether regional connections associated with phonemic fluency in AMD patients were similarly linked to phonemic fluency in healthy participants. Behavior-based connectivity analysis (BBCA) was applied to resting-state, functional magnetic resonance imaging (fMRI) data from seven patients (mean age 79.9+7.5 years) with bilateral AMD who completed fluency tasks prior to imaging. Phonemic fluency was inversely related to the strength of functional connectivity (FC) among six pairs of brain regions, representing eight nodes: left opercular portion of inferior frontal gyrus (which includes Broca's area), left superior temporal gyrus (which includes part of Wernicke's area), inferior parietal lobe (bilaterally), right superior parietal lobe, right supramarginal gyrus, right supplementary motor area, and right precentral gyrus. The FC of these reference links was not related to phonemic fluency among 32 healthy individuals (16 younger adults, mean age 23.5 + 4.6 years and 16 older adults, mean age 68.3+3.4 years). Compared to healthy individuals, AMD patients exhibited higher mean connectivity within the reference links and within the default mode network (DMN), possibly reflecting compensatory changes to support performance in the setting of reduced vision. These findings are consistent with the hypothesis that phonemic fluency deficits in AMD reflect underlying brain changes that develop in the context of AMD.
PMID: 25313954 [PubMed - as supplied by publisher]
Increased functional connectivity strength of right inferior temporal gyrus in first-episode, drug-naive somatization disorder.
Aust N Z J Psychiatry. 2014 Oct 13;
Authors: Su Q, Yao D, Jiang M, Liu F, Jiang J, Xu C, Dai Y, Yu M, Long L, Li H, Liu J, Zhang Z, Zhang J, Xiao C, Guo W
BACKGROUND: Evidence of brain structural and functional alterations have been implicated in patients with somatization disorder (SD). However, little is known about brain functional connectivity in SD. In the present study, resting-state functional magnetic resonance imaging (fMRI) and graph theory were used to obtain a comprehensive view of whole-brain functional connectivity and to investigate the changes of voxel-wise functional networks in patients with SD.
METHODS: Twenty-five first-episode, medication-naive patients with SD and 28 age-, sex- and education-matched healthy controls (HCs) underwent resting-state fMRI. The graph theory approach was employed to analyze the data.
RESULTS: Compared to the HCs, patients with SD showed significantly increased functional connectivity strength in the right inferior temporal gyrus (ITG). There is a significant positive correlation between the z-values of the cluster in the right ITG and Hamilton Anxiety Scale scores.
CONCLUSIONS: Our findings indicate that there is a disruption of the functional connectivity pattern in the right ITG in first-episode, treatment-naive patients with SD, which bears clinical significance.
PMID: 25313257 [PubMed - as supplied by publisher]
Baseline effects of transcranial direct current stimulation on glutamatergic neurotransmission and large-scale network connectivity.
Brain Res. 2014 Oct 10;
Authors: Hunter MA, Coffman BA, Gasparovic C, Calhoun VD, Trumbo MC, Clark VP
Transcranial direct current stimulation (tDCS) modulates glutamatergic neurotransmission and can be utilized as a novel treatment intervention for a multitude of populations. However, the exact mechanism by which tDCS modulates the brain's neural architecture, from the micro to macro scales, have yet to be illuminated. Using a within-subjects design, resting-state functional magnetic resonance imaging (rs-fMRI) and proton magnetic resonance spectroscopy ((1)H-MRS) were performed immediately before and after the administration of anodal tDCS over right parietal cortex. Group independent component analysis (ICA) was used to decompose fMRI scans into 75 brain networks, from which 12 resting-state networks were identified that had significant voxel-wise functional connectivity to anatomical regions of interest. (1)H-MRS was used to obtain estimates of combined glutamate and glutamine (Glx) concentrations from bilateral intraparietal sulcus. Paired sample t-tests showed significantly increased Glx under the anodal electrode, but not in homologous regions of the contralateral hemisphere. Increases of within-network connectivity were observed within the superior parietal, inferior parietal, left frontal-parietal, salience and cerebellar intrinsic networks, and decreases in connectivity were observed in the anterior cingulate and the basal ganglia (p<0.05, FDR-corrected). Individual differences in Glx concentrations predicted network connectivity in most of these networks. The observed relationships between glutamatergic neurotransmission and network connectivity may be used to guide future tDCS protocols that aim to target and alter neuroplastic mechanisms in healthy individuals as well as those with psychiatric and neurologic disorders.
PMID: 25312829 [PubMed - as supplied by publisher]
Brain Imaging Analysis.
Annu Rev Stat Appl. 2014 Jan;1:61-85
Authors: Bowman FD
The increasing availability of brain imaging technologies has led to intense neuroscientific inquiry into the human brain. Studies often investigate brain function related to emotion, cognition, language, memory, and numerous other externally induced stimuli as well as resting-state brain function. Studies also use brain imaging in an attempt to determine the functional or structural basis for psychiatric or neurological disorders and, with respect to brain function, to further examine the responses of these disorders to treatment. Neuroimaging is a highly interdisciplinary field, and statistics plays a critical role in establishing rigorous methods to extract information and to quantify evidence for formal inferences. Neuroimaging data present numerous challenges for statistical analysis, including the vast amounts of data collected from each individual and the complex temporal and spatial dependence present. We briefly provide background on various types of neuroimaging data and analysis objectives that are commonly targeted in the field. We present a survey of existing methods targeting these objectives and identify particular areas offering opportunities for future statistical contribution.
PMID: 25309940 [PubMed - as supplied by publisher]
Functional connectivity and neuronal variability of resting state activity in bipolar disorder-reduction and decoupling in anterior cortical midline structures.
Hum Brain Mapp. 2014 Oct 12;
Authors: Magioncalda P, Martino M, Conio B, Escelsior A, Piaggio N, Presta A, Marozzi V, Rocchi G, Anastasio L, Vassallo L, Ferri F, Huang Z, Roccatagliata L, Pardini M, Northoff G, Amore M
Introduction: The cortical midline structures seem to be involved in the modulation of different resting state networks, such as the default mode network (DMN) and salience network (SN). Alterations in these systems, in particular in the perigenual anterior cingulate cortex (PACC), seem to play a central role in bipolar disorder (BD). However, the exact role of the PACC, and its functional connections to other midline regions (within and outside DMN) still remains unclear in BD. Methods: We investigated functional connectivity (FC), standard deviation (SD, as a measure of neuronal variability) and their correlation in bipolar patients (n = 40) versus healthy controls (n = 40), in the PACC and in its connections in different frequency bands (standard: 0.01-0.10 Hz; Slow-5: 0.01-0.027 Hz; Slow-4: 0.027-0.073 Hz). Finally, we studied the correlations between FC alterations and clinical-neuropsychological parameters and we explored whether subgroups of patients in different phases of the illness present different patterns of FC abnormalities. Results: We found in BD decreased FC (especially in Slow-5) from the PACC to other regions located predominantly in the posterior DMN (such as the posterior cingulate cortex (PCC) and inferior temporal gyrus) and in the SN (such as the supragenual anterior cingulate cortex and ventrolateral prefrontal cortex). Second, we found in BD a decoupling between PACC-based FC and variability in the various target regions (without alteration in variability itself). Finally, in our subgroups explorative analysis, we found a decrease in FC between the PACC and supragenual ACC (in depressive phase) and between the PACC and PCC (in manic phase). Conclusions: These findings suggest that in BD the communication, that is, information transfer, between the different cortical midline regions within the cingulate gyrus does not seem to work properly. This may result in dysbalance between different resting state networks like the DMN and SN. A deficit in the anterior DMN-SN connectivity could lead to an abnormal shifting toward the DMN, while a deficit in the anterior DMN-posterior DMN connectivity could lead to an abnormal shifting toward the SN, resulting in excessive focusing on internal contents and reduced transition from idea to action or in excessive focusing on external contents and increased transition from idea to action, respectively, which could represent central dimensions of depression and mania. If confirmed, they could represent diagnostic markers in BD. Hum Brain Mapp, 2014. © 2014 Wiley Periodicals, Inc.
PMID: 25307723 [PubMed - as supplied by publisher]
Research Review: Functional brain connectivity and child psychopathology - overview and methodological considerations for investigators new to the field.
J Child Psychol Psychiatry. 2014 Oct 12;
Authors: Matthews M, Fair DA
BACKGROUND: Functional connectivity MRI is an emerging technique that can be used to investigate typical and atypical brain function in developing and aging populations. Despite some of the current confounds in the field of functional connectivity MRI, the translational potential of the technique available to investigators may eventually be used to improve diagnosis, early disease detection, and therapy monitoring.
METHOD AND SCOPE: Based on a comprehensive survey of the literature, this review offers an introduction of resting-state functional connectivity for new investigators to the field of resting-state functional connectivity. We discuss a brief history of the technique, various methods of analysis, the relationship of functional networks to behavior, as well as the translational potential of functional connectivity MRI to investigate neuropsychiatric disorders. We also address some considerations and limitations with data analysis and interpretation.
CONCLUSIONS: The information provided in this review should serve as a foundation for investigators new to the field of resting-state functional connectivity. The discussion provides a means to better understand functional connectivity and its application to typical and atypical brain function.
PMID: 25307115 [PubMed - as supplied by publisher]
Abnormal Functional Resting-State Networks in ADHD: Graph Theory and Pattern Recognition Analysis of fMRI Data.
Biomed Res Int. 2014;2014:380531
Authors: Dos Santos Siqueira A, Biazoli Junior CE, Comfort WE, Rohde LA, Sato JR
The framework of graph theory provides useful tools for investigating the neural substrates of neuropsychiatric disorders. Graph description measures may be useful as predictor variables in classification procedures. Here, we consider several centrality measures as predictor features in a classification algorithm to identify nodes of resting-state networks containing predictive information that can discriminate between typical developing children and patients with attention-deficit/hyperactivity disorder (ADHD). The prediction was based on a support vector machines classifier. The analyses were performed in a multisite and publicly available resting-state fMRI dataset of healthy children and ADHD patients: the ADHD-200 database. Network centrality measures contained little predictive information for the discrimination between ADHD patients and healthy subjects. However, the classification between inattentive and combined ADHD subtypes was more promising, achieving accuracies higher than 65% (balance between sensitivity and specificity) in some sites. Finally, brain regions were ranked according to the amount of discriminant information and the most relevant were mapped. As hypothesized, we found that brain regions in motor, frontoparietal, and default mode networks contained the most predictive information. We concluded that the functional connectivity estimations are strongly dependent on the sample characteristics. Thus different acquisition protocols and clinical heterogeneity decrease the predictive values of the graph descriptors.
PMID: 25309910 [PubMed - as supplied by publisher]