Fuyuze Tokoglu

Groupwise whole-brain parcellation from resting-state fMRI data for network node identification.

In this paper, we present a groupwise graph-theory-based parcellation approach to define nodes for network analysis. The application of network-theory-based analysis to extend the utility of functional MRI has recently received increased attention. Such analyses require first and foremost a reasonable definition of a set of nodes as input to the network analysis. To date many applications have used existing atlases based on cytoarchitecture, task-based fMRI activations, or anatomic delineations. A potential pitfall in using such atlases is that the mean timecourse of a node may not represent any of the constituent timecourses if different functional areas are included within a single node. The proposed approach involves a groupwise optimization that ensures functional homogeneity within each subunit and that these definitions are consistent at the group level. Parcellation reproducibility of each subunit is computed across multiple groups of healthy volunteers and is demonstrated to be high. Issues related to the selection of appropriate number of nodes in the brain are considered. Within typical parameters of fMRI resolution, parcellation results are shown for a total of 100, 200, and 300 subunits. Such parcellations may ultimately serve as a functional atlas for fMRI and as such three atlases at the 100-, 200- and 300-parcellation levels derived from 79 healthy normal volunteers are made freely available online along with tools to interface this atlas with SPM, BioImage Suite and other analysis packages.

Connectivity-behavior analysis reveals that functional connectivity between left BA39 and Broca's area varies with reading ability.

Correlations between temporal fluctuations in MRI signals may reveal functional connectivity between brain regions within individual subjects. Such correlations would be especially useful indices of functional connectivity if they covary with behavioral performance or other subject variables. This study investigated whether such a relationship could be demonstrated in the context of the reading circuit in the brain. The method proved sufficiently powerful to reveal significant correlations between the reading abilities of subjects and the strength of their functional connection between left Brodmanns area 39 and Brocas area during reading. This suggests that the disconnection of the angular gyrus previously reported for dyslexic readers is part of a larger continuum in which poor (but nonimpaired readers) also show reduced connectivity to the region. In addition, it illustrates the potential power of paradigms that examine correlations between behavior and functional brain connections.

Sex differences in normal age trajectories of functional brain networks

Resting‐state functional magnetic resonance image (rs‐fMRI) is increasingly used to study functional brain networks. Nevertheless, variability in these networks due to factors such as sex and aging is not fully understood. This study explored sex differences in normal age trajectories of resting‐state networks (RSNs) using a novel voxel‐wise measure of functional connectivity, the intrinsic connectivity distribution (ICD). Males and females showed differential patterns of changing connectivity in large‐scale RSNs during normal aging from early adulthood to late middle‐age. In some networks, such as the default‐mode network, males and females both showed decreases in connectivity with age, albeit at different rates. In other networks, such as the fronto‐parietal network, males and females showed divergent connectivity trajectories with age. Main effects of sex and age were found in many of the same regions showing sex‐related differences in aging. Finally, these sex differences in aging trajectories were robust to choice of preprocessing strategy, such as global signal regression. Our findings resolve some discrepancies in the literature, especially with respect to the trajectory of connectivity in the default mode, which can be explained by our observed interactions between sex and aging. Overall, results indicate that RSNs show different aging trajectories for males and females. Characterizing effects of sex and age on RSNs are critical first steps in understanding the functional organization of the human brain. Hum Brain Mapp 36:1524–1535, 2015.

Intrinsic Brain Connectivity Related to Age in Young and Middle Aged Adults

Age-related variations in resting state connectivity of the human brain were examined from young adulthood through middle age. A voxel-based network measure, degree, was used to assess age-related differences in tissue connectivity throughout the brain. Increases in connectivity with age were found in paralimbic cortical and subcortical regions. Decreases in connectivity were found in cortical regions, including visual areas and the default mode network. These findings differ from those of recent developmental studies examining earlier growth trajectories, and are consistent with known changes in cognitive function and emotional processing during mature aging. The results support and extend previous findings that relied on a priori definitions of regions of interest for their analyses. This approach of applying a voxel-based measure to examine the functional connectivity of individual tissue elements over time, without the need for a priori region of interest definitions, provides an important new tool in brain science.

Acupuncture-Induced Blood Oxygenation Level-Dependent Signals in Awake and Anesthetized Volunteers: A Pilot Study

BACKGROUND:There are conflicting data regarding clinical efficacy of acupuncture applied while patients are under general anesthesia. We hypothesize that these conflicting data are a result of the inhibitory effect of anesthesia on acupuncture-induced central nervous system activity that can be demonstrated using magnetic resonance imaging. METHODS:Using a crossover study design, volunteers received standardized Stomach 36 manual acupuncture in two experimental conditions: while undergoing a propofol-based general anesthetic, and while awake. Functional magnetic resonance imaging was conducted during both experimental sessions. Paired-t-test analyses were performed to examine the differences in acupuncture-induced blood oxygenation level-dependent (BOLD) signals between awake and anesthesia conditions. A secondary analysis was performed to account for the changes in regional cerebral blood flow at six regions of interest (thalamus, red nucleus, insula, periaqueductal gray, retrosplenial cingular gyri, and the inferior temporal region). RESULTS:Using BOLD, we found significant differences between the two experimental sessions in brain areas, including postcentral gyri, retrosplenial cingular area, left posterior insula, bilateral precuneus, thalamus, red nuclei, and substantia nigra (cluster 100, P < 0.01). A secondary analysis correcting for background cerebral blood flow found that BOLD signal differences between experimental conditions were not directly caused by changes in regional blood flow. DISCUSSION:Propofol-based anesthesia reduces the neurophysiological response to acupuncture stimulation as measured by acupuncture-induced BOLD signals. Further work should be conducted to determine the clinical significance of these findings.

Influences on the Test–Retest Reliability of Functional Connectivity MRI and its Relationship with Behavioral Utility

Abstract Best practices are currently being developed for the acquisition and processing of resting‐state magnetic resonance imaging data used to estimate brain functional organization—or “functional connectivity.” Standards have been proposed based on test‐retest reliability, but open questions remain. These include how amount of data per subject influences whole‐brain reliability, the influence of increasing runs versus sessions, the spatial distribution of reliability, the reliability of multivariate methods, and, crucially, how reliability maps onto prediction of behavior. We collected a dataset of 12 extensively sampled individuals (144 min data each across 2 identically configured scanners) to assess test‐retest reliability of whole‐brain connectivity within the generalizability theory framework. We used Human Connectome Project data to replicate these analyses and relate reliability to behavioral prediction. Overall, the historical 5‐min scan produced poor reliability averaged across connections. Increasing the number of sessions was more beneficial than increasing runs. Reliability was lowest for subcortical connections and highest for within‐network cortical connections. Multivariate reliability was greater than univariate. Finally, reliability could not be used to improve prediction; these findings are among the first to underscore this distinction for functional connectivity. A comprehensive understanding of test‐retest reliability, including its limitations, supports the development of best practices in the field.

Altered functional connectivity in seizure onset zones revealed by fMRI intrinsic connectivity

Objective: The purpose of this study was to investigate functional connectivity (FC) changes in epileptogenic networks in intractable partial epilepsy obtained from resting-state fMRI by using intrinsic connectivity contrast (ICC), a voxel-based network measure of degree that reflects the number of connections to each voxel. Methods: We measured differences between intrahemispheric- and interhemispheric-ICC (ICCintra−inter) that could reveal localized connectivity abnormalities in epileptogenic zones while more global network changes would be eliminated when subtracting these values. The ICCintra−inter map was compared with the seizure onset zone (SOZ) based on intracranial EEG (icEEG) recordings in 29 patients with at least 1 year of postsurgical follow-up. Two independent reviewers blindly interpreted the icEEG and fMRI data, and the concordance rates were compared for various clinical factors. Results: Concordance between the icEEG SOZ and ICCintra−inter map was observed in 72.4% (21/29) of the patients, which was higher in patients with good surgical outcome, especially in those patients with temporal lobe epilepsy (TLE) or lateral temporal seizure localization. Concordance was also better in the extratemporal lobe epilepsy than the TLE group. In 85.7% (18/21) of the cases, the ICCintra−inter values were negative in the SOZ, indicating decreased FC within the epileptic hemisphere relative to between hemispheres. Conclusions: Assessing alterations in FC using fMRI-ICC map can help localize the SOZ, which has potential as a noninvasive presurgical diagnostic tool to improve surgical outcome. In addition, the method reveals that, in focal epilepsy, both intrahemispheric- and interhemispheric-FC may be altered, in the presence of both regional as well as global network abnormalities.

Fluctuations in Global Brain Activity Are Associated With Changes in Whole-Brain Connectivity of Functional Networks

Objective: The aim of this study was to explore the relationship between global brain activity, changes in whole-brain connectivity, and changes in brain states across subjects using resting-state functional magnetic resonance imaging. Methods: We extended current methods that use a sparse set of coactivation patterns to extract critical time points in global brain activity. Critical activity time points were defined as points where the global signal is greater than one standard deviation above or below the average global signal. Four categories of critical points were defined along dimensions of global signal intensity and trajectory. Voxel-based methods were used to interrogate differences in connectivity between these critical points. Results: Several differences in connectivity were found in functional resting-state networks (RSNs) as a function of global activity. RSNs associated with cognitive functions in frontal, parietal, and subcortical regions exhibited greater whole-brain connectivity during lower global activity states. Meanwhile, RSNs associated with sensory functions exhibited greater whole-brain connectivity during the higher global activity states. Moreover, we present evidence that these results depend in part upon the standard deviation threshold used to define the critical points, suggesting critical points at different thresholds represent unique brain states. Conclusion: Overall, the findings support the hypothesis that the brain oscillates through different states over the course of a resting-state study reflecting differences in RSN connectivity associated with global brain activity. Significance: Increased understanding of brain dynamics may help to elucidate individual differences in behavior and dysfunction.

Modulating Intrinsic Connectivity: Adjacent Subregions within Supplementary Motor Cortex, Dorsolateral Prefrontal Cortex, and Parietal Cortex Connect to Separate Functional Networks during Task and Also Connect during Rest

Supplementary motor area (SMA), the inferior frontal junction (IFJ), superior frontal junction (SFJ) and parietal cortex are active in many cognitive tasks. In a previous study, we found that subregions of each of these major areas were differentially active in component processes of executive function during working memory tasks. In the present study, each of these subregions was used as a seed in a whole brain functional connectivity analysis of working memory and resting state data. These regions show functional connectivity to different networks, thus supporting the parcellation of these major regions into functional subregions. Many regions showing significant connectivity during the working memory residual data (with task events regressed from the data) were also significantly connected during rest suggesting that these network connections to subregions within major regions of cortex are intrinsic. For some of these connections, task demands modulate activity in these intrinsic networks. Approximately half of the connections significant during task were significant during rest, indicating that some of the connections are intrinsic while others are recruited only in the service of the task. Furthermore, the network connections to traditional ‘task positive’ and ‘task negative’ (a.k.a ‘default mode’) regions shift from positive connectivity to negative connectivity depending on task demands. These findings demonstrate that such task-identified subregions are part of distinct networks, and that these networks have different patterns of connectivity for task as they do during rest, engaging connections both to task positive and task negative regions. These results have implications for understanding the parcellation of commonly active regions into more specific functional networks.

Data-Driven Analysis of Functional Connectivity Reveals a Potential Auditory Verbal Hallucination Network

Abstract Schizophrenia is a severe global health problem, with over half of such patients experiencing auditory verbal hallucinations (AVHs). A better understanding of the neural correlates differentiating patients experiencing AVHs from patients not experiencing AVHs and healthy controls may identify targets that lead to better treatment strategies for AVHs. Employing 2 data-driven, voxel-based measure of functional connectivity, we studied 46 patients with schizophrenia or schizoaffective disorder (28 experiencing AVHs and 18 not experiencing AVHs). Twenty healthy controls matched for age, gender, ethnicity, education level, handedness, and estimated verbal intelligence were included for comparison. The intrinsic connectivity distribution (ICD) was used to model each voxel’s connectivity to the rest of the brain using a Weibull distribution. To investigate lateralization of connectivity, we used cross-hemisphere ICD, a method that separates the contribution of each hemisphere to interrogate connectivity laterality. Patients with AVHs compared with patients without AVHs exhibited significantly decreased whole-brain connectivity in the medial prefrontal cortex and posterior cingulate cortex, less lateralized connectivity in left putamen, and more lateralized connectivity in left interior frontal gyrus. Correlations with Auditory Hallucination Rating Scale (AHRS) and post hoc seed connectivity analyses revealed significantly altered network connectivity. Using the results from all analyses comparing the patient groups and correlations with AHRS, we identified a potential AVH network, consisting of 25 nodes, showing substantial overlap with the default mode network and language processing networks. This network as a whole, instead of individual nodes, may represent actionable targets for interventions.