scholarly journals Data on subjective recollection effects reflected in large-scale functional connectivity patterns in postpartum women

Data in Brief ◽  
2018 ◽  
Vol 19 ◽  
pp. 1142-1147
Author(s):  
Yoonjin Nah ◽  
Na-Young Shin ◽  
Sehjung Yi ◽  
Seung-Koo Lee ◽  
Sanghoon Han
eLife ◽  
2018 ◽  
Vol 7 ◽  
Author(s):  
Ruedeerat Keerativittayayut ◽  
Ryuta Aoki ◽  
Mitra Taghizadeh Sarabi ◽  
Koji Jimura ◽  
Kiyoshi Nakahara

Although activation/deactivation of specific brain regions has been shown to be predictive of successful memory encoding, the relationship between time-varying large-scale brain networks and fluctuations of memory encoding performance remains unclear. Here, we investigated time-varying functional connectivity patterns across the human brain in periods of 30–40 s, which have recently been implicated in various cognitive functions. During functional magnetic resonance imaging, participants performed a memory encoding task, and their performance was assessed with a subsequent surprise memory test. A graph analysis of functional connectivity patterns revealed that increased integration of the subcortical, default-mode, salience, and visual subnetworks with other subnetworks is a hallmark of successful memory encoding. Moreover, multivariate analysis using the graph metrics of integration reliably classified the brain network states into the period of high (vs. low) memory encoding performance. Our findings suggest that a diverse set of brain systems dynamically interact to support successful memory encoding.


Neurology ◽  
2019 ◽  
Vol 92 (22) ◽  
pp. e2550-e2558 ◽  
Author(s):  
Gianluca Coppola ◽  
Antonio Di Renzo ◽  
Barbara Petolicchio ◽  
Emanuele Tinelli ◽  
Cherubino Di Lorenzo ◽  
...  

ObjectiveWe investigated resting-state (RS)-fMRI using independent component analysis (ICA) to determine the functional connectivity (FC) between networks in chronic migraine (CM) patients and their correlation with clinical features.MethodsTwenty CM patients without preventive therapy or acute medication overuse underwent 3T MRI scans and were compared to a group of 20 healthy controls (HC). We used MRI to collect RS data in 3 selected networks, identified using group ICA: the default mode network (DMN), the executive control network (ECN), and the dorsal attention system (DAS).ResultsCompared to HC, CM patients had significantly reduced functional connectivity between the DMN and the ECN. Moreover, in patients, the DAS showed significantly stronger FC with the DMN and weaker FC with the ECN. The higher the severity of headache, the increased the strength of DAS connectivity, and the lower the strength of ECN connectivity.ConclusionThese results provide evidence for large-scale reorganization of functional cortical networks in chronic migraine. They suggest that the severity of headache is associated with opposite connectivity patterns in frontal executive and dorsal attentional networks.


2018 ◽  
Author(s):  
Paulina Kieliba ◽  
Sasidhar Madugula ◽  
Nicola Filippini ◽  
Eugene P. Duff ◽  
Tamar R. Makin

AbstractMeasuring whole-brain functional connectivity patterns based on task-free (‘restingstate’) spontaneous fluctuations in the functional MRI (fMRI) signal is a standard approach to probing habitual brain states, independent of task-specific context. This view is supported by spatial correspondence between task- and rest-derived connectivity networks. Yet, it remains unclear whether intrinsic connectivity observed in a resting-state acquisitions is persistent during task. Here, we sought to determine how changes in ongoing brain activation, elicited by task performance, impact the integrity of whole-brain functional connectivity patterns. We employed a ‘steadystates’ paradigm, in which participants continuously executed a specific task (without baseline periods). Participants underwent separate task-based (visual, motor and visuomotor) or task-free (resting) steady-state scans, each performed over a 5-minute period. This unique design allowed us to apply a set of traditional resting-state analyses to various task-states. In addition, a classical fMRI block-design was employed to identify individualized brain activation patterns for each task, allowing to characterize how differing activation patterns across the steady-states impact whole-brain intrinsic connectivity patterns. By examining correlations across segregated brain regions (nodes) and the whole brain (using independent component analysis), we show that the whole-brain network architecture characteristic of the resting-state is robustly preserved across different steady-task states, despite striking inter-task changes in brain activation (signal amplitude). Subtler changes in functional connectivity were detected locally, within the active networks. Together, we show that intrinsic connectivity underlying the canonical resting-state networks is relatively stable even when participants are engaged in different tasks and is not limited to the resting-state.New and NoteworthyDoes intrinsic functional connectivity (FC) reflect the canonical or transient state of the brain? We tested the consistency of the intrinsic connectivity networks across different task-conditions. We show that despite local changes in connectivity, at the whole-brain level there is little modulation in FC patterns, despite profound and large-scale activation changes. We therefore conclude that intrinsic FC largely reflects the a priori habitual state of the brain, independent of the specific cognitive context.


2021 ◽  
Author(s):  
Ayan S Mandal ◽  
Rafael Romero-Garcia ◽  
Jakob Seidlitz ◽  
Michael G Hart ◽  
Aaron Alexander-Bloch ◽  
...  

Diffuse gliomas have been hypothesized to originate from neural stem cells in the subventricular zone. Here, we evaluated this hypothesis by mapping independent sources of glioma localization and determining their relationships with neurogenic niches, genetic markers, and large-scale connectivity networks. Using lesion data from a total of 410 patients with glioma, we identified -- and replicated in an independent sample -- three lesion covariance networks (LCNs), which reflect clusters of frequent glioma co-localization. Each LCN overlapped with a distinct horn of the lateral ventricles. The first LCN, which overlapped with the anterior horn, was associated with low-grade, IDH-mutated/1p19q-codeleted tumors, as well as a neural transcriptomic signature and improved overall survival. Each LCN significantly corresponded with multiple brain networks, with LCN1 bearing an especially strong relationship with structural and functional connectivity, consistent with its neural transcriptomic profile. Finally, we identified subcortical, periventricular structures with functional connectivity patterns to the cortex that significantly matched each LCN. Cumulatively, our findings support a model wherein periventricular brain connectivity guides tumor development.


2011 ◽  
Vol 106 (3) ◽  
pp. 1125-1165 ◽  
Author(s):  
B. T. Thomas Yeo ◽  
Fenna M. Krienen ◽  
Jorge Sepulcre ◽  
Mert R. Sabuncu ◽  
Danial Lashkari ◽  
...  

Information processing in the cerebral cortex involves interactions among distributed areas. Anatomical connectivity suggests that certain areas form local hierarchical relations such as within the visual system. Other connectivity patterns, particularly among association areas, suggest the presence of large-scale circuits without clear hierarchical relations. In this study the organization of networks in the human cerebrum was explored using resting-state functional connectivity MRI. Data from 1,000 subjects were registered using surface-based alignment. A clustering approach was employed to identify and replicate networks of functionally coupled regions across the cerebral cortex. The results revealed local networks confined to sensory and motor cortices as well as distributed networks of association regions. Within the sensory and motor cortices, functional connectivity followed topographic representations across adjacent areas. In association cortex, the connectivity patterns often showed abrupt transitions between network boundaries. Focused analyses were performed to better understand properties of network connectivity. A canonical sensory-motor pathway involving primary visual area, putative middle temporal area complex (MT+), lateral intraparietal area, and frontal eye field was analyzed to explore how interactions might arise within and between networks. Results showed that adjacent regions of the MT+ complex demonstrate differential connectivity consistent with a hierarchical pathway that spans networks. The functional connectivity of parietal and prefrontal association cortices was next explored. Distinct connectivity profiles of neighboring regions suggest they participate in distributed networks that, while showing evidence for interactions, are embedded within largely parallel, interdigitated circuits. We conclude by discussing the organization of these large-scale cerebral networks in relation to monkey anatomy and their potential evolutionary expansion in humans to support cognition.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Chandra Sripada ◽  
Mike Angstadt ◽  
Aman Taxali ◽  
D. Angus Clark ◽  
Tristan Greathouse ◽  
...  

AbstractGeneral cognitive ability (GCA) is an individual difference dimension linked to important academic, occupational, and health-related outcomes and its development is strongly linked to differences in socioeconomic status (SES). Complex abilities of the human brain are realized through interconnections among distributed brain regions, but brain-wide connectivity patterns associated with GCA in youth, and the influence of SES on these connectivity patterns, are poorly understood. The present study examined functional connectomes from 5937 9- and 10-year-olds in the Adolescent Brain Cognitive Development (ABCD) multi-site study. Using multivariate predictive modeling methods, we identified whole-brain functional connectivity patterns linked to GCA. In leave-one-site-out cross-validation, we found these connectivity patterns exhibited strong and statistically reliable generalization at 19 out of 19 held-out sites accounting for 18.0% of the variance in GCA scores (cross-validated partial η2). GCA-related connections were remarkably dispersed across brain networks: across 120 sets of connections linking pairs of large-scale networks, significantly elevated GCA-related connectivity was found in 110 of them, and differences in levels of GCA-related connectivity across brain networks were notably modest. Consistent with prior work, socioeconomic status was a strong predictor of GCA in this sample, and we found that distributed GCA-related brain connectivity patterns significantly statistically mediated this relationship (mean proportion mediated: 15.6%, p < 2 × 10−16). These results demonstrate that socioeconomic status and GCA are related to broad and diffuse differences in functional connectivity architecture during early adolescence, potentially suggesting a mechanism through which socioeconomic status influences cognitive development.


2019 ◽  
Author(s):  
Jonathan F. O’Rawe ◽  
Hoi-Chung Leung

AbstractThe striatum is postulated to play a role in gating cortical processing during goal-oriented behavior. However, the underlying circuit structure for striatal gating remains unclear. Deviating from previous approaches which typically treat the striatum as a homogenous structure or small compartments, we took a functional connectivity approach that utilizes the entire anatomical space of the caudate nucleus and examined its functional relationship with the cortex and how that relationship changes with age. We defined the topography of the caudate functional connectivity with the rest of the brain using three publicly available resting-state fMRI data samples. There were several key findings. First, our results revealed two stable gradients of connectivity patterns across the caudate: medial-lateral (M-L) and anterior-posterior (A-P) axes, which supports findings in previous anatomical studies of non-human primates that there is more than one organizational principle. Second, the differential connectivity patterns along the caudate’s M-L gradient were not limited to single structures but rather organized with respect to large-scale neural networks; in particular, networks associated with internal orienting behavior are closely linked to the medial extent of the caudate whereas networks associated with external orienting behavior are closely linked to the lateral extent of the caudate. Third, we found a decrease in the integrity of M-L organization with healthy aging which was associated with age-related changes in behavioral measures of flexible control. In sum, the caudate shows a topographic organization with respect to large-scale networks in the human brain and changes this organization seem to have implications for age-related decline in flexible control of behavior.


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