scholarly journals Resting-State Functional Connectivity in Mathematical Expertise

2021 ◽  
Vol 11 (4) ◽  
pp. 430
Author(s):  
Miseon Shim ◽  
Han-Jeong Hwang ◽  
Ulrike Kuhl ◽  
Hyeon-Ae Jeon
Keyword(s):  
Functional Connectivity ◽  
Resting State ◽  
Resting State Fmri ◽  
Blood Oxygen Level Dependent ◽  
Brain Regions ◽  
Resting State Functional Connectivity ◽  
Blood Oxygen Level ◽  
Orbital Gyrus ◽  
Neural Efficiency ◽  
Mathematical Expertise

To what extent are different levels of expertise reflected in the functional connectivity of the brain? We addressed this question by using resting-state functional magnetic resonance imaging (fMRI) in mathematicians versus non-mathematicians. To this end, we investigated how the two groups of participants differ in the correlation of their spontaneous blood oxygen level-dependent fluctuations across the whole brain regions during resting state. Moreover, by using the classification algorithm in machine learning, we investigated whether the resting-state fMRI networks between mathematicians and non-mathematicians were distinguished depending on features of functional connectivity. We showed diverging involvement of the frontal–thalamic–temporal connections for mathematicians and the medial–frontal areas to precuneus and the lateral orbital gyrus to thalamus connections for non-mathematicians. Moreover, mathematicians who had higher scores in mathematical knowledge showed a weaker connection strength between the left and right caudate nucleus, demonstrating the connections’ characteristics related to mathematical expertise. Separate functional networks between the two groups were validated with a maximum classification accuracy of 91.19% using the distinct resting-state fMRI-based functional connectivity features. We suggest the advantageous role of preconfigured resting-state functional connectivity, as well as the neural efficiency for experts’ successful performance.

scholarly journals Effects of long-term cocaine self-administration on brain resting-state functional connectivity in nonhuman primates

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Stephen J. Kohut ◽  
Dionyssios Mintzopoulos ◽  
Brian D. Kangas ◽  
Hannah Shields ◽  
Kelly Brown ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Cognitive Processing ◽  
Resting State ◽  
Resting State Fmri ◽  
Brain Regions ◽  
Anterior Cingulate ◽  
Resting State Functional Connectivity ◽  
Self Administration ◽  
Chronic Cocaine

AbstractLong-term cocaine use is associated with a variety of neural and behavioral deficits that impact daily function. This study was conducted to examine the effects of chronic cocaine self-administration on resting-state functional connectivity of the dorsal anterior cingulate (dACC) and putamen—two brain regions involved in cognitive function and motoric behavior—identified in a whole brain analysis. Six adult male squirrel monkeys self-administered cocaine (0.32 mg/kg/inj) over 140 sessions. Six additional monkeys that had not received any drug treatment for ~1.5 years served as drug-free controls. Resting-state fMRI imaging sessions at 9.4 Tesla were conducted under isoflurane anesthesia. Functional connectivity maps were derived using seed regions placed in the left dACC or putamen. Results show that cocaine maintained robust self-administration with an average total intake of 367 mg/kg (range: 299–424 mg/kg). In the cocaine group, functional connectivity between the dACC seed and regions primarily involved in motoric behavior was weaker, whereas connectivity between the dACC seed and areas implicated in reward and cognitive processing was stronger. In the putamen seed, weaker widespread connectivity was found between the putamen and other motor regions as well as with prefrontal areas that regulate higher-order executive function; stronger connectivity was found with reward-related regions. dACC connectivity was associated with total cocaine intake. These data indicate that functional connectivity between regions involved in motor, reward, and cognitive processing differed between subjects with recent histories of cocaine self-administration and controls; in dACC, connectivity appears to be related to cumulative cocaine dosage during chronic exposure.

scholarly journals Resting-state functional connectivity of social brain regions predicts motivated dishonesty

2021 ◽  
Author(s):  
Luoyao Pang ◽  
Huidi Li ◽  
Quanying Liu ◽  
Yue-jia Luo ◽  
Dean Mobbs ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Resting State ◽  
Region Of Interest ◽  
Resting State Fmri ◽  
Brain Regions ◽  
Resting State Functional Connectivity ◽  
Social Brain ◽  
Moral Regulation ◽  
Interpretable Model ◽  
Reward Valuation

Motivated dishonesty is a typical social behavior varying from person to person. Resting-state fMRI (rsfMRI) is capable of identifying unique patterns from functional connectivity (FC) between brain networks. To identify the relevant neural patterns and build an interpretable model to predict dishonesty, we scanned 8-min rsfMRI before an information-passing task. In the task, we employed monetary rewards to induce dishonesty. We applied both connectome-based predictive modeling (CPM) and region-of-interest (ROI) analysis to examine the association between FC and dishonesty. CPM indicated that the stronger FC between fronto-parietal and default mode networks can predict a higher dishonesty rate. The ROIs were set in the regions involving four cognitive processes (self-reference, cognitive control, reward valuation, and moral regulation). The ROI analyses showed that a stronger FC between these regions and the prefrontal cortex can predict a higher dishonesty rate. Our study offers an integrated model to predict dishonesty with rsfMRI, and the results suggest that the frequent motivated dishonest behavior may require a higher engagement of social brain regions.

scholarly journals Advanced Meditation Alters Resting-State Brain Network Connectivity Correlating With Improved Mindfulness

2021 ◽  
Vol 12 ◽  
Author(s):  
Ramana V. Vishnubhotla ◽  
Rupa Radhakrishnan ◽  
Kestas Kveraga ◽  
Rachael Deardorff ◽  
Chithra Ram ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Resting State ◽  
Network Connectivity ◽  
Blood Oxygen Level Dependent ◽  
Brain Network ◽  
Resting State Functional Connectivity ◽  
Blood Oxygen Level ◽  
Default Mode ◽  
Before And After ◽  
Brain Network Connectivity

Purpose: The purpose of this study was to investigate the effect of an intensive 8-day Samyama meditation program on the brain functional connectivity using resting-state functional MRI (rs-fMRI).Methods: Thirteen Samyama program participants (meditators) and 4 controls underwent fMRI brain scans before and after the 8-day residential meditation program. Subjects underwent fMRI with a blood oxygen level dependent (BOLD) contrast at rest and during focused breathing. Changes in network connectivity before and after Samyama program were evaluated. In addition, validated psychological metrics were correlated with changes in functional connectivity.Results: Meditators showed significantly increased network connectivity between the salience network (SN) and default mode network (DMN) after the Samyama program (p < 0.01). Increased connectivity within the SN correlated with an improvement in self-reported mindfulness scores (p < 0.01).Conclusion: Samyama, an intensive silent meditation program, favorably increased the resting-state functional connectivity between the salience and default mode networks. During focused breath watching, meditators had lower intra-network connectivity in specific networks. Furthermore, increased intra-network connectivity correlated with improved self-reported mindfulness after Samyama.Clinical Trials Registration: [https://clinicaltrials.gov], Identifier: [NCT04366544]. Registered on 4/17/2020.

scholarly journals Differential effects of anesthetics on resting state functional connectivity in the mouse

2019 ◽  
Vol 40 (4) ◽  
pp. 875-884 ◽  
Author(s):  
Hongyu Xie ◽  
David Y Chung ◽  
Sreekanth Kura ◽  
Kazutaka Sugimoto ◽  
Sanem A Aykan ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Resting State ◽  
Chloral Hydrate ◽  
Low Frequency ◽  
Blood Oxygen Level Dependent ◽  
Resting State Functional Connectivity ◽  
Blood Oxygen Level ◽  
Intrinsic Signal ◽  
Optical Intrinsic Signal ◽  
Important Approach

Blood oxygen level-dependent (BOLD) functional MRI (fMRI) is a standard approach to examine resting state functional connectivity (RSFC), but fMRI in animal models is challenging. Recently, functional optical intrinsic signal imaging—which relies on the same hemodynamic signal underlying BOLD fMRI—has been developed as a complementary approach to assess RSFC in mice. Since it is difficult to ensure that an animal is in a truly resting state while awake, RSFC measurements under anesthesia remain an important approach. Therefore, we systematically examined measures of RSFC using non-invasive, widefield optical intrinsic signal imaging under five different anesthetics in male C57BL/6J mice. We find excellent seed-based, global, and interhemispheric connectivity using tribromoethanol (Avertin) and ketamine–xylazine, comparable to results in the literature including awake animals. Urethane anesthesia yielded intermediate results, while chloral hydrate and isoflurane were both associated with poor RSFC. Furthermore, we found a correspondence between the strength of RSFC and the power of low-frequency hemodynamic fluctuations. In conclusion, Avertin and ketamine–xylazine provide robust and reproducible measures of RSFC in mice, whereas chloral hydrate and isoflurane do not.

scholarly journals Parietal and hippocampal hyper-connectivity is associated with low math achievement in adolescence

2021 ◽  
Author(s):  
Roberto A. Abreu-Mendoza ◽  
Melanie Pincus ◽  
Yaira Chamorro ◽  
Dietsje Jolles ◽  
Esmeralda Matute ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Resting State ◽  
Math Achievement ◽  
Resting State Fmri ◽  
Brain Regions ◽  
Math Performance ◽  
Resting State Functional Connectivity ◽  
Neural Basis ◽  
Math Ability ◽  
Control Seed

Mathematical cognition requires coordinated activity across multiple brain regions, leading to the emergence of resting-state functional connectivity as a method for studying the neural basis of differences in mathematical achievement. Hyper-connectivity of the intraparietal sulcus (IPS), a key locus of mathematical and numerical processing, has been associated with poor mathematical skills in childhood, whereas greater connectivity has been related to better performance in adulthood. No studies to date have considered its role in adolescence. Further, hippocampal connectivity can predict mathematical learning, yet no studies have considered its contributions to contemporaneous measures of math achievement. Here, we used seed-based resting-state fMRI analyses to examine IPS and hippocampal intrinsic functional connectivity relations to math achievement in a group of 31 adolescents (mean age=16.42 years, range 15-17), whose math performance spanned the 1% to 99% percentile. After controlling for IQ, IPS connectivity was negatively related to math achievement, akin to findings in children. However, the specific temporooccipital regions, were more akin to the posterior loci implicated in adults. Hippocampal connectivity with frontal regions was also negatively correlated with concurrent math measures, which contrasts with results from learning studies. Finally, hyper-connectivity was not a global feature of low math performance, as connectivity of Heschl’s gyrus, a control seed not involved in math cognition, was not modulated by math performance. Together, our results point to adolescence as a transitional stage in which patterns found in childhood and adulthood can be observed; most notably, hyper-connectivity continues to be related to low math ability in this period.

scholarly journals Insulin Resistance-Associated Interhemispheric Functional Connectivity Alterations in T2DM: A Resting-State fMRI Study

2015 ◽  
Vol 2015 ◽  
pp. 1-9 ◽  
Author(s):  
Wenqing Xia ◽  
Shaohua Wang ◽  
Andrea M. Spaeth ◽  
Hengyi Rao ◽  
Pin Wang ◽  
...  
Keyword(s):  
Insulin Resistance ◽  
Functional Connectivity ◽  
Resting State ◽  
Correlation Coefficients ◽  
Resting State Fmri ◽  
Brain Regions ◽  
Middle Temporal Gyrus ◽  
Model Assessment ◽  
Healthy Controls ◽  
Resting State Functional Connectivity

We aim to investigate whether decreased interhemispheric functional connectivity exists in patients with type 2 diabetes mellitus (T2DM) by using resting-state functional magnetic resonance imaging (rs-fMRI). In addition, we sought to determine whether interhemispheric functional connectivity deficits associated with cognition and insulin resistance (IR) among T2DM patients. We compared the interhemispheric resting state functional connectivity of 32 T2DM patients and 30 healthy controls using rs-fMRI. Partial correlation coefficients were used to detect the relationship between rs-fMRI information and cognitive or clinical data. Compared with healthy controls, T2DM patients showed bidirectional alteration of functional connectivity in several brain regions. Functional connectivity values in the middle temporal gyrus (MTG) and in the superior frontal gyrus were inversely correlated with Trail Making Test-B score of patients. Notably, insulin resistance (log homeostasis model assessment-IR) negatively correlated with functional connectivity in the MTG of patients. In conclusion, T2DM patients exhibit abnormal interhemispheric functional connectivity in several default mode network regions, particularly in the MTG, and such alteration is associated with IR. Alterations in interhemispheric functional connectivity might contribute to cognitive dysfunction in T2DM patients.

scholarly journals Changes in visual and sensory-motor resting-state functional connectivity support motor learning by observing

2015 ◽  
Vol 114 (1) ◽  
pp. 677-688 ◽  
Author(s):  
Heather R. McGregor ◽  
Paul L. Gribble
Keyword(s):  
Functional Connectivity ◽  
Motor Learning ◽  
Resting State ◽  
Action Observation ◽  
Resting State Fmri ◽  
Learning Task ◽  
Brain Regions ◽  
Neural Systems ◽  
Resting State Functional Connectivity ◽  
Somatosensory Cortices

Motor learning occurs not only through direct first-hand experience but also through observation (Mattar AA, Gribble PL. Neuron 46: 153–160, 2005). When observing the actions of others, we activate many of the same brain regions involved in performing those actions ourselves (Malfait N, Valyear KF, Culham JC, Anton JL, Brown LE, Gribble PL. J Cogn Neurosci 22: 1493–1503, 2010). Links between neural systems for vision and action have been reported in neurophysiological (Strafella AP, Paus T. Neuroreport 11: 2289–2292, 2000; Watkins KE, Strafella AP, Paus T. Neuropsychologia 41: 989–994, 2003), brain imaging (Buccino G, Binkofski F, Fink GR, Fadiga L, Fogassi L, Gallese V, Seitz RJ, Zilles K, Rizzolatti G, Freund HJ. Eur J Neurosci 13: 400–404, 2001; Iacoboni M, Woods RP, Brass M, Bekkering H, Mazziotta JC, Rizzolatti G. Science 286: 2526–2528, 1999), and eye tracking (Flanagan JR, Johansson RS. Nature 424: 769–771, 2003) studies. Here we used a force field learning paradigm coupled with resting-state fMRI to investigate the brain areas involved in motor learning by observing. We examined changes in resting-state functional connectivity (FC) after an observational learning task and found a network consisting of V5/MT, cerebellum, and primary motor and somatosensory cortices in which changes in FC were correlated with the amount of motor learning achieved through observation, as assessed behaviorally after resting-state fMRI scans. The observed FC changes in this network are not due to visual attention to motion or observation of movement errors but rather are specifically linked to motor learning. These results support the idea that brain networks linking action observation and motor control also facilitate motor learning.

scholarly journals High-throughput preprocessing pipeline for resting-state fMRI

2018 ◽  
Author(s):  
Evangeline Yee
Keyword(s):  
Functional Connectivity ◽  
High Throughput ◽  
Resting State ◽  
Cluster Computing ◽  
Medical Image Analysis ◽  
Building Blocks ◽  
Resting State Fmri ◽  
Brain Regions ◽  
Posterior Cingulate Cortex ◽  
Resting State Functional Connectivity

Resting-state functional magnetic resonance imaging (fMRI) examines functional connectivity between brain regions by measuring spontaneous fluctuation of blood-oxygen-level dependent (BOLD) signal while subjects are at rest. Recent studies have revealed that neurodegenerative diseases are associated with abnormalities in resting-state functional connectivity. This thesis work aimed to develop a high-throughput preprocessing pipeline for minimizing spatial and temporal artifacts in resting-state fMRI data. The building blocks and cluster computing capabilities of the pipeline are discussed in detail. In an effort to validate this pipeline, a seed-based analysis was performed on preprocessed data using 3 seeds placed in the posterior cingulate cortex (PCC), supplementary motor area (SMA) and inferior parietal sulcus (IPS). These 3 seeds represent the core components of the default mode network (DMN) and task-positive network (TPN), two of the most commonly examined resting-state networks. Consistent with literature, results indicate that activity in the PCC is functionally correlated to regions of the DMN and anti-correlated to regions of the TPN, whereas activities in the SMA and IPS are functionally correlated to regions of the TPN and anti-correlated to regions of the DMN. These functional connectivity patterns were consistent across scans on both group-level and subject-level. This preprocessing pipeline will support researchers and clinical collaborators of Medical Image Analysis Lab (MIAL) in their analysis of resting-state functional connectivity.

scholarly journals Resting-State Functional Connectivity Signatures of Apathy in Community-Living Older Adults

2021 ◽  
Vol 13 ◽  
Author(s):  
Jung Yun Jang ◽  
S. Duke Han ◽  
Belinda Yew ◽  
Anna E. Blanken ◽  
Shubir Dutt ◽  
...  
Keyword(s):  
Older Adults ◽  
Functional Connectivity ◽  
Orbitofrontal Cortex ◽  
Resting State ◽  
Neural Mechanism ◽  
Resting State Fmri ◽  
Brain Regions ◽  
Anterior Cingulate ◽  
Resting State Functional Connectivity ◽  
The Right

Apathy predicts poor outcomes in older adults, and its underlying neural mechanism needs further investigation. We examined the association between symptoms of apathy and functional connectivity (FC) in older adults without stroke or dementia. Participants included 48 individuals (mean age = 70.90) living independently in the community, who underwent resting-state fMRI and completed the Apathy Evaluation Scale (AES). Seed-to-voxel analysis (cluster-level p-FDR <0.05, voxel threshold p < 0.001) tested the association between AES scores and the whole-brain FC of brain regions involved in reward- and salience-related processing. We found that AES scores were negatively associated with FC of the right insula cortex and right anterior temporal regions (124 voxels, t = −5.10) and FC of the left orbitofrontal cortex and anterior cingulate regions (160 voxels, t = −5.45), and were positively associated with FC of the left orbitofrontal cortex and left lateral prefrontal (282 voxels, t = 4.99) and anterior prefrontal (123 voxels, t = 4.52) regions. These findings suggest that apathy in older adults may reflect disruptions in neural connectivity involved in reward- and salience-related processing.

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