Interacting Brain Networks Underlying Creative Cognition and Artistic Performance

2018 ◽  
Author(s):  
Roger E. Beaty ◽  
Rex E. Jung
Keyword(s):  
Brain Networks ◽  
Region Of Interest ◽  
Network Connectivity ◽  
Brain Regions ◽  
Brain Network ◽  
Potential Interaction ◽  
Significant Advance ◽  
Dynamic Interactions ◽  
Creative Cognition ◽  
Brain Network Connectivity

Cognitive neuroscience research has begun to address the potential interaction of brain networks supporting creativity by employing new methods in brain network science. Network methods offer a significant advance compared to individual region of interest studies due to their ability to account for the complex and dynamic interactions among discrete brain regions. As this chapter demonstrates, several recent studies have reported a remarkably similar pattern of brain network connectivity across a range of creative tasks and domains. In general, such work suggests that creative thought may involve dynamic interactions, primarily between the default and control networks, providing key insights into the roles of spontaneous and controlled processes in creative cognition. The chapter summarizes this emerging body of research and proposes a framework designed to account for the joint influence of controlled and spontaneous thought processes in creativity.

Graph Theory-Based Brain Network Connectivity Analysis and Classification of Alzheimer’s Disease

2021 ◽  
Author(s):  
A. Thushara ◽  
C. Ushadevi Amma ◽  
Ansamma John
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Graph Theory ◽  
Neurodegenerative Disorder ◽  
Brain Networks ◽  
Network Connectivity ◽  
Brain Regions ◽  
Brain Network ◽  
Fiber Tracts ◽  
The Brain

Alzheimer’s Disease (AD) is basically a progressive neurodegenerative disorder associated with abnormal brain networks that affect millions of elderly people and degrades their quality of life. The abnormalities in brain networks are due to the disruption of White Matter (WM) fiber tracts that connect the brain regions. Diffusion-Weighted Imaging (DWI) captures the brain’s WM integrity. Here, the correlation betwixt the WM degeneration and also AD is investigated by utilizing graph theory as well as Machine Learning (ML) algorithms. By using the DW image obtained from Alzheimer’s Disease Neuroimaging Initiative (ADNI) database, the brain graph of each subject is constructed. The features extracted from the brain graph form the basis to differentiate between Mild Cognitive Impairment (MCI), Control Normal (CN) and AD subjects. Performance evaluation is done using binary and multiclass classification algorithms and obtained an accuracy that outperforms the current top-notch DWI-based studies.

scholarly journals F37. CACNA1C HYPOFUNCTION IN KETAMINE-ACTIVATED BRAIN NETWORKS IMPAIRS MEMORY CONSOLIDATION AND FUNCTIONAL BRAIN NETWORK CONNECTIVITY

2018 ◽  
Vol 44 (suppl_1) ◽  
pp. S233-S233
Author(s):  
Rebecca Hughes ◽  
Cosima Willi ◽  
Jayde Whittingham-Dowd ◽  
Susan Broughton ◽  
Greg Bristow ◽  
...  
Keyword(s):  
Memory Consolidation ◽  
Brain Networks ◽  
Network Connectivity ◽  
Brain Network ◽  
Functional Brain ◽  
Functional Brain Network ◽  
Brain Network Connectivity

Sex Differences in the Associations Between Symptom Severity, Social Cognition, and Social Brain Network Connectivity in Alcohol Use Disorder

2020 ◽  
Author(s):  
Abigail Waters ◽  
Sergey Chernyak ◽  
Amy Janes ◽  
William Killgore ◽  
Shelly Greenfield ◽  
...  
Keyword(s):  
Sex Differences ◽  
Social Cognition ◽  
Alcohol Use ◽  
Symptom Severity ◽  
Alcohol Use Disorder ◽  
Brain Networks ◽  
Network Connectivity ◽  
Brain Network ◽  
Men And Women ◽  
Brain Network Connectivity

Background and Aims: Large-scale neurocognitive brain networks are necessary to coordinate social cognition. Regions of prefrontal cortex that are key nodes in these networks are highly vulnerable to alcohol neurotoxicity, which may link poor social function and alcohol use disorder (AUD). However, there is very little research on how brain networks associated with social cognition are affected by AUD, and no studies of how these effects may differ between men and women. The current study aims to address this gap by examining the interaction between sex and AUD on the connectivity between brain networks implicated in social cognition.Methods: Matched groups of men and women with and without AUD (N=156; N=39/group) were selected from the Human Connectome Project. Resting-state functional magnetic resonance imaging data were used to compute functional connectivity between prefrontal networks, including default mode sub-networks (anterior dorsomedial: aDMN, ventromedial: vmDMN, temporal lobe: tDMN, and posterior DMN: pDMN), and central executive, dorsal attention, ventral attention, salience, and striatal networks. Between-network connectivity was assessed for interactions between sex, AUD diagnosis and symptom severity, and a measure of composite social cognition using non-parametric permutation testing, corrected for number of network pairs tested (Benjamini-Hochberg procedure, p<0.05 corrected). Results: Connectivity between aDMN–tDMN (AUDcontrols, pcor=.030) differed between groups. An interaction between sex and AUD symptom severity was significantly associated with aDMN–VAN (pcor= .032) connectivity. Social cognition scores were associated with aDMN–vmDMN connectivity (pcor=.003), with the relationship being moderated by sex, AUD-status, and symptom severity. Conclusions: This study addresses a critical gap in the literature on how brain network connectivity that underpins social cognition may be impaired in men and women with AUD. Our findings show that vulnerabilities emerge in men and women even at mild symptom severity and that there are significant sex differences, suggesting sex-specific treatment considerations are warranted.

scholarly journals EFFECTS OF FUNCTIONAL BRAIN NETWORKS AND WHITE MATTER DISEASE ON MOBILITY OF OLDER ADULTS IN AN EXERCISE INTERVENTION

2019 ◽  
Vol 3 (Supplement_1) ◽  
pp. S851-S852
Author(s):  
Blake R Neyland ◽  
Robert Kraft ◽  
Mary Lyles ◽  
Stephen Kritchevsky ◽  
Paul J Laurienti ◽  
...  
Keyword(s):  
Older Adults ◽  
White Matter ◽  
Exercise Intervention ◽  
Brain Networks ◽  
Network Connectivity ◽  
Brain Network ◽  
White Matter Disease ◽  
Before And After ◽  
Functional Brain Networks ◽  
Brain Network Connectivity

Abstract Declining mobility is associated with increased accumulation of white matter hyperintensities (WMH). However, a high WMH burden is not always accompanied by impaired mobility. Our previous work demonstrates that some variance in mobility may be explained by brain network connectivity. Here, we extended this work by measuring WMHs and brain networks in older adults participating in a lifestyle intervention. The Short Physical Performance Battery (SPPB) and resting state functional magnetic resonance imaging (fMRI) were collected before and after a 5-month caloric restriction plus aerobic exercise intervention in 57 obese, sedentary adults aged 65-78. Participants were categorized based on median splits of baseline SPPB scores and WMH burden: Expected Healthy (EH: low WMH, SPPB≥11, n=16), Expected Impaired (EI: high WMH, SPPB≤10, n=17), Unexpected Healthy (UH: high WMH, SPPB≥11, n=12), and Unexpected Impaired (UI: low WMH, SPPB≤10, n=12). Graph theory-based methods were used to characterize brain networks and compare the four groups. At baseline, the somatomotor cortex community structure (SMC-CS) was less consistent in EI (p=0.05) and UI (p=0.23) compared to EH. The EI (mean=1.25, p=0.003) and UI (mean=1.57, p=0.001) significantly improved their SPPB scores following the intervention. Although both groups had equivalent SPPB scores, SMC-CS was less consistent in the UH than EH (p=0.16). However, UH displayed a significant (p=0.004) increase in second-order connections to the precuneus compared to EH. These data suggest that studying brain networks could improve the understanding of the development of mobility disability and the CNS contributions to mobility independent of white matter disease.

scholarly journals Different effects of the DRD4 genotype on intrinsic brain network connectivity strength in drug-naïve children with ADHD and healthy controls

2021 ◽  
Author(s):  
Shuangli Chen ◽  
Andan Qian ◽  
Jiejie Tao ◽  
Ronghui Zhou ◽  
Chuqi Fu ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Network Connectivity ◽  
Brain Regions ◽  
Brain Network ◽  
Healthy Children ◽  
Healthy Controls ◽  
Children With Adhd ◽  
Functional Relationships ◽  
Brain Network Connectivity ◽  
Drug Naïve

AbstractThe dopamine D4 receptor gene (DRD4) has been consistently reported to be associated with attention-deficit/hyperactivity disorder (ADHD). Recent studies have linked DRD4 to functional connectivity among specific brain regions. The current study aimed to compare the effects of the DRD4 genotype on functional integrity in drug-naïve ADHD children and healthy children. Resting-state functional MRI images were acquired from 49 children with ADHD and 37 healthy controls (HCs). We investigated the effects of the 2-repeat allele of DRD4 on brain network connectivity in both groups using a parameter called the degree of centrality (DC), which indexes local functional relationships across the entire brain connectome. A voxel-wise two-way ANCOVA was performed to examine the diagnosis-by-genotype interactions on DC maps. Significant diagnosis-by-genotype interactions with DC were found in the temporal lobe, including the left inferior temporal gyrus (ITG) and bilateral middle temporal gyrus (MTG) (GRF corrected at voxel level p < 0.001 and cluster level p < 0.05, two-tailed). With the further subdivision of the DC network according to anatomical distance, additional brain regions with significant interactions were found in the long-range DC network, including the left superior parietal gyrus (SPG) and right middle frontal gyrus (MFG). The post-hoc pairwise analysis found that altered network centrality related to DRD4 differed according to diagnostic status (p < 0.05). This genetic imaging study suggests that the DRD4 genotype regulates the functional integration of brain networks in children with ADHD and HCs differently. This may have important implications for our understanding of the role of DRD4 in altering functional connectivity in ADHD subjects.

scholarly journals Brain network connectivity underlying decisions between the "lesser of two evils"

2018 ◽  
Author(s):  
Colleen Mills-Finnerty ◽  
Catherine Hanson ◽  
Stephen J Hanson
Keyword(s):  
Prefrontal Cortex ◽  
Brain Activity ◽  
Network Connectivity ◽  
Brain Regions ◽  
Brain Network ◽  
Anterior Cingulate ◽  
Approach And Avoidance ◽  
Car Accidents ◽  
Brain Network Connectivity ◽  
Choice Framing

In daily life we are often forced to choose between the “lesser of two evils,” yet there remains limited understanding of how the brain encodes choices between aversive stimuli, particularly choices involving hypothetical futures. We tested how choice framing affects brain activity and network connectivity by having participants make choices about individualized, aversive, hypothetical stimuli (i.e. illnesses, car accidents, etc.) under approach and avoidance frames (“which would you rather have/avoid”) during fMRI scanning. We tested whether limbic and frontal regions show patterns of signal intensity and network connectivity that differed by frame, and compared this to response to similar appetitive choices involving appetitive preferences (i.e. hobbies, vacation destinations). We predicted that regions such as the insula, amgydala, and striatum would respond differently to approach vs. avoidance choices during aversive hypothetical choices. We identified activations for both choice frames in areas broadly associated with decision making, including the putamen, insula, and anterior cingulate, as well as deactivations in areas shown to be sensitive to valence, including the amygdala, insula, prefrontal cortex, and hippocampus. Connectivity between brain regions differed based on choice frame, with greater connectivity among deactive regions including the amygdala, insula, and ventromedial prefrontal cortex during avoidance frames compared to approach frames. These differences suggest that approach and avoidance frames lead to different behavioral and brain network response when deciding which of two evils are the lesser.

scholarly journals Brain network connectivity underlying decisions between the "lesser of two evils"

2018 ◽  
Author(s):  
Colleen Mills-Finnerty ◽  
Catherine Hanson ◽  
Stephen J Hanson
Keyword(s):  
Prefrontal Cortex ◽  
Brain Activity ◽  
Network Connectivity ◽  
Brain Regions ◽  
Brain Network ◽  
Anterior Cingulate ◽  
Approach And Avoidance ◽  
Car Accidents ◽  
Brain Network Connectivity ◽  
Choice Framing

In daily life we are often forced to choose between the “lesser of two evils,” yet there remains limited understanding of how the brain encodes choices between aversive stimuli, particularly choices involving hypothetical futures. We tested how choice framing affects brain activity and network connectivity by having participants make choices about individualized, aversive, hypothetical stimuli (i.e. illnesses, car accidents, etc.) under approach and avoidance frames (“which would you rather have/avoid”) during fMRI scanning. We tested whether limbic and frontal regions show patterns of signal intensity and network connectivity that differed by frame, and compared this to response to similar appetitive choices involving appetitive preferences (i.e. hobbies, vacation destinations). We predicted that regions such as the insula, amgydala, and striatum would respond differently to approach vs. avoidance choices during aversive hypothetical choices. We identified activations for both choice frames in areas broadly associated with decision making, including the putamen, insula, and anterior cingulate, as well as deactivations in areas shown to be sensitive to valence, including the amygdala, insula, prefrontal cortex, and hippocampus. Connectivity between brain regions differed based on choice frame, with greater connectivity among deactive regions including the amygdala, insula, and ventromedial prefrontal cortex during avoidance frames compared to approach frames. These differences suggest that approach and avoidance frames lead to different behavioral and brain network response when deciding which of two evils are the lesser.

scholarly journals Brain network connectivity underlying decisions between the "lesser of two evils"

2017 ◽  
Author(s):  
Colleen Mills-Finnerty ◽  
Catherine Hanson ◽  
Stephen J Hanson
Keyword(s):  
Prefrontal Cortex ◽  
Brain Activity ◽  
Network Connectivity ◽  
Brain Regions ◽  
Brain Network ◽  
Anterior Cingulate ◽  
Approach And Avoidance ◽  
Car Accidents ◽  
Brain Network Connectivity ◽  
Choice Framing

In daily life we are often forced to choose between the “lesser of two evils,” yet there remains limited understanding of how the brain encodes choices between aversive stimuli, particularly choices involving hypothetical futures. We tested how choice framing affects brain activity and network connectivity by having participants make choices about individualized, aversive, hypothetical stimuli (i.e. illnesses, car accidents, etc.) under approach and avoidance frames (“which would you rather have/avoid”) during fMRI scanning. We tested whether limbic and frontal regions show patterns of signal intensity and network connectivity that differed by frame, and compared this to response to similar appetitive choices involving appetitive preferences (i.e. hobbies, vacation destinations). We predicted that regions such as the insula, amgydala, and striatum would respond differently to approach vs. avoidance choices during aversive hypothetical choices. We identified activations for both choice frames in areas broadly associated with decision making, including the putamen, insula, and anterior cingulate, as well as deactivations in areas shown to be sensitive to valence, including the amygdala, insula, prefrontal cortex, and hippocampus. Connectivity between brain regions differed based on choice frame, with greater connectivity among deactive regions including the amygdala, insula, and ventromedial prefrontal cortex during avoidance frames compared to approach frames. These differences suggest that approach and avoidance frames lead to different behavioral and brain network response when deciding which of two evils are the lesser.

scholarly journals Miswiring the brain: Human prenatal Δ9-tetrahydrocannabinol use associated with altered fetal hippocampal brain network connectivity

2021 ◽  
pp. 101000
Author(s):  
Moriah E. Thomason ◽  
Ava C. Palopoli ◽  
Nicki N. Jariwala ◽  
Denise M. Werchan ◽  
Alan Chen ◽  
...  
Keyword(s):  
Network Connectivity ◽  
Brain Network ◽  
Brain Network Connectivity ◽  
The Brain

scholarly journals Reconfiguration of human evolving large-scale epileptic brain networks prior to seizures: an evaluation with node centralities

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Rieke Fruengel ◽  
Timo Bröhl ◽  
Thorsten Rings ◽  
Klaus Lehnertz
Keyword(s):  
Large Scale ◽  
Brain Networks ◽  
Brain Regions ◽  
Brain Network ◽  
Theoretical Concept ◽  
Global Network ◽  
Time Resolved ◽  
Functional Connections ◽  
Node Centrality ◽  
Network Mechanism

AbstractPrevious research has indicated that temporal changes of centrality of specific nodes in human evolving large-scale epileptic brain networks carry information predictive of impending seizures. Centrality is a fundamental network-theoretical concept that allows one to assess the role a node plays in a network. This concept allows for various interpretations, which is reflected in a number of centrality indices. Here we aim to achieve a more general understanding of local and global network reconfigurations during the pre-seizure period as indicated by changes of different node centrality indices. To this end, we investigate—in a time-resolved manner—evolving large-scale epileptic brain networks that we derived from multi-day, multi-electrode intracranial electroencephalograpic recordings from a large but inhomogeneous group of subjects with pharmacoresistant epilepsies with different anatomical origins. We estimate multiple centrality indices to assess the various roles the nodes play while the networks transit from the seizure-free to the pre-seizure period. Our findings allow us to formulate several major scenarios for the reconfiguration of an evolving epileptic brain network prior to seizures, which indicate that there is likely not a single network mechanism underlying seizure generation. Rather, local and global aspects of the pre-seizure network reconfiguration affect virtually all network constituents, from the various brain regions to the functional connections between them.

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