79. Transdiagnostic Prediction of Memory and Cognitive Abilities From Functional Connectivity Data: A Multidimensional Connectome-Based Predictive Modeling Study

2018 ◽  
Vol 83 (9) ◽  
pp. S33
Author(s):  
Dustin Scheinost ◽  
Siyuan Gao ◽  
Abigail Greene ◽  
R. Todd Constable
Keyword(s):  
Functional Connectivity ◽  
Predictive Modeling ◽  
Cognitive Abilities ◽  
Modeling Study

scholarly journals Infant functional connectivity fingerprints predict long-term language and pre-literacy outcomes

2020 ◽  
Author(s):  
Xi Yu ◽  
Silvina Ferradal ◽  
Danielle D. Sliva ◽  
Jade Dunstan ◽  
Clarisa Carruthers ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Cognitive Abilities ◽  
Functional Organization ◽  
Literacy Skills ◽  
Language And Literacy ◽  
Functional Connections ◽  
Literacy Outcomes ◽  
Functional Brain Networks ◽  
Longitudinal Imaging

AbstractFunctional brain networks undergo extensive development within the first few years of life. Previous studies have linked infant functional connectivity to cognitive abilities in toddlerhood. However, little is known regarding the long-term relevance of functional connections established in infancy for the protracted development of higher-order abilities of language and literacy. Employing a five-year longitudinal imaging project starting in infancy, this study utilizes resting-state functional MRI to demonstrate prospective associations between infant functional connectivity fingerprints and subsequent language and foundational literacy skills at a mean age of 6.5. These longitudinal associations are preserved when key environmental influences are controlled for and are independent of emergent language abilities in infancy, suggesting early development of functional network characteristics in supporting the acquisition of high-order language and pre-literacy skills. Altogether, the current results highlight the importance of functional organization established in infancy as a neural scaffold underlying the learning process of complex cognitive functions.

scholarly journals Lynn_etal_MathSkills_CPM_Preprint_V1_05July2021

2021 ◽  
Author(s):  
Andrew Lynn ◽  
Eric D. Wilkey ◽  
Gavin Price
Keyword(s):  
Functional Connectivity ◽  
Predictive Modeling ◽  
Brain Connectivity ◽  
Network Connectivity ◽  
Brain Regions ◽  
Math Skills ◽  
Whole Brain ◽  
Building Models ◽  
State Dependent ◽  
Brain Behavior

The human brain comprises multiple canonical networks, several of which are distributed across frontal, parietal, and temporooccipital regions. Studies report both positive and negative correlations between children’s math skills and the strength of functional connectivity among these regions during math-related tasks and at rest. Yet, it is unclear how the relation between children’s math skills and functional connectivity map onto patterns of distributed whole-brain connectivity, canonical network connectivity, and whether these relations are consistent across different task-states. We used connectome-based predictive modeling to test whether functional connectivity during number comparison and at rest predicts children’s math skills (N=31, Mage=9.21years) using distributed whole-brain connections versus connections among canonical networks. We found that weaker connectivity distributed across the whole brain and weaker connectivity between key math-related brain regions in specific canonical networks predicts better math skills in childhood. The specific connections predicting math skills, and whether they were distributed or mapped onto canonical networks, varied between tasks, suggesting that state-dependent rather than trait-level functional network architectures support children’s math skills. Furthermore, the current predictive modeling approach moves beyond brain-behavior correlations and toward building models of brain connectivity that may eventually aid in predicting future math skills.

scholarly journals Effects of Cognitive Training in Mild Cognitive Impairmentmeasured by Resting State Functional Imaging

2020 ◽  
Vol 10 (11) ◽  
pp. 175
Author(s):  
Seungho Kim ◽  
Eunhee Park ◽  
Hyunsil Cha ◽  
Jae-Chang Jung ◽  
Tae-Du Jung ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Training Program ◽  
Cognitive Training ◽  
Resting State ◽  
Cognitive Abilities ◽  
Motor Coordination ◽  
Network Connectivity ◽  
Functional Magnetic Resonance ◽  
Function Test ◽  
The Brain

Mild cognitive impairment (MCI) is defined as an intermediate state of cognitive alteration between normal aging and dementia. In this study, we performed a functional network connectivity analysis using resting-state functional magnetic resonance imaging to investigate the association between changes in functional connectivity in the brain and the improvement in cognitive abilities after cognitive training. A computerized cognitive training program was used to improve the abilities of fifteen participants with MCI. The cognitive training program (Comcog), which consists of three weekly sessions totaling 90 min, was conducted with all participants over six weeks. The cognitive abilities before (pre-Comcog) and after (post-Comcog) the cognitive training process were measured using a neurocognitive function test. After the Comcog, the participants enhanced their visual and verbal memories, attention, and visuo-motor coordination. The functional connectivity between cingulo-opercular (CON) and default mode (DMN) showed significant improvements after Comcog training. Therefore, our study suggests that cognitive training may improve the cognitive abilities of participants. This improvement was associated with an increase in the functional connectivity between DMN and CON. The increase in functional connectivity after cognitive training was specifically associated with overall cognitive functions, including executive, memory, decision-making, and motivational functions.

scholarly journals Connectome-based predictive modeling of attention: Comparing different functional connectivity features and prediction methods across datasets

NeuroImage ◽  
2018 ◽  
Vol 167 ◽  
pp. 11-22 ◽  
Author(s):  
Kwangsun Yoo ◽  
Monica D. Rosenberg ◽  
Wei-Ting Hsu ◽  
Sheng Zhang ◽  
Chiang-Shan R. Li ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Predictive Modeling ◽  
Prediction Methods

scholarly journals Functional connectivity differences in early infancy precede autism symptoms: a multivariate pattern analysis

2019 ◽  
Author(s):  
Abigail Dickinson ◽  
Manjari Daniel ◽  
Andrew Marin ◽  
Bilwaj Goanker ◽  
Mirella Dapretto ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Cognitive Abilities ◽  
Pattern Analysis ◽  
Brain Connectivity ◽  
Familial Risk ◽  
Autism Spectrum ◽  
Support Vector ◽  
Multivariate Pattern Analysis ◽  
Autism Symptoms ◽  
Multivariate Pattern

AbstractFunctional brain connectivity is altered in children and adults with autism spectrum disorder (ASD). Mapping pre-symptomatic functional disruptions in ASD could identify infants based on neural risk, providing a crucial opportunity to mediate outcomes before behavioral symptoms emerge.Here we quantify functional connectivity using scalable EEG measures of oscillatory phase coherence (6-12Hz). Infants at high and low familial risk for ASD (N=65) underwent an EEG recording at 3 months of age and were assessed for ASD symptoms at 18 months using the Autism Diagnostic Observation Schedule-Toddler Module. Multivariate pattern analysis was used to examine early functional patterns that are associated with later ASD symptoms.Support vector regression (SVR) algorithms accurately predicted observed ASD symptoms at 18 months from EEG data at 3 months (r=0.76, p=0.02). Specifically, lower frontal connectivity and higher right temporo-parietal connectivity predicted higher ASD symptoms. The SVR model did not predict non-verbal cognitive abilities at 18 months (r=0.15, p=0.36), suggesting specificity of these brain alterations to ASD.These data suggest that frontal and temporo-parietal dysconnectivity play important roles in the early pathophysiology of ASD. Early functional differences in ASD can be captured using EEG during infancy and may inform much-needed advancements in the early detection of ASD.

scholarly journals Explaining the heterogeneity of functional connectivity findings in multiple sclerosis: An empirically informed modeling study

2018 ◽  
Vol 39 (6) ◽  
pp. 2541-2548 ◽  
Author(s):  
Prejaas Tewarie ◽  
Martijn D. Steenwijk ◽  
Matthew J. Brookes ◽  
Bernard M. J. Uitdehaag ◽  
Jeroen J. G. Geurts ◽  
...  
Keyword(s):  
Multiple Sclerosis ◽  
Functional Connectivity ◽  
Modeling Study

scholarly journals Differential functional connectivity of insular subdivisions in de novo Parkinson’s Disease with mild cognitive impairment

2021 ◽  
Author(s):  
Chenxi Pan ◽  
Jingru Ren ◽  
Lanting Li ◽  
Yuqian Li ◽  
Jianxia Xu ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Cognitive Impairment ◽  
Executive Function ◽  
Mild Cognitive Impairment ◽  
Functional Connectivity ◽  
Cognitive Abilities ◽  
De Novo ◽  
Cognitive Disorders ◽  
The Right

Abstract The insula, consisting of functionally diverse subdivisions, plays a significant role in Parkinson’s disease (PD)-related cognitive disorders. However, the functional connectivity (FC) patterns of insular subdivisions in PD remain unclear. Our aim is to investigate the changes in FC patterns of insular subdivisions and their relationships with cognitive domains. Three groups of participants were recruited in this study, including PD patients with mild cognitive impairment (PD-MCI, n = 25), PD patients with normal cognition (PD-NC, n = 13), and healthy controls (HCs, n = 17). Resting-state functional magnetic resonance imaging (rs-fMRI) was used to investigate the FC in insular subdivisions of the three groups. Moreover, all participants underwent a neuropsychological battery to assess cognition so that the relationship between altered FC and cognitive performance could be elucidated. Compared with the PD-NC group, the PD-MCI group exhibited increased FC between the left dorsal anterior insular (dAI) and the right superior parietal gyrus (SPG), and altered FC was negatively correlated with memory and executive function. Compared with the HC group, the PD-MCI group showed significantly increased FC between the right dAI and the right median cingulate and paracingulate gyri (DCG), and altered FC was positively related to attention/working memory, visuospatial function, and language. Our findings highlighted the different abnormal FC patterns of insular subdivisions in PD patients with different cognitive abilities. Furthermore, dysfunction of the dAI may partly contribute to the decline in executive function and memory in early drug-naïve PD patients.

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