scholarly journals Novel Age-Dependent Cortico-Subcortical Morphologic Interactions Predict Fluid Intelligence: A Multi-Cohort Geometric Deep Learning Study

2021 ◽  
Author(s):  
Yunan Wu ◽  
Pierre Besson ◽  
Emanuel Azcona ◽  
Sarah Bandt ◽  
Todd Parrish ◽  
...  
Keyword(s):  
Cognitive Function ◽  
Fluid Intelligence ◽  
State Of The Art ◽  
Brain Morphology ◽  
Subcortical Structures ◽  
Human Connectome Project ◽  
Strong Hypothesis ◽  
Age Dependent ◽  
Relationship Of ◽  
The Relationship

Abstract The relationship of human brain structure to cognitive function is complex, and how this relationship differs between childhood and adulthood is poorly understood. One strong hypothesis suggests the cognitive function of Fluid Intelligence (Gf) is dependent on prefrontal cortex and parietal cortex. In this work, we developed a novel graph convolutional neural networks (gCNNs) for the analysis of localized anatomic shape and prediction of Gf. Morphologic information of the cortical ribbons and subcortical structures was extracted from T1-weighted MRIs within two independent cohorts, the Adolescent Brain Cognitive Development Study (ABCD; age: 9.93 ± 0.62 years) of children and the Human Connectome Project (HCP; age: 28.81 ± 3.70 years). Prediction combining cortical and subcortical surfaces together yielded the highest accuracy of Gf for both ABCD (R = 0.314) and HCP datasets (R = 0.454), outperforming the state-of-the-art prediction of Gf from any other brain measures in the literature. Across both datasets, the morphology of the amygdala, hippocampus, and nucleus accumbens, along with temporal, parietal and cingulate cortex consistently drove the prediction of Gf, suggesting a significant reframing of the relationship between brain morphology and Gf to include systems involved with reward/aversion processing, judgment and decision-making, motivation, and emotion.

scholarly journals Novel age-dependent cortico-subcortical morphologic interactions predict fluid intelligence: A multi-cohort geometric deep learning study

2020 ◽  
Author(s):  
Yunan Wu ◽  
Pierre Besson ◽  
Emanuel A. Azcona ◽  
S. Kathleen Bandt ◽  
Todd B Parrish ◽  
...  
Keyword(s):  
Neural Networks ◽  
Cross Validation ◽  
Fluid Intelligence ◽  
Brain Morphology ◽  
Learning Study ◽  
Subcortical Structures ◽  
Brain Functions ◽  
Human Connectome Project ◽  
Age Dependent ◽  
Tightly Coupled

AbstractBrain structure is tightly coupled with brain functions, but it remains unclear how cognition is related to brain morphology, and what is consistent across neurodevelopment. In this work, we developed graph convolutional neural networks (gCNNs) to predict Fluid Intelligence (Gf) from shapes of cortical ribbons and subcortical structures. T1-weighted MRIs from two independent cohorts, the Human Connectome Project (HCP; age: 28.81±3.70) and the Adolescent Brain Cognitive Development Study (ABCD; age: 9.93±0.62) were independently analyzed. Cortical and subcortical surfaces were extracted and modeled as surface meshes. Three gCNNs were trained and evaluated using six-fold nested cross-validation. Overall, combining cortical and subcortical surfaces yielded the best predictions on both HCP (R=0.454) and ABCD datasets (R=0.314), and outperformed the current literature. Across both datasets, the morphometry of the amygdala and hippocampus, along with temporal, parietal and cingulate cortex consistently drove the prediction of Gf, suggesting a novel reframing of the morphometry underlying Gf.

scholarly journals The Relationship of Psychiatric Symptoms with Performance-Based and Self-Reported Cognitive Function After Ischemic Stroke

2021 ◽  
pp. 1-13
Author(s):  
Elisabeth Kliem ◽  
Elise Gjestad ◽  
Truls Ryum ◽  
Alexander Olsen ◽  
Bente Thommessen ◽  
...  
Keyword(s):  
Ischemic Stroke ◽  
Executive Function ◽  
Depressive Symptoms ◽  
Cognitive Function ◽  
Psychiatric Symptoms ◽  
Post Stroke ◽  
Cognitive Difficulties ◽  
Memory And Attention ◽  
Relationship Of ◽  
The Relationship

Abstract Objective: Findings on the relationship of psychiatric symptoms with performance-based and self-reported cognitive function post-stroke are inconclusive. We aimed to (1) study the relation of depression and anxiety to performance-based cognitive function and (2) explore a broader spectrum of psychiatric symptoms and their association with performance-based versus self-reported cognitive function. Method: Individuals with supratentorial ischemic stroke performed neuropsychological examination 3 months after stroke. For primary analyses, composite scores for memory and attention/executive function were calculated based on selected neuropsychological tests, and the Hospital Anxiety and Depression Scale (HADS) was used. Psychiatric symptoms and self-reported cognitive function for secondary aims were assessed using the Symptom-Checklist-90 – Revised (SCL-90-R). Results: In a sample of 86 patients [mean (M) age: 64.6 ± 9.2; Mini-Mental State Examination (MMSE), 3–7 days post-stroke: M = 28.4 ± 1.7; National Institutes of Health Stroke Scale (NIHSS) after 3 months: M = 0.7 ± 1.6] depressive symptoms (HADS) were associated with poorer memory performance after controlling for age, sex, and education (p ≤ .01). In a subsample (n = 41; Age: M = 65.7 ± 8.1; MMSE: M = 28.4 ± 1.8; NIHSS: M = 1.0 ± 1.9), symptoms of phobic anxiety (SCL-90-R) were associated with poorer performance-based memory and attention/executive function, and symptoms of anxiety (SCL-90-R) with lower attention/executive function. Higher levels of self-reported cognitive difficulties were associated with higher scores in all psychiatric domains (p ≤ .05). Conclusion: Even in relatively well-functioning stroke patients, depressive symptoms are associated with poorer memory. The results also suggest that various psychiatric symptoms are more related to self-reported rather than to performance-based cognitive function. Screening for self-reported cognitive difficulties may not only help to identify patients with cognitive impairment, but also those who need psychological treatment.

scholarly journals Blood-based bioenergetic profiling is related to differences in brain morphology in African Americans with Type 2 diabetes

2018 ◽  
Vol 132 (23) ◽  
pp. 2509-2518 ◽  
Author(s):  
Gargi Mahapatra ◽  
S. Carrie Smith ◽  
Timothy M. Hughes ◽  
Benjamin Wagner ◽  
Joseph A. Maldjian ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
White Matter ◽  
African Americans ◽  
Mitochondrial Function ◽  
Brain Morphology ◽  
Intracranial Volume ◽  
Peripheral Blood Mononuclear ◽  
Relationship Of ◽  
The Relationship

Blood-based bioenergetic profiling has promising applications as a minimally invasive biomarker of systemic bioenergetic capacity. In the present study, we examined peripheral blood mononuclear cell (PBMC) mitochondrial function and brain morphology in a cohort of African Americans with long-standing Type 2 diabetes. Key parameters of PBMC respiration were correlated with white matter, gray matter, and total intracranial volumes. Our analyses indicate that these relationships are primarily driven by the relationship of systemic bioenergetic capacity with total intracranial volume, suggesting that systemic differences in mitochondrial function may play a role in overall brain morphology.

scholarly journals Computationally replicating the Smith et al. (2015) positive-negative mode linking functional connectivity and subject measures

2020 ◽  
Author(s):  
Nikhil Goyal ◽  
Dustin Moraczewski ◽  
Peter Bandettini ◽  
Emily S. Finn ◽  
Adam Thomas
Keyword(s):  
Brain Activity ◽  
Strong Positive Correlation ◽  
Activity Data ◽  
Functional Brain ◽  
Human Connectome Project ◽  
Using Data ◽  
Functional Brain Activity ◽  
Relationship Of ◽  
The Relationship ◽  
Landmark Study

AbstractUnderstanding brain functionality and predicting human behavior based on functional brain activity is a major goal of neuroscience. Numerous studies have been conducted to investigate the relationship between functional brain activity and attention, subject characteristics, autism, psychiatric disorders, and more. By modeling brain activity data as networks, researchers can leverage the mathematical tools of graph and network theory to probe these relationships. In their landmark study, Smith et al. (2015) analyzed the relationship of young adult connectomes and subject measures, using data from the Human Connectome Project (HCP). Using canonical correlation analysis (CCA), Smith et al. found that there was a single prominent CCA mode which explained a statistically significant percentage of the observed variance in connectomes and subject measures. They also found a strong positive correlation of 0.87 between the primary CCA mode connectome and subject measure weights. In this study, we computationally replicate the findings of the original study in both the HCP 500 and HCP 1200 subject releases. The exact computational replication in the HCP 500 dataset was a success, validating our analysis pipeline for extension studies. The extended replication in the larger HCP 1200 dataset was partially successful and demonstrated a dominant primary mode.

Genetic mediation in the relationship of education to cognitive function in older people.

1995 ◽  
Vol 10 (1) ◽  
pp. 48-53 ◽  
Author(s):  
Dorit Carmelli ◽  
Gary E. Swan ◽  
Lon R. Cardon
Keyword(s):  
Cognitive Function ◽  
Older People ◽  
Relationship Of ◽  
The Relationship

Starting up a Business with Support of Subsidies for the Development of Entrepreneurship

2016 ◽  
Vol 41 (3) ◽  
pp. 59-74 ◽  
Author(s):  
Dorota Jegorow
Keyword(s):  
Cognitive Function ◽  
Public Support ◽  
Secondary Data ◽  
Descriptive Statistics ◽  
Data Sources ◽  
Secondary Data Sources ◽  
Relationship Of ◽  
The Relationship ◽  
Further Development

The aim of this article is to determine the relationship of subsidies for starting up a business with its further development. Presented synthesis combines the analysis of literature, secondary data sources, descriptive statistics and observation. Thus, the article is a part of the cognitive function of economics. The analysis shows that recent years were characterized by a clear quantitative growth of newly registered enterprises.  This was accompanied by large public support provided in the form of subsidies for starting up a business. However, in many cases, the objective of the business was to be granted subsidies rather than its development under the auspices of the financing institutions

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