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Ozlem Korucuoglu

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3 papers

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YNIMG Journal 2022 Journal Article

Reliability and stability challenges in ABCD task fMRI data

James T. Kennedy
Michael P. Harms
Ozlem Korucuoglu
Serguei V. Astafiev
Deanna M. Barch
Wesley K. Thompson
James M. Bjork
Andrey P. Anokhin

Trait stability of measures is an essential requirement for individual differences research. Functional MRI has been increasingly used in studies that rely on the assumption of trait stability, such as attempts to relate task related brain activation to individual differences in behavior and psychopathology. However, recent research using adult samples has questioned the trait stability of task-fMRI measures, as assessed by test-retest correlations. To date, little is known about trait stability of task fMRI in children. Here, we examined within-session reliability and long-term stability of individual differences in task-fMRI measures using fMRI measures of brain activation provided by the adolescent brain cognitive development (ABCD) Study Release v4.0 as an individual's average regional activity, using its tasks focused on reward processing, response inhibition, and working memory. We also evaluated the effects of factors potentially affecting reliability and stability. Reliability and stability (quantified as the ratio of non-scanner related stable variance to all variances) was poor in virtually all brain regions, with an average value of 0.088 and 0.072 for short term (within-session) reliability and long-term (between-session) stability, respectively, in regions of interest (ROIs) historically-recruited by the tasks. Only one reliability or stability value in ROIs exceeded the 'poor' cut-off of 0.4, and in fact rarely exceeded 0.2 (only 4.9%). Motion had a pronounced effect on estimated reliability/stability, with the lowest motion quartile of participants having a mean reliability/stability 2.5 times higher (albeit still 'poor') than the highest motion quartile. Poor reliability and stability of task-fMRI, particularly in children, diminishes potential utility of fMRI data due to a drastic reduction of effect sizes and, consequently, statistical power for the detection of brain-behavior associations. This essential issue urgently needs to be addressed through optimization of task design, scanning parameters, data acquisition protocols, preprocessing pipelines, and data denoising methods.

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YNIMG Journal 2020 Journal Article

Test-retest reliability of fMRI-measured brain activity during decision making under risk

Ozlem Korucuoglu
Michael P. Harms
Serguei V. Astafiev
James T. Kennedy
Semyon Golosheykin
Deanna M. Barch
Andrey P. Anokhin

Neural correlates of decision making under risk are being increasingly utilized as biomarkers of risk for substance abuse and other psychiatric disorders, treatment outcomes, and brain development. This research relies on the basic assumption that fMRI measures of decision making represent stable, trait-like individual differences. However, reliability needs to be established for each individual construct. Here we assessed long-term test-retest reliability (TRR) of regional brain activations related to decision making under risk using the Balloon Analogue Risk Taking task (BART) and identified regions with good TRRs and familial influences, an important prerequisite for the use of fMRI measures in genetic studies. A secondary goal was to examine the factors potentially affecting fMRI TRRs in one particular risk task, including the magnitude of neural activation, data analytical approaches, different methods of defining boundaries of a region, and participant motion. For the average BOLD response, reliabilities ranged across brain regions from poor to good (ICCs of 0 to 0. 8, with a mean ICC of 0. 17) and highest reliabilities were observed for parietal, occipital, and temporal regions. Among the regions that were of a priori theoretical importance due to their reported associations with decision making, the activation of left anterior insula and right caudate during the decision period showed the highest reliabilities (ICCs of 0. 54 and 0. 63, respectively). Among the regions with highest reliabilities, the right fusiform, right rostral anterior cingulate and left superior parietal regions also showed high familiality as indicated by intrapair monozygotic twin correlations (ranging from 0. 66 to 0. 69). Overall, regions identified by modeling the average BOLD response to a specific event type (rather than its modulation by a parametric regressor), regions including significantly activated vertices (compared to a whole parcel), and regions with greater magnitude of task-related activations showed greater reliabilities. Participant motion had a moderate negative effect on TRR. Regions activated during decision period rather than outcome period of risky decisions showed the greatest TRR and familiality. Regions with reliable activations can be utilized as neural markers of individual differences or endophenotypes in future clinical neuroscience and genetic studies of risk-taking.

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YNIMG Journal 2019 Journal Article

Shared genetic influences on adolescent body mass index and brain structure: A voxel-based morphometry study in twins

James T. Kennedy
Serguei V. Astafiev
Semyon Golosheykin
Ozlem Korucuoglu
Andrey P. Anokhin

Background Previous research has demonstrated significant relationships between obesity and brain structure. Both phenotypes are heritable, but it is not known whether they are influenced by common genetic factors. We investigated the genetic etiology of the relationship between individual variability in brain morphology and BMIz using structural MRI in adolescent twins. Method The sample (n = 258) consisted of 54 monozygotic and 75 dizygotic twin pairs (mean(SD) age = 13. 61(0. 505), BMIz = 0. 608(1. 013). Brain structure (volume and density of gray and white matter) was assessed using VBM. Significant voxelwise heritability of brain structure was established using the Accelerated Permutation inference for ACE models (APACE) program, with structural heritability varying from 15 to 97%, depending on region. Bivariate heritability analyses were carried out comparing additive genetic and unique environment models with and without shared genetics on BMIz and the voxels showing significant heritability in the APACE analyses. Results BMIz was positively related to gray matter volume in the brainstem and thalamus and negatively related to gray matter volume in the bilateral uncus and medial orbitofrontal cortex, gray matter density in the cerebellum, prefrontal lobe, temporal lobe, and limbic system, and white matter density in the brainstem. Bivariate heritability analyses showed that BMIz and brain structure share ∼1/3 of their genes and that ∼95% of the phenotypic correlation between BMIz and brain structure is due to shared additive genetic influences. These regions included areas related to decision-making, motivation, liking vs. wanting, taste, interoception, reward processing/learning, caloric evaluation, and inhibition. Conclusion These results suggested genetic factors are responsible for the relationship between BMIz and heritable BMIz related brain structure in areas related to eating behavior.

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