The individual functional connectome is unique and stable over months to years

Horien, Corey; Shen, Xilin; Scheinost, Dustin; Constable, R. Todd

doi:10.1016/j.neuroimage.2019.02.002

Cited by 173 publications

(160 citation statements)

References 51 publications

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“…This is the first study to show that identification accuracy of one's resting state scanhow much it reflects a "functional fingerprint" -depends on the amount of time in between assessments. We provide supporting evidence that adolescents have similar levels of fingerprinting accuracy to adults (Horien et al, 2019;Miranda-Dominguez et al, 2018) and extend this literature to show that this pattern is consistent on a same-day visit and visits 1.5 years apart. Using multiple methods, we also found that a small number of edges, which are more likely to be in the Frontoparietal, Default, and Dorsal Attention networks, are consistently predictive of an individual's scan.…”

Section: Discussionsupporting

confidence: 80%

“…We did not observe differences in the fingerprinting accuracy between youth and adults, for both same day and 1.5-year comparisons. Indeed, others have found that identification accuracy is stable in both youth and adults (Horien et al, 2019). We extend these findings by showing accuracy is high both for same day and longer-term (1.5 years) intervals.…”

Section: Identification Accuracy Is Similar In Youths and Adultssupporting

confidence: 81%

“…Alternatively, "functional fingerprinting", i.e., identification accuracy of an individual's resting state scan could be robust to these changes. This is an open question, given the conflicted findings observed in the literature (Horien et al, 2019;Kaufmann et al, 2017).…”

Section: Introductionmentioning

confidence: 94%

“…Accumulating evidence from resting-state functional magnetic resonating imaging (rsfMRI) indicates that brain network architecture is highly individualized (Gordon et al, 2017;Gratton et al, 2018;Laumann et al, 2015aLaumann et al, , 2015b. Specifically, several studies have shown that individuals' patterns from one scan can identify another scan from that same individual at a high level of accuracy (Finn et al, 2015;Horien et al, 2019;Miranda-Dominguez et al, 2014).…”

Section: Introductionmentioning

confidence: 99%

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Functional connectome fingerprinting accuracy in youths and adults is similar when examined on the same day and 1.5 years apart

Jalbrzikowski

Lei

Foran

et al. 2019

Preprint

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Initial studies found that individual correlational patterns from resting-state functional magnetic resonance imaging studies can accurately identify another scan from that same individual. This method is known as "connectotyping" or functional connectome "fingerprinting".We leveraged a unique dataset of 12-30 years old (N=140) individuals who had two distinct resting state scans on the same session (Visit 1, V1), and again 12-18 months later (Visit 2, V2; henceforth 1.5 years) to assess the sensitivity and specificity of identification accuracy across different time scales (same day, 1.5 years apart) and developmental periods (youths, adults).We also used multiple statistical methods to identify the connections that enhance fingerprinting accuracy. We found that sensitivity and specificity to identify one's own scan was high (overall average AUC: 0.94), and identifiability was significantly higher in the same session (average AUC: 0.97) in comparison to the 1.5-year comparison (average AUC:0.91). The level of fingerprinting accuracy in youths (average AUC:0.93) was not significantly different from adults (average AUC:0.96). Select connections from the Frontoparietal, Default, and Dorsal Attention networks enhanced the ability to identify an individual. Finally, we found that identification of these features generalized across datasets and use of these features improve fingerprinting accuracy in an independent longitudinal data set (N=208). These results provide a framework for understanding that features of fingerprinting accuracy are stable from adolescence through adulthood. Importantly, these features contribute to one's uniqueness, suggesting that cognitive and default networks play a primary role in establishing one's connectome.

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Section: Discussionsupporting

confidence: 80%

Section: Identification Accuracy Is Similar In Youths and Adultssupporting

confidence: 81%

Section: Introductionmentioning

confidence: 94%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Functional connectome fingerprinting accuracy in youths and adults is similar when examined on the same day and 1.5 years apart

Jalbrzikowski

Lei

Foran

et al. 2019

Preprint

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“…Moreover, although absolute values of intra-individual edges show low reproducibility (Noble et al 2019), inter-individual differences in the functional connectome are stable across, days, months and even years (Horien et al 2019;Finn et al 2015;Miranda-Dominguez et al 2014), and its characteristics are uniquely associated with a particular individual across time (Horien et al 2019).…”

Section: Discussionmentioning

confidence: 99%

Resting-state network topology and planning ability in healthy adults

Vriend

Wagenmakers

Heuvel

et al. 2019

Preprint

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Functional magnetic resonance imaging (fMRI) studies have been used extensively to investigate the brain areas that are recruited during the Tower of London (ToL) task. Nevertheless, little research has been devoted to study the neural correlates of the ToL task using a network approach. Here we investigated the association between functional connectivity and network topology during restingstate fMRI and ToL task performance, that was performed outside the scanner. Sixty-two (62) healthy subjects (21-74 years) underwent eyes-closed rsfMRI and performed the task on a laptop. We studied global (whole-brain) and within subnetwork resting-state topology as well as functional connectivity between subnetworks, with a focus on the default-mode, fronto-parietal and dorsal and ventral attention networks. Efficiency and clustering coefficient were calculated to measure network integration and segregation, respectively, at both the global and subnetwork level. Our main finding was that higher global efficiency was associated with slower performance (β = .22, Pbca = .04) and this association seemed mainly driven by inter-individual differences in default-mode network connectivity. The reported results were independent from age, sex, education-level and motion.Although this finding is contrary to earlier findings on general cognition, we tentatively hypothesize that the reported association may indicate that individuals with a more integrated brain during the resting-state are less able to further increase network efficiency when transitioning from a rest to task state, leading to slower responses. This study also adds to a growing body of literature supporting a central role for the default-mode network in individual differences in cognitive performance.

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Functional Connectivity of the Nucleus Accumbens and Changes in Appetite in Patients With Depression

Kroemer

Teckentrup

et al. 2022

JAMA Psychiatry

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ImportanceMajor depressive disorder (MDD) is characterized by a substantial burden on health, including changes in appetite and body weight. Heterogeneity of depressive symptoms has hampered the identification of biomarkers that robustly generalize to most patients, thus calling for symptom-based mapping.ObjectiveTo define the functional architecture of the reward circuit subserving increases vs decreases in appetite and body weight in patients with MDD by specifying their contributions and influence on disease biomarkers using resting-state functional connectivity (FC).Design, Setting, and ParticipantsIn this case-control study, functional magnetic resonance imaging (fMRI) data were taken from the Marburg-Münster FOR 2107 Affective Disorder Cohort Study (MACS), collected between September 2014 and November 2016. Cross-sectional data of patients with MDD (n = 407) and healthy control participants (n = 400) were analyzed from March 2018 to June 2022.Main Outcomes and MeasuresChanges in appetite during the depressive episode and their association with FC were examined using fMRI. By taking the nucleus accumbens (NAcc) as seed of the reward circuit, associations with opposing changes in appetite were mapped, and a sparse symptom-specific elastic-net model was built with 10-fold cross-validation.ResultsAmong 407 patients with MDD, 249 (61.2%) were women, and the mean (SD) age was 36.79 (13.4) years. Reduced NAcc-based FC to the ventromedial prefrontal cortex (vmPFC) and the hippocampus was associated with reduced appetite (vmPFC: bootstrap r = 0.13; 95% CI, 0.02-0.23; hippocampus: bootstrap r = 0.15; 95% CI, 0.05-0.26). In contrast, reduced NAcc-based FC to the insular ingestive cortex was associated with increased appetite (bootstrap r = −0.14; 95% CI, −0.24 to −0.04). Critically, the cross-validated elastic-net model reflected changes in appetite based on NAcc FC and explained variance increased with increasing symptom severity (all patients: bootstrap r = 0.24; 95% CI, 0.16-0.31; patients with Beck Depression Inventory score of 28 or greater: bootstrap r = 0.42; 95% CI, 0.25-0.58). In contrast, NAcc FC did not classify diagnosis (MDD vs healthy control).Conclusions and RelevanceIn this study, NAcc-based FC reflected important individual differences in appetite and body weight in patients with depression that can be leveraged for personalized prediction. However, classification of diagnosis using NAcc-based FC did not exceed chance levels. Such symptom-specific associations emphasize the need to map biomarkers onto more confined facets of psychopathology to improve the classification and treatment of MDD.

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The individual functional connectome is unique and stable over months to years

Cited by 173 publications

References 51 publications

Functional connectome fingerprinting accuracy in youths and adults is similar when examined on the same day and 1.5 years apart

Functional connectome fingerprinting accuracy in youths and adults is similar when examined on the same day and 1.5 years apart

Resting-state network topology and planning ability in healthy adults

Functional Connectivity of the Nucleus Accumbens and Changes in Appetite in Patients With Depression

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