Intraindividual variability in functional cortical organization relates to hormone levels and stress
Poster No:
1711
Submission Type:
Abstract Submission
Authors:
Bianca Serio1, Deniz Yilmaz2, Laura Pritschet3, Hannah Grotzinger3, Emily Jacobs3, Simon Eickhoff4, Sofie Valk5
Institutions:
1Max Planck School of Cognition, Leipzig, Germany, 2Palo Alto High School, Palo Alto, USA, 3University of California Santa Barbara, Santa Barbara, USA, 4Institute for Systems Neuroscience, Medical Faculty, Heinrich-Heine University Düsseldorf, Düsseldorf, Germany, 5Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
First Author:
Co-Author(s):
Simon Eickhoff
Institute for Systems Neuroscience, Medical Faculty, Heinrich-Heine University Düsseldorf
Düsseldorf, Germany
Institute for Systems Neuroscience, Medical Faculty, Heinrich-Heine University Düsseldorf
Düsseldorf, Germany
Introduction:
Open science initiatives and study consortia allow the field of neuroscience to conduct population-level research, with large samples in the order of thousands of subjects aiming to yield more generalizable effects (Marek et al., 2022). However, generalizability implies focusing on inter-individual similarities to detect group-level effects, and large samples require the collection of unspecific data that answers general questions. We thus lack studies focusing on intra-individual variability through fine-grained data, designed to mechanistically probe neurocognitive processes such as the neuromodulatory role of hormones (Pritschet et al., 2021) or the physiological and neurocognitive influence of stress (Harrewijn et al., 2020). Here, we used densely sampled and deeply phenotyped data to investigate intra-individual variability in functional organization, exploring hormone levels and self-reported stress as potential underpinnings.
Methods:
One female (23 years) and one male (26 years) were respectively tested for 29 and 20 consecutive days in time-locked study sessions including brain imaging, venipuncture/salivary sampling and self-report questionnaires. We computed the sensory-association (S-A) axis as our measure of functional organization as it represents a key macroscale organizational principle. For this, we used diffusion map embedding to reduce the dimensionality of functional connectivity matrices (Margulies et al., 2016) at each timepoint for both subjects (Fig. 1A-B). We tested inter-individual differences in intra-individual variability along the S-A axis over time with Levene's test for equality of variances, quantifying variability as the standard deviation (STD) of parcel loadings on the S-A axis, and differences in variability by subtracting male from female STD. We used linear models to test local effects of hormone levels (serum estradiol and progesterone in the female, salivary testosterone and cortisol in the male), as well as self-reported stress, on the S-A axis. We used Spearman's rank correlation to test for associations between patterns in these local effects and patterns of inter-individual differences in variability. We also used linear models to test system-level effects of hormones and stress on measures of network topography, namely within- (WN) and between- (BN) network dispersion, quantifying the spread of functional networks along the S-A axis. False discovery rate correction was used on linear model local-level results, and Bonferroni correction was used on linear model system-level results (7 networks for WN dispersion, 21 pairwise network comparisons for BN dispersion), in addition to spin permutation testing (1000 permutations) to control for spatial autocorrelation.
Results:
Inter-individual differences in variability were found along the S-A axis, predominantly in association areas belonging to the default mode network (Fig. 1C-D). In fact, statistically significant greater local variability was found exclusively in the male subject. Except for testosterone (Fig. 1E), there were no local-level effects of hormones or stress on the S-A axis, and except for cortisol, there were no associations between patterns of local effects and patterns of inter-individual differences in variability. However, stress and the hormones assessed per subject all revealed some intra-individual system-level effects on WN dispersion (Fig. 1F-G). There were no effects on BN dispersion.
Conclusions:
Using a dense sampling approach, we showed daily variations in human functional organization in two healthy subjects. Interestingly, we found extensive intra-individual system-level effects of hormone levels and perceived stress on WN dispersion, whereas local-level effects on the S-A axis were only subtle. Further research in larger samples is required to generalize endocrine and cognitive diurnal effects on intra-individual variability and to probe sex differences as well as limits to reliability in such effects.
Emotion, Motivation and Social Neuroscience:
Social Cognition
Modeling and Analysis Methods:
fMRI Connectivity and Network Modeling 1
Task-Independent and Resting-State Analysis
Novel Imaging Acquisition Methods:
BOLD fMRI
Physiology, Metabolism and Neurotransmission :
Physiology, Metabolism and Neurotransmission Other 2
Keywords:
Cognition
Computational Neuroscience
Cortex
Data analysis
FUNCTIONAL MRI
Multivariate
Open Data
Other - Intra-Individual Variability; Hormones; Stress
1|2Indicates the priority used for review
·Figure 1
Provide references using author date format
Marek, S. (2022). Reproducible brain-wide association studies require thousands of individuals. Nature, 603(7902), 654-660.
Margulies, D. S. (2016). Situating the default-mode network along a principal gradient of macroscale cortical organization. Proceedings of the National Academy of Sciences, 113(44), 12574-12579.
Pritschet, L. (2021). Applying dense-sampling methods to reveal dynamic endocrine modulation of the nervous system. Current opinion in behavioral sciences, 40, 72-78.