Biology subjects

Taylor, C. M.

Publications and source records attributed to Taylor, C. M..

8 recordsLinked to original sources

bioRxiv2024

Idiosyncrasy and generalizability of contraceptive- and hormone-related functional connectomes across the menstrual cycle

Neuroendocrinology has received little attention in human neuroscience research, resulting in a dearth of knowledge surrounding potent and dynamic modulators of cognition and behavior, as well as brain structure and function. This work addresses one such phenomenon by studying functional connectomics related to ovarian hormone fluctuations throughout the adult menstrual cycle. To do so, we used functional magnetic resonance imaging (fMRI) and hormone assessments from two dense, longitudinal datasets to assess variations in functional connectivity with respect to endogenous and exogenous endocrine factors throughout the menstrual cycle. First, we replicated prior findings that common, group-level and individual specific factors have similar relative contributions to functional brain network organization. Second, we found widespread connectivity related to hormonal contraceptive (HC) use, in addition to sparser estradiol- and progesterone-related connectivity, and differential generalizability of these subnetworks that suggests progestin-specific impacts on functional connectivity in HC users. These results provide novel insight into within-individual changes in brain organization across the menstrual cycle and the extent to which these changes are shared between individuals, illuminating understudied phenomena in reproductive health and important information for all neuroimaging studies that include participants who menstruate. Author SummaryEndocrine modulation of brain function across the menstrual cycle is poorly understood. Human neuroimaging research on the menstrual cycle has long relied on group- and or coarse, within-individual cycle stage-differences, overlooking considerable individual differences in brain organization, the menstrual cycle, and hormone concentrations. Here, we take a multi-dataset approach to identify idiosyncratic contraceptive- and hormone-related functional connectivity from within-individual neuroendocrine dynamics and then test the generalizability of this connectivity to other individuals. In doing so, we identified idiosyncratic hormone-responsive subnetworks that are somewhat generalizable to other individuals, though this generalizability is complicated by hormonal contraceptive use, potentially reflecting differential connectivity between contraceptive formulations. Thus, this work illuminates individual similarities and differences in neuroendocrine dynamics across the menstrual cycle.

neuroscience↗

bioRxiv2024

Circadian rhythms tied to changes in brain morphology in a densely-sampled male

Circadian, infradian, and seasonal changes in steroid hormone secretion have been tied to changes in brain volume in several mammalian species. However, the relationship between circadian changes in steroid hormone production and rhythmic changes in brain morphology in humans is largely unknown. Here, we examined the relationship between diurnal fluctuations in steroid hormones and multiscale brain morphology in a precision imaging study of a male who completed forty MRI and serological assessments at 7 A.M. and 8 P.M. over the course of a month, targeting hormone concentrations at their peak and nadir. Diurnal fluctuations in steroid hormones were tied to pronounced changes in global and regional brain morphology. From morning to evening, total brain volume, gray matter volume, and cortical thickness decreased, coincident with decreases in steroid hormone concentrations (testosterone, estradiol, and cortisol). In parallel, cerebrospinal fluid and ventricle size increased from A.M. to P.M. Global changes were driven by decreases within the occipital and parietal cortices. These findings highlight natural rhythms in brain morphology that keep time with the diurnal ebb and flow of steroid hormones. Significance StatementThough rhythmic changes in steroid hormone secretion have been tied to changes in brain volume in several mammalian species, this relationship has not been well characterized in humans. In this precision neuroimaging study, we found that global and regional brain morphology and steroid hormone levels exhibit tandem circadian rhythms. These findings provide high-resolution insight into the anatomical signature of diurnal changes in brain morphology and steroid hormone production in a human male and reveal the metronomic regularity of these rhythms over time.

neuroscience↗

bioRxiv2024

Standard rodent diets differentially impact alcohol consumption and preference and gut microbiome diversity

Alcohol Use Disorder (AUD) is a complex and widespread disease with limited pharmacotherapies. Preclinical animal models of AUD use a variety of voluntary alcohol consumption procedures to recapitulate different phases of AUD including binge alcohol consumption and dependence. However, voluntary alcohol consumption in mice is widely variable rendering it difficult to reproduce results across labs. Accumulating evidence indicates that different brands of commercially available rodent chow can profoundly influence alcohol intake. In this study, we investigated the effects of three commercially available and widely used rodent diet formulations on alcohol consumption and preference in C57BL/6J mice using the 24h intermittent access procedure. The three brands of chow tested were LabDiet 5001 (LD 5001), LabDiet 5053 (LD 5053), and Teklad 2019S (TL2019S) from two companies (Research Diets and Envigo respectively). Mice fed LD5001 displayed the highest levels of alcohol consumption and preference followed by LD5053 and TL2019S. We also found that alcohol consumption and preference could be rapidly switched by changing the diet 48h prior to alcohol administration. Sucrose, saccharin, and quinine preference were not altered suggesting that the diets did not alter taste perception. We also found that mice fed LD5001 displayed increased quinine-resistant alcohol intake compared to mice fed TL2019S, suggesting that diets could influence the development of "compulsive" like alcohol consumption. We profiled the gut microbiome of water and alcohol drinking mice that were maintained on different diets and found significant differences in bacterial alpha and beta diversity, which could impact gut-brain axis signaling and alcohol consumption.

neuroscience↗

bioRxiv2023

Neuroanatomical changes observed over the course of a human pregnancy

Pregnancy is a period of profound hormonal and physiological change experienced by millions of women annually, yet the neural changes unfolding in the maternal brain throughout gestation have not been studied in humans. Leveraging precision imaging, we mapped neuroanatomical changes in an individual from preconception through two years postpartum. Pronounced decreases in gray matter volume and cortical thickness were evident across the brain, which stand in contrast to increases in white matter microstructural integrity, ventricle volume, and cerebrospinal fluid, with few regions untouched by the transition to motherhood. This dataset serves as the first comprehensive map of the human brain across gestation, providing an open-access resource for the brain imaging community to stimulate further exploration and discovery.

neuroscience↗

bioRxiv2020

Dynamic community detection reveals transient reorganization of functional brain networks across a female menstrual cycle

Sex steroid hormones have been shown to alter regional brain activity, but the extent to which they modulate connectivity within and between large-scale functional brain networks over time has yet to be characterized. Here, we applied dynamic community detection techniques to data from a highly sampled female with 30 consecutive days of brain imaging and venipuncture measurements to characterize changes in resting-state community structure across the menstrual cycle. Four stable functional communities were identified consisting of nodes from visual, default mode, frontal control, and somatomotor networks. Limbic, subcortical, and attention networks exhibited higher than expected levels of nodal flexibility, a hallmark of between-network integration and transient functional reorganization. The most striking reorganization occurred in a default mode subnetwork localized to regions of the prefrontal cortex, coincident with peaks in serum levels of estradiol, luteinizing hormone, and follicle stimulating hormone. Nodes from these regions exhibited strong intra-network increases in functional connectivity, leading to a split in the stable default mode core community and the transient formation of a new functional community. Probing the spatiotemporal basis of human brain-hormone interactions with dynamic community detection suggests that ovulation results in a temporary, localized patterns of brain network reorganization. Author SummarySex steroid hormones influence the central nervous system across multiple spatiotemporal scales. Estrogen and progesterone concentrations rise and fall throughout the menstrual cycle, but it remains poorly understood how day-to-day fluctuations in hormones shape human brain dynamics. Here, we assessed the structure and stability of resting-state brain network activity in concordance with serum hormone levels from a female who underwent fMRI and venipuncture for 30 consecutive days. Our results reveal that while network structure is largely stable over the menstrual cycle, there is temporary reorganization of several largescale functional brain networks during the ovulatory window. In particular, a default mode subnetwork exhibits increased connectivity with itself and with regions from temporoparietal and limbic networks, providing novel perspective into brain-hormone interactions.

neuroscience↗

bioRxiv2020

Progesterone shapes medial temporal lobe volume across the human menstrual cycle

The rhythmic production of sex steroid hormones is a central feature of the mammalian endocrine system. In rodents and nonhuman primates, sex hormones are powerful regulators of hippocampal subfield morphology. However, it remains unknown whether intrinsic fluctuations in sex hormones alter hippocampal morphology in the human brain. In a series of dense-sampling studies, we used high-resolution imaging of the medial temporal lobe (MTL) to determine whether endogenous fluctuations (Study 1) and exogenous manipulation (Study 2) of sex hormones alter MTL volume over time. Across the menstrual cycle, intrinsic fluctuations in progesterone were associated with volumetric changes in CA2/3, entorhinal, perirhinal, and parahippocampal cortex. Chronic progesterone suppression abolished these cycle-dependent effects and led to pronounced volumetric changes in entorhinal cortex and CA2/3 relative to freely cycling conditions. No associations with estradiol were observed. These results establish progesterones ability to rapidly and dynamically shape MTL morphology across the human menstrual cycle. HighlightsO_LISex hormones are powerful regulators of hippocampal plasticity in mammals. C_LIO_LIThe impact of hormone fluctuations on hippocampal morphology in humans is unknown. C_LIO_LIHigh resolution imaging of the MTL was conducted across two 30-day periods. C_LIO_LIProgesterone dynamically shapes MTL volume across the human menstrual cycle. C_LIO_LIChronic progesterone suppression abolishes cycle-dependent changes. C_LI

neuroscience↗

bioRxiv2019

Functional reorganization of brain networks across the human menstrual cycle

The brain is an endocrine organ, sensitive to the rhythmic changes in sex hormone production that occurs in most mammalian species. In rodents and nonhuman primates, estrogen and progesterones impact on the brain is evident across a range of spatiotemporal scales. Yet, the influence of sex hormones on the functional architecture of the human brain is largely unknown. In this dense-sampling, deep phenotyping study, we examine the extent to which endogenous fluctuations in sex hormones alter intrinsic brain networks at rest in a woman who underwent brain imaging and venipuncture for 30 consecutive days. Standardized regression analyses illustrate estrogen and progesterones widespread associations with functional connectivity. Time-lagged analyses examined the temporal directionality of these relationships and suggest that cortical network dynamics (particularly in the Default Mode and Dorsal Attention Networks, whose hubs are densely populated with estrogen receptors) are preceded--and perhaps driven--by hormonal fluctuations. A similar pattern of associations was observed in a follow-up study one year later. Together, these results reveal the rhythmic nature in which brain networks reorganize across the human menstrual cycle. Neuroimaging studies that densely sample the individual connectome have begun to transform our understanding of the brains functional organization. As these results indicate, taking endocrine factors into account is critical for fully understanding the intrinsic dynamics of the human brain. HighlightsO_LIIntrinsic fluctuations in sex hormones shape the brains functional architecture. C_LIO_LIEstradiol facilitates tighter coherence within whole-brain functional networks. C_LIO_LIProgesterone has the opposite, reductive effect. C_LIO_LIOvulation (via estradiol) modulates variation in topological network states. C_LIO_LIEffects are pronounced in network hubs densely populated with estrogen receptors. C_LI

neuroscience↗

bioRxiv2019

PICRUSt2: An improved and extensible approach for metagenome inference

One major limitation of microbial community marker gene sequencing is that it does not provide direct information on the functional composition of sampled communities. Here, we present PICRUSt2 (https://github.com/picrust/picrust2), which expands the capabilities of the original PICRUSt method1 to predict the functional potential of a community based on marker gene sequencing profiles. This updated method and implementation includes several improvements over the previous algorithm: an expanded database of gene families and reference genomes, a new approach now compatible with any OTU-picking or denoising algorithm, and novel phenotype predictions. Upon evaluation, PICRUSt2 was more accurate than PICRUSt1 and other current approaches overall. PICRUSt2 is also now more flexible and allows the addition of custom reference databases. We highlight these improvements and also important caveats regarding the use of predicted metagenomes, which are related to the inherent challenges of analyzing metagenome data in general.

bioinformatics↗