scholarly journals Individual variability in functional connectivity architecture of the mouse brain

2020 ◽  
Vol 3 (1) ◽  
Author(s):  
Eyal Bergmann ◽  
Xenia Gofman ◽  
Alexandra Kavushansky ◽  
Itamar Kahn
Keyword(s):  
Functional Connectivity ◽  
Individual Variation ◽  
Brain Research ◽  
Motor Behavior ◽  
Resting State Fmri ◽  
Individual Variability ◽  
Behavioral Variability ◽  
Brain Organization ◽  
Mouse Cortex ◽  
Mechanistic Investigations

AbstractIn recent years precision fMRI has emerged in human brain research, demonstrating characterization of individual differences in brain organization. However, mechanistic investigations to the sources of individual variability are limited in humans and thus require animal models. Here, we used resting-state fMRI in awake mice to quantify the contribution of individual variation to the functional architecture of the mouse cortex. We found that the mouse connectome is also characterized by stable individual features that support connectivity-based identification. Unlike in humans, we found that individual variation is homogeneously distributed in sensory and association networks. Finally, connectome-based predictive modeling of motor behavior in the rotarod task revealed that individual variation in functional connectivity explained behavioral variability. Collectively, these results establish the feasibility of precision fMRI in mice and lay the foundation for future mechanistic investigations of individual brain organization and pre-clinical studies of brain disorders in the context of personalized medicine.

scholarly journals Individual variability in functional connectivity architecture of the mouse brain

2020 ◽  
Author(s):  
Eyal Bergmann ◽  
Xenia Gofman ◽  
Alexandra Kavushansky ◽  
Itamar Kahn
Keyword(s):  
Functional Connectivity ◽  
Personalized Medicine ◽  
Individual Variation ◽  
Resting State ◽  
Functional Organization ◽  
Individual Variability ◽  
Functional Networks ◽  
Behavioral Variability ◽  
Mouse Cortex ◽  
Mechanistic Investigations

AbstractThe functional organization of brain networks can be estimated using fMRI by examining the coherence of spontaneous fluctuations in the fMRI signal, a method known as resting-state functional connectivity MRI. Previous studies in humans reported that such functional networks are dominated by stable group and individual factors, demonstrating that fMRI is suited to measuring subject-specific characteristics, and suggesting the utility of such precision fMRI approach in personalized medicine. However, mechanistic investigations to the sources of individual variability in health and disease are limited in humans and thus require animal models. Here, we used repeated-measurement resting-state fMRI in awake mice to quantify the contribution of individual variation to the functional architecture of the mouse cortex. Comparing the organization of functional networks across the group, we found dominant common organizational principles. The data also revealed stable individual features, which create a unique fingerprint that allow identification of individual mice from the group. Examining the distribution of individual variation across the mouse cortex, we found it is homogeneously distributed in both sensory and association networks. Finally, connectome-based predictive modeling of motor behavior in the rotarod task revealed that individual variation in functional connectivity explained behavioral variability. Collectively, these results show that mouse functional networks are characterized by individual variations suggesting that individual variation characterizes the mammalian cortex in general, and not only the primate cortex. These findings lay the foundation for future mechanistic investigations of individual brain organization and pre-clinical studies of brain disorders in the context of personalized medicine.

scholarly journals Individual Variation in Functional Brain Network Topography is Linked to Schizophrenia Symptomatology

2020 ◽  
Author(s):  
Uzma Nawaz ◽  
Ivy Lee ◽  
Adam Beermann ◽  
Shaun Eack ◽  
Matcheri Keshavan ◽  
...  
Keyword(s):  
Individual Differences ◽  
Functional Connectivity ◽  
Negative Symptom ◽  
Individual Variation ◽  
Symptom Severity ◽  
Spatial Organization ◽  
Brain Connectivity ◽  
Brain Network ◽  
Brain Organization ◽  
Functional Brain Network

Abstract Resting-state fMRI (rsfMRI) demonstrates that the brain is organized into distributed networks. Numerous studies have examined links between psychiatric symptomatology and network functional connectivity. Traditional rsfMRI analyses assume that the spatial organization of networks is invariant between individuals. This dogma has recently been overturned by the demonstration that networks show significant variation between individuals. We tested the hypothesis that previously observed relationships between schizophrenia-negative symptom severity and network connectivity are actually due to individual differences in network spatial organization. Forty-four participants diagnosed with schizophrenia underwent rsfMRI scans and clinical assessments. A multivariate pattern analysis determined how whole-brain functional connectivity correlates with negative symptom severity at the individual voxel level. Brain connectivity to a region of the right dorsolateral prefrontal cortex correlates with negative symptom severity. This finding results from individual differences in the topographic distribution of 2 networks: the default mode network (DMN) and the task-positive network (TPN). Both networks demonstrate strong (r = ~0.49) and significant (P < .001) relationships between topography and symptom severity. For individuals with low symptom severity, this critical region is part of the DMN. In highly symptomatic individuals, this region is part of the TPN. Previously overlooked individual variation in brain organization is tightly linked to differences in schizophrenia symptom severity. Recognizing critical links between network topography and pathological symptomology may identify key circuits that underlie cognitive and behavioral phenotypes. Individual variation in network topography likely guides different responses to clinical interventions that rely on anatomical targeting (eg, transcranial magnetic stimulation [TMS]).

scholarly journals Prevalent and sex-biased breathing patterns modify functional connectivity MRI in young adults

2020 ◽  
Vol 11 (1) ◽  
Author(s):  
Charles J. Lynch ◽  
Benjamin M. Silver ◽  
Marc J. Dubin ◽  
Alex Martin ◽  
Henning U. Voss ◽  
...  
Keyword(s):  
Young Adults ◽  
Functional Connectivity ◽  
Resting State ◽  
Resting State Fmri ◽  
Resonance Imaging ◽  
Breathing Patterns ◽  
Resting State Functional Connectivity ◽  
Brain Organization ◽  
Normal Breathing ◽  
Functional Connectivity Mri

Abstract Resting state functional connectivity magnetic resonance imaging (fMRI) is a tool for investigating human brain organization. Here we identify, visually and algorithmically, two prevalent influences on fMRI signals during 440 h of resting state scans in 440 healthy young adults, both caused by deviations from normal breathing which we term deep breaths and bursts. The two respiratory patterns have distinct influences on fMRI signals and signal covariance, distinct timescales, distinct cardiovascular correlates, and distinct tendencies to manifest by sex. Deep breaths are not sex-biased. Bursts, which are serial taperings of respiratory depth typically spanning minutes at a time, are more common in males. Bursts share features of chemoreflex-driven clinical breathing patterns that also occur primarily in males, with notable neurological, psychiatric, medical, and lifespan associations. These results identify common breathing patterns in healthy young adults with distinct influences on functional connectivity and an ability to differentially influence resting state fMRI studies.

scholarly journals Individual Variation in Brain Network Topography is Linked to Schizophrenia Symptomatology

2019 ◽  
Author(s):  
Uzma Nawaz ◽  
Ivy Lee ◽  
Adam Beermann ◽  
Shaun Eack ◽  
Matcheri Keshavan ◽  
...  
Keyword(s):  
Individual Differences ◽  
Functional Connectivity ◽  
Negative Symptom ◽  
Individual Variation ◽  
Symptom Severity ◽  
Spatial Organization ◽  
Brain Connectivity ◽  
Network Connectivity ◽  
Brain Network ◽  
Brain Organization

AbstractBackgroundResting state fMRI (rsfMRI) demonstrates that the brain is organized into distributed networks. Numerous studies have examined links between psychiatric symptomatology and network functional connectivity. Traditional rsfMRI analyses assume that the spatial organization of networks is invariant between individuals. This dogma has recently been overturned by the demonstration that networks show significant variation between individuals. We tested the hypothesis that previously observed relationships between schizophrenia negative symptom severity and network connectivity are actually due to individual differences in network spatial organization.Methods44 participants diagnosed with schizophrenia underwent rsfMRI scans and clinical assessments. A multivariate pattern analysis determined how whole brain functional connectivity correlates with negative symptom severity at the individual voxel level.ResultsBrain connectivity to a region of the right dorso-lateral pre-frontal cortex correlates with negative symptom severity. This finding results from individual differences in the topographic distribution of two networks: the default mode network (DMN) and the task positive network (TPN). Both networks demonstrate strong (r∼0.49) and significant (p<0.001) relationships between topography and symptom severity. For individuals with low symptom severity, this critical region is part of the DMN. In highly symptomatic individuals, this region is part of the TPN.ConclusionPreviously overlooked individual variation in brain organization is tightly linked to differences in schizophrenia symptom severity. Recognizing critical links between network topography and pathological symptomology may identify key circuits that underlie cognitive and behavioral phenotypes. Individual variation in network topography likely guides different responses to clinical interventions that rely on anatomical targeting (e.g. TMS).

scholarly journals Inter-individual Variability of Functional Connectivity in Awake and Anesthetized Rhesus Monkeys

2019 ◽  
Author(s):  
Ting Xu ◽  
Darrick Sturgeon ◽  
Julian S.B. Ramirez ◽  
Seán Froudist-Walsh ◽  
Daniel S. Margulies ◽  
...  
Keyword(s):  
Individual Differences ◽  
Functional Connectivity ◽  
Nonhuman Primate ◽  
Individual Variation ◽  
Large Scale ◽  
Functional Organization ◽  
Individual Variability ◽  
Initial Examination ◽  
Long Distance ◽  
Lower Variability

ABSTRACTBackgroundNonhuman primate models (NHP) are commonly used to advance our understanding of brain function and organization. However, to date, they have offered few insights into individual differences among NHPs. In large part, this is due to the logistical challenges of NHP research, which limit most studies to five subjects or fewer.MethodsWe leveraged the availability of a large-scale open NHP imaging resource to provide an initial examination of individual differences in the functional organization of the nonhuman primate brain. Specifically, we selected one awake fMRI dataset (Newcastle: n = 10) and two anesthetized fMRI data sets (Oxford: n = 19; UC-Davis: n = 19) to examine individual differences in functional connectivity characteristics across the cortex, as well as potential state dependencies.ResultsWe noted significant individual variations of functional connectivity across the macaque cortex. Similar to the findings in human, during the awake state, the primary sensory and motor cortices showed lower variability than the high-order association regions. This variability pattern was significantly correlated with T1w/T2w map, the degree of long-distance connectivity, but not short-distance connectivity. However, the inter-individual variability under anesthesia exhibited a very distinct pattern, with lower variability in medial frontal cortex, precuneus and somatomotor regions and higher variability in the lateral ventral frontal and insular cortices.ConclusionsThis work has implications for our understanding of the evolutionary origins of individual variation in the human brain, as well as methodological implications that must be considered in any pursuit to study individual variation in NHP models.

Inter-individual variation shapes the human microbiome

2019 ◽  
Vol 42 ◽  
Author(s):  
Emily F. Wissel ◽  
Leigh K. Smith
Keyword(s):  
Individual Differences ◽  
Individual Variation ◽  
Human Microbiome ◽  
Individual Variability ◽  
Microbiota Composition ◽  
Target Article ◽  
Microbiome Research

Abstract The target article suggests inter-individual variability is a weakness of microbiota-gut-brain (MGB) research, but we discuss why it is actually a strength. We comment on how accounting for individual differences can help researchers systematically understand the observed variance in microbiota composition, interpret null findings, and potentially improve the efficacy of therapeutic treatments in future clinical microbiome research.

The Negative Impact of Biological Variation in the Effect and Clearance of Warfarin on Methods for Prediction of Dose Requirements

1986 ◽  
Vol 56 (03) ◽  
pp. 371-375 ◽  
Author(s):  
Peretz Weiss ◽  
Hillel Halkin ◽  
Shlomo Almog
Keyword(s):  
Individual Variation ◽  
Negative Impact ◽  
Warfarin Dose ◽  
Empirical Therapy ◽  
Maintenance Phase ◽  
Individual Variability ◽  
Dose Prediction ◽  
Group I ◽  
Over Time ◽  
Variance Explained

SummaryWithin-individual variation over time in the clearance (Cl) and effect (PT%) of warfarin, was measured in 25 inpatients (group I) studied after standard single or individualized split loading doses and 1-3 times (n = 16) 8-16 weeks later during maintenance. Mean Cl (2.5 α 0.9 ml/min) was similar in both phases but significant changes occurred in 6/16 patients, exceeding those expected from within-individual variation alone (defined by its 95% tolerance limits -24% to +62%). Initial PT% (21 α 5) was unaffected by dosing schedule, total or free plasma warfarin, varying between patients by only 18-24%. Mean initial and maintenance dose-PT% ratios (8.2 mg/d: 21% and 4.1 mg/d: 40%) were similar but significant changes in sensitivity to warfarin occurred in 4/16 patients. In group I and 64 other outpatients on maintenance therapy, between-individual variability was 36-52% for Cl and 49-56% for effect. PT% correlated best (r = 0.56) with free and total plasma warfarin but poorly with dose (r = 0.29), with only 30% of PT% variance explained at best, due to high between patient variability.Warfarin dose prediction whether based on extrapolation from initial effects to the maintenance phase, or on iterative methods not allowing for between- or within-patient variation in warfarin clearance or effect which may occur independently over time, have not improved on empirical therapy. This, due to the elements of biological variability as well as the intricacy of the warfarin - prothrombin complex interaction not captured by any kinetic-dynamic model used for prediction to date.

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