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.

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.

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.

scholarly journals Stroke-related alterations in inter-areal communication revealed via Granger causality analysis

2021 ◽  
Author(s):  
Michele Allegra ◽  
Chiara Favaretto ◽  
Nicholas Metcalf ◽  
Maurizio Corbetta ◽  
Andrea Brovelli
Keyword(s):  
Functional Connectivity ◽  
Granger Causality ◽  
Resting State ◽  
Information Transfer ◽  
Large Scale ◽  
Functional Organization ◽  
Information Flows ◽  
Causality Analysis ◽  
Stroke Patients ◽  
Granger Causality Analysis

ABSTRACTNeuroimaging and neurological studies suggest that stroke is a brain network syndrome. While causing local ischemia and cell damage at the site of injury, stroke strongly perturbs the functional organization of brain networks at large. Critically, functional connectivity abnormalities parallel both behavioral deficits and functional recovery across different cognitive domains. However, the reasons for such relations remain poorly understood. Here, we tested the hypothesis that alterations in inter-areal communication underlie stroke-related modulations in functional connectivity (FC). To this aim, we used resting-state fMRI and Granger causality analysis to quantify information transfer between brain areas and its alteration in stroke. Two main large-scale anomalies were observed in stroke patients. First, inter-hemispheric information transfer was strongly decreased with respect to healthy controls. Second, information transfer within the affected hemisphere, and from the affected to the intact hemisphere was reduced. Both anomalies were more prominent in resting-state networks related to attention and language, and they were correlated with impaired performance in several behavioral domains. Overall, our results support the hypothesis that stroke perturbs inter-areal communication within and across hemispheres, and suggest novel therapeutic approaches aimed at restoring normal information flow.SIGNIFICANCE STATEMENTA thorough understanding of how stroke perturbs brain function is needed to improve recovery from the severe neurological syndromes affecting stroke patients. Previous resting-state neuroimaging studies suggested that interaction between hemispheres decreases after stroke, while interaction between areas of the same hemisphere increases. Here, we used Granger causality to reconstruct information flows in the brain at rest, and analyze how stroke perturbs them. We showed that stroke causes a global reduction of inter-hemispheric communication, and an imbalance between the intact and the affected hemisphere: information flows within and from the latter are impaired. Our results may inform the design of stimulation therapies to restore the functional balance lost after stroke.

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]).

Analysis of individual differences in behavioural responsiveness in pigs

1989 ◽  
Vol 1989 ◽  
pp. 92-92
Author(s):  
C. Terlouw ◽  
A.B. Lawrence ◽  
A.W. Illius
Keyword(s):  
Individual Differences ◽  
Individual Variation ◽  
Mating Behaviour ◽  
Individual Variability ◽  
General Description ◽  
Environmental Challenges ◽  
Group A ◽  
Considerable Individual Variation ◽  
Environmental Challenge

Animals show considerable individual variation in many behaviour patterns such as feeding and mating behaviour. Often, this individual variability is ignored in favour of a more general description of the population. However, this may mask important information regarding the causes and functions of this individual variability. Behavioural work on other species has suggested that individuals tend to respond actively or passively to environmental challenge. It is of interest to know if a similar dimension of responsiveness exists in pigs as it may serve, amongst other things, to explain the considerable individual variability in pigs responses to putitive stresses such as tethered housing. This paper describes a series of tests made of behavioural responsiveness in pigs to assess the extent of consistent variability in individuals responses to a wide variety of environmental challenges.The subjects were two groups [Group A and B: n = 26 and 36 respectively) of modern hybrid non-pregnant gilts [Cotswold Pig Development Company Ltd, UK). Initially, the gilts were subjected to a number of tests of behavioural responsiveness at the Cotswold unit.

scholarly journals Is baseline pupil size related to cognitive ability? Yes (under proper lighting conditions).

2020 ◽  
Author(s):  
Jason S. Tsukahara ◽  
Randall W Engle
Keyword(s):  
Working Memory ◽  
Individual Differences ◽  
Cognitive Ability ◽  
Pupil Size ◽  
Large Scale ◽  
Fluid Intelligence ◽  
Functional Organization ◽  
Working Memory Capacity ◽  
Memory Capacity ◽  
Lighting Conditions

We found that individual differences in baseline pupil size correlated with fluid intelligence and working memory capacity. Larger pupil size was associated with higher cognitive ability. However, other researchers have not been able to replicate our 2016 finding – though they only measured working memory capacity and not fluid intelligence. In a reanalysis of Tsukahara et al. (2016) we show that reduced variability on baseline pupil size will result in a higher probability of obtaining smaller and non-significant correlations with working memory capacity. In two large-scale studies, we demonstrated that reduced variability in baseline pupil size values was due to the monitor being too bright. Additionally, fluid intelligence and working memory capacity did correlate with baseline pupil size except in the brightest lighting conditions. Overall, our findings demonstrated that the baseline pupil size – working memory capacity relationship was not as strong or robust as that with fluid intelligence. Our findings have strong methodological implications for researchers investigating individual differences in task-free or task-evoked pupil size. We conclude that fluid intelligence does correlate with baseline pupil size and that this is related to the functional organization of the resting-state brain through the locus coeruleus-norepinephrine system.

scholarly journals Overlapping connectivity gradients in the anterior temporal lobe underlie semantic cognition

2020 ◽  
Author(s):  
Myrthe Faber ◽  
Izabela Przeździk ◽  
Guillén Fernández ◽  
Koen V. Haak ◽  
Christian F. Beckmann
Keyword(s):  
Individual Differences ◽  
Functional Connectivity ◽  
Temporal Lobe ◽  
Functional Organization ◽  
The Other ◽  
Story Comprehension ◽  
Anterior Temporal Lobe ◽  
Semantic Cognition ◽  
Human Connectome Project ◽  
Spatially Varying

AbstractConvergent evidence from neuroimaging, computational, and clinical research has shown that the anterior temporal lobe (ATL) is critically involved in two key aspects of semantic cognition: the representation of semantic knowledge, and the executive regulation of this knowledge. Both are necessary for integrating features to understand concepts, and to integrate concepts to understand discourse. Here, we tested the hypothesis that these differential aspects of integration map onto different patterns of ATL connectivity. Specifically, we hypothesized that there are two overlapping modes of functional connectivity of the ATL that each predict distinct aspects of semantic cognition on an individual level. We used a novel analytical approach (connectopic mapping) to identify the first two dominant modes connection topographies (i.e. maps of spatially varying connectivity) in the ATL in 766 participants (Human Connectome Project), and summarized these into 16 parameters that reflect inter-individual differences in their functional organization. If these connection topographies reflect the ATL’s functional multiplicity, then we would expect to find a dissociation where one mode (but not the other) correlates with cross-modal matching of verbal and visual information (picture vocabulary naming), and the other (but not the former) correlates with how quickly and accurately relevant semantic information is retrieved (story comprehension). Our analysis revealed a gradient of spatially varying connectivity along the inferior-superior axis, and secondly, an anterior to posterior gradient. Multiple regression analyses revealed a double dissociation such that individual differences in the inferior-superior gradient are predictive of differences in story comprehension, whereas the anterior-posterior gradient maps onto differences in picture vocabulary naming, but not vice versa. These findings indicate that overlapping gradients of functional connectivity in the ATL are related to differential behaviors, which is important for understanding how its functional organization underlies its multiple functions.

scholarly journals Impact of inter- and intra-individual variation, sample storage and sampling fraction on human stool microbial community profiles

PeerJ ◽  
2019 ◽  
Vol 7 ◽  
pp. e6172 ◽  
Author(s):  
Yun Kit Yeoh ◽  
Zigui Chen ◽  
Mamie Hui ◽  
Martin C.S. Wong ◽  
Wendy C.S. Ho ◽  
...  
Keyword(s):  
Microbial Community ◽  
Community Composition ◽  
Individual Variation ◽  
Large Scale ◽  
Microbial Community Composition ◽  
Amplicon Sequencing ◽  
Relative Effect ◽  
Individual Variability ◽  
Rrna Gene ◽  
Sample Collection

Stools are commonly used as proxies for studying human gut microbial communities as sample collection is straightforward, cheap and non-invasive. In large-scale human population surveys, however, sample integrity becomes an issue as it is not logistically feasible for researchers to personally collect stools from every participant. Instead, participants are usually given guidelines on sample packaging and storage, and asked to deliver their stools to a centralised facility. Here, we tested a number of delivery conditions (temperature, duration and addition of preservative medium) and assessed their effects on stool microbial community composition using 16S rRNA gene amplicon sequencing. The largest source of variability in stool community composition was attributable to inter-individual differences regardless of delivery condition. Although the relative effect of delivery condition on community composition was small compared to inter-individual variability (1.6% vs. 60.5%, permutational multivariate analysis of variance [PERMANOVA]) and temporal variation within subjects over 10 weeks (5.2%), shifts in microbial taxa associated with delivery conditions were non-systematic and subject-specific. These findings indicated that it is not possible to model or accurately predict shifts in stool community composition associated with sampling logistics. Based on our findings, we recommend delivery of fresh, preservative-free stool samples to laboratories within 2 hr either at ambient or chilled temperatures to minimise perturbations to microbial community composition. In addition, subsamples from different fractions of the same stool displayed a small (3.3% vs. 72.6% inter-individual variation, PERMANOVA) but significant effect on community composition. Collection of larger sample volumes for homogenisation is recommended.

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 Individual variability in functional organization of the human and monkey auditory cortex

2020 ◽  
Author(s):  
Jianxun Ren ◽  
Hesheng Liu ◽  
Ting Xu ◽  
Danhong Wang ◽  
Meiling Li ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Auditory Cortex ◽  
Cognitive Processes ◽  
Functional Organization ◽  
Individual Variability ◽  
Dependent Plasticity ◽  
Visual Areas ◽  
Connectivity Patterns ◽  
Fmri Analysis ◽  
Auditory Functions

AbstractAccumulating evidence shows that auditory cortex (AC) of humans, and other primates, is involved in more complex cognitive processes than feature segregation only, which are shaped by experience-dependent plasticity and thus likely show substantial individual variability. However, thus far, individual variability of ACs has been considered a methodological impediment rather than a phenomenon of theoretical importance. Here, we examined the variability of ACs using intrinsic functional connectivity patterns in humans and macaques. Our results demonstrate that in humans, functional variability is 1) greater near the non-primary than primary ACs, 2) greater in ACs than comparable visual areas, and 3) greater in the left than right ACs. Remarkably similar modality differences and lateralization of variability were observed in macaques. These connectivity-based findings are consistent with a confirmatory task-based fMRI analysis. The quantitative proof of the exceptional variability of ACs has implications for understanding the evolution of advanced auditory functions in humans.

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