Distinct structure-function relationships across cortical regions and connectivity scales in the rat brain

AbstractAn improved understanding of the structure-function relationship in the brain is necessary to know to what degree structural connectivity underpins abnormal functional connectivity seen in disorders. We integrated high-field resting-state fMRI-based functional connectivity with high-resolution macro-scale diffusion-based and meso-scale neuronal tracer-based structural connectivity, to obtain an accurate depiction of the structure-function relationship in the rat brain. Our main goal was to identify to what extent structural and functional connectivity strengths are correlated, macro- and meso-scopically, across the cortex. Correlation analyses revealed a positive correspondence between functional and macro-scale diffusion-based structural connectivity, but no significant correlation between functional connectivity and meso-scale neuronal tracer-based structural connectivity. Zooming in on individual connections, we found strong functional connectivity in two well-known resting-state networks: the sensorimotor and default mode network. Strong functional connectivity within these networks coincided with strong short-range intrahemispheric structural connectivity, but with weak heterotopic interhemispheric and long-range intrahemispheric structural connectivity. Our study indicates the importance of combining measures of connectivity at distinct hierarchical levels to accurately determine connectivity across networks in the healthy and diseased brain. Although characteristics of the applied techniques may affect where structural and functional networks (dis)agree, distinct structure-function relationships across the brain could also have a biological basis.

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Distinct structure-function relationships across cortical regions and connectivity scales in the rat brain

10.1101/742833 ◽

2019 ◽

Author(s):

Milou Straathof ◽

Michel R.T. Sinke ◽

Theresia J.M. Roelofs ◽

Erwin L.A. Blezer ◽

R. Angela Sarabdjitsingh ◽

...

Keyword(s):

Functional Connectivity ◽

Structure Function ◽

Rat Brain ◽

Resting State ◽

Structural Connectivity ◽

Distinct Structure ◽

Macro Scale ◽

Function Relationship ◽

The Brain ◽

Meso Scale

AbstractAn improved understanding of the structure-function relationship in the brain is necessary to know to what degree structural connectivity underpins abnormal functional connectivity seen in many disorders. We integrated high-field resting-state fMRI-based functional connectivity with high-resolution macro-scale diffusion-based and meso-scale neuronal tracer-based structural connectivity, to obtain an accurate depiction of the structure-function relationship in the rat brain. Our main goal was to identify to what extent structural and functional connectivity strengths are correlated, macro- and meso-scopically, across the cortex. Correlation analyses revealed a positive correspondence between functional connectivity and macro-scale diffusion-based structural connectivity, but no correspondence between functional connectivity and meso-scale neuronal tracer-based structural connectivity. Locally, strong functional connectivity was found in two well-known resting-state networks: the sensorimotor and default mode network. Strong functional connectivity within these networks coincided with strong short-range intrahemispheric structural connectivity, but with weak heterotopic interhemispheric and long-range intrahemispheric structural connectivity. Our study indicates the importance of combining measures of connectivity at distinct hierarchical levels to accurately determine connectivity across networks in the healthy and diseased brain. Distinct structure-function relationships across the brain can explain the organization of networks and may underlie variations in the impact of structural damage on functional networks and behavior.

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A systematic review on the quantitative relationship between structural and functional network connectivity strength in mammalian brains

Journal of Cerebral Blood Flow & Metabolism ◽

10.1177/0271678x18809547 ◽

2018 ◽

Vol 39 (2) ◽

pp. 189-209 ◽

Cited By ~ 21

Author(s):

Milou Straathof ◽

Michel RT Sinke ◽

Rick M Dijkhuizen ◽

Willem M Otte

Keyword(s):

Functional Connectivity ◽

Structure Function ◽

Brain Plasticity ◽

Structural Connectivity ◽

Quantitative Relationship ◽

Mammalian Brain ◽

Structure Function Relationship ◽

Functional Connectivity Strength ◽

Function Relationship ◽

Connectivity Strength

The mammalian brain is composed of densely connected and interacting regions, which form structural and functional networks. An improved understanding of the structure–function relation is crucial to understand the structural underpinnings of brain function and brain plasticity after injury. It is currently unclear how functional connectivity strength relates to structural connectivity strength. We obtained an overview of recent papers that report on correspondences between quantitative functional and structural connectivity measures in the mammalian brain. We included network studies in which functional connectivity was measured with resting-state fMRI, and structural connectivity with either diffusion-weighted MRI or neuronal tract tracers. Twenty-seven of the 28 included studies showed a positive structure–function relationship. Large inter-study variations were found comparing functional connectivity strength with either quantitative diffusion-based (correlation coefficient (r) ranges: 0.18–0.82) or neuronal tracer-based structural connectivity measures (r = 0.24–0.74). Two functional datasets demonstrated lower structure–function correlations with neuronal tracer-based (r = 0.22 and r = 0.30) than with diffusion-based measures (r = 0.49 and r = 0.65). The robust positive quantitative structure–function relationship supports the hypothesis that structural connectivity provides the hardware from which functional connectivity emerges. However, methodological differences between the included studies complicate the comparison across studies, which emphasize the need for validation and standardization in brain structure–function studies.

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Time-resolved structure-function coupling in brain networks

10.1101/2021.07.08.451672 ◽

2021 ◽

Author(s):

Zhen-Qi Liu ◽

Bertha Vazquez-Rodriguez ◽

R. Nathan Spreng ◽

Boris Bernhardt ◽

Richard F. Betzel ◽

...

Keyword(s):

Functional Connectivity ◽

Structure Function ◽

Insular Cortex ◽

Dynamic Structure ◽

Time Resolved ◽

Informative Feature ◽

Dorsal Attention Network ◽

Function Relationship ◽

The Relationship ◽

The Brain

The relationship between structural and functional connectivity in the brain is a key question in systems neuroscience. Modern accounts assume a single global structure-function relationship that persists over time. Here we show that structure-function coupling is dynamic and regionally heterogeneous. We use a temporal unwrapping procedure to identify moment-to-moment co-fluctuations in neural activity, and reconstruct time-resolved structure-function coupling patterns. We find that patterns of dynamic structure-function coupling are highly organized across the cortex. These patterns reflect cortical hierarchies, with stable coupling in unimodal and transmodal cortex, and dynamic coupling in intermediate regions, particularly in insular cortex (salience network) and frontal eye fields (dorsal attention network). Finally, we show that the variability of structure-function coupling is shaped by the distribution of connection lengths. The time-varying coupling of structural and functional connectivity points towards an informative feature of the brain that may reflect how cognitive functions are flexibly deployed and implemented.

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The Brain Resting-State Functional Connectivity Underlying Violence Proneness: Is It a Reliable Marker for Neurocriminology? A Systematic Review

Behavioral Sciences ◽

10.3390/bs9010011 ◽

2019 ◽

Vol 9 (1) ◽

pp. 11 ◽

Cited By ~ 4

Author(s):

Ángel Romero-Martínez ◽

Macarena González ◽

Marisol Lila ◽

Enrique Gracia ◽

Luis Martí-Bonmatí ◽

...

Keyword(s):

Functional Connectivity ◽

Effective Treatment ◽

Resting State ◽

Brain Structures ◽

Prevention Programs ◽

Angular Gyrus ◽

Resting State Functional Connectivity ◽

Treatment And Prevention ◽

Reliable Marker ◽

The Brain

Introduction: There is growing scientific interest in understanding the biological mechanisms affecting and/or underlying violent behaviors in order to develop effective treatment and prevention programs. In recent years, neuroscientific research has tried to demonstrate whether the intrinsic activity within the brain at rest in the absence of any external stimulation (resting-state functional connectivity; RSFC) could be employed as a reliable marker for several cognitive abilities and personality traits that are important in behavior regulation, particularly, proneness to violence. Aims: This review aims to highlight the association between the RSFC among specific brain structures and the predisposition to experiencing anger and/or responding to stressful and distressing situations with anger in several populations. Methods: The scientific literature was reviewed following the PRISMA quality criteria for reviews, using the following digital databases: PubMed, PsycINFO, Psicodoc, and Dialnet. Results: The identification of 181 abstracts and retrieval of 34 full texts led to the inclusion of 17 papers. The results described in our study offer a better understanding of the brain networks that might explain the tendency to experience anger. The majority of the studies highlighted that diminished RSFC between the prefrontal cortex and the amygdala might make people prone to reactive violence, but that it is also necessary to contemplate additional cortical (i.e. insula, gyrus [angular, supramarginal, temporal, fusiform, superior, and middle frontal], anterior and posterior cingulated cortex) and subcortical brain structures (i.e. hippocampus, cerebellum, ventral striatum, and nucleus centralis superior) in order to explain a phenomenon as complex as violence. Moreover, we also described the neural pathways that might underlie proactive violence and feelings of revenge, highlighting the RSFC between the OFC, ventral striatal, angular gyrus, mid-occipital cortex, and cerebellum. Conclusions. The results from this synthesis and critical analysis of RSFC findings in several populations offer guidelines for future research and for developing a more accurate model of proneness to violence, in order to create effective treatment and prevention programs.

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Functional connectivity of fMRI using differential covariance predicts structural connectivity and behavioral reaction times

10.1101/2021.09.01.458609 ◽

2021 ◽

Author(s):

Yusi Chen ◽

Qasim Bukhari ◽

Tiger Wutu Lin ◽

Terrence J Sejnowski

Keyword(s):

Magnetic Resonance Imaging ◽

Magnetic Resonance ◽

Functional Connectivity ◽

Resting State ◽

Structural Connectivity ◽

Reaction Times ◽

Resonance Imaging ◽

Brain Areas ◽

Human Connectome Project ◽

Wide Range

Recordings from resting state functional magnetic resonance imaging (rs-fMRI) reflect the influence of pathways between brain areas. A wide range of methods have been proposed to measure this functional connectivity (FC), but the lack of ''ground truth'' has made it difficult to systematically validate them. Most measures of FC produce connectivity estimates that are symmetrical between brain areas. Differential covariance (dCov) is an algorithm for analyzing FC with directed graph edges. Applied to synthetic datasets, dCov-FC was more effective than covariance and partial correlation in reducing false positive connections and more accurately matching the underlying structural connectivity. When we applied dCov-FC to resting state fMRI recordings from the human connectome project (HCP) and anesthetized mice, dCov-FC accurately identified strong cortical connections from diffusion Magnetic Resonance Imaging (dMRI) in individual humans and viral tract tracing in mice. In addition, those HCP subjects whose rs-fMRI were more integrated, as assessed by a graph-theoretic measure, tended to have shorter reaction times in several behavioral tests. Thus, dCov-FC was able to identify anatomically verified connectivity that yielded measures of brain integration causally related to behavior.

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Computerized physical and cognitive training improves the functional architecture of the brain in adults with Down syndrome: A network science EEG study

Network Neuroscience ◽

10.1162/netn_a_00177 ◽

2020 ◽

pp. 1-21

Author(s):

Alexandra Anagnostopoulou ◽

Charis Styliadis ◽

Panagiotis Kartsidis ◽

Evangelia Romanopoulou ◽

Vasiliki Zilidou ◽

...

Keyword(s):

Down Syndrome ◽

Functional Connectivity ◽

Cognitive Training ◽

Resting State ◽

Network Architecture ◽

Right Hemisphere ◽

Random Network ◽

Brain Activity ◽

Hierarchical Organization ◽

The Brain

Understanding the neuroplastic capacity of people with Down syndrome (PwDS) can potentially reveal the causal relationship between aberrant brain organization and phenotypic characteristics. We used resting-state EEG recordings to identify how a neuroplasticity-triggering training protocol relates to changes in the functional connectivity of the brain’s intrinsic cortical networks. Brain activity of 12 PwDS before and after a 10-week protocol of combined physical and cognitive training was statistically compared to quantify changes in directed functional connectivity in conjunction with psychosomatometric assessments. PwDS showed increased connectivity within the left hemisphere and from left-to-right hemisphere, as well as increased physical and cognitive performance. Our findings reveal a strong adaptive neuroplastic reorganization as a result of the training that leads to a less-random network with a more pronounced hierarchical organization. Our results go beyond previous findings by indicating a transition to a healthier, more efficient, and flexible network architecture, with improved integration and segregation abilities in the brain of PwDS. Resting-state electrophysiological brain activity is used here for the first time to display meaningful relationships to underlying Down syndrome processes and outcomes of importance in a translational inquiry. This trial is registered with ClinicalTrials.gov Identifier NCT04390321.

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Local and Distant responses to single pulse electrical stimulation reflect different forms of connectivity

10.1101/2020.10.13.20212266 ◽

2020 ◽

Author(s):

Britni Crocker ◽

Lauren Ostrowski ◽

Ziv M. Williams ◽

Darin D. Dougherty ◽

Emad N. Eskandar ◽

...

Keyword(s):

Electrical Stimulation ◽

Resting State ◽

Diffusion Tensor ◽

Effective Connectivity ◽

Clinical Care ◽

Structural Connectivity ◽

Intractable Epilepsy ◽

Single Pulse ◽

Intracranial Electrode ◽

The Brain

AbstractBackgroundMeasuring connectivity in the human brain can involve innumerable approaches using both noninvasive (fMRI, EEG) and invasive (intracranial EEG or iEEG) recording modalities, including the use of external probing stimuli, such as direct electrical stimulation.Objective/HypothesisTo examine how different measures of connectivity correlate with one another, we compared ‘passive’ measures of connectivity during resting state conditions map to the more ‘active’ probing measures of connectivity with single pulse electrical stimulation (SPES).MethodsWe measured the network engagement and spread of the cortico-cortico evoked potential (CCEP) induced by SPES at 53 total sites across the brain, including cortical and subcortical regions, in patients with intractable epilepsy (N=11) who were undergoing intracranial recordings as a part of their clinical care for identifying seizure onset zones. We compared the CCEP network to functional, effective, and structural measures of connectivity during a resting state in each patient. Functional and effective connectivity measures included correlation or Granger causality measures applied to stereoEEG (sEEGs) recordings. Structural connectivity was derived from diffusion tensor imaging (DTI) acquired before intracranial electrode implant and monitoring (N=8).ResultsThe CCEP network was most similar to the resting state voltage correlation network in channels near to the stimulation location. In contrast, the distant CCEP network was most similar to the DTI network. Other connectivity measures were not as similar to the CCEP network.ConclusionsThese results demonstrate that different connectivity measures, including those derived from active stimulation-based probing, measure different, complementary aspects of regional interrelationships in the brain.

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Brain network dynamics correlate with personality traits

10.1101/702266 ◽

2019 ◽

Cited By ~ 1

Author(s):

Aya Kabbara ◽

Veronique Paban ◽

Arnaud Weill ◽

Julien Modolo ◽

Mahmoud Hassan

Keyword(s):

Functional Connectivity ◽

Personality Traits ◽

Resting State ◽

Brain Networks ◽

Neural Substrates ◽

Brain Network ◽

Functional Brain ◽

Human Connectome Project ◽

Functional Brain Networks ◽

The Brain

AbstractIntroductionIdentifying the neural substrates underlying the personality traits is a topic of great interest. On the other hand, it is now established that the brain is a dynamic networked system which can be studied using functional connectivity techniques. However, much of the current understanding of personality-related differences in functional connectivity has been obtained through the stationary analysis, which does not capture the complex dynamical properties of brain networks.ObjectiveIn this study, we aimed to evaluate the feasibility of using dynamic network measures to predict personality traits.MethodUsing the EEG/MEG source connectivity method combined with a sliding window approach, dynamic functional brain networks were reconstructed from two datasets: 1) Resting state EEG data acquired from 56 subjects. 2) Resting state MEG data provided from the Human Connectome Project. Then, several dynamic functional connectivity metrics were evaluated.ResultsSimilar observations were obtained by the two modalities (EEG and MEG) according to the neuroticism, which showed a negative correlation with the dynamic variability of resting state brain networks. In particular, a significant relationship between this personality trait and the dynamic variability of the temporal lobe regions was observed. Results also revealed that extraversion and openness are positively correlated with the dynamics of the brain networks.ConclusionThese findings highlight the importance of tracking the dynamics of functional brain networks to improve our understanding about the neural substrates of personality.

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