Numerical Simulation of Higher-Order Nonlinearity of Human Brain Functional Connectivity Using Hypergraph p-Laplacian

Unravelling how the human brain structure gives rise to function is a central question in neuroscience and remains partially answered. Recent studies show that the graph Laplacian of the human brain’s structural connectivity (SC) plays a dominant role in shaping the pattern of resting-state functional connectivity (FC). The modeling of FC using the graph Laplacian of the brain’s SC is limited, owing to the sparseness of the Laplacian matrix. It is unable to model the negative functional correlations. We extended the graph Laplacian to the hypergraph p-Laplacian in order to describe better the nonlinear and high-order relations between SC and FC. First we estimated those possible links showing negative correlations between the brain areas shared across subjects by statistical analysis. Then we presented a hypergraph p-Laplacian model by embedding the two matrices referring to the sign of the correlations between the brain areas relying on the brain structural connectome. We tested the model on two experimental connectome datasets and evaluated the predicted FC by estimating its Pearson correlation with the empirical FC matrices. The results showed that the proposed diffusion model based on hypergraph p-Laplacian can predict functional correlations more accurately than the models using graph Laplacian as well as hypergraph Laplacian.

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Mapping Connectional Differences between Humans and Macaques in the Nucleus Accumbens Shell-Core Architecture

10.1101/2020.06.12.147546 ◽

2020 ◽

Cited By ~ 1

Author(s):

Xiaoluan Xia ◽

Lingzhong Fan ◽

Chen Cheng ◽

Luqi Cheng ◽

Long Cao ◽

...

Keyword(s):

Prefrontal Cortex ◽

Nucleus Accumbens ◽

Resting State ◽

Structural Connectivity ◽

Nucleus Accumbens Shell ◽

Resting State Functional Connectivity ◽

Brain Areas ◽

Common Space ◽

Species Comparisons ◽

The Brain

AbstractTwo nucleus accumbens subregions, the shell and core, differ in the patterns whereby they integrate signals from prefrontal and limbic areas of the brain. In this study, we investigated whether the disproportionate volumetric differences of these brain areas, particularly the prefrontal cortex, between humans and macaques are accompanied by unique modifications of their macroscopic integrative connections with the shell and core. More specifically, we characterized the tractographic connectivity profiles of the human and macaque shell-core architecture and compared them between the two species. To make the cross-species comparisons more viable, we used the same whole-brain voxel-wise tractography-defined shell-like and core-like divisions in the two species as seeds and delineated pairs of interspecies connectionally comparable (ICC) target regions based on the similarity of the resting-state functional connectivity profiles for the two species, and finally used these seeds and ICC targets to establish a fingerprint-based common space for cross-species comparisons. Our results revealed that dissimilar structural connectivity profiles were found in the prefrontal but not the subcortical target group. We further localized this difference to specific targets to infer possible functional modifications between the two species.

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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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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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Comparing the temporal relationship of structural and functional connectivity changes in different adult human brain networks: a single-case study

Wellcome Open Research ◽

10.12688/wellcomeopenres.14572.1 ◽

2018 ◽

Vol 3 ◽

pp. 50 ◽

Cited By ~ 1

Author(s):

Takamitsu Watanabe ◽

Geraint Rees

Keyword(s):

Functional Connectivity ◽

Human Brain ◽

Large Scale ◽

Single Case ◽

Brain Networks ◽

Structural Connectivity ◽

Time Lags ◽

Single Case Study ◽

Adult Human

Background: Despite accumulated evidence for adult brain plasticity, the temporal relationships between large-scale functional and structural connectivity changes in human brain networks remain unclear. Methods: By analysing a unique richly detailed 19-week longitudinal neuroimaging dataset, we tested whether macroscopic functional connectivity changes lead to the corresponding structural alterations in the adult human brain, and examined whether such time lags between functional and structural connectivity changes are affected by functional differences between different large-scale brain networks. Results: In this single-case study, we report that, compared to attention-related networks, functional connectivity changes in default-mode, fronto-parietal, and sensory-related networks occurred in advance of modulations of the corresponding structural connectivity with significantly longer time lags. In particular, the longest time lags were observed in sensory-related networks. In contrast, such significant temporal differences in connectivity change were not seen in comparisons between anatomically categorised different brain areas, such as frontal and occipital lobes. These observations survived even after multiple validation analyses using different connectivity definitions or using parts of the datasets. Conclusions: Although the current findings should be examined in independent datasets with different demographic background and by experimental manipulation, this single-case study indicates the possibility that plasticity of macroscopic brain networks could be affected by cognitive and perceptual functions implemented in the networks, and implies a hierarchy in the plasticity of functionally different brain systems.

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FMRI Functional Connectivity Evaluation in Alzheimer’s Stages: Linear and Non-Linear Approaches

10.21203/rs.3.rs-189491/v1 ◽

2021 ◽

Author(s):

Hessam Ahmadi ◽

Emad Fatemizadeh ◽

Ali Motie Nasrabadi

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Functional Connectivity ◽

Permutation Test ◽

Pearson Correlation ◽

Functional Integration ◽

Clustering Coefficient ◽

Kernel Trick ◽

Non Linear ◽

The Brain

Abstract Neuroimaging data analysis reveals the underlying interactions in the brain. It is essential, yet controversial, to choose a proper tool to manifest brain functional connectivity. In this regard, researchers have not reached a definitive conclusion between the linear and non-linear approaches, as both have pros and cons. In this study, to evaluate this concern, the functional Magnetic Resonance Imaging (fMRI) data of different stages of Alzheimer’s disease are investigated. In the linear approach, the Pearson Correlation Coefficient (PCC) is employed as a common technique to generate brain functional graphs. On the other hand, for non-linear approaches, two methods including Distance Correlation (DC) and the kernel trick are utilized. By the use of the three mentioned routines and graph theory, functional brain networks of all stages of Alzheimer’s disease (AD) are constructed and then sparsed. Afterwards, graph global measures are calculated over the networks and a non-parametric permutation test is conducted. Results reveal that the non-linear approaches have more potential to discriminate groups in all stages of AD. Moreover, the kernel trick method is more powerful in comparison to the DC technique. Nevertheless, AD degenerates the brain functional graphs more at the beginning stages of the disease. At the first phase, both functional integration and segregation of the brain degrades, and as AD progressed brain functional segregation further declines. The most distinguishable feature in all stages is the clustering coefficient that reflects brain functional segregation.

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Asymmetric high-order anatomical brain connectivity sculpts effective connectivity

Network Neuroscience ◽

10.1162/netn_a_00150 ◽

2020 ◽

Vol 4 (3) ◽

pp. 871-890

Author(s):

Arseny A. Sokolov ◽

Peter Zeidman ◽

Adeel Razi ◽

Michael Erb ◽

Philippe Ryvlin ◽

...

Keyword(s):

White Matter ◽

Dynamic Range ◽

Diffusion Processes ◽

Brain Connectivity ◽

Effective Connectivity ◽

Structural Connectivity ◽

Laplacian Matrix ◽

Graph Laplacian ◽

Brain Regions ◽

High Order

Bridging the gap between symmetric, direct white matter brain connectivity and neural dynamics that are often asymmetric and polysynaptic may offer insights into brain architecture, but this remains an unresolved challenge in neuroscience. Here, we used the graph Laplacian matrix to simulate symmetric and asymmetric high-order diffusion processes akin to particles spreading through white matter pathways. The simulated indirect structural connectivity outperformed direct as well as absent anatomical information in sculpting effective connectivity, a measure of causal and directed brain dynamics. Crucially, an asymmetric diffusion process determined by the sensitivity of the network nodes to their afferents best predicted effective connectivity. The outcome is consistent with brain regions adapting to maintain their sensitivity to inputs within a dynamic range. Asymmetric network communication models offer a promising perspective for understanding the relationship between structural and functional brain connectomes, both in normalcy and neuropsychiatric conditions.

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Alterations of the Brain Microstructure and Corresponding Functional Connectivity in Early-Blind Adolescents

Neural Plasticity ◽

10.1155/2019/2747460 ◽

2019 ◽

Vol 2019 ◽

pp. 1-12 ◽

Cited By ~ 1

Author(s):

Zhifeng Zhou ◽

Jinping Xu ◽

Leilei Shi ◽

Xia Liu ◽

Fen Hou ◽

...

Keyword(s):

Functional Connectivity ◽

Diffusion Tensor ◽

Mean Diffusivity ◽

Region Of Interest ◽

Visual Deprivation ◽

Light Perception ◽

Resting State Functional Connectivity ◽

Structural Reorganization ◽

Brain Microstructure ◽

The Brain

Although evidence from studies on blind adults indicates that visual deprivation early in life leads to structural and functional disruption and reorganization of the brain, whether young blind people show similar patterns remains unknown. Therefore, this study is aimed at exploring the structural and functional alterations of the brain of early-blind adolescents (EBAs) compared to normal-sighted controls (NSCs) and investigating the effects of residual light perception on brain microstructure and function in EBAs. We obtained magnetic resonance imaging (MRI) data from 23 EBAs (8 with residual light perception (LPs), 15 without light perception (NLPs)) and 21 NSCs (age range 11-19 years old). Whole-brain voxel-based analyses of diffusion tensor imaging metrics and region-of-interest analyses of resting-state functional connectivity (RSFC) were performed to compare patterns of brain microstructure and the corresponding RSFC between the groups. The results showed that structural disruptions of LPs and NLPs were mainly located in the occipital visual pathway. Compared with NLPs, LPs showed increased fractional anisotropy (FA) in the superior frontal gyrus and reduced diffusivity in the caudate nucleus. Moreover, the correlations between FA of the occipital cortices or mean diffusivity of the lingual gyrus and age were consistent with the development trajectory of the brain in NSCs, but inconsistent or even opposite in EBAs. Additionally, we found functional, but not structural, reorganization in NLPs compared with NSCs, suggesting that functional neuroplasticity occurs earlier than structural neuroplasticity in EBAs. Altogether, these findings provided new insights into the mechanisms underlying the neural reorganization of the brain in adolescents with early visual deprivation.

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