Discovering effective connectivity among brain regions from functional MRI data

AbstractFigurative language processing (e.g. metaphors) is commonly impaired in schizophrenia. In the present study, we investigated the neural activity and propagation of information within neural circuits related to the figurative speech, as a neural substrate of impaired conventional metaphor processing in schizophrenia. The study included 30 schizophrenia outpatients and 30 healthy controls, all of whom were assessed with a functional Magnetic Resonance Imaging (fMRI) and electroencephalography (EEG) punchline-based metaphor comprehension task including literal (neutral), figurative (metaphorical) and nonsense (absurd) endings. The blood oxygenation level-dependent signal was recorded with 3T MRI scanner and direction and strength of cortical information flow in the time course of task processing was estimated with a 64-channel EEG input for directed transfer function. The presented results revealed that the behavioral manifestation of impaired figurative language in schizophrenia is related to the hypofunction in the bilateral fronto-temporo-parietal brain regions (fMRI) and various differences in effective connectivity in the fronto-temporo-parietal circuit (EEG). Schizophrenia outpatients showed an abnormal pattern of connectivity during metaphor processing which was related to bilateral (but more pronounced at the left hemisphere) hypoactivation of the brain. Moreover, we found reversed lateralization patterns, i.e. a rightward-shifted pattern during metaphor processing in schizophrenia compared to the control group. In conclusion, the presented findings revealed that the impairment of the conventional metaphor processing in schizophrenia is related to the bilateral brain hypofunction, which supports the evidence on reversed lateralization of the language neural network and the existence of compensatory recruitment of alternative neural circuits in schizophrenia.

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Structural and Functional MRI Brain Changes in Patients with Schizophrenia Following Electroconvulsive Therapy: A Systematic Review

Current Neuropharmacology ◽

10.2174/1570159x19666210809101248 ◽

2021 ◽

Vol 19 ◽

Author(s):

Yuchao Jiang ◽

Mingjun Duan ◽

Hui He ◽

Dezhong Yao ◽

Cheng Luo

Keyword(s):

Systematic Review ◽

Functional Mri ◽

Electroconvulsive Therapy ◽

Brain Regions ◽

Parahippocampal Gyrus ◽

Medical Subject Headings ◽

Therapeutic Mechanisms ◽

Brain Changes ◽

Meta Analyses ◽

Induced Changes

Background: Schizophrenia (SZ) is a severe psychiatric disorder typically characterized by multidimensional psychotic syndromes. Electroconvulsive therapy (ECT) is a treatment option for medication-resistant patients with SZ or to resolve acute symptoms. Although the efficacy of ECT has been demonstrated in clinical use, its therapeutic mechanisms in the brain remain elusive. Objective: This study aimed to summarize brain changes on structural magnetic resonance imaging (sMRI) and functional MRI (fMRI) after ECT. Methods: According to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, a systematic review was carried out. The PubMed and Medline databases were systematically searched using the following medical subject headings (MeSH): (electroconvulsive therapy OR ECT) AND (schizophrenia) AND (MRI OR fMRI OR DTI OR DWI). Results: This review yielded 12 MRI studies, including 4 with sMRI, 5 with fMRI and 3 with multimodal MRI. Increases in volumes of the hippocampus and its adjacent regions (parahippocampal gyrus and amygdala) as well as insula and frontotemporal regions were noted after ECT. fMRI studies found ECT-induced changes in different brain regions/networks, including the hippocampus, amygdala, default model network, salience network and other regions/networks that are thought to highly correlate with the pathophysiologic characteristics of SZ. The results of the correlation between brain changes and symptom remissions are inconsistent Conclusion: Our review provides evidence supporting ECT-induced brain changes on sMRI and fMRI in SZ and explores the relationship between these changes and symptom remission.

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Category representations in the brain are both discretely localized and widely distributed

Journal of Neurophysiology ◽

10.1152/jn.00912.2017 ◽

2018 ◽

Vol 119 (6) ◽

pp. 2256-2264 ◽

Cited By ~ 3

Author(s):

Zarrar Shehzad ◽

Gregory McCarthy

Keyword(s):

Functional Mri ◽

Brain Connectivity ◽

Strong Support ◽

Brain Regions ◽

Distributed Representations ◽

Domain Specific ◽

Category Information ◽

Shared Information ◽

Unique Domain ◽

The Brain

Whether category information is discretely localized or represented widely in the brain remains a contentious issue. Initial functional MRI studies supported the localizationist perspective that category information is represented in discrete brain regions. More recent fMRI studies using machine learning pattern classification techniques provide evidence for widespread distributed representations. However, these latter studies have not typically accounted for shared information. Here, we find strong support for distributed representations when brain regions are considered separately. However, localized representations are revealed by using analytical methods that separate unique from shared information among brain regions. The distributed nature of shared information and the localized nature of unique information suggest that brain connectivity may encourage spreading of information but category-specific computations are carried out in distinct domain-specific regions. NEW & NOTEWORTHY Whether visual category information is localized in unique domain-specific brain regions or distributed in many domain-general brain regions is hotly contested. We resolve this debate by using multivariate analyses to parse functional MRI signals from different brain regions into unique and shared variance. Our findings support elements of both models and show information is initially localized and then shared among other regions leading to distributed representations being observed.

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Altered Prefrontal–Basal Ganglia Effective Connectivity in Patients With Poststroke Cognitive Impairment

Frontiers in Neurology ◽

10.3389/fneur.2020.577482 ◽

2020 ◽

Vol 11 ◽

Author(s):

Jing Zhang ◽

Zixiao Li ◽

Xingxing Cao ◽

Lijun Zuo ◽

Wei Wen ◽

...

Keyword(s):

Cognitive Impairment ◽

Basal Ganglia ◽

Cognitive Decline ◽

Effective Connectivity ◽

Network Connectivity ◽

Brain Regions ◽

Neuronal Model ◽

Causal Modeling ◽

Healthy Controls

We investigated the association between poststroke cognitive impairment and a specific effective network connectivity in the prefrontal–basal ganglia circuit. The resting-state effective connectivity of this circuit was modeled by employing spectral dynamic causal modeling in 11 poststroke patients with cognitive impairment (PSCI), 8 poststroke patients without cognitive impairment (non-PSCI) at baseline and 3-month follow-up, and 28 healthy controls. Our results showed that different neuronal models of effective connectivity in the prefrontal–basal ganglia circuit were observed among healthy controls, non-PSCI, and PSCI patients. Additional connected paths (extra paths) appeared in the neuronal models of stroke patients compared with healthy controls. Moreover, changes were detected in the extra paths of non-PSCI between baseline and 3-month follow-up poststroke, indicating reorganization in the ipsilesional hemisphere and suggesting potential compensatory changes in the contralesional hemisphere. Furthermore, the connectivity strengths of the extra paths from the contralesional ventral anterior nucleus of thalamus to caudate correlated significantly with cognitive scores in non-PSCI and PSCI patients. These suggest that the neuronal model of effective connectivity of the prefrontal–basal ganglia circuit may be sensitive to stroke-induced cognitive decline, and it could be a biomarker for poststroke cognitive impairment 3 months poststroke. Importantly, contralesional brain regions may play an important role in functional compensation of cognitive decline.

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Dynamic and stable brain connectivity during movie watching as revealed by functional MRI

10.1101/2021.09.14.460293 ◽

2021 ◽

Author(s):

Xin Di ◽

Zhiguo Zhang ◽

Ting Xu ◽

Bharat B. Biswal

Keyword(s):

Functional Mri ◽

Brain Connectivity ◽

Brain Regions ◽

Posterior Cingulate Cortex ◽

Temporoparietal Junction ◽

Related Information ◽

Movie Clip ◽

Brain Changes ◽

Brain Processing ◽

Dynamic Connectivity

AbstractSpatially remote brain regions show synchronized activity as typically revealed by correlated functional MRI (fMRI) signals. An emerging line of research has focused on the temporal fluctuations of connectivity, however, its relationships with stable connectivity have not been clearly illustrated. We examined the stable and dynamic connectivity from fMRI data when the participants watched four different movie clips. Using inter-individual correlation, we were able to estimate functionally meaningful dynamic connectivity associated with different movies. Widespread consistent dynamic connectivity was observed for each movie clip as well as their differences between clips. A cartoon movie clip showed higher consistent dynamic connectivity with the posterior cingulate cortex and supramarginal gyrus, while a court drama clip showed higher dynamic connectivity with the auditory cortex and temporoparietal junction, which suggest the involvement of specific brain processing for different movie contents. In contrast, stable connectivity was highly similar among the movie clips, and showed fewer statistical significant differences. The patterns of dynamic connectivity had higher accuracy for classifications of different movie clips than the stable connectivity and regional activity. These results support the functional significance of dynamic connectivity in reflecting functional brain changes, which could provide more functionally related information than stable connectivity.

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Individual Differences in Mental Imagery Modulate Effective Connectivity of Scene-Selective Regions During Resting State

10.21203/rs.3.rs-887061/v1 ◽

2021 ◽

Author(s):

Maria Giulia Tullo ◽

Hannes Almgren ◽

Frederik Van de Steen ◽

Valentina Sulpizio ◽

Daniele Marinazzo ◽

...

Keyword(s):

Individual Differences ◽

Mental Imagery ◽

Resting State ◽

Effective Connectivity ◽

Relevant Information ◽

Brain Regions ◽

Intrinsic Activity ◽

Inhibitory Influence ◽

Cortical Regions ◽

Intrinsic Fluctuation

Abstract Successful navigation relies on the ability to identify, perceive, and correctly process the spatial structure of a scene. It is well known that visual mental imagery plays a crucial role in navigation. Indeed, cortical regions encoding navigationally relevant information are also active during mental imagery of navigational scenes. However, it remains unknown whether their intrinsic activity and connectivity reflect the individuals’ ability to imagine a scene. Here, we primarily investigated the intrinsic causal interactions among scene-selective brain regions such as Parahipoccampal Place Area (PPA), Retrosplenial Complex (RSC), and Occipital Place Area (OPA) using Dynamic Causal Modelling (DCM) for resting-state functional magnetic resonance (rs-fMRI) data. Second, we tested whether resting-state effective connectivity parameters among scene-selective regions could reflect individual differences in mental imagery in our sample, as assessed by the self-reported Vividness of Visual Imagery Questionnaire (VVIQ). We found an inhibitory influence of occipito-medial on temporal regions, and an excitatory influence of more anterior on more medial and posterior brain regions. Moreover, we found that a key role in imagery is played by the connection strength from OPA to PPA, especially in the left hemisphere, since the influence of the signal between these scene-selective regions positively correlated with good mental imagery ability. Our investigation contributes to the understanding of the complexity of the causal interaction among brain regions involved in navigation and provides new insight in understanding how an essential ability, such as mental imagery, can be explained by the intrinsic fluctuation of brain signal.

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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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A functional MRI study of presurgical cognitive deficits in glioma patients

Neuro-Oncology Practice ◽

10.1093/nop/npaa059 ◽

2020 ◽

Author(s):

Irena T Schouwenaars ◽

Miek J de Dreu ◽

Geert-Jan M Rutten ◽

Nick F Ramsey ◽

Johan M Jansma

Keyword(s):

Functional Mri ◽

Cognitive Deficits ◽

Brain Activity ◽

Neuropsychological Testing ◽

Region Of Interest ◽

High Grade Glioma ◽

Brain Regions ◽

Brain State ◽

Low Grade ◽

Activity Levels

Abstract Background The main goal of this functional MRI (fMRI) study was to examine whether cognitive deficits in glioma patients prior to treatment are associated with abnormal brain activity in either the central executive network (CEN) or default mode network (DMN). Methods Forty-six glioma patients, and 23 group-matched healthy controls (HCs) participated in this fMRI experiment, performing an N-back task. Additionally, cognitive profiles of patients were evaluated outside the scanner. A region of interest–based analysis was used to compare brain activity in CEN and DMN between groups. Post hoc analyses were performed to evaluate differences between low-grade glioma (LGG) and high-grade glioma (HGG) patients. Results In-scanner performance was lower in glioma patients compared to HCs. Neuropsychological testing indicated cognitive impairment in LGG as well as HGG patients. fMRI results revealed normal CEN activation in glioma patients, whereas patients showed reduced DMN deactivation compared to HCs. Brain activity levels did not differ between LGG and HGG patients. Conclusions Our study suggests that cognitive deficits in glioma patients prior to treatment are associated with reduced responsiveness of the DMN, but not with abnormal CEN activation. These results suggest that cognitive deficits in glioma patients reflect a reduced capacity to achieve a brain state necessary for normal cognitive performance, rather than abnormal functioning of executive brain regions. Solely focusing on increases in brain activity may well be insufficient if we want to understand the underlying brain mechanism of cognitive impairments in patients, as our results indicate the importance of assessing deactivation.

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The neurophysiological architecture of semantic dementia: spectral dynamic causal modelling of a neurodegenerative proteinopathy

Scientific Reports ◽

10.1038/s41598-020-72847-1 ◽

2020 ◽

Vol 10 (1) ◽

Author(s):

Elia Benhamou ◽

Charles R. Marshall ◽

Lucy L. Russell ◽

Chris J. D. Hardy ◽

Rebecca L. Bond ◽

...

Keyword(s):

Network Architecture ◽

Large Scale ◽

Effective Connectivity ◽

Brain Regions ◽

Semantic Dementia ◽

Older Individuals ◽

World Knowledge ◽

Causal Modelling ◽

Dynamic Causal Modelling ◽

Semantic Impairment

Abstract The selective destruction of large-scale brain networks by pathogenic protein spread is a ubiquitous theme in neurodegenerative disease. Characterising the circuit architecture of these diseases could illuminate both their pathophysiology and the computational architecture of the cognitive processes they target. However, this is challenging using standard neuroimaging techniques. Here we addressed this issue using a novel technique—spectral dynamic causal modelling—that estimates the effective connectivity between brain regions from resting-state fMRI data. We studied patients with semantic dementia—the paradigmatic disorder of the brain system mediating world knowledge—relative to healthy older individuals. We assessed how the effective connectivity of the semantic appraisal network targeted by this disease was modulated by pathogenic protein deposition and by two key phenotypic factors, semantic impairment and behavioural disinhibition. The presence of pathogenic protein in SD weakened the normal inhibitory self-coupling of network hubs in both antero-mesial temporal lobes, with development of an abnormal excitatory fronto-temporal projection in the left cerebral hemisphere. Semantic impairment and social disinhibition were linked to a similar but more extensive profile of abnormally attenuated inhibitory self-coupling within temporal lobe regions and excitatory projections between temporal and inferior frontal regions. Our findings demonstrate that population-level dynamic causal modelling can disclose a core pathophysiological feature of proteinopathic network architecture—attenuation of inhibitory connectivity—and the key elements of distributed neuronal processing that underwrite semantic memory.

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