scholarly journals Group and Individual Level Variations between Symmetric and Asymmetric DLPFC Montages for tDCS over Large Scale Brain Network Nodes

2020 ◽  
Author(s):  
Ghazaleh Soleimani ◽  
Mehrdad Saviz ◽  
Marom Bikson ◽  
Farzad Towhidkhah ◽  
Rayus Kuplicki ◽  
...  
Keyword(s):  
Large Scale ◽  
Current Flow ◽  
Brain Network ◽  
Brain Anatomy ◽  
Global Networks ◽  
Individual Level ◽  
Dorsolateral Prefrontal ◽  
Two Factors ◽  
Large Scale Networks ◽  
Flow Stimulation

AbstractTwo challenges to optimizing transcranial direct current stimulation (tDCS) are selecting between, often similar, electrode montages and accounting for inter-individual differences in response. These two factors are related by how tDCS montage determines current flow through the brain considered across or within individuals. MRI-based computational head models (CHMs) predict how brain anatomy determine electric field (EF) patterns for a given tDCS montage. Because conventional tDCS produces diffuse brain current flow, stimulation outcomes may be understood as modulation of global networks. Therefore, we developed network-led, rather than region-led, approach. We specifically considered two common frontal tDCS montages that nominally target the dorsolateral prefrontal cortex; asymmetric unilateral (anode/cathode: F4/Fp1) and symmetric bilateral (F4/F3) electrode montages. CHMs of 66 participants were constructed. We showed that cathode location significantly affects EFs in the limbic network. Furthermore, using a finer parcellation of large-scale networks, we found significant differences in some of main nodes within a network, even if there is no difference at the network level. This study generally demonstrates a methodology for considering the components of large-scale networks in CHMs instead of targeting a single region and specifically provides insight into how symmetric vs asymmetric frontal tDCS may differentially modulate networks across a population.

scholarly journals Group and individual level variations between symmetric and asymmetric DLPFC montages for tDCS over large scale brain network nodes

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Ghazaleh Soleimani ◽  
Mehrdad Saviz ◽  
Marom Bikson ◽  
Farzad Towhidkhah ◽  
Rayus Kuplicki ◽  
...  
Keyword(s):  
Large Scale ◽  
Current Flow ◽  
Brain Network ◽  
Brain Anatomy ◽  
Global Networks ◽  
Individual Level ◽  
Dorsolateral Prefrontal ◽  
Two Factors ◽  
Large Scale Networks ◽  
Flow Stimulation

AbstractTwo challenges to optimizing transcranial direct current stimulation (tDCS) are selecting between, often similar, electrode montages and accounting for inter-individual differences in response. These two factors are related by how tDCS montage determines current flow through the brain considered across or within individuals. MRI-based computational head models (CHMs) predict how brain anatomy determines electric field (EF) patterns for a given tDCS montage. Because conventional tDCS produces diffuse brain current flow, stimulation outcomes may be understood as modulation of global networks. Therefore, we developed a network-led, rather than region-led, approach. We specifically considered two common “frontal” tDCS montages that nominally target the dorsolateral prefrontal cortex; asymmetric “unilateral” (anode/cathode: F4/Fp1) and symmetric “bilateral” (F4/F3) electrode montages. CHMs of 66 participants were constructed. We showed that cathode location significantly affects EFs in the limbic network. Furthermore, using a finer parcellation of large-scale networks, we found significant differences in some of the main nodes within a network, even if there is no difference at the network level. This study generally demonstrates a methodology for considering the components of large-scale networks in CHMs instead of targeting a single region and specifically provides insight into how symmetric vs asymmetric frontal tDCS may differentially modulate networks across a population.

How small can the epileptogenic region be?

Neurology ◽  
2017 ◽  
Vol 88 (21) ◽  
pp. 2017-2019 ◽  
Author(s):  
Graeme D. Jackson ◽  
Mangor Pedersen ◽  
A. Simon Harvey
Keyword(s):  
Large Scale ◽  
Intractable Epilepsy ◽  
Brain Network ◽  
Local Connectivity ◽  
Whole Brain ◽  
Network Characteristics ◽  
Small Areas ◽  
Language Deficit ◽  
Large Scale Networks ◽  
Combine Information

Objective:To present a case that demonstrates that seizures and interictal disturbances can be driven by a small area of functionally abnormal cortex.Methods:Two novel functional MRI network analysis methods were used to supplement conventional seizure and lesion localization methods: (1) regional homogeneity to quantify local connectivity, or synchrony, with a resolution of less than 1 cm3 of cortex; and (2) small-worldness to combine information about whole brain network segregation and integration.Results:After a small corticectomy in the dominant supramarginal gyrus (13 × 7 × 6 mm) limited to the area of abnormal local connectivity, and smaller than the PET and SPECT abnormalities, the patient has been seizure-free for 3 years with no language deficit. Whole brain network characteristics normalized (small-worldness) to that of healthy controls.Conclusions:This case demonstrates that small areas of cortex may be highly epileptogenic, drive intractable epilepsy, and disrupt large-scale networks likely to be involved in core cognitive functions.

scholarly journals Brain network dynamics are hierarchically organized in time

2017 ◽  
Vol 114 (48) ◽  
pp. 12827-12832 ◽  
Author(s):  
Diego Vidaurre ◽  
Stephen M. Smith ◽  
Mark W. Woolrich
Keyword(s):  
Large Scale ◽  
Temporal Dynamics ◽  
Brain Network ◽  
Specific Measure ◽  
Brain Areas ◽  
Neuronal Populations ◽  
Subject Specific ◽  
Large Scale Networks ◽  
Network Patterns ◽  
The Brain

The brain recruits neuronal populations in a temporally coordinated manner in task and at rest. However, the extent to which large-scale networks exhibit their own organized temporal dynamics is unclear. We use an approach designed to find repeating network patterns in whole-brain resting fMRI data, where networks are defined as graphs of interacting brain areas. We find that the transitions between networks are nonrandom, with certain networks more likely to occur after others. Further, this nonrandom sequencing is itself hierarchically organized, revealing two distinct sets of networks, or metastates, that the brain has a tendency to cycle within. One metastate is associated with sensory and motor regions, and the other involves areas related to higher order cognition. Moreover, we find that the proportion of time that a subject spends in each brain network and metastate is a consistent subject-specific measure, is heritable, and shows a significant relationship with cognitive traits.

scholarly journals Brain network topology and personality traits: a source level magnetoencephalographic study

2021 ◽  
Author(s):  
Emahnuel Troisi Lopez ◽  
Valentina Colonnello ◽  
Marianna Liparoti ◽  
Mauro Castaldi ◽  
Paolo Maria Russo ◽  
...  
Keyword(s):  
Individual Differences ◽  
Personality Traits ◽  
Caudate Nucleus ◽  
Large Scale ◽  
Brain Network ◽  
Neural Communication ◽  
Character Inventory ◽  
Left Caudate ◽  
Source Level ◽  
Large Scale Networks

Abstract Personality neuroscience is focusing on the correlation between individual differences and the efficiency of large-scale networks from the perspective of the brain as an interconnected network. A suitable technique to explore this relationship is the magnetoencephalography (MEG), but little are MEG studies aimed at investigating topological properties correlated to personality traits. By using MEG, the present study is aimed at evaluating how individual differences described in Cloninger’s psychobiological model are correlated with specific cerebral structures. Fifty healthy individuals (20 males, 30 females, mean age: 27.4 ± 4.8 years) underwent Temperament and Character Inventory examination and MEG recording during a resting state condition. High harm avoidance scores were associated with a reduced centrality of the left caudate nucleus and this negative correlation was maintained in females when we analyzed gender differences. Our data suggest that the caudate nucleus plays a key role in adaptive behavior and could be a critical node in insular salience network. The clear difference between males and females allows us to suggest that topological organization correlated to personality is highly dependent on gender. Our findings provide new insights to evaluate the mutual influences of topological and functional connectivity in neural communication efficiency and disruption as biomarkers of psychopathological traits.

scholarly journals Post-Stroke Cognitive Impairment: Pathophysiological Insights into Brain Disconnectome from Advanced Neuroimaging Analysis Techniques

2021 ◽  
Vol 23 (3) ◽  
pp. 297-311
Author(s):  
Jae-Sung Lim ◽  
Jae-Joong Lee ◽  
Choong-Wan Woo
Keyword(s):  
Cognitive Impairment ◽  
Large Scale ◽  
Imaging Techniques ◽  
Brain Network ◽  
Clinical Neurology ◽  
Post Stroke ◽  
Large Scale Networks ◽  
High Level ◽  
New Treatments ◽  
The Brain

The neurological symptoms of stroke have traditionally provided the foundation for functional mapping of the brain. However, there are many unresolved aspects in our understanding of cerebral activity, especially regarding high-level cognitive functions. This review provides a comprehensive look at the pathophysiology of post-stroke cognitive impairment in light of recent findings from advanced imaging techniques. Combining network neuroscience and clinical neurology, our research focuses on how changes in brain networks correlate with post-stroke cognitive prognosis. More specifically, we first discuss the general consequences of stroke lesions due to damage of canonical resting-state large-scale networks or changes in the composition of the entire brain. We also review emerging methods, such as lesion-network mapping and gradient analysis, used to study the aforementioned events caused by stroke lesions. Lastly, we examine other patient vulnerabilities, such as superimposed amyloid pathology and blood-brain barrier leakage, which potentially lead to different outcomes for the brain network compositions even in the presence of similar stroke lesions. This knowledge will allow a better understanding of the pathophysiology of post-stroke cognitive impairment and provide a theoretical basis for the development of new treatments, such as neuromodulation.

scholarly journals Shared and unique brain network features predict cognition, personality and mental health in childhood

2020 ◽  
Author(s):  
Jianzhong Chen ◽  
Angela Tam ◽  
Valeria Kebets ◽  
Csaba Orban ◽  
Leon Qi Rong Ooi ◽  
...  
Keyword(s):  
Mental Health ◽  
Individual Differences ◽  
Large Scale ◽  
Population Level ◽  
Brain Network ◽  
Behavioral Variability ◽  
Network Organization ◽  
Individual Level ◽  
And Task ◽  
Behavioral Domains

AbstractThe manner through which individual differences in brain network organization track population-level behavioral variability is a fundamental question in systems neuroscience. Recent work suggests that resting-state and task-state functional connectivity can predict specific traits at the individual level. However, the focus of most studies on single behavioral traits has come at the expense of capturing broader relationships across behaviors. Here, we utilized a large-scale dataset of 1858 typically developing children to estimate whole-brain functional network organization that is predictive of individual differences in cognition, impulsivity-related personality, and mental health during rest and task states. Predictive network features were distinct across the broad behavioral domains: cognition, personality and mental health. On the other hand, traits within each behavioral domain were predicted by highly similar network features. This is surprising given decades of research emphasizing that distinct brain networks support different mental processes. Although tasks are known to modulate the functional connectome, we found that predictive network features were similar between resting and task states. Overall, our findings reveal shared brain network features that account for individual variation within broad domains of behavior in childhood, yet are unique to different behavioral domains.

scholarly journals Genetic and neuroanatomical support for functional brain network dynamics in epilepsy

2018 ◽  
Author(s):  
Pranav G. Reddy ◽  
Richard F. Betzel ◽  
Ankit N. Khambhati ◽  
Preya Shah ◽  
Lohith Kini ◽  
...  
Keyword(s):  
White Matter ◽  
Large Scale ◽  
Focal Epilepsy ◽  
Network Dynamics ◽  
Brain Network ◽  
Brain Anatomy ◽  
Functional Brain ◽  
Genetic Constraints ◽  
Number Of Patients ◽  
Functional Brain Network

AbstractFocal epilepsy is a devastating neurological disorder that affects an overwhelming number of patients world-wide, many of whom prove resistant to medication. The efficacy of current innovative technologies for the treatment of these patients has been stalled by the lack of accurate and effective methods to fuse multimodal neuroimaging data to map anatomical targets driving seizure dynamics. Here we propose a parsimonious model that explains how large-scale anatomical networks and shared genetic constraints shape inter-regional communication in focal epilepsy. In extensive ECoG recordings acquired from a group of patients with medically refractory focal-onset epilepsy, we find that ictal and preictal functional brain network dynamics can be accurately predicted from features of brain anatomy and geometry, patterns of white matter connectivity, and constraints complicit in patterns of gene coexpression, all of which are conserved across healthy adult populations. Moreover, we uncover evidence that markers of non-conserved architecture, potentially driven by idiosyncratic pathology of single subjects, are most prevalent in high frequency ictal dynamics and low frequency preictal dynamics. Finally, we find that ictal dynamics are better predicted by white matter features and more poorly predicted by geometry and genetic constraints than preictal dynamics, suggesting that the functional brain network dynamics manifest in seizures rely on – and may directly propagate along – underlying white matter structure that is largely conserved across humans. Broadly, our work offers insights into the generic architectural principles of the human brain that impact seizure dynamics, and could be extended to further our understanding, models, and predictions of subject-level pathology and response to intervention.

scholarly journals A Brain Centred View of Psychiatric Comorbidity in Tinnitus: From Otology to Hodology

2014 ◽  
Vol 2014 ◽  
pp. 1-15 ◽  
Author(s):  
Massimo Salviati ◽  
Francesco Saverio Bersani ◽  
Giuseppe Valeriani ◽  
Amedeo Minichino ◽  
Roberta Panico ◽  
...  
Keyword(s):  
Psychiatric Disorders ◽  
Large Scale ◽  
Brain Plasticity ◽  
Current Knowledge ◽  
Relevant Literature ◽  
Brain Network ◽  
Emergent Properties ◽  
Search Terms ◽  
Dorsolateral Prefrontal ◽  
Pubmed Search

Introduction. Comorbid psychiatric disorders are frequent among patients affected by tinnitus. There are mutual clinical influences between tinnitus and psychiatric disorders, as well as neurobiological relations based on partially overlapping hodological and neuroplastic phenomena. The aim of the present paper is to review the evidence of alterations in brain networks underlying tinnitus physiopathology and to discuss them in light of the current knowledge of the neurobiology of psychiatric disorders.Methods. Relevant literature was identified through a search on Medline and PubMed; search terms included tinnitus, brain, plasticity, cortex, network, and pathways.Results. Tinnitus phenomenon results from systemic-neurootological triggers followed by neuronal remapping within several auditory and nonauditory pathways. Plastic reorganization and white matter alterations within limbic system, arcuate fasciculus, insula, salience network, dorsolateral prefrontal cortex, auditory pathways, ffrontocortical, and thalamocortical networks are discussed.Discussion. Several overlapping brain network alterations do exist between tinnitus and psychiatric disorders. Tinnitus, initially related to a clinicoanatomical approach based on a cortical localizationism, could be better explained by an holistic or associationist approach considering psychic functions and tinnitus as emergent properties of partially overlapping large-scale neural networks.

scholarly journals The causal role of α-oscillations in feature binding

2019 ◽  
Vol 116 (34) ◽  
pp. 17023-17028 ◽  
Author(s):  
Yanyu Zhang ◽  
Yifei Zhang ◽  
Peng Cai ◽  
Huan Luo ◽  
Fang Fang
Keyword(s):  
Large Scale ◽  
Brain Network ◽  
Feature Binding ◽  
Causal Role ◽  
Human Cognition ◽  
Neural Oscillations ◽  
Switch Rate ◽  
Transcranial Alternating Current Stimulation ◽  
Large Scale Networks

The binding problem—how to integrate features into objects—poses a fundamental challenge for the brain. Neural oscillations, especially γ-oscillations, have been proposed as a potential mechanism to solve this problem. However, since γ-oscillations usually reflect local neural activity, how to implement feature binding involving a large-scale brain network remains largely unknown. Here, combining electroencephalogram (EEG) and transcranial alternating current stimulation (tACS), we employed a bistable color-motion binding stimulus to probe the role of neural oscillations in feature binding. Subjects’ perception of the stimulus switched between its physical binding and its illusory (active) binding. The active binding has been shown to involve a large-scale network consisting of spatially distant brain areas. α-Oscillations presumably reflect the dynamics of such large-scale networks, especially due to volume conduction effects in EEG. We found that, relative to the physical binding, the α-power decreased during the active binding. Additionally, individual α-power was negatively correlated with the time proportion of the active binding. Subjects’ perceptual switch rate between the 2 bindings was positively correlated with their individual α-frequency. Furthermore, applying tACS at individual α-frequency decreased the time proportion of the active binding. Moreover, delivering tACS at different temporal frequencies in the α-band changed subjects’ perceptual switch rate through affecting the active binding process. Our findings provide converging evidence for the causal role of α-oscillations in feature binding, especially in active feature binding, thereby uncovering a function of α-oscillations in human cognition.

scholarly journals Resting state cerebral networks in mouse lemur primates: from multilevel validation to comparison with humans

2019 ◽  
Author(s):  
Clément M. Garin ◽  
Nachiket A. Nadkarni ◽  
Brigitte Landeau ◽  
Gaël Chételat ◽  
Jean-Luc Picq ◽  
...  
Keyword(s):  
Resting State ◽  
Large Scale ◽  
Brain Network ◽  
Mouse Lemur ◽  
Mr Images ◽  
Resting State Functional Connectivity ◽  
Functional Regions ◽  
Mouse Lemurs ◽  
Large Scale Networks ◽  
First Time

AbstractMeasures of resting-state functional connectivity allow the description of neuronal networks in humans and provide a window on brain function in normal and pathological conditions. Animal models are critical to further address experimentally the function of brain networks and their roles in pathologies. Here we describe for the first time brain network organization in the mouse lemur (Microcebus murinus), a small primate attracting increased attention as a model for neuroscience. Resting-state functional MR images were recorded at 11.7 Tesla. Forty-eight functional regions were identified and used to identify networks using graph theory, dictionary learning and seed-based analyses. Comparison of results issued from these three complementary methods allowed the description of the most robust networks from mouse lemurs. Large scale networks were then identified from resting-state functional MR images of humans using the same method as for lemurs. Strong homologies were outlined between cerebral networks in mouse lemurs and humans.

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