scholarly journals The modular organization of human anatomical brain networks: Accounting for the cost of wiring

2017 ◽  
Vol 1 (1) ◽  
pp. 42-68 ◽  
Author(s):  
Richard F. Betzel ◽  
John D. Medaglia ◽  
Lia Papadopoulos ◽  
Graham L. Baum ◽  
Ruben Gur ◽  
...  
Keyword(s):  
Cost Reduction ◽  
Brain Networks ◽  
Standard Technique ◽  
Detection Algorithm ◽  
Brain Regions ◽  
Modular Organization ◽  
Functional Roles ◽  
Detection Approach ◽  
Module Detection ◽  
Spatially Distributed

Brain networks are expected to be modular. However, existing techniques for estimating a network’s modules make it difficult to assess the influence of organizational principles such as wiring cost reduction on the detected modules. Here we present a modification of an existing module detection algorithm that allowed us to focus on connections that are unexpected under a cost-reduction wiring rule and to identify modules from among these connections. We applied this technique to anatomical brain networks and showed that the modules we detected differ from those detected using the standard technique. We demonstrated that these novel modules are spatially distributed, exhibit unique functional fingerprints, and overlap considerably with rich clubs, giving rise to an alternative and complementary interpretation of the functional roles of specific brain regions. Finally, we demonstrated that, using the modified module detection approach, we can detect modules in a developmental dataset that track normative patterns of maturation. Collectively, these findings support the hypothesis that brain networks are composed of modules and provide additional insight into the function of those modules.

scholarly journals Static and dynamic functional connectivity supports the configuration of brain networks associated with creative cognition

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Abhishek Uday Patil ◽  
Sejal Ghate ◽  
Deepa Madathil ◽  
Ovid J. L. Tzeng ◽  
Hsu-Wen Huang ◽  
...  
Keyword(s):  
Cognitive Processes ◽  
Large Scale ◽  
Brain Networks ◽  
Blood Oxygen Level Dependent ◽  
Detection Algorithm ◽  
Brain Regions ◽  
Creative Cognition ◽  
Network Flexibility ◽  
Community Detection Algorithm ◽  
Window Approach

AbstractCreative cognition is recognized to involve the integration of multiple spontaneous cognitive processes and is manifested as complex networks within and between the distributed brain regions. We propose that the processing of creative cognition involves the static and dynamic re-configuration of brain networks associated with complex cognitive processes. We applied the sliding-window approach followed by a community detection algorithm and novel measures of network flexibility on the blood-oxygen level dependent (BOLD) signal of 8 major functional brain networks to reveal static and dynamic alterations in the network reconfiguration during creative cognition using functional magnetic resonance imaging (fMRI). Our results demonstrate the temporal connectivity of the dynamic large-scale creative networks between default mode network (DMN), salience network, and cerebellar network during creative cognition, and advance our understanding of the network neuroscience of creative cognition.

scholarly journals A new era for executive function research: On the transition from centralized to distributed executive functioning

2020 ◽  
Author(s):  
Nicolas Zink ◽  
Sebastian Markett ◽  
Agatha Lenartowicz
Keyword(s):  
Brain Connectivity ◽  
Brain Networks ◽  
Brain Regions ◽  
Central Executive ◽  
Control Mechanisms ◽  
Control Functions ◽  
Wide Range ◽  
Spatially Distributed ◽  
Higher Cognitive Functions ◽  
The Brain

“Executive functions” (EFs) is an umbrella term for higher cognitive functions such as working memory, inhibition, and cognitive flexibility. These functions refer to dissociable mechanisms that are also intricately related, justifying the view of EF as a unitary mental faculty. One of the most challenging theoretical problems in this field of research has been to explain how the wide range of cognitive processes subsumed as EFs are controlled without an all-powerful but ill-defined central executive in the brain. Efforts to localize control mechanisms in circumscribed brain regions have not led to breakthrough in understanding how the brain controls and regulates itself, and no single brain system underlying a ‘central executive’ has yet been identified. We discuss how a distributed control network view can help to refine our understanding of the neurophysiological mechanisms underlying EFs. In this view, executive control functions are realized by spatially distributed brain networks, thus precluding the need for a modular central executive. We further discuss how graph-theory driven analysis of brain networks offers a unique lens on this problem by providing a reference frame to study brain connectivity in EFs in a holistic way and how neuroscience network research endeavors to investigate clinical neuropathology of disrupted EFs.

scholarly journals Gray-Matter Expansion of Social Brain Networks in Individuals High in Public Self-Consciousness

2021 ◽  
Vol 11 (3) ◽  
pp. 374
Author(s):  
Tomoyo Morita ◽  
Minoru Asada ◽  
Eiichi Naito
Keyword(s):  
Gray Matter ◽  
Structural Changes ◽  
Gray Matter Volume ◽  
Brain Networks ◽  
Japanese Version ◽  
Brain Regions ◽  
The Self ◽  
Social Brain ◽  
Default Mode ◽  
Public Self Consciousness

Self-consciousness is a personality trait associated with an individual’s concern regarding observable (public) and unobservable (private) aspects of self. Prompted by previous functional magnetic resonance imaging (MRI) studies, we examined possible gray-matter expansions in emotion-related and default mode networks in individuals with higher public or private self-consciousness. One hundred healthy young adults answered the Japanese version of the Self-Consciousness Scale (SCS) questionnaire and underwent structural MRI. A voxel-based morphometry analysis revealed that individuals scoring higher on the public SCS showed expansions of gray matter in the emotion-related regions of the cingulate and insular cortices and in the default mode network of the precuneus and medial prefrontal cortex. In addition, these gray-matter expansions were particularly related to the trait of “concern about being evaluated by others”, which was one of the subfactors constituting public self-consciousness. Conversely, no relationship was observed between gray-matter volume in any brain regions and the private SCS scores. This is the first study showing that the personal trait of concern regarding public aspects of the self may cause long-term substantial structural changes in social brain networks.

scholarly journals Incerto-thalamic modulation of fear via GABA and dopamine

2021 ◽  
Author(s):  
Archana Venkataraman ◽  
Sarah C. Hunter ◽  
Maria Dhinojwala ◽  
Diana Ghebrezadik ◽  
JiDong Guo ◽  
...  
Keyword(s):  
Brain Regions ◽  
Zona Incerta ◽  
Dependent Manner ◽  
Post Traumatic Stress ◽  
Functional Roles ◽  
Functional Connections ◽  
Optogenetic Stimulation ◽  
Fear Generalization ◽  
Stimulation Of

AbstractFear generalization and deficits in extinction learning are debilitating dimensions of Post-Traumatic Stress Disorder (PTSD). Most understanding of the neurobiology underlying these dimensions comes from studies of cortical and limbic brain regions. While thalamic and subthalamic regions have been implicated in modulating fear, the potential for incerto-thalamic pathways to suppress fear generalization and rescue deficits in extinction recall remains unexplored. We first used patch-clamp electrophysiology to examine functional connections between the subthalamic zona incerta and thalamic reuniens (RE). Optogenetic stimulation of GABAergic ZI → RE cell terminals in vitro induced inhibitory post-synaptic currents (IPSCs) in the RE. We then combined high-intensity discriminative auditory fear conditioning with cell-type-specific and projection-specific optogenetics in mice to assess functional roles of GABAergic ZI → RE cell projections in modulating fear generalization and extinction recall. In addition, we used a similar approach to test the possibility of fear generalization and extinction recall being modulated by a smaller subset of GABAergic ZI → RE cells, the A13 dopaminergic cell population. Optogenetic stimulation of GABAergic ZI → RE cell terminals attenuated fear generalization and enhanced extinction recall. In contrast, optogenetic stimulation of dopaminergic ZI → RE cell terminals had no effect on fear generalization but enhanced extinction recall in a dopamine receptor D1-dependent manner. Our findings shed new light on the neuroanatomy and neurochemistry of ZI-located cells that contribute to adaptive fear by increasing the precision and extinction of learned associations. In so doing, these data reveal novel neuroanatomical substrates that could be therapeutically targeted for treatment of PTSD.

scholarly journals The Modular Organization of Pain Brain Networks: An fMRI Graph Analysis Informed by Intracranial EEG

2020 ◽  
Vol 1 (1) ◽  
Author(s):  
Camille Fauchon ◽  
David Meunier ◽  
Isabelle Faillenot ◽  
Florence B Pomares ◽  
Hélène Bastuji ◽  
...  
Keyword(s):  
Information Integration ◽  
Functional Organization ◽  
Brain Connectivity ◽  
Brain Networks ◽  
Modular Organization ◽  
Noxious Heat ◽  
Intracranial Eeg ◽  
Brain Connectome ◽  
Posterior Parietal ◽  
The Brain

Abstract Intracranial EEG (iEEG) studies have suggested that the conscious perception of pain builds up from successive contributions of brain networks in less than 1 s. However, the functional organization of cortico-subcortical connections at the multisecond time scale, and its accordance with iEEG models, remains unknown. Here, we used graph theory with modular analysis of fMRI data from 60 healthy participants experiencing noxious heat stimuli, of whom 36 also received audio stimulation. Brain connectivity during pain was organized in four modules matching those identified through iEEG, namely: 1) sensorimotor (SM), 2) medial fronto-cingulo-parietal (default mode-like), 3) posterior parietal-latero-frontal (central executive-like), and 4) amygdalo-hippocampal (limbic). Intrinsic overlaps existed between the pain and audio conditions in high-order areas, but also pain-specific higher small-worldness and connectivity within the sensorimotor module. Neocortical modules were interrelated via “connector hubs” in dorsolateral frontal, posterior parietal, and anterior insular cortices, the antero-insular connector being most predominant during pain. These findings provide a mechanistic picture of the brain networks architecture and support fractal-like similarities between the micro-and macrotemporal dynamics associated with pain. The anterior insula appears to play an essential role in information integration, possibly by determining priorities for the processing of information and subsequent entrance into other points of the brain connectome.

scholarly journals On the structural connectivity of large-scale models of brain networks at cellular level

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Giuseppe Giacopelli ◽  
Domenico Tegolo ◽  
Emiliano Spera ◽  
Michele Migliore
Keyword(s):  
Large Scale ◽  
Brain Networks ◽  
Structural Connectivity ◽  
Network Models ◽  
Brain Regions ◽  
Cellular Level ◽  
Scale Model ◽  
Mathematical Framework ◽  
Underlying Mechanisms ◽  
Experimental Findings

AbstractThe brain’s structural connectivity plays a fundamental role in determining how neuron networks generate, process, and transfer information within and between brain regions. The underlying mechanisms are extremely difficult to study experimentally and, in many cases, large-scale model networks are of great help. However, the implementation of these models relies on experimental findings that are often sparse and limited. Their predicting power ultimately depends on how closely a model’s connectivity represents the real system. Here we argue that the data-driven probabilistic rules, widely used to build neuronal network models, may not be appropriate to represent the dynamics of the corresponding biological system. To solve this problem, we propose to use a new mathematical framework able to use sparse and limited experimental data to quantitatively reproduce the structural connectivity of biological brain networks at cellular level.

scholarly journals Reconfiguration of human evolving large-scale epileptic brain networks prior to seizures: an evaluation with node centralities

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Rieke Fruengel ◽  
Timo Bröhl ◽  
Thorsten Rings ◽  
Klaus Lehnertz
Keyword(s):  
Large Scale ◽  
Brain Networks ◽  
Brain Regions ◽  
Brain Network ◽  
Theoretical Concept ◽  
Global Network ◽  
Time Resolved ◽  
Functional Connections ◽  
Node Centrality ◽  
Network Mechanism

AbstractPrevious research has indicated that temporal changes of centrality of specific nodes in human evolving large-scale epileptic brain networks carry information predictive of impending seizures. Centrality is a fundamental network-theoretical concept that allows one to assess the role a node plays in a network. This concept allows for various interpretations, which is reflected in a number of centrality indices. Here we aim to achieve a more general understanding of local and global network reconfigurations during the pre-seizure period as indicated by changes of different node centrality indices. To this end, we investigate—in a time-resolved manner—evolving large-scale epileptic brain networks that we derived from multi-day, multi-electrode intracranial electroencephalograpic recordings from a large but inhomogeneous group of subjects with pharmacoresistant epilepsies with different anatomical origins. We estimate multiple centrality indices to assess the various roles the nodes play while the networks transit from the seizure-free to the pre-seizure period. Our findings allow us to formulate several major scenarios for the reconfiguration of an evolving epileptic brain network prior to seizures, which indicate that there is likely not a single network mechanism underlying seizure generation. Rather, local and global aspects of the pre-seizure network reconfiguration affect virtually all network constituents, from the various brain regions to the functional connections between them.

scholarly journals Species functional traits and abundance as drivers of multiplex ecological networks: first empirical quantification of inter-layer edge weights

2020 ◽  
Vol 287 (1939) ◽  
pp. 20202127
Author(s):  
S. Hervías-Parejo ◽  
C. Tur ◽  
R. Heleno ◽  
M. Nogales ◽  
S. Timóteo ◽  
...  
Keyword(s):  
Species Traits ◽  
Abundant Species ◽  
Modular Organization ◽  
Vertebrate Species ◽  
Multilayer Network ◽  
Functional Roles ◽  
Different Types ◽  
Seed Dispersers ◽  
Natural Communities

Many vertebrate species act as both plant pollinators and seed-dispersers, thus interconnecting these processes, particularly on islands. Ecological multilayer networks are a powerful tool to explore interdependencies between processes; however, quantifying the links between species engaging in different types of interactions (i.e. inter-layer edges) remains a great challenge. Here, we empirically measured inter-layer edge weights by quantifying the role of individually marked birds as both pollinators and seed-dispersers of Galápagos plant species over an entire year. Although most species (80%) engaged in both functions, we show that only a small proportion of individuals actually linked the two processes, highlighting the need to further consider intra-specific variability in individuals' functional roles. Furthermore, we found a high variation among species in linking both processes, i.e. some species contribute more than others to the modular organization of the multilayer network. Small and abundant species are particularly important for the cohesion of pollinator seed-dispersal networks, demonstrating the interplay between species traits and neutral processes structuring natural communities.

scholarly journals Psychological resilience correlates with EEG source-space brain network flexibility

2019 ◽  
Vol 3 (2) ◽  
pp. 539-550 ◽  
Author(s):  
Véronique Paban ◽  
Julien Modolo ◽  
Ahmad Mheich ◽  
Mahmoud Hassan
Keyword(s):  
Brain Networks ◽  
Brain Regions ◽  
Brain Network ◽  
Personality Testing ◽  
Functional Networks ◽  
Psychological Resilience ◽  
Full Spectrum ◽  
Sliding Windows ◽  
Resilience Scale ◽  
Network Flexibility

We aimed at identifying the potential relationship between the dynamical properties of the human functional network at rest and one of the most prominent traits of personality, namely resilience. To tackle this issue, we used resting-state EEG data recorded from 45 healthy subjects. Resilience was quantified using the 10-item Connor-Davidson Resilience Scale (CD-RISC). By using a sliding windows approach, brain networks in each EEG frequency band (delta, theta, alpha, and beta) were constructed using the EEG source-space connectivity method. Brain networks dynamics were evaluated using the network flexibility, linked with the tendency of a given node to change its modular affiliation over time. The results revealed a negative correlation between the psychological resilience and the brain network flexibility for a limited number of brain regions within the delta, alpha, and beta bands. This study provides evidence that network flexibility, a metric of dynamic functional networks, is strongly correlated with psychological resilience as assessed from personality testing. Beyond this proof-of-principle that reliable EEG-based quantities representative of personality traits can be identified, this motivates further investigation regarding the full spectrum of personality aspects and their relationship with functional networks.

scholarly journals Conditioned fear reactions are associated with gray matter density but not cortical microstructure

2020 ◽  
Author(s):  
Christoph Fraenz ◽  
Dorothea Metzen ◽  
Christian J. Merz ◽  
Helene Selpien ◽  
Nikolai Axmacher ◽  
...  
Keyword(s):  
Gray Matter ◽  
Conditioned Fear ◽  
Brain Networks ◽  
Brain Regions ◽  
Matter Density ◽  
Fear Learning ◽  
Future Research ◽  
Fear Reaction ◽  
Gray Matter Density ◽  
Diffusion Weighted Images

AbstractResearch has shown that fear acquisition, in reaction to potentially harmful stimuli or situations, is characterized by pronounced interindividual differences. It is likely that such differences are evoked by variability in the macro- and microstructural properties of brain regions involved in the processing of threat or safety signals from the environment. Indeed, previous studies have shown that the strength of conditioned fear reactions is associated with the cortical thickness or volume of various brain regions. However, respective studies were exclusively targeted at single brain regions instead of whole brain networks. Here, we tested 60 young and healthy individuals in a differential fear conditioning paradigm while they underwent fMRI scanning. In addition, we acquired T1-weighted and multi-shell diffusion-weighted images prior to testing. We used task-based fMRI data to define global brain networks which exhibited increased BOLD responses towards CS+ or CS- presentations, respectively. From these networks, we obtained mean values of gray matter density, neurite density, and neurite orientation dispersion. We found that mean gray matter density averaged across the CS+ network was significantly correlated with the strength of conditioned fear reactions quantified via skin conductance response. Measures of neurite architecture were not associated with conditioned fear reaction in any of the two networks. Our results extend previous findings on the relationship between brain morphometry and fear learning. Most importantly, our study is the first to introduce neurite imaging to fear learning research and discusses how its implementation can be improved in future research.

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