scholarly journals Dynamic reorganization of brain functional networks during cognition

2014 ◽  
Author(s):  
Michał Bola ◽  
Bernhard Sabel

How cognition emerges from neural dynamics? The dominant hypothesis states that interactions among distributed brain regions through phase synchronization give basis for cognitive processing. Such phase-synchronized networks are transient and dynamic, established on the timescale of milliseconds in order to perform specific cognitive operations. But unlike resting-state networks, the complex organization of transient cognitive networks is typically not characterized within the graph theory framework. Thus, it is not known whether cognitive processing merely changes strength of functional connections or, conversely, requires qualitatively new topological arrangements of functional networks. To address this question, we recorded high-density EEG when subjects performed a visual discrimination task and conducted and event-related network analysis (ERNA) where source-space weighted functional networks were characterized with graph measures. We revealed rapid, transient, and frequency-specific reorganization of the network?s topology during cognition. Specifically, cognitive networks were characterized by strong clustering, low modularity, and strong interactions between hub-nodes. Our findings suggest that dense and clustered connectivity between the hub nodes belonging to different modules is the ?network fingerprint? of cognition. Such reorganization patterns might facilitate global integration of information and provide a substrate for a ?global workspace? necessary for cognition and consciousness to occur. Thus, characterizing topology of the event-related networks opens new vistas to interpret cognitive dynamics in the broader conceptual framework of graph theory.


2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Yin Tian ◽  
Huishu Zhou ◽  
Huiling Zhang ◽  
Tianhao Li

Previous studies have shown that different frequency band oscillations are associated with cognitive processing such as working memory (WM). Electroencephalogram (EEG) coherence and graph theory can be used to measure functional connections between different brain regions and information interaction between different clusters of neurons. At the same time, it was found that better cognitive performance of individuals indicated stronger small-world characteristics of resting-state WM networks. However, little is known about the neural synchronization of the retention stage during ongoing WM tasks (i.e., online WM) by training on the whole-brain network level. Therefore, combining EEG coherence and graph theory analysis, the present study examined the topological changes of WM networks before and after training based on the whole brain and constructed differential networks with different frequency band oscillations (i.e., theta, alpha, and beta). The results showed that after WM training, the subjects’ WM networks had higher clustering coefficients and shorter optimal path lengths than before training during the retention period. Moreover, the increased synchronization of the frontal theta oscillations seemed to reflect the improved executive ability of WM and the more mature resource deployment; the enhanced alpha oscillatory synchronization in the frontoparietal and fronto-occipital regions may reflect the enhanced ability to suppress irrelevant information during the delay and pay attention to memory guidance; the enhanced beta oscillatory synchronization in the temporoparietal and frontoparietal regions may indicate active memory maintenance and preparation for memory-guided attention. The findings may add new evidence to understand the neural mechanisms of WM on the changes of network topological attributes in the task-related mode.



2021 ◽  
Author(s):  
N. Williams ◽  
S. H. Wang ◽  
G. Arnulfo ◽  
L. Nobili ◽  
S. Palva ◽  
...  

Modules in brain connectomes are essential to balancing the functional segregation and integration crucial to brain operation. Connectomes are the set of structural or functional connections between each pair of brain regions. Non-invasive methodologies, Electroencephalography (EEG) and Magnetoencephalography (MEG), have been used to identify modules in connectomes of phase-synchronization, but have been compromised by spurious phase-synchronization due to EEG volume conduction or MEG field spread. In this study, we used invasive, intracerebral recordings with stereo-electroencephalography (SEEG, N = 67), to identify modules in connectomes of phase-synchronization. To do this, we used submillimetre localization of SEEG contacts and closest-white-matter referencing, to generate group-level connectomes of phase-synchronization minimally affected by volume conduction. Then, we employed community detection methods together with a novel consensus clustering approach, to identify modules in connectomes of phase-synchronization. The connectomes of phase-synchronization possessed significant modular organization at multiple spatial scales, from 3-320 Hz. These identified modules were highly similar within neurophysiologically meaningful frequency bands. Modules up to the high-gamma frequency band comprised only anatomically contiguous regions, unlike modules identified with functional Magnetic Resonance Imaging (fMRI). Strikingly, the identified modules comprised cortical regions involved in shared repertoires of cognitive functions including vision, language and attention. These results demonstrate the viability of combining SEEG with advanced methods, to identify modules in connectomes of phase-synchronization. The modules correspond to brain systems with specific functional roles in perceptual, cognitive, and motor processing.



2017 ◽  
Author(s):  
Jie Lisa Ji ◽  
Marjolein Spronk ◽  
Kaustubh Kulkarni ◽  
Grega Repovs ◽  
Alan Anticevic ◽  
...  

Understanding complex systems such as the human brain requires characterization of the system's architecture across multiple levels of organization - from neurons, to local circuits, to brain regions, and ultimately large-scale brain networks. Here we focus on characterizing the human brain's large-scale network organization, as it provides an overall framework for the organization of all other levels. We developed a highly principled approach to identify cortical network communities at the level of functional systems, calibrating our community detection algorithm using extremely well-established sensory and motor systems as guides. Building on previous network partitions, we replicated and expanded upon well-known and recently-identified networks, including several higher-order cognitive networks such as a left-lateralized language network. We expanded these cortical networks to subcortex, revealing 358 highly-organized subcortical parcels that take part in forming whole-brain functional networks. Notably, the identified subcortical parcels are similar in number to a recent estimate of the number of cortical parcels (360). This whole-brain network atlas - released as an open resource for the neuroscience community - places all brain structures across both cortex and subcortex into a single large-scale functional framework, with the potential to facilitate a variety of studies investigating large-scale functional networks in health and disease.



2016 ◽  
Author(s):  
Josephine Cruzat ◽  
Gustavo Deco ◽  
Adrià Tauste ◽  
Alessandro Principe ◽  
Albert Costa ◽  
...  

AbstractCognitive processing requires the ability to flexibly integrate and process information across large brain networks. More information is needed on how brain networks dynamically reorganize to allow such broad communication across many different brain regions in order to integrate the necessary information. Here, we use intracranial EEG to record neural activity from 12 epileptic patients while they perform three cognitive tasks in order to study how the functional connectivity changes to facilitate communication across the underlying network spanning many different brain regions. At the topological level, this facilitation is characterized by measures of integration and segregation. Across all patients, we found significant increases in integration and decreases in segregation during cognitive processing, especially in the gamma band (50-90 Hz). Accordingly, we also found significantly higher level of global synchronization and functional connectivity during the execution of the cognitive task, again particularly in the gamma band. More importantly, we demonstrate here for the first time that the modulations at the level of functional connectivity facilitating communication across the network were not caused by changes in the level of the underlying oscillations but caused by a rearrangement of the mutual synchronisation between the different nodes as proposed by the “Communication Through Coherence” Theory.



Author(s):  
Archana Venkataraman ◽  
Sarah C. Hunter ◽  
Maria Dhinojwala ◽  
Diana Ghebrezadik ◽  
JiDong Guo ◽  
...  

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.



2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Rieke Fruengel ◽  
Timo Bröhl ◽  
Thorsten Rings ◽  
Klaus Lehnertz

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.





2015 ◽  
Vol 21 (3) ◽  
pp. 203-213 ◽  
Author(s):  
Jonathan C. Ipser ◽  
Gregory G. Brown ◽  
Amanda Bischoff-Grethe ◽  
Colm G. Connolly ◽  
Ronald J. Ellis ◽  
...  

AbstractHIV-associated cognitive impairments are prevalent, and are consistent with injury to both frontal cortical and subcortical regions of the brain. The current study aimed to assess the association of HIV infection with functional connections within the frontostriatal network, circuitry hypothesized to be highly vulnerable to HIV infection. Fifteen HIV-positive and 15 demographically matched control participants underwent 6 min of resting-state functional magnetic resonance imaging (RS-fMRI). Multivariate group comparisons of age-adjusted estimates of connectivity within the frontostriatal network were derived from BOLD data for dorsolateral prefrontal cortex (DLPFC), dorsal caudate and mediodorsal thalamic regions of interest. Whole-brain comparisons of group differences in frontostriatal connectivity were conducted, as were pairwise tests of connectivity associations with measures of global cognitive functioning and clinical and immunological characteristics (nadir and current CD4 count, duration of HIV infection, plasma HIV RNA). HIV – associated reductions in connectivity were observed between the DLPFC and the dorsal caudate, particularly in younger participants (<50 years, N=9). Seropositive participants also demonstrated reductions in dorsal caudate connectivity to frontal and parietal brain regions previously demonstrated to be functionally connected to the DLPFC. Cognitive impairment, but none of the assessed clinical/immunological variables, was also associated with reduced frontostriatal connectivity. In conclusion, our data indicate that HIV is associated with attenuated intrinsic frontostriatal connectivity. Intrinsic connectivity of this network may therefore serve as a marker of the deleterious effects of HIV infection on the brain, possibly via HIV-associated dopaminergic abnormalities. These findings warrant independent replication in larger studies. (JINS, 2015, 21, 1–11)



2019 ◽  
Vol 3 (2) ◽  
pp. 539-550 ◽  
Author(s):  
Véronique Paban ◽  
Julien Modolo ◽  
Ahmad Mheich ◽  
Mahmoud Hassan

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.



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