scholarly journals Task-related effective connectivity reveals that the cortical rich club gates cortex-wide communication

2017 ◽  
Author(s):  
Mario Senden ◽  
Niels Reuter ◽  
Martijn P. van den Heuvel ◽  
Rainer Goebel ◽  
Gustavo Deco ◽  
...  
Keyword(s):  
Information Exchange ◽  
Effective Connectivity ◽  
Functional Integration ◽  
Brain Regions ◽  
Rich Club ◽  
State Dependent ◽  
Gating Mechanism ◽  
The Rich ◽  
Cortical Regions ◽  
Peripheral Regions

AbstractHigher cognition may require the globally coordinated integration of specialized brain regions into functional networks. A collection of structural cortical hubs - referred to as the rich club - has been hypothesized to support task-specific functional integration. In the present paper, we use a whole-cortex model to estimate directed interactions between 68 cortical regions from fMRI activity for four different tasks (reflecting different cognitive domains) and resting state. We analyze the state-dependent input and output effective connectivity of the structural rich club and relate these to whole-cortex dynamics and network reconfigurations. We find that the cortical rich club exhibits an increase in outgoing effective connectivity during task performance as compared to rest while incoming connectivity remains constant. Increased outgoing connectivity targets a sparse set of peripheral regions with specific regions strongly overlapping between tasks. At the same time, community detection analyses reveal massive reorganizations of interactions among peripheral regions, including those serving as target of increased rich club output. This suggests that while peripheral regions may play a role in several tasks, their concrete interplay might nonetheless be task-specific. Furthermore, we observe that whole-cortex dynamics are faster during task as compared to rest. The decoupling effects usually accompanying faster dynamics appear to be counteracted by the increased rich club outgoing effective connectivity. Together our findings speak to a gating mechanism of the rich club that supports fast-paced information exchange among relevant peripheral regions in a task-specific and goal-directed fashion, while constantly listening to the whole network.

scholarly journals Dwelling quietly in the rich club: brain network determinants of slow cortical fluctuations

2015 ◽  
Vol 370 (1668) ◽  
pp. 20140165 ◽  
Author(s):  
Leonardo L. Gollo ◽  
Andrew Zalesky ◽  
R. Matthew Hutchison ◽  
Martijn van den Heuvel ◽  
Michael Breakspear
Keyword(s):  
Spatial Scales ◽  
Brain Regions ◽  
Brain Network ◽  
Morphological Properties ◽  
Brain Organization ◽  
Rich Club ◽  
Guiding Principle ◽  
The Rich ◽  
Cortical Regions ◽  
The Brain

For more than a century, cerebral cartography has been driven by investigations of structural and morphological properties of the brain across spatial scales and the temporal/functional phenomena that emerge from these underlying features. The next era of brain mapping will be driven by studies that consider both of these components of brain organization simultaneously—elucidating their interactions and dependencies. Using this guiding principle, we explored the origin of slowly fluctuating patterns of synchronization within the topological core of brain regions known as the rich club, implicated in the regulation of mood and introspection. We find that a constellation of densely interconnected regions that constitute the rich club (including the anterior insula, amygdala and precuneus) play a central role in promoting a stable, dynamical core of spontaneous activity in the primate cortex. The slow timescales are well matched to the regulation of internal visceral states, corresponding to the somatic correlates of mood and anxiety. In contrast, the topology of the surrounding ‘feeder’ cortical regions shows unstable, rapidly fluctuating dynamics likely to be crucial for fast perceptual processes. We discuss these findings in relation to psychiatric disorders and the future of connectomics.

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

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.

Perceptual Representations and the Vividness of Stimulus-Triggered and Stimulus-Independent Experiences

2020 ◽  
Vol 15 (5) ◽  
pp. 1200-1213 ◽  
Author(s):  
Peter Fazekas ◽  
Georgina Nemeth ◽  
Morten Overgaard
Keyword(s):  
Working Memory ◽  
Mental Imagery ◽  
Information Exchange ◽  
Activity Patterns ◽  
Mind Wandering ◽  
Brain Regions ◽  
Neural Basis ◽  
Fine Grained ◽  
Common Framework ◽  
Cortical Regions

In recent years, researchers from independent subfields have begun to engage with the idea that the same cortical regions that contribute to on-line perception are recruited during and underlie off-line activities such as information maintenance in working memory, mental imagery, hallucinations, dreaming, and mind wandering. Accumulating evidence suggests that in all of these cases the activity of posterior brain regions provides the contents of experiences. This article is intended to move one step further by exploring specific links between the vividness of experiences, which is a characteristic feature of consciousness regardless of its actual content, and certain properties of the content-specific neural-activity patterns. Investigating the mechanisms that underlie mental imagery and its relation to working memory and the processes responsible for mind wandering and its similarities to dreaming form two clusters of research that are in the forefront of the recent scientific study of mental phenomena, yet communication between these two clusters has been surprisingly sparse. Here our aim is to foster such information exchange by articulating a hypothesis about the fine-grained phenomenological structure determining subjective vividness and its possible neural basis that allows us to shed new light on these mental phenomena by bringing them under a common framework.

FC07-06 - Differences in the modulatory role of escitalopram and citalopram revealed by effective connectivity analysis

2011 ◽  
Vol 26 (S2) ◽  
pp. 1851-1851
Author(s):  
C. Windischberger ◽  
C. Kasess ◽  
R. Sladky ◽  
E. Moser ◽  
S. Kasper ◽  
...  
Keyword(s):  
Bayesian Model Averaging ◽  
Effective Connectivity ◽  
Functional Integration ◽  
Pharmacological Study ◽  
Model Averaging ◽  
Brain Regions ◽  
Antidepressant Effect ◽  
Racemic Mixture ◽  
Double Blind ◽  
Fmri Study

IntroductionCitalopram is a widely applied SSRI in patients suffering from affective disorder. It is a racemic mixture of the S- and R-enantiomer of citalopram, consisting of equal parts of S-citalopram and R-citalopram, respectively. It has been shown that the inhibitory potency in serotonin reuptake of S-citalopram is much higher compared to R-citalopram, and it is assumed that S-citalopram is the main carrier of the antidepressant effect.ObjectivesHere we investigated the effects of the two SSRIs Citalopram (50% S-, 50% R-citalopram) and Escitalopram (100% S-citalopram) on brain networks during emotion processing using pharmacological functional magnetic resonance imaging (fMRI) and dynamic causal modelling (DCM), an advanced tool to investigate functional integration between different brain regions.MethodsOur results are based on a placebo-controlled, randomized, double-blind, cross-over pharmacological study in 16 healthy subjects during three fMRI scanning sessions performing a facial emotional discrimination paradigm (Windischberger, Neuroimage, 2010). 32 models of pharmacological modulation within the amygdalar-parahippocampal-orbitofrontal network were analysed using Bayesian Model Averaging (BMA) as implemented in SPM8.ResultsS-citalopram showed statistically significant modulatory effects on forward amygdala-orbitofrontal and bidirectional amygdala-parahippocampal connections. No significant modulatory effects of R-citalopram were found.ConclusionsThis is the first fMRI study that showed stimulus-specific differential effects of the two enantiomeres R- and S-citalopram at the neural connectivity level. Our results corroborate studies in rats where escitalopram-induced increases in extracellular serotonin levels were found attenuated when R-citalopram was coinjected. Taken together this might explain the response differences between study drugs as demonstrated in previous clinical trials.

scholarly journals Network structural dependency in the human connectome across the life-span

2019 ◽  
Vol 3 (3) ◽  
pp. 792-806 ◽  
Author(s):  
Markus D. Schirmer ◽  
Ai Wern Chung ◽  
P. Ellen Grant ◽  
Natalia S. Rost
Keyword(s):  
Life Span ◽  
Age Groups ◽  
Model Fitting ◽  
Gaussian Mixture ◽  
Global Functioning ◽  
Rich Club ◽  
Network Measure ◽  
The Rich ◽  
Cortical Regions ◽  
Dependency Index

Principles of network topology have been widely studied in the human connectome. Of particular interest is the modularity of the human brain, where the connectome is divided into subnetworks from which changes with development, aging or disease can be investigated. We present a weighted network measure, the Network Dependency Index (NDI), to identify an individual region’s importance to the global functioning of the network. Importantly, we utilize NDI to differentiate four subnetworks (Tiers) in the human connectome following Gaussian mixture model fitting. We analyze the topological aspects of each subnetwork with respect to age and compare it to rich club-based subnetworks (rich club, feeder, and seeder). Our results first demonstrate the efficacy of NDI to identify more consistent, central nodes of the connectome across age groups, when compared with the rich club framework. Stratifying the connectome by NDI led to consistent subnetworks across the life-span, revealing distinct patterns associated with age where, for example, the key relay nuclei and cortical regions are contained in a subnetwork with highest NDI. The divisions of the human connectome derived from our data-driven NDI framework have the potential to reveal topological alterations described by network measures through the life-span.

scholarly journals Computation is concentrated in rich clubs of local cortical networks

2019 ◽  
Vol 3 (2) ◽  
pp. 384-404 ◽  
Author(s):  
Samantha P. Faber ◽  
Nicholas M. Timme ◽  
John M. Beggs ◽  
Ehren L. Newman
Keyword(s):  
Neural Circuits ◽  
Effective Connectivity ◽  
Neural Computation ◽  
Information Propagation ◽  
Cortical Circuits ◽  
Amount Of Information ◽  
Rich Club ◽  
The Rich ◽  
The Relationship ◽  
Do So

To understand how neural circuits process information, it is essential to identify the relationship between computation and circuit organization. Rich clubs, highly interconnected sets of neurons, are known to propagate a disproportionate amount of information within cortical circuits. Here, we test the hypothesis that rich clubs also perform a disproportionate amount of computation. To do so, we recorded the spiking activity of on average ∼300 well-isolated individual neurons from organotypic cortical cultures. We then constructed weighted, directed networks reflecting the effective connectivity between the neurons. For each neuron, we quantified the amount of computation it performed based on its inputs. We found that rich-club neurons compute ∼160% more information than neurons outside of the rich club. The amount of computation performed in the rich club was proportional to the amount of information propagation by the same neurons. This suggests that in these circuits, information propagation drives computation. In total, our findings indicate that rich-club organization in effective cortical circuits supports not only information propagation but also neural computation.

scholarly journals Effective connectivity inferred from fMRI transition dynamics during movie viewing points to a balanced reconfiguration of cortical interactions

2017 ◽  
Author(s):  
Matthieu Gilson ◽  
Gustavo Deco ◽  
Karl Friston ◽  
Patric Hagmann ◽  
Dante Mantini ◽  
...  
Keyword(s):  
Effective Connectivity ◽  
Functional Integration ◽  
Brain Regions ◽  
Connectivity Pattern ◽  
Model Parameters ◽  
Auditory Information ◽  
Brain Areas ◽  
Brain Hemispheres ◽  
Dynamic Coordination ◽  
The Brain

AbstractOur behavior entails a flexible and context-sensitive interplay between brain areas to integrate information according to goal-directed requirements. How-ever, the neural mechanisms governing the entrainment of functionally specialized brain areas remain poorly understood. In particular, the question arises whether observed changes in the regional activity for different cognitive conditions are explained by modifications of the inputs to the brain or its connectivity? We observe that transitions of fMRI activity between areas convey information about the tasks performed by 19 subjects, watching a movie versus a black screen (rest). We use a model-based framework that explains this spatiotemporal functional connectivity pattern by the local variability for 66 cortical regions and the network effective connectivity between them. We find that, among the estimated model parameters, movie viewing affects to a larger extent the local activity, which we interpret as extrinsic changes related to the increased stimulus load. However, detailed changes in the effective connectivity preserve a balance in the propagating activity and select specific pathways such that high-level brain regions integrate visual and auditory information, in particular boosting the communication between the two brain hemispheres. These findings speak to a dynamic coordination underlying the functional integration in the brain.

Hemisphere and Gender Differences in the Rich-Club Organization of Structural Networks

2019 ◽  
Vol 29 (11) ◽  
pp. 4889-4901 ◽  
Author(s):  
Bin Wang ◽  
Qionghui Zhan ◽  
Ting Yan ◽  
Sumaira Imtiaz ◽  
Jie Xiang ◽  
...  
Keyword(s):  
Gender Differences ◽  
Cognitive Control ◽  
Spatial Attention ◽  
Visual Processing ◽  
Gender Effects ◽  
Rich Club ◽  
The Rich ◽  
And Gender ◽  
Structural Networks ◽  
Peripheral Regions

AbstractStructural and functional differences in brain hemispheric asymmetry have been well documented between female and male adults. However, potential differences in the connectivity patterns of the rich-club organization of hemispheric structural networks in females and males remain to be determined. In this study, diffusion tensor imaging was used to construct hemispheric structural networks in healthy subjects, and graph theoretical analysis approaches were applied to quantify hemisphere and gender differences in rich-club organization. The results showed that rich-club organization was consistently observed in both hemispheres of female and male adults. Moreover, a reduced level of connectivity was found in the left hemisphere. Notably, rightward asymmetries were mainly observed in feeder and local connections among one hub region and peripheral regions, many of which are implicated in visual processing and spatial attention functions. Additionally, significant gender differences were revealed in the rich-club, feeder, and local connections in rich-club organization. These gender-related hub and peripheral regions are involved in emotional, sensory, and cognitive control functions. The topological changes in rich-club organization provide novel insight into the hemisphere and gender effects on white matter connections and underlie a potential network mechanism of hemisphere- and gender-based differences in visual processing, spatial attention and cognitive control.

scholarly journals Attractor dynamics gate cortical information flow during decision-making

2019 ◽  
Author(s):  
Arseny Finkelstein ◽  
Lorenzo Fontolan ◽  
Michael N. Economo ◽  
Nuo Li ◽  
Sandro Romani ◽  
...  
Keyword(s):  
Frontal Cortex ◽  
Information Flow ◽  
Sensory Information ◽  
Brain Regions ◽  
Optogenetic Stimulation ◽  
Course Of Action ◽  
State Dependent ◽  
Gating Mechanism ◽  
Attractor Dynamics ◽  
Evoked Activity

AbstractDecisions about future actions are held in memory until enacted, making them vulnerable to distractors. The neural mechanisms controlling decision robustness to distractors remain unknown. We trained mice to report optogenetic stimulation of somatosensory cortex, with a delay separating sensation and action. Distracting stimuli influenced behavior less when delivered later during delay – demonstrating temporal gating of sensory information flow. Gating occurred even though distractor-evoked activity percolated through the cortex without attenuation. Instead, choice-related dynamics in frontal cortex became progressively robust to distractors as time passed. Reverse-engineering of neural networks trained to reproduce frontal-cortex activity revealed that chosen actions were stabilized via attractor dynamics, which gated out distracting stimuli. Our results reveal a dynamic gating mechanism that operates by controlling the degree of commitment to a chosen course of action.One Sentence SummaryMechanisms controlling state-dependent communication between brain regions allow for robust action-selection.

scholarly journals Computation is concentrated in rich clubs of local cortical neurons

2018 ◽  
Author(s):  
Samantha P. Faber ◽  
Nicholas M. Timme ◽  
John M. Beggs ◽  
Ehren L. Newman
Keyword(s):  
Cortical Neurons ◽  
Effective Connectivity ◽  
Neural Computation ◽  
Information Propagation ◽  
Cortical Circuits ◽  
Amount Of Information ◽  
Rich Club ◽  
The Rich ◽  
Do So ◽  
Spiking Activity

ABSTRACTTo understand how neural circuits process information, it is essential to identify the relationship between computation and circuit topology. Rich-clubs, highly interconnected sets of neurons, are known to propagate a disproportionate amount of information within cortical circuits. Here, we test the hypothesis that rich-clubs also perform a disproportionate amount of computation. To do so, we recorded the spiking activity of on average ∼300 well-isolated individual neurons from organotypic cortical cultures. We then constructed weighted, directed networks reflecting the effective connectivity between the neurons. For each neuron, we quantified the amount of computation it performed based on its inputs. We found that rich-club neurons compute ∼200% more information than neurons outside of the rich club. Indeed, the amount of computation performed in the rich-club was proportional to the amount information propagation by the same neurons. This suggests that, in these circuits, information propagation drives computation. Comparing the computation-to-propagation ratio inside versus outside of the rich club showed that rich clubs compute at a slightly, though significantly, reduced level (∼4% lower). In total, our findings indicate that rich club topology in effective cortical circuits supports not only information propagation but also neural computation.AUTHOR SUMMARYHere we answer the question of whether rich club topology in functional cortical circuits supports neural computation as it has been previously shown to do for information propagation. To do so, we combined network analysis with information theoretic tools to analyze the spiking activity of hundreds of neurons recorded from organotypic cultures of mouse somatosensory cortex. We found that neurons in rich clubs computed significantly more than neurons outside of rich clubs, suggesting that rich-clubs do support computation in cortical circuits. Indeed, the amount of computation that we found in the rich club was proportional to the amount of information they propagate suggesting that, in these circuits, information propagation drives computation.

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