Network neuroscience and the connectomics revolution

Network science provides theoretical, computational, and empirical tools that can be used to understand the structure and function of the human brain in novel ways using simple concepts and mathematical representations. Network neuroscience is a rapidly growing field that is providing considerable insight into human structural connectivity, functional connectivity while at rest, changes in functional networks over time (dynamics), and how these properties differ in clinical populations. In addition, a number of studies have begun to quantify network characteristics in a variety of cognitive processes and provide a context for understanding cognition from a network perspective. In this review, we outline the contributions of network science to cognitive neuroscience. We describe the methodology of network science as applied to the particular case of neuroimaging data and review its uses in investigating a range of cognitive functions including sensory processing, language, emotion, attention, cognitive control, learning, and memory. In conclusion, we discuss current frontiers and the specific challenges that must be overcome to integrate these complementary disciplines of network science and cognitive neuroscience. Increased communication between cognitive neuroscientists and network scientists could lead to significant discoveries under an emerging scientific intersection known as cognitive network neuroscience.

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From static to temporal network theory: Applications to functional brain connectivity

Network Neuroscience ◽

10.1162/netn_a_00011 ◽

2017 ◽

Vol 1 (2) ◽

pp. 69-99 ◽

Cited By ~ 28

Author(s):

William Hedley Thompson ◽

Per Brantefors ◽

Peter Fransson

Keyword(s):

Network Theory ◽

Temporal Dynamics ◽

Brain Connectivity ◽

Resting State Fmri ◽

Network Activity ◽

Temporal Network ◽

Functional Brain ◽

Brain Connectome ◽

The Brain ◽

Network Neuroscience

Network neuroscience has become an established paradigm to tackle questions related to the functional and structural connectome of the brain. Recently, interest has been growing in examining the temporal dynamics of the brain’s network activity. Although different approaches to capturing fluctuations in brain connectivity have been proposed, there have been few attempts to quantify these fluctuations using temporal network theory. This theory is an extension of network theory that has been successfully applied to the modeling of dynamic processes in economics, social sciences, and engineering article but it has not been adopted to a great extent within network neuroscience. The objective of this article is twofold: (i) to present a detailed description of the central tenets of temporal network theory and describe its measures, and; (ii) to apply these measures to a resting-state fMRI dataset to illustrate their utility. Furthermore, we discuss the interpretation of temporal network theory in the context of the dynamic functional brain connectome. All the temporal network measures and plotting functions described in this article are freely available as the Python package Teneto.

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Network Neuroscience and Personality

Personality Neuroscience ◽

10.1017/pen.2018.12 ◽

2018 ◽

Vol 1 ◽

Cited By ~ 13

Author(s):

Sebastian Markett ◽

Christian Montag ◽

Martin Reuter

Keyword(s):

Nervous System ◽

Individual Differences ◽

Personality Traits ◽

Brain Connectivity ◽

Gray Matter Volume ◽

Actual Behavior ◽

Present Contribution ◽

Nervous Systems ◽

The Brain ◽

Network Neuroscience

AbstractPersonality and individual differences originate from the brain. Despite major advances in the affective and cognitive neurosciences, however, it is still not well understood how personality and single personality traits are represented within the brain. Most research on brain-personality correlates has focused either on morphological aspects of the brain such as increases or decreases in local gray matter volume, or has investigated how personality traits can account for individual differences in activation differences in various tasks. Here, we propose that personality neuroscience can be advanced by adding a network perspective on brain structure and function, an endeavor that we label personality network neuroscience.With the rise of resting-state functional magnetic resonance imaging (MRI), the establishment of connectomics as a theoretical framework for structural and functional connectivity modeling, and recent advancements in the application of mathematical graph theory to brain connectivity data, several new tools and techniques are readily available to be applied in personality neuroscience. The present contribution introduces these concepts, reviews recent progress in their application to the study of individual differences, and explores their potential to advance our understanding of the neural implementation of personality.Trait theorists have long argued that personality traits are biophysical entities that are not mere abstractions of and metaphors for human behavior. Traits are thought to actually exist in the brain, presumably in the form of conceptual nervous systems. A conceptual nervous system refers to the attempt to describe parts of the central nervous system in functional terms with relevance to psychology and behavior. We contend that personality network neuroscience can characterize these conceptual nervous systems on a functional and anatomical level and has the potential do link dispositional neural correlates to actual behavior.

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Advanced network neuroscience approaches in sleep neurobiology on extreme environments

2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) ◽

10.1109/embc.2019.8857053 ◽

2019 ◽

Author(s):

Christos A. Frantzidis ◽

Christiane M. Nday ◽

Panteleimon Chriskos ◽

Polyxeni T. Gkivogkli ◽

Panagiotis D. Bamidis ◽

...

Keyword(s):

Extreme Environments ◽

Network Neuroscience

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The road ahead in clinical network neuroscience

Network Neuroscience ◽

10.1162/netn_a_00103 ◽

2019 ◽

Vol 3 (4) ◽

pp. 969-993 ◽

Cited By ~ 7

Author(s):

Linda Douw ◽

Edwin van Dellen ◽

Alida A. Gouw ◽

Alessandra Griffa ◽

Willem de Haan ◽

...

Keyword(s):

State Of The Art ◽

Brain Network ◽

Disease Classification ◽

Clinical Neuroscience ◽

The Road ◽

Clinical Network ◽

Current State ◽

Structural Network ◽

Multidisciplinary Group ◽

Network Neuroscience

Clinical network neuroscience, the study of brain network topology in neurological and psychiatric diseases, has become a mainstay field within clinical neuroscience. Being a multidisciplinary group of clinical network neuroscience experts based in The Netherlands, we often discuss the current state of the art and possible avenues for future investigations. These discussions revolve around questions like “How do dynamic processes alter the underlying structural network?” and “Can we use network neuroscience for disease classification?” This opinion paper is an incomplete overview of these discussions and expands on ten questions that may potentially advance the field. By no means intended as a review of the current state of the field, it is instead meant as a conversation starter and source of inspiration to others.

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