Methods for analysis of brain connectivity: An IFCN-sponsored review

Rossini, Paolo Maria; Iorio, Riccardo Di; Bentivoglio, Marina; Bertini, Giuseppe; Ferreri, Florinda; Gerloff, Christian; Ilmoniemi, Risto J.; Miraglia, Francesca; Nitsche, Michael A.; Pestilli, Franco; Rosanova, Mario; Shirota, Yasuhiko; Tesoriero, Chiara; Ugawa, Yoshikazu; Vecchio, Fabrizio; Ziemann, Ulf; Hallett, Mark

doi:10.1016/j.clinph.2019.06.006

Cited by 130 publications

(89 citation statements)

References 333 publications

(374 reference statements)

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“…Electroencephalography (EEG) and magnetoencephalography (MEG) can be used to analyze functional connectivity (FC) through the analysis of temporal correlations between spontaneous activity of different regions and are characterized by elevated temporal resolution. Functional MRI (fMRI) has a higher spatial resolution and represents the most used approach to explore brain network organization in vivo [12,13]. Resting state-fMRI (rs-fMRI) offers the chance to explore overall brain connectivity in healthy individuals and in different pathological conditions [14,15].…”

Section: Brain Network Organizationmentioning

confidence: 99%

Synaptic Plasticity Shapes Brain Connectivity: Implications for Network Topology

Bassi

Iezzi

Gilio

et al. 2019

IJMS

107

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Studies of brain network connectivity improved understanding on brain changes and adaptation in response to different pathologies. Synaptic plasticity, the ability of neurons to modify their connections, is involved in brain network remodeling following different types of brain damage (e.g., vascular, neurodegenerative, inflammatory). Although synaptic plasticity mechanisms have been extensively elucidated, how neural plasticity can shape network organization is far from being completely understood. Similarities existing between synaptic plasticity and principles governing brain network organization could be helpful to define brain network properties and reorganization profiles after damage. In this review, we discuss how different forms of synaptic plasticity, including homeostatic and anti-homeostatic mechanisms, could be directly involved in generating specific brain network characteristics. We propose that long-term potentiation could represent the neurophysiological basis for the formation of highly connected nodes (hubs). Conversely, homeostatic plasticity may contribute to stabilize network activity preventing poor and excessive connectivity in the peripheral nodes. In addition, synaptic plasticity dysfunction may drive brain network disruption in neuropsychiatric conditions such as Alzheimer’s disease and schizophrenia. Optimal network architecture, characterized by efficient information processing and resilience, and reorganization after damage strictly depend on the balance between these forms of plasticity.

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Section: Brain Network Organizationmentioning

confidence: 99%

Synaptic Plasticity Shapes Brain Connectivity: Implications for Network Topology

Bassi

Iezzi

Gilio

et al. 2019

IJMS

107

View full text Add to dashboard Cite

show abstract

“…As result, confirming the existence of any white matter connection, invasive methods and comparative work is mandatory. Indeed, in-vivo tractography findings are often complemented with comparisons to anatomical knowledge from post-mortem methods, advancing knowledge and discovery (for a discussion about statistical methods for tractography evaluation see also Pestilli 2015Pestilli , 2018Rokem et al 2017;Rossini et al 2019;Takemura et al 2016b). It has been demonstrated that, under certain conditions of scientific rigor, in-vivo tractography helps to clarify the organization of white matter anatomy otherwise left unresolved by post-mortem methods (Takemura et al 2016b;Takemura et al 2019;Wandell 2016;Sani et al 2019;Yeatman et al 2014;Puzniak et al 2019;Takemura et al 2017;Leong et al 2016).…”

Section: Discussionmentioning

confidence: 99%

The visual white matter connecting human area prostriata and the thalamus is retinotopically organized

Kurzawski

Mikellidou

Morrone

et al. 2020

Preprint

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The human visual system is capable of processing visual information from fovea to the far peripheral visual field. Recent fMRI studies have shown a full and detailed retinotopic map in area prostriata, located ventro-dorsally and anterior to the calcarine sulcus along the parietooccipital sulcus with strong preference for peripheral and wide-field stimulation. Here, we report the anatomical pattern of white-matter connections between area prostriata and the thalamus encompassing the lateral geniculate nucleus (LGN). We observe a continuous and extended bundle of white matter fibers from which two subcomponents can be extracted: one passing ventrally parallel to the optic radiations (OR) and another passing dorsally circumventing the lateral ventricle. Interestingly, the loop travelling dorsally connects the thalamus with the central visual field representation of prostriata, while the other loop travelling more ventrally connects the LGN with the more peripheral visual field representation. This is consistent with a retinotopic segregation recently demonstrated in the OR, connecting the LGN and V1 in humans. Our results demonstrate for the first time a retinotopic segregation regarding the trajectory of a fiber bundle between the thalamus and an associative visual area.

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“…Graph theory offers a helpful approach to analyzing connectivity data deriving from neurophysiological (i.e., electroencephalography and magnetoencephalography) or imaging (i.e., functional MRI, fMRI) techniques [12][13][14][15][16][17]. Complex brain networks can be modeled as a series of nodes, indicating different brain regions, and edges, representing the connections between nodes.…”

Section: Brain Network Architecture Provides Resilience To Damagementioning

confidence: 99%

“…Complex brain networks can be modeled as a series of nodes, indicating different brain regions, and edges, representing the connections between nodes. The edges are defined on the basis of structural (i.e., diffusion tensor imaging, DTI) or functional connectivity (i.e., temporal covariation of spontaneous activity) between different regions [17][18][19]. Specific measures describing network functioning have been defined.…”

Section: Brain Network Architecture Provides Resilience To Damagementioning

confidence: 99%

Modeling Resilience to Damage in Multiple Sclerosis: Plasticity Meets Connectivity

Bassi

Iezzi

Pavone

et al. 2019

IJMS

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Multiple sclerosis (MS) is a chronic inflammatory disease of the central nervous system (CNS) characterized by demyelinating white matter lesions and neurodegeneration, with a variable clinical course. Brain network architecture provides efficient information processing and resilience to damage. The peculiar organization characterized by a low number of highly connected nodes (hubs) confers high resistance to random damage. Anti-homeostatic synaptic plasticity, in particular long-term potentiation (LTP), represents one of the main physiological mechanisms underlying clinical recovery after brain damage. Different types of synaptic plasticity, including both anti-homeostatic and homeostatic mechanisms (synaptic scaling), contribute to shape brain networks. In MS, altered synaptic functioning induced by inflammatory mediators may represent a further cause of brain network collapse in addition to demyelination and grey matter atrophy. We propose that impaired LTP expression and pathologically enhanced upscaling may contribute to disrupting brain network topology in MS, weakening resilience to damage and negatively influencing the disease course.

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Methods for analysis of brain connectivity: An IFCN-sponsored review

Cited by 130 publications

References 333 publications

Synaptic Plasticity Shapes Brain Connectivity: Implications for Network Topology

Synaptic Plasticity Shapes Brain Connectivity: Implications for Network Topology

The visual white matter connecting human area prostriata and the thalamus is retinotopically organized

Modeling Resilience to Damage in Multiple Sclerosis: Plasticity Meets Connectivity

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