Probabilistic mapping of human functional brain networks identifies regions of high group consensus

Dworetsky, Ally; Seitzman, Benjamin A.; Adeyemo, Babatunde; Neta, Maital; Coalson, Rebecca S.; Petersen, Steven E.; Gratton, Caterina

doi:10.1016/j.neuroimage.2021.118164

Cited by 46 publications

(76 citation statements)

References 54 publications

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“…This procedure consisted of a two-fold check of (1) the variance explained by the first principal component of the pre-variant, resulting from a principal component analysis on variants’ vertex-wise seed maps (i.e., ‘homogeneity’ (Gordon et al, 2016)) and (2) the proportion of the variant’s territory that is dominated by a single network in the individual’s subject-specific vertex-wise network map. In these vertex-wise maps, each cortical vertex is individually assigned to a network using a template-matching procedure (see (Dworetsky et al, 2021; Gordon et al, 2017a; Gordon et al, 2017b) which matches each vertex’s thresholded seedmap to each network’s thresholded seedmap (each thresholded at the top 5% of values) and assigns the vertex to the network with the best fit (measured via the Dice coefficient; similar to (Gordon et al, 2017b)). Using the MSC as a pilot dataset and manually rating whether each pre-variant should be flagged to be divided based on these criteria, thresholds were set at 66.7% homogeneity and 75% network dominance in the individual network map.…”

Section: Methodsmentioning

confidence: 99%

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Two common and distinct forms of variation in human functional brain networks

Dworetsky¹,

Seitzman²,

Adeyemo³

et al. 2021

Preprint

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The cortex has a characteristic layout with specialized functional areas forming distributed large-scale networks. However, substantial work shows striking variation in this organization across people, which relates to differences in behavior. While a dominant assumption is that cortical 'variants' represent boundary shifts in the borders between regions, here we show that variants can also occur at a distance from their typical position, forming ectopic intrusions. Both forms of variants are common across individuals, but the forms differ in their location, network linkages, and activations during tasks. Sub-groups of individuals share similar variant properties, but sub-grouping on the two variant forms appears independent. This work argues that individual differences in brain organization commonly occur in two dissociable forms, border shifts and ectopic intrusions, that must be separately accounted for in the analysis of cortical systems across people. This work expands our knowledge of cortical variation in humans and helps reconceptualize the discussion of how cortical systems variability arises and links to individual differences in behavior.

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Section: Methodsmentioning

confidence: 99%

“…For the HCP dataset (given differences in dataset resolution and acquisition parameters (Van Essen et al, 2012b); see also (Dworetsky et al, 2021)), a dataset-specific network template was generated from the set of 384 subjects (Supp. Fig.…”

Section: Methodsmentioning

confidence: 99%

Two common and distinct forms of variation in human functional brain networks

Dworetsky¹,

Seitzman²,

Adeyemo³

et al. 2021

Preprint

Self Cite

View full text Add to dashboard Cite

show abstract

“…Even well-studied networks that appear in roughly similar brain locations in almost every person do not correspond exactly anatomically (e.g., the default network (80) or somatomotor networks (90)). A recent quantitative examination of inter-subject variability of 14 large-scale brain networks finds that while networks exhibit a common core, consistency across individuals falls off sharply, especially in higher order networks in the frontal and parietal lobe (79). This individual variation suggests that standardized parcellation schemes that are uniformly applied to a sample without respect for functional neuroanatomic variability can mischaracterize network estimates, resulting in reductions in specificity and analytical power in inter-individual comparisons (91)(92)(93)(94).…”

Section: Inter-individual Variabilitymentioning

confidence: 99%

Controversies and progress on standardization of large-scale brain network nomenclature

Uddin¹,

Betzel²,

Cohen³

et al. 2022

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Progress in scientific disciplines is often accompanied by the standardization of terminology and nomenclature. Network neuroscience, as applied at the level of macro-scale organization of the brain, has emerged over the past decade from interdisciplinary collaborations. The field is only beginning to confront the challenges associated with developing and refining a taxonomy of its fundamental explanatory constructs. Despite initial attempts, there is currently a lack of consensus around basic questions such as “What constitutes a brain network”?, “Are there universal and reproducible brain networks that can be observed across individuals”? and “What naming and reporting conventions could be adopted to facilitate cross-laboratory communication?” The Workgroup for HArmonized Taxonomy of NETworks (WHATNET) was formed in 2020 as an Organization for Human Brain Mapping (OHBM)-endorsed committee on best practices in large-scale brain network nomenclature. The objective is to provide concrete reporting recommendations similar to those produced by the Committee on Best Practices in Data Analysis and Sharing (COBIDAS) and the magneto- and electroencephalography best practices committee. A working group was formed of cognitive and network neuroscientists, engineers, and philosophers who are actively engaged in research examining functional and structural brain networks using a range of neuroimaging modalities. The goal of WHATNET is to provide recommendations on points of consensus, identify open questions, and highlight areas of debate in the scientific community. The committee conducted a Qualtrics survey that was circulated by the OHBM executive office and advertised on Twitter to catalog current practices in large-scale brain network nomenclature. As expected, a few well-known network names (eg. default network) dominated responses to the survey. However, a number of interesting and illuminating points of disagreement emerged as well. The goal of this initiative is to move the field towards providing clear criteria and developing tools to aid in standardization of reporting network neuroscience results. Here we summarize survey results, discuss considerations, and provide initial recommendations from the workgroup. In doing so, we discuss multiple challenges to this enterprise, including: 1) network scale, resolution, and hierarchies; 2) inter-individual variability of networks; 3) consideration of network affiliations of subcortical structures; 4) consideration of multi-modal information, and 5) dynamics and non-stationarity of networks. We close with a set of minimal reporting guidelines that we urge the cognitive and network neuroscience communities to adopt while awaiting more concrete recommendations that we anticipate will be forthcoming from this group.

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“…Recent alternate methods have also been proposed, involving probabilistic mapping to improve consensus and inferences, see Dworetsky et al, 2021(Dworetsky et al, 2021.…”

Section: Signal From the Noisementioning

confidence: 99%

Neural Mechanisms and Psychology of Psychedelic Ego Dissolution

Stoliker¹,

Egan²,

Friston³

et al. 2021

Preprint

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Neuroimaging studies of psychedelics have advanced our understanding of hierarchical brain organisation and the mechanisms underlying their subjective and therapeutic effects. The primary mechanism of action of classic psychedelics is binding to serotonergic 5HT2A receptors. Agonist activity at these receptors leads to neuromodulatory changes in synaptic efficacy that can have a profound effect on hierarchical message passing in the brain. Here, we review the cognitive and neuroimaging evidence for the effects of psychedelics; in particular, their influence on selfhood and subject-object boundaries—known as ego dissolution—surmised to underwrite their subjective and therapeutic effects. Agonist of 5HT2A receptors, located at the apex of the cortical hierarchy may have a particularly powerful effect on sentience and consciousness. These effects can endure well after the pharmacological half life, suggesting that psychedelics may have long-term effects on neural plasticity – that may play a role in their therapeutic efficacy. Psychologically, this may be accompanied by a surrender of ego resistance that increases the repertoire of perceptual hypotheses, including those that undergird selfhood. We consider the interaction between serotonergic neuromodulation and sentience through the lens of hierarchical predictive coding, which speaks to the value of psychedelics in understanding how we make sense of the world—and specific predictions about effective connectivity in cortical hierarchies that can be tested using functional neuroimaging.

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Probabilistic mapping of human functional brain networks identifies regions of high group consensus

Cited by 46 publications

References 54 publications

Two common and distinct forms of variation in human functional brain networks

Two common and distinct forms of variation in human functional brain networks

Controversies and progress on standardization of large-scale brain network nomenclature

Neural Mechanisms and Psychology of Psychedelic Ego Dissolution

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