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:10.1101/2020.09.28.313791

Cited by 8 publications

(25 citation statements)

References 57 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Using this group approach means, of course, that individual differences in the DAN may not be accounted for in our analyses. Although the functional anatomy of the DAN is well conserved across individuals (Dworetsky et al, 2020;Gratton et al, 2018), we nonetheless could have considered alternatives, such as using a localizer scan or templates, to identify the DAN in order to define individual participant ROIs, as we have done in some prior work (Fannon, Saron, & Mangun, 2008). Indeed, some prior decoding studies have defined the DAN at the individual participant level in native space (Liu & Hou, 2013), whereas others have taken approaches similar to our group-level/standard-space method (Zhang & Golomb, 2021).…”

Section: Definition Of Roimentioning

confidence: 99%

The Microstructure of Attentional Control in the Dorsal Attention Network

Rajan

Meyyappan

Liu

et al. 2021

Journal of Cognitive Neuroscience

View full text Add to dashboard Cite

The top–down control of attention involves command signals arising chiefly in the dorsal attention network (DAN) in frontal and parietal cortex and propagating to sensory cortex to enable the selective processing of incoming stimuli based on their behavioral relevance. Consistent with this view, the DAN is active during preparatory (anticipatory) attention for relevant events and objects, which, in vision, may be defined by different stimulus attributes including their spatial location, color, motion, or form. How this network is organized to support different forms of preparatory attention to different stimulus attributes remains unclear. We propose that, within the DAN, there exist functional microstructures (patterns of activity) specific for controlling attention based on the specific information to be attended. To test this, we contrasted preparatory attention to stimulus location (spatial attention) and to stimulus color (feature attention), and used multivoxel pattern analysis to characterize the corresponding patterns of activity within the DAN. We observed different multivoxel patterns of BOLD activation within the DAN for the control of spatial attention (attending left vs. right) and feature attention (attending red vs. green). These patterns of activity for spatial and feature attentional control showed limited overlap with each other within the DAN. Our findings thus support a model in which the DAN has different functional microstructures for distinctive forms of top–down control of visual attention.

show abstract

Section: Definition Of Roimentioning

confidence: 99%

The Microstructure of Attentional Control in the Dorsal Attention Network

Rajan

Meyyappan

Liu

et al. 2021

Journal of Cognitive Neuroscience

View full text Add to dashboard Cite

show abstract

“…While there is a growing movement towards individualized functional communities, group-level partitions are still widely used, as they allow researchers to easily compare results across participants without the confound of differences in the size or number of communities. Further, individualized approaches typically require large amounts of data per individual 9,65,66 , and thus may not always be feasible in developmental studies.…”

Section: Broader Implications and Future Directionsmentioning

confidence: 99%

“…Prioritizing methods that estimate the uncertainty and variation in community assignment, such as soft partitioning approaches that assign weighted probabilities of community assignment to each vertex (e.g., Refs. 27,66 ), will enable us to test whether functional brain network architecture becomes more solidified as children grow up.…”

Section: Broader Implications and Future Directionsmentioning

confidence: 99%

“…Thus, we examined areas of high uncertainty in community assignment across both community detection approaches we employed. We com-bined the confidence measure from the data-driven com-491 munity detection approach and the variability measure each vertex (e.g., [26,62]), will enable us to test whether functional brain network architecture becomes more solidified as children grow up.…”

Section: Uncertainty In Both Developmental Partitionsmentioning

confidence: 99%

See 1 more Smart Citation

Functional brain network community structure in childhood: Unfinished territories and fuzzy boundaries

Tooley

Bassett

Mackey

2021

Preprint

View full text Add to dashboard Cite

Adult cortex is organized into distributed functional communities. Yet, little is known about community architecture in childhood. Here, we address this gap by studying the community structure of cortex in 670 children aged 9-11 years from the Adolescent Brain and Cognitive Development study. Using fMRI, we first applied a data-driven partitioning algorithm to assign regions to communities, then used a model-based algorithm to further probe community interactions. Children showed similar community structure to adults in early-developing sensory and motor communities. Differences emerged in transmodal areas, manifesting in expanded limbic territory and more flexible interactions between association regions in children relative to adults. The greatest uncertainty in algorithmic assignment was localized to areas supporting attention, indicating complex undifferentiated connectivity patterns in these regions. Collectively, our findings suggest that community boundaries are not solidified in middle childhood, an instability that provides important context for children’s thoughts and behaviors during this period.

show abstract

“…Though ABCD will provide an impressive resource for describing individual variation in network organization over time, “only” 20 minutes of resting state data is collected per participant, which may reduce the ability to maximize the precision of the individualized connectome across all participants. However, the shorter resting state data set is still valuable for precision mapping using new ‘supervised’ methods (Dworetsky et al, 2020; Gordon et al, 2017b) that create individual-specific networks that may only be marginally less precise. Furthermore, as task activity only adds a relatively small amount of variance to global resting-state brain organization (Gratton et al, 2018a), the additional task fMRI data (40 minutes) per participant can be used to generate individual-specific networks using similar amounts of data as prior reports (Cui et al, 2020; Gordon et al, 2017a; Laumann et al, 2015).…”

Section: Introductionmentioning

confidence: 99%

A Precision Functional Atlas of Network Probabilities and Individual-Specific Network Topography

Hermosillo

Moore

Feczko

et al. 2022

Preprint

Self Cite

View full text Add to dashboard Cite

The brain is organized into a broad set of functional neural networks. These networks and their various characteristics have been described and scrutinized through in vivo resting state functional magnetic resonance imaging (rs-fMRI). While the basic properties of networks are generally similar between healthy individuals, there is vast variability in the precise topography across the population. These individual differences are often lost in population studies due to population averaging which assumes topographical uniformity. We leveraged precision brain mapping methods to establish a new open-source, method-flexible set of probabilistic functional network atlases: the Masonic Institute for the Developing Brain (MIDB) Precision Atlas. Using participants from the Adolescent Brain Cognitive Development (ABCD) study, single subject precision maps were generated with two supervised network-matching procedures (template matching and non-negative matrix factorization), as well as an unsupervised community detection algorithm (Infomap). We demonstrate that probabilistic network maps generated for two demographically-matched groups of n~3000 each were nearly identical, both between groups (Pearson r >0.999) and between methods (r=0.96), revealing both regions of high invariance and high variability. Compared to using parcellations based on groups averages, the MIDB Precision Atlases allowed us to derive a set of brain regions that are largely invariant in network topography and provide more reproducible statistical maps of executive function brain-wide associations. We explore an example use case for probabilistic maps, highlighting their potential for use in targeted neuromodulation. The MIDB Precision Atlas is expandable to alternative datasets and methods and is provided open-source with an online web interface to encourage the scientific community to experiment with probabilistic atlases and individual-specific topographies to more precisely relate network phenomenon to functional organization of the human brain.

show abstract

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

Cited by 8 publications

References 57 publications

The Microstructure of Attentional Control in the Dorsal Attention Network

The Microstructure of Attentional Control in the Dorsal Attention Network

Functional brain network community structure in childhood: Unfinished territories and fuzzy boundaries

A Precision Functional Atlas of Network Probabilities and Individual-Specific Network Topography

Contact Info

Product

Resources

About