#CommunicationSoWhite

Chakravartty, Paula; Kuo, Rachel; Grubbs, Victoria Netanus; McIlwain, Charlton D.

doi:10.1093/joc/jqy003

Cited by 417 publications

(226 citation statements)

References 23 publications

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“…Recent work in neuroscience and other fields has identified a bias in citation practices such that papers from women and other minorities are under-cited relative to the number of such papers in the field (Maliniak et al, 2013, Caplar et al, 2017, Chakravartty et al, 2018, Thiem et al, 2018, Dion et al, 2018, Dworkin et al, 2020. Here we sought to proactively consider choosing references that reflect the diversity of the field in thought, form of contribution, gender, and other factors.…”

Section: Citation Gender Diversity Statementmentioning

confidence: 99%

Integrating multimodal connectivity improves prediction of individual cognitive abilities

Dhamala

Jamison

Jaywant

et al. 2020

Preprint

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SummaryHow white matter pathway integrity and neural co-activation patterns in the brain relate to complex cognitive functions remains a mystery in neuroscience. Here, we integrate neuroimaging, connectomics, and machine learning approaches to explore how multimodal brain connectivity relates to cognition. Specifically, we evaluate whether integrating functional and structural connectivity improves prediction of individual crystallised and fluid abilities in 415 unrelated healthy young adults from the Human Connectome Project. Our primary results are two-fold. First, we demonstrate that integrating functional and structural information – at both a model input or output level – significantly outperforms functional or structural connectivity alone to predict individual verbal/language skills and fluid reasoning/executive function. Second, we show that distinct pairwise functional and structural connections are important for these predictions. In a secondary analysis, we find that structural connectivity derived from deterministic tractography is significantly better than structural connectivity derived from probabilistic tractography to predict individual cognitive abilities.

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Section: Citation Gender Diversity Statementmentioning

confidence: 99%

Integrating multimodal connectivity improves prediction of individual cognitive abilities

Dhamala

Jamison

Jaywant

et al. 2020

Preprint

View full text Add to dashboard Cite

show abstract

“…Recent work in neuroscience and other fields has identified a bias in citation practices such that papers from women and other minorities are under-cited relative to the number of such papers in the field [65][66][67][68][69][70] . Here, we sought to proactively consider choosing references that reflect the diversity of the field in thought, form of contribution, gender and other factors.…”

Section: Citation Diversity Statementmentioning

confidence: 99%

Multimodalin vivorecording using transparent graphene microelectrodes illuminates spatiotemporal seizure dynamics at the microscale

Driscoll

Rosch

Murphy

et al. 2020

Preprint

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Neurological disorders such as epilepsy arise from disrupted brain networks. Our capacity to treat these disorders is limited by our inability to map these networks at sufficient temporal and spatial scales to target interventions. Current best techniques either sample broad areas at low temporal resolution (e.g. calcium imaging) or record from discrete regions at high temporal resolution (e.g. electrophysiology). This limitation hampers our ability to understand and intervene in aberrations of network dynamics. Here we present a technique to map the onset and spatiotemporal spread of acute epileptic seizures in vivo by simultaneously recording high bandwidth microelectrocorticography and calcium fluorescence using transparent graphene microelectrode arrays. We integrate dynamic data features from both modalities using non-negative matrix factorization to identify sequential spatiotemporal patterns of seizure onset and evolution, revealing how the temporal progression of ictal electrophysiology is linked to the spatial evolution of the recruited seizure core. This integrated analysis of multimodal data reveals otherwise hidden state transitions in the spatial and temporal progression of acute seizures. The techniques demonstrated here may enable future targeted therapeutic interventions and novel spatially embedded models of local circuit dynamics during seizure onset and evolution.

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“…Recent work in neuroscience and other fields has identified a bias in citation practices such that papers from women and other minorities are under-cited relative to the number of such papers in the field (76)(77)(78)(79)(80)(81). Here we sought to proactively consider choosing references that reflect the diversity of the field in thought, form of contribution, gender, and other factors.…”

Section: Citation Diversity Statementmentioning

confidence: 99%

Segregation of default mode from frontoparietal system protects against smoking lapse

Lydon‐Staley¹,

Rr²,

Eb³

et al. 2020

Preprint

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Quitting smoking is notoriously difficult. Models of nicotine dependence posit that deficits in cognitive control contribute to failures to maintain smoking abstinence during smoking cessation attempts. We examine the role for large-scale functional brain systems associated with cognitive control in smoking lapse. We use data from 70, five-minute functional magnetic resonance imaging (fMRI) scans in 17 daily smokers (5 female) undergoing a smoking lapse paradigm after 12 hours of smoking abstinence. Cox regression results indicate that decreased segregation of the default mode system from the frontoparietal system undermine the ability to resist smoking. Results lend support to the hypothesis that large-scale functional brain systems associated with cognitive control are implicated in smoking lapse behavior and point to the importance of cognitive control as a mechanism underlying smoking relapse.

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#CommunicationSoWhite

Cited by 417 publications

References 23 publications

Integrating multimodal connectivity improves prediction of individual cognitive abilities

Integrating multimodal connectivity improves prediction of individual cognitive abilities

Multimodalin vivorecording using transparent graphene microelectrodes illuminates spatiotemporal seizure dynamics at the microscale

Segregation of default mode from frontoparietal system protects against smoking lapse

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