Long-term neural and physiological phenotyping of a single human

Poldrack, Russell A.; Laumann, Timothy O.; Koyejo, Oluwasanmi; Gregory, Brenda; Hover, Ashleigh M.; Chen, Mei Yen; Gorgolewski, Krzysztof J.; Luci, Jeffrey J.; Joo, Sung Jun; Boyd, Ryan L.; Hunicke-Smith, Scott Patrick; Simpson, Zack B.; Caven, W Thomas; Sochat, Vanessa; Shine, James M.; Gordon, Evan M.; Snyder, Abraham Z.; Adeyemo, Babatunde; Petersen, Steven E.; Glahn, David C.; McKay, D. Reese; Curran, Joanne E.; Göring, Harald H.H.; Carless, Melanie A.; Blangero, John; Dougherty, Robert F.; Leemans, Alexander; Handwerker, Daniel A.; Frick, Laurie; Marcotte, Edward M.; Mumford, Jeanette A.

doi:10.1038/ncomms9885

Cited by 402 publications

(385 citation statements)

References 70 publications

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“…Researchers continue to take seriously the effort to systematically measure the factors that influence test/ retest reliability of responses across time and tasks, and these sorts of studies are increasingly common [83][84][85][86][87][88] . Other research programs focus on addressing questions about the long-term within-subject stability of responses [89][90] , and how the accurate assessment of within-participant differences might address questions about individual differences 93 . There is increasing support for conducting and publishing the results of confirmatory studies [94][95] , thereby rectifying some existing biases that often favor the publication of new, novel results over confirmatory ones.…”

Section: Results Reproducibilitymentioning

confidence: 99%

Progress toward openness, transparency, and reproducibility in cognitive neuroscience

Gilmore¹,

Diaz²,

Wyble³

et al. 2017

Preprint

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Accumulating evidence suggests that many findings in psychological science and cognitive neuroscience may prove difficult to reproduce; statistical power in brain imaging studies is low, and has not improved recently; software errors in common analysis tools are common, and can go undetected for many years; and, a few large scale studies notwithstanding, open sharing of data, code, and materials remains the rare exception. At the same time, there is a renewed focus on reproducibility, transparency, and openness as essential core values in cognitive neuroscience. The emergence and rapid growth of data archives, meta-analytic tools, software pipelines, and research groups devoted to improved methodology reflects this new sensibility. We review evidence that the field has begun to embrace new open research practices, and illustrate how these can begin to address problems of reproducibility, statistical power, and transparency in ways that will ultimately accelerate discovery.

show abstract

Section: Results Reproducibilitymentioning

confidence: 99%

Progress toward openness, transparency, and reproducibility in cognitive neuroscience

Gilmore¹,

Diaz²,

Wyble³

et al. 2017

Preprint

View full text Add to dashboard Cite

show abstract

“…Further, while the neurobiological basis of inter-individual variability is coming into increasing focus, we still know relatively little about how individual brains change over time (intra-individual variability) [23]. Likewise, the relevance of lab-based measures of self-control (to take one relevant example) for predicting individual variability in real-world behavior remains largely unclear.…”

Section: Enter: Neuropredictionmentioning

confidence: 99%

Predicting violent behavior: What can neuroscience add?

Poldrack

Monahan

Imrey

et al. 2017

Preprint

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The ability to accurately predict violence and other forms of seriously antisocial behavior would provide important societal benefits, and there is substantial enthusiasm for the potential predictive accuracy of neuroimaging techniques. We review the current status of violence prediction using actuarial and clinical methods, and assess the current state of neuroprediction. We then outline a number of questions that need to be addressed by future studies of neuroprediction if they are to be successfully translated into public policy.

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“…The molecular profiles of well-being phenotypes can also be studied in a dynamic approach over a period of months, because phenotypes like well-being are likely also to be characterized by short-and medium-term molecular fluctuations of molecular networks. This concept has recently been applied to a single participant who was characterized in-depth over the period of 532 days for dynamics of brain function and their relation to psychological and biological parameters (Poldrack et al 2015). Molecular profiles related to well-being can also serve as endpoints in intervention studies for promoting happiness, as recently shown for a Yoga intervention that was able to reduce inflammation-related biomarkers among fatigued breast cancer survivor (Irwin et al 2014) and family dementia care givers (Black et al 2013).…”

Section: A First Research Question Is About Molecular Profiling Of DImentioning

confidence: 99%

Happiness and its molecular fingerprints

Probst‐Hensch

2017

Int Rev Econ

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Happiness and well-being are in part heritable, but modifiable traits. The promotion of well-being and happiness, much like the primary prevention of noncommunicable diseases (NCD), will become increasingly important in a world that is facing an NCD epidemic due to demographic aging and urbanization. The costs for the often lifelong treatment of NCDs are already high and may increase further with the arrival of expensive personalized medicine. The effective promotion of happiness at the individual and population level in order to guide policy requires a causal and mechanistic understanding of its modifiable determinants. With more than half of the world's population living in cities, it becomes, for example, important to understand how environmental, social, and lifestyle characteristics of urban life influence well-being. Yet, the correlation between many of these factors and the fact that they act in concert poses a large challenge in causal inference. The -omics biomarkers which form a pillar of personalized medicine are at the same time essential research instruments of modern-day observational epidemiology. The paper discusses how they can be applied to overcome the challenges researchers face in studies on the association of complex risk and protective patterns with specific well-being phenotypes and their relation to diseases. Important concepts are discussed in the context of well-being that were recently developed by epidemiologists to stimulate more investments into the understanding of the modifiable part of health (e.g., Exposome; Meet-in-the-Middle; Mendelian Randomization) to match the huge investments that went into genetic research.

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Long-term neural and physiological phenotyping of a single human

Cited by 402 publications

References 70 publications

Progress toward openness, transparency, and reproducibility in cognitive neuroscience

Progress toward openness, transparency, and reproducibility in cognitive neuroscience

Predicting violent behavior: What can neuroscience add?

Happiness and its molecular fingerprints

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