Cognitive neuroscience 2.0: building a cumulative science of human brain function

doi:10.1016/j.tics.2010.08.004

Trends in Cognitive Sciences

Volume 14, Issue 11, November 2010, Pages 489-496

https://doi.org/10.1016/j.tics.2010.08.004 Get rights and content

Cognitive neuroscientists increasingly recognize that continued progress in understanding human brain function will require not only the acquisition of new data, but also the synthesis and integration of data across studies and laboratories. Here we review ongoing efforts to develop a more cumulative science of human brain function. We discuss the rationale for an increased focus on formal synthesis of the cognitive neuroscience literature, provide an overview of recently developed tools and platforms designed to facilitate the sharing and integration of neuroimaging data, and conclude with a discussion of several emerging developments that hold even greater promise in advancing the study of human brain function.

Section snippets

Science by synthesis

Science is, by nature, a cumulative endeavor. Scientific advances generally build directly on previous studies and issue findings that only make sense in light of existing knowledge. In cognitive neuroscience, as in many other scientific disciplines, a gold standard for scientific progress and accumulation of knowledge has historically been the ‘critical experiment’: a single empirical test that decisively disqualifies one or more hypotheses from further consideration [1]. Valuable as they can

The rationale

Why is an increased focus on formal synthesis of cognitive neuroscience literature needed? Much of the difficulty in drawing strong and selective inferences about brain structure and function reflects fundamental statistical and methodological constraints that are difficult, if not impossible, for most individual studies to overcome. We focus here on several limitations that can be ameliorated by synthesizing results across many experiments and laboratories.

The methods

Many researchers in the field of cognitive neuroscience increasingly appreciate the importance of conducting formal syntheses of cognitive neuroscience literature. In this section we summarize relevant history and discuss several recently developed tools and platforms designed to facilitate the sharing and integration of neuroimaging data. Our review is by no means exhaustive; it mainly emphasizes what we view as some of the more promising recent developments.

The future

The tools and techniques described in the previous section represent, in many respects, only the first steps towards a truly cumulative cognitive neuroscience. Going forward, new tools and technologies will undoubtedly continue to reshape the way cognitive neuroscientists conduct research. Here we highlight several emerging developments that could confer important benefits for the field.

Concluding remarks

The explosive growth of human brain mapping over the past two decades has raised important challenges for the field. As the primary literature expands, the need for powerful tools capable of synthesizing and distilling the findings of many different studies grows commensurately. The present article highlighted the benefits of a synthesis-oriented research strategy and reviewed several ongoing efforts to facilitate greater integration of the published literature. Going forward, such integration

Acknowledgements

This work was supported by NIH award F32NR012081 to T.Y., NIH awards NIMH R01MH076136 and NIDA R01DA027794 to T.D.W., NIH award R01MH082795 to R.A.P., and NIH award R01MH60974 to D.V.E.

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Trends in Cognitive Sciences

ReviewCognitive neuroscience 2.0: building a cumulative science of human brain function

Section snippets

Science by synthesis

The rationale

The methods

The future

Concluding remarks

Acknowledgements

Curr. Opin. Neurobiol.

Trends Cogn. Sci.

Neuroimage

Trends Neurosci.

Neuroimage

Neuron

Neuroimage

Neuroimage

Curr. Opin. Neurobiol.

Neuroimage

Alzheimers Dement.

Curr. Opin. Neurobiol.

Neuroimage

NeuroImage

J. Biomed. Inform.

Neuroimage

Neuroimage

Neuroimage

Neuroimage

Neuroimage

Neuroimage

Strong inference

Science

Big correlations in little studies: Inflated fMRI correlations reflect low statistical power–Commentary on Vul et al. (2009)

Perspect. Psychol. Sci.

Why most discovered true associations are inflated

Epidemiology

Meta-analysis of functional neuroimaging data: current and future directions

Soc. Cogn. Affect. Neurosci.

A default mode of brain function

Proc. Natl. Acad. Sci. U. S. A.

The human brain is intrinsically organized into dynamic, anticorrelated functional networks

Proc. Natl. Acad. Sci. U. S. A.

Review
Cognitive neuroscience 2.0: building a cumulative science of human brain function