The NIH BRAIN Initiative’s Impacts in Systems and Computational Neuroscience, 2014-2023

Reviewer #1 (Public review):

Summary:

This is a convincing description of approximately ten years of funding from the NIH BRAIN initiative. It is of particular value at this moment in history, given the cataclysmic changes in the US government structure and function occurring in early 2025.

Strengths:

The paper contains a fair bit of documentation so that the curious reader can actually parse what this BRAIN program funded.

Weaknesses:

There are too many acronyms, and the manuscript reads as if it were an internal NIH document, where the audience knows all of the NIH nomenclature and program details. It is not particularly friendly to the outside, lay reader.

Reviewer #2 (Public review):

Summary:

The authors provide an important summary of ten years of Brain Initiative funding including a description of the historical development of the initiative, the specific funding mechanisms utilized, and examples of grants funded and work produced. The authors also conduct analyses of the impact on overall funding in Systems and Computational Neuroscience, the raw and field normalized bibliographic impact of the work, the social media impact of the funded work, and the popularity of some tools developed.

Strengths:

This is a useful perspective on an important funding initiative over a ten-year period. It is clearly written and the illustrations and analyses are mostly useful for understanding the impact of the initiative.

Weaknesses:

The major limitation is that the bibliographic analysis does not provide a comparison group of funded grants. Because work that successfully competes for funding is likely to be more impactful than all work in a given area, the normalization of citations to field medians may reflect this "grant review" effect, rather than anything special about the Brain Initiative. Hopefully, this speculation is incorrect (I would guess that it is), but it would be helpful to try to demonstrate this more directly by including a funded comparison group.

There are also minor inconsistencies in the numbering of the figures that need to be cleared up.

Author response:

eLife Assessment

The authors provide a useful summary of ten years of Brain Initiative funding including the historical development, the specific funding mechanisms, and examples of grants funded and work produced. The authors also conduct analyses of the impact on overall funding in Systems and Computational Neuroscience, the raw and field normalized bibliographic impact of the work, the social media impact of the funded work, and the popularity of some tools developed. The evidence for impact is incomplete due to the omission of a comparison group of funded grants.

In this combined version, we include a comparison group of non-BRAIN Initiative R01s derived from the parent notice of funding opportunity from FY2014-2022. We performed a bibliometric analysis of the publications, citations, RCR and budget productivity measure of the non-BRAIN parent R01.

Public Reviews:

Reviewer #1 (Public review):

Summary:

This is a convincing description of approximately ten years of funding from the NIH BRAIN initiative. It is of particular value at this moment in history, given the cataclysmic changes in the US government structure and function occurring in early 2025.

Strengths:

The paper contains a fair bit of documentation so that the curious reader can actually parse what this BRAIN program funded.

Weaknesses:

There are too many acronyms, and the manuscript reads as if it were an internal NIH document, where the audience knows all of the NIH nomenclature and program details. It is not particularly friendly to the outside, lay reader.

In this version, we have attempted to minimize acronyms and explain NIH nomenclature and program details to make it more accessible to readers not familiar with NIH terminology.

Reviewer #2 (Public review):

Summary:

The authors provide an important summary of ten years of Brain Initiative funding including a description of the historical development of the initiative, the specific funding mechanisms utilized, and examples of grants funded and work produced. The authors also conduct analyses of the impact on overall funding in Systems and Computational Neuroscience, the raw and field normalized bibliographic impact of the work, the social media impact of the funded work, and the popularity of some tools developed.

Strengths:

This is a useful perspective on an important funding initiative over a ten-year period. It is clearly written and the illustrations and analyses are mostly useful for understanding the impact of the initiative.

Weaknesses:

The major limitation is that the bibliographic analysis does not provide a comparison group of funded grants. Because work that successfully competes for funding is likely to be more impactful than all work in a given area, the normalization of citations to field medians may reflect this "grant review" effect, rather than anything special about the Brain Initiative. Hopefully, this speculation is incorrect (I would guess that it is), but it would be helpful to try to demonstrate this more directly by including a funded comparison group.

In this version, we have provided a comparison group of parent R01s that are not funded through the BRAIN Initiative from FY2014-2022 in Figure 3. We include publication metrics and budget efficiency measures for this comparison group.

There are also minor inconsistencies in the numbering of the figures that need to be cleared up.

We have updated the figure numbers.