The NIH Advisory Committee to the Director released a report in early June,
BRAIN 2025: A Scientific Vision, that emphasizes the importance of statistics. Its executive summary lists seven scientific goals that are high priorities for achieving this vision including:
Identifying fundamental principles: Produce conceptual foundations for understanding the biological basis of mental processes through development of new theoretical and data analysis tools. Rigorous theory, modeling, and statistics are advancing our understanding of complex, nonlinear brain functions where human intuition fails. New kinds of data are accruing at increasing rates, mandating new methods of data analysis and interpretation. To enable progress in theory and data analysis, we must foster collaborations between experimentalists and scientists from statistics, physics, mathematics, engineering, and computer science.
This goal is then discussed in section 2.5, titled, "Theory, Modeling, and Statistics Will Be Essential to Understanding the Brain." That section listed and discussed several "areas that appear promising for the collaborative efforts of theorists and experimentalists:"
- New Statistical and Quantitative Approaches to New Kinds of Data
- Dimensionality and Dynamics in Large‐Scale Population Recordings
- Linking Activity Across Spatial and Temporal Scales
- Flexible Behavior and Decision‐Making
The working group that wrote the report (and which includes Emery Brown) was convened by NIH soon after the announcement of the President's BRAIN Initiative. When released, the report got the most attention for its estimate for the cost of the initiative, $4.5 billion over a decade. (See for example this ScienceInsider piece, "A $4.5 Billion Price Tag for the BRAIN Initiative?")
In April, the ASA released a whitepaper, "Statistical Research and Training Under the BRAIN Initiative," that complements very well the statistical theme of the NIH report. A paraphrasing of the executive summary reads:
Each of the modalities used in brain research—including neuroimaging (radiography, fMRI, MEG, PET), electrophysiology from multiple electrodes (EEG, ECoG, LFP, spike trains), calcium imaging, optical imaging, optogenetics, and anatomical methods (diffusion imaging, electron microscopy, fluorescent microscopy)—produces data with its own set of statistical and analytical challenges that will become more formidable as these techniques are improved and new ones developed. These advances have begun to produce exciting breakthroughs but, to realize their potential, new analysis and computational techniques are needed to optimize data acquisition, manage acquired data on the fly, screen and segment the data, correct for artifacts, and align and register data across multiple time points, multiple experiments, multiple subjects, or different laboratories. In addition, as the data-generation process becomes more complex, and the data sets themselves grow larger and more varied, it is crucial that reliability and scientific relevance of results be assessed against the backdrop of natural variation and measurement noise. This is the essential role of statistical analysis.
To read more about this whitepaper and other ASA whitepapers, see this July
Amstat News article,
Statistical Scientists Advance Federal Research Initiatives. If you'll be at JSM, you can also attend Late-Breaking Session I:
Statistical Science and the President's BRAIN Initiative — Invited Special Presentation on Monday, August 4 at 10:30 am in CC-258C.
In the
FY15 budget request, NIH proposed an increase to $100 million from the $40 million currently funded. The NSF FY15 request doubles NSF’s contribution to the administration’s BRAIN Initiative from $14 million to $29 million. In its FY15 Commerce, Justice Science bill, the House provide strong support for neuroscience at NSF with two paragraphs in the NSF section:
Neuroscience.--NSF is uniquely positioned to advance the nonmedical aspects of cognitive science and neuroscience, particularly through interdisciplinary science, computational models, visualization techniques, innovative technologies and the underlying data and data infrastructure needed to transform our understanding of these areas. The Committee encourages NSF to continue working in conjunction with the IWGN as well as the Brain Research through Advancing Innovative Neurotechnologies (BRAIN) initiative to accelerate understanding of how the brain functions. The recommendation provides an increase of $21,150,000 for research related to the BRAIN initiative and cognitive science and neuroscience research.
Within the amount provided for NSF, funds are also included to support an international conference on neuroscience. This conference should convene government representatives, neuroscience researchers, private entities, non-profit institutions and others to share research and foster collaboration around neuroscience-related activities. The Committee urges NSF to report to the Committee on the results of such conference.
The corresponding Senate bill did not mention the BRAIN initiative or neuroscience. Report language from the appropriations bill that includes NIH is not yet available.
See
other ASA Science Policy blog entries. For ASA science policy updates, follow @ASA_SciPol on Twitter.