Connectionists: Brain-like computing fanfare and big data fanfare

Stephen José Hanson jose at psychology.rutgers.edu
Thu Jan 30 08:25:40 EST 2014


Terry,

I think the issue for many of us was the avoidance of Neuroimaging
methods, other than
to do research on new methods with better resolution (217).      Clearly
the Human Connectome
RFP and funded Groups are dominated with fMRI Resting state.   While the
brain initiative is
focused on celluar/circuit research.     

So prior to all the Jim emails.. it does seem there is there is a
concern amoungst imagers why
the advisory group decided exclude neuroimaging.

Steve


 On Wed, 2014-01-29 at 17:06 -0800, Terry Sejnowski wrote:
> There are some misconceptions about the BRAIN Initiative that seem to be 
> driving this discussion and some facts might help focus this issues.
> 
> The NIH advisory group issued an interim report that made recommendations 
> to the director of NIH, which was used to issue the RFAs for FY 2014:
> 
> http://acd.od.nih.gov/presentations/BRAIN-Interim-Report.pdf
> 
> See section 5 on Page 33:
> "Theory, Modeling and Statistics Will Be Essential to
> Understanding the Brain"
> 
> There are many oportunities for those on this list to contribute to the 
> BRAIN Initiative.  Here are a few:
> 
> p. 32: 4. The Importance of Behavior
> "High Priority Research Area for FY2014: Link Neuronal Activity to 
> Behavior. The clever use of virtual reality, machine learning, and 
> miniaturized recording devices has the potential to dramatically increase 
> our understanding of how neuronal activity underlies cognition and 
> behavior. This path can be enabled by developing technologies to quantify 
> and interpret animal behavior, at high temporal and spatial resolution, 
> reliably, objectively, over long periods of time, under a broad set of 
> conditions, and in combination with concurrent measurement and 
> manipulation of neuronal activity."
> 
> p. 35:  New Statistical and Quantitative Approaches to New Kinds of Data 
> "As new kinds of data become available through advances in molecular 
> sensors and optical recording, equal effort must be expended to extract 
> maximum insight from these novel data sets. Data analytic and theoretical 
> problems are likely to emerge that we cannot anticipate at the present 
> time. Resources should be available for experts from essential disciplines 
> such as statistics, optimization, signal processing and machine learning 
> to develop new approaches to identifying and analyzing the relevant 
> signals."
> 
> p. 16: "The BRAIN Initiative will deliver transformative scientific tools 
> and methods that should accelerate all of basic neuroscience, 
> translational neuroscience, and direct disease studies, as well as biology 
> beyond neuroscience. It will deliver a foundation of knowledge about the 
> function of the normal brain, its cellular components, the wiring of its 
> circuits, its patterns of electrical activity at local and global scales, 
> the causes and effects of those activity patterns, and the expression of 
> brain activity in behavior. Through the interaction of experiment and 
> theory, the BRAIN Initiative should elucidate the computational logic as 
> well as the specific mechanisms of brain function at different spatial and 
> temporal scales, defining the connections between molecules, neurons, 
> circuits, activity, and behavior."
> 
> p. 5: Recomendation #1. Generate a Census of Cell Types. We do not know 
> how many types of neurons and glia there are. Two neurons with the same 
> morphology could project to different areas and have different functions. 
> Classification of cell types will depend on analyzing the high-dimensional 
> transcriptome and proteome of single cells and combining this with 
> anatomical and physiolgical data.  Why is this important?  Experimenters 
> need to label and manipulate each cell type to discover its function. 
> There are deep issues of what constitutes cell identity that need to be 
> settled, which will depend on analyzing the distribution of heterogeneous 
> data in high-dimensional spaces.
> 
> p. 50 8d. Establish Platforms for Sharing Data
> The goal of the BRAIN Initiative is not to create big data sets.  This is 
> already happening in neuroscience, as it is in every area of science. One 
> of the recommendations is to make it easier for neuroscientists to share 
> their data so others can analyze them.
> 
> This is an interim report.  The final report, due in June 2014, will have 
> more specific priorities, milestones and goals for each of the 
> recommendations.
> 
> Note also that there are 3 agencies involved in the BRAIN Initiative. 
> NSF has not yet announced its program. DARPA has announced 2 BAAs:
> 
> http://www.cccblog.org/2013/12/02/darpa-announces-two-programs-as-part-of-white-house-brain-initiative/
> 
> Finally, new money for the BRAIN Initiative was set aside in the budget 
> that was recently passed by Congress.
> 
> Terry
> 
> -----
> 

-- 
Stephen José Hanson
Director RUBIC (Rutgers Brain Imaging Center)
Professor of Psychology
Member of Cognitive Science Center (NB)
Member EE Graduate Program (NB)
Member CS Graduate Program (NB)
Rutgers University 


email: jose at psychology.rutgers.edu
web: psychology.rutgers.edu/~jose
lab: www.rumba.rutgers.edu
fax: 866-434-7959
voice: 973-353-3313 (RUBIC)
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