@article {2542, title = {New Data Science tools for analyzing neural data and computational models}, year = {2016}, abstract = {

As the amount of data collected by neuroscientists continues to increase (Stevenson et al, 2011), new tools are needed to turn this data into insights into about the algorithms that underlie complex behavior (Brown et al, 2004). Here we present our latest research on computational tools we have developed at Hampshire College and at the Center for Brains, Minds and Machines at MIT. In particular, we describe new tools for neural population decoding including a graphical user interface to the Neural Decoding Toolbox (Meyers 2013), methods for analyzing single neurons, and ongoing work on a parallelized population decoding framework that uses R and Apache Spark{\texttrademark} to greatly increase the speed of population decoding. We also discuss CBaaS, which is a distributed platform that allows one to evaluate the effectiveness of different computational models (such as different versions of deep neural networks). These tools will allow researchers to gain deeper insights from the data they collect, and to better assess whether computational models are acting in similar ways to biological systems.\ 

}, author = {Ethan Meyers and Mike Dean and Gregory J Hale} } @article {460, title = {Neural ensemble communities: open-source approaches to hardware for large-scale electrophysiology}, journal = {Current Opinion in Neurobiology}, volume = {32}, year = {2015}, month = {01/2015}, pages = {53 - 59}, abstract = {

One often-overlooked factor when selecting a platform for largescale electrophysiology is whether or not a particular data acquisition system is {\textquoteleft}open{\textquoteright} or {\textquoteleft}closed{\textquoteright}: that is, whether or not the system{\textquoteright}s schematics and source code are available to end users. Open systems have a reputation for being difficult to acquire, poorly documented, and hard to maintain. With the arrival of more powerful and compact integrated circuits, rapid prototyping services, and web-based tools for collaborative development, these stereotypes must be reconsidered. We discuss some of the reasons why multichannel extracellular electrophysiology could benefit from open-source approaches and describe examples of successful community-driven tool development within this field. In order to promote the adoption of open-source hardware and to reduce the need for redundant development efforts, we advocate a move toward standardized interfaces that connect each element of the data processing pipeline. This will give researchers the flexibility to modify their tools when necessary, while allowing them to continue to benefit from the high-quality products and expertise provided by commercial vendors.

Available online 17 December 2014

In Print:\  June 2015

}, issn = {09594388}, doi = {10.1016/j.conb.2014.11.004}, url = {http://www.sciencedirect.com/science/article/pii/S0959438814002268}, author = {Siegle, Joshua H and Gregory J Hale and Jonathan P Newman and Voigts, Jakob} }