Putting big data to good use in neuroscience

Abstract

Big data has transformed fields such as physics and genomics. Neuroscience is set to collect its own big data sets, but to exploit its full potential, there need to be ways to standardize, integrate and synthesize diverse types of data from different levels of analysis and across species. This will require a cultural shift in sharing data across labs, as well as to a central role for theorists in neuroscience research.

Figure 1

The spatiotemporal domain of neuroscience and of the main methods available for the study of the nervous system in 2014. Each colored region represents the useful domain of spatial and temporal resolution for one method available for the study of the brain. Open regions represent measurement techniques; filled regions, perturbation techniques. Inset, a cartoon rendition of the methods available in 1988, notable for the large gaps where no useful method existed. The regions allocated to each domain are somewhat arbitrary and represent our own estimates. EEG, electroencephalography; MEG, magnetoencephalography; PET, positron emission tomography; VSD, voltage-sensitive dye; TMS, transcranial magnetic stimulation; 2-DG, 2-deoxyglucose.