The Neurodata Without Borders (NWB) initiative promotes data standardization in neuroscience to increase research reproducibility and opportunities. In the first NWB pilot project, neurophysiologists and software developers produced a common data format for recordings and metadata of cellular electrophysiology and optical imaging experiments. The format specification, application programming interfaces, and sample datasets have been released.

Summary Advances in technology are opening new windows on the structural connectivity and functional dynamics of brain circuits. Quantitative frameworks are needed that integrate these data from anatomy and physiology. Here we present a modeling approach that creates such a link. The goal is to infer the structure of a neural circuit from sparse neural recordings, using partial knowledge of its anatomy as a regularizing constraint. We recorded visual responses from the output neurons of the retina, the ganglion cells. We then generated a systematic sequence of circuit models that represent retinal neurons and connections, and fitted them to the experimental data. The optimal models faithfully recapitulated the ganglion cell outputs. More importantly, they made predictions about dynamics and connectivity among unobserved neurons internal to the circuit, and these were subsequently confirmed by experiment. This circuit inference framework promises to facilitate the integration and understanding of big data in neuroscience.

Bipolar cells (BCs) form parallel channels that carry visual signals from the outer to the inner retina. Each BC type is thought to carry a distinct visual message to select types of amacrine cells (ACs) and ganglion cells (GCs). However, the number of GC types exceeds that of BCs providing their input, suggesting that BC signals diversify on transmission to GCs. Here we explored in the salamander retina how signals from individual BCs feed into multiple GCs, and found that each BC could evoke distinct responses among GCs, differing in kinetics, adaptation, and rectification properties. This signal divergence results primarily from interactions with ACs that allow each BC to send distinct signals to its target GCs. Our results indicate that individual BC-GC connections have distinct transfer functions. This expands the number of visual channels in the inner retina and enhances the computational power and feature selectivity of early visual processing.

Acoustic processing requires integration over time. We have used in vivo intracellular recording to measure neuronal integration times in anesthetized rats. Using natural sounds and other stimuli, we found that synaptic inputs to auditory cortical neurons showed a rather long context dependence, up to > or =4 s (tau approximately 1 s), even though sound-evoked excitatory and inhibitory conductances per se rarely lasted greater, similar 100 ms. Thalamic neurons showed only a much faster form of adaptation with a decay constant tau <100 ms, indicating that the long-lasting form originated from presynaptic mechanisms in the cortex, such as synaptic depression. Restricting knowledge of the stimulus history to only a few hundred milliseconds reduced the predictable response component to about half that of the optimal infinite-history model. Our results demonstrate the importance of long-range temporal effects in auditory cortex and suggest a potential neural substrate for auditory processing that requires integration over timescales of seconds or longer, such as stream segregation.