One of the major limitations in the current set of techniques available to neuroscientists is a dearth of methods for imaging individual cells deep within the brains of live animals. To overcome this limitation, we developed two forms of minimally invasive fluorescence microendoscopy and tested their abilities to image cells in vivo. Both one- and two-photon fluorescence microendoscopy are based on compound gradient refractive index (GRIN) lenses that are 350-1,000 microm in diameter and provide micron-scale resolution. One-photon microendoscopy allows full-frame images to be viewed by eye or with a camera, and is well suited to fast frame-rate imaging. Two-photon microendoscopy is a laser-scanning modality that provides optical sectioning deep within tissue. Using in vivo microendoscopy we acquired video-rate movies of thalamic and CA1 hippocampal red blood cell dynamics and still-frame images of CA1 neurons and dendrites in anesthetized rats and mice. Microendoscopy will help meet the growing demand for in vivo cellular imaging created by the rapid emergence of new synthetic and genetically encoded fluorophores that can be used to label specific brain areas or cell classes.

The advent of methods for optical imaging of large-scale neural activity at cellular resolution in behaving animals presents the problem of identifying behavior-encoding cells within the resulting image time series. Rapid and precise identification of cells with particular neural encoding would facilitate targeted activity measurements and perturbations useful in characterizing the operating principles of neural circuits. Here we report a regression-based approach to semiautomatically identify neurons that is based on the correlation of fluorescence time series with quantitative measurements of behavior. The approach is illustrated with a novel preparation allowing synchronous eye tracking and two-photon laser scanning fluorescence imaging of calcium changes in populations of hindbrain neurons during spontaneous eye movement in the larval zebrafish. Putative velocity-to-position oculomotor integrator neurons were identified that showed a broad spatial distribution and diversity of encoding. Optical identification of integrator neurons was confirmed with targeted loose-patch electrical recording and laser ablation. The general regression-based approach we demonstrate should be widely applicable to calcium imaging time series in behaving animals.

In a neural integrator, the variability and topographical organization of neuronal firing rate persistence can provide information about the circuit’s functional architecture. Here we use optical recording to measure the time constant of decay of persistent firing (“persistence time”) across a population of neurons comprising the larval zebrafish oculomotor velocity-to-position neural integrator. We find extensive persistence time variation (10-fold; coefficients of variation 0.58–1.20) across cells within individual larvae. We also find that the similarity in firing between two neurons decreased as the distance between them increased and that a gradient in persistence time was mapped along the rostrocaudal and dorsoventral axes. This topography is consistent with the emergence of persistence time heterogeneity from a circuit architecture in which nearby neurons are more strongly interconnected than distant ones. Collectively, our results can be accounted for by integrator circuit models characterized by multiple dimensions of slow firing rate dynamics.

In neural integrators, transient inputs are accumulated into persistent firing rates that are a neural correlate of short-term memory. Integrators often contain two opposing cell populations that increase and decrease sustained firing as a stored parameter value rises. A leading hypothesis for the mechanism of persistence is positive feedback through mutual inhibition between these opposing populations. We tested predictions of this hypothesis in the goldfish oculomotor velocity-to-position integrator by measuring the eye position and firing rates of one population, while pharmacologically silencing the opposing one. In complementary experiments, we measured responses in a partially silenced single population. Contrary to predictions, induced drifts in neural firing were limited to half of the oculomotor range. We built network models with synaptic-input thresholds to demonstrate a new hypothesis suggested by these data: mutual inhibition between the populations does not provide positive feedback in support of integration, but rather coordinates persistent activity intrinsic to each population.Persistent neural activity refers to a sustained discharge of action potentials that long outlasts a briefly presented stimulus, thus representing a short-term memory of the external cue. In neural integrator circuits, populations of neurons exhibiting graded levels of persistent activity store an accumulation of the stimulus over time: that is, a temporal integral. Neural integrators have been characterized at many levels of the nervous system, from brainstem to cortex 1-3 .