Deep-brain optical recording of neural dynamics during behavior

Recent advances in light patterned optogenetic photostimulation in freely moving mice

Optogenetics opened the door to a new era of neuroscience. New optical developments are under way to enable high-resolution neuronal activity imaging and selective photostimulation of neuronal ensembles in freely moving animals. These advancements could allow researchers to interrogate, with cellular precision, functionally relevant neuronal circuits in the framework of naturalistic brain activity. We provide an overview of the current state-of-the-art of imaging and photostimulation in freely moving rodents and present a road map for future optical and engineering developments toward miniaturized microscopes that could reach beyond the currently existing systems.

Cell Signaling in the Circadian Pacemaker: New Insights from in vivo Imaging

BACKGROUND

"One for all, and all for one," the famous rallying cry of the Three Musketeers, in Alexandre Dumas's popular novel, certainly applies to the 20,000 cells composing the suprachiasmatic nuclei (SCN). These cells work together to form the central clock that coordinates body rhythms in tune with the day-night cycle. Like virtually every body cell, individual SCN cells exhibit autonomous circadian oscillations, but this rhythmicity only reaches a high level of precision and robustness when the cells are coupled with their neighbors. Therefore, understanding the functional network organization of SCN cells beyond their core rhythmicity is an important issue in circadian biology.

SUMMARY

The present review summarizes the main results from our recent study demonstrating the feasibility of recording SCN cells in freely moving mice and the significance of variations in intracellular calcium over several timescales.

KEY MESSAGE

We discuss how in vivo imaging at the cell level will be pivotal to interrogate the mammalian master clock, in an integrated context that preserves the SCN network organization, with intact inputs and outputs.

An integrated microfluidic and fluorescence platform for probing in vivo neuropharmacology

Neurotechnologies and genetic tools for dissecting neural circuit functions have advanced rapidly over the past decade, although the development of complementary pharmacological method-ologies has comparatively lagged. Understanding the precise pharmacological mechanisms of neuroactive compounds is critical for advancing basic neurobiology and neuropharmacology, as well as for developing more effective treatments for neurological and neuropsychiatric disorders. However, integrating modern tools for assessing neural activity in large-scale neural networks with spatially localized drug delivery remains a major challenge. Here, we present a dual microfluidic-photometry platform that enables simultaneous intracranial drug delivery with neural dynamics monitoring in the rodent brain. The integrated platform combines a wireless, battery-free, miniaturized fluidic microsystem with optical probes, allowing for spatially and temporally specific drug delivery while recording activity-dependent fluorescence using genetically encoded calcium indicators (GECIs), neurotransmitter sensors GRAB NE and GRAB DA , and neuropeptide sensors. We demonstrate the performance this platform for investigating neuropharmacological mechanisms in vivo and characterize its efficacy in probing precise mechanistic actions of neuroactive compounds across several rapidly evolving neuroscience domains.

An opponent striatal circuit for distributional reinforcement learning

Machine learning research has achieved large performance gains on a wide range of tasks by expanding the learning target from mean rewards to entire probability distributions of rewards - an approach known as distributional reinforcement learning (RL)1. The mesolimbic dopamine system is thought to underlie RL in the mammalian brain by updating a representation of mean value in the striatum2,3, but little is known about whether, where, and how neurons in this circuit encode information about higher-order moments of reward distributions4. To fill this gap, we used high-density probes (Neuropixels) to acutely record striatal activity from well-trained, water-restricted mice performing a classical conditioning task in which reward mean, reward variance, and stimulus identity were independently manipulated. In contrast to traditional RL accounts, we found robust evidence for abstract encoding of variance in the striatum. Remarkably, chronic ablation of dopamine inputs disorganized these distributional representations in the striatum without interfering with mean value coding. Two-photon calcium imaging and optogenetics revealed that the two major classes of striatal medium spiny neurons - D1 and D2 MSNs - contributed to this code by preferentially encoding the right and left tails of the reward distribution, respectively. We synthesize these findings into a new model of the striatum and mesolimbic dopamine that harnesses the opponency between D1 and D2 MSNs5-15 to reap the computational benefits of distributional RL.