Recent developments in genetically encoded indicators of neural activity (GINAs) have greatly advanced the field of systems neuroscience. As they are encoded by DNA, GINAs can be targeted to genetically defined cellular populations. Combined with fluorescence microscopy, most notably multi-photon imaging, GINAs allow chronic simultaneous optical recordings from large populations of neurons or glial cells in awake, behaving mammals, particularly rodents. This large-scale recording of neural activity at multiple temporal and spatial scales has greatly advanced our understanding of the dynamics of neural circuitry underlying behavior-a critical first step toward understanding the complexities of brain function, such as sensorimotor integration and learning. Here, we summarize the recent development and applications of the major classes of GINAs. In particular, we take an in-depth look at the design of available GINA families with a particular focus on genetically encoded calcium indicators (GCaMPs), sensors probing synaptic activity, and genetically encoded voltage indicators. Using the family of the GCaMP as an example, we review established sensor optimization pipelines. We also discuss practical considerations for end users of GINAs about experimental methods including approaches for gene delivery, imaging system requirements, and data analysis techniques. With the growing toolbox of GINAs and with new microscopy techniques pushing beyond their current limits, the age of light can finally achieve the goal of broad and dense sampling of neuronal activity across time and brain structures to obtain a dynamic picture of brain function.

Genetically encoded dopamine sensors based on green fluorescent protein (GFP) enable high-resolution imaging of dopamine dynamics in behaving animals. However, these GFP-based variants cannot be readily combined with commonly used optical sensors and actuators, due to spectral overlap. We therefore engineered red-shifted variants of dopamine sensors called RdLight1, based on mApple. RdLight1 can be combined with GFP-based sensors with minimal interference and shows high photostability, permitting prolonged continuous imaging. We demonstrate the utility of RdLight1 for receptor-specific pharmacological analysis in cell culture, simultaneous assessment of dopamine release and cell-type-specific neuronal activity and simultaneous subsecond monitoring of multiple neurotransmitters in freely behaving rats. Dual-color photometry revealed that dopamine release in the nucleus accumbens evoked by reward-predictive cues is accompanied by a rapid suppression of glutamate release. By enabling multiplexed imaging of dopamine with other circuit components in vivo, RdLight1 opens avenues for understanding many aspects of dopamine biology.

Neuromodulatory systems exert profound influences on brain function. Understanding how these systems modify the operating mode of target circuits requires spatiotemporally precise measurement of neuromodulator release. We developed dLight1, an intensity-based genetically encoded dopamine indicator, to enable optical recording of dopamine dynamics with high spatiotemporal resolution in behaving mice. We demonstrated the utility of dLight1 by imaging dopamine dynamics simultaneously with pharmacological manipulation, electrophysiological or optogenetic stimulation, and calcium imaging of local neuronal activity. dLight1 enabled chronic tracking of learning-induced changes in millisecond dopamine transients in mouse striatum. Further, we used dLight1 to image spatially distinct, functionally heterogeneous dopamine transients relevant to learning and motor control in mouse cortex. We also validated our sensor design platform for developing norepinephrine, serotonin, melatonin, and opioid neuropeptide indicators.

Neuropeptides are ubiquitous in the nervous system. Research into neuropeptides has been limited by a lack of experimental tools that allow for the precise dissection of their complex and diverse dynamics in a circuit-specific manner. Opioid peptides modulate pain, reward and aversion and as such have high clinical relevance. To illuminate the spatiotemporal dynamics of endogenous opioid signaling in the brain, we developed a class of genetically encoded fluorescence sensors based on kappa, delta and mu opioid receptors: κLight, δLight and µLight, respectively. We characterized the pharmacological profiles of these sensors in mammalian cells and in dissociated neurons. We used κLight to identify electrical stimulation parameters that trigger endogenous opioid release and the spatiotemporal scale of dynorphin volume transmission in brain slices. Using in vivo fiber photometry in mice, we demonstrated the utility of these sensors in detecting optogenetically driven opioid release and observed differential opioid release dynamics in response to fearful and rewarding conditions.

Serotonin plays a central role in cognition and is the target of most pharmaceuticals for psychiatric disorders. Existing drugs have limited efficacy; creation of improved versions will require better understanding of serotonergic circuitry, which has been hampered by our inability to monitor serotonin release and transport with high spatial and temporal resolution. We developed and applied a binding-pocket redesign strategy, guided by machine learning, to create a high-performance, soluble, fluorescent serotonin sensor (iSeroSnFR), enabling optical detection of millisecond-scale serotonin transients. We demonstrate that iSeroSnFR can be used to detect serotonin release in freely behaving mice during fear conditioning, social interaction, and sleep/wake transitions. We also developed a robust assay of serotonin transporter function and modulation by drugs. We expect that both machine-learning-guided binding-pocket redesign and iSeroSnFR will have broad utility for the development of other sensors and in vitro and in vivo serotonin detection, respectively.