Voltage imaging has emerged as a powerful tool for recording membrane potential changes in living cells, offering a direct measurement of rapid neuronal events with high temporal precision. Since the brain is a three-dimensional circuit, it is essential to record signals across a volume. However, achieving effective three-dimensional voltage imaging over large neuronal populations remains challenging due to the need for high imaging speed, high signal-to-noise ratio, and extensive volume coverage. In this study, we demonstrate in vivo three-dimensional voltage imaging in larval zebrafish using oblique plane microscopy and QFDBD-QUAS-driven expression of the genetically encoded voltage indicator Ace-mNeon2-Kv2.1, achieving volumetric imaging rates of up to 200 volumes per second (VPS). This approach enables dye-free voltage imaging, simplifying experimental workflows and improving the reproducibility of in vivo voltage imaging experiments for investigating neuronal circuit dynamics in the living zebrafish animal model.

The neurotransmitter acetylcholine (ACh) is essential in both the central and peripheral nervous systems. Recent studies highlight the significance of interactions between ACh and various neuromodulators in regulating complex behaviors. The ability to simultaneously image ACh and other neuromodulators can provide valuable information regarding the mechanisms underlying these behaviors. Here we developed a series of red fluorescent G-protein-coupled receptor activation-based ACh sensors, with a wide detection range and expanded spectral profile. The high-affinity sensor rACh1h reliably detects ACh release in various brain regions, including the nucleus accumbens, amygdala, hippocampus and cortex. Moreover, rACh1h can be coexpressed with green fluorescent sensors to record ACh release together with other neurochemicals in various behavioral contexts using fiber photometry, mesoscopic imaging and two-photon imaging with high spatiotemporal resolution.

Many open questions about neural circuit and systems function could be answered if spikes and synaptic potentials could be accurately measured from many neurons simultaneously in a given network with cell-type specificity, cellular resolution, and at the millisecond time scale. Voltage imaging with genetically encoded voltage indicators (GEVIs) has advanced to the point that this is now possible for small networks or sparsely labeled neurons, and emerging optical methods promise to soon enable imaging from larger, dense cell populations. This review describes recent discoveries made using GEVIs to understand local and propagating cortical activity, network oscillations, and cortical and hippocampal microcircuit dynamics, and outlines several promising future applications in systems neuroscience.

Voltage dynamics in dendrites, which result both from integrating synaptic inputs and back-propagating action potentials (bAPs) from the soma, contribute to plasticity. Mapping these dynamics in the dendritic arbors of live animals is crucial for understanding neuronal computation and plasticity rules. Here we combine targeted channelrhodopsin activation with dual-plane structured illumination voltage imaging for simultaneous monitoring of dendritic and somatic voltage response dynamics in cortical layer 2/3 pyramidal neurons in anesthetized and awake mice. We examined the integration of synaptic inputs and compared the dynamics of optogenetically evoked, spontaneous and sensory-evoked subthreshold and bAP dynamics. Our measurements revealed a broadly correlated membrane voltage throughout the dendritic arbor and only weak signatures of electrical compartmentalization within individual dendritic branches. However, we observed strong spiking-history-dependent modulation of bAP propagation into distal dendrites. We propose that this dendritic filtering of bAPs may have a critical role in the regulation of bursting and in activity-dependent plasticity.

Animals integrate knowledge about how the state of the environment evolves to choose actions that maximise reward. Such goal-directed behaviour - or model-based (MB) reinforcement learning (RL) - can flexibly adapt choice to changes, being thus distinct from simpler habitual - or model-free (MF) RL - strategies. Previous inactivation and neuroimaging work implicates prefrontal cortex (PFC) and the caudate striatal region in MB-RL; however, details are scarce about its implementation at the single-neuron level. Here, we recorded from two PFC regions - the dorsal anterior cingulate cortex (ACC) and dorsolateral PFC (DLPFC), and two striatal regions, caudate and putamen - while two rhesus macaques performed a sequential decision-making (two-step) task in which MB-RL involves knowledge about the statistics of reward and state transitions. All four regions, but particularly the ACC, encoded the rewards received and tracked the probabilistic state transitions that occurred. However, ACC (and to a lesser extent caudate) encoded the key variables of the task - namely the interaction between reward, transition, and choice - which underlies MB decision-making. ACC and caudate neurons also encoded MB-derived estimates of choice values. Moreover, caudate value estimates of the choice options flipped when a rare transition occurred, demonstrating value update based on structural knowledge of the task. The striatal regions were unique (relative to PFC) in encoding the current and previous rewards with opposing polarities, reminiscent of dopaminergic neurons, and indicative of an MF prediction error. Our findings provide a deeper understanding of selective and temporally dissociable neural mechanisms underlying goal-directed behaviour.

Dopamine is essential for striatal function and learning. Striatal dopamine release can be triggered by dopamine cell firing, but also by coordinated cholinergic interneuron activity, which stimulates dopamine release via presynaptic nicotinic acetylcholine receptors on dopamine axons. While acetylcholine-dependent dopamine release is well-documented ex vivo and under artificial optogenetic stimulation in vivo, its role during natural behavior has remained unclear. One possible endogenous driver of acetylcholine-dependent dopamine release is thalamic input, which provides strong excitatory drive to cholinergic interneurons. To examine whether thalamic input provokes acetylcholine-dependent dopamine release during behavior, we performed simultaneous fiber photometry recordings of striatal dopamine (GRAB-rDA3m) and thalamic axon activity (gCaMP8m) in the dorsomedial (DMS) and dorsolateral striatum (DLS) of mice learning the accelerating rotarod, a striatal-dependent task that demands precise and effortful motor control. Recordings were obtained on- and off-task and across days of training to capture the full arc of learning. Dopamine transients in DMS, but not DLS, were frequently coupled to peaks in thalamic axon activity via an acetylcholine-dependent mechanism. The occurrence of these thalamic-evoked DMS dopamine transients depended on learning, task engagement, and the recent history of dopamine activity, but did not contribute to motor error signals. Together, these findings establish thalamic input as a physiological driver of acetylcholine-dependent dopamine release in DMS. Moreover, they reveal that striatal sensitivity to this local release mechanism is dynamically gated by dopaminergic history, providing a compelling framework for understanding how local and soma-triggered dopamine signals are coordinated to support learning.

High-resolution extracellular electrophysiology is the gold standard for recording spikes from distributed neural populations and is especially powerful when combined with optogenetics for manipulation of specific cell types with high temporal resolution. We integrated these approaches into prototype Neuropixels Opto probes, which combine electronic and photonic circuits. These devices pack 960 electrical recording sites and two sets of 14 light emitters onto a 70-μm-wide, 1-cm-long shank, allowing spatially addressable optogenetic stimulation with blue and red light. In mouse cortex, Neuropixels Opto probes delivered high-quality recordings together with spatially addressable optogenetics, differentially activating or silencing neurons at distinct cortical depths. In the mouse striatum and other deep structures, Neuropixels Opto probes delivered efficient optotagging, facilitating the identification of two cell types in parallel. Neuropixels Opto probes represent a promising tool for recording, identifying and manipulating neuronal populations.