The ventral pallidum (VP) is a central hub in the reward circuitry with diverse projections that have different behavioral roles attributed mostly to the connectivity with the downstream target. However, different VP projections may represent, as in the striatum, separate neuronal populations that differ in more than just connectivity. In this study, we performed in mice of both sexes a multimodal dissection of four major projections of the VP-to the lateral hypothalamus (VP→LH), ventral tegmental area (VP→VTA), lateral habenula (VP→LHb), and mediodorsal thalamus (VP→MDT)-with physiological, anatomical, genetic, and behavioral tools. We also tested for physiological differences between VP neurons receiving input from nucleus accumbens medium spiny neurons (MSNs) that express either the D1 (D1-MSNs) or the D2 (D2-MSNs) dopamine receptor. We show that each VP projection (1) when inhibited during a cocaine conditioned place preference (CPP) test affects performance differently, (2) receives a different pattern of inputs using rabies retrograde labeling, (3) shows differentially expressed genes using RNA sequencing, and (4) has projection-specific characteristics in excitability and synaptic input characteristics using whole-cell patch clamp. VP→LH and VP→VTA projections have different effects on CPP and show low overlap in circuit tracing experiments, as VP→VTA neurons receive more striatal input, while VP→LH neurons receive more olfactory input. Additionally, VP→VTA neurons are less excitable, while VP→LH neurons are more excitable than the average VP neuron, a difference driven mainly by D2-MSN-responding neurons. Thus, VP→VTA and VP→LH neurons may represent largely distinct populations of VP neurons.

High-density probes allow electrophysiological recordings from many neurons simultaneously across entire brain circuits but don\'t reveal cell type. Here, we develop a strategy to identify cell types from extracellular recordings in awake animals, revealing the computational roles of neurons with distinct functional, molecular, and anatomical properties. We combine optogenetic activation and pharmacology using the cerebellum as a testbed to generate a curated ground-truth library of electrophysiological properties for Purkinje cells, molecular layer interneurons, Golgi cells, and mossy fibers. We train a semi-supervised deep-learning classifier that predicts cell types with greater than 95% accuracy based on waveform, discharge statistics, and layer of the recorded neuron. The classifier\'s predictions agree with expert classification on recordings using different probes, in different laboratories, from functionally distinct cerebellar regions, and across animal species. Our classifier extends the power of modern dynamical systems analyses by revealing the unique contributions of simultaneously-recorded cell types during behavior.

Mapping neuronal circuits that generate focal to bilateral tonic-clonic seizures is essential for understanding general principles of seizure propagation and modifying the risk of death and injury due to bilateral motor seizures. We used novel techniques developed over the past decade to study these circuits. We propose the general hypothesis that at the mesoscale, seizures follow anatomical projections of the seizure focus, preferentially activating more excitable neurons.

In mammalian cortex, feedforward excitatory connections recruit feedforward inhibition. This is often carried by parvalbumin (PV+) interneurons, which may densely connect to local pyramidal (Pyr) neurons. Whether this inhibition affects all local excitatory cells indiscriminately or is targeted to specific subnetworks is unknown. Here, we test how feedforward inhibition is recruited by using two-channel circuit mapping to excite cortical and thalamic inputs to PV+ interneurons and Pyr neurons to mouse primary vibrissal motor cortex (M1). Single Pyr and PV+ neurons receive input from both cortex and thalamus. Connected pairs of PV+ interneurons and excitatory Pyr neurons receive correlated cortical and thalamic inputs. While PV+ interneurons are more likely to form local connections to Pyr neurons, Pyr neurons are much more likely to form reciprocal connections with PV+ interneurons that inhibit them. This suggests that Pyr and PV ensembles may be organized based on their local and long-range connections, an organization that supports the idea of local subnetworks for signal transduction and processing. Excitatory inputs to M1 can thus target inhibitory networks in a specific pattern which permits recruitment of feedforward inhibition to specific subnetworks within the cortical column.

Intracortical inhibition in motor cortex (M1) regulates movement and motor learning. If cortical and thalamic inputs target different inhibitory cell types in different layers, then these afferents may play different roles in regulating M1 output. Using mice of both sexes, we quantified input to two main classes of M1 interneurons, parvalbumin+ (PV+) cells and somatostatin+ (SOM+) cells, using monosynaptic rabies tracing. We then compared anatomic and functional connectivity based on synaptic strength from sensory cortex and thalamus. Functionally, each input innervated M1 interneurons with a unique laminar profile. Different interneuron types were excited in a distinct, complementary manner, suggesting feedforward inhibition proceeds selectively via distinct circuits. Specifically, somatosensory cortex (S1) inputs primarily targeted PV+ neurons in upper layers (L2/3) but SOM+ neurons in middle layers (L5). Somatosensory thalamus [posterior nucleus (PO)] inputs targeted PV+ neurons in middle layers (L5). In contrast to sensory cortical areas, thalamic input to SOM+ neurons was equivalent to that of PV+ neurons. Thus, long-range excitatory inputs target inhibitory neurons in an area and a cell type-specific manner, which contrasts with input to neighboring pyramidal cells. In contrast to feedforward inhibition providing generic inhibitory tone in cortex, circuits are selectively organized to recruit inhibition matched to incoming excitatory circuits.SIGNIFICANCE STATEMENT M1 integrates sensory information and frontal cortical inputs to plan and control movements. Although inputs to excitatory cells are described, the synaptic circuits by which these inputs drive specific types of M1 interneurons are unknown. Anatomical results with rabies tracing and physiological quantification of synaptic strength shows that two main classes of inhibitory cells (PV+ and SOM+ interneurons) both receive substantial cortical and thalamic input, in contrast to interneurons in sensory areas (where thalamic input strongly prefers PV+ interneurons). Further, each input studied targets PV+ and SOM+ interneurons in a different fashion, suggesting that separate, specific circuits exist for recruitment of feedforward inhibition.

To understand the function of neuronal circuits, it is crucial to disentangle the connectivity patterns within the network. However, most tools currently used to explore connectivity have low throughput, low selectivity, or limited accessibility. Here, we report the development of an improved packaging system for the production of the highly neurotropic RVdGenvA-CVS-N2c rabies viral vectors, yielding titers orders of magnitude higher with no background contamination, at a fraction of the production time, while preserving the efficiency of transsynaptic labeling. Along with the production pipeline, we developed suites of \'starter\' AAV and bicistronic RVdG-CVS-N2c vectors, enabling retrograde labeling from a wide range of neuronal populations, tailored for diverse experimental requirements. We demonstrate the power and flexibility of the new system by uncovering hidden local and distal inhibitory connections in the mouse hippocampal formation and by imaging the functional properties of a cortical microcircuit across weeks. Our novel production pipeline provides a convenient approach to generate new rabies vectors, while our toolkit flexibly and efficiently expands the current capacity to label, manipulate and image the neuronal activity of interconnected neuronal circuits in vitro and in vivo.

Dopaminergic neurons in the substantia nigra pars compacta (SNc) differentially degenerate in Parkinson\'s Disease, with the ventral region degenerating more severely than the dorsal region. Compared with the dorsal neurons, the ventral neurons in the SNc have distinct dendritic morphology, electrophysiological characteristics, and circuit connections with the basal ganglia. These characteristics shape information processing in the ventral SNc and structure the balance of inhibition and disinhibition in the striatonigral circuitry. In this paper, I review foundational studies and recent work comparing the circuitry of the ventral and dorsal SNc neurons and discuss how loss of the ventral neurons early in Parkinson\'s Disease could affect the overall balance of inhibition and disinhibition of dopamine signals.

Decades of research have revealed the remarkable complexity of the midbrain dopamine (DA) system, which comprises cells principally located in the ventral tegmental area (VTA) and substantia nigra pars compacta (SNc). Neither homogenous nor serving a singular function, the midbrain DA system is instead composed of distinct cell populations that (1) receive different sets of inputs, (2) project to separate forebrain sites, and (3) are characterized by unique transcriptional and physiological signatures. To appreciate how these differences relate to circuit function, we first need to understand the anatomical connectivity of unique DA pathways and how this connectivity relates to DA-dependent motivated behavior. We and others have provided detailed maps of the input-output relationships of several subpopulations of midbrain DA cells and explored the roles of these different cell populations in directing behavioral output. In this study, we analyze VTA inputs and outputs as a high dimensional dataset (10 outputs, 22 inputs), deploying computational techniques well-suited to finding interpretable patterns in such data. In addition to reinforcing our previous conclusion that the connectivity in the VTA is dependent on spatial organization, our analysis also uncovered a set of inputs elevated onto each projection-defined VTADA cell type. For example, VTADA→NAcLat cells receive preferential innervation from inputs in the basal ganglia, while VTADA→Amygdala cells preferentially receive inputs from populations sending a distributed input across the VTA, which happen to be regions associated with the brain\'s stress circuitry. In addition, VTADA→NAcMed cells receive ventromedially biased inputs including from the preoptic area, ventral pallidum, and laterodorsal tegmentum, while VTADA→mPFC cells are defined by dominant inputs from the habenula and dorsal raphe. We also go on to show that the biased input logic to the VTADA cells can be recapitulated using projection architecture in the ventral midbrain, reinforcing our finding that most input differences identified using rabies-based (RABV) circuit mapping reflect projection archetypes within the VTA.

Transplantation in Parkinson\'s disease using human embryonic stem cell (hESC)-derived dopaminergic (DA) neurons is a promising future treatment option. However, many of the mechanisms that govern their differentiation, maturation, and integration into the host circuitry remain elusive. Here, we engrafted hESCs differentiated toward a ventral midbrain DA phenotype into the midbrain of a preclinical rodent model of Parkinson\'s disease. We then injected a novel DA-neurotropic retrograde MNM008 adeno-associated virus vector capsid, into specific DA target regions to generate starter cells based on their axonal projections. Using monosynaptic rabies-based tracing, we demonstrated for the first time that grafted hESC-derived DA neurons receive distinctly different afferent inputs depending on their projections. The similarities to the host DA system suggest a previously unknown directed circuit integration. By evaluating the differential host-to-graft connectivity based on projection patterns, this novel approach offers a tool to answer outstanding questions regarding the integration of grafted hESC-derived DA neurons.

In this issue of Neuron, Petersen et al. (2021) introduce CellExplorer, an open-source tool to integrate neurophysiological metrics of neuronal activity from circuits to behavior. Together with other neuroinformatic resources, it may facilitate community-based multidisciplinary characterization of brain cell types.