Probes for INS

Cues that predict the availability of food rewards influence motivational states and elicit food-seeking behaviors. If a cue no longer predicts food availability, animals may adapt accordingly by inhibiting food seeking responses. Sparsely activated sets of neurons, coined neuronal ensembles, have been shown to encode the strength of reward-cue associations. While alterations in intrinsic excitability have been shown to underlie many learning and memory processes, little is known about these properties specifically on cue-activated neuronal ensembles. We examined the activation patterns of cue-activated orbitofrontal cortex (OFC) and nucleus accumbens (NAc) shell ensembles using wild-type and Fos-GFP mice following appetitive conditioning with sucrose and extinction learning. We also investigated the neuronal excitability of recently activated, GFP+ neurons in these brain areas using whole-cell electrophysiology in brain slices. Exposure to a sucrose cue elicited activation of neurons in both the NAc shell and OFC. In the NAc shell, but not the OFC, these activated GFP+ neurons were more excitable than surrounding GFP- neurons. Following extinction, the number of neurons activated in both areas was reduced and activated ensembles in neither area exhibited altered excitability. These data suggest that learning-induced alterations in the intrinsic excitability of neuronal ensembles is regulated dynamically across different brain areas. Furthermore, we show that changes in associative strength modulate the excitability profile of activated ensembles in the NAc shell.SIGNIFICANCE STATEMENTSparsely distributed sets of neurons called 'neuronal ensembles' encode learned associations about food and cues predictive of its availability. Widespread changes in neuronal excitability have been observed in limbic brain areas after associative learning, but little is known about the excitability changes that occur specifically on neuronal ensembles that encode appetitive associations. Here we reveal that sucrose cue exposure recruited a more excitable ensemble in the nucleus accumbens, but not orbitofrontal cortex compared to their surrounding neurons. This excitability difference was not observed when the cue's salience was diminished following extinction learning. These novel data provide evidence that the intrinsic excitability of appetitive memory-encoding ensembles is differentially regulated across brain areas and dynamically adapts to changes in associative strength.

Repetitive behaviors are diagnostic for autism spectrum disorder (ASD) and commonly observed in other neurodevelopmental disorders. Currently, there are no effective pharmacological treatments for repetitive behavior in these clinical conditions. This is due to the lack of information about the specific neural circuitry that mediates the development and expression of repetitive behavior. Our previous work in mouse models has linked repetitive behavior to decreased activation of the subthalamic nucleus, a brain region in the indirect and hyperdirect pathways in the basal ganglia circuitry. The present experiments were designed to further test our hypothesis that pharmacological activation of the indirect pathway would reduce repetitive behavior. We used a combination of adenosine A1 and A2A receptor agonists that have been shown to alter the firing frequency of dorsal striatal neurons within the indirect pathway of the basal ganglia. This drug combination markedly and selectively reduced repetitive behavior in both male and female C58 mice over a six-hour period, an effect that required both A1 and A2A agonists as neither alone reduced repetitive behavior. The adenosine A1 and A2A receptor agonist combination also significantly increased the number of Fos transcripts and Fospositive cells in dorsal striatum. Fos induction was found in both direct and indirect pathway neurons suggesting that the drug combination restored the balance of activation across these complementary basal ganglia pathways. The adenosine A1 and A2A receptor agonist combination also maintained its effectiveness in reducing repetitive behavior over a 7-day period. These findings point to novel potential therapeutic targets for development of drug therapies for repetitive behavior in clinical disorders.

Major depressive disorder (MDD) patients display a common but often variable set of symptoms making successful, sustained treatment difficult to achieve. Separate depressive symptoms may be encoded by differential changes in distinct circuits in the brain, yet how discrete circuits underlie behavioral subsets of depression and how they adapt in response to stress has not been addressed. We identify two discrete circuits of parvalbumin-positive (PV) neurons in the ventral pallidum (VP) projecting to either the lateral habenula or ventral tegmental area contributing to depression. We find that these populations undergo different electrophysiological adaptations in response to social defeat stress, which are normalized by antidepressant treatment. Furthermore, manipulation of each population mediates either social withdrawal or behavioral despair, but not both. We propose that distinct components of the VP PV circuit can subserve related, yet separate depressive-like phenotypes in mice, which could ultimately provide a platform for symptom-specific treatments of depression.

Behavioral and molecular characterization of cell-type-specific populations governing fear learning and behavior is a promising avenue for the rational identification of potential therapeutics for fear-related disorders. Examining cell-type-specific changes in neuronal translation following fear learning allows for targeted pharmacological intervention during fear extinction learning, mirroring possible treatment strategies in humans. Here we identify the central amygdala (CeA) Drd2-expressing population as a novel fear-supporting neuronal population that is molecularly distinct from other, previously identified, fear-supporting CeA populations. Sequencing of actively translating transcripts of Drd2 neurons using translating ribosome affinity purification (TRAP) technology identifies mRNAs that are differentially regulated following fear learning. Differentially expressed transcripts with potentially targetable gene products include Npy5r, Rxrg, Adora2a, Sst5r, Fgf3, Erbb4, Fkbp14, Dlk1, and Ssh3. Direct pharmacological manipulation of NPY5R, RXR, and ADORA2A confirms the importance of this cellpopulation and these cell-type-specific receptors in fear behavior. Furthermore, these findings validate the use of functionally identified specific cell populations to predict novel pharmacological targets for the modulation of emotional learning.

The mammalian brain is composed of diverse, specialized cell populations. To systematically ascertain and learn from these cellular specializations, we used Drop-seq to profile RNA expression in 690,000 individual cells sampled from 9 regions of the adult mouse brain. We identified 565 transcriptionally distinct groups of cells using computational approaches developed to distinguish biological from technical signals. Cross-region analysis of these 565 cell populations revealed features of brain organization, including a gene-expression module for synthesizing axonal and presynaptic components, patterns in the co-deployment of voltage-gated ion channels, functional distinctions among the cells of the vasculature and specialization of glutamatergic neurons across cortical regions. Systematic neuronal classifications for two complex basal ganglia nuclei and the striatum revealed a rare population of spiny projection neurons. This adult mouse brain cell atlas, accessible through interactive online software (DropViz), serves as a reference for development, disease, and evolution.