Biology subjects

Kenny, P. J.

Publications and source records attributed to Kenny, P. J..

6 recordsLinked to original sources

bioRxiv2026

Cerebellar microRNA-206 tunes Purkinje neuron firing dynamics to control sensorimotor gating

MicroRNAs are potent regulators of gene expression in the brain, yet the cellular mechanisms through which they shape neuronal activity and behavior remain poorly understood. MicroRNA-206 (miR-206) has been genetically and transcriptionally linked to schizophrenia and other neuropsychiatric disorders, but its functions in the nervous system are largely unknown. Here we show that miR-206 expression in the brain is restricted to postnatal cerebellar Purkinje cells (PCs). miR-206 was dispensable for PC cell fate specification, dendritic morphogenesis, and cerebellar-regulated motor coordination. Transcriptional profiling with single-nucleus and spatial resolution, integrated with Ago2-associated miRNA-target repression mapping (HITS-CLIP) and ribosome-associated RNA profiling (TRAP-seq), showed that miR-206 regulates translational programs in PCs controlling neuronal excitability. Accordingly, miR-206 deficiency increased the tonic firing of PCs, whereas elevating miR-206 expression shifted PCs from tonic to high-frequency burst firing. Constitutive or PC-specific deletion of miR-206 impaired prepulse inhibition (PPI) of the acoustic startle response, a conserved form of sensorimotor gating disrupted in schizophrenia and related disorders. Restoration of miR-206 expression in PCs rescued PPI deficits in miR-206-deficient mice, while elevating miR-206 expression in PCs impaired PPI in wild-type animals. Together, these findings reveal that a schizophrenia-linked microRNA tunes Purkinje neuron firing dynamics to control sensorimotor gating.

neuroscience↗

bioRxiv2024

An anterior hypothalamic circuit gates stress vulnerability

Prior adversity increases susceptibility to subsequent stressful events, but the causal underlying changes in brain circuitry are poorly understood. We harnessed unbiased whole-brain activity mapping to identify circuits that are functionally remodeled by prior adversity. This revealed that the anterior hypothalamic nucleus (AHN) displays heightened stress reactivity in previously stressed mice. This was accompanied by increased functional connectivity between the AHN and a threat-related limbic network. Using in vivo Miniscope imaging, we found that neuronal activity in the AHN encodes stressor valence. Moreover, stimulating AHN neurons enhanced, and inhibiting their activity mitigated, reactivity to stressful events. Lastly, silencing amygdala inputs to the AHN abolished the ability of prior adversity to increase stress sensitivity. These findings define a key role of the AHN in gating stress vulnerability by scaling valence signals from the amygdala.

neuroscience↗

bioRxiv2024

FABEL: Forecasting Animal Behavioral Events with Deep Learning-Based Computer Vision

Behavioral neuroscience aims to provide a connection between neural phenomena and emergent organism-level behaviors. This requires perturbing the nervous system and observing behavioral outcomes, and comparing observed post-perturbation behavior with predicted counterfactual behavior and therefore accurate behavioral forecasts. In this study we present FABEL, a deep learning method for forecasting future animal behaviors and locomotion trajectories from historical locomotion alone. We train an offline pose estimation network to predict animal body-part locations in behavioral video; then sequences of pose vectors are input to deep learning time-series forecasting models. Specifically, we train an LSTM network that predicts a future food interaction event in a specified time window, and a Temporal Fusion Transformer that predicts future trajectories of animal body-parts, which are then converted into probabilistic label forecasts. Importantly, accurate prediction of food interaction provides a basis for neurobehavioral intervention in the context of compulsive eating. We show promising results on forecasting tasks between 100 milliseconds and 5 seconds timescales. Because the model takes only behavioral video as input, it can be adapted to any behavioral task and does not require specific physiological readouts. Simultaneously, these deep learning models may serve as extensible modules that can accommodate diverse signals, such as in-vivo fluorescence imaging and electrophysiology, which may improve behavior forecasts and elucidate invervention targets for desired behavioral change.

neuroscience↗

bioRxiv2023

Shared and divergent transcriptomic regulation in nucleus accumbens D1 and D2 medium spiny neurons by cocaine and morphine

Substance use disorders (SUDs) induce widespread molecular dysregulation in the nucleus accumbens (NAc), a brain region pivotal for coordinating motivation and reward. These molecular changes are thought to support lasting neural and behavioral disturbances that promote drug-seeking in addiction. However, different drug classes exert unique influences on neural circuits, cell types, physiology, and gene expression despite the overlapping symptomatology of SUDs. To better understand common and divergent molecular mechanisms governing SUD pathology, our goal was to survey cell-type-specific restructuring of the NAc transcriptional landscape in after psychostimulant or opioid exposure. We combined fluorescence-activated nuclei sorting and RNA sequencing to profile NAc D1 and D2 medium spiny neurons (MSNs) across cocaine and morphine exposure paradigms, including initial exposure, prolonged withdrawal after repeated exposure, and re-exposure post-withdrawal. Our analyses reveal that D1 MSNs display many convergent transcriptional responses across drug classes during exposure, whereas D2 MSNs manifest mostly divergent responses between cocaine and morphine, with morphine causing more adaptations in this cell type. Utilizing multiscale embedded gene co-expression network analysis (MEGENA), we discerned transcriptional regulatory networks subserving biological functions shared between cocaine and morphine. We observed largely integrative engagement of overlapping gene networks across drug classes in D1 MSNs, but opposite regulation of key D2 networks, highlighting potential therapeutic gene network targets within MSNs. These studies establish a landmark, cell-type-specific atlas of transcriptional regulation induced by cocaine and by morphine that can serve as a foundation for future studies towards mechanistic understanding of SUDs. Our findings, and future work leveraging this dataset, will pave the way for the development of targeted therapeutic interventions, addressing the urgent need for more effective treatments for cocaine use disorder and enhancing the existing strategies for opioid use disorder.

neuroscience↗

bioRxiv2021

Ensemble encoding of conditioned fear by prefrontal somatostatin interneurons

Neurons preferentially activated by learning have been ascribed the unique potential to encode memory. However, it remains unclear which genetically-defined cell types are recruited as part of such an ensemble, or what role discrete subpopulations play in behavior. Here we show that fear conditioning activates a heterogeneous neural ensemble in the medial prefrontal cortex (mPFC), comprised to a large degree of GABAergic interneurons immunoreactive for somatostatin (SST-INs). Using an intersectional genetic approach, we demonstrate that fear learning-activated SST-INs exhibit distinct circuit properties, are preferentially reactivated during memory retrieval, and mediate the expression of defensive freezing. We further show that a rewarding experience, morphine treatment, activates an orthogonal SST-IN population that exerts opposing control over fear. These results outline an important role for discrete GABAergic ensembles in fear memory encoding, and point to an unappreciated capacity for functional specialization among SST-INs.

neuroscience↗

bioRxiv2019

The Habenular Receptor GPR151 Regulates Addiction Vulnerability Across Drug Classes

The habenula controls the addictive properties of nicotine but also densely expresses opioid and cannabinoid receptors. As such, identification of strategies to manipulate habenular activity may yield new approaches to treat substance use disorders. Here we show that GPR151, an orphan G protein-coupled receptor (GPCR) highly enriched in the habenula of humans and rodents plays a critical role in regulating habenular function and behavioral responses to addictive drugs. We show that GPR151 is expressed on axonal and presynaptic membranes and synaptic vesicles, and regulates synaptic fidelity and plasticity. We find that GPR151 associates with synaptic components controlling vesicle release and ion transport and couples to the G-alpha inhibitory protein Go1 to reduce cAMP levels. Stable cell lines expressing GPR151 confirm that it signals via Gi/o and are amenable to ligand screens. Gpr151 null mice show diminished behavioral responses to nicotine, and self-administer greater quantities of the drug, phenotypes rescued by viral re-expression of Gpr151 in the habenula. Gpr151 null mice are also insensitive to the behavioral actions of morphine and cannabinoids. These data identify GPR151 as a critical modulator of habenular function that controls addiction vulnerability across different drug classes.\n\nHighlightsO_LIHabenula neurons are enriched in nicotinic, opioid, cannabinoid and GPR151 receptors\nC_LIO_LIGPR151 modulates synaptic fidelity and release probability at habenular terminals.\nC_LIO_LIHabenular GPR151 plays a role in drug abuse and food intake/weight control\nC_LIO_LIGPR151 couples to the G-alpha inhibitory protein Go1 to reduce cAMP levels.\nC_LI\n\neTOC BlurbAntolin-Fontes at al. identify a G protein-coupled receptor, GPR151, which is highly enriched in human habenular neurons. These neurons are primarily enriched with nicotinic, opioid and cannabinoid receptors. We find that GPR151 modulates habenular synaptic vesicle release probability and behavioral responses to these drugs of abuse.

neuroscience↗