Biology subjects

Wilke, S. A.

Publications and source records attributed to Wilke, S. A..

7 recordsLinked to original sources

bioRxiv2025

A cell type-specific mechanism driving the rapid antidepressant effects of transcranial magnetic stimulation

Repetitive transcranial magnetic stimulation (rTMS) is an emerging treatment for brain disorders, but its therapeutic mechanism is unknown. We developed a novel mouse model of rTMS with superior clinical face validity and investigated the neural mechanism by which accelerated intermittent theta burst stimulation (aiTBS) - the first rapid-acting rTMS antidepressant protocol - reversed chronic stress-induced behavioral deficits. Using fiber photometry, we showed that aiTBS drives distinct patterns of neural activity in intratelencephalic (IT) and pyramidal tract (PT) projecting neurons in dorsomedial prefrontal cortex (dmPFC). However, only IT neurons exhibited persistently increased activity during both aiTBS and subsequent depression-related behaviors. Similarly, aiTBS reversed stress-related loss of dendritic spines on IT, but not PT neurons, further demonstrating cell type-specific effects of stimulation. Finally, chemogenetic inhibition of dmPFC IT neurons during rTMS blocked the antidepressant-like behavioral effects of aiTBS. Thus, we demonstrate a prefrontal mechanism linking rapid aiTBS-driven therapeutic effects to cell type-specific circuit plasticity.

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bioRxiv2025

Microglia regulate nucleus accumbens synaptic development and circuit function underlying threat avoidance behaviors

While CNS microglia have well-established roles in synapse pruning during neurodevelopment, only a few studies have identified roles for microglia in synapse formation. These studies focused on the cortex and primary sensory circuits during restricted developmental time periods, leaving substantial gaps in our understanding of the early developmental functions of microglia. Here we investigated how the absence of microglia impacts synaptic development in the nucleus accumbens (NAc), a region critical for emotional regulation and motivated behaviors and where dysfunction is implicated in psychiatric disorders that arise early in life. Using a genetically modified mouse that lacks microglia (Csf1r {Delta}FIRE/{Delta}FIRE), we found blunted excitatory synapse formation in the NAc. This effect was most prominent during the second and third postnatal weeks, when we previously found microglia to be overproduced, and was accompanied by an increase in presynaptic release probability and alterations in postsynaptic kinetics. Tissue-level NAc proteomics confirmed that microglial absence impacted numerous proteins involved in synapse structure, trans-synaptic signaling, and pre-synaptic function. However, microglial absence did not perturb levels of astrocyte-derived cues and adhesive proteins that promote synaptogenesis, suggesting that reduced synapse number may be caused by absence of a microglial-derived synaptogenic cue. Although observed electrophysiological synaptic changes were largely normalized by adulthood, we identified lasting effects of microglial absence on threat avoidance behavior, and these behavioral effects were directly associated with alterations of NAc neuronal activity. Together, these results indicate a critical role for microglia in regulating the synaptic landscape of the developing NAc and in establishing functional circuits underlying adult behavioral repertoires.

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bioRxiv2024

Transformations in prefrontal ensemble activity underlying rapid threat avoidance learning

The capacity to learn cues that predict aversive outcomes, and understand how to avoid those outcomes, is critical for adaptive behavior. Naturalistic avoidance often means accessing a safe location, but whether a location is safe depends on the nature of the impending threat. These relationships must be rapidly learned if animals are to survive. The prelimbic subregion (PL) of the medial prefrontal cortex (mPFC) integrates learned associations to influence these threat avoidance strategies. Prior work has focused on the role of PL activity in avoidance behaviors that are fully established, leaving the prefrontal mechanisms that drive rapid avoidance learning poorly understood. To determine when and how these learning-related changes emerge, we recorded PL neural activity using miniscope calcium imaging as mice rapidly learned to avoid a threatening cue by accessing a safe location. Over the course of learning, we observed enhanced modulation of PL activity representing intersections of a threatening cue with safe or risky locations and movements between them. We observed rapid changes in PL population dynamics that preceded changes observable in the encoding of individual neurons. Successful avoidance could be predicted from cue-related population dynamics during early learning. Population dynamics during specific epochs of the conditioned tone period correlated with the modeled learning rates of individual animals. In contrast, changes in single-neuron encoding occurred later, once an avoidance strategy had stabilized. Together, our findings reveal the sequence of PL changes that characterize rapid threat avoidance learning.

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bioRxiv2024

Prefrontal dopamine circuits are required for active avoidance learning but not fear learning

To survive, animals must rapidly learn to avoid predictable threats. Such learning depends on detecting reliable cue-outcome relationships that efficiently drive behavioral adaptations. The medial prefrontal cortex (mPFC) integrates learned information about the environment to guide adaptive behaviors1-7 and is critical for threat avoidance8-15. However, as most studies have focused on well-learned threat avoidance strategies, the specific inputs that signal avoidability and drive rapid avoidance learning remain poorly understood. Dopamine (DA) inputs from the ventral tegmental area (VTA) potently modulate prefrontal function and are preferentially engaged by aversive stimuli16-21. Previous studies implicated VTA and prefrontal DA in aversive learning22-25, but their findings have been constrained by limited spatiotemporal resolution. Here, we used high-resolution tools to dissect the role of the VTA-mPFC DA circuit in rapid avoidance learning. Optogenetic suppression of VTA DA terminals in mPFC selectively impaired learning of a cued avoidance response, without affecting cue-shock association learning, reactive escape behaviors, or expression of previously learned avoidance. Using a fluorescent DA sensor, we observe rapid, event-locked DA activity that emerged transiently during the initiation of learning. Increased DA encoded aversive outcomes and their predictive cues, while decreased DA encoded their omission and predicted how quickly mice learned to avoid. In yoked mice lacking control over shock omission, these dynamics were largely absent. Together, these findings demonstrate that the VTA-mPFC DA circuit is necessary for rapid acquisition of proactive avoidance behaviors and reveal transient event-related DA signals that underlie this form of learning.

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bioRxiv2022

Neural activity in the anterior cingulate cortex is required for effort-based decision making

Adaptive decision making requires the evaluation of cost-benefit tradeoffs to guide action selection. Effort-based decision making (EBD) involves weighing predicted gains against effort costs and is disrupted in several neuropsychiatric disorders. The anterior cingulate cortex (ACC) is postulated to control effort-based choice via its role in encoding the value of overcoming effort costs in rodent EBD assays. However, temporally precise methods of manipulating neural activity have rarely been applied to EBD. We developed and validated a mouse version of the barrier T-maze EBD task, in which action selection is spatiotemporally segregated from surmounting an effortful obstacle and effort is minimally confounded with time cost. Optogenetic silencing of ACC excitatory neurons during action selection, rapidly and reversibly impaired preference to exert greater effort for a larger reward, when a less effortful alternative was available. Detailed analysis of mouse choice trajectories revealed that silencing ACC disrupts kinematics, especially prior to high effort choices. However, there were no effects on overall mobility or tendency to exert effort in non-choice assays. These findings establish causality between ACC neural activity and effortful action selection during spatial cost-benefit decision making. SIGNIFICANCE STATEMENTDisturbances in evaluating effort-based costs during decision making occur in depression, schizophrenia, addiction and Parkinsons disease. Precisely resolving the function of prefrontal brain regions in mediating these processes will reveal key loci of dysfunction and potential therapeutic intervention in these disorders.

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bioRxiv2021

BehaviorDEPOT: a tool for automated behavior classification and analysis in rodents

Quantitative descriptions of animal behavior are essential to understand the underlying neural substrates. Many behavioral analyses are performed by hand or with expensive and inflexible commercial software that often fail on animals with attached head implants, such as those used for in vivo optogenetics and calcium imaging. With the development of machine learning algorithms that can estimate animal positions across time and space, it is becoming easier for users with no prior coding experience to perform automated animal tracking in behavioral video recordings. Yet classifying discrete behaviors based on positional tracking data remains a significant challenge. To achieve this, we must start with reliable ground truth definitions of behavior, a process that is hindered by unreliable human annotations. To overcome these barriers, we developed BehaviorDEPOT (DEcoding behavior based on POsitional Tracking), a MATLAB-based application comprising six independent modules and a graphical user interface. In the Analysis Module we provide hard-coded classifiers for freezing and rearing. Optionally applied spatiotemporal filters allow users to analyze behaviors in varied experimental designs (e.g. cued tasks or optogenetic manipulations). Even inexperienced users can generate organized behavioral data arrays that can be seamlessly aligned with neurophysiological recordings for detailed analyses of the neural substrates. Four additional modules create an easy-to-use pipeline for establishing reliable ground-truth definitions of behaviors as well as custom behavioral classifiers. Finally, our Experiment Module runs fear conditioning experiments using an Arduino-based design that interfaces with commercialhardware and significantly reduces associated costs. We demonstrate the utility and flexibility of BehaviorDEPOT in widely used behavioral assays including fear conditioning, avoidance, and decision-making tasks. We also demonstrate the robustness of the BehaviorDEPOT freezing classifier across multiple camera types and in mice and rats wearing optogenetic patch cables and head-mounted Miniscopes. BehaviorDEPOT provides a simple, flexible, automated pipeline to move from pose tracking to reliably quantifying a wide variety of task-relevant behaviors.

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bioRxiv2021

Convergence of clinically relevant manipulations on dopamine-regulated prefrontal activity underlying stress-coping responses

BackgroundDepression is a pleiotropic condition that can be produced or ameliorated by diverse genetic, environmental, and pharmacological manipulations. In this context, identifying patterns of circuit activity on which many of these manipulations converge would be important, because studying these patterns could reveal underlying biological processes related to depression and/or new therapies. In particular, the prefrontal cortex and dopaminergic signaling have both been implicated in depression. Nevertheless, how dopamine influences disease-relevant patterns of prefrontal circuit activity remains unknown. MethodsWe used calcium imaging in brain slices to identify depression-relevant patterns of activity in prefrontal microcircuits, and measure how these are modulated by dopamine D2 receptors (D2Rs). Then, we used optogenetic and genetic manipulations to test how dopamine and D2Rs contribute to stress-coping behavior in a paradigm commonly used to assay how manipulations promote or ameliorate depression-like states. ResultsPatterns of correlated activity in prefrontal microcircuits are enhanced by D2R stimulation as well as by two mechanistically distinct antidepressants: ketamine and fluoxetine. Conversely, this D2R-driven effect was disrupted in two etiologically distinct models of depression: a genetic susceptibility model and chronic social defeat. Phasic stimulation of dopamine afferents to prefrontal cortex increased effortful responses to tail suspension stress. Conversely, deleting prefrontal D2R receptors reduced the duration of individual struggling episodes. ConclusionsCorrelated prefrontal microcircuit activity represents a point of convergence for multiple depression-related manipulations. Prefrontal D2Rs enhance this activity. Through this mechanism, prefrontal dopamine signaling may promote network states associated with antidepressant actions that manifest as effortful responses to stress.

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