Neuroscience, 2017-2026

Bipolar disorder (BD) is a complex psychiatric condition characterized by recurrent mood episodes and disruptions in sleep, cognition, and emotional regulation. Recent genetic studies have identified loss-of-function mutations in Akap11 as a significant risk factor for BD, yet the cellular and molecular consequences of Akap11 dysfunction remain poorly understood. This project investigates what cell-type-specific molecular effects loss-of-function in Akap11 has in two BD-relevant brain regions: the thalamic reticular nucleus (TRN) and deep cerebellar nuclei (DCN) in the cerebellum. We developed and applied region-specific nuclei isolation workflows that utilized antibody-based fluorescence-activated sorting to enrich neuronal and subtype-specific nuclei in wild-type (WT) and knockout (KO) mice. Single-nucleus RNA sequencing was performed using the 10x Genomics Chromium platform to quantify transcriptional alterations and changes in cell-type composition. Processed datasets were integrated with spatial and reference transcriptomic atlases to refine cell-type annotations and localize gene expression changes. Together, these approaches aim to define how Akap11 loss broadly reshapes the cellular and molecular landscape by disrupting cell-type specific gene regulation in BD-relevant circuits. While this work is done in mice, it provides a foundational mechanistic model and is a portion of a broader project dedicated to understanding cell-type-specific perturbations in human circuits implicated in the disorder to engineer alternative therapeutic opportunities.

The hippocampus is classically implicated in allocentric spatial memory, but its contribution to complex navigation in a distal cue-lacking environment, particularly under single-session learning conditions, remains poorly characterized. Here, we investigated the effects of optogenetic inhibition of hippocampal region CA1 on navigational behavior in a novel, high-complexity maze paradigm lacking external distal cues. Water-deprived mice were allowed to freely enter and exit our maze task over the course of a single learning session, where a water reward port was located multiple nodes away from the home cage. The route to obtain the reward was densely populated with sequential decision points, and the nature of the task emphasized the proximal orientation of self in space, rather than orientation via external landmarks. When mice entered into the maze, CA1 was perturbed optogenetically through the expression of Channelrhodopsin-2 (ChR2) in GABAergic hippocampal neurons. We assessed cumulative reward-zone entries, reward visit rate, route directness, route duration, average speed, and spatial node occupancy in order to determine whether hippocampal perturbation altered reward retrieval, route efficiency, or the broader organization of navigation. Across conditions, cumulative reward-zone entries increased over time, suggesting that mice were able to learn the maze within a single session. Optogenetic inhibition did not produce a gross reduction in total reward retrieval. However, the temporal pattern of reward-zone entry differed significantly across conditions, suggesting that perturbation altered how reward-seeking behavior evolved over the course of learning rather than simply increasing or decreasing performance overall. Additional analyses of route directness, direction-specific trajectories, and occupancy patterns further suggested that hippocampal inhibition influenced the structure of navigation more than endpoint reward acquisition itself. These findings are preliminary, but we hope they provide insights on how regional inhibition may alter the dynamics of navigation, rather than task success alone.

While schizophrenia is regarded as a neurodevelopmental disorder, the mechanisms through which exposure to the environment contributes to the onset of psychosis still lack a clear scientific explanation. The most well-established finding in epidemiology of the condition is a connection between growing up in the city and higher risks of the disease. However, urbanicity is commonly considered in terms of being a contextual rather than a developmental exposure that is associated with a biological response. Existing theories usually consider one component of schizophrenia in isolation without fully explaining its interaction. The main argument of this thesis is that urbanicity should be considered through developmental contexts in which stress experiences become biologically encoded. Based on findings derived from epidemiology, neurobiology, and stress sensitization literature, this thesis claims that the constant experience of stress in the urban environment triggers sensitization of stress response systems, specifically the HPA-axis and dopaminergic system. Such sensitization affects salience processing, leading to lower thresholds for experiencing a psychotic episode. Predictive coding theory is also employed to explain how these changes manifest. According to this theory, in the case of continuous stress, predictive systems responsible for adequately weighting and updating inputs from the environment can become faulty, leading to overestimation of certain stimuli. Building off this framework, chronic social stress in cities where the population is dense, fragmented, and unpredictable results in the formation of psychotic experiences in people who are predisposed to the disease. Unlike current models, this thesis attempts to conceptualize urbanicity as a collection of multiple developmental exposures that interact over time to shape a person's biological makeup and increase vulnerability to psychosis. This approach provides a comprehensive explanation of the effects of the environment on the neurodevelopment of psychosis.

Preparatory neural activity underlies every voluntary movement we make, yet somehow it does not lead to premature muscle activation. The dorsal premotor cortex (PMd) and the primary motor cortex (M1) are regions that map directly to the spinal cord and exhibit preparatory neural activity. The null space theory attempts to explain the lack of downstream motion, claiming that there is a theoretical space in which any changes will result in muscle activation which the preparatory activity avoids (Kaufman et al., 2014). This means that preparatory neural activity operates in dimensions that are not recognized as task-relevant and are therefore output-null. Essentially, there is coordinated population cancelation behavior that does not result in muscle readouts. This study uses neural and muscle data from Kaufman et al., 2014 to assess whether the presence of preparatory activity in the null space and the low dimensional communication subspace can be better captured through reduced rank ridge regression, compared to the ridge regularized principal component regression. The results of this study indicate that the reduced rank ridge regression preserves more output variance through the communication space with the same rank as that of Kaufman et al., 2014. Additionally, it appears that the preparatory activity is strongly constrained to the null space when evaluating the degree of tuning that the preparatory activity has to this space. This means that the brain is essentially able to perform unseen computations to prepare for movement through utilizing the many dimensions in the null space.

Autism is a prevalent and highly heterogeneous condition that affects functioning in multiple domains of life. Animal models of autism are useful in studying behaviors resulting from direct manipulation of genes associated with autism in humans. The present study investigated cognitive and locomotor behaviors in the L7-Tsc1 mutant and Shank3B knockout autism mouse models. These two genotypes and a cohort of wild-type mice were included in an array of behavioral experiments, including an open field test, dyadic social interaction, and an evidence accumulation task. Behavioral clusters were extracted from the locomotor data and analyzed in conjunction with evidence accumulation task learning trajectory and behavioral learning state occupancy. Results showed preliminary trends of learning trajectory differences and behavioral cluster occupancy between autism and wild-type groups. These results highlight the importance of advancing the understanding of the heterogeneity of the autism spectrum.

Early life stress refers to ‘chronic and/or extreme stress in early life’, and has been associated with a multitude of negative and persistent effects on ‘prefrontal–hypothalamic–amygdala and dopaminergic circuits’ (Smith & Pollak, 2020). However, the molecular mechanisms underlying these effects have yet to be fully elucidated. Researchers continue to investigate the biological mechanisms responsible for these adverse effects as both ELS and adult stress have been shown to alter the transcriptome. The most abundant RNA modification, N6-methyladenosine (m6A) methylation, refers to the methylation of the adenosine base at the nitrogen-6 position within RNA (Jiang, 2021). This modification plays a crucial role in a variety of biological processes by influencing RNA metabolism and gene expression, and it is recognized by proteins called ‘readers’ which initiate a signal cascade. This research project evaluated how levels of m6A readers are affected by ELS, with the secondary aim of determining whether sex is a factor affecting m6A reader expression. The goal is to provide a deeper understanding of the role that m6A transcriptomic alterations play in the biology behind psychological disorders such as anxiety and depression.

Psychedelics reveal that perceptual stability is not given but constructed, exposing how a defined biological perturbation can propagate across neural systems to reorganize hierarchical inference. Despite extensive work at the molecular, systems, and computational levels, there remains no fully integrated account of how these levels relate in a principled way. This thesis addresses that gap by arguing that psilocybin induces a biologically driven destabilization of hierarchical inference that begins with 5-HT₂A receptor activation on layer V pyramidal neurons, propagates through cortical microcircuitry and large-scale network organization, and ultimately reduces the precision of high-level priors. Drawing together evidence on receptor localization, intracellular signaling, default mode network disintegration, increased global connectivity, reduced alpha-band oscillations, and elevated neural entropy, the thesis evaluates predictive processing and REBUS as frameworks for explaining these effects. Predictive processing provides the necessary computational architecture for describing changes in perception, but remains insufficiently constrained at the level of biological implementation. REBUS, by contrast, links these computational changes to a specific pharmacological mechanism and generates more precise predictions about the direction and structure of hierarchical disruption, though it remains incomplete without the broader inferential framework provided by predictive processing. The central claim is therefore not that one framework supersedes the other, but that psychedelic effects are best understood through their integration, as a coordinated process in which biological perturbations reorganize hierarchical inference across levels of analysis. Finally, by comparing psychedelic states with dreaming, the thesis proposes that both reflect distinct perturbations of a common predictive system under reduced constraint, offering a broader account of hallucination-like experience as a consequence of increased influence of internally generated activity. Taken together, this work argues that psychedelics do not simply distort perception, but make visible the mechanisms by which the brain constructs, stabilizes, and, under specific conditions, reorganizes its model of the world.

The medial entorhinal cortex (mEC) and hippocampus (HPC) are both critically involved in the formation and maintenance of cognitive maps. Although historically studied during spatial navigation, such mental maps may be an instance of a common mechanism for organizing knowledge across many domains. For example, the hippocampal formation encodes not only locations in navigational space but also 'locations' in other continuous task-relevant variables, such as visual space, sound frequency, and sensory evidence, among others. Yet, whether or how cognitive maps conjointly represent dimensions across different domains is less well understood. A recent study demonstrated integration of spatial location and sensory evidence in the HPC, but whether there is similar joint encoding across these dimensions in mEC, a major input to HPC, is unknown. Understanding whether such conjunctive coding exists in the mEC is essential for uncovering how cognitive maps are constructed and utilized to guide complex behaviors. To close this knowledge gap, we use an established virtual-reality navigation decision-making task – the accumulating towers task (ATT) – in which mice integrate pulsatile visual evidence during virtual navigation to make a choice about which way to turn to obtain a reward. Through acute electrophysiological recordings (via Neuropixel probes), we demonstrate that mEC neurons encode both navigational space and accumulated evidence conjointly during the ATT, with firing pattern and speed analyses underlining the possibility that this population of entorhinal conjunctive neurons includes grid cells. Our evidence of conjoint encoding in the entorhinal circuit supplements the growing body of work examining cognitive maps within the hippocampal formation that not only guide us through physical space, but also structure learning, memory, and decision making.

Adult onset hypothyroidism, characterized by a decreased level of circulating thyroid hormones, is robustly associated with depressive- and anxiety-like phenotypes/features in both clinical and rodent populations, implicating thyroid hormone signaling as a broad modulator of affective states and behaviors. However, how it contributes to shaping behavioral and neural responses to ethologically relevant stressors, such as social defeat, remains poorly characterized. Here, male C57BL/6J mice with propylthiouracil (PTU)-induced hypothyroidism exposed to acute social defeat stress paradigm enabled comparisons of behavioral coping strategy and whole-brain c-Fos as a neural activity proxy between controls. Manual behavioral scoring for active and passive coping strategies revealed no significant differences in retaliation and fleeing responses, or their compositions and switching dynamics, suggesting appropriate retention of defense under acute social threat. Individual variation in coping strategies correlated with c-Fos activity in most notably hypothalamic and amygdalar nuclei, regardless of condition. Whole-brain iDISCO+ c-Fos mapping identified nominally significant brain region activity differences that partake in social behaviors and stress responses (e.g. periaqueductal gray, basolateral and basomedial amygdalar nuclei, dentate gyrus), though no regions survived FDR correction. Cross-validation of the periaqueductal gray using traditional immunohistochemistry and FIJI-based cell counting elicited a similar weaker neural recruitment trend in PTU mice and partial correlation with individual-based active coping. Together, these findings provide evidence for behaviorally intact but preliminary diverse brain nodes where thyroid hormone status and social stress processing may interact, offering insight for future exploration of hypothyroidism may be shaping stress-circuitry and vulnerability to social adversity.

How the human auditory cortex processes complex auditory stimuli, in addition to lower-level tonotopical organization, remains not well understood. In this experiment, 13 subjects underwent functional magnetic resonance imaging while being presented brief sounds from six categories: adult speech, kids speech, animals, instruments, objects, and Pokémon. There were regions along Heschl’s gyrus and superior temporal gyrus (STG) that were more responsive to instruments and speech respectively. Representational similarity analysis revealed a strong distinction between the neural responses to speech and non-speech categories, particularly in regions around STG. Spectral analysis and animacy ratings obtained for all sounds suggest that frequency, a lower-level sound feature, may underlie the functional representation of sound categories in both primary auditory cortex (PAC) and STG, while animacy may drive the organization of only STG. A classifier trained on the neural data was able to predict the sound category presented with slightly above chance accuracy. Specific binary decoding analyses for speech and instrument categories performed with higher accuracy. Overall, these findings indicate that the auditory system may exhibit both parallel and hierarchical processing of auditory information. The functional organization of the six sound categories tested in this experiment is not distinct enough for a classifier to decode categories with high accuracy.

Alzheimer’s Disease (AD) is a neurodegenerative disorder characterized by progressive cognitive decline. Current therapeutics for AD only temporarily alleviate the symptoms of cognitive impairment, and broadly impact multiple brain regions without targeting localized cell populations that specifically drive AD pathology. Recent research suggests that the entorhinal cortex may be one of the first brain regions impacted by AD pathology. Layer 2 (L2) neurons within the entorhinal cortex are particularly vulnerable to neurodegeneration, as this layer exhibits the initial and most severe cellular degeneration of any other brain region in AD patients. This identifies these neurons as a reasonable target for studying AD pathology. This is a proof of principle study with the goal of identifying and validating glutamatergic L2/3 cell-type specific entorhinal cortex candidate enhancers. The study aims to address a knowledge gap in current AD research as there is currently a primary focus on Aβ accumulation and tau hyperphosphorylation as causal drivers of the disease pathology, even though dysfunction of the entorhinal cortex is one of the first signs of AD. Cell-type specific targeting of neurons in this region will provide a better understanding of the role of neural circuits containing L2 neurons, which are known to be particularly vulnerable to neurodegeneration. Successful identification and validation of a cell type-specific L2 entorhinal enhancer may lead to therapeutics aimed at preserving cognitive function using targeted adeno-associated virus (AAV) delivery.

Language ability in autism spectrum disorder (ASD) varies widely across individuals, yet the neural basis of this heterogeneity remains poorly understood. Most prior work has focused on classical cortical language regions, leaving open the question of how subcortical and cerebellar contributors shape language outcomes. This thesis examined whether structural and functional features of the cerebellar-thalamo-cortical language network predict language ability and social-communication symptom severity in autistic youth. Using structural and resting-state functional MRI data from the Autism Brain Imaging Data Exchange (ABIDE), I fit robust linear models relating regional volumes, functional connectivity, and volumetric interactions to standardized language assessments (CELF), clinician-rated communication symptoms (ADOS), and caregiver-reported communicative history (ADI-R) in 373 ASD participants aged 7-19 years. Four associations survived Benjamini-Hochberg correction within their respective test families. Resting-state functional connectivity from right Crus II to right inferior frontal gyrus negatively predicted CELF receptive language scores, with stronger coupling associated with weaker language ability– a pattern consistent with reduced network differentiation in autism. Bilateral medial geniculate nucleus (MGN) volume predicted CELF expressive and core language scores, identifying the auditory thalamic relay as a structural correlate of language ability. These results are consistent with a view of language in autism that is shaped by distributed cortical-subcortical-cerebellar circuits and individual subcortical structures, rather than by classical cortical language regions alone.

Adolescence is characterized by increased difficulties in emotional awareness and regulation, as well as an elevated risk for developing psychopathology. Prior studies show that the capacity to experience mixed emotions increases during this period, as does alexithymia (i.e., difficulty identifying and describing emotions). Although substantial research links alexithymia to poorer mental health during the transition to adolescence, we know little about the potential role of mixed emotions (i.e., the capacity to feel both positive and negative emotions simultaneously) in these relationships. We hypothesized that alexithymia will peak in adolescence, mixed emotions will increase across age, and higher levels of alexithymia will be associated with higher mixed emotion. Participants (N=163) aged 7 to 25 years completed a situational mixed emotions task where they reported their affect after playing a game designed to elicit mixed emotions. They also completed a questionnaire to assess their levels of alexithymia. Using correlation tests, multiple regression analysis, and generalized additive models, we tested relationships between age, alexithymia, and mixed emotions. We also explored whether the relationship between alexithymia and mixed emotions was moderated by age. We found a significant negative linear effect of age on alexithymia. Interestingly, our other analyses were not significant: age negatively influenced mixed emotions linearly at the trend level, alexithymia and mixed emotions were positively related linearly at the trend level, and age did not moderate this relationship. Our findings can help us better understand both normative and maladaptive emotion development, allowing us to better prevent and treat psychopathology onset in adolescence.

Early life stress (ELS) is associated with onset of mental health disorders later in life. It is also an extremely common exposure, with 60% of American adults reporting at least one and 16% reporting four or more experiences. In particular, ELS is associated with risk of generalized anxiety disorder (GAD), major depressive disorder (MDD), and posttraumatic stress disorder (PTSD). ELS is particularly damaging because the brain is still actively developing, and during this sensitive period, can disrupt brain development and thus lifelong function. The mechanisms are multifactorial, but studies in humans and animals have clearly established that this effect is maintained by distinct transcriptomes arising from ELS. These patterns of gene expression affect a variety of brain regions, particularly those associated with cognitive function and emotion. One of the most well-established are via neuroendocrine pathways during development. Indeed, TH has previously been shown to mediate ELS in areas whose disruption is implicated in ELS pathology. This study aims to develop on this basis in the amygdala, whose greater excitation is associated with ELS and whose role is to integrate stress and neuroendocrine function. I hypothesized that the expression of genes of interest (GOI) during ELS and hypothyroidism will similarly disrupt the E/I balance in the amygdala via increased glutamatergic signaling, increased glucocorticoid signaling, and decreased GABA signaling/inhibitory structural integrity mediated thyroid hormone, and that thyroid supplement LT4 treatment will therefore rescue for this effect by regulating genes associated with MDD and PTSD in a sex-specific manner. To answer this question, I utilized snRNA sequencing data from the amygdala of mice in four conditions: standard reared controls, ELS-reared, thyroid suppressed mice, and ELS-reared, LT4 treated from postnatal day 21 at weaning. In GABA and glutamatergic cells, I investigated how each condition affected expression of genes involved in neuron excitability, inhibition, and GABA/glutamate transmission. I further observed this within the distinct subnuclei of the amygdala and observed how these expression patterns vary by sex. I provide evidence that ELS is mediated by reduced thyroid hormone activity in glutamatergic and GABAergic neurons and that LT4 may reverse and rescue this effect by altering ion channels and glutamate transporter expression with some variance in treatment sensitivity by sex. By better isolating the effects of thyroid hormone in the amygdala during ELS, this research suggests potential mechanisms by which it does so. This contributes to a greater understanding of thyroid hormone’s mediation of ELS and, importantly, LT4’s potential efficacy for treating ELS-associated psychiatric illnesses.

Primary visual cortex (V1) responses carry information about temporal context and prior experience. I ask whether four days of exposure to a fixed A → B → C movie-clip sequence (the Allen Brain Observatory training paradigm) changes V1 responses to each clip given its predecessor. Using two-photon calcium imaging from 12 mice, I tracked excitatory V1 neurons across pre- and post-training days via a Hungarian-plus-IoU pipeline (286 matched neurons). For each neuron I compared peak ∆F/F when a clip was preceded by its trained versus untrained predecessor, testing whether this difference grew from Day 0 to Day 4. No training-induced trained-versus-untrained difference emerged on Day 4 (Wilcoxon p = 0.966). Instead, a small Day-0 baseline asymmetry (trained > untrained, +0.010 ∆F/F ) was eliminated by Day 4 (trained − untrained ≈ 0), yielding a negative difference-of-differences with 10/12 mice in the same direction (per-mouse Wilcoxon p = 0.052). The change therefore reflects the disappearance of the pre-training baseline asymmetry rather than the development of a clean Day 4 suppression of trained-context responses; this pattern is consistent with, but does not by itself establish, a predictive-coding account in which repeated exposure causes expected transitions to evoke smaller responses than unexpected ones. Response timing was null on average. At the single-neuron level, however, amplitude and latency changes were coupled: shrunken responses peaked earlier and vice versa (Pearson p = 0.0036). The paradigm thus produces a small cohort-consistent suppression of trained-context responses with coupled amplitude–timing adjustments, consistent with an experience-dependent gain change.

Art and its purpose stands as a pillar of humanity, embodying invaluable expression throughout history and across peoples. The advent of artificial intelligence evidences some ability to generate art, however its outputs are contested as true to cognitive accounts and art theory. This thesis presents a unified cognitive framework on the basis of visual art creativity by synthesizing standing theories on creative art cognition, neuroscientific understanding of the visual-perceptual system and semantic networks, and artificial model attempts to emulate these behaviors as a tool. Altogether, we posit a hierarchy of representations towards visual creation starting with semantics and features, then form and shape, texture and pattern, and finally mark-making and line. These representational stages are derived from a refined reversal of the visual ventral pathway and artificial vision network architecture, and are grounded in correlates in both models. A secondary argument within this framework is that features and texture representations are grounded in semantic meaning, but form and mark-making are disconnected. This study then considers Janik’s (2023) perturbation of the BigGAN network and its curious output of artistic, essential renditions. We thus develop a perturbation-based theory where a neural correlate of perturbation of the representational stages in this novel framework, is responsible for the creation of visual art across forms and styles. A case study grounds these theories, employing layer-specific and representation-specific perturbations, which are assessed on perceptual manifestation of the four representations in this framework. Altogether, these findings scaffold the gap in explaining visual creativity, and push the interdisciplinary frontier towards an objective, functional understanding of subjective, artistic experience.

Organisms make choices that reflect how they value the options presented to them. While research has established that value plays a critical role in decision making, Schonberg et al. presents novel research suggesting that the intrinsic value of goods can be modulated by cue-approach training (presenting an item concurrently with an irrelevant auditory cue signaling participants to make a motor response), with choice and willingness-to-pay (WTP) serving as measures of preference shift. Yet the mechanism for how the preference shift occurs as a result of cue-approach training remains unclear. To quantify the relationship between gaze bias and choice, Krajbich et al. introduces a drift-diffusion model (DDM) where fixations affect the value comparison process through the introduction of a temporary drift bias toward the fixated item. Using the model, Kraijbich performed experiments demonstrating that eye fixations affect value: people tend to choose the item they spend the most time looking at. This, Krajibich’s model quantifies the effect of eye fixations on value. The hypothesis of this thesis is that the Krajbich valuation effect mediates the Schonberg preference change: cue approach training affects eye movement and this affects valuation. I investigate this account by fitting the Krajbich DDM model to Schonberg data demonstrating how cue-approach training shifts preference. This thesis proposes a quantitative mechanism explaining how valuation changes as measured by WTP and choice when there is increased eye movement specificity towards the trained items. The thesis also examines behavioral health applications of using eye-tracking data to understand choice.

In this thesis, I developed and evaluated a deep learning approach for classifying estrous stage from vaginal cytology images in a lab-specific rodent dataset. Using a VGG16-based convolutional neural network trained with class balancing, augmentation, and cross-validation, the final model achieved stable three-class performance (~65% accuracy), substantially improving over earlier baselines. However, the most important findings were not about overall accuracy alone. Model errors were concentrated in biologically adjacent stages, particularly between diestrus and proestrus, and these same regions showed the highest levels of annotator disagreement. This suggests that classification difficulty is not just technical and that it reflects underlying biological ambiguity and limitations in how continuous endocrine states are represented with discrete labels. I also tested whether adding short-term temporal context through adjacent-day image pairs could improve classification, but this approach did not resolve ambiguity and instead introduced a strong bias toward diestrus. The results show that estrous-stage classification is shaped by an interaction between model design, annotation structure, and the dynamic nature of the biology itself. Rather than building a perfect classifier, this thesis demonstrates that classifier performance can be used as a tool to identify where biological boundaries are most difficult to define and where current labeling frameworks may fall short.

Perceptual decision making requires animals to integrate noisy sensory evidence over time, but whether the sensorimotor context in which that evidence is acquired shapes how this information contributes to choice election remains poorly understood. Here, I investigate how the presence or absence of running influences both learning rate and temporal evidence weighting in a head-fixed virtual reality accumulation task. Six double-transgenic GCaMP6f mice were trained in one of two conditions: Active (full running over virtual corridor traversal) or Passive (replayed visual flow without running). Training progression was separated into four stages (Level 3 Sublevel 1 < 80%, Level 3 Sublevel 1 ≥ 80%, Level 3 Sublevels 2+3, and Level 4) to enable comparisons across task types at matched task difficulty. Active mice (n = 4) advanced through the training protocol faster and with steeper psychometric slopes than Passive mice (n = 2). Three of the Active mice reached the Level 4 evidence accumulation stage while no Passive mice currently did. A lick-zone validation test confirmed that both conditions suppressed premature licking during the cue region and committed to choices only in the reward zone. At Level 4, a spatial bin logistic regression revealed that Active mice weighted late-corridor evidence far more heavily than early-corridor evidence (population WDR = 15.20 ± 10.73), producing a recency bias that contradicts the mild primacy reported by Pinto et al. (2018) in a T-maze version of the same task. The variation in bias may reflect a critical design difference: the T-maze allows multidirectional ball movement that lets mice lean toward their eventual choice during the cue region, whereas the lick-spout task constrains the ball to unidirectional forward motion and confines the choice to a single lick in the reward zone. These findings suggest that running and intentional navigation accelerates task learning, but that the observed temporal evidence weighting depends on whether the task demands permit progressive commitment during evidence accumulation.

Social isolation stress in adulthood has profound relevance in society today, and individuals who have experienced this stress have shown greater susceptibility to psychiatric disorders related to emotional regulation. Past studies have explored multiple types of social stress at different timepoints, such in early life and adolescence, but it is currently unknown how social isolation stress in adulthood may impact behavior and neural connections in the hippocampus. The present study looked at how social isolation stress affected avoidance behavior, other EPM microbehaviors, neuronal outputs of inhibitory and excitatory neurons, and microglial changes in the ventral CA1 region. We investigated these measures in C57 wild type and Cx3cr1⁺/⁻ mice, in order to explore whether CX3CR1 signaling was necessary for social-isolation related changes. Firstly, we will discuss behavioral data or neural outputs that showed social isolation effects. The results demonstrated that 4 week social isolation conditions induced decreased avoidance behavior and increased PV intensity that was ameliorated by impaired CX3CR1 signaling. We also showed that social isolation weakened the correlations between EPM microbehaviors and quantitative metrics, and this observation was not mediated by CX3CR1 signaling. Our preliminary findings suggest that social isolation may downregulate GABAAδ receptor expression, and the potential role of CX3CR1 signaling remains to be studied. Next, we will discuss data that did not show differences due to social isolation. The EPM microbehaviors did not show alterations related to social isolation, but the stretch attend postures were different in Cx3cr1⁺/⁻ mice. The calbindin expression from active pyramidal cells in the ventral CA1 region were not different between housing conditions, but there was a genotypic difference. This study broadens our understanding of the effects of social isolation stress in adulthood on behavior and neuronal outputs in the ventral CA1, and whether CX3CR1 microglial-neuronal signaling is required for these changes.