The rate of cognitive decline in Alzheimer's disease (AD) varies considerably from person to person. Numerous epidemiological studies point to the protective effects of cognitive, social, and physical enrichment as potential mediators of cognitive decline in AD; however, there is much debate as to the mechanism underlying these protective effects. The retrosplenial cortex (RSC) is one of the earliest brain regions with impaired functions during AD pathogenesis, and its activity is affected by cognitive, social, and physical stimulation, making it a particularly interesting region to investigate the influences of an enriched lifestyle on AD pathogenesis. In the current study, we use the 5xFAD mouse mode of AD to examine the impact of enriched housing conditions on cognitive function in AD and the viability of a particularly vulnerable cell population within the RSC-parvalbumin interneurons (PV-INs). Enriched housing conditions improved cognitive performance in female 5xFAD mice. These changes in cognitive performance coincided with restored functional connectivity of the RSC and preserved PV-IN density within this region. Along with preserved PV-IN density, there was an increase in the density of Wisteria floribunda agglutinin-positive perineuronal nets (WFA+ PNNs) across the RSC of 5xFAD mice housed in enriched conditions. Direct manipulation of WFA+ PNNs revealed that these extracellular matrix structures protect PV-INs from amyloid toxicity and may be the mechanisms underlying the protective effects of enrichment. Together, these results provide support for the WFA+ PNN-mediated maintenance of PV-INs in the RSC as a potential mechanism mediating the protective effects of enrichment against cognitive decline in AD.

PTCHD1 is an X-linked three-exon gene associated with autism spectrum disorder (ASD) and/or intellectual disability (ID). Mice lacking Ptchd1 exon 2 (Ptchd1Δexon2) exhibit hyperactivity and learning impairments, but do not recapitulate ASD-like traits. Through mapping of clinically reported loss-of-function mutations in human patients, we determined that PTCHD1 exon 3 is a high-risk locus. We therefore generated an alternative Ptchd1 knockout mouse model by targeting Ptchd1 exon 3 (Ptchd1Δexon3) using CRISPR/Cas9. Our analyses revealed that two major PTCHD1/Ptchd1 transcripts-a (full-length) and c (shorter)-were expressed in the brain. In Ptchd1Δexon2 mice, Ptchd1_a was lost, but Ptchd1_c was compensatorily upregulated, and these mice showed no ASD-like social deficits. In Ptchd1Δexon3 mutants, both Ptchd1_a and Ptchd1_c were lost, along with dysregulation of social and communication behaviors, increased repetitive behavior, and motor and learning impairments. Our side-by-side analyses of Ptchd1Δexon2 and Ptchd1Δexon3 mice suggest a functional link between PTCHD1/Ptchd1 and ASD, demonstrating that loss-of-function mutations disrupting C-terminal Ptchd1 lead to robust ASD-relevant phenotypes in mice, more faithfully recapitulating clinically observed traits.

Alzheimer's disease (AD) is a progressive neurodegenerative disorder characterized by cognitive decline and synaptic dysfunction. Among the earliest regions affected is the retrosplenial cortex (RSC), where parvalbumin-expressing (PV + ) interneurons are particularly susceptible to AD-related pathology. To understand the molecular alterations within these vulnerable neurons we employed a dual-platform spatial transcriptomics approach, integrating GeoMx Digital Spatial Profiler (DSP) and Xenium In Situ. We analyzed the transcriptomic profiles of PV+ and NeuN+ neurons in the RSC of female 5xFAD mice. We leveraged the individual strengths of each platform to generate a robust and comprehensive dataset. Using non-negative matrix factorization and k-means clustering, we identified disease-associated metagenes and examined their spatial distribution. Our analysis revealed distinct transcriptional subpopulations within PV+ interneurons, with specific metagenes differentially expressed in RSC. Dner, Gad1, and Pvalb exhibited significant down-regulation in TG mice, suggesting impairments in PV+ interneuron function and GABAergic signalling. Cross-validation between GeoMx DSP and Xenium In Situ as well as RNAscope and immunohistochemistry confirmed the reproducibility and robustness of these findings. This study provides insights into the heterogeneity and molecular vulnerabilities of PV+ interneurons in AD and demonstrates the power of integrating spatial transcriptomic platforms to uncover disease-associated neuronal subtypes and molecular markers.

De novo heterozygous variants in CUGBP Elav-like family member 2 (CELF2) have recently been associated with a rare neurodevelopmental disorder, yet the mechanisms linking specific variants to distinct clinical phenotypes remain poorly understood. Here, we reported a cohort of 18 individuals and provided evidence that variants causing CELF2 mislocalization, but not protein-null variants, were associated with seizures. Using proband-derived human cortical neurons and transgenic mouse models, we demonstrated that CELF2 underwent activity-dependent nucleocytoplasmic shuttling in excitatory neurons and that its cytoplasmic retention caused neuronal hyperactivity, elevated seizure susceptibility, and learning and memory deficits. We further found that cytoplasmic CELF2 regulated mRNAs critical for synaptic function and neuronal excitability and implicated in epileptic seizures and intellectual disability. Drug screening further identified AKT signaling as a key regulator of CELF2 nucleocytoplasmic shuttling and a candidate target for reversing neuronal hyperactivity. Together, our findings expand the clinical and genetic spectrum of CELF2-related neurodevelopmental disorders and establish a variant-specific mechanism that links CELF2 mislocalization to neuronal hyperactivity, seizures, and cognitive impairment.

Females have a higher lifetime risk of Alzheimer's disease (AD) and show greater neuropathology and cognitive decline than males. Furthermore, possession of APOEε4 alleles confers greater risk and burden of AD in females than males. To better understand how AD affects females, female-specific factors like parity (pregnancy and parenthood) are important to consider. Indeed, parity impacts brain aging in both humans and rodents, and has been associated with increased risk, greater neuropathology, and earlier age of onset for AD. We found that previous parity had opposite effects depending on genetic risk for late-onset AD (in an humanized (h)APOEε4 rat model). Parity was associated with beneficial effects on brain health biomarkers in wildtype rats, yet detrimental effects in hAPOEε4 rats. This research explores the influences of parity and hAPOEε4 genotype on activation and connectivity of brain regions implicated in cognition and AD in middle-aged rats. Wildtype and hAPOEε4 rats were either nulliparous (never mothered) or primiparous (one-time mothers). At middle age, rats were tested on a spatial working memory task then euthanized to examine functional connectivity using the immediate early gene, zif268, in response to memory retrieval. We examined activation of neurons across 19 brain regions to understand how previous parity and hAPOEε4 alter connectivity of neural networks. Our findings demonstrate that previous primiparity in wildtype rats enhanced neural network efficiency and integration. In contrast, primiparity in hAPOEε4 rats was associated with increased fragmentation of the overall neural network. Primiparity in hAPOEε4 rats also reduced neural activation of key brain regions critical for memory, including the frontal cortex, dorsal striatum, nucleus accumbens, and retrosplenial cortex. Activation of subregions in the ventral hippocampus and granular retrosplenial cortex, both individually and in pairs, consistently predicted cognitive strategy use in a spatial working memory task, which depended on hAPOEε4 genotype. By revealing distinct patterns of network organization and regional importance, this study provides insight into the neural networks underlying cognition altered by primiparity and hAPOEε4 in middle-aged female rats. These findings also demonstrate that considering within-sex factors is crucial to unraveling the dynamic effects of AD risk on brain health outcomes.

Early life stress (ELS) increases susceptibility to cognitive and socioemotional dysfunction by disrupting the neurobiological systems that regulate these behaviors. Animal models provide a valuable tool for investigating the underlying mechanisms, enabling precise manipulation of stress exposure during development. The limited bedding and nesting (LBN) model, which induces maternal stress by restricting access to bedding and nesting materials in rodents, has been instrumental in advancing our understanding of chronic ELS. While this paradigm has been widely adopted, variations in apparatus designs and subtle differences in methodologies could impact consistency across studies. Here, we provide standardized guidelines for a cost-effective open-source mouse LBN apparatus design, which could further enhance the model's utility while supporting pup survival. We additionally present our findings observed during the duration of the LBN paradigm, which spans from postnatal day (PND) 2 to 10, for both dams and pups. We observe comparable corticosterone in control and LBN dams from PND 3 to 5. However, from PND 6 to 10, corticosterone remains elevated in LBN dams, while control dams show a decline. Notably, the LBN paradigm disrupts maternal care, as LBN dams exhibit more frequent nest exits and stereotypic behaviors during the dark phase. At PND 10, pups exhibit significantly reduced blood serum corticosterone levels and lower body weight compared with those reared under control conditions. By providing open-source equipment and detailed experimental protocols, our work aims to build on existing LBN paradigms to further enhance the accessibility and reproducibility of chronic ELS models.

Cognition and its underlying neurobiology change throughout the trajectory of aging, with prominent sex differences and influences of sex-specific factors. Research has shown that parity (pregnancy and parenthood) uniquely altered various biomarkers of brain health in middle age depending on presence of Alzheimers disease (AD) risk. The present study builds on prior work by providing a comprehensive view of functional connectivity changes and elucidating how network-level dynamics contribute to cognitive outcomes depending on primiparity and APOEe4 genotype, the top genetic risk factor for late-onset sporadic AD risk. We assessed neural activation in middle-aged wildtype and hAPOEe4 rats that were either nulliparous (0 litters) or primiparous (1 litter). Activation of the immediate early gene zif268 was quantified across 19 brain regions implicated in memory and AD. Primiparous hAPOEe4 rats exhibited widespread reductions in neural activation, particularly in the dorsal striatum, nucleus accumbens, frontal cortex, and retrosplenial cortex. Network analyses further revealed that primiparous wildtype rats had the most cohesive and efficient functional connectivity networks. Notably, the hierarchy of influence of brain regions within the neural network shifted based on parity and hAPOEe4 genotype. Activation of hippocampal new-born neurons in conjunction with subregions of the dorsal striatum, frontal cortex, and retrosplenial cortex dynamically predicted cognitive performance in a parity- and genotype-dependent manner. These findings underscore the lasting impact of reproductive history on brain health and cognitive aging, highlighting the need to consider sex-specific experiences in aging and AD research. ### Competing Interest Statement The authors have declared no competing interest.

Alzheimer's disease is a debilitating neurodegenerative disorder with no cure and few treatment options. In early stages of Alzheimer's disease, impaired metabolism and functional connectivity of the retrosplenial cortex strongly predict future cognitive impairments. Therefore, understanding Alzheimer's disease-related deficits in the retrosplenial cortex is critical for understanding the origins of cognitive impairment and identifying early treatment targets. Using the 5xFAD mouse model, we discovered early, sex-dependent alterations in parvalbumin-interneuron transcriptomic profiles. This corresponded with impaired parvalbumin-interneuron activity, which was sufficient to induce cognitive impairments and dysregulate retrosplenial functional connectivity. In fMRI scans from patients with mild cognitive impairment and Alzheimer's disease, we observed a similar sex-dependent dysregulation of retrosplenial cortex functional connectivity and, in postmortem tissue from subjects with Alzheimer's disease, a loss of parvalbumin interneurons. Reversal of cognitive deficits by stimulation of parvalbumin interneurons in the retrosplenial cortex suggests that this may serve as a promising therapeutic strategy.

Parvalbumin inhibitory interneurons (PV-INs) are critical regulators of excitatory/inhibitory balance in the cortex, and their dysfunction has been observed in various neurological disorders. Despite increasing recognition of sex differences in brain function, little is known about how PV-INs differ between males and females under healthy conditions. Previous work has pointed to sex differences in PV-IN vulnerability in disease and injury models. Here, we investigated sex differences in PV-IN characteristics, connectivity, and function in the retrosplenial cortex (RSC) of healthy mice. We found that female mice have significantly fewer PV-INs in the RSC compared to males, yet exhibit comparable memory induced neuronal activation (fos expression). Despite their lower numbers, female PV-INs displayed greater synaptic connectivity, as evidenced by increased synaptotagmin-2 (Syt-2) puncta per PV-IN and higher axonal bouton density. Additionally, fewer female PV-INs were surrounded by perineuronal nets (PNNs), suggesting greater plasticity in female inhibitory networks. From ex vivo slice electrophysiology recordings we observed greater excitability in female PV-INs compared to male PV-INs and, a reduced incidence of IPSCs. These findings indicate that female mice may compensate for reduced PV-IN numbers through enhanced synaptic output, preserving inhibitory function in the RSC. Finally, using spatial transcriptomic profiling of PV-INs we observed a number of differentially expressed genes that are consistent with the observed structural and functional differences between female and male PV-INs. Understanding these sex-specific inhibitory mechanisms is crucial for developing more targeted interventions for conditions involving PV-IN impairment and for understanding sex specific vulnerabilities to certain conditions such as Alzheimer’s disease. ### Competing Interest Statement The authors have declared no competing interest. Canada Foundation for Innovation, https://ror.org/000az4664, #38160, #42065 Alberta Children’s Hospital Research Institute Women’s Brain Health Initiative, #5542

Cognitive aging is influenced by sex and sex-specific factors. Indeed, research has shown that parity (pregnancy and parenthood) uniquely alters biomarkers of brain health in middle age depending on Alzheimer's disease (AD) risk. This study investigated functional connectivity changes and network dynamics at middle age based on parity and APOEε4 genotype, the top genetic risk factor for late-onset sporadic AD risk. Neural activation was assessed in middle-aged wildtype and hAPOEε4 rats that were either nulliparous (0 litters) or primiparous (1 litter), by quantifying expression of the immediate early gene, zif268, across 19 brain regions implicated in memory and AD. Primiparous hAPOEε4 rats exhibited widespread reductions in neural activation, particularly in the dorsal striatum, nucleus accumbens, frontal cortex, and retrosplenial cortex. Network analyses further revealed that primiparous wildtype rats had the most cohesive and efficient functional connectivity networks. Activation of hippocampal new neurons in conjunction with the dorsal striatum, frontal cortex, and retrosplenial cortex dynamically predicted cognitive performance depending on parity and hAPOEε4 genotype. These findings underscore the importance of considering sex-specific factors in aging and AD research.

Incidental memories encoded through spontaneous interaction with stimuli in an environment contribute to higher cognitive functions. The spontaneous Identical (IST) and the Different Stimuli Tests (DST), with objects and odors, allow for incidental memory testing using variable memory loads in rats. Here, fiber photometry and chemogenetics were used to examine the necessity of CaMKII-expressing neurons in medial prefrontal cortex (mPFC) for novelty discrimination in the IST and DST with odors. Male and female Long Evans rats completed 6-odor IST and DST. No differences in total exploration times or stimuli visits were observed in either test or sex. During the sample phase of the DST, a heightened response and a sustained increase in mPFC neuronal activity occurred during the first stimulus interaction. A sustained increase in mPFC neuronal activity during interaction with the novel stimulus was also observed in the test phase of the DST, but not the IST. Activation of inhibitory DREADDs expressed in mPFC CaMKII-expressing neurons impaired novelty preference in the DST, but not IST, and significantly decreased c-Fos + cells in the mPFC. Taken together, we show increased activity in mPFC CaMKII-expressing neurons facilitates novelty recognition under higher memory loads in the DST.

INTRODUCTION:Tau pathology impacts neurodegeneration and cognitive decline in Alzheimer's disease (AD), with the dorsal raphe nucleus (DRN) being among the brain regions showing the earliest tau pathology. As a serotonergic hub, DRN activity is altered by selective serotonin reuptake inhibitors (SSRIs), which also have variable effects on cognitive decline and pathology in AD. METHODS:We examined N = 191 subjects with baseline 18F-fluorodeoxyglucose positron emission tomography and plasma biomarker data to study the effects of SSRIs on tau pathology, cognitive decline, and DRN metabolism. RESULTS:Plasma phosphorylated tau 181 (p-tau181) was lower with SSRI use. The effect of SSRIs on cognition varied by cognitive assessment. The DRN was hypometabolic in AD patients relative to healthy controls; however, SSRI use restored the metabolic activity of this region in AD patients. DISCUSSION:Long-term SSRI use may reduce the pathological presentation of AD but has variable effects on cognitive performance. HIGHLIGHTS:Tau pathology spreads throughout the brain during AD pathogenesis. The DRN is among the first regions to develop tau pathology during this process. SSRI use restores the metabolic activity of the DRN and reduces plasma p-tau181.

Voluntary wheel running is a common measure of general activity in many rodent models across neuroscience and physiology. However, current commercial wheel monitoring systems can be cost-prohibitive to many investigators, with many of these systems requiring investments of thousands of dollars. In recent years, several open-source alternatives have been developed, and while these tools are much more cost effective than commercial system, they often lack the flexibility to be applied to a wide variety of projects. Here, we have developed PAW, a 3D Printable Arduino-based Wheel logger. PAW is wireless, fully self-contained, easy to assemble, and all components necessary for its production can be obtained for only $75 CAD. Furthermore, with its compact internal electronics, the 3D printed casing can be easily modified to be used with a wide variety of running wheel designs for a wide variety of rodent species. Data recorded with the PAW system shows circadian patterns of activity which is expected from mice and is consistent with results found in the literature. Altogether, PAW is a flexible, low-cost system that can be beneficial to a broad range of researchers who study rodent models.

INTRODUCTION:Not all individuals who experience mild cognitive impairment (MCI) transition through progressive stages of cognitive decline at the same rate, if at all. Previous observational studies have identified the retrosplenial cortex (RSC) as an early site of hypometabolism in MCI which seems to be predictive of later transition to Alzheimer's disease (AD). METHODS:We examined N = 399 MCI subjects with baseline 18F-fluorodeoxyglucose positron emission tomography. Subjects were classified based on whether their diagnosis converted from MCI to AD. RESULTS:Whole-brain metabolism was decreased in converters (MCI-AD). This effect was more prominent at the RSC, where MCI-AD subjects showed even greater hypometabolism. Observations of RSC hypometabolism and its utility in predicting transition from MCI-AD withstood statistical analyses in a large retrospective study. DISCUSSION:These results point to the utility of incorporating RSC hypometabolism into predictive models of AD progression risk and call for further examination of mechanisms underlying this relationship. HIGHLIGHTS:Not all individuals who develop MCI will progress to AD. Individuals with MCI who progress to AD show early whole-brain hypometabolism. Early hypometabolism is particularly prominent at the RSC.

BackgroundChronic childhood stress is a prominent risk factor for developing affective disorders, yet mechanisms underlying this association remain unclear. Maintenance of optimal serotonin (5-HT) levels during early postnatal development is critical for the maturation of brain circuits. Understanding the long-lasting effects of early life stress (ELS) on serotonin-modulated brain connectivity is crucial to develop treatments for affective disorders, arising from childhood stress.MethodsUsing a mouse model of chronic developmental stress, we determined the long-lasting consequences of ELS on 5-HT circuits and behavior in female and male mice. Using FosTRAP mice, we cross-correlated regional c-fos density to determine brain-wide functional connectivity of the raphe nucleus. We next performed in vivo fiber photometry to establish ELS-induced deficits in 5-HT dynamics and optogenetics to stimulate 5-HT release to improve behavior.ResultsAdult female and male mice exposed to ELS showed heightened anxiety-like behavior. ELS further enhanced susceptibility to acute stress by disrupting the brain-wide functional connectivity of the raphe nucleus and the activity of 5-HT neuron population, in conjunction with increased orbitofrontal cortex (OFC) activity and disrupted 5-HT release in medial OFC (mOFC). Optogenetic stimulation of 5-HT terminals in the mOFC elicited an anxiolytic effect in ELS mice in a sex-dependent manner.ConclusionThese findings suggest a significant disruption in 5-HT-modulated brain connectivity in response to ELS, with implications for sex-dependent vulnerability. The anxiolytic effect of the raphe-mOFC circuit stimulation provides potential implications for developing targeted stimulation-based treatments for affective disorders that arise from early life adversities.

Aerobic exercise has many effects on brain function, particularly at the hippocampus. Exercise has been shown to increase the rate of adult neurogenesis within the dentate gyrus and decrease the density of perineuronal nets in area CA1. The relationship between the rate of neurogenesis and the density of perineuronal nets in CA1 is robust; however, these studies only ever examined these effects across longer time scales, with running manipulations of 4 weeks or longer. With such long periods of manipulation, the precise temporal nature of the relationship between running-induced neurogenesis and reduced perineuronal net density in CA1 is unknown. Here, we provided male and female mice with home cage access to running wheels for 0, 1, 2, or 4 weeks and quantified hippocampal neurogenesis and CA1 perineuronal net density. In doing so, we observed a 2-week delay period prior to the increase in neurogenesis, which coincided with the same delay prior to decreased CA1 perineuronal net density. These results highlight the closely linked temporal relationship between running-induced neurogenesis and decreased perineuronal net expression in CA1.

Studying how spatially discrete neuroanatomical regions across the brain interact is critical to advancing our understanding of the brain. Traditional neuroimaging techniques have led to many important discoveries about the nature of these interactions, termed functional connectivity. However, in animal models these traditional neuroimaging techniques have generally been limited to anesthetized or head-fixed setups or examination of small subsets of neuroanatomical regions. Using the brain-wide expression density of immediate early genes (IEG), we can assess brain-wide functional connectivity underlying a wide variety of behavioural tasks in freely behaving animal models. Here we provide an overview of the necessary steps required to perform IEG-based analyses of functional connectivity. We also outline important considerations when designing such experiments and demonstrate the implications of these considerations using an IEG-based network dataset generated for the purpose of this review.

Classification is a fundamental task in biology used to assign members to a class. While linear discriminant functions have long been effective, advances in phenotypic data collection are yielding increasingly high-dimensional datasets with more classes, unequal class covariances, and non-linear distributions. Numerous studies have deployed machine learning techniques to classify such distributions, but they are often restricted to a particular organism, a limited set of algorithms, and/or a specific classification task. In addition, the utility of ensemble learning or the strategic combination of models has not been fully explored.We performed a meta-analysis of 33 algorithms across 20 datasets containing over 20,000 high-dimensional shape phenotypes using an ensemble learning framework. Both binary (e.g., sex, environment) and multi-class (e.g., species, genotype, population) classification tasks were considered. The ensemble workflow contains functions for preprocessing, training individual learners and ensembles, and model evaluation. We evaluated algorithm performance within and among datasets. Furthermore, we quantified the extent to which various dataset and phenotypic properties impact performance.We found that discriminant analysis variants and neural networks were the most accurate base learners on average. However, their performance varied substantially between datasets. Ensemble models achieved the highest performance on average, both within and among datasets, increasing average accuracy by up to 3% over the top base learner. Higher class R2 values, mean class shape distances, and between- vs. within-class variances were positively associated with performance, whereas higher class covariance distances were negatively associated. Class balance and total sample size were not predictive.Learning-based classification is a complex task driven by many hyperparameters. We demonstrate that selecting and optimizing an algorithm based on the results of another study is a flawed strategy. Ensemble models instead offer a flexible approach that is data agnostic and exceptionally accurate. By assessing the impact of various dataset and phenotypic properties on classification performance, we also offer potential explanations for variation in performance. Researchers interested in maximizing performance stand to benefit from the simplicity and effectiveness of our approach made accessible via the R package pheble.