bioRxiv Subject Collection: Neuroscience's Journal

Reverse Spatiotemporal Hierarchy during Cross-modal Memory Recall and Imagery
Recalling past events is often accompanied by mental imagery of those experiences. Based on previous research, this process engages memory- and sensory-related brain areas. However, the underlying spatiotemporal dynamics remain poorly investigated. Here, we used naturalistic videos of audiovisual events and recorded fMRI data during the tasks in which human participants recalled visual contents when hearing associated sounds and recalled sounds when watching silent videos, after they had well memorized the video contents. With time-resolved fMRI multivariate pattern analyses, we observed reverse spatiotemporal hierarchy during the visual memory recall and imagery: the neural activity in primary visual cortex was delayed compared with high-order visual areas. A similar pattern was found during auditory memory recall and imagery, where the bottom-up progression from the mid-level planum temporale to the high-level superior temporal gyrus observed during auditory perception was absent. However, the primary auditory area was not involved, suggesting modality differences in the role of primary sensory areas in corresponding memory recall. We also observed the activity of the hippocampus, the parahippocampal cortex, the retrosplenial cortex, and the precuneus and examined their temporal dynamics. Overall, our study provided both spatial and temporal accounts of neural activity during the cross-modal memory recall and imagery.

Structure and function of the nervous system in the stem of the siphonophore Nanomia septata: its role in swimming coordination.
The multiple swimming bells, or nectophores, of the colonial hydrozoan Nanomia septata are capable of coordinated avoidance swims in both forward and reverse directions. Individual nectophores also contribute to slower forms of swimming during foraging. Communication between a nectophore and the rest of the colony is at cone-shaped structures in the colony stem. The stem provides an attachment point for the nectophores and houses the simple nervous system responsible for their coordination. The stem nervous system, revealed by immunocytochemistry, has three main components: two giant axons, a distributed, polygonal nerve network and a set of FMRFamide-immunoreactive nerve tracts. Whereas the nerve network is distributed throughout the stem, the nerve tracts link specific contra-lateral nectophores. Action potentials in the giant axons spread excitation rapidly along the stem, but their connection with individual nectophores is by way of the nerve network. Anatomical evidence is provided for the location of two connecting pathways between the nerve network and the nectophore; one excites an epithelial impulse and leads to reverse swimming; the other provides excitation for forward swimming by feeding into a ganglion-like cluster of nerve cells. Excitation passes to the swimming muscle epithelium by way of a single nerve axon and a nerve ring at the nectophore margin. The work presents physiological evidence for mechanisms, such as facilitation and summation, operating within a multifunctional, bidirectional nerve network, responsible for coordinating epithelial and neural signals in an early-evolved nervous system containing both condensed and distributed units.

Neurochemically-evoked activity in slice preparations of the octopus arm nerve cord
Octopus arms contain circuits that support local sensorimotor integration and autonomy, responsible for fast and flexible behaviors, but their population dynamics remain unknown. The axial nerve cord (ANC) is a series of sucker-associated ganglia whose cortex layer houses multiple classes of intermingled neurons. Here we use calcium imaging in ex vivo slices from arms of Octopus bocki, to visualize how these networks respond to controlled application of neurotransmitters and neuromodulators. Glutamate and dopamine are dominant excitatory drivers that activate most neurons in the ANC cortex, with a substantial overlapping populations and smaller transmitter-specific subsets. Glutamate continues to excite additional neurons at higher concentration, whereas dopamine responses saturate. Serotonin alone evokes mixed responses but, when applied first, consistently reduces glutamate- and dopamine-driven activation, revealing a state-dependent modulatory role. GABA and octopamine yield weak heterologous effects, and high-dose acetylcholine sharply suppresses global ANC neuronal activity while inducing muscular contraction, consistent with inhibitory cholinergic receptors in arm ganglia. Across conditions, responsive neurons show no evidence of spatial structure, with no clear anatomical segregation by transmitter response profiles. These results provide the first link between neurochemical architecture and real-time firing dynamics in a semi-autonomous circuit.

Associations Between Age, Heart Rate Variability, and BOLD fMRI Signal Variability
Numerous studies report that BOLD fMRI signal variance (SDBOLD) decreases with age. However, these associations may partly reflect cardiovascular contributions to the BOLD signal. For example, heart rate variability (HRV) has been positively associated with Resting State Fluctuation Amplitude (RSFA), which captures low frequency components of BOLD fMRI variability. HRV is also negatively associated with age, which could potentially confound age-SDBOLD associations. Yet, limited research has examined HRV-SDBOLD associations or tested within-person HRV-SDBOLD coupling using sliding window analyses of simultaneous HRV and SDBOLD. We analyzed resting-state fMRI data from two independent Midlife in the United States (MIDUS) samples: Core at M3 (n=115) and Refresher at MR1 (n=101). Partial Least Squares (PLS) analyses revealed significant positive HRV-SDBOLD associations (Core: permutation p=0.018; Refresher: permutation p<0.001). Whole brain age-SDBOLD PLS associations were non-significant via permutation tests across several models (Core: permutation p=0.201; Refresher: permutation p=0.121). We found age-related decreases in SDBOLD across ~70% of voxels in both samples. Concordance analyses showed 67-69% of brain voxels exhibited negative age-SDBOLD but positive HRV-SDBOLD relationships, suggesting that regions showing age-related decreases in SDBOLD also showed HRV-related increases in SDBOLD. Sliding-window analyses demonstrated robust positive within-person associations between person-centered HRV and SDBOLD via different HRV metrics: SDNN (Core: p < 0.001; Refresher: p < 0.001), RMSSD (Core: p = 0.072; Refresher: p = 0.009), and low frequency (Core: p < 0.001; Refresher: p < 0.001), with non-significant effects of high frequency (Core: p = 0.516; Refresher: p = 0.12) HRV. Thus, regardless of baseline levels, windows with higher HRV corresponded to higher SDBOLD, suggesting that cardiovascular factors partially explain age-SDBOLD associations and HRV may mechanistically influence SDBOLD. These results suggest that controlling for HRV, especially low-frequency HRV or SDNN, may be necessary when analyzing SDBOLD to isolate neural effects.

Emergence of Value and Action Codes in Bimodular Spiking Actor-Critic Networks
Decision-making depends on coordinated computations distributed across dorsal and ventral circuits, often described as actor-critic systems. We examined how this division of labor gives rise to value- and decision-related representations by training a bimodular recurrent network on an economic choice task and transferring it to an expanded gated spiking model that preserved its latent dynamics while stabilizing the underlying neural representations. The two modules assumed complementary roles: the actor encoded action-value differences and spatial contingencies required for selecting between actions, whereas the critic represented object values predictive of reward. Neurons across modules were selective for object, action, total, and difference values, supporting decision- and confidence-related activity. Low-dimensional analyses revealed structured trajectories reflecting temporal evolution, spatial configuration, and value-dependent divergence. These results clarify how distributed circuits can jointly implement valuation and action selection, providing a foundation for linking reinforcement-trained recurrent models with anatomically inspired dorsal-ventral frameworks.

Network Adaptability Governs Resilience and Susceptibility to Social Defeat
Stress resilience is defined as the ability to maintain mental health after adversity. In humans, resilience is marked by threat/safety discrimination and extinction of fear, whereas susceptibility involves fear generalization and extinction resistance. Using a translational mouse model of chronic social defeat stress combined with preregistered multimodal brain imaging, we investigated structural and network level markers of resilience, susceptibility, and threat learning. Resilience was characterized by preserved dentate gyrus integrity, greater microstructural complexity in prefrontal regions, and signatures consistent with enhanced inhibitory gating within amygdalar circuits. Susceptibility, in contrast, involved reduced dentate gyrus complexity and diminished microstructural flexibility, with a weaker but parallel pattern in the basolateral amygdala. Impaired threat learning was linked to compromised CA1/CA2 integrity and reduced pons connectivity, highlighting hippocampal brainstem interactions in memory consolidation. Overall, these findings show that resilience emerges from adaptive network reorganization, whereas susceptibility and impaired learning reflect distinct dysfunctions, underscoring individual coping differences even among genetically identical animals.

Effect of dependency and tail behavior on a probability inequality occurring in modeling cognitive processes
A central idea in modeling performance in cognitive tasks is dynamic competition among processes in separate channels, known as "race model". This model implies a certain inequality between associated probability distributions under rather general conditions. The inequality represents an important empirical test of the race model, but its usefulness is limited since it requires the assumption of stochastic independence between the channels. Using the stop signal paradigm as reference, we investigate more general forms of stochastic dependence that still imply the inequality using the concepts of copula and heavy-tailed marginal distributions.

CB2 cannabinoid receptor-specific therapeutic antibody agonists for treatment of chemotherapy-induced peripheral neuropathy
Chemotherapy-induced peripheral neuropathy (CIPN) is a debilitating complication of cancer treatment. CB2 cannabinoid receptor activation reduces inflammation and is an attractive therapeutic target. Antibodies targeting G protein-coupled receptors (GPCRs), like CB2, offer high specificity and peripheral-restriction, thereby minimizing off-target activity. Here, we investigated the efficacy of first-in-class CB2-specific antibody agonists (AB110 and AB120) and an isotype control (AB100) on mechanical and cold hypersensitivity induced by paclitaxel in both tumor-free and mammary (4T1) tumor-bearing female mice. These CB2 antibody agonists exhibit biased G-alfa; signaling and also reduce macrophage markers and pro-inflammatory cytokines in vitro. Paclitaxel produced behavioral hypersensitivities to mechanical and cold stimulation, which were reduced by AB110 and AB120 for approximately 48 hours post-injection in female mice. Repeated daily dosing did not lead to tolerance to the anti-allodynic effects. Prophylactic treatment with AB110 and AB120 during paclitaxel treatment delayed, but did not prevent, the development of paclitaxel-induced behavioral hypersensitivities after termination of dosing with antibody agonists. AB100 had no effect under any conditions. The anti-allodynic effects of AB120 were absent in CB2 knockout mice, confirming pharmacological specificity via CB2 receptors. Furthermore, AB120 remained effective in paclitaxel-treated tumor-bearing mice. Neither AB110 nor AB120 affected locomotor activity in otherwise naive mice. The cytotoxic activity of paclitaxel on 4T1 tumor cell line was maintained in the presence of CB2 antibody agonists in vitro. Overall, our results suggest that CB2-specific antibody agonists are promising candidates for treating CIPN, providing lasting pain relief without tolerance, off target effects or unwanted CB1-mediated motor side effects.

A computational model of the mammalian auditory periphery with a multichannel, energy-driven, medial olivocochlear reflex
The afferent auditory system, and how its specialized mechanisms and circuits support ecologically relevant auditory computations such as speech recognition, has received considerable attention in decades past. This work has culminated in accurate computational models of early afferent coding alongside a good understanding of how low-level mechanisms (e.g., peripheral tuning) impact auditory perception. In contrast, the auditory efferent system and its role in auditory perception is much less well understood. To address this gap in knowledge, we describe modifications to a model of the auditory periphery to include a medial olivocochlear efferent pathway that dynamically adjusts cochlear gain in response to sound via the classical medial olivocochlear reflex loop. We show that this model can simulate the effects of contralateral elicitors on auditory-nerve responses, including the effect of elicitors that are tonotopically distant from probes. Inclusion of across-frequency efferent effects necessitated a novel multichannel design.

Sleep controls peroxisomal abundance to reduce wake-induced brain oxidation
Sleep is increasingly linked to the regulation of Reactive Oxygen Species (ROS) and lipid metabolism. However, the mechanisms underlying this interaction are underexplored. Here, we use Drosophila melanogaster to report a bidirectional relationship between sleep and peroxisomes, cellular organelles that process lipids and alleviate ROS. Of the genes that change expression after sleep deprivation in the dorsal fan-shaped body, knockdown of the peroxisomal biogenesis factor Pex16 results in decreased sleep. Pex16 acts in several brain regions to modulate sleep amount, with ellipsoid body neurons (EB) producing the highest sleep reduction of the sleep-promoting regions. Consistent with a general role for peroxisomes, knockdown of other peroxisomal enzymes relevant for lipid import and synthesis also decreases sleep. Whole-brain peroxisomal numbers increase with wake, which is supported by lipidomic analysis indicating that peroxisomal-derived phospholipids are the major contributors to phospholipid changes after wake or sleep deprivation. Peroxisomal proliferation in the EB is driven by neuronal activity and increased oxidation, suggesting that these mediate the effect of wake/sleep loss. In turn, peroxisomes alleviate the oxidation accumulated during wake, such that loss of Pex16 in the EB works non-cell autonomously to increase lipid peroxidation brain-wide. This likely contributes to sleep loss, as sleep is rescued with an antioxidant. Together, these results position peroxisomes as key players in sleep, regulating ROS and thereby maintaining normal cycles.

Improved Estimation of Correlation Accuracy for Machine Learning Brain-Phenotype Associations
Machine learning is used in neuroscience to examine brain-phenotype associations and facilitate individual prediction from high-dimensional brain imaging. For continuous phenotypes, Pearson correlation between the observed and predicted phenotype is used to quantify model accuracy in testing data. However, recent research suggests millions of samples may be needed to reliably estimate the maximum achievable predictive accuracy (MAPA). We formally define the MAPA and show that the Pearson estimator is biased for this quantity and its confidence intervals fail to capture the target. We develop a semiparametric (double machine learning) one-step estimator that more accurately estimates the MAPA and yields valid confidence intervals across flexible machine learning settings. Analyzing data from the Reproducible Brain Charts dataset, we show that this estimator has smaller bias when estimating brain-phenotype associations of neuroimaging data with age and psychopathology phenotypes. We show that MAPA for psychopathology factor scores using machine learning models built on structural and functional imaging measures is not better than using demographic and nuisance covariates alone.

ACSS2 mediates prenatal alcohol exposure-related morphological and behavioral phenotypes
The metabolic enzyme Acetyl-CoA Synthetase 2 (ACSS2) recently emerged as an unexpected regulator of molecular and behavioral changes associated with alcohol use. Its role during prenatal exposure, however, remains unknown. Here, we use a combination of proteomic, genomic and behavioral approaches to establish ACSS2 as a key mediator of prenatal alcohol exposure-related phenotypes. We define the developmental window during which ACSS2 translocates to nuclei in the mouse brain, and show that alcohol-derived acetate is incorporated into fetal brain histone acetylation in utero. Using genetically engineered mice not expressing ACSS2, we demonstrate that loss of this enzyme attenuates chronic prenatal alcohol exposure-induced craniofacial abnormalities, motor function deficits, cognitive impairments as well as associated chromatin and gene expression changes in the dorsal hippocampus and the cerebellar vermis. Our results outline a previously unknown mechanism underlying prenatal alcohol exposure-related phenotypes regulated by ACSS2, which will inform the development of future therapeutic interventions.

A Functional Resting-State Network Atlas Based on 420 Older Adults with Hypertension
The Risk Reduction for Alzheimer's Disease (rrAD) trial included 513 cognitively normal, sedentary, hypertensive older adults (aged 60 to 85 years) with dementia risk factors. We utilized 420 high-quality baseline resting-state functional MRI (rs-fMRI) scans from this cohort to develop a functional atlas tailored for aging populations. Typical rs-fMRI atlases derived from healthy young adults do not account for age-related changes, such as cortical atrophy, enlarged ventricles, and altered connectivity. To address this gap, we created a cohort-specific MNI-adjacent anatomical template, rrAD420, using SPM12's DARTEL registration. In this space, we derived a comprehensive functional atlas using both group independent component analysis (GICA) and probabilistic functional mode decomposition (PROFUMO). The rrAD420 atlas offers detailed representations of Resting-State Network (RSN) connectivity, encompassing unique configurations and overlapping interactions. It features two Default-Mode Network (DMN)-specific seed-based maps (DMN24 with cerebellum, DMN18 without) and data-driven components resembling the major RSNs. Furthermore, PROFUMO allowed for the identification of multimodal and combinatory networks, capturing connections within and between RSNs. While optimized for hypertensive older adults, the rrAD420 atlas serves as a versatile tool for broader aging populations, aiding in the study of neurodegenerative processes and biomarker discovery.

GPR34 regulation of disease-associated microglial states and responses to physiological stimuli
GPR34 is a microglia-enriched GPCR whose expression is downregulated under several disease conditions, including Alzheimers disease (AD) and multiple sclerosis (MS). Despite this, its function is poorly understood in normal or disease conditions, as is its contribution to disease-related microglia states. Using RNA-sequencing, we find that microglia from global Gpr34 knockout (KO) mouse brains exhibited transcriptional shifts toward disease-associated microglia (DAM) and inflammatory profiles, partially mirroring the microglial phenotype seen in 5xFAD AD model mice. Notably, when Gpr34 KO mice were crossed with 5xFAD mice, DAM transcriptional profiles and glial pathology were further exacerbated despite the already robust DAM signature driven by amyloidosis. This occurred without affecting amyloid plaque burden. In human stem cell-derived microglia (iMGLs), GPR34 KO strongly reduced calcium and phosphorylated ERK signaling in response to known GPR34 agonists, including lyso-phosphatidylserine (lysoPS) and myelin, and caused transcriptional alterations linked to immune regulation and cell proliferation. Interestingly, GPR34 loss selectively impaired phagocytosis of myelin but not amyloid-beta; or E. coli. Furthermore, GRP34 KO diminished, but did not abolish, the transcriptional response elicited by myelin. Together, these findings suggest that GPR34 is important for maintaining microglia homeostasis, mediating phagocytosis of and transcriptional response to myelin, and restraining microglial response to neurodegenerative disease conditions.

Projection-defined ventral tegmental area neurons exhibit distinct fentanyl-induced molecular and functional adaptations that differentially support drug-context associations
Synthetic opioids like fentanyl are contributing to unprecedented overdose rates. Despite the abundance of fentanyl in the illicit drug supply, an understanding of fentanyl s effects on the brain remains lacking. The ventral tegmental area (VTA) is an important site of fentanyl s rewarding actions in the brain and sends diverse projections to several regions including the nucleus accumbens (NAc) and prefrontal cortex (PFC). Previous work shows downstream projection target influences baseline properties and opioid-induced neuroadaptations in VTA, but most work has focused on single neurotransmitter-defined cell types. Here, we investigate how projection-defined VTA neurons exhibit different responses to fentanyl independent of cell type. We use RNA sequencing to show that fentanyl induces discordant transcriptional adaptations in VTA neurons that project to NAc vs PFC. We then used fiber photometry and chemogenetics to characterize functional differences in fentanyl-related behavior. We found different timescales of activation between VTA-NAc and VTA-PFC during conditioned place preference that support distinct aspects of fentanyl-context association. Together, our data demonstrate that based on projection target alone, VTA neurons can undergo vastly different adaptations in response to fentanyl, providing new insight into VTA encoding of opioid behaviors.

Early, sex-dependent and progressive proteomic imbalance in the amygdala during Alzheimers disease progression
Background: The amygdala is involved in the emotional expression, memory processing and managing stimulatory input. Although amygdala atrophy is early evidenced in Alzheimers Disease (AD), the molecular mechanisms disrupted in initial neuropathological stages are still unknown. In the present study, we investigated the proteomic impairment of the amygdaloid region from AD-Braak stage I-II and III-IV subjects to better understand the neuropathological processes occurred early in this area and to identify potential targets that may face AD from the beginning of the disease. Methods: Label-free quantitative proteomics was applied using an Orbitrap Exploris 480 mass-spectrometer in 24 postmortem amygdala specimens derived from non-demented (n=3F/5M), AD-Braak stage I-II (n=4F/4M) and AD-Braak stage III-IV (n=4F/4M). Data analysis was performed using MaxQuant and Perseus software (two-way Student T-test; p<0.05). Metascape and Ingenuity Pathway Analysis softwares were considered for biological interpretation. Connectivity map platform was used for drug repurposing analyses. Transcriptomic/proteomic data of other brain regions were obtained from AlzData, Neuropro, and Agora repositories. Results: Amygdaloid proteome of AD-Braak stage I-II and III-IV subjects compared to controls revealed a progressive proteomic impairment with a minimal overlap across Braak stages. Some of the amygdaloid DEPs were known interactors of human A{beta} plaques, APP, or Tau proteins or were previously identified at transcriptional or translational level in other brain regions affected by AD. Interestingly, amygdaloid proteome was more severely affected in women than in men with a particular protein expression profile associated to each AD stage. Comparing our sex-dependent differential proteome datasets with transcriptomic data of different brain regions, we identified potential sex-specific proteins related to cognitive decline and neurodegeneration. Finally, data-driven drug repositioning using amygdaloid omics profiles unveiled that most of the small molecule candidates were neuropathological stage and/or sex-specific. Conclusions: Early and sex-specific amygdaloid proteome dysregulation in AD highlights the consideration of a deliberate stratification by sex in future research and clinical trials to develop effective therapeutic strategies in AD for both sexes.

Intranigral injection of Alpha-Synuclein pre-formed fibrils leads to BBB compromise and Bilateral Dopaminergic Neurodegeneration in A53T Alpha-Synuclein transgenic mice.
Parkinson's disease (PD) is a progressive neurodegenerative disorder characterized by alpha-Synuclein neuronal aggregation and loss of dopaminergic (DA) neurons. Developing animal models that replicate PD neuropathological phenotypes is critical for understanding its pathophysiology and evaluating potential therapeutic targets. In this study, we show that direct unilateral injection of human Synuclein PFFs into the Substantia Nigra (SN) of mutant A53T alpha-synuclein overexpressing mice induce bilateral phosphorylated alpha-Synuclein (pS129) pathology in the SN. This pathology spreads to the striatum, cerebral cortex, and midbrain within 60 days and is accompanied by neuroinflammation in the midbrain and cerebral cortex. Additionally, we observed synuclein-dependent neurodegeneration, with a 50% reduction in Tyrosine Hydroxylase (TH) intensity in the SN and a 40% reduction in Striatum, both bilaterally. The model also revealed a compromised blood-brain barrier (BBB) and T-cell infiltration in the PFF injected animals, correlating with pS129 pathology and neuroinflammation. Taken together, we developed a mouse model that recapitulates multiple PD phenotypes, providing a valuable platform for testing therapeutic strategies targeting human alpha-Synuclein pathology and for exploring CNS-peripheral immune interactions in PD.

Longitudinal Changes in Cortical Response Dynamics with Deep Brain Stimulation to the Subcallosal Cingulate for Treatment-Resistant Depression
Deep brain stimulation (DBS) of the subcallosal cingulate cortex (SCC) is a promising intervention for treatment-resistant depression, yet objective biomarkers that track recovery remain limited. This study examined longitudinal changes in stimulation-evoked potentials (SEPs) to characterize how SCC-driven cortical communication evolves during treatment. Ten patients across three SCC-DBS trials underwent high-density EEG recordings at 4 and 24 weeks. SEP features were extracted from source-localized SCC signals and related to clinical outcomes and fractional anisotropy (FA) of midcingulate cingulum fibers. Cortical responses showed a consistent reduction in latency and an increase in magnitude over time, indicating faster and stronger electrocortical signaling with chronic stimulation. Higher baseline midcingulate FA predicted greater latency acceleration, linking SEP timing to white-matter integrity. These findings identify temporal SEP dynamics as candidate mechanistic biomarkers that reflect circuit engagement during SCC-DBS and offer a pathway toward physiology-guided optimization of neuromodulation for depression.

Split trial analysis reveals the information capacity of neural population codes
Understanding how correlated neural noise affects neural population coding represents one basic question in computational and systems neuroscience. Recent theoretical work suggest that shared noise along the stimulus encoding direction is the primary factor that limits information encoding (i.e., information-limiting noise). Despite this theoretical insight, it has been difficult to test experimentally due to the challenges in inferring information-limiting noise from neural data. To overcome this challenge, we have developed a method (i.e., split-trial analysis) based on partitioning the neural population response of an individual trial. Results from extensive numerical simulations suggest that split-trial analysis substantially outperforms existing methods in accuracy, efficiency, and robustness. Notably, it does so without estimating the noise covariance matrix, which represents a major barrier for prior studies. Applications of split-trial analysis to a number of neurophysiological datasets reveals insights into the precision of the neural codes for several systems. First, it reveals a substantial amount of information-limiting noise in the head direction system in mice. Second, it suggests a small yet positive information-limiting noise in the orientation code in mouse V1. Third, it reveals that the information-limiting noise in the macaque prefrontal cortex is highly consistent over time during a simple saccade task. Split-trial analysis is a general technique that should be widely applicable in analyzing the properties of population codes in the brain.

Proteomic Analysis in Alzheimer's Disease with Psychosis Reveals Separate Molecular Signatures for Core AD Proteinopathy and Postsynaptic Density Disruption
Background and Hypothesis: Alzheimer's disease with psychosis (AD+P) is a subgroup of AD patients with more rapid cognitive deterioration. While our previous study showed that AD+P is associated with loss of prefrontal cortex postsynaptic density (PSD) proteins, identifying proteins in the broader cellular environment that influence PSD loss addresses a critical knowledge gap about synaptic dysfunction mechanisms in early disease stages. Study Design: We conducted a proteomic analysis comparing prefrontal grey matter cortex tissue homogenates from elderly normal controls (n=18), individuals with AD+P (n=61), and individuals with AD-P (n=48), all with Braak stages 3-5. Study Results: AD+P showed the most pronounced alterations relative to controls (178 proteins with q<0.05), although alterations in AD-P and AD+P relative to controls were highly similar (R2=0.965, p<0.001). Weighted-gene correlation network analysis (WGCNA) identified four modules significantly associated with disease status, comparing AD subjects to controls, but none differed significantly between AD+P and AD-P. We identified 15 proteins significantly correlated with PSD yield across all samples, including ENPP6, linked to AD+P by GWAS. Additionally, PSD yield-associated proteins showed minimal overlap with altered AD proteins (1 of 137). WGCNA revealed one module significantly correlated with PSD yield across all samples, enriched for inflammatory terms. Conclusions: Our findings suggest a model in which AD+P arises from the combination of quantitative alterations within a shared AD proteome profile and a superimposed set of protein alterations correlated with PSD yield that are largely independent of the shared AD proteome, conferring distinct mechanisms of synaptic vulnerability and psychosis risk.

The developmental emergence of tonic and phasic REM sleep in rats
REM sleep is composed of two substates - phasic and tonic - that differ in their behavioral, sensory, and electrophysiological features. Although these substates are well characterized in adults, their developmental trajectory remains unclear. Here, we examined the development of tonic and phasic REM in rats from postnatal day (P) 12-24, spanning a period of rapid corticothalamic development. We recorded local field potentials and single units from primary motor cortex (M1), together with high-speed video and electromyographic recordings of the nuchal muscle. Periods of behavioral quiescence along with high delta power indicated NREM sleep, whereas periods of sustained muscle atonia and low delta power indicated REM sleep. At P16, M1 theta oscillations first appeared, and the delay to the first twitch increased, revealing the start of a distinct twitch-free portion of REM sleep. Motivated by this, we divided REM sleep into phasic and tonic periods, with and without twitching, respectively. Spiking activity and gamma power were consistently higher during phasic REM. At P20, phasic REM also showed faster theta oscillations than tonic REM. At P24, tonic REM was accompanied by a distinct alpha oscillation. These results show that the features distinguishing the two REM substates appear sequentially across development, revealing a progressive differentiation of REM sleep into tonic and phasic periods, a developmental refinement that may support increasingly complex forms of sleep-dependent plasticity.