bioRxiv Subject Collection: Neuroscience's Journal

OASIS: in vivo AAV-mediated transduction and genome editing of adult oligodendrocytes
New viral approaches have revolutionized neuroscience by precisely delivering genes in neurons; for example, to control or monitor activity in specific neuronal cell types. In contrast, the manipulation of oli-godendrocytes requires the Cre-LoxP system and gene-by-gene engineering, breeding, and genotyping. Here we introduce OASIS (Oligodendrocyte AAV-CRISPR mediated Specific In vivo editing System), a ver-satile platform that combines SELECTIV, an AAV-receptor-based transduction strategy, with HiUGE, an NHEJ-mediated CRISPR/Cas9 knock-in approach. We show efficient and specific oligodendrocyte trans-duction across the brain and tagging of endogenous cytoskeletal, myelin, cell adhesion, scaffolding, and junctional proteins. OASIS enables sparse yet reliable labeling, allowing direct visualization of subcellular protein localization with single-cell resolution. We successfully fused the biotin-ligase TurboID with endogenous oligodendroglial Neurofascin-155, thereby achieving targeted biotinylation of the axoglial junction. OASIS is rapidly customizable for any gene-of-interest. Together, OASIS overcomes longstand-ing barriers in oligodendrocyte biology, providing a powerful system for precise, customizable genome editing and subcellular visualization in the adult brain.

Asymmetries in hue measured behaviorally and with visual evoked potentials
Hue percepts vary more rapidly along some directions in color space (e.g. near yellow) than others (e.g. near green) with corresponding differences in the size or stimulus range of different hue categories. The basis for these differences is not known. We examined whether the asymmetries are present in early cortical color coding by comparing the strength of hue differences using visual evoked potentials (VEPs) recorded from occipital cortex. Stimuli were spatial gratings with a fixed nominal contrast in the cone-opponent plane that varied sinusoidally in hue rather than saturation. The responses to different levels of hue separation were measured by the amplitude of the frequency-tagged signals and also in behavioral measurements employing a contrast matching task. For both, the same separation in hue angle resulted in stronger responses for angular differences centered on the yellow quadrant of the cone-opponent space. Responses were also larger for the yellow than blue quadrant, ruling out a general sensitivity loss to the blue-yellow axis as the basis for the differences. The responses differences paralleled the asymmetries in the rates of change in color appearance based on analyses of previous measures of hue scaling functions. The presence of these asymmetries in the VEP responses suggests that they arise relatively early in the cortical sensory representation of color rather than emerging late as a product of inference or color category learning.

Memory recall errors reflect interacting sensory and mnemonic representations
Visual working memory (WM) enables the maintenance of information that is no longer present in the environment. Some accounts propose that WM is supported by abstract representations so that new sensory inputs do not interfere with existing memories. Others posit that early sensory representations are recruited to maintain memory precision, potentially at the cost of interference caused by new inputs. Here we tested these accounts using an orientation recall task to determine whether memory errors reflect interacting representations of sensory and mnemonic information. We found that adding noise to the memoranda and presenting feature-neutral distractors independently increased recall errors. However, distractors that shared a feature with remembered stimuli led to systematic attractive biases such that memory errors were pulled toward the orientation of the distractor. The magnitude of this bias was modulated by both stimulus noise and whether the distractor was behaviorally relevant. Our results demonstrate that while working memory can utilize abstract representations, it remains susceptible to feature-specific sensory interference, suggesting partial reliance on sensory-like codes.

Nuclear receptor-neurotransmitter coupling links behavior to metabolic state
Animals must flexibly respond to environmental stimuli to survive, and optimal responses critically depend on the organism's current needs. Many organisms have evolved both cell-intrinsic and intertissue signaling pathways that integrate metabolic status. However, how this information is encoded in molecular signals is currently not well understood. Here we show that the nematode C. elegans employs lipidated neurohormones that combine the neurotransmitter octopamine and fat metabolism-derived building blocks to relay information about lipid metabolic status and drive inhibition of aversive olfactory responses during food removal. Using targeted metabolomics, we show that lipidated neurohormone synthesis requires the carboxylesterase CEST-2.1, which links octopamine-glucosides with endogenous methyl-branched or diet-derived cyclopropane fatty acids that act as agonists of the nuclear receptor and master regulator of fat metabolism, NHR-49/PPAR. Loss of cest-2.1, loss of bacterial cyclopropane fatty acid production, or loss of endogenous biosynthesis of the methyl-branched fatty acid substrates of CEST-2.1 mimics the behavioral responses of animals lacking octopamine, indicating that regulation of neurotransmitter-dependent behavior is linked to the coordination of fat metabolism via NHR-49/PPAR. Biosynthesis and subsequent neuromodulation via lipidated neurohormone relies on an intertissue trafficking pathway in which octopamine is shuttled first into the intestine where it is chemically modified, which is likely followed by neuronal import and intracellular hydrolysis to finally release free octopamine. We propose that esterase-dependent synthesis and subsequent hydrolysis of lipidated neurohormones represents a chemical encoding mechanism by which animals integrate information from neurotransmitter signaling and lipid homeostasis to direct appropriate behaviors.

Voluntary Dissociation of Motor Unit Activity in the Vastii Muscles
The CNS coordinates movement through consistent activation patterns across muscles and motor units, suggesting the presence of a relatively fixed and high-dimensional number of neural constraints on voluntary actions. In the human quadriceps, the vastus medialis (VM) and vastus lateralis (VL) control the knee extensor torque and are considered a synergistic pair largely activated by shared neural inputs. However, some evidence suggests that these muscles, or even subregions within them, can be controlled independently. In this study, we investigated whether humans can dissociate neural input to VM and VL during isometric contractions. Ten participants received real-time feedback from multiple intramuscular EMG electrodes that targeted different regions of the VM and VL while attempting to activate each muscle or sub-regions selectively. We found that nine out of ten subjects were able to clearly separate VM and VL activity based on the intramuscular EMG feedback. However, motor unit decomposition from the intramuscular EMGs revealed that selective recruitment of a unique set of motor units was possible only within the proximal region of VM. In contrast, VL and distal VM showed highly correlated activation, indicating tight functional coupling. Correlation analyses confirmed that the proximal VM exhibited distinct activation profiles compared with both distal VM and VL, supporting the existence of compartmentalized control within VM. These findings demonstrate that it is possible to dissociate the activation of motor units within this synergistic muscle group during low-force isometric contractions.

Parkinson's disease risk factors are expressed at brain barriers.
Parkinson's disease (PD) is characterized by the selective loss of dopaminergic neurons in the substantia nigra pars compacta, but whether its etiology is cell autonomous remains unclear. Increasing evidence implicates the blood-central nervous system (CNS) barriers in disease development, highlighting the importance of identifying genetic risk factors linked to cells forming the cerebrovasculature to advance this emerging area of research. The objective of this study is to identify PD genetic risk factors associated with blood-brain (BBB) and blood-cerebrospinal fluid (BCSFB) barriers, and to validate protein localization in human tissue and experimental models. To do so, we integrated genome-wide association studies and single nuclei RNA-sequencing datasets from the human postmortem substantia nigra (SN), midbrain, or cortical samples from control and PD donors. An in-depth bioinformatics analysis identified genes enriched in cell types that form the multicellular architecture of brain barriers, including CAVIN2, ANXA1, ANO2, and LRP1B. We further validated whether corresponding proteins were present in cell types associated with the blood-CNS barriers in human and mouse post-mortem tissues, as well as in iPSC-differentiated cells and choroid plexus organoids. Results showed that quantifying the proportion of endothelial cells expressing PD-related genes was under-evaluated at the transcript level compared to immunofluorescence analyses. In addition, we observed that CAVIN2 and ANXA1 proteins were more abundant at the vasculature of the substantia nigra vs. cortex, and CAVIN2 protein levels were reduced in PD vs. control human postmortem tissues. In contrast, the investigation of mouse postmortem samples demonstrated that the CAVIN2 protein is only present in a subset of mouse blood vessels, compared to nearly all vessels in human tissue. Similarly, mouse ANXA1 protein localizes to dopaminergic neurons of the substantia nigra and not at the vasculature, as seen in human tissue. The primary outcome of this study is the identification of PD-relevant risk genes specifically expressed at brain barriers and enriched in PD-relevant brain regions. The secondary outcome is the demonstration of poor transcript-protein correlation in - at least - a subset of PD risk factors, and a low interspecies conservation of protein localization for the selected candidates. In conclusion, the BBB and BCSFB may represent understudied contributors to PD, endothelial-specific proteins appear differentially regulated compared to transcripts, and experimental models require comprehensive validation to ensure relevance to the human condition.

PDZD8 deficiency drives lipid accumulation in SNr and dopaminergic disinhibition
The basal ganglia integrate cortical inputs to regulate motor, cognitive, and emotional behaviors through precisely balanced inhibitory and excitatory circuits. The substantia nigra pars reticulata (SNr) serves as a major output nucleus exerting tonic inhibition over thalamic and midbrain targets. However, how lipid metabolic disturbances affect SNr circuitry and dopaminergic regulation remains unclear. Here, we identify a crucial role for the lipid transport protein PDZD8 in maintaining basal ganglia circuit integrity. PDZD8 deficiency leads to marked lipid and lipofuscin accumulation selectively in the SNr, accompanied by enhanced striatal inhibitory inputs and reduced SNr projections to the ventromedial thalamus (VM) and midbrain dopaminergic nuclei (SNc, VTA). This circuit reorganization results in functional disinhibition and hyperactivation of dopaminergic neurons, producing maladaptive reinforcement of striatal inhibition. Our previous findings revealed that PDZD8 deficient mice exhibit hyperactivity, reduced anxiety, and impaired fear memory, behavioral phenotypes reminiscent of attention deficit/hyperactivity disorder (ADHD). These findings demonstrate that lipid accumulation in the SNr disrupts inhibitory output and dopaminergic regulation, forming a maladaptive basal ganglia thalamocortical loop. Our study provides the first mechanistic link between lipid metabolic dysfunction, dopaminergic disinhibition, and ADHD like behavioral phenotypes, highlighting PDZD8 as a key regulator of metabolic circuit coupling in the basal ganglia.

Comparative gene editing reduces dopamine receptor levels across rodent species
Translational challenges in neuroscience originate from species-specific differences that limit the generalizability of experimental findings. Comparative approaches can help distinguish conserved from species-specific mechanisms, but their application has been limited by the lack of molecular tools beyond traditional model organisms, complicating direct comparisons of conserved and divergent mechanisms of neural function. This gap is particularly evident for the dopaminergic system, a key regulator of motivated behaviors across species and the principal pharmacological target for current psychotherapies. Building on our recent development of comparative gene editing, we here present an adeno-associated virus-mediated CRISPR/Cas9 strategy to reduce in vivo dopamine receptors D1 and D2 levels across the rodent phylogeny. Using this approach, we achieved specific reduction of receptor levels in three rodent species (house mouse, prairie vole, and Syrian hamster), which we demonstrate with radioactive ligand binding assays. This toolkit expands the reach of comparative gene editing approaches, enabling functional investigation of the dopaminergic system across rodent species. Thereby, it supports comparative neuroscience by facilitating the identification of conserved versus species-specific neural mechanisms with enhanced translational potential.

Cardiac-neurovascular crosstalk: Cardiac rhythms reveal maladaptive cerebral autoregulation and constrained ventilatory status
In the context of brain-heart interactions, several pathways have been proposed to mediate feedback loops between neurophysiological oscillations. However, the role of cerebrovascular dynamics in shaping this interplay remains poorly understood. In particular, the interaction between cardiac autonomic control, ventilation mechanisms, and cerebral autoregulation is not well characterized, especially in ageing and post-stroke conditions, where cerebral perfusion is often compromised. In a cohort of 57 elderly participants, including 30 stroke survivors, we investigated the relationship between cardiac sympathetic activity and both, cerebral blood flow regulation and ventilatory status. Sympathetic reflexes, assessed via cardiac sympathetic index (CSI) during sit-to-stand transitions, were preserved across all participants, with no significant group differences between stroke and non-stroke populations. However, among individuals with constrained ventilation, indexed by reduced end-tidal CO2 (EtCO2) at baseline, we identified a more elevated CSI following postural change, scaling with the degree of CO2 dysregulation. Furthermore, transcranial Doppler measurements revealed exaggerated changes in mean flow velocity (MFV) within the right middle cerebral artery in most participants. These MFV shifts significantly correlated with the magnitude of cardiac sympathetic change under orthostatic stress, suggesting that CSI can capture maladaptive neurovascular responses. Together, these findings highlight a distinct cardiac-neurovascular crosstalk in elderly individuals, revealing a potential mechanism of compensatory overactivation under impaired cerebrovascular control.

Modelling Predictive Coding in the Primary Visual Cortex (V1): Layer 4 Receptive Field Properties in a Balanced Recurrent Spiking Neuronal Network
Understanding how the cortex encodes sensory input in a biologically efficient and computationally robust manner remains a central question in neuroscience. Predictive coding offers a compelling theoretical framework for such cortical processing, but existing models lack the biological detail to fully explain the function of the cortical microcircuits. This study introduces a spiking neural network model of layer 4 of the primary visual cortex (V1), grounded in predictive coding principles, to clarify how the thalamorecipient layer transforms feedforward input into prediction-error-like signals under realistic excitatory-inhibitory constraints and to yield testable circuit-level predictions. The model integrates structured feedforward input, distinct excitatory and inhibitory populations, and balanced lateral connectivity to simulate spontaneous and stimulus-driven activity. Network responses are systematically examined under spatially unstructured noise input and structured grating stimuli. Neural membrane potentials encode real-time reconstruction errors between external input and internal estimates, with spikes dynamically correcting these mismatches. The network reproduces hallmark in vivo features, including irregular spontaneous activity, sparse and selective responses, and emergent orientation and phase tuning. Excitatory-Inhibitory (E-I) balance was maintained across conditions, with inhibitory neurons exhibiting tighter input coupling than excitatory neurons. Furthermore, the network exhibited contrast-dependent modulation of firing rates and E-I balance, dynamically adjusting its activity to changes in input strength. Decoding analyses demonstrates that structured inputs can be robustly reconstructed under moderate noise levels, although decoding fidelity declines sharply under severe corruption. Together, these results suggest that cortical layer 4 may serve as a structured sensory encoding stage in a hierarchical predictive coding system, providing a biologically grounded foundation for modeling prediction error computations in higher cortical areas.

Neuroprotective action of agonists and modulators of A 1 adenosine receptors upon hyperexcitation: mechanism of the antiepileptic activity and role of neuron-glial interaction
Hyperexcitation of neuronal networks is believed to be the main reason for the excitotoxic death of neurons in different central nervous system pathologies, including epilepsy, ischemic stroke, and traumatic brain injury. G i-coupled receptors can be considered as promising targets for the development of new neuroprotectors. Here, we studied the anticonvulsant activity of the agonists and positive allosteric modulators (PAM) of A 1 adenosine receptors (A 1 Rs). Our experiments demonstrate that A 1 R agonists, CCPA and N 6-cyclohexyladenosine (N 6-CHA), suppress hyperexcitation in three different in vitro models , including acute glutamate excitotoxicity, NH 4 Cl-and bicuculline-induced epileptiform activity. We have found that the inhibitory action of the agonists is mediated by the activation of not only the neuronal A 1 Rs but also the astrocytic receptors. In astrocytes, A 1 R agonists enhance GABA release, possibly via induction of calcium transients. Using inhibitory analysis, we have demonstrated that G{beta}{gamma}-mediated activation of phospholipase C and subsequent Ca 2+ mobilization from internal stores are essential for generating calcium transients in astrocytes following N 6-CHA application. We have shown first that Ca 2+-dependent activation of protein kinase C, which is involved in the mechanism of GABA release by astrocytes, is a pivotal step in the realization of the antiepileptic action of A 1 R agonists. Moreover, using the model of epileptiform activity induced by GABA A R blockade, we have shown that PAMs, PD81723 and VCP171, also suppress hyperexcitation. Furthermore, using the picrotoxin-induced epilepsy model in mice, we demonstrated that A 1 R agonists exhibit significant anticonvulsant effects and improve animal survival. The PAMs PD81723 and VCP171, when administered one hour before seizure induction, did not significantly affect seizure severity or survival rates. However, chronic administration of VCP171 produced a pronounced anticonvulsant effect and significantly increased survival.. Importantly, PAMs provided therapeutic benefits without significantly affecting overall activity levels in mice. Thus, our study demonstrates that both agonists and PAMs of A 1 R can be considered as potential therapeutic agents with antiepileptic and neuroprotective activity.

Imagined movement increases the segregation of brain-heart networks
Understanding the mechanisms of motor imagery, the mental simulation of movement without execution, is key for the development of neurotechnologies. For instance, for detecting covert motor intent in noncommunicative patients or refining motor commands through brain-computer interfaces. While motor imagery engages motor-related brain regions, its precise mechanisms remain unclear, particularly in relation to cardiac dynamics. Evidence suggests heart-rate variability features have potential to enhance tasks classifications, yet the brain-heart relationship is not well understood. In this study, we examined motor imagery learning using a task involving right-hand grasping imagery. We found that motor imagery is correlated with a cardiac sympathetic uncoupling with directed connectivity within the motor cortex. Additionally, cerebellar-supplementary motor area segregation, in relation to cardiac parasympathetic activity, indexed longitudinal motor learning. These results suggest that varying patterns of heart rhythmicity and brain connectivity within the motor network actively change during motor imagery, suggesting the brain-heart axis as influencer of sensorimotor function and associated neuroplasticity of learning.

Indirect Deuterium Displacement Exchange Imaging for Non-invasive High-Resolution CSF Production Mapping
Cerebrospinal fluid (CSF) production is central to brain homeostasis, yet existing measurement techniques are invasive, technically demanding, and confounded by intracranial perturbations. Here, we introduce indirect deuterium displacement exchange imaging (CSF-iDDxI), a noninvasive MRI approach for mapping CSF production in vivo. The method leverages intravenously infused deuterium oxide (D2O), which crosses the blood-CSF barrier, replaces existing H2O in CSF, producing concentration-dependent attenuation of proton (1H) signal within CSF spaces. Using high-resolution 3D balanced steady-state free precession MRI in rats, we demonstrate robust and spatially widespread D2O-induced CSF signal loss that is selectively suppressed by acetazolamide, a carbonic anhydrase inhibitor known to suppress CSF production by the choroid plexus. Dynamic imaging during intravenous D2O infusion further revealed that cortical parenchymal signal changes were unaffected by acetazolamide, confirming specificity to CSF production. Exploratory kinetic modeling estimated rapid CSF water turnover (k ~ 0.09 min-1) under physiological conditions, reduced to k ~ 0.031 min-1 with acetazolamide suppression, consistent with prior isotope tracer studies. Together, these findings establish CSF-iDDxI as a sensitive, pharmacologically validated tool for quantifying CSF production and turnover.

A human brain network specialized for abstract formal reasoning
Humans stand out in the animal kingdom for their ability to reason in highly abstract ways. Using a deep-data precision fMRI approach, we identify and richly characterize a network of frontal brain areas that support abstract formal reasoning. This 'abstract reasoning' network robustly dissociates from the domain-general Multiple Demand network--the current leading candidate substrate of fluid intelligence--as well as from three other networks supporting high-level cognition: the language network, the intuitive physical reasoning network, and the social reasoning network. Finally, the areas of this network respond robustly during both deductive and inductive reasoning, during classic matrix reasoning problems, and when solving multiplication and division problems. This network may therefore support the most abstract forms of reasoning, possibly constituting a human-specific adaptation.

Resolving temporal threat uncertainty by observational learning involves the amygdala, hippocampus and anterior insula
While the neurobiological distinction between temporally predictable (cued) and unpredictable (contextual) threats has been well-characterized in direct learning using the NPU paradigm, it is poorly understood how these processes unfold during observational learning, a key mechanism of human threat-learning. In this study, we developed a novel observational paradigm based on the NPU paradigm (Experiment 1, n=20, male and female) and combined it with fMRI (Experiment 2, n=23, male and female) to investigate how the brain encodes predictable and unpredictable threat cues observed in others. Participants learned predictable (P), unpredictable (U), and no-threat (N) cues by observation and encountered the same threat cues during an expression phase. Threat expectations indicated that participants successfully learned threat contingencies, showing heightened threat expectations for predictable cues and unpredictable contexts. This converged with neural responses in the anterior insula during the expression phase. Reflecting the dynamic process of learning, the amygdala responded to predictable threat cues with a linear decrease across trials. Interestingly, we found that learning to predict threats from others pain was accompanied by enhanced neural response within the amygdala, insula and hippocampus, as compared to unpredictable conditions. Our findings suggest that humans learn to resolve temporal uncertainty relying solely on observation. The ability to learn shapes the neural response to an observed threat.

Astrocytic PIEZO activation by heartbeat sound promotes extracellular matrix and maturation in human brain organoids
Heartbeat sound is one of the first rhythmic stimuli encountered by the developing human brain, yet its biological role has remained unexplored. Here we show that heartbeat sound promotes structural and functional maturation of human cortical organoids with a physiological astrocyte-to-neuron ratio. Continuous stimulation with heartbeat expanded the extracellular space (ECS), visualized by super-resolution 3D STED and 2-photon shadow imaging, and increased extracellular matrix (ECM) synthesis, detected by LC-MS/MS proteomics. Heartbeat sound promoted neuronal and astrocytic differentiation, synaptogenesis, and organoid maturation, as shown by single-cell RNA sequencing, synaptic marker immunohistochemistry, and high-density multielectrode electrophysiology. Transcriptomic analyses demonstrated astrocyte-specific expression of mechanosensitive PIEZO channels. Using Ca2+ imaging, we confirmed that low-frequency sound stimulation, including heartbeat, activates PIEZO-mediated Ca2+ responses, which in turn upregulate astrocytic ECM synthesis. Experiments with biomimetic hydrogels demonstrated that physiological matrix stiffness attenuates PIEZO activation, suggesting a mechanoprotective mechanism. Our findings demonstrate a fundamental mechanism for inducing ECM synthesis and neural differentiation through astrocytic PIEZO activation by heartbeat sound, suggesting that interoception of the internal acoustic environment is an underappreciated driver of human brain development.

Musicianship and active musical engagement predict facilitation of auditory-motor plasticity: evidence from auditory-motor paired associative stimulation
Abstract: Background and Aim: Auditory motor paired associative stimulation (PAS) probes experience dependent plasticity in auditory motor circuits. We tested whether musical experience and musical sophistication modulate PAS induced facilitation when instrument tones are paired with transcranial magnetic stimulation (TMS) over the left primary motor cortex. Method: Sixteen musicians and thirteen non-musicians completed two sessions. Session 1 estimated an individualized inter-stimulus interval (ISI) by testing seven tone TMS delays (25 to 300 ms). Session 2 applied PAS at the optimal ISI. Corticospinal excitability was assessed by motor evoked potentials (MEPs) from right first dorsal interosseus at baseline and post-intervention. Group comparisons and a stepwise multiple regression with Goldsmiths Musical Sophistication Index (Gold MSI) subscales evaluated predictors of the PAS effect. Results: A stepwise multiple regression model selected Group and Active Engagement (Gold MSI Factor 1) as independent predictors (F (2,26) = 4.59, p = 0.020, adjusted R2 = 0.204), without interaction: musicians exhibited smaller facilitation than non-musicians, and higher Active Engagement predicted greater facilitation across groups. Discussion: The lack of facilitation in musicians contrasts with somatosensory PAS reports of enhanced plasticity in experts. A modality specific ceiling effect may contribute, whereby long term training optimizes auditory motor transmission, reducing headroom for facilitation. The association with Active Engagement suggests motivational/reward mechanisms potentially dopaminergic gate responsiveness to auditory motor PAS. Conclusion: Under this protocol, auditory motor PAS with instrument tones facilitated corticospinal excitability in non-musicians but not in musicians. Individual differences in Active Engagement predicted facilitation, indicating that both group membership and active musical engagement shape susceptibility to auditory motor associative plasticity.

Frontal cortex encodes action goals and social context in freely moving and socially interacting macaques
Despite decades of research on goal-directed behavior in primates, our understanding of frontal cortical circuits in natural social contexts remains very limited. Classic studies with macaques revealed rich motor representations in both ventral premotor (PMv) and ventrolateral prefrontal cortex (vlPFC), but the limitations imposed by constrained tasks offered a limited window to investigate the complexity of natural behaviors and social interactions. Freely-moving wireless electrophysiological recordings allowed us to investigate the involvement of these areas during different spontaneous behaviors, including social affiliative interactions, and revealed a robust encoding of the social context of motor actions in both PMv and vlPFC. This provides novel evidence that the frontal lobe integrates social information in naturalistic settings, bridging motor control and social cognition, highlighting the need for ecological neuroscience approaches.

Elevated activity of the mesolimbic dopamine system promotes feeding during pregnancy in mice
The pregnancy period is accompanied by increased feeding behavior to accommodate the elevated energy demands associated with fetal growth and development. However, the underlying neural circuitry and molecular mechanisms mediating increased feeding during pregnancy are largely unknown. Here, we utilize a combination of fiber photometry, chemogenetics, and mouse behavioral assays to characterize altered feeding behavior during pregnancy in mice. We uncover that pregnancy increases the activity of the mesolimbic dopamine system during both homeostatic and hedonic feeding behavior in mice. VTA dopamine neurons are ultimately required for promoting increased hedonic feeding during pregnancy as inhibition of these cells selectively reduces acute high fat diet intake in pregnant mice. Further, pregnant mice exhibit increased sensitivity to food deprivation, an effect which requires activity of the mesolimbic dopamine system. Together, these findings provide a circuit basis mediating altered hedonic feeding behavior and sensitivity to negative energy balance during pregnancy in mice.

The serotonin 1B receptor modulates striatal activity differentially based on behavioral context
The dorsomedial striatum (DMS) is critical for goal-directed behavior and has been implicated in both motivating and inhibiting behavioral responses. The DMS circuitry is complex as it integrates multiple inputs from the cortex, thalamus, and other subcortical structures including midbrain dopamine neurons. Though less studied, serotonin neurons from the dorsal raphe nucleus also richly innervate the DMS, which expresses the majority of the 14 receptor subtypes for serotonin. In particular, slice electrophysiology shows that the serotonin 1B receptor (5-HT1BR) impacts DMS physiology and plasticity, and behavioral experiments show that 5-HT1BR expression modulates impulsivity and other DMS-dependent reward-related behaviors. In these studies, our goal was to investigate the effects of 5-HT1BR on the DMS in vivo during goal-directed behavior in mice. Using a genetic 5-HT1BR loss-of-function model, we examined the calcium activity of individual medium spiny neurons (MSNs) in the DMS during operant tasks of responding and waiting. We found that knockout of 5-HT1BRs resulted in a significant reduction of excitatory calcium responses and an increase in the proportion of cells with inhibitory calcium responses following receipt of a reward. This suggests that serotonin may recruit MSN activity in response to reward via actions at 5-HT1BRs. On the other hand, in a behavioral paradigm designed to test impulsivity, we found that serotonin may inhibit DMS calcium activity through 5-HT1BRs. Specifically, mice lacking 5-HT1BR expression had a larger proportion of cells showing increased calcium responses during the waiting period of the trial, compared to controls. These results point to the importance of in vivo studies to understand the functional role of DMS serotonin in reward-related behavior. Overall our results demonstrate that serotonin can modulate the DMS in a behavioral state-specific manner, potentially providing a mechanism for how serotonin effects on behavior are context-dependent.

Exploring the functions of JAKMIP1 in neuronal IL-6/STAT3 signaling and its relevance to chromosome 15q-duplication syndrome
Growing evidence supports neuroinflammation as a risk factor for neurodevelopmental and psychiatric disorders. Interleukin 6 (IL-6), a classical pro-inflammatory cytokine, has been associated with autism spectrum disorder (ASD)-related phenotypes. To better understand molecular factors that modify neuronal cytokine responses in ASD, we investigated potential roles for JAKMIP1, a gene linked to chromosome 15q-duplication syndrome (Dup15q; a form of syndromic ASD), in regulating IL-6/STAT3 signaling. We observe that JAKMIP1 deficiency impairs IL-6/STAT3 signaling and IL-6-induced neuritogenesis in SH-SY5Y cells; and discover that JAKMIP1 may regulate STAT3 expression via its C-terminus, which exhibits nucleoplasmic localization. Additionally, we find that IL-6/STAT3 signaling is altered in Dup15q hiPSCs-derived cortical neurons, which display heightened responsiveness to IL-6; though it is unclear whether and how JAKMIP1 contributes to this. Overall, our findings identify JAKMIP1 as a modulator of neuronal IL-6/STAT3 signaling and support that ASD-linked genetic variants can alter the inflammatory landscape of ASD.

Burst suppression: a default brain state associated with loss of network complexity
Burst suppression (BS) is a highly stereotyped EEG pattern observed across a wide range of clinical contexts, from general anesthesia and postanoxic coma to neonatal encephalopathy. Despite its consistent appearance, BS comprises two distinct forms with markedly different implications. BS with identical bursts (IBS) is almost exclusively seen in patients with severe, irreversible encephalopathy and is consistently associated with poor neurological outcome. In contrast, heterogeneous BS (HBS) can appear in reversible conditions such as anesthesia. The mechanisms that give rise to these divergent forms remain elusive. Existing theories impose disease-specific processes on otherwise healthy networks, but such models fail to explain why BS emerges across diverse etiologies and disregard the clinically critical distinction between IBS and HBS. We combined clinical, experimental, and computational approaches to identify shared mechanisms underlying BS. We analyzed EEG recordings from patients with a severe postanoxic encephalopathy and from patients undergoing general anesthesia. These clinical observations were compared with activity recordings from human induced pluripotent stem cell-derived neuronal networks and rodent cortical cultures, and simulations of biophysically grounded neuronal network models. Purely excitatory, low-complexity networks, both in vitro and in silico, spontaneously generated activity virtually indistinguishable from pathological IBS. Introducing inhibitory neurons, modular network structure, or diverse external inputs progressively increased signal complexity and produced HBS-like or continuous activity resembling physiological EEG. Our findings suggest that BS, and particularly IBS, reflects a default dynamic state of simplified excitatory networks that emerges when biological complexity is lost. Different clinical conditions may compromise distinct mechanisms--inhibition, connectivity, or afferent input--yet converge on the same underlying activity pattern. While IBS reflects near-complete loss of complexity, HBS indicates partial preservation. This unified framework explains how diverse etiologies converge on BS and highlights identical forms as signatures of severely reduced network complexity.

PGC-1α and PPARs cooperatively mediate photoreceptor neuroprotection in rd1 mouse inherited retinal degeneration
Retinitis pigmentosa (RP) is a group of inherited diseases characterized by a primary rod photoreceptor dysfunction and progressive rod and cone cell death. Due to their very high energy demand, the degeneration of photoreceptors may be linked to insufficient energy supply or metabolic imbalance. Critical transcription factors that regulate metabolism such as peroxisome proliferator-activated receptors (PPARs) and their co-activator PGC-1 have been found to play important roles in neurodegenerative diseases, but their potential roles in RP have yet not been disclosed. In this study, we used organotypic retinal explant cultures derived from the rd1 mouse model for RP to investigate the effects of PPAR, PPAR{gamma}, PPAR{beta}/{delta} agonists, as well as PGC-1 activation and inhibition. Photoreceptor death in the outer nuclear layer (ONL) of the retina was quantified using the TUNEL assay, while in situ activity assays were used to monitor effects of PPARs and PGC-1 on poly(ADP-ribose)polymerase (PARP) and calpain activity. In addition, we performed immunostainings to evaluate poly(ADP-ribose) (PAR) generation and activation of calpain-1 and calpain-2. We found that PPAR{beta}/{delta} agonists had limited effects, while activation of PPAR, PPAR{gamma}, and PGC-1 significantly reduced photoreceptor death and PARP activity in rd1 retina. Conversely, inhibition of PGC-1 had a strong detrimental effect on photoreceptor viability. Activation of the histone deacetylase sirtuin-1, an upstream agonist of PGC-1, had no effect unless it was combined with simultaneous inhibition of PARP. Furthermore, PPAR{gamma} and PGC-1 effectively suppressed overall calpain activity and overactivation of calpain-2, alleviating photoreceptor degeneration caused by Ca2+ imbalance. In summary, our data supports the concept of a PARP-sirtuin-1-PGC-1-PPAR-PARP feedback control that connects defective energy metabolism to photoreceptor degeneration. Specifically, our findings suggest that PPAR, PPAR{gamma}, and PGC-1 cooperate to preserve photoreceptor viability, highlighting PPAR signaling as a promising target for future therapeutic interventions.

Selective reduction of KCNA4 in vulnerable glutamatergic-serotonin neurons of the dorsal raphe nucleus in Alzheimers Disease
INTRODUCTIONWe previously demonstrated that htau mice recapitulate many neuropsychiatric features of early Alzheimers disease (AD), and that the dorsal raphe nucleus (DRN) contains distinct subregions. Herein, we investigate vulnerability of the centromedial DRN to pathologically-phosphorylated tau (pTau), a region composed predominantly of dually serotonergic/glutamatergic (5HT/glut) neurons.

METHODSWe use computational, molecular, biophysical, and behavioral techniques to assess the centromedial DRN across preclinical and post-mortem settings.

RESULTSThe centromedial DRN contains 5HT/glut neurons that differentially express ion-channel genes in the htau mouse. 5HT/glut neurons exhibit increased excitability, which we demonstrate may dually promote pTau accumulation and the severity of depressive-like behaviors in htau mice. At Braak 2, KCNA4 is reduced in 5HT/glut neurons in AD, which are especially vulnerable to pTau compared to 5HT-nonglut neurons.

DISCUSSIONTau-mediated dysfunction of the DRN may be driven by changes in ion channel activity that concomitantly promote the spread of pTau in Braak progression.

Resting-state Functional Connections with the Hippocampus and with the Caudate Nucleus Predict Working Memory Performance in Multiple Sclerosis
Episodic memory (EM) dysfunction is a common symptom of multiple sclerosis (MS). A related process, working memory (WM), supports long-term EM and is often also impaired. Functional connectivity (FC) between the hippocampus and caudate nucleus supports EM performance. However, this connectivity's specific influences on WM performance in MS is relatively unknown. Resting-state FC (RSFC) possesses clinical utility, including predicting cognitive impairments before they are captured by assessment. The present study tested whether RSFC with the hippocampus and caudate could predict WM performance in people with MS and in healthy individuals (HC). In a secondary analysis of 78 participants (42 MS, 36 HC), RSFC between the hippocampus, caudate nucleus, and other regions was quantified. These connections' predictive influence on WM performance was then examined using a global WM performance measure for a subset with available neuropsychological data (26 MS, 15 HC). Across the entire sample (N=78), MS participants displayed stronger coupling between the right hippocampus and left dorsomedial prefrontal cortex, compared to HC participants. Within MS participants, stronger coupling between the left hippocampus (LHipp) and left ventral anterior cingulate (LvACC), and between the left caudate (LCaud) and right insula, were observed. Stronger decoupling between the LHipp and left supramarginal gyrus (LSMG) also emerged. Stronger LHipp-LvACC connectivity predicted worse WM performance, whereas stronger LHipp-LSMG connectivity and LCaud-RInsula connectivity each predicted better performance. The hippocampal connections were also inversely correlated. Findings identify a caudate circuit and potential hippocampal network whose aberrant, intrinsic activity could serve as neural markers for WM dysfunction in MS.

Architecture of Near-Death Experience Spaces
Near-Death Experiences (NDEs) challenge conventional research methods, as they are often described as exceeding the limits of verbal expression. While most studies rely on narrative accounts, little attention has been given to graphic representations as a complementary mode of investigation. This study employs a hybrid approach combining a semi-structured digital questionnaire with a graphic reconstruction task. Participants first segmented their Out-of-Body Experience (OBE) and NDE into distinct experiential sequences by assigning chronological numbers to each phase. This sequencing enabled the identification and isolation of the core NDE component across participants. The graphic reconstructions represent each perceived space, Self-Location (S-L), the perceived spatial position where one experiences oneself to be located and Self-Motion (S-M), the perceived spatial trajectories and directionalities of oneself within these visuo-spatial configurations. This dual-method design was intended to capture experiential features of OBEs and NDEs that may not be conveyed through verbal reports alone. Notably, OBEs have rarely been examined regarding their independence from or conjunction with NDEs, nor their placement within the overall temporal sequence. The graphic reconstructions revealed consistent visual-field invariants: conical forms, elliptic arcs with variable Visual-Field Extents (VFE), and ellipsoidal configurations, each correlated with specific chromatic and luminance perceptual qualities of the Visual Field (VF).

DNA Break Induced Epigenetic Alterations Promote Plaque Formation and Behavioral Deficits in an Alzheimer's Disease Mouse Model
The dramatic increase in human longevity over recent decades has contributed to a rising prevalence of age-related diseases, including neurodegenerative disorders such as Alzheimer's disease (AD). While accumulating evidence implicates DNA damage and epigenetic alterations in the pathogenesis of AD, their precise mechanistic role remains unclear. To address this, we developed a novel mouse model, DICE (Dementia from Inducible Changes to the Epigenome), by crossing the APP/PSEN1 (APP/PS1) transgenic AD model with the ICE (Inducible Changes to the Epigenome) model, which allows for the controlled induction of double-strand DNA breaks (DSBs) to stimulate aging-related epigenetic drift. We hypothesized that DNA damage induced epigenetic alterations could influence the onset and progression of AD pathology. After experiencing DNA damage for four weeks, DICE mice, together with control, ICE, and APP/PS1 mice, were allowed to recover for six weeks before undergoing a battery of behavioral assessments including the open-field test, light/dark preference test, elevated plus maze, Y-maze, Barnes maze, social interaction, acoustic startle, and pre-pulse inhibition (PPI). Molecular and histological analyses were then performed to assess amyloid-beta pathology and neuroinflammatory markers. Our findings reveal that DNA damage-induced epigenetic changes significantly affect cognitive behavior and alters amyloid-beta plaque morphology and neuroinflammation as early as six months of age. These results provide the first direct evidence that DNA damage can modulate amyloid pathology in a genetically susceptible AD model. Future studies will be aimed at investigating DNA damage-induced epigenetic remodeling across additional models of AD and neurodegeneration to further elucidate its role in brain aging and disease progression.

A clinical grade neurostimulation implant for hierarchical control of physiological activity
Bioelectronic implants for neurostimulation aim to steer disordered neurophysiological processes back towards a healthy state. However, physiology is subject to biological rhythms, including the circadian rhythm and the sleep-wake cycle. These predictable rhythms affect disease symptomatology, biomarkers used in closed-loop therapies, and a physiological system's expected response to stimulation. Therefore, therapeutic devices should incorporate feedforward elements to align algorithm parameters with predictable changes in physiological state, as a parallel of physiological rheostatic control. Here we introduce the DyNeuMo-2c, the first clinical-grade implant capable of delivering closed-loop neurostimulation while flexibly changing its functional configuration according to time of day. The device can chronically measure brain activity and motion state to track potential biomarker patterns in natural, out-of-clinic settings, allowing identification and targeting of patient-specific chronotypes. The system implements a hierarchical control flow, with baseline therapy set by a circadian scheduler, and adaptive policies layered to take effect based on specific biomarkers indicating patient and disease state. Using a benchtop validation setup, we demonstrate that the system has the required capabilities for delivering time-contingent closed-loop therapy in two established clinical use cases: Parkinson's disease and epilepsy. Next, we deploy the system in vivo to deliver closed-loop deep brain stimulation in a healthy non-human primate model of vigilance, highlighting the importance of synchronisation between device operation and physiological state in various conditions (task performance, unconstrained behaviour, and sleep). Time-of-day-dependent adaptation of closed-loop stimulation enabled modulation of both vigilance and behaviour. Overall, the novel device architecture provides a proof-of-concept for delivering time-contingent therapy in chronic therapeutic settings where biological rhythms are of key importance.

Luteal-phase resistance training enhances nocturnal heat dissipation and delta power during sleep
Study Objectives: This study examined the effects of resistance training on sleep architecture, physiological heat dissipation, and {delta} power in young adult women during the follicular and luteal phases of the menstrual cycle. Methods: Twelve healthy young women participated in a four-condition crossover protocol comprising (1) follicular phase non-exercise, (2) follicular phase exercise, (3) luteal phase non-exercise, and (4) luteal phase exercise. The exercise condition consisted of 30 minutes of resistance training at 70% of one-repetition maximum performed during the day. During each night, electroencephalography, body temperature, and core body temperature were measured in the home environment. The distal-proximal body temperature gradient (DPG), which is a validated indicator of heat dissipation, was calculated. Results: Resistance training enhanced heat dissipation, as reflected by increased DPG values, and increased the proportion of stage N3 sleep during both menstrual cycle phases, with more pronounced effects during the luteal phase. Sleep from bedtime to wake time was divided into four equal segments. Under the luteal phase with exercise, the appearance of stage N3, {delta} power, and the DPG were elevated in the mid-to-late segments of sleep. Conclusions: These findings suggest that daytime resistance training promotes nocturnal deep sleep and facilitates thermoregulatory heat loss, as indicated by an increased DPG, particularly during the luteal phase when thermoregulation is less stable than the follicular phase. This training may represent a practical intervention to improve sleep quality and physiological recovery in women across different phases of the menstrual cycle.

MRI-Based Quantification of Central Nervous System Tissue and Cerebrospinal Fluid Volumes in Developing Pigs
There is a growing need for alternative animal models to test brain-targeted therapies, and pigs are emerging as a promising option. Their utility, however, depends on reliable estimations of central nervous system (CNS) tissue and cerebrospinal fluid (CSF) volumes, which are essential for translating therapeutic doses between studies in animals and humans. To address this need, we conducted a cross-sectional study of 12 commercial pigs (Sus scrofa) across four age groups (2, 5, 11, and 19 weeks). High-resolution magnetic resonance images (MRI) of the brain and spinal cord were acquired using T2-weighted turbo spin echo with fat saturation and short tau inversion recovery scans. CNS tissue and CSF volumes were segmented and quantified using 3D Slicer, along with additional anatomical measurements. Our findings reveal notable age-related changes, including spinal CSF volume surpassing brain CSF volume in older pigs, highlighting shifts in CSF distribution that may influence dosing and delivery strategies for CNS-targeted therapies. This study provides a reference for future research using pig models in CNS disease studies and underscores the importance of incorporating brain and spinal CSF and CNS volume data into preclinical models.

Hebbian learning accounts for the effects of experience and novel exposure on representational drift in CA1 of hippocampus
Neuronal activity patterns slowly change over time even when sensory stimuli and animal behavior remain stable, a phenomenon known as representational drift. In area CA1 of the hippocampus, the amount of drift in the tuning of place cells on a familiar linear track is proportional to the time the animal spends exploring that track while the drift in cells' mean rate depends on the absolute time elapsed between sessions. Recently it was shown that exploration of a novel, enriched environment between sessions on the familiar track actually decreases the drift in tuning on that track, i.e. it stabilizes place fields compared to a baseline condition without the novel learning. This finding challenges computational models of drift in which new learning leads to overwriting and hence one would expect more drift, not less. Here we show that such models are indeed compatible with the observed findings as long as spatially-tuned input populations to CA1 which are active on the track versus the enriched environment are largely non-overlapping. Furthermore, in order to reproduce the findings, we must assume that the total amount of learning between the baseline and novel-exposure conditions is the same. Namely, the synaptic resources available for encoding patterns, or episodes, is fixed over a given period of time, but can be preferentially allocated to episodes of particular salience, such as the exploration of novel environments.

Sleep deprivation constrains dynamic configurations of integrated and segregated brain states impacting cognitive performance
The breakdown of cognitive control following sleep deprivation is widely recognised, but the physiological mechanisms and brain signatures that produce this vulnerability have not been resolved. Effective cognition relies on large-scale brain networks flexibly reconfiguring between states of integration and segregation. Here we combined functional magnetic resonance imaging (fMRI), electroencephalography (EEG), and electrocardiography (ECG) collected during cognitive tasks under rested wakefulness, after sleep deprivation, and following a recovery nap to test the hypothesis that sleep deprivation constrains this dynamical repertoire and disrupts its physiological regulation. Using time-resolved functional connectivity and graph theory, we show that sleep deprivation increases the distribution of connections across networks, while reducing the temporal variability of between-network connectivity. Furthermore, dynamic fluctuations between integrated and segregated modes of network topology were dampened, with brain regions spending more time in intermediate configurations and showing greater instability of mode transitions. These alterations were tightly linked to behavioural impairment: participants who exhibited greater contraction toward intermediate topologies also showed poorer task accuracy and slower responses. Under well-rested conditions, thalamic activity peaked prior to transitions into integrated states and was suppressed during transitions into segregated states, consistent with a coordinating role in cortical dynamics. Sleep deprivation weakened and delayed this thalamic coupling. Finally, global and regional fMRI fluctuations were elevated after sleep loss, becoming decoupled from cardiac physiology while more strongly coupled to EEG delta power, further linking reduced arousal to constrained network flexibility. Together, these findings show that sleep deprivation narrows the brain's dynamical repertoire, due to disrupted thalamic regulation and changes to the physiological integration with cortical networks.

Insights from multidimensional analyses of post-stroke fatigue
Post-stroke fatigue (PSF) is an overlooked and debilitating condition. As a multidimensional construct, fatigue encompasses physical, cognitive, and emotional components, complicating efforts to understand PSF pathophysiological mechanisms and identify key predictors. We aimed to investigate the impact of lesion characteristics on the different facets of PSF while accounting for socio-demographic, psychological, and neurological factors. 231 first-ever ischemic stroke patients from a prospective hospital-based cohort were assessed using the Multidimensional Fatigue Inventory (MFI) and the Hospital Anxiety and Depression Scale (HAD) alongside routine clinical evaluations. Lesion analysis was done through two approaches: a voxel-based method using support vector regression-based multivariate lesion-symptom mapping (SVR-LSM), and a network-based method using principal component analysis (PCA) of lesioned gray and white matter regions. The overall prevalence of PSF was 20.8%. PSF was more frequent among women and younger patients and strongly associated with HAD scores. SVR-LSM identified an association between lesions in the right corona radiata and external capsule and total MFI scores but none with HAD scores. The network-based approach showed associations between mental fatigue and reduced activity subdimensions and brain components involving cerebro-cerebellar tracts. Our findings suggest that PSF arises from an interplay of socio-demographic, emotional, and cerebral risk factors, accounting for its heterogeneous presentation. Regarding the associations with the lesioned regions, the involvement of motor pathways raises the possibility that neuronal overactivity, compensating for disrupted networks, may contribute to long-term fatigue. Further whole-brain analyses are warranted to confirm and extend these observations.

Generative inference unifies feedback processing for learning and perception in natural and artificial vision
We understand how neurons respond selectively to patterns in visual input to support object recognition; however, how these circuits support perceptual grouping, illusory percepts, and imagination is not understood. These perceptual experiences are thought to require combining what we have learned about the world with incoming sensory signals, yet the neural mechanism for this integration remains unclear. Here we show that networks tuned for object recognition implicitly learn the distribution of their input, which can be accessed through feedback connections that tune synaptic weights. We introduce Generative Inference, a computational framework in which feedback pathways that adjust connection weights during learning are repurposed during perception to combine learned knowledge with sensory input, fulfilling flexible inference goals such as increasing confidence. Generative Inference enables networks tuned solely for recognition to spontaneously produce perceptual grouping, illusory contours, shape completion, and pattern formation resembling imagination, while preserving their recognition abilities. The framework reproduces neural signatures observed across perceptual experiments: delayed responses in feedback-receiving layers of early visual cortex that disappear when feedback connections are disrupted. We show that, under stated assumptions, gradients of classification error approximate directions that are informative about the data distribution, establishing a theoretical connection between recognition and generation. Together, these findings show that pattern recognition and pattern generation rely on a shared computational substrate through dual use of feedback pathways. This principle explains how neural systems recognize familiar objects reliably while remaining flexible enough to interpret incomplete or ambiguous information, and suggests that reusing learning signals for perception may be a general feature of both biological brains and artificial networks.