bioRxiv Subject Collection: Neuroscience's Journal

Mitochondrial calcium influx-driven bioenergetics in the dopaminergic system selectively enable drug reward
Drugs of abuse hijack the brain's reward system, driving pathological dopamine surges that underlie compulsive behavior and addiction. However, directly targeting dopamine signaling for treatment risks disrupting natural reward processes. Here, we identify a bioenergetic mechanism that selectively promotes addiction-related dopamine release and behaviors. Opioids and methamphetamine, but not natural rewards, induce mitochondrial calcium (Ca2+) influx via the mitochondrial calcium uniporter (MCU) in dopaminergic terminals of the nucleus accumbens. Optogenetic stimulation reveals that this mitochondrial Ca2+ influx occurs exclusively during high-intensity dopaminergic neuronal activation. This Ca2+ influx drives rapid ATP production, compensating for energy deficits caused by neuronal hyperactivity and enabling sustained dopamine release. Genetic deletion or pharmacological inhibition of MCU in dopaminergic neurons selectively reduces drug-induced dopamine release and prevents addictive behaviors while sparing natural reward processing in mice. These findings uncover a distinct mitochondrial bioenergetic mechanism underlying drug reward and propose MCU as a promising therapeutic target for addiction treatment.

fMRI-Based CSF Flow Quantification Identifies Cardiac Pulsatility as the Dominant Driver Over Respiratory and Slow Vasomotion Cycles
Studying cerebrospinal fluid (CSF) flow can reveal physiological and neural drivers of potential importance in brain clearance. CSF flow may be acquired in functional magnetic resonance imaging (fMRI) scans by considering the inflow effect in an edge-slice. Such measurements have large potential considering the broad availability of fMRI, and the already extensive databases focusing on e.g. aging and dementia. However, limiting factors are that the measurements are not quantitative and can rarely separate contributions from different driving mechanisms due to insufficient sampling rate. Here, we present a method that translates fMRI CSF signals into quantitative flow rates associated with cardiac, respiratory and slow-vasomotion cycles, by modeling the spin-history of an oscillating ensemble of molecules. Phantom experiments showed excellent correlations between estimated and true velocities for cardiac- and respiratory-like frequencies, and moderate correlations for a slow vasomotion-like frequency (r = 0.94, 0.97, 0.58 respectively). We also applied the method in a cohort of 48 subjects from the population (68-82 years, 19 women) to characterize CSF flow at the foramen magnum at resting state. These measurements showed a CSF stroke volume of 0.86 [0.61, 1.17] mL for the cardiac, 0.44 [0.25, 0.94] mL for the respiratory, and 0.28 [0.14, 0.45] mL for the slow vasomotion cycle. In conclusion, the method presented here enabled quantitative assessments of CSF flow compatible with typical fMRI acquisitions and showed that the cardiac cycle is a dominant driver of CSF flow.

Disruption of GABA-Regulated Network Resilience in Human Cerebral Organoids Leads to Fragmented Small-World States and Reduced Connectivity
Neuronal network resilience, the ability of brain circuits to maintain and recover functional connectivity following perturbation, is fundamental to cognitive stability and adaptability. Using human cerebral organoids and multi-electrode arrays (MEAs), we investigated how mechanical stress disrupts network stability and identified key mechanisms regulating recovery. Blast overpressure exposure destabilized small-world network (SWN) organization, increasing network fragmentation and reducing overall integration. Merged SWNs, which exhibit high connectivity, were particularly vulnerable, while fragmented and single SWNs persisted for extended periods, indicating a shift toward less resilient network states. Optogenetic stimulation promoted network recovery, reducing the persistence of fragile states and facilitating transitions toward more cohesive network structures. GABAergic signaling emerged as a critical regulator of network resilience, with pharmacological inhibition exacerbating fragmentation and impairing network reorganization. These findings reveal fundamental principles of how inhibitory networks regulate circuit stability, with implications extending beyond mechanical injury to broader conditions characterized by network dysfunction, including anxiety, depression, PTSD, and neurodegenerative disorders. Understanding the mechanisms governing network adaptation and resilience could inform new therapeutic strategies aimed at stabilizing disrupted neural circuits across a range of neurological conditions.

A CRISPR-CAS9 high throughput machine-learning platform for modulation of genes involved in Parkinson's disease-associated PINK1-mitophagy in iPSC-derived dopaminergic neurons
Parkinson's disease (PD) is a progressive neurodegenerative disorder characterised by the loss of dopaminergic neurons, driven by complex molecular mechanisms that are not fully understood. To address this issue, we have developed a novel high-content phenotypic screening platform using human induced pluripotent stem cell-derived dopaminergic neurons to investigate the PINK1-PARKIN mitophagy pathway, a critical process in PD pathogenesis. Utilising high throughput, 384 well arrayed CRISPR-CAS9 genetic manipulation and high-content immunofluorescence imaging complemented with machine learning analysis, we examined ubiquitin (Ub) pSer65 levels. Ub pSer65, a potential PD clinical biomarker, is a key marker of mitophagy initiation in dopaminergic neurons upon mitophagy initiation using exogenous stimuli to mimic the disease relevant environment. The CRISPR-CAS9 knockout (KO) screen revealed two distinct phenotypic classes: essential genes causing cell death upon deletion, and genes modulating Ub pSer65 levels. Notably, KO of PINK1, PARKIN, and TOM7 genes decreased Ub pSer65 upregulation during mitophagy activation, confirming their established roles in the pathway and validating the suitability of the platform for target identification. This innovative platform provides a precise tool to further interrogate PD-associated genes, offering insights into mitophagy-related pathogenic mechanisms and identification of potential therapeutic targets. By bridging functional genomics with disease-specific neuronal models, this approach presents a promising strategy for advancing PD research and developing targeted interventions. To our knowledge, this is the first reported use of a human, translationally relevant cell model to study genetic perturbation within a disease relevant phenotype.

Biomarkers in cerebrospinal fluid sediments
Cerebrospinal fluid (CSF) biomarkers for neurodegenerative diseases have been extensively studied over the years. However, CSF samples are routinely centrifuged, and the resulting sediment or pellet is typically discarded to remove cellular debris and high-density particles. This standard practice raises a critical question: could these discarded sediments harbour potential biomarkers relevant to the diagnosis and prognosis of certain brain diseases? In this study, we analysed CSF pellets from various cases and identified, entrapped among undetermined remnants, brain-derived structures such as wasteosomes and psammoma bodies. Furthermore, we observed that disease-relevant proteins can become deposited in the sediment, as is the case for both tau and A{beta}42 in Alzheimer's disease or tau in progressive supranuclear palsy disease. These findings suggest that some potential biomarkers might accumulate or be hidden in the sediment and, taken as a whole, the results underscore the need to broaden the scope of biomarker research

Decoupling simultaneous motor imagination and execution via orthogonal ECoG neural representations
The brain coordinates multiple parallel motor programs, ensuring synergy and preventing interference during movements. Yet, performance often degrades when brain-machine interfaces are used during concurrent tasks or ongoing movements. We suggest that latent neural representations may represent a strategy to solve this issue. In this study, we addressed this question using neural signals from a tetraplegic individual with partial residual motor function, implanted with a wireless epidural electrocorticography (ECoG) device. By adapting dimensionality reduction techniques, we found that motor execution and motor imagery span partially overlapping subspaces in mesoscale neural signals, shaped by specific frequency band contributions. Despite substantial shared variance, we show that identifying orthogonal, condition-specific dimensions enables successful decoding of executed and imagined movements, even when performed simultaneously. These findings show that ECoG signals can expose separable neural subspaces, allowing executed and imagined actions to be harnessed independently and in concert. This opens a promising avenue to develop brain-machine interfaces that can simultaneously control multiple external devices or operate alongside natural movements.

Fos labels a distinct excitatory neuron ensemble for memory retrieval
Experience-triggered expression of Fos has been extensively used as a marker representing memory engram. It is generally assumed that Fos-positive neurons are preferentially excited by the experience, yet this has not been directly examined. In this study, we tracked neuron activity and Fos expression in somatosensory cortex and dentate gyrus of hippocampus in mice, during electric shock-induced fear memory formation and retrieval. Contrary to the prevailing view, we found that calcium features fail to predict Fos for individual cells. Fos-positive neurons show no specific activation to stimuli during memory encoding, but their activities become stimuli-selective during retrieval. Surprisingly, inhibiting neurons that will express Fos during encoding does not affect the induction of memory-guided behavior upon their activation. Network simulation and voltage imaging further showed that connectivity to interneurons, not stimulus responsiveness, is a major factor determining Fos expression. Our results indicate that Fos labels excitatory neurons specific for memory retrieval.

A quantitative comparison of two methods for higher-order EEG microstate syntax analysis
Entropy rate (ER) and sample entropy (SE) are two metrics that have been used to quantify the syntactic complexity of electroencephalography (EEG) microstate sequences. We here present a theoretical and numerical comparison of these two metrics and apply them to a resting-state EEG dataset from individuals with Alzheimer disease (AD) and a control group. We first derive theoretical entropy rate and sample entropy estimates for first-order discrete Markov processes, providing a null hypothesis for statistical testing of higher-order syntax properties. Under the first-order syntax null hypothesis, we find a close mathematical relationship between both metrics that can be expressed by the microstate transition probability matrix. An inequality is derived that shows entropy rate to be an upper bound to sample entropy under the Markov approximation. We quantify accuracy and precision of the theoretical ER and SE estimates on EEG microstate sequences from the healthy control group. We then show that ER and SE identify significant higher-order syntax properties in microstate sequences from the control and AD groups. Group comparison demonstrates that continuous microstate sequences from the AD group have lower entropy values (ER, SE), whereas jump sequences from the AD group have higher entropy values compared to control. Finally, we introduce a new syntax metric that normalizes ER and SE values with respect to their first-order syntax levels, to assess differences that only depend on syntax order. This metric revealed no differences between control and AD groups for either continuous or jump microstate sequences. This study provides further insights into higher-order microstate syntax and how it can be quantified with respect to the underlying first-order syntax. Similarities and differences between ER and SE as syntax metrics are highlighted and exemplified on experimental data. Our results show that (i) EEG microstate sequences from control and AD subjects show higher-order syntax properties across the tested syntax levels, (ii) continuous and jump sequences from control and AD groups are syntactically different, and (iii) differences between the control and AD groups disappear when higher-order syntax properties are normalized to the group-specific Markov level.

Continuous flashing suppression of V1 responses and the perceptual consequences revealed via two-photon calcium imaging and transformer modeling
Continuous flash suppression (CFS), where a dynamic masker presented to one eye suppresses the conscious perception of a stimulus shown to the other eye, has been extensively used to study visual consciousness. Various studies reported high-level visual and cognitive functions under CFS, which, however, has more recently been questioned and at least partially attributed to low-level stimulus. A key but unsettled issue is the extent to which the responses of V1 neurons, where inputs from two eyes first merge, are affected, as severely suppressed V1 responses would not sustain high-level processing. Here, we used two-photon calcium imaging to record the responses of V1 neurons to a grating stimulus under CFS in awake, fixating macaques. The results revealed that CFS substantially suppressed V1 orientation responses. Ocularity-wise, it nearly completely eliminated the orientation responses of V1 neurons preferring the masker eye or both eyes, while also significantly suppressing the responses of those preferring the grating eye. Modeling analyses suggest that, under CFS, the brain retains the ability of classifying coarse orientations, but may become less capable of reconstructing the grating stimulus. Consequently, while CFS-suppressed orientation information still supports low-level orientation discrimination, it may not suffice for high-level visual and cognitive processing.

Cocaine withdrawal enhances subthalamic reward sensitivity
High-frequency stimulation of the subthalamic nucleus (STN) has shown therapeutic potential in preclinical models of addiction. However, its rewarding properties remain unclear. Here, we show that cocaine withdrawal enhances STN intracranial self-stimulation, revealing a reward-based mechanism that may contribute to the beneficial effects of STN deep brain stimulation in addiction and related neuropsychiatric disorders.

Sexually-dimorphic neurons in the Drosophila whole-brain connectome
Sexual dimorphisms are present across brains. Male and female brains contain sets of cell types with differences in cell number, morphology, or synaptic connectivity between the two sexes. These differences are driven by differentially-expressed transcription factors, which set the stage for disparate sexual and social behaviors observed between males and females, such as courtship, aggression, receptivity, and mating. In the Drosophila brain, sexual dimorphisms result from differential expression of two transcription factors, Fruitless (Fru) and Doublesex (Dsx), and genetic reagents driven by enhancers for Fru and Dsx label sexually-dimorphic neurons in both male and female brains. The recent release of the first whole-brain connectome for Drosophila provides a unique opportunity to study the connectivity between these neurons as well as their integration into the larger brain network. Here, we identify 91 putative Fru or Dsx cell types, comprising ~1400 neurons, within the whole-brain connectome, using morphological similarity between electron microscopic (EM) reconstructions and light microscopic (LM) images of known Fru and Dsx neurons. We discover that while Fru and Dsx neurons are highly interconnected, each cell type typically receives more inputs from and sends more outputs to non-Fru/Dsx neurons. We characterize the connectivity in the Fru/Dsx networks to predict the function of cell types not previously characterized, we measure distances to the sensory periphery and uncover multisensory interactions, and we map connections to descending neurons that drive behavior. All Fru and Dsx labels reported here are shared within FlyWire Codex (codex.flywire.ai; gene==Fruitless or Doublesex); this work is a critical first step towards deciphering the neural basis of sexually-dimorphic behaviors and for making comparisons with future connectomes of the male brain.

The geometry of cortical sound processing in slow wave sleep
During wake, sound-evoked and spontaneous neural activity of the auditory cortex evolve in distinct subspaces whereas anesthesia disrupts sound responses and merges these spaces. To evaluate if similar modifications of the sound representation geometry explain sensory disconnection during sleep, we followed large neural populations of the mouse auditory cortex across slow wave sleep and wakefulness. We observed that sleep dampens sound responses but preserves the geometry of sound representations which remain separate from spontaneous activity. Moreover, response dampening was strongly coordinated across neurons and varied throughout sleep spanning from fully preserved response patterns to population response failures on a fraction of sound presentations. These failures are more common during high spindle-band activity and more rarely observed in wakefulness. Therefore, in sleep, the auditory system preserves sound feature selectivity up to the cortex for detailed acoustic surveillance, but concurrently implements an intermittent gating mechanism leading to local sensory disconnections.

An open dataset of cerebral tau deposition in young healthy adults based on MK6240 positron emission tomography
Tauopathies are pathologies wherein phosphorylated insoluble tau aggregates in neurons, leading to neuronal dysfunction and degeneration. Positron emission tomography (PET) can measure tau deposition in vivo, with second-generation radiotracers such as [18F]MK6240 showing high affinity for tau with minimal off-target binding. While typically observed in conditions associated with advanced age, notably Alzheimer's disease (AD), tauopathies are also implicated in pathologies affecting younger individuals. This includes autosomal dominant AD, Niemann-Pick disease type C, chronic traumatic encephalopathy, and epilepsy, thus highlighting the need for generating normative data in non-geriatric populations. Here, we present a dataset of 33 young to middle-age healthy adults (mean age 32.8{+/-}10.2 years, 12 female) with [18F]MK6240 PET data and T1w magnetic resonance imaging. Longitudinal data are also available in a subset of 9 participants with a minimum follow-up time of 1 year. Our dataset aims to support imaging biomarker studies on younger individuals who may be at risk for AD and to advance work in tauopathies affecting non-geriatric populations, who are generally excluded from studies focused on neurodegeneration.

An Adaptive Visuomotor Transformation Reservoir Embedded in the Vertebrate Brain
Adaptive sensorimotor transformation is essential for animal survival in dynamic environments. The optic tectum (OT), homologous to the mammalian superior colliculus, serves as a central hub for visuomotor processing. To elucidate how OT circuits discriminate visual inputs and generate relevant behavior outputs, we leveraged the mesoscopic connectome of zebrafish OT to build a biophysically constrained reservoir computing network that models visuomotor transformations. In silico lesion revealed that the accuracy and robustness of sensorimotor outputs are governed by different combinations of tectal interneuron (TIN) subtypes. Furthermore, specific lamina-projecting serotoninergic subsystems distinctly bias network output toward either escape or orienting behaviors via regulating TIN activities. Our findings establish a mesoscopic connectome-based reservoir for vertebrate sensorimotor processing, where TINs control accuracy and robustness, highlighting TINs as a tunable gate and serotoninergic neurons as a context-dependent modulator of behavioral flexibility.

CCorGsDB: A Database for Clock Correlated Genes in the Mouse and Human Central Nervous Systems
We introduce CCorGsDB, a web-based tool that integrates co-expression networks filtered by circadian biomarkers to identify candidate clock-regulated genes in spatially defined regions of the mouse and human central nervous systems. Built using Weighted Gene Co-expression Network Analysis (WGCNA), CCorGsDB includes ~16,000 genes for mouse and ~37,000 for human, highlighting genes highly correlated with canonical clock markers. The tool incorporates disease associations and drug target information for compounds with short half-lives acting on the CNS, supporting chronopharmacological research. Users can explore region-specific data through an interactive interface offering query, visualization, and download options. CCorGsDB is freely accessible at https://famed.ufal.br/ccorgs.

Resolving a paradox about how vision is transformed into familiarity
While humans and other primates are generally quite good at remembering the images they have seen, they systematically remember some images better than others. Here, we leverage the behavioral signature of "image memorability" to resolve a puzzle around how the brain transforms seeing into familiarity. Namely, the neural signal driving familiarity reports is thought to be repetition suppression, a reduction in the vigor of the population response in brain regions including inferotemporal cortex (ITC). However, within ITC, more memorable images evoke higher firing rate responses than less memorable ones, even when they are repeated. These two observations appear to conflict: if reduced firing leads to stronger memory signaling, then why are the images that induce greater firing more memorable? To resolve this paradox, we compared neural activity in ITC and the hippocampus (HC) as two rhesus monkeys performed a single-exposure image familiarity task. We found evidence that the paradox is resolved in HC where neural representations reflected an isolated memory signal that was larger for more memorable images, but HC responses were otherwise uncorrupted by memorability. Memorability behavior could not be accounted for by trivial computations applied to ITC (like thresholding). However, it could be decoded from ITC with a linear decoder that corrects for memorability modulation, consistent with the hypothesis that ITC reflects familiarity signals that are selectively extracted through medial temporal lobe (MTL) computation. These results suggest a novel role for the MTL in familiarity behavior and shed new light on how the brain supports familiarity more generally.

Directional growth of developing myelin mediated by Wnt gradient and required for proper axon functions
Axon-wrapping myelin sheaths formed by oligodendrocytes are essential for proper functions of the central nervous system. Although much is known about oligodendrocyte development, how the myelin dynamically forms remains unclear. Here we show the preferentially unidirectional extension of developing myelin mediated by Wnt gradient and required for proper axon functions. Using larval zebrafish as an in vivo model, we found that developing myelin in the spinal cord preferentially extends to the anterior end, and this process is dependent on an anterior-to-posterior Wnt4b gradient. Taking advantage of the large size of Mauthner-cell axons, we further showed that disruption of this directional extension impairs the even length distribution of myelin sheaths and faithful transduction of action potentials on the axon, and reduces the reliability of escape behavior. Thus, our study reveals a novel process for precise regulation of myelination, providing a new insight into myelin structuring and functioning.

Spectral Matched Filtering in the Butterfly Visuomotor System
Color provides an important dimension for object detection and classification. In most animals, color- and motion-vision are largely separated throughout early stages of visual processing. However, accumulating evidence indicates crosstalk between chromatic and achromatic pathways. Here we investigate the spectral sensitivity of the butterfly motion-vision pathway at the level of pre-motor descending neurons (DNs), which connect the brain to thoracic motor centres. Butterflies engage in fast agile flight within often-colorful visual ecologies, which may heighten evolutionary pressure to integrate color- and motion-vision. Indeed, we observed a separation of spectral sensitivities that matches the functional properties of butterfly DNs, such that wide-field optic flow-sensitive DNs involved in stabilisation reflexes have effectively broadband spectral responses, whilst target-selective DNs involved in target-tracking are comparatively narrowband and match conspecific wing coloration. Our findings demonstrate an integration of color- and motion-vision within a pre-motor neuronal bottleneck that controls behavior.

Erratic Maternal Care Induces Avoidant-Like Attachment Deficits in a Mouse Model of Early Life Adversity
Attachment theory offers an important clinical framework for understanding and treating negative effects of early life adversity. Attachment styles emerge during critical periods of development in response to caregivers ability to consistently meet their offspring needs. Attachment styles are classified as secure or insecure (anxious, avoidant, or disorganized), with rates of insecure attachment rising in high-risk populations and correlating with a plethora of negative health outcomes throughout life. Despite its importance, little is known about the neural basis of attachment. Work in rats has demonstrated that limited bedding and nesting (LB) impairs maternal care and produces abnormal maternal attachment linked to increased pup corticosterone. However, the effects of LB on attachment-like behavior have not been investigated in mice where additional genetic and molecular tools are available. Furthermore, no group has utilized home-cage monitoring to link abnormal maternal care with deficits in attachment-like behavior. Using home-cage monitoring, we confirmed a robust increase in maternal fragmentation among LB dams. Abnormal maternal care was correlated with elevated corticosterone levels on post-natal day seven (P7) and a stunted growth trajectory that persisted later in life. LB did not alter maternal buffering at P8 or maternal preference at P18, indicating that certain attachment-like behaviors remain unaffected despite exposure to high levels of erratic maternal care. However, LB pups vocalized less in response to maternal separation at P8, did not readily approach their dam at P13, and exhibited higher anxiety-like behavior at P18, suggesting that LB induces avoidant-like attachment deficits in mice.

How Minds Take Shape: Graph-ESN Reveals How Neural Ensembles Engineer Stable Representations
Deciphering how neural populations encode, integrate, and dynamically transform information to generate predictive neural dynamics remains a fundamental pursuit in systems neuroscience. Although information is processed and represented across distributed neural ensembles, a critical question remains: How do these populations accumulate information and interact over time to form stable, coherent representations? The cortex comprises ensembles of interacting populations that cooperate to enable thought. However, an open challenge is to map how each population evolves its internal context in response to incoming information and crucially, how this evolving context shapes what each population communicates to other populations. To address this, we employ a customized variant of the Graph Echo State Network (Graph ESN) architecture that involves specialized populations. This formulation enables the model to disentangle and represent multiscale oscillatory patterns in neural data, offering a more biologically plausible and task-relevant alternative to traditional ESNs. By leveraging the rich hidden-state dynamics of this architecture, we illustrate how neural ensembles iteratively interact and converge toward stable, temporally evolving representations of information. We further investigate the distinct contributions of individual populations in this collaborative process of representational stabilization. Mapping this temporally unfolding, cooperative structure sheds light on the neural mechanisms underlying distributed representation and inter-population coordination, processes that may ultimately support organized cognition.

Food seeking suppression by environmental enrichment accompanies cell type- and circuit-specific prelimbic cortical modulation
Cues such as fast-food advertisements associated with food can provoke food cravings which may lead to unhealthy overeating. To effectively control such cravings, we need to better understand the factors that reduce food cue reactivity and reveal corresponding anti-craving brain mechanisms. We previously reported that access to environmental enrichment (EE) that provides cognitive and physical stimulation in mice reduced cue-evoked sucrose seeking and prelimbic cortex (PL) neuronal reactivity. To date, the phenotype of PL neurons that undergo EE-induced adaptations has not been fully elucidated. Therefore, we used brain slice electrophysiology to investigate how EE modulated intrinsic excitability in the general population of PL interneurons and pyramidal cells. Additionally, we used retrograde tracing and the neuronal activity marker Fos to investigate how EE modulated cue-evoked recruitment of pyramidal cells projecting to the paraventricular nucleus of the thalamus (PVT) and nucleus accumbens core (NAc). Before the cue-evoked sucrose seeking test, EE enhanced the general, baseline excitability of inhibitory interneurons, but not pyramidal cells, thereby promoting inhibitory overdrive. During cue-evoked sucrose seeking, EE suppressed recruitment of PVT-, but not NAc-projecting, neurons thereby selectively promoting corticothalamic, but not corticoaccumbens, excitatory underdrive. Collectively, we further illuminate EE's anti-food seeking actions whereby EE promotes both cell type-specific (inhibitory interneuron overdrive) and circuit-specific (excitatory corticothalamic underdrive) neuroadaptations in the PL.

rAAV-miniBEND: A targeted vector for brain endothelial cell gene delivery and cerebrovascular malformation modeling
Defects in brain endothelial cells (brainECs) can cause severe cerebrovascular malformations, including arteriovenous malformation (AVM) and cerebral cavernous malformation (CCM). The lack of appropriate tools for cerebrovascular disease modeling and local genetic manipulation of the brain vasculature hinders research on cerebrovascular malformations. Here we develop a recombinant adeno-associated virus (rAAV) tool miniBEND (rAAV-based mini-system for brain endothelial cells, rAAV-miniBEND), which combines a minimal promoter and an optimized cis-acting element (cis-element) isolated from the mouse gene Tek. This system achieves gene expression specifically in mouse and rat brainECs. Using rAAV-miniBEND, we achieve high-efficiency and high-specificity gene expression in brainECs through intracranial injection at various developmental stages and through intravenous administration at all postnatal stages in mice. Furthermore, we use rAAV-miniBEND to model sporadic CCMs mediated by MAP3K3I441M and AVMs mediated by BrafV600E. We demonstrate that somatic expression of BrafV600E in brainECs induces an AVM phenotype, and that brainEC proliferation are important for AVM development. Thus, our rAAV-miniBEND system provides a valuable and widely applicable tool for cerebrovascular disease modeling and local or global brainEC gene delivery.

Napping alters Functional Brain Responses in the Aged
Circadian rhythms shape the temporal organization of sleep and wakefulness and evolve throughout the adult lifespan, leading to higher sleep-wake cycle fragmentation with ageing. The increasing prevalence of daytime napping represents a visible manifestation of such fragmentation and has been suggested to forecast age-related cognitive decline. Here, we assessed the impact of napping on functional brain correlates of performance on a Sternberg working memory (WM) task using functional magnetic resonance imaging in 60 healthy older individuals, prospectively recruited with respect to their napping habits (39 females, age: 59-82y). As compared to non-nappers, nappers showed reduced hemispheric asymmetry in the dorsolateral prefrontal cortex (DLPFC, p< 0.001) and decreased performance at high WM load levels. Only in non-nappers was increased ipsilateral activation in the DLPFC associated with better performance at high WM load levels (p < 0.05), while contralateral activation across all WM load levels was not associated with performance. These results suggest altered functional brain compensation and dedifferentiation processes, and that napping could consist of a marker of inter-individual variability in cognitive and brain aging.

Motor protein disruption critically alters organelle trafficking, NMJ formation, and excitation contraction coupling.
Trafficking of intracellular cargoes along the neuronal axon microtubule tracks is a motor-protein-dependent process. It is well-established that the motor protein kinesin is responsible for anterograde trafficking of axonal cargo, while the dynein/dynactin complex regulates retrograde trafficking. However, there is still much to uncover regarding the various isoforms of these motor proteins as well as the adapter and cargo-associated proteins involved in the precise trafficking dynamics. Here we use a targeted genetic approach to knockdown candidate kinesin genes involved in trafficking organelles like synaptic vesicles, mitochondria, and dense core vesicles in motor neurons. Using fluorescently tagged cargo proteins; live-imaging experiments were conducted to quantify intracellular trafficking changes, and 2 genes, kinesins 1 and 3, were identified as critical regulators. Disruptions in either gene product, reduce rates of axonal trafficking in motor neurons, and lead to the formation of large intracellular aggregates in somas and axons. Downstream, disruptions in both kinesin 1 and 3 expression led to significant changes in neuropeptide (NP) abundance at boutons, and changes in synaptic morphology, including innervation length, bouton number, and active zone composition. Spinning disc confocal imaging revealed fewer NP trafficking through, or getting captured in kinesin knockdown experiments, and a dramatic reduction in NP release at motor neuron terminals. We go on to show profound reductions in neuromuscular transduction, and excitation-contraction coupling in kinesin 1 knockdowns, but not for kinesin 3. Changes in larval crawling as well as development were observed for kinesin 1 knockdowns. Taken together we have not only identified which kinesins are critically involved in organelle trafficking, but also revealed critical disruptions in cellular morphology, function, physiology, and behavior in genetically disrupted animals.