bioRxiv Subject Collection: Neuroscience's Journal

Astroglial Dysfunction, Demyelination and Nodular inflammation in Necrotizing Meningoencephalitis
Necrotizing Meningoencephalitis (NME), a form of Meningoencephalitis of Unknown Origin (MUO), is a progressive neuroinflammatory disease that primarily affects young, small-breed dogs. Due to limited understanding of its pathophysiology, early detection and the development of targeted therapies remain challenging. Definitive ante-mortem diagnosis is often unfeasible, and dogs with NME are frequently grouped under the broader MUO category. Our long-term objective is to identify distinct disease mechanisms within each MUO subtype to improve diagnostic accuracy, therapeutic approaches, and prognostic outcomes. To establish unique inflammatory patterns as they relate to neuropathologic changes in NME, we studied we studied the degree of immune cell infiltration, astrogliosis, demyelination, and microglial activation, comparing these factors with granulomatous meningoencephalomyelitis (GME), a closely related MUO subtype. We found that in the leptomeninges, NME is characterized by mild immune cell infiltration, in contrast to the prominent, B cell-rich aggregates seen in GME. In the neuroparenchyma, both diseases exhibit a comparable degree of lymphocyte infiltration; however, demyelination is more pronounced in NME, particularly within the subcortical white matter. Notably, areas of the brain affected by NME display a reduction in astrogliosis, which is associated with a marked decrease in the expression of the water channel protein aquaporin-4 (AQP4), a reduction not observed in GME. Additionally, we found that AQP4 expression levels correlate with the extent of microglial and macrophage activation. These findings suggest that astrocyte dysfunction in regions of microglial inflammation is a driver of NME and with adaptive immune responses likely playing a supportive role.

Mu and beta power effects of fast response trait double dissociate during precue and movement execution in the sensorimotor cortex
A better understanding of the neural and muscular mechanisms underlying motor responses is essential for advancing neurorehabilitation protocols, brain-computer interfaces (BCI), feature engineering for biosignal classification algorithms, and identifying biomarkers of disease and performance enhancement strategies. In this study, we examined the neuromuscular dynamics of healthy individuals during a sequential finger-pinching task, focusing on the relationships between cortical oscillations and muscle activity in simultaneous electroencephalography (EEG) and electromyography (EMG) recordings. We contrasted two pairs of subsets of the dataset based on the latency of EMG onset: an across-subjects trait-based comparison and a within-subjects state-based comparison. Trait-based analyses showed that fast responders had higher baseline beta power, indicating stronger motor inhibition and efficient resetting of motor networks, and greater mu desynchronization during movement, reflecting enhanced motor cortex activation. Visual association areas also displayed more pronounced changes in different phases of the task in subjects with lower latency. Fast responders exhibited lower baseline EMG activity and stronger EMG power during movement initiation, showing effective motor inhibition and rapid muscle activation. State-based analyses revealed no significant EEG differences between fast and slow trials, while EMG differences were only detected after movement onset. These results highlight that fast response trait is related to electrophysiological differences at specific frequency bands and task phases, offering insights for enhancing motor function in rehabilitation, biomarker identification and BCI applications.

Communication subspaces align with training in ANNs
Communication subspaces have recently been identified as a promising mechanism for selectively routing information between brain areas. In this study, we explored whether communication subspaces develop with training in artificial neural networks (ANNs) and explored differences across connection types. Specifically, we analyzed the subspace angles between activations and weights in ResNet-50 before and after training. We found that activations were more aligned to the weight layers after training, although this effect decreased in deeper layers. We also analyzed the angles between pairs of weight layers. We found that for all branching, direct, and skip connections, weight layer pairs were more geometrically aligned in trained versus untrained models throughout the entire network. These findings indicate that such alignment is essential for the proper functioning of deep networks and highlights the potential to enhance training efficiency through pre-alignment. In biological data, our results motivate further exploration into whether learning induces similar subspace alignment.

Peripheral CGRP engages brain-wide electrical network activity of migraine
Migraine is a disorder consisting of severe, recurrent headaches and debilitating sensory symptoms which often include affective symptoms or comorbidities such as depression, anxiety, and irritability. As such, migraine is a complex nervous system disorder that involves integration of many modalities across the brain. This makes migraine a complex systems neuroscience problem represented by the confluence of sensory, pain, cognitive, autonomic, and affect-related circuits. Thus, it is essential to understand how neuronal activity across various brain regions implicated in migraine is coordinated during migraine pathophysiology. Using a calcitonin gene-related peptide (CGRP) mouse model of migraine, we probed neural oscillatory activity in the anterior cingulate cortex, amygdala (BLA and CeA), thalamus (Po, VPM, and MDthal), and parabrachial nucleus following peripheral administration of CGRP. We identified three frequency bands in which directional signals occur in this network and found that power in these frequencies across the network was lower than vehicle within 10 minutes of peripheral CGRP exposure, which was sustained for (~40-50 min). Coherence, on the other hand, was mostly disrupted in CeA brain region pairings, and took on a shorter timecourse. Sumatriptan partially blunted or reversed these CGRP-induced network responses, especially with regard to amygdala power and coherence pairings. Early life stress, which has been shown to increase the likelihood of migraine in adulthood in humans, exacerbated CGRP-induced migraine-related behavioral phenotypes and induced corresponding network changes in LFP power in the CeA and Po and coherence in Po-related pairings. Clustering based on a changepoint analysis of coherence identified individual mice hypersusceptible to migraine. Overall, our findings demonstrate coordinated brain-wide network activity by which migraine is mediated in the brain in response to peripheral CGRP.

Social Anxiety Alters Theory of Mind Activation and Intersubject Neural Variability During Movie Viewing
Social anxiety is characterized by an intense fear of judgment in social situations, yet the underlying mechanisms driving this condition remain poorly understood. One hypothesis holds that specific alterations in Theory of Mind (ToM) affect the ability to interpret others' thoughts and emotions. Another hypothesis proposes that broader interpretive biases lead individuals to perceive social cues as overly significant, even in neutral settings. We investigated these possibilities by measuring brain activity, pupil responses, and heart rates in socially anxious individuals and matched controls as they viewed 'Partly Cloudy', an animated film known to engage the ToM network during specific scenes. While overall brain activity during ToM-related scenes was similar across groups, socially anxious participants exhibited reduced activation in the left posterior superior temporal sulcus (pSTS), a key area for ToM processing. Additionally, intersubject correlation analysis revealed a distinct neural response pattern in the socially anxious group, marked by uniform responses in sensory regions and heightened variability in higher-order cortical areas. This pattern persisted throughout the film and occurred without changes in heart rate or pupil responses, indicating a neural processing bias that manifests even in non-evaluative settings. These findings provide a neural basis for ToM alterations and broader interpretive biases in social anxiety, supporting cognitive-behavioral models and suggesting novel targets for intervention.

Resting After Learning Facilitates Memory Consolidation and Reverses Spatial Reorientation Impairments in 'New Surroundings' in 3xTg-AD Mice
Sleep is an essential component of productive memory consolidation and waste clearance, including pathology associated with Alzheimer's disease (AD). Facilitation of sleep decreases A{beta} and tau accumulation and is important for the consolidation of spatial memories. We previously found that 6-month female 3xTg-AD mice were impaired at spatial reorientation. Given the association between sleep and AD, we assessed the impact of added rest on impaired spatial reorientation that we previously observed. We randomly assigned 3xTg-AD mice to a rest (n=7; 50 min pre- & post-task induced rest) or a non-rest group (n=7; mice remained in the home cage pre- & post- task). Mice in both groups were compared to non-Tg, age-matched, non-rest controls (n=6). To confirm that our sleep condition induced sleep, we performed the same experiment with rest sessions for both 3xTg-AD and non-Tg mice (n=6/group) implanted with recording electrodes to capture local field potentials (LFPs), which were used to classify sleep states. Markers of pathology were also assessed in the parietal-hippocampal network, where we previously showed pTau positive cell density predicted spatial reorientation ability (pTau, 6E10, M78, and M22). However, we found that 3xTg-AD rest mice were not impaired at spatial reorientation compared to non-Tg mice and performed better than 3xTg-AD non-rest mice (replicating our previous work). This recovered behavior persisted despite no change in the density of pathology positive cells. Thus, improving sleep in early stages of AD pathology offers a promising approach for facilitating memory consolidation and improving cognition.

Downregulation of astrocytic C3 production alleviates neuronal mitochondrial dysfunction in tauopathy models
Astrocytic complement system over-activation is linked to the progression of neuronal dysfunction and degeneration in neurodegenerative disorders such as Alzheimer's Disease (AD) and tauopathies. Blocking Complement C3 (C3) expression rescues neuronal dysfunction and loss in tauopathy models, however, mechanism of C3 mediating neurodegeneration remains unclear. In this study, we found that activated astrocytes can trigger tau-mediated neuronal mitochondrial swelling and dysfunction through C3 over-production. Increased neuronal mitochondrial dysfunction resulted in the activation of the necroptosis pathway. Our data revealed that downregulation of astrocytic C3 production by anserine, a natural imidazole dipeptide that can target astrocytes had the ability to prevent neuronal mitochondrial dysfunction and necroptosis activation, both in the in vitro and in vivo tauopathy models. Suppression of astrocyte activation and C3 production also rescued the cognitive function and prolonged the survival rate. Our findings reveal the neurotoxic role of astrocytic C3 in mediating neuronal mitochondrial dysfunction and sequent death through promoting tau pathology and suggest the therapies that can downregulate A1 astrocyte activation and C3 secretion such as anserine have a potential role in alleviating this neurotoxic effect.

The impact of FreeSurfer versions on structural neuroimaging analyses of Parkinson's disease
Image processing software impacts the quantification of brain measures, playing an important role in the search for clinical biomarkers. We investigated the impact of the variability between FreeSurfer releases on the estimation of structural brain measures in Parkinson's disease (PD). Structural brain scans from 106 controls and 209 patients were analyzed with FreeSurfer versions 5.3, 6.0.1, and 7.3.2, including longitudinal data from 125 patients. First, we measured the differences in the estimation of volume, surface area, and cortical thickness between FreeSurfer versions. Second, we focused on the relationship between MRI-derived brain measures and group differences as well as disease severity clinical outcomes, which were evaluated both cross-sectionally and longitudinally. We found high software-induced variability in the estimation of all three structural measures, which impacted clinical outcomes. There were differences between software versions in group differences between patients and healthy controls in subcortical volume and vertex-wise cortical thickness. Software variability also impacted the estimated relationship between brain structure and disease severity in patients. Hence, software variability not only relates to the estimation of structural measures, but it also impacts clinically-relevant MRI measures. Our study provides insight into the reproducibility of structural neuroimaging studies in PD populations.

An integrative layer-resolved atlas of the adult human meninges
The human meninges are a dynamic tri-layered brain border that plays a key role in brain development, CSF homeostasis, immune regulation, and higher-level brain function. The meninges have also been implicated in central nervous system (CNS) pathologies such as infection, autoimmunity, and brain trauma. To understand how the meningeal microenvironment is altered under pathological conditions it is necessary to have a complete understanding of its normotypic cellular architecture and function. To date, there is no complete atlas of the normotypic adult human meninges. By surgically extracting each human meningeal layer during surgery, we generated the first layer-resolved map of all meningeal cell types via an integration of whole cell single cell RNA sequencing, multiplexed error-robust fluorescence in situ hybridization (MERFISH), and protein immunolabelling. Since fibroblasts play key roles in meningeal homeostasis yet remain less well-characterised than other meningeal cell types, we deeply phenotyped these cells in all layers. We identified 10 fibroblast subpopulations with unique predicted functions that localise to distinct neuroanatomical niches. Fibroblast interaction analysis in the dura and subarachnoid space (SAS) uncovered novel interactions with vascular cell populations mediated by insulin growth factor signaling. Together, these data serve as a comprehensive resource for future investigations of meningeal function in the healthy and diseased brain.

Subcortical nuclei of the human ascending arousal system encode anticipated reward but do not predict subsequent memory
Subcortical nuclei of the ascending arousal system play an important role in regulating brain and cognition. However, functional MRI of these nuclei in humans involves unique challenges due to their size and location deep within the brain. Here, we used ultra-high-field MRI and other methodological advances to investigate the activity of six subcortical nuclei during reward anticipation and memory encoding: the locus coeruleus, basal forebrain, median and dorsal raphe nuclei, substantia nigra and ventral tegmental area. Participants performed a monetary incentive delay task, which successfully induced a state of reward anticipation, and a 24-hour delayed surprise memory test. Region-of-interest analyses revealed that activity in all subcortical nuclei increased in anticipation of potential rewards as opposed to neutral outcomes. In contrast, activity in none of the nuclei predicted memory performance 24 hours later. These findings provide new insights into the cognitive functions that are supported by the human ascending arousal system.

Calcium-based input timing learning
Stimulus-triggered synaptic long-term plasticity is the foundation of learning and other cognitive abilities of the brain. In general, long-term synaptic plasticity is subdivided into two different forms: homosynaptic plasticity describes synaptic changes at stimulated synapses, while heterosynaptic plasticity summarizes synaptic changes at non-stimulated synapses. For homosynaptic plasticity, the Ca2+-hypothesis pinpoints the calcium concentration within a stimulated dendritic spine as key mediator or controller of underlying biochemical and -physical processes. On the other hand, for heterosynaptic plasticity, although theoretical studies attribute important functional roles to it, such as synaptic competition and cooperation, experimental results remain ambiguous regarding its manifestation and biological basis. By integrating insights from Ca2+-dependent homosynaptic plasticity with experimental data of dendritic Ca2+-dynamics, we developed a mathematical model that describes the complex temporal and spatial dynamics of calcium in the dendritic shaft and respective dendritic spines. We show that the increased influx of calcium into a stimulated spine can lead to its diffusion through the shaft to neighboring spines, triggering heterosynaptic effects such as synaptic competition or cooperation. By considering different input strengths, our model explains the ambiguity of reported experimental results of heterosynaptic plasticity, suggesting that the Ca2+ hypothesis of homosynaptic plasticity can be extended to also model heterosynaptic plasticity. Furthermore, our model predicts that, via diffusion of calcium, a synapse can modulate the expression of homosynaptic plasticity at a neighboring synapse in an input-timing-dependent manner, without the need of postsynaptic spiking. The resulting sensitivity of synaptic plasticity on input-spike-timing can be influenced by the distance between involved spines as well as the local diffusion properties of the connecting dendritic shaft, providing a new way of dendritic computation.

Unique Asymmetric Branching of Drosophila Neurons Optimizes Temporal Dendritic Computation
Neurons execute a versatile array of computations through a complex interplay of factors, including their morphology and synaptic architecture. Dendritic branching encodes upstream inputs into diverse spike patterns transmitted via downstream axons. While earlier studies highlighted the distinct morphologies and functions of a few representative neurons, the availability of large-scale electron microscopy and fluorescent imaging now enables comprehensive data analysis and further simulations to explore structure-function relationships more broadly. This study investigates the general morphological characteristics of diverse neuron types in the fly model. By employing the Strahler Order (SO) metric, we identified a specific bias towards asymmetry in neuronal branching and further investigated the effect of the asymmetry on computational capabilities. Specifically, symmetric branching enhances coincidence detection capability, whereas asymmetric branching increases input order-selectivity. While certain neurons exhibit extreme symmetry or asymmetry optimized for specific tasks, most neurons strike a balance between these computational strategies. This balance underscores the intricate relationship between neuronal structure and function. In contrast to the wide range of branching symmetries found in random bifurcation models, neurons across different species exhibit species-specific asymmetry, suggesting shared underlying branching mechanisms. Our findings provide a fresh perspective on the exploration of neuronal morphologies and their computational roles.

Fructose-2,6-bisphosphate restores TDP-43 pathology-driven genome repair deficiency in motor neuron diseases
TAR DNA-binding protein 43 (TDP-43) proteinopathy plays a critical role in neurodegenerative diseases, including amyotrophic lateral sclerosis and frontotemporal dementia (FTD). In our recent discovery, we identified that TDP-43 plays a critical role in DNA double-strand break (DSB) repair via the non-homologous end joining (NHEJ) pathway. Here, we found persistent DNA damage in brains of ALS/FTD patients, primarily in the transcribed regions of the genome. We further investigated the underlying mechanism and found that the activity of polynucleotide kinase 3' phosphatase (PNKP) was severely impaired in the nuclear extracts of both the patient brains and TDP-43-depleted cells. PNKP is a key player in DSB repair within the transcribed genome, where its 3'-P termini processing activity is crucial for preventing persistent DNA damage and neuronal death. The inactivation of PNKP in ALS/FTD was due to reduced levels of its interacting partner, phosphofructo-2-kinase fructose 2,6 bisphosphatase (PFKFB3), and its biosynthetic product, fructose-2,6 bisphosphate (F2,6BP), an allosteric modulator of glycolysis. Recent work from our group has shown that F2,6BP acts as a positive modulator of PNKP activity in vivo. Notably, exogenous supplementation with F2,6BP restored PNKP activity in both nuclear extracts from ALS/FTD brain samples and in patient-derived induced pluripotent stem (iPS) cells harboring pathological mutations. Our findings underscore the possibility of exploring the therapeutic potential of F2,6BP or its analogs in TDP-43 pathology-associated motor neuron diseases.

Single-cell transcriptomic analysis of macaque LGN neurons reveals novel subpopulations
Neurons in the lateral geniculate nucleus (LGN) provide a pivotal role in the visual system by modulating and relaying signals from the retina to the visual cortex. Although the primate LGN, with its distinct divisions (magnocellular, M; parvocellular, P; and koniocellular, K), has been extensively characterized, the intrinsic heterogeneity of LGN neurons has remained unexplained. With the development of high-throughput single-cell transcriptomics, researchers can rapidly isolate and profile large sets of neuronal nuclei, revealing a surprising diversity of genetic expression within the nervous systems. Here, we analyzed the transcriptomes of individual cells belonging to macaque LGN using raw data from a public database to explore the heterogeneity of LGN neurons. Using statistical analyses, we found additional subpopulations within the LGN transcriptomic population, whose gene expressions imply functional differences. Our results suggest the existence of a more nuanced complexity in LGN processing beyond the classic view of the three cell types and highlight a need to combine transcriptomic and functional assessments. A complete account of the cell type diversity of the primate LGN is critical to understanding how vision works.

Spontaneous Brain Dynamics Associated With Acceleration Of Longterm Functional Connectome In Postnatal Development
The first six postnatal months are a critical period for brain development, marked by rapid changes in functional neural circuits. However, long-term changes in neonatal functional connectome lacks an interpretive imaging indicator for the future development due to the non-linearity characteristics. In this study, we introduce an approach to extract intrinsic brain states from short-term brain dynamics to study the long-term (longitudinal) development. We found a high association (r=0.460) between the co-activated pattern of specific brain state and the acceleration pattern of non-linear development of static functional connectome. The fractional occupancy, self-sustaining probability of this short-term state share the similar age tendency with the long-term change rate within the majority of the function connectome. These findings suggest that short-term brain dynamics could serve as potential biomarkers for predicting the long-term development of functional connectome.

Deep Neural Networks Explain Spiking Activity in Auditory Cortex
For static stimuli or at gross (~1-s) time scales, artificial neural networks (ANNs) that have been trained on challenging engineering tasks, like image classification and automatic speech recognition, are now the best predictors of neural responses in primate visual and auditory cortex. It is, however, unknown whether this success can be extended to spiking activity at fine time scales, which are particularly relevant to audition. Here we address this question with ANNs trained on speech audio, and acute multi-electrode recordings from the auditory cortex of squirrel monkeys. We show that layers of trained ANNs can predict the spike counts of neurons responding to speech audio and to monkey vocalizations at bin widths of 50 ms and below. For some neurons, the ANNs explain close to all of the explainable variance---much more than traditional spectrotemporal--receptive-field models, and more than untrained networks. Non-primary neurons tend to be more predictable by deeper layers of the ANNs, but there is much variation by neuron, which would be invisible to coarser recording modalities.

Single-cell transcriptomic landscape of the neuroimmune compartment in amyotrophic lateral sclerosis brain and spinal cord
Development of therapeutic approaches that target specific microglia responses in amyotrophic lateral sclerosis (ALS) is crucial due to the involvement of microglia in ALS progression. Our study identifies the predominant microglia subset in human ALS primary motor cortex and spinal cord as an undifferentiated phenotype with dysregulated respiratory electron transport. Moreover, we find that the interferon response microglia subset is enriched in donors with aggressive disease progression, while a previously described potentially protective microglia phenotype is depleted in ALS. Additionally, we observe an enrichment of non-microglial immune cell, mainly NK/T cells, in ALS central nervous system, primarily in the spinal cord. These findings pave the way for the development of microglia subset-specific therapeutic interventions to slow or even stop ALS progression.

Impaired online and enhanced offline motor sequence learning in individuals with Parkinson's disease
Whereas memory consolidation research has traditionally focused on longer temporal windows (i.e., hours to days) following an initial learning episode, recent research has also examined the functional significance of the shorter rest epochs commonly interspersed with blocks of task practice (i.e., "micro-offline" intervals on the timescale of seconds to minutes). In the motor sequence learning domain, evidence from young, healthy individuals suggests that micro-offline epochs afford a rapid consolidation process that is supported by the hippocampus. Consistent with these findings, amnesic patients with hippocampal damage were recently found to exhibit degraded micro-offline performance improvements. Interestingly, these offline losses were compensated for by larger performance gains during online practice. Given the known role of the striatum in online motor sequence learning, we hypothesized that individuals with dysfunction of the striatal system would exhibit impaired online, yet enhanced micro-offline, learning (i.e., a pattern of results opposite to those observed in patients with hippocampal lesions). We tested this hypothesis using Parkinson's disease (PD) as a model of striatal dysfunction. Forty-two de novo, drug-naive individuals (men and women) with a clinical diagnosis of unilateral PD and 29 healthy control subjects completed a motor sequence learning paradigm. Individuals with PD exhibited deficits during online task practice that were paralleled by greater improvements over micro-offline intervals. This pattern of results could not be explained by disease-related deficits in movement execution. These data suggest that striatal dysfunction disrupts online learning, yet total learning remains unchanged because of greater micro-offline performance improvements that potentially reflect hippocampal-mediated compensatory processes.

Descending locus coeruleus noradrenergic signaling to spinal astrocyte subset is required for stress-induced pain facilitation
It is known that stress powerfully alters pain, but its underlying mechanisms remain elusive. Here, we identified a circuit, locus coeruleus descending noradrenergic neurons projecting to the spinal dorsal horn (LC[->]SDH-NA neurons), that is activated by acute exposure to restraint stress and is required for stress-induced mechanical pain hypersensitivity in mice. Interestingly, the primary target of spinal NA released from descending LC[->]SDH-NAergic terminals causing the stress-induced pain hypersensitivity was 1A-adrenaline receptors (1ARs) in Hes5-positive (Hes5+) astrocytes located in the SDH, an astrocyte subset that has an ability to induce pain sensitization. Furthermore, activation of Hes5+ astrocytes reduced activity of SDH-inhibitory neurons (SDH-INs) that have an inhibitory role in pain processing. This astrocytic reduction of IN activity was canceled by an A1-adenosine receptor (A1R)-knockdown in SDH-INs, and the A1R-knockdown suppressed pain hypersensitivity caused by acute restraint stress. Therefore, our findings suggest that LC[->]SDH-NA neuronal signaling to Hes5+ SDH astrocytes and subsequent astrocytic reduction of SDH-IN activity are essential for pain facilitation caused by stress.

Humans anticipate the consequences of motor control demands when making perceptual decisions between actions
Animals, including humans, are often faced with situations where they must decide between potential actions to perform based on various sources of information, including movement parameters that incur time and energy costs. Consistent with this fact, many behavioral studies indicate that decisions and actions show a high level of integration during goal-directed behavior. In particular, motor costs very often bias the choice process of human and non-human subjects facing successive decisions between actions. However, it appears as well that depending on the design in which the experiment occurs, the effect of motor costs on decisions can vary or even vanish. This suggests a contextual dependence of the influence of motor costs on decision-making. Moreover, it is not currently known whether or not the impact of motor costs on perceptual decisions depend on the difficulty of the decision. We addressed these two important issues by studying the behavior of healthy human subjects engaged in a new perceptual decision-making paradigm in which the constraint level associated with the movement executed to report a choice was volitionally chosen by the participants, and in which the difficulty of the perceptual decision to make continuously evolved depending on their motor performance. The results indicate that the level of constraint associated with a movement executed to express a perceptual decision strongly impacts the duration of these decisions, with a shortening of decisions when these are expressed by demanding movements. This influence appears most important when the decisions are difficult, but it is also present for easy decisions. We interpret this strategy as an adaptive way to optimize the participants' overall rate of success at the session level.

No Effect of Value on the Task Irrelevant Auditory Mismatch Negativity
Behavioural and neuroscientific evidence suggests visual stimuli that signal value involuntarily capture attention and are preferentially processed, even when unattended. We examined whether learned value associations for task-irrelevant auditory stimuli modulate pre-attentive processing and involuntarily capture attention. Across two experiments, the effect of learned value on the visual- and auditory-evoked mismatch negativity (MMN) and P3a event-related potential (ERP) components was measured. Participants performed a primary visual detection task while an irrelevant, unattended oddball stimulus stream was concurrently presented. Deviants within this oddball stream had been previously learned to signal one of several value outcomes: monetary reward, loss or no change. Neither the auditory nor the visual MMN was influenced by these value associations. However, stimulus value affected performance on the primary task and the magnitude of the P3a in those who could identify the stimulus-value pairings at test. Supplementary mass univariate analyses and time frequency decomposition (theta phase-locking) confirmed the presence of the MMN and the absence of any influence of stimulus value on the MMN response. Findings suggest that learned value associations do not meaningfully influence the MMN prediction signaling mechanism for task-irrelevant auditory stimuli.

Pathological microcircuits initiate epileptiform events in patient hippocampal slices
How seizures begin at the level of microscopic neural circuits remains unknown. High-density CMOS microelectrode arrays provide a new avenue for investigating neuronal network activity, with unprecedented spatial and temporal resolution. We use high-density CMOS-based microelectrode arrays to probe the network activity of human hippocampal brain slices from six patients with mesial temporal lobe epilepsy in the presence of hyperactivity promoting media. Two slices from the dentate gyrus exhibited epileptiform activity in the presence of low magnesium media with kainic acid. Both slices displayed an electrophysiological phenotype consistent with a reciprocally connected circuit, suggesting a recurrent feedback loop is a key driver of epileptiform onset. Larger prospective studies are needed, but these findings have the potential to elucidate the network signals underlying the initiation of seizure behavior.

Dynamic prioritisation of sensory and motor contents in working memory
Internal selective attention prioritises both sensory and motor contents in working memory to guide prospective behaviour. Prior research has shown how attention modulation of sensory contents is flexible and temporally tuned depending on access requirements, but whether the prioritisation of motor contents follows similar flexible dynamics remains elusive. Also uncharted is the degree of co-dependence of sensory and motor modulation, which gets at the nature of both working-memory representations and internal attention functions. To address these questions, we independently tracked the prioritisation of sensory and motor working-memory contents as a function of dynamically evolving temporal expectations. The design orthogonally manipulated when an item location (left vs right side) and associated prospective action (left vs right hand) would be relevant. Contralateral modulation of posterior alpha (8-12 Hz) activity in electroencephalography (EEG) tracked prioritisation of the item location, while contralateral modulation of central mu/beta (8-30 Hz) activity tracked response prioritisation. Proactive and dynamic alpha and mu/beta modulation confirmed the flexible and temporally structured prioritisation of sensory and motor contents alike. Intriguingly, the prioritisation of sensory and motor contents was temporally uncoupled, showing dissociable patterns of modulation. The findings reveal multiple modulatory functions of internal attention operating in tandem to prepare relevant aspects of internal representations for adaptive behaviour.

Restoring Synaptic Balance in Schizophrenia: Insights from a thalamo-cortical conductance-based model.
The dysconnectivity hypothesis of schizophrenia suggests that atypical, aberrant neural communication underlies the disorder's diverse symptoms. Building on this framework, our study introduces a novel approach to understanding schizophrenia and exploring potential ways to adjust neural activity through synaptic restoration. Using a combination of magnetoencephalography data and dynamic causal modeling, we identified specific synaptic disturbances in schizophrenia patients, including increased NMDA receptor-mediated excitation in superficial pyramidal neurons and reduced GABA-B receptor-mediated inhibition between interneurons and pyramidal cells. These findings reveal a critical imbalance in excitation and inhibition within thalamo-cortical circuits, manifesting as altered gamma and alpha oscillations. The cornerstone of our research is an in silico synaptic restoration analysis, which demonstrates that targeted modifications to AMPA, NMDA, GABA-A, and GABA-B receptor-mediated connections can recalibrate altered neural activity in schizophrenia, aligning it with healthy control patterns. This restoration approach not only highlights the complex nature of synaptic dysfunction in the disorder but also identifies specific pathways as potential therapeutic targets, offering new avenues for investigating schizophrenia's diverse symptomatology.

Astrocytic connexin43 phosphorylation contributes to seizure susceptibility after mild Traumatic Brain Injury
Astrocytes play a crucial role in maintaining brain homeostasis through functional gap junctions (GJs) primarily formed by connexin43 (Cx43). These GJs facilitate electrical and metabolic coupling between astrocytes, allowing the passage of ions, glucose, and metabolites. Dysregulation of Cx43 has been implicated in various pathologies, including traumatic brain injury (TBI) and acquired epilepsy. We previously identified a subset of atypical astrocytes after mild TBI that exhibit reduced Cx43 expression and coupling and are correlated with the development of spontaneous seizures. Given that mild TBI affects millions globally and can lead to long-term complications, including post-traumatic epilepsy, understanding the molecular events post-TBI is critical for developing therapeutic strategies.

In the present study, we assessed the heterogeneity of Cx43 protein expression after mild TBI. In accordance with our previous findings, a subset of astrocytes lost Cx43 expression. As previously reported after TBI, we also found a significant increase in total Cx43 protein expression after mild TBI, predominantly in the soluble form, suggesting that while junctional Cx43 protein levels remained stable, hemichannels and cytoplasmic Cx43 were increased. We then investigated the phosphorylation of Cx43 at serine 368 after TBI, which is known to influence GJ assembly and function. Phosphorylation of Cx43 at serine 368 is elevated following TBI and Cx43S368A mutant mice, lacking this phosphorylation, exhibited reduced susceptibility to seizures induced by pentylenetetrazol (PTZ). These findings suggest that TBI-induced Cx43 phosphorylation enhances seizure susceptibility, while inhibiting this modification presents a potential therapeutic avenue for mitigating neuronal hyperexcitability and seizure development.

Significance statementConnexin43 (Cx43) is the main protein of astrocyte gap junctions, mediating astrocyte coupling of astrocytes into cellular networks, but has also other non-junctional functions. Many pathologies present with altered Cx43 regulation. In this study, we studied Cx43 alterations after mild traumatic brain injury (TBI) in a mouse model. We found that while some astrocyte lost Cx43 expression, a subset of astrocytes experienced an increase in cytoplasmic and hemichannel Cx43. This increase correlated with an increase in phosphorylated Cx43 at serine 368. Cx43S368A mutant mice, lacking this phosphorylation, exhibited reduced susceptibility to seizures induced by pentylenetetrazol (PTZ). These findings suggest that TBI-induced Cx43 phosphorylation enhances seizure susceptibility.

Modeling of blood flow dynamics in the rat somatosensory cortex
The cerebral microvasculature forms a dense network of interconnected blood vessels where flow is modulated partly by astrocytes. Increased neuronal activity stimulates astrocytes to release vasoactive substances at the endfeet, altering the diameters of connected vessels. Our study simulated the coupling between blood flow variations and vessel diameter changes driven by astrocytic activity in the rat somatosensory cortex. We developed a framework with three key components: coupling between vasculature and synthesized astrocytic morphologies, a fluid dynamics model to compute flow in each vascular segment, and a stochastic process replicating the effect of astrocytic endfeet on vessel radii. The model was validated against experimental flow values from literature across cortical depths. We found that local vasodilation from astrocyte activity increased blood flow, especially in capillaries, exhibiting a layer-specific response in deeper cortical layers. Additionally, the highest blood flow variability occurred in capillaries, emphasizing their role in cerebral perfusion regulation. We discovered that astrocytic activity impacts blood flow dynamics in a localized, clustered manner, with most vascular segments influenced by two to three neighboring endfeet. These insights enhance our understanding of neurovascular coupling and guide future research on blood flow-related diseases.

Spatial Transcriptomic Analysis Identifies a SERPINA3-Expressing Astrocytic State Associated with the Human Neuritic Plaque Microenvironment
Single-nucleus transcriptomic studies have revealed glial cell states associated with Alzheimers disease; however, these nuclei are dissociated from the complex architecture of the human neocortex. Here, we successfully performed an unbiased distance-based analytic strategy on spatially-registered transcriptomic data. Leveraging immunohistochemistry in the same tissue section, our analyses prioritized SERPINA3 and other genes, such as metallothioneins, as altered in the vicinity of neuritic amyloid plaques. Results were validated at the protein level by immunofluorescence, highlighting that a reactive SERPINA3+ astrocyte subtype, Ast.5, plays a role in the plaque microenvironment.

Sulfatide deficiency-induced astrogliosis and myelin lipid dyshomeostasis are independent of Trem2-mediated microglial activation
Disrupted lipid homeostasis and neuroinflammation often co-exist in neurodegenerative disorders including Alzheimers disease (AD). However, the intrinsic connection and causal relationship between these deficits remain elusive. Our previous studies show that the loss of sulfatide (ST), a class of myelin-enriched lipids, causes AD-like neuroinflammatory responses, cognitive impairment, bladder enlargement, as well as lipid dyshomeostasis. To better understand the relationship between neuroinflammation and lipid disruption induced by ST deficiency, we established a ST-deficient mouse model with constitutive Trem2 knockout and studied the impact of Trem2 in regulating ST deficiency-induced microglia-mediated neuroinflammation, astrocyte activation and lipid disruption. Our study demonstrates that Trem2 regulates ST deficiency-induced microglia-mediated neuroinflammatory pathways and astrogliosis at the transcriptomic level, but not astrocyte activation at the protein level, suggesting that Trem2 is indispensable for ST deficiency-induced microglia-mediated neuroinflammation but not astrogliosis. Meanwhile, ST loss-induced lipidome disruption and free water retention were consistently observed in the absence of Trem2. Collectively, these results emphasize the essential role of Trem2 in mediating lipid loss-associated microglia-mediated neuroinflammation, but not both astrogliosis and myelin lipid disruption. Moreover, we demonstrated that attenuating neuroinflammation has a limited impact on brain ST loss-induced lipidome alteration or AD-like peripheral disorders. Our findings suggest that preserving lipidome and astrocyte balance may be crucial in decelerating the progression of AD.

Bidirectional Impact of miR-29a modulation on Memory Stability in the Adult Brain
MicroRNAs are key regulators of brain gene expression, with miR-29a notably upregulated from development to adulthood and in aging, and showing links to cognitive decline. However, the extent to which miR-29 levels influence learning and memory processes, and its molecular mediators, remains to be determined. Here, we down- and up-regulated miR-29a levels in the dorsal hippocampus of adult mice to reveal miR-29 role in memory. Inhibiting miR-29a enhanced trace fear memory stability, increased Dnmt3a levels, and affected CpG methylation in gene regulation regions. In contrast, increasing miR-29a impaired memory performances and decreased Dnmt3a levels, suggesting a destabilization of memory processes. Proteomic and transcriptomic analysis demonstrated that miR-29a antagonism upregulated RNA-binding and synaptic proteins and downregulated inflammation and myelin associated proteins. These results underscore miR-29a pivotal role in memory persistence, plasticity, and cognitive aging, suggesting that miR-29a modulation could offer potential strategies for cognitive enhancement and age-related memory decline.

A Unified Approach for Identifying PET-based Neuronal Activation and Molecular Connectivity with the functional PET toolbox
Purpose: Functional PET (fPET) enables the identification of stimulation-specific changes of various physiological processes (e.g., glucose metabolism, neurotransmitter synthesis) as well as computation of individual molecular connectivity and group-level molecular covariance. However, currently no consistent analysis approach is available for these techniques. We present a versatile, freely available toolbox designed for the analysis of fPET data, thereby filling a gap in the assessment of neuroimaging data. Methods: The fPET toolbox supports analyses for a variety of radiotracers, scanners, experimental protocols, cognitive tasks and species. It includes general linear model (GLM)-based assessment of task-specific effects, percent signal change and absolute quantification, as well as independent component analysis (ICA) for data-driven analyses. Furthermore, it allows computation of molecular connectivity via temporal correlations of PET signals between regions and molecular covariance as between-subject covariance using static images. Results: Toolbox performance was validated by analysis protocols established in previous work. Stimulation-induced changes in [18F]FDG metabolic demands and neurotransmitter dynamics obtained with 6-[18F]FDOPA and [11C]AMT were robustly detected across different cognitive tasks. Molecular connectivity analysis demonstrated metabolic interactions between different networks, whereas group-level covariance analysis highlighted interhemispheric relationships. These results underscore the flexibility of fPET in capturing dynamic molecular processes. Conclusions: The toolbox offers a comprehensive, unified and user-friendly platform for analyzing fPET data across a variety of experimental settings. It provides a reproducible analysis approach, which in turn facilitates sharing of analyses pipelines and comparison across centers to advance the study of brain metabolism and neurotransmitter dynamics in health and disease.

Modeling Complex Animal Behavior with Latent State Inverse Reinforcement Learning
Understanding complex animal behavior is crucial for linking brain computation to observed actions. While recent research has shifted towards modeling behavior as a dynamic process, few approaches exist for modeling long-term, naturalistic behaviors such as navigation. We introduce discrete Dynamical Inverse Reinforcement Learning (dDIRL), a latent state-dependent paradigm for modeling complex animal behavior over extended periods. dDIRL models animal behavior as being driven by internal state-specific rewards, with Markovian transitions between the distinct internal states. Using expectation-maximization, we infer reward functions corresponding to each internal states and the transition probabilities between them, from observed behavior. We applied dDIRL to water-starved mice navigating a labyrinth, analyzing each animal individually. Our results reveal three distinct internal states sufficient to describe behavior, including a consistent water-seeking state occupied for less than half the time. We also identified two clusters of animals with different exploration patterns in the labyrinth. dDIRL offers a nuanced understanding of how internal states and their associated rewards shape observed behavior in complex environments, paving the way for deeper insights into the neural basis of naturalistic behavior.

Interactions established by isoform-specific TrkB-T1 sequences govern inflammatory response and neurotoxicity in stroke
Ugalde-Trivino et al. develop cell-penetrating peptides derived from neurotrophin receptor TrkB-T1 to identify isoform-specific protein interactions and demonstrate protective effects on neuroinflammation and neurotoxicity reducing brain damage in a mice model of ischemic stroke, of relevance to human therapy.

AbstractGlia reactivity, neuroinflammation and excitotoxic neuronal death are central processes to ischemic stroke and neurodegenerative diseases, altogether a leading cause of death, disability, and dementia. Due to the high incidence of these pathologies and the lack of efficient treatments, it is a priority developing brain protective therapies impacting both neurons and glial cells. Truncated neurotrophin receptor TrkB-T1, a protein produced by all these cells, plays relevant roles in excitotoxicity and ischemia. We have hypothesized that interactions established by isoform-specific TrkB-T1 sequences might be relevant to neurotoxicity and/or reactive gliosis and, therefore, constitute a therapeutic target. We identify here the TrkB-T1-specific interactome, poorly described to date, and demonstrate that interference of these protein-protein interactions using brain-accessible TrkB-T1-derived peptides can prevent reactive gliosis and decrease excitotoxicity-induced damage in cellular and mouse models of stroke. The pivotal role played by TrkB-T1 on microglia and astrocyte reactivity suggests that isoform-derived peptides could become important in development of therapies for human stroke and other excitotoxicity-associated pathologies.

Older is Order: Entropy reduction in cortical spontaneous activity marks healthy aging
Entropy trajectories remain unclear for the aging process of human brain system due to the lacking of longitudinal neuroimaging resource. We used open data from an accelerated longitudinal cohort (PREVENT-AD) that included 24 healthy aging participants followed by 4 years with 5 visits per participant to establish cortical entropy aging curves and distinguish with the effects of age and cohort. This reveals that global cortical entropy decreased with aging, while a significant cohort effect was detectable that people who were born earlier showed higher cortical entropy. Such entropy reductions were also evident for large-scale cortical networks, although with different rates of reduction for different networks. Specifically, the primary and intermediate networks reduce their entropy faster than the higher-order association networks. We conclude two specific characteristics of the entropy of the human cortex with aging: the shift of the complexity hierarchy and the diversity of complexity strengthen.

Brain functional network connectivity interpolation characterizes neuropsychiatric continuum and heterogeneity
Psychiatric disorders such as schizophrenia (SZ) and autism spectrum disorder (ASD) are challenging to characterize in part due to their heterogeneous presentation in individuals, with psychotic symptoms now thought to exist on a continuum from the general population to chronic SZ. Conventional diagnostic and neuroimaging analytical approaches rely on subjective assessment or group differences, but typically ignore progression between groups or heterogeneity within a group. Here, we propose a functional network connectivity (FNC) interpolation framework based on an unsupervised generative model, a variational autoencoder (VAE), to estimate the neuropsychiatric continuum and heterogeneity using static FNC (sFNC) and dynamic FNC (dFNC) data from controls and patients with SZ or ASD. We first demonstrate that VAEs significantly outperform a linear baseline and a semi-supervised counterpart in the interpolation task. We next utilize VAEs to perform sFNC and dFNC interpolation separately. For sFNC interpolation, we observe a high degree of correspondence between the generated sFNC and the corresponding original sFNC. We display the sFNC matrices on a two-dimensional grid to examine individual- and group-specific patterns, as well as pattern alterations. Specifically, the interpolated continua from patients to controls in both disorders show increased hyper-connectivity within the auditory, sensorimotor and visual networks, and between the subcortical and cerebellar domains, as well as hypo-connectivity between the subcortical domain and the sensory domains, and between the cerebellar domain and the sensory regions. For dFNC interpolation, we find that the generated dFNC states effectively capture representative and generalizable dynamic properties for each group. Finally, we show examples of how to leverage interpolation in the VAE latent space, following pathological, state-based, or temporal trajectories. The proposed framework offers added advantages over traditional methods, including data-driven discovery of hidden relationships, visualization of individual differences, imputation of missing values along a continuous spectrum, and estimation of the stage where an individual falls within the continuum. Further, it could potentially be applied to identify patient subgroups and predict future disorder progression.

Comparative analysis of spike-sorters in large-scale brainstem recordings
Recent technological advancements in high-density multi-channel electrodes have made it possible to record large numbers of neurons from previously inaccessible regions. While the performance of automated spike-sorters has been assessed in recordings from cortex, dentate gyrus, and thalamus, the most effective and efficient approach for spike-sorting can depend on the target region due to differing morphological and physiological characteristics. We therefore assessed the performance of five commonly used sorting packages, Kilosort3, MountainSort5, Tridesclous, SpyKING CIRCUS, and IronClust, in recordings from the rostral ventromedial medulla, a region that has been characterized using single-electrode recordings but that is essentially unexplored at the high-density network level. As demonstrated in other brain regions, each sorter produced unique results. Manual curation preferentially eliminated units detected by only one sorter. Kilosort3 and IronClust required the least curation while maintaining the largest number of units, whereas SpyKING CIRCUS and MountainSort5 required substantial curation. Tridesclous consistently identified the smallest number of units. Nonetheless, all sorters successfully identified classically defined RVM physiological cell types. These findings suggest that while the level of manual curation needed may vary across sorters, each can extract meaningful data from this deep brainstem site.

Significance StatementHigh-density multichannel recording probes that can access deep brainstem structures have only recently become commercially available, but the performance of open-source spike-sorting packages applied to recordings from these regions has not yet been evaluated. The present findings demonstrate that Kilosort3, MountainSort5, Tridesclous, SpyKING CIRCUS, and IronClust can all be reasonably used to identify units in a deep brainstem structure, the rostral ventromedial medulla (RVM). However, manual curation of the output was essential for all sorters. Importantly, all sorters identified the known, physiologically defined RVM cell classes, confirming their utility for deep brainstem recordings. Our findings provide suggestions for processing parameters to use for brainstem recordings and highlight considerations when using high-density silicon probes in the brainstem.

SEX-RELATED GENE EXPRESSION IN THE POSTERODORSAL MEDIAL AMYGDALA OF CYCLING FEMALE RATS ALONG WITH PROLACTIN MODULATION OF LORDOSIS BEHAVIOR
The rat posterodorsal medial amygdala (MePD) is sexually dimorphic, has a high concentration of receptors for gonadal hormones and prolactin (PRL), and modulates reproduction. To unravel genetic and functional data for this relevant node of the social behavior network, we studied the expression of ERalpha, ERbeta, GPER1, Kiss1, Kiss1R, PRGR, PRL, PRLR, EGR1, JAK2, STAT5A, and STAT5B in the MePD of males and females along the estrous cycle using the RT-qPCR technique. We also investigated whether PRL in the MePD would affect the sexual behavior display of proestrus females by microinjecting saline, the PRL receptor antagonist Del1-9-G129R-hPRL (1 microM and 10 microM), or PRL (1 nM) and Del1-9-G129R-hPRL (10 microM) 3h before the onset of the dark-cycle period. The estrogen-dependent lordosis behavior, indicative of sexual receptivity of proestrus females, was recorded and compared before (control) and after (test) microinjections in these groups. Sex differences were found in the right and left MePD gene expression. ERalpha and Kiss1R, as well as PRL, Short PRLR, and STAT5B expression is higher in cycling females than males. Kiss1 expression is higher in males than females, and GPER1 is higher during diestrus than proestrus. Furthermore, Del1-9-G129R-hPRL in the MePD significantly reduced the full display and quotient of lordosis in proestrus females, an effect restored by the co-microinjection of PRL. In conjunction, the expression of studied genes showed specific sex and estrous cycle phase features while, in proestrus, PRL action in the MePD plays an essential role in the display of lordosis during the ovulatory period.

Multimodal investigation of the neurocognitive deficits underlying dyslexia in adulthood
Dyslexia is a neurobiological disorder characterised by reading difficulties, yet its underlying causes remain unclear. Neuroimaging and behavioural studies found anomalous responses in tasks requiring phonological processing, motion perception, and implicit learning, and showed gray and white matter abnormalities in several brain regions of dyslexics compared to controls, indicating that dyslexia is a heterogeneous condition and promoting a multifactorial approach. In order to evaluate whether the combination of behavioural and multimodal MRI can have greater sensitivity in identifying neurocognitive traits of dyslexia compared to monocomponential approaches, in 19 dyslexic and 19 control subjects we acquired behavioural cognitive assessments, multiple (phonological, visual motion, rhythmic) mismatch-response functional MRI tasks, structural diffusion-weighted and T1-weighted images. To examine between-group differences in the multimodal neurocognitive measures, we applied univariate and multivariate approaches. Results showed that dyslexics performed worse than controls in behavioural phonological tasks. Neuroimaging analyses revealed that individuals with dyslexia present reduced cerebellar responses to mismatching rhythmic stimuli, as well as structural disorganization in several white matter tracts and cortical regions previously implicated in dyslexia. Most importantly, in line with the view of dyslexia as a multifactorial phenomenon, a machine learning model trained with features from all three MRI modalities (functional, diffusion, and T1-weighted) discriminated between dyslexics and controls with greater accuracy than models including just one modality. The individual classification scores in the multimodal machine learning model correlated with behavioural reading accuracy. These results confirm that dyslexia should be approached as a composite condition characterised by multiple distinctive cognitive and brain features.

Feature similarity: a sensitive method to capture the functional interaction of brain regions and networks to support flexible behavior
The brain is a dynamic system where complex behaviours emerge from interactions across distributed regions. Accurately linking brain function to cognition requires tools that are sensitive to these dynamics. We introduce a novel technique - Feature Similarity (FS) - to capture intricate interaction patterns between brain systems. Our results show that FS can capture functional brain organisation: regions within the same functional network have greater FS compared to those in different networks, and FS also identifies the principal gradient that spans from unimodal to transmodal cortices. FS was found to be more sensitive to task modulation than traditional functional connectivity (FC). Specifically, FS reveals interaction patterns missed by FC, such as a double dissociation in the Dorsal Attention Network (DAN): greater interaction with the Visual network during working memory tasks and greater interaction with the default mode network (DMN) during long-term memory tasks. This study highlights FS as a promising tool for understanding flexibility in brain network dynamics.

Putative Role of Norrin in Neuroretinal Differentiation Revealed by bulk and scRNA Sequencing of Human Retinal Organoids
Pathogenic variants in the X-linked gene NDP (Norrie disease protein) have been associated with a variety of non-syndromic and syndromic human retinal diseases, including Norrie disease and familial exudative vitroretinopathy. The gene codes for Norrin, a secreted angiogenic molecule which binds to FZD4 and its co-receptors LRP5/6 and TSPAN12 and activates Wnt-signaling. Additionally, it also potentiates Wnt-signaling by binding to the LGR4 receptor. Norrin was also found to exert a neuroprotective function in the retina, specifically for retinal ganglion cells. Furthermore, it was suggested to be involved in neurodevelopmental processes such as early neuro-ectodermal specification and differentiation, as well as maintenance of cochlear hair cells. To better understand the putative role of Norrin in neuronal cells of the retina we generated NDP mutant and eGFP-expressing NDP reporter human induced pluripotent stem cells, which were differentiated to retinal organoids. Bulk RNA sequencing and fixed single-cell RNA sequencing revealed alterations in gene expression as well as cellular composition, with increased proportions of retinal progenitors as well as Muller glia cells in NDPKO retinal organoids. Differential expression of genes related to glutamate signaling, Wnt and MAPK signaling, as well as neurogenesis was detected. Furthermore, genes associated with functions in the extracellular matrix were also differentially expressed. The considerable decrease in retinal neurons found in our NDPKO organoids suggest that Norrin is also important for retinal neurogenesis, which may precede the vascular manifestations in NDP-associated diseases.

On Levodopa interactions with brain disease proteins at the nanoscale
The cerebral accumulation of alpha-Synuclein (alpha-Syn) and amyloid beta-1-42 (Abeta-42) proteins are known to play a crucial role in the pathology of neurocognitive disorders such as Parkinson's disease (PD). Currently, Levodopa (L-dopa) is the dopamine replacement therapy for treating bradykinetic symptoms visible in PD patients. Here, we use atomic force microscopy to evidence at nanometer length scales the effects of L-dopa on the morphology of alpha-Syn and Abeta-42 protein fibrils. L-dopa treatment reduces the length and diameter of both types of protein fibrils, with a stark reduction observed for Abeta-42 both in physiological buffer and human spinal fluid. The insights gained on Abeta-42 fibril disassembly from the nanoscale imaging experiments are substantiated using atomic-scale molecular dynamics simulations. Our results reveal the mechanism governing L-dopa-driven reversal of protein aggregation, which may be useful in drug design of small molecule drugs for potentially treating neurocognitive disorders and provide leads for designing chemical effector-mediated disassembly of protein architectures.

Regenerative potential of human enteric glia in a preclinical model of acute brain injury
Acute brain injuries are characterized by extensive tissue damage, resulting in neuronal loss and severe functional deficits in patients. Self-regeneration is insufficient for the repair of damaged tissue. Therapies based on exogenous cells may offer a promising approach. In this study, we evaluated the feasibility of transplanting exogenous human enteric glia (hEG) in a preclinical model of brain injury. hEG were isolated, expanded and administered intranasally in brain-injured immunocompetent rats. hEG satisfied the safety criteria for cell therapy and were well tolerated. Additionally, hEG migrated to the injured area of the brain, where they enhanced endogenous angiogenesis and neurogenesis, contributing to tissue regeneration. Notably, hEG generated neurons that engrafted and integrated into the brain tissue. These neurons were enveloped by host oligodendrocytes and formed synaptic connections within the host tissue. Our findings provide evidence that hEG have regenerative potential and might be safely used for repair strategies in brain injury.

Regional Brain Entropy, Brain Network and Structural-Functional Coupling in Human Brain
Brain entropy (BEN) indicates the irregularity, unpredictability and complexity of brain activity. In healthy brains, resting-state fMRI-based regional BEN (rBEN) distribution has been shown to have potential relationships with functional brain networks. However, the relationship between rBEN and structural and functional networks, as well as how rBEN facilitates the coupling between structural and functional networks remains unclear. Additionally, network dimensionality reduction methods, such as the use of connectome gradients, have become popular in recent years for explaining the hierarchical architecture of brain function, and the sensorimotor-association (S-A) axis, as a major axis of hierarchical cortical organization, exerts a widespread influence on both brain structure and function. However, how this functional hierarchy affects the relationship between rBEN and brain networks remains unclear. In this study, we systematically examine the relationship between rBEN and both structural and functional networks, including BOLD-based functional networks and MEG-based functional networks. We also assess the impact of the BEN and network gradients, as well as the influence of the S-A axis, on the relationship between rBEN and brain networks. Our results reveal a negative correlation between BEN and the network efficiency of both structural and BOLD-based functional networks, as assessed by average connection strength, degree centrality, and local efficiency. Additionally, BEN shows a negative correlation with the coupling between structural and BOLD functional networks. In contrast, the relationship between BEN and MEG functional network efficiency varies from negative to positive across different frequency bands, with a shift from negative to positive correlation observed in the coupling between BEN and MEG-functional networks. Moreover, the coupling between BOLD and MEG functional networks is positively correlated with BEN. The relationship between BEN and network gradients is complex, and no consistent patterns were observed. Importantly, the relationship between BEN and brain networks is influenced by the S-A axis, and the connection between BEN and networks is further modulated by changes in cytoarchitectural organization. These results are consistent with the commonly observed relationship between elevated rBEN and impaired networks in psychiatric disorders. The negative correlation between BEN and the efficiency of both structural and BOLD functional networks, as well as their coupling, may suggest that lower rBEN is associated with higher information processing potential. Additionally, the positive correlation between BEN and high-frequency MEG functional networks, as well as the coupling between BOLD and MEG functional networks, may indicate that brain processes related to information acquisition and integration could increase rBEN. In summary, this complex relationship may reflect a dynamic process in which the brain continuously acquires external information for integration (increasing entropy) and internalizes it (decreasing entropy) as part of its information-processing mechanism in different timescales.

Filling-in of the Blindspot is Multisensory
The blind spot is an area on the retina that lacks photoreceptors, thus no visual information is encoded. Yet, we can maintain the sense of a seamless visual field owing to perceptual filling-in. Traditionally viewed as a surface interpolation mechanism, filling-in has been studied predominantly under unimodal conditions. However, there are limits to this process; the brain cannot always reconstruct all surfaces. Multisensory processing may bolster the process of perceptual filling-in to occur even with complex and dynamic perceptual stimuli. In this study, we employed the Audiovisual (AV) Rabbit Illusion to investigate how auditory stimuli influence visual filling-in at the blind spot. Our findings confirmed that auditory cues can induce the perception of an illusory flash within the blind spot, indicating that the brain leverages multimodal information to enrich visual scenes. This suggests that perceptual filling-in is not merely unimodal surface interpolation but a cross-modally integrated spatial representation and therefore more similar to other visual field locations than previously hypothesized. Furthermore, for blind spot filling-in to occur, visual stimuli do not need to be spatially contiguous, they simply need to be crossmodally associated (or grouped), which supports a higher-level sensory processing in filling-in than previously understood.

Single MAPT knock-in mouse models of frontotemporal dementia for sharing with the neurodegenerative research community
We recently reported development of human MAPT knock-in mice that carry single or double pathogenic mutations of frontotemporal dementia. However, it takes more than 14 months for the line with the most aggressive phenotypes to exhibit tau pathology without forming high-order tau oligomers, along with concomitant abnormal behavior. We thus generated MAPT knock-in mice carrying triple mutations, among which the MAPTP301S;Int10+3;S320F line exhibited robust pathology starting earlier than 6 months. Tau accumulation took place mainly in the thalamus, hypothalamus, amygdala and entorhinal cortex, but less so in the hippocampus, leading to synaptic loss, atrophy and behavioral abnormalities. Crossbreeding MAPTP301S;Int10+3;S320F with App knock-in mice AppNL-G-F resulted in the manifestation of tau pathology in the hippocampus and cortex. These mutant mice will be valuable tools for understanding the mechanisms of frontotemporal dementia, Alzheimer's disease and other tauopathies.

Variable Cerebral Blood Flow Responsiveness to Acute Hypoxic Hypoxia
Cerebrovascular reactivity (CVR) to changes in blood carbon dioxide and oxygen levels is a robust indicator of vascular health. Although CVR is typically assessed with hypercapnia, the interplay between carbon dioxide and oxygen, and their ultimate roles in dictating vascular tone, can vary with pathology. Methods to characterize vasoreactivity to oxygen changes, particularly hypoxia, would provide important complementary information to established hypercapnia techniques. However, existing methods to study hypoxic CVR, typically with arterial spin labeling (ASL) MRI, demonstrate high variability and paradoxical responses. To understand whether these responses are real or due to methodological confounds of ASL, we used phase-contrast MRI to quantify whole-brain blood flow in 21 participants during baseline, hypoxic, and hypercapnic respiratory states in three scan sessions. Hypoxic CVR reliability was poor-to-moderate (ICC=0.42 for CVR relative to PETO2 changes, ICC=0.56 relative to SpO2 changes) and was less reliable than hypercapnic CVR (ICC=0.67). Without the uncertainty from ASL-related confounds, we still observed paradoxical responses at each timepoint. Concurrent changes in blood carbon dioxide levels did not account for paradoxical responses. Hypoxic CVR and hypercapnic CVR shared approximately 40% of variance across the dataset, indicating that the two effects may indeed reflect distinct, complementary elements of vascular regulation.

Attentional failures after sleep deprivation represent moments of cerebrospinal fluid flow
Sleep deprivation rapidly disrupts cognitive function, and in the long term contributes to neurological disease. Why sleep deprivation has such profound effects on cognition is not well understood. Here, we use simultaneous fast fMRI-EEG to test how sleep deprivation modulates cognitive, neural, and fluid dynamics in the human brain. We demonstrate that after sleep deprivation, sleep-like pulsatile cerebrospinal fluid (CSF) flow events intrude into the awake state. CSF flow is coupled to attentional function, with high flow during attentional impairment. Furthermore, CSF flow is tightly orchestrated in a series of brain-body changes including broadband neuronal shifts, pupil constriction, and altered systemic physiology, pointing to a coupled system of fluid dynamics and neuromodulatory state. The timing of these dynamics is consistent with a vascular mechanism regulated by neuromodulatory state, in which CSF begins to flow outward when attention fails, and flow reverses when attention recovers. The attentional costs of sleep deprivation may thus reflect an irrepressible need for neuronal rest periods and widespread pulsatile fluid flow.