Glia-Mediated Antigen Presentation In The Retina During Degeneration
Glia antigen-presenting cells (APCs) are pivotal regulators of immune surveillance within the retina, maintaining tissue homeostasis and promptly responding to insults. The intricate mechanisms underlying their local coordination and activation remain unclear. Our study integrates an animal model of retinal injury, retrospective analysis of human retinas, and in vitro experiments to elucidate insights into the pivotal role of antigen presentation in neuroimmunology during retinal degeneration, uncovering the involvement of various glial cells, notably Muller glia, and microglia. Glial cells act as sentinels, detecting antigens released during degeneration and interacting with T-cells via MHC molecules, which are essential for immune responses. Microglia function as APCs via the MHC class II pathway, upregulating key molecules such as Csf1r and cytokines. In contrast, Muller cells act as atypical APCs through the MHC class I pathway, exhibiting upregulated antigen processing genes and promoting a CD8+ T-cell response. Human retinal specimens corroborate these findings, demonstrating glial activation and MHC expression correlating with degenerative changes. In vitro assays also confirmed differential T-cell migration responses to activated microglia and Muller cells, highlighting their role in shaping the immune milieu within the retina. These insights emphasize the complex interplay between glial cells and T-cells, influencing the inflammatory environment and potentially modulating degenerative processes. In summary, our study emphasizes the involvement of retinal glial cells in modulating the immune response after insults to the retinal parenchyma. Thus, unraveling the intricacies of glia-mediated antigen presentation in retinal degeneration is essential for developing precise therapeutic interventions for retinal pathologies.

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Brain age prediction and deviations from normative trajectories in the neonatal connectome
Structural and functional connectomes undergo rapid changes during the third trimester and the first month of postnatal life. Despite progress, our understanding of the developmental trajectories of the connectome in the perinatal period remains incomplete. Brain age prediction uses machine learning to estimate the brain's maturity relative to normative data. The difference between the individual's predicted and chronological age, or brain age gap (BAG),represents the deviation from these normative trajectories. Here, we assess brain age prediction and BAGs using structural and functional connectomes for infants in the first month of life. We used resting-state fMRI and DTI data from 611 infants (174 preterm; 437 term) from the Developing Human Connectome Project (dHCP) and connectome-based predictive modeling to predict postmenstrual age (PMA). Structural and functional connectomes accurately predicted PMA for term and preterm infants. Predicted ages from each modality were correlated. At the network level, nearly all canonical brain networks, even putatively later developing ones, generated accurate PMA prediction. Additionally, BAGs were associated with perinatal exposures and toddler behavioral outcomes. Overall, our results underscore the importance of normative modeling and deviations from these models during the perinatal period.

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Bridging verbal coordination and neural dynamics
Our use of language, which is profoundly social in nature, essentially takes place in interactive contexts and is shaped by precise coordination dynamics that interlocutors must observe. Thus language interaction is high demanding on fast adjustment of speech production. Here, we developed a real-time coupled-oscillators virtual partner that allows - by changing the coupling strength parameters - to modulate the ability to synchronise speech with a speaker. Then, we recorded the intracranial brain activity of 16 patients with drug-resistant epilepsy while they performed a verbal coordination task with the virtual partner (VP). More precisely, patients had to repeat short sentences synchronously with the VP. This synchronous speech task is efficient to highlight both the dorsal and ventral language pathways. Importantly, combining time-resolved verbal coordination and neural activity shows more spatially differentiated patterns and different types of neural sensitivity along the dorsal pathway. More precisely, high-frequency activity in secondary auditory regions is highly sensitive to verbal coordinative dynamics, while primary regions are not. Finally, the high-frequency activity of the IFG BA44 seems to specifically index the online coordinative adjustments that are continuously required to compensate deviation from synchronisation. These findings illustrate the possibility and value of using a fully dynamic, adaptive and interactive language task to gather deeper understanding of the subtending neural dynamics involved in speech perception, production as well as their interaction.

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A human forebrain organoid model reveals the essential function of GTF2IRD1-TTR-ERK axis for the neurodevelopmental deficits of Williams Syndrome
Williams Syndrome (WS; OMIM#194050) is a rare disorder, which is caused by the microdeletion of one copy of 25-27 genes, and WS patients display diverse neuronal deficits. Although remarkable progresses have been achieved, the mechanisms for these distinct deficits are still largely unknown. Here, we have shown that neural progenitor cells (NPCs) in WS forebrain organoids display abnormal proliferation and differentiation capabilities, and synapse formation. Genes with altered expression are related to neuronal development and neurogenesis. Single cell RNA-seq (scRNA-seq) data analysis revealed 13 clusters in healthy control and WS organoids. WS organoids show an aberrant generation of excitatory neurons. Mechanistically, the expression of transthyretin (TTR) are remarkably decreased in WS forebrain organoids. We have found that GTF2IRD1 encoded by one WS associated gene GTF2IRD1 binds to TTR promoter regions and regulates the expression of TTR. In addition, exogenous TTR can activate ERK signaling and rescue neurogenic deficits of WS forebrain organoids. Gtf2ird1 deficient mice display similar neurodevelopmental deficits as WS organoids. Collectively, our study reveals critical function of GTF2IRD1 in regulating neurodevelopment of WS forebrain organoids and mice, and provides novel insight into mechanisms underlying the abnormal neurodevelopment of WS.

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Ca2+-dependent phosphodiesterase 1 regulates the plasticity of striatal spiny projection neuron glutamatergic synapses
Long-term synaptic plasticity at glutamatergic synapses on striatal spiny projection neurons (SPNs) is central to learning goal-directed behaviors and habits. Although considerable attention has been paid to the mechanisms underlying synaptic strengthening and new learning, little scrutiny has been given to those involved in the attenuation of synaptic strength that attends suppression of a previously learned association. Our studies revealed a novel, non-Hebbian, long-term postsynaptic depression of glutamatergic SPN synapses induced by interneuronal nitric oxide (NO) signaling (NO-LTD) that was preferentially engaged at quiescent synapses. This form of plasticity was gated by local Ca2+ influx through CaV1.3 Ca2+ channels and stimulation of phosphodiesterase 1 (PDE1), which degraded cyclic guanosine monophosphate (cGMP) and blunted NO signaling. Consistent with this model, mice harboring a gain-of-function mutation in the gene coding for the pore-forming subunit of CaV1.3 channels had elevated depolarization-induced dendritic Ca2+ entry and impaired NO-LTD. Extracellular uncaging of glutamate and intracellular uncaging of cGMP suggested that this Ca2+-dependent regulation of PDE1 activity allowed for local regulation of dendritic NO signaling. This inference was supported by simulation of SPN dendritic integration, which revealed that dendritic spikes engaged PDE1 in a branch-specific manner. In a mouse model of Parkinson's disease (PD), NO-LTD was absent not because of a postsynaptic deficit in NO signaling machinery, but rather due to impaired interneuronal NO release. Re-balancing intrastriatal neuromodulatory signaling in the PD model restored NO release and NO-LTD. Taken together, these studies provide novel insights into the mechanisms governing NO-LTD in SPN and its role in psychomotor disorders, like PD.

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Connectomic Analysis of Mitochondria in the Central Brain of Drosophila
Mitochondria are an integral part of the metabolism of a neuron. EM images of fly brain volumes, taken for connectomics, contain mitochondria as well as the cells and synapses that have already been reported. Here, from the Drosophila hemibrain dataset, we extract, classify, and measure approximately 6 million mitochondria among roughly 21 thousand neurons of more than 5500 cell types. Each mitochondrion is classified by its appearance - dark and dense, light and sparse, or intermediate - and the location, orientation, and size (in voxels) are annotated. These mitochondria are added to our publicly available data portal, and each synapse is linked to its closest mitochondrion. Using this data, we show quantitative evidence that mitochodrial trafficing extends to the smallest dimensions in neurons. The most basic characteristics of mitochondria - volume, distance from synapses, and color - vary considerably between cell types, and between neurons with different neurotransmitters. We find that polyadic synapses with more post-synaptic densities (PSDs) have closer and larger mitochondria on the pre-synaptic side, but smaller and more distant mitochondria on the PSD side. We note that this relationship breaks down for synapses with only one PSD, suggesting a different role for such synapses.

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A Drosophila model for mechanistic investigation of tau protein spread
Brain protein aggregates are a hallmark of neurodegenerative disease. Previous work indicates that specific protein components of these aggregates are toxic, including tau in Alzheimers disease and related tauopathies. Increasing evidence also indicates that these toxic proteins traffic between cells in a prion-like fashion, thereby spreading pathology from one brain region to another. However, the mechanisms involved in trafficking are poorly understood. We therefore developed a transgenic Drosophila model to facilitate rapid evaluation of candidate tau trafficking modifiers. Our model uses the bipartite Q system to drive co-expression of tau and GFP in the fly eye. We find age-dependent tau spread into the brain, represented by detection of tau, but not GFP in the brain. We also found that tau trafficking was attenuated upon inhibition of the endocytic factor dynamin or the kinase glycogen synthase kinase-3{beta} (GSK-3{beta}). Further work revealed that dynamin promotes tau uptake in recipient tissues, whereas GSK-3{beta} appears to promote tau spread via direct phosphorylation of tau. Our robust and flexible system will promote the identification of tau trafficking components involved in the pathogenesis of neurodegenerative diseases.

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Adenosine deficiency facilitates CA1 synaptic hyperexcitability in the presymptomatic phase of a knock in mouse model of Alzheimer's disease.
The disease's trajectory of Alzheimer's disease (AD) is associated with and worsened by hippocampal hyperexcitability. Here we show that during the asymptomatic stage in a knock in mouse model of Alzheimer's disease (APPNL-G-F/NL-G-F; APPKI), hippocampal hyperactivity occurs at the synaptic compartment, propagates to the soma and is manifesting at low frequencies of stimulation. We show that this aberrant excitability is associated with a deficient adenosine tone, an inhibitory neuromodulator, driven by reduced levels of CD39/73 enzymes, responsible for the extracellular ATP-to-adenosine conversion. Both pharmacologic (adenosine kinase inhibitor) and non-pharmacologic (ketogenic diet) restorations of the adenosine tone successfully normalize hippocampal neuronal activity. Our results demonstrated that neuronal hyperexcitability during the asymptomatic stage of a KI model of Alzheimer's disease originated at the synaptic compartment and is associated with adenosine deficient tone. These results extend our comprehension of the hippocampal vulnerability associated with the asymptomatic stage of Alzheimer's disease.

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Prefrontal encoding of an internal model for emotional inference
A key function of brain systems mediating emotion is to learn to anticipate unpleasant experiences based on predictive sensory cues in the environment. While organisms readily associate sensory stimuli with aversive outcomes, higher-order forms of emotional learning and memory require inference to extrapolate the circumstances surrounding directly experienced aversive events to other indirectly related contexts and sensory patterns which weren't a part of the original experience. To achieve this type of learning requires internal models of emotion which flexibly track directly experienced and inferred aversive associations. While the brain mechanisms of simple forms of aversive learning have been well studied in areas such as the amygdala, whether and how the brain represents internal models of emotionally relevant associations is not known. Here we report that neurons in the rodent dorsomedial prefrontal cortex (dmPFC) encode an internal model of emotion by linking sensory stimuli in the environment with aversive events, whether they were directly or indirectly associated with that experience. These representations are flexible, and updating the behavioral significance of individual features of the association selectively modifies corresponding dmPFC representations. While dmPFC population activity encodes all salient associations, dmPFC neurons projecting to the amygdala specifically represent and are required to express inferred associations. Together, these findings reveal how internal models of emotion are encoded in dmPFC to regulate subcortical systems for recall of inferred emotional memories.

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Imaging the large-scale and cellular cortical response to focal traumatic brain injury in mouse neocortex
Traumatic brain injury (TBI) affects neural function at the local injury site and also at distant, connected brain areas. However, the real-time neural dynamics in response to injury and subsequent effects on sensory processing and behavior are not fully resolved, especially across a range of spatial scales. We used in vivo calcium imaging in awake, head-restrained male and female mice to measure large-scale and cellular resolution neuronal activation, respectively, in response to a mild TBI induced by focal controlled cortical impact (CCI) injury of the motor cortex (M1). Widefield imaging revealed an immediate CCI-induced activation at the injury site, followed by a massive slow wave of calcium signal activation that traveled across the majority of the dorsal cortex within approximately 30 s. Correspondingly, two-photon calcium imaging in primary somatosensory cortex (S1) found strong activation of neuropil and neuronal populations during the CCI-induced traveling wave. A depression of calcium signals followed the wave, during which we observed atypical activity of a sparse population of S1 neurons. Longitudinal imaging in the hours and days after CCI revealed increases in the area of whisker-evoked sensory maps at early time points, in parallel to decreases in cortical functional connectivity and behavioral measures. Neural and behavioral changes mostly recovered over hours to days in our mild-TBI model, with a more lasting decrease in the number of active S1 neurons. Our results provide novel spatial and temporal views of neural adaptations that occur at cortical sites remote to a focal brain injury.

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Neural circuit basis of adolescent THC-induced potentiation of opioid responses in adult mice
Use of one drug of abuse typically influences the behavioral response to other drugs, either administered at the same time or a subsequent time point. The nature of the drugs being used, as well as the timing and dosing, also influence how these drugs interact. Here, we tested the effects of adolescent THC exposure on the development of morphine-induced behavioral adaptations following repeated morphine exposure during adulthood. We found that adolescent THC administration impacted morphine-induced behaviors across several dimensions, including potentiating reward and paradoxically impairing the development of morphine reward. We then mapped the whole-brain response to a reinstatement dose of morphine, finding that adolescent THC administration led to increased activity in the basal ganglia and increased functional connectivity between frontal cortical regions and the ventral tegmental area. Last, we show using rabies virus-based circuit mapping that adolescent THC exposure triggers a long-lasting elevation in connectivity from the frontal cortex regions onto ventral tegmental dopamine cells that has the potential to influence dopaminergic response to morphine administration during adulthood. Our study adds to the rich literature on the interaction between drugs of abuse and provides potential circuit substates by which adolescent THC exposure influences responses to morphine later in life.

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Accelerated spike-triggered non-negative matrix factorization reveals coordinated ganglion cell subunit mosaics in the primate retina
A standard circuit motif in sensory systems is the pooling of sensory information from an upstream neuronal layer. A downstream neuron thereby collects signals across different locations in stimulus space, which together compose the neuron's receptive field. In addition, nonlinear transformations in the signal transfer between the layers give rise to functional subunits inside the receptive field. For ganglion cells in the vertebrate retina, for example, receptive field subunits are thought to correspond to presynaptic bipolar cells. Identifying the number and locations of subunits from the stimulus-response relationship of a recorded ganglion cell has been an ongoing challenge in order to characterize the retina's functional circuitry and to build computational models that capture nonlinear signal pooling. Here we present a novel version of spike-triggered non-negative matrix factorization (STNMF), which can extract localized subunits in ganglion-cell receptive fields from recorded spiking responses under spatiotemporal white-noise stimulation. The method provides a more than 100-fold speed increase compared to a previous implementation, which can be harnessed for systematic screening of hyperparameters, such as sparsity regularization. We demonstrate the power and flexibility of this approach by analyzing populations of ganglion cells from salamander and primate retina. We find that subunits of midget as well as parasol ganglion cells in the marmoset retina form separate mosaics that tile visual space. Moreover, subunit mosaics show alignment with each other for ON and OFF midget as well as for ON and OFF parasol cells, indicating a spatial coordination of ON and OFF signals at the bipolar-cell level. Thus, STNMF can reveal organizational principles of signal transmission between successive neural layers, which are not easily accessible by other means.

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Synaptic architecture of a memory engram in the mouse hippocampus
Memory engrams are formed through experience-dependent remodeling of neural circuits, but their detailed architectures have remained unresolved. Using 3D electron microscopy, we performed nanoscale reconstructions of the hippocampal CA3-CA1 pathway following chemogenetic labeling of cellular ensembles with a remote history of correlated excitation during associative learning. Projection neurons involved in memory acquisition expanded their connectomes via multi-synaptic boutons without altering the numbers and spatial arrangements of individual axonal terminals and dendritic spines. This expansion was driven by presynaptic activity elicited by specific negative valence stimuli, regardless of the co-activation state of postsynaptic partners. The rewiring of initial ensembles representing an engram coincided with local, input-specific changes in the shapes and organelle composition of glutamatergic synapses, reflecting their weights and potential for further modifications. Our findings challenge the view that the connectivity among neuronal substrates of memory traces is governed by Hebbian mechanisms, and offer a structural basis for representational drifts.

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Theta oscillons in behaving rats
Recently discovered constituents of the brain waves--the oscillons--provide high-resolution representation of the extracellular field dynamics. Here we study the most robust, highest-amplitude oscillons that manifest in actively behaving rats and generally correspond to the traditional theta-waves. We show that the resemblances between theta-oscillons and the conventional theta-waves apply to the ballpark characteristics--mean frequencies, amplitudes, and bandwidths. In addition, both hippocampal and cortical oscillons exhibit a number of intricate, behavior-attuned, transient properties that suggest a new vantage point for understanding the theta-rhythms' structure, origins and functions. We demonstrate that oscillons are frequency-modulated waves, with speed-controlled parameters, embedded into a noise background. We also use a basic model of neuronal synchronization to contextualize and to interpret the observed phenomena. In particular, we argue that the synchronicity level in physiological networks is fairly weak and modulated by the animal's locomotion.

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Scale-free dynamics of cerebrospinal fluid regions is associated with Alzheimer's disease-related pathology
Cerebrospinal Fluid (CSF) clearance is one of the central mechanisms for removal of amyloid-{beta} (A{beta}) and tau proteins from the central nervous system that are closely linked to Alzheimer's Disease (AD) pathology. Conventional functional imaging studies in AD have primarily focused on activities in the brain while ignoring macroscopic cerebrospinal fluid (CSF) activities. In the current study, we utilized a public dataset from the Alzheimer's Disease Neuroimaging Initiative. Our analysis spanned both brain and cerebrospinal fluid (CSF) areas. We compared the scale-free dynamics in fMRI signals across three groups: cognitively normal individuals (CN), people with Alzheimer's Disease (AD), and those with mild cognitive impairments (MCI). Scale-free dynamics are patterns of brain activity that remain consistent across different time scales. Our comparison focused on the Hurst exponent (H), a measure derived from detrended fluctuation analysis (DFA), to characterize these dynamics. This comparison revealed clusters in the fourth ventricle and subarachnoid space (medioventral channel along the spinal axis). In these CSF-filled structures, H was significantly higher in AD group comparing to CN. Moreover, H in these two clusters correlated with AD pathological biomarkers including CSF A{beta} and tau in the AD group. These findings suggested scale-free properties of macroscopic CSF flow as a potential imaging biomarker for AD. This biomarker can be readily acquired from common resting-state fMRI scans and therefore may be valuable for AD diagnosis.

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Progressive multi-stage extrapolation of predictable motion in human visual cortex
Neural processing of sensory information takes time. Consequently, to estimate the current state of the world, the brain must rely on predictive processes - for example, extrapolating the motion of a ball to determine its probable present position. Mounting evidence suggests that extrapolation occurs during early (retinal) processing, however it remains unclear whether extrapolation continues during later-stage (cortical) processing. Moreover, we currently lack a spatially precise characterisation of extrapolation effects in the human brain, with most studies relying on invasive neurophysiological techniques in animals. Here, we address these issues by demonstrating how precise probabilistic maps can be constructed from human EEG recordings. Participants (N = 18) viewed a stimulus moving along a circular trajectory while EEG was recorded. Using LDA classification, we extracted maps of stimulus location over time and found evidence of a widespread temporal shift occurring across distinct processing stages. This accelerated emergence of position representations indicates progressive extrapolation occurring at multiple stages of processing, with representations across the hierarchy shifted closer to real-time. We further show evidence of representational overshoot during early-stage processing following unexpected changes to an object's trajectory, and demonstrate that the observed dynamics can emerge spontaneously in a simulated neural network via spike-timing-dependent plasticity.

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EEG Analyses of visual cue effects on executed movements
Background. In electroencephalographic (EEG) or electrocorticographic (ECoG) experiments, visual cues are commonly used for timing synchronization but may inadvertently induce neural activity and cognitive processing, posing challenges when decoding self-initiated tasks. New Method. To address this concern, we introduced four new visual cues (Fade, Rotation, Reference, and Star) and investigated their impact on brain signals. Our objective was to identify a cue that minimizes its influence on brain activity, facilitating cue-effect free classifier training for asynchronous applications, particularly aiding individuals with severe paralysis. Results. 22 able-bodied, right-handed participants aged 18-30 performed hand movements upon presentation of the visual cues. Analysis of time-variability between movement onset and cue-aligned data, grand average MRCPs, and classification outcomes revealed significant differences among cues. Rotation and Reference cue exhibited favorable results in minimizing temporal variability, maintaining MRCP patterns, and achieving comparable accuracy to self-paced signals in classification. Comparison with Existing Methods. Our study contrasts with traditional cue-based paradigms by introducing novel visual cues designed to mitigate unintended neural activity. We demonstrate the effectiveness of Rotation and Reference cue in eliciting consistent and accurate MRCPs during motor tasks, surpassing previous methods in achieving precise timing and high discriminability for classifier training. Conclusions. Precision in cue timing is crucial for training classifiers, where both Rotation and Reference cue demonstrate minimal variability and high discriminability, highlighting their potential for accurate classifications in online scenarios. These findings offer promising avenues for refining brain-computer interface systems, particularly for individuals with motor impairments, by enabling more reliable and intuitive control mechanisms.

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Aging distorts the representation of emotions by amplifying prefrontal variability
Effectively navigating a complex social life requires stable representations of emotions, thereby necessitating an optimal computation of uncertainty around it. Here, we focus on a regime where this optimal estimation of uncertainty is disrupted, focusing on healthy aging and its consequences on emotional experiences. Our findings indicate that older adults represent an increased uncertainty around emotions, leading to variable emotional response profiles across a range of emotional tasks. Furthermore, the boundaries between emotional categories become less distinct with age, causing substantial overlap between adjacent emotions compared to younger individuals. By employing a Bayesian learning model, we revealed that these age-related effects emerge from an increased predictive uncertainty of emotional valence during hierarchical inference. Crucially, model outputs were consistent with neural signatures in the lateral orbitofrontal cortex across young and older brains while watching an emotionally intense movie. Specifically, we found that older adults exhibit heightened neural variability in this region with distorted latent dynamics, contributing to their overall variable emotional experience. Taken together, we aimed to integrate disparate evidence in age-associated emotional changes under a unified framework of misestimation of uncertainty.

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Mating proximity blinds threat perception.
Romantic engagement can bias sensory perception. This 'love blindness' reflects a common behavioral principle across organisms: favoring pursuit of a coveted reward over potential risks. In the case of animal courtship, such sensory biases may support reproductive success but can also expose individuals to danger, such as predation. How do neural networks balance the trade-off between risk and reward? Here, we discover a dopamine-governed filter mechanism in male Drosophila that reduces threat perception as courtship progresses. We show that during early courtship stages, threat-activated visual neurons inhibit central courtship nodes via specific serotonergic neurons. This serotonergic inhibition prompts flies to abort courtship when they see imminent danger. However, as flies advance in the courtship process, the dopaminergic filter system reduces visual threat responses, shifting the balance from survival to mating. By recording neural activity from males as they approach mating, we demonstrate that progress in courtship is registered as dopaminergic activity levels ramping up. This dopamine signaling inhibits the visual threat detection pathway via Dop2R receptors, allowing male flies to focus on courtship when they are close to copulation. Thus, dopamine signaling biases sensory perception based on perceived goal proximity, in order to prioritize between competing behaviors.

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Relationship between therapeutic activity and preferential targeting of toxic soluble aggregates by amyloid-beta-directed antibodies
Amyloid-beta (Abeta)-directed antibodies tested clinically for therapeutic activity against Alzheimer disease (AD) have shown varying degrees of efficacy. Although all of these antibodies target the Abeta peptide, their binding profile to different molecular species of Abeta (monomers, oligomers, fibrils) differs and may underly the observed variability in clinical outcomes. Surface plasmon resonance (SPR) was used to conduct a side-by-side comparison of the binding of various Abeta-directed antibodies to monomers and soluble low and high molecular weight Abeta oligomers from AD brains. Immunohistochemistry was performed to assess reactivity with Abeta fibrils in plaque. Non-selective, pan-Abeta reactive antibodies such as crenezumab and gantenerumab, which have failed to produce a clinical benefit, bound all forms of Abeta tested. In a competition assay aimed at replicating the in vivo abundance of monomers in the blood and the central nervous system (CNS), these antibodies lost the ability to bind toxic AD brain oligomers when exposed to even low concentrations of monomers. In contrast, aggregate-selective antibodies such as aducanumab, lecanemab and donanemab, which have reported a clinical benefit, showed reduced monomer binding and a greater ability to withstand monomer competition suggesting a relationship between therapeutic activity and preferential targeting of toxic soluble aggregates. Of the antibodies in earlier stages of clinical testing, ACU193 and PMN310 displayed the greatest ability to retain binding to toxic AD brain oligomers when faced with high monomer concentrations while PRX h2731 was highly susceptible to monomer competition. Plaque binding was observed with all aggregate-reactive antibodies with the exception of PMN310 which was strictly selective for soluble oligomers. While a correlation has been observed between antibody plaque binding/clearance and reported increases in the risk of ARIA, plaque binding did not translate into clinical benefit in the case of gantenerumab. Overall, these results suggest that selectivity for soluble toxic Abeta oligomers may be a driver of clinical efficacy, with a potential reduced risk of ARIA if engagement with plaque is minimized.

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