bioRxiv Subject Collection: Neuroscience's Journal

Deep Neural Networks to Register and Annotate the Cells of the C. elegans Nervous System
Aligning and annotating the heterogeneous cell types that make up complex cellular tissues remains a major challenge in the analysis of biomedical imaging data. Here, we present a series of deep neural networks that allow for automatic non-rigid registration and cell identification in the context of the nervous system of freely-moving C. elegans. A semi-supervised learning approach was used to train a C. elegans registration network (BrainAlignNet) that aligns pairs of images of the bending C. elegans head with single pixel-level accuracy. When incorporated into an image analysis pipeline, this network can link neuronal identities over time with 99.6% accuracy. A separate network (AutoCellLabeler) was trained to annotate >100 neuronal cell types in the C. elegans head based on multi-spectral fluorescence of genetic markers. This network labels >100 different cell types per animal with 98% accuracy, exceeding individual human labeler performance by aggregating knowledge across manually labeled datasets. Finally, we trained a third network (CellDiscoveryNet) to perform unsupervised discovery and labeling of >100 cell types in the C. elegans nervous system by analyzing unlabeled multi-spectral imaging data from many animals. The performance of CellDiscoveryNet matched that of trained human labelers. These tools will be useful for a wide range of applications in C. elegans research and should be straightforward to generalize to many other applications requiring alignment and annotation of dense heterogeneous cell types in complex tissues.

Inhibition of nitric oxide synthase transforms carotid occlusion-mediated benign oligemia into de novo large cerebral infarction
It remains unclear why unilateral proximal carotid artery occlusion (UCAO) causes benign oligemia, without progressing to cerebral infarction, in mice, yet leads to a wide variety of outcomes (ranging from asymptomatic to death) in humans. We hypothesized that inhibition of NOS both transforms UCAO-mediated oligemia into full infarction and expands pre-existing infarction. In support, intraperitoneal administration of N{omega}-nitro-L-arginine methyl ester (L-NAME) followed by UCAO induced large-arterial infarction in mice, unlike UCAO alone. Six-hour laser-speckle-contrast imaging detected spreading ischemia in mice with infarction as assessed at 24h. In agreement with vasoconstriction/microthrombus formation shown by intravital microscopy, the NO-donor, molsidomine and the endothelial-NOS-activating antiplatelet, cilostazol, attenuated or prevented progression to infarction. Moreover, UCAO without L-NAME caused infarction in mice with hyperglycemia and hyperlipidemia, which, in turn, were associated with greater symmetric dimethylarginine (SDMA) levels. Further, increased levels of glucose and cholesterol associated with significantly larger infarct volumes in 438 consecutive patients with UCAO-mediated infarction. Lastly, Mendelian randomization identified a causative role of NOS inhibition, particularly in elevated SDMA concentration, in ischemic stroke risk. Therefore, NOS activity is a key factor determining the fate of hypoperfused brain following acute carotid occlusion, where SDMA could be a potential risk predictor.

Multi-Omic Analysis Reveals Lipid Dysregulation Associated with Mitochondrial Dysfunction in Parkinson's Disease Brain
Parkinson's Disease (PD) is an increasingly prevalent condition within the aging population. PD can be attributed to rare genetic mutations, but most cases are sporadic where the gene-environment interactions are unknown/likely contributory. Age related dysregulation of the glycosphingolipid degradation pathway has been implicated in the development of PD, however, our understanding of how brain lipids vary across different regions of the brain, with age and in disease stages, remains limited. In this study we profiled several phospho- and sphingolipid classes in eight distinct regions of the human brain and investigated the association of lipids with a spatio-temporal pathology gradient, utilising PD samples from early, mid, and late stages of the disease. We performed high-precision tissue sampling in conjunction with targeted LC-MS/MS and applied this to post-mortem samples from PD and control subjects. The lipids were analysed for correlations with untargeted proteomics and mitochondrial activity data, in a multi-omics approach. We concluded that the different brain regions demonstrated their own distinct profiles and also found that several lipids were correlated with age. The strongest differences between PD and controls were identified in ganglioside, sphingomyelin and n-hexosylceramides. Sphingomyelin was also found to correlate with several proteins implicated in Parkinson's disease pathways. Mitochondrial activity was correlated with the levels of several lipids in the putamen region. Finally, we identified a gradient corresponding to Braak's disease spread across the brain regions, where the areas closer to the brainstem/substantia nigra showed alterations in PC, LPC and glycosphingolipids, while the cortical regions showed changes in glycosphingolipids, specifically gangliosides, HexCer and Hex2Cer.

Circulating Myeloid-Derived Suppressor Cell load and disease severity are associated to an enhanced oligodendroglial production in a murine model of multiple sclerosis
Background: Multiple sclerosis (MS) is a chronic, inflammatory and demyelinating disease of the central nervous system (CNS) that is highly heterogeneous in terms of disease severity and tissue damage extent. Improving myelin restoration is essential to prevent neurodegeneration and the associated disability in MS patients. However, remyelinating therapies are failing in clinical trials, in part, due to the absence of classifying biomarkers of different endogenous regenerative capacities amongst enrolled patients. We previously reported that circulating monocytic myeloid-derived suppressor cells (M-MDSCs) at the onset of the murine model of MS experimental autoimmune encephalomyelitis (EAE) are associated with milder disease courses and less degree of demyelination and axonal damage in spinal cord lesions, while at peak are indicative of a better symptom recovery. Moreover, M-MDSCs are able to promote in vitro oligodendrocyte precursor cell (OPC) proliferation and differentiation towards mature oligodendrocytes (OLs) through the release of the soluble factor osteopontin. Results: Here, we show a relationship between disease severity and a gradient of OPCs between the rim and the core in mixed active-inactive lesions of MS patients, along with a positive correlation between M-MDSC density and OPC abundance in the same lesions. We also show that EAE disease severity negatively influences the density of total and newly generated OPCs found associated to the demyelinated lesions of the spinal cord at the peak of the disease. In addition, disease severity also impacts the abundance of newly generated OLs originated either during the effector phase or during the early recovery phase. We also demonstrate the positive association between infiltrated M-MDSCs and the abundance of OPCs in the periplaque of demyelinating lesions at the peak of EAE. Interestingly, circulating M-MDSCs at EAE onset and peak of the disease are directly associated to a higher density of newly generated OLs in the plaque and periplaque, respectively. Conclusion: Disease severity clearly impacts oligodendrocyte generation during a neuroinflammatory insult like EAE. Our results set the basis for further studies on M-MDSCs as a promising new biomarker that identify a CNS prone to the generation of new OLs that may contribute to restore myelin.

ARGX-119, a therapeutic agonist antibody targeting MuSK
ARGX-119 is a novel, humanized, agonist monoclonal SIMPLE Antibody specific for muscle-specific kinase (MuSK) that is being developed for treatment of patients with neuromuscular diseases. ARGX-119 is the first monoclonal antibody (mAb) that binds with high affinity to the Frizzled-like domain of human, non-human primate, rat and mouse MuSK, without off-target binding, making it suitable for clinical development. Within the Fc-region, ARGX-119 harbors L234A, L235A mutations to diminish potential immune-activating effector functions. Its mode-of-action is to activate MuSK without interfering with its natural ligand neural Agrin, and cluster acetylcholine receptors (AChRs) in a dose-dependent manner, thereby stabilizing neuromuscular function. In a mouse model for DOK7 congenital myasthenia (CM), ARGX-119 prevented early postnatal lethality and reversed disease relapse by restoring neuromuscular function and reducing muscle weakness and fatigability in a dose-dependent manner. Pharmacokinetic (PK) studies in non-human primates, rats and mice revealed non-linear PK behavior of ARGX-119, indicative of target-mediated-drug disposition (TMDD) and in vivo target engagement. Instability of neuromuscular synapses contributes to symptoms in many neuromuscular diseases for example congenital myasthenia (CM), amyotrophic lateral sclerosis (ALS) and spinal muscular atrophy (SMA). ARGX-119 is a novel, first-in-class MuSK agonist mAb in clinical development. Based on this proof-of-concept study, it has the potential to alleviate neuromuscular diseases hallmarked by impaired neuromuscular synaptic function.

Freestanding rGO electrodes with tunable porous structures for improved neural recording
Penetrating recording neural electrodes prepared from materials with miniaturized geometrical size could improve the longevity of implants by reducing the chronic inflammatory response. Reduced graphene oxide (rGO) microfibers with tunable porous structures have a large electrochemical surface area (ESA)/ geometrical surface area (GSA) ratio that has been reported to possess low impedance and high charge injection capacity (CIC), yet the control of the porous structure remains to be fully investigated. In this study, we introduce wet-spun rGO electrodes with pores tuned by sucrose concentrations in the coagulation bath. The electrochemical properties of thermally reduced rGO were optimized by adjusting the ratio of rGO to sucrose, resulting in significantly lower impedance, higher CIC, and higher charge storage capacity (CSC) than platinum microwires. Tensile and insertion tests confirmed that optimized electrodes had sufficient strength to ensure a 100% insertion success rate with low angle shift, thus allowing precise implantation without the need for additional mechanical enhancement. Acute in-vivo recordings from the auditory cortex found low impedance benefits from the recorded amplitude of spikes, leading to an increase in the signal-to-noise ratio (SNR). Ex-vivo recordings from hippocampal brain slices demonstrate that it is possible to record and/or stimulate with rGO electrodes with good fidelity compared with conventional electrodes.

The interpretation attributed to observed gaze shifts affects their social-cueing effect
In an environment busy with abundant stimulation, individuals must rely on attentional cues to select the most relevant targets. As social creatures, a crucial strategy involves monitoring where others are focusing their attention and following them, assuming that locations attended by others are more likely to yield benefits than other locations. Given that gaze shifts represent a visible shift in attention, mirroring the gaze shifts of others can serve as an effective, social-attentional strategy. Indeed, research demonstrates that observing others redirect their gaze results in a reflexive shift of attention, reflected by improved perceptual performance for objects located at the gazed-at positions. This phenomenon is known as the gaze cueing effect (GCE). However, gaze shifts may not always align with the direction of attention. Individuals often avert their gaze while they are engaged in demanding cognitive tasks. Such gaze shifts signify internal focus rather than shifting attention outward. Here we hypothesize that the response to a gaze-shift cue is not reflexive but is contingent upon social context. In two pre-registered experiments, participants viewed videos of gaze shifts and engaged in a perceptual task, with one group primed to perceive the gaze shifts as reflecting cognitive processing rather than overt attentional shifts. Results indicated that GCE was suppressed in this group, suggesting that GCE is influenced by contextual cues framing the nature of the gaze shifts. These findings suggest that social attention is flexible and depends on the specific interpretation of the social context.

Precuneus activity during retrieval is positively associated with amyloid burden in cognitively normal older APOE4 carriers
The precuneus is an early site of amyloid-beta accumulation. Previous cross-sectional studies reported increased precuneus fMRI activity in older adults with mild cognitive deficits or elevated amyloid-beta. However, longitudinal studies in early Alzheimer's disease (AD) risk stages are lacking and the interaction with Apolipoprotein-E (APOE) genotype is unclear. In the PREVENT-AD cohort, we assessed how precuneus activity during successful memory retrieval at baseline and over time relates to future amyloid-beta and tau burden and to change in memory performance. We further studied the moderation by APOE4 genotype. We included 165 older adults (age: 62.8 years; 113 female; 66 APOE4 carriers) who were cognitively normal at baseline and had a family history of AD. All participants performed task-fMRI at baseline and underwent [18F]-flortaucipir PET and [18F]-NAV4694 amyloid PET on average 5 years later. We found that higher baseline activity and greater longitudinal change in activity in precuneus were associated with higher subsequent amyloid-beta in APOE4 carriers but not non-carriers. There were no effects of precuneus activity on tau burden. Finally, APOE4 non-carriers with low baseline activity in the precuneus exhibited better longitudinal performance in an independent memory test compared to APOE4 non-carriers with high baseline activity and APOE4 carriers. Our findings suggest that higher task-related precuneus activity at baseline and over time are associated with subsequent amyloid-beta burden in cognitively normal APOE4 carriers. Our results further indicate that the absence of hyperactivation and the absence of the APOE4 allele is related with the best future cognitive outcome in cognitively normal older adults at risk for AD.

TREM2 expression level is critical for microglial state, metabolic capacity and efficacy of TREM2 agonism
Triggering receptor expressed on myeloid cells 2 (TREM2) is a central regulator of microglial activity and sequence variants are major risk factors for late onset Alzheimer's disease (LOAD). To better understand the molecular and functional changes associated with TREM2 signalling, we generated a TREM2 reporter mouse model and observed a gradual upregulation of reporter expression with increasing plaque proximity. Isolated microglia were sorted based on reporter expression and their transcriptomic profiles acquired in both wildtype and APP transgenic animals, allowing us to disentangle TREM2 versus pathology-specific effects. Bulk RNA-sequencing highlighted TREM2 level-dependent changes in major immunometabolic pathways, with enrichment of genes in oxidative phosphorylation and cholesterol metabolism in microglia with increased TREM2 expression. To confirm these findings, we next analysed uptake of fluorodeoxyglucose (FDG) and examined metabolomic and lipidomic profiles. Again, independent of A{beta} pathology, TREM2 expression correlated with uptake of FDG as well as increased cellular redox, energetics, and cholesterol homeostasis. Finally, we performed chronic treatment with a brain penetrant TREM2 agonist and identified a window of TREM2 expression where microglia are most responsive. Thus, our data provide novel insights into TREM2-mediated regulation of microglial metabolic function and informs current efforts to bring TREM2 agonists into clinical application.

The Origin of Cognitive Modules for Face Processing: A Computational Evolutionary Perspective
Despite extensive research, understanding how cognitive modules emerge remains elusive due to the complex interplay of genetic, developmental, and environmental factors. Computational modeling, however, provides a means of exploring their origins by directly manipulating these factors. Here we aimed to investigate the emergence of cognitive modules by developing the Dual-Task Meta-Learning Partitioned (DAMP) model, whose plastic architecture facilitates automatic structure optimization through a genetic algorithm that emulates natural selection by iteratively selecting for efficient learning fitness. We found that a specialized module for face identification robustly emerged in the DAMP model. Critically, the emergence of the face module was not influenced by the demands of cognitive tasks (identification versus categorization) or the type of stimuli (faces versus non-face objects). Instead, it was determined by the structural constraint of sparse connectivity within the network, suggesting that the face module may arise as an adaptation strategy to challenges posed by sparse connections in neural networks, rather than being an information processor required by certain stimuli or tasks. These findings provide a new evolutionary perspective on the formation of cognitive modules in the human brain, highlighting the pivotal role of the structural properties of neural networks in shaping their cognitive functionality.

CB-1 receptor agonist drastically changes oscillatory activity, defining active sleep
Brain oscillations in different behavioral states are essential for cognition, and oscillopathies contribute to cognitive dysfunction in neuro-psychiatric diseases. Cannabis-1 receptor (CB1-R) activation was reported to suppress theta and fast gamma activities in rats during waking exploration, and here, we show that cannabis fundamentally alters network activity during sleep, as well. Prominent theta rhythm is present in rapid eye movement sleep (REMS), whereas fast oscillations appear as regular sequences of sleep spindles during intermediate sleep (IS) - both implicated in dreaming and memory consolidation. The CB1-R agonist disrupted these mechanisms, restructuring IS-REMS episodes; IS lengthened 6-fold and intruded REMS, where on-going theta was drastically reduced. The spindle architecture was also affected; its amplitude increased, and its peak frequency down-shifted into the theta range. Cannabis is known to induce psychotic-like conditions and cognitive deficits; thus, our results may help in understanding the dual effect of cannabis on cognitive states and the role of network oscillations in psychiatric pathology.

How do we imagine a speech? A triple network model for situationally simulated inner speech
Inner speech is a silent verbal experience and plays central roles in human consciousness and cognition. Despite impressive studies over the past decades, the neural mechanisms of inner speech remain largely unknown. In this study, we adopted an ecological paradigm called situationally simulated inner speech. Unlike mere imaging speech of words, situationally simulated inner speech involves the dynamic integration of contextual background, episodic and semantic memories, and external events into a coherent structure. We conducted dynamic activation and network analyses on fMRI data, where participants were instructed to engage in inner speech prompted by cue words across 10 different contextual backgrounds. Our seed-based co-activation pattern analyses revealed dynamic involvement of the language network, sensorimotor network, and default mode network in situationally simulated inner speech. Additionally, frame-wise dynamic conditional correlation analysis uncovered four temporal-reoccurring states with distinct functional connectivity patterns among these networks. We proposed a triple network model for deliberate inner speech, including language network for a truncated form of overt speech, sensorimotor network for perceptual simulation and monitoring, and default model network for integration and 'sense-making' processing.

Correlated spontaneous activity sets up multi-sensory integration in the developing higher-order cortex
To perceive and navigate complex sensory environments, animals combine sensory information from multiple modalities in specialized brain circuits. Known as multisensory integration, this process typically depends on the existence of co-aligned topographic connections from several sensory areas to downstream circuits exhibiting multimodal representations. How such topographically co-aligned connectivity necessary for multisensory integration gets set up in early stages of development is still unknown. Inspired by the role of spontaneous activity in refining topographic connectivity between early sensory circuits, here we investigated the potential of such spontaneous activity to also guide the co-alignment of multiple sensory modalities in RL, a higher-order associative cortical area rostro-lateral to V1. Analyzing spontaneous activity simultaneously recorded in primary visual and somatosensory cortex and area RL at different developmental ages before sensory experience, we identify candidate features of this activity to guide the emergence of co-aligned topographic multisensory projections with somatosensory leading the visual projection. We confirm this hypothesis using a computational model of activity-dependent circuit refinement, and show that the correlation of spontaneous activity between the visual and somatosensory primary cortex can establish an optimal fraction of multisensory neurons in RL for stimulus decoding. Our model provides an exciting new computational perspective of the role of spontaneous activity in the emergence of topographically co-aligned multimodal sensory representations in downstream circuits, specialized for the processing of rich sensory environments.

ASO-enhancement of TARDBP exitron splicing mitigates TDP-43 proteinopathies
Amyotrophic lateral sclerosis and frontotemporal lobar degeneration are fatal neurodegenerative diseases characterized by pathological aggregation and nuclear functional loss of TDP-431,2. Current therapies inadequately address this core pathology3,4, necessitating innovative approaches that target aggregation while preserving TDP-43's essential functions. Here we demonstrate that enhancing the splicing of the TARDBP exitron--a cryptic intron encoding the aggregation-prone intrinsically disordered region (IDR) of TDP-435,6--effectively mitigates TDP-43 pathology. This exitron splicing event, directly regulated by nuclear TDP-437-9, suppresses the expression of IDR-containing TDP-43 isoforms and generates IDR-spliced-out TDP-43 isoforms7,9,10 (which we term "IDRsTDP"). Our findings reveal that IDRsTDP, known to heterodimerize with full-length TDP-4310, inhibits TDP-43 aggregation by suppressing IDR-mediated clustering and enhances TDP-43 clearance via chaperone-mediated autophagy. In disease states, however, impaired nuclear TDP-43 function disrupts exitron splicing, leading to increased levels of IDR-containing TDP-439,11 and reduced levels of IDRsTDP, exacerbating aggregation and nuclear dysfunction6,12-17. By identifying HNRNPA1 and HNRNPC as key repressors of TARDBP exitron splicing, we designed antisense oligonucleotides (ASOs) to block their binding and restore splicing. These ASOs suppressed TDP-43 pathology and neurodegeneration in both neuronal cell models with impaired nuclear transport and a mouse model of proteasome dysfunction-induced TDP-43 proteinopathy. Our strategy, by rescuing the impaired autoregulatory pathway, inhibits the pathological cycle of TDP-43 aggregation and nuclear dysfunction, offering a promising avenue for treating these currently intractable neurodegenerative diseases.

Binocular processing facilitates escape behavior through multiple pathways to the superior colliculus
The superior colliculus (SC) is the main brain region regulating innate defensive behaviors to visual threat. Yet, how the SC integrates binocular visual information and to what extent binocular vision drives defensive behaviors is unknown. Here, we show that binocular vision facilitates visually-evoked escape behavior. Furthermore, we find that SC neurons respond to binocular visual input with diverse synaptic and spiking responses, and summate visual inputs largely sublinearly. Using pathway-specific optogenetic silencing we find that contralateral and ipsilateral visual information is carried to binocular SC neurons through retinal, interhemispheric and corticotectal pathways. These pathways carry binocular visual input to the SC in a layer-specific manner, with superficial layers receiving visual information through retinal input, whereas intermediate and deep layers rely on interhemispheric and corticotectal pathways. Together, our data shed light on the cellular and circuit mechanisms underlying binocular visual processing in the SC and its role in escape behavior.

Dynamic integration of cortical activity in the deep layer of the anterolateral superior colliculus
The superior colliculus (SC) receives inputs from various brain regions in a layer- and radial location-specific manner, but whether the SC exhibits location-specific dynamics remains unclear. To address this issue, we recorded the spiking activity of single SC neurons while photoactivating cortical areas in awake head-fixed Thy1-ChR2 rats. We classified 309 neurons that responded significantly into 8 clusters according to the response dynamics. Among them, neurons with monophasic excitatory responses (7-12 ms latency) that returned to baseline within 20 ms were commonly observed in the optic and intermediate gray layers of centromedial and centrolateral SC. In contrast, neurons with complex polyphasic responses were commonly observed in the deep layers of the anterolateral SC. Cross-correlation analysis suggested that the complex pattern could be only partly explained by an internal circuit of the deep gray layer. Our results indicate that medial to centrolateral SC neurons simply relay cortical activity, whereas neurons in the deep layers of the anterolateral SC dynamically integrate inputs from the cortex, SNr, CN, and local circuits. These findings suggest a spatial gradient in SC integration, with a division of labor between simple relay circuits and those integrating complex dynamics.

mRNA stability fine tunes gene expression in the developing cortex to control neurogenesis
RNA expression levels are controlled by the complementary processes of synthesis and degradation. Although mis-regulation of RNA turnover is linked to neurodevelopmental disorders, how it contributes to cortical development is largely unknown. Here, we profile the RNA stability landscape of the cortex across development and demonstrate that control of stability by the CCR4-NOT complex is essential for corticogenesis in vivo. First, we use SLAM-seq to measure RNA half-lives transcriptome-wide across multiple stages of cortical development. We characterize cis-acting features associated with RNA stability and find that RNAs that are upregulated across development tend to be more stable, while downregulated RNAs are less stable. To probe how disruption of RNA turnover impacts cortical development, we assess developmental requirements of CNOT3, a core component of the CCR4-NOT deadenylase complex. Mutations in CNOT3 are associated with human neurodevelopmental disorders, however its role in cortical development is unknown. Conditional knockout of Cnot3 in neural progenitors and their progeny in the developing mouse cortex leads to severe microcephaly due to reduced neuron production and p53-dependent apoptosis. Collectively, our findings demonstrate that fine-tuned control of RNA turnover is crucial for brain development.

White matter tract crossing and bottleneck regions in the fetal brain
There is a growing interest in using diffusion MRI to study the white matter tracts and structural connectivity of the fetal brain. Recent progress in data acquisition and processing suggests that this imaging modality has a unique role in elucidating the normal and abnormal patterns of neurodevelopment in utero. However, there have been no efforts to quantify the prevalence of crossing tracts and bottleneck regions, important issues that have been extensively researched for adult brains. In this work, we determined the brain regions with crossing tracts and bottlenecks between 23 and 36 gestational weeks. We performed probabilistic tractography on 59 fetal brain scans and extracted a set of 51 distinct white tracts, which we grouped into 10 major tract bundle groups. We analyzed the results to determine the patterns of tract crossings and bottlenecks. Our results showed that 20-25% of the white matter voxels included two or three crossing tracts. Bottlenecks were more prevalent. Between 75-80% of the voxels were characterized as bottlenecks, with more than 40% of the voxels involving four or more tracts. The results of this study highlight the challenge of fetal brain tractography and structural connectivity assessment and call for innovative image acquisition and analysis methods to mitigate these problems.

Velocities of Hippocampal Traveling Waves Proportional to Their Coherence Frequency
Cortical traveling waves, characterized by their spatial, temporal, and frequency attributes, offer insights into active regions, timing, frequency, and the direction of activity propagation. Recent evidence suggests that these waves' directionality and spatiotemporal extent encode cognitive processes, yet the encoding mechanism related to their frequency remains unclear. We explore the hypothesis that coherence frequency dictates the velocity of wave propagation. Using nonlinear coherence analysis to compute propagation pathways among four local-field-potential signals collected along the human hippocampus's long axis, we present evidence that the coherence frequency of traveling waves encodes temporal communication aspects. Unlike linear analyses, which may overestimate velocities due to bidirectional flow when considering multiple pair coherences, nonlinear analysis treats pathways as holistic units with affectively unidirectional flow, making it more suitable for calculating wave velocities. Our findings reveal that propagation velocities along the hippocampus at low frequencies (<~35Hz) demonstrate a linear dependency on frequency, with an increased slope at higher frequencies, suggesting different underlying mechanisms. Although observed within the hippocampus, these findings capture a dependency between frequency and velocity of traveling waves which may be applicable to other cortical areas as well.

Modelling alcohol consumption in rodents using two-bottle choice home cage drinking and optional lickometry-based microstructural analysis
Two-bottle choice home cage drinking is one of the most widely used paradigms to study ethanol consumption in rodents. In its simplest form, animals are provided with access to two drinking bottles, one of which contains regular tap water and the other ethanol, for 24 hr/day with daily intake measured via change in bottle weight over the 24 hr period. Consequently, this approach requires no specialized laboratory equipment. While such ease of implementation is likely the greatest contributor to its widespread adoption by preclinical alcohol researchers, the resolution of drinking data acquired using this approach is limited by the number of times the researcher measures bottle weight (e.g., once daily). However, the desire to examine drinking patterns in the context of overall intake, pharmacological interventions, and neuronal manipulations has prompted the development of home cage lickometer systems that can acquire data at the level of individual licks. Although a number of these systems have been developed recently, the open-source system, LIQ HD, has garnered significant attention in the field for its affordability and user friendliness. Although exciting, this system was designed for use in mice. Here, we review appropriate procedures for standard and lickometer-equipped two-bottle choice home cage drinking. We also introduce methods for adapting the LIQ HD system to rats including hardware modifications to accommodate larger cage size and a redesigned 3D printed bottle holder compatible with standard off-the-shelf drinking bottles. Using this approach, researchers can examine daily drinking patterns in addition to levels of intake in many rats in parallel thereby increasing the resolution of acquired data with minimal investment in additional resources. These methods provide researchers with the flexibility to use either standard bottles or a lickometer-equipped apparatus to interrogate the neurobiological mechanisms underlying alcohol drinking depending on their precise experimental needs.

Human iPSC-derived myelinating organoids andgloboid cells to study Krabbe Disease
Krabbe disease (Kd) is a lysosomal storage disorder (LSD) caused by the deficiency of the lysosomal galactosylceramidase (GALC) which cleaves the myelin enriched lipid galactosylceramide (GalCer). Accumulated GalCer is catabolized into the cytotoxic lipid psychosine that causes myelinating cells death and demyelination which recruits microglia/macrophages that fail to digest myelin debris and become globoid cells. Here, to understand the pathological mechanisms of Kd, we used induced pluripotent stem cells (iPSCs) from Kd patients to produce myelinating organoids and microglia. We show that Kd organoids have no obvious defects in neurogenesis, astrogenesis, and oligodendrogenesis but manifest early myelination defects. Specifically, Kd organoids showed shorter but a similar number of myelin internodes than controls at the peak of myelination and a reduced number and shorter internodes at a later time point. Interestingly, myelin is affected in the absence of autophagy and mTOR pathway dysregulation, suggesting lack of lysosomal dysfunction which makes this organoid model a very valuable tool to study the early events that drive demyelination in Kd. Kd iPSC-derived microglia show a marginal rate of globoid cell formation under normal culture conditions that is drastically increased upon GalCer feeding. Under normal culture conditions, Kd microglia show a minor LAMP1 content decrease and a slight increase in the autophagy protein LC3B. Upon GalCer feeding, Kd cells show accumulation of autophagy proteins and strong LAMP1 reduction that at a later time point are reverted showing the compensatory capabilities of globoid cells. Altogether, this supports the value of our cultures as tools to study the mechanisms that drive globoid cell formation and the compensatory mechanism in play to overcome GalCer accumulation in Kd.

Consequences of decoy site repair and feedback regulation on neurotransmission dynamics
Neurons form the fundamental unit of the central nervous system with the human brain containing close to 100 billion neurons. We present a systems-level model of a chemical synapse by which signals from a presynaptic neuron are transmitted to a postsynaptic neuron. In this model, neurotransmitter-filled synaptic vesicles (SVs) dock with a given rate at a fixed number of docking sites in the axon terminal of the presynaptic neuron. Upon the arrival of an action potential (AP), each docked SV has a certain probability to fuse with the presynaptic membrane and release neurotransmitters into the synaptic cleft. After the SV fusion event, the corresponding docking site undergoes repair before becoming available to be reoccupied by an SV. We develop a stochastic model of these coupled processes and derive exact analytical results quantifying the mean and the degree of random fluctuations (i.e., noise) in the levels of docked SVs and released neurotransmitters in response to a train of APs. Our results show that the repair of docking sites exacerbates synaptic depression, i.e., reduces the ability of the chemical synapse to release neurotransmitters in response to an AP. Moreover, repair amplifies statistical fluctuations in neurotransmission for fixed mean neurotransmitter levels. We next consider feedback regulation where the released neurotransmitters affect the rate of SV docking. Counterintuitively, our analysis reveals that for certain physiological parameter spaces, positive feedback loops can reduce noise levels in both the number of docked SVs and neurotransmitters in the cleft.

Non-Negative Connectivity Causes Bow-Tie Architecture in Neural Circuits
Bow-tie or hourglass architecture is commonly found in biological neural networks. Recently, artificial neural networks with bow-tie architecture have been widely used in various machine-learning applications. However, it is unclear how bow-tie architecture in neural circuits can be formed. We address this by training multi-layer neural network models to perform classification tasks. We demonstrate that during network learning and structural changes, non-negative connections amplify error signals and quench neural activity particularly in the hidden layer, resulting in the emergence of the network's bow-tie architecture. We further show that such architecture has low wiring cost, robust to network size, and generalizable to different discrimination tasks. Overall, our work suggests a possible mechanism for the emergence of bow-tie neural architecture and its functional advantages.

A Burst-Dependent Algorithm for Neuromorphic On-Chip Learning of Spiking Neural Networks
The field of neuromorphic engineering addresses the high energy demands of neural networks through brain-inspired hardware for efficient neural network computing. For on-chip learning with spiking neural networks, neuromorphic hardware requires a local learning algorithm able to solve complex tasks. Approaches based on burst-dependent plasticity have been proposed to address this requirement, but their ability to learn complex tasks has remained unproven. Specifically, previous burst-dependent learning was demonstrated on a spiking version of the XOR problem using a network of thousands of neurons. Here, we extend burst-dependent learning, termed 'Burstprop', to address more complex tasks with hundreds of neurons. We evaluate Burstprop on a rate-encoded spiking version of the MNIST dataset, achieving low test classification errors, comparable to those obtained using backpropagation through time on the same architecture. Going further, we develop another burst-dependent algorithm based on the communication of two types of error-encoding events for the communication of positive and negative errors. We find that this new algorithm performs better on the image classification benchmark. We also tested our algorithms under various types of feedback connectivity, establishing that the capabilities of fixed random feedback connectivity is preserved in spiking neural networks. Lastly, we tested the robustness of the algorithm to weight discretization. Together, these results suggest that spiking Burstprop can scale to more complex learning tasks while maintaining efficiency, potentially providing a viable method for learning with neuromorphic hardware.

Uncovering the Neural Correlates of the Urge-to-Blink: A Study Utilising Subjective Urge Ratings and Paradigm Free Mapping
Neuroimaging plays a significant role in understanding the neurophysiology of Tourette syndrome (TS), in particular the main symptom, tics, and the urges associated with them. Premonitory urge is thought to be a negative reinforcer of tic expression in TS. Tic expression during neuroimaging is most often required as an overt marker of increased urge-to-tic, which can lead to considerable head movement, and thus data loss. This study aims to identify the brain regions involved in urge in healthy subjects using multi-echo functional MRI and a timing-free approach to localise the BOLD response associated with the urge-to-act without information of when these events occur. Blink suppression is an analogous behaviour that can be expressed overtly in the MRI scanner which gives rise to an urge like those described by individuals with TS. We examined the urge-to-blink in 20 healthy volunteers with an experimental paradigm including two conditions, "Okay to blink" and "Suppress blinking", to identify brain regions involved in blink suppression. Multi-echo functional MRI data was analysed using a novel approach to investigate the BOLD signal correlated with the build-up of the urge-to-blink that participants continuously reported using a rollerball device. In addition, we used the method of multi-echo paradigm free mapping (MESPFM) to identify these regions without prior specification of task timings. Subjective urge scores were correlated with activity in the right posterior and ventral-anterior insula as well as the mid-cingulate and occipital cortices. Furthermore, blink suppression was associated with activation in the dorsolateral prefrontal cortex, cerebellum, right dorsal-anterior insula, mid-cingulate cortex and thalamus. These findings illustrate that different insula subregions contribute to the urge-for-action and suppression networks. The MESPFM approach showed co-activation of the right insula and cingulate cortex. The MESPFM activation maps showed the highest overlap with activation associated with blink suppression, as identified using general linear model analysis, demonstrating that activity associated with suppression can be determined without prior knowledge of task timings.

Spiking neural network models of sound localisation via a massively collaborative process
Neuroscientists are increasingly initiating large-scale collaborations which bring together tens to hundreds of researchers. However, while these projects represent a step-change in scale, they retain a traditional structure with centralised funding, participating laboratories and data sharing on publication. Inspired by an open-source project in pure mathematics, we set out to test the feasibility of an alternative structure by running a grassroots, massively collaborative project in computational neuroscience. To do so, we launched a public Git repository, with code for training spiking neural networks to solve a sound localisation task via surrogate gradient descent. We then invited anyone, anywhere to use this code as a springboard for exploring questions of interest to them, and encouraged participants to share their work both asynchronously through Git and synchronously at monthly online workshops. At a scientific level, our work investigated how a range of biologically-relevant parameters, from time delays to membrane time constants and levels of inhibition, could impact sound localisation in networks of spiking units. At a more macro-level, our project brought together 31 researchers from multiple countries, provided hands-on research experience to early career participants, and opportunities for supervision and teaching to later career participants. Looking ahead, our project provides a glimpse of what open, collaborative science could look like and provides a necessary, tentative step towards it.

Power-law adaptation in the presynaptic vesicle cycle
After synaptic transmission, fused synaptic vesicles are recycled, enabling the synapse to recover its capacity for renewed release. The recovery steps, which range from endocytosis to vesicle docking and priming, have been studied individually, but it is not clear what their impact on the overall dynamics of synaptic recycling is, and how they influence signal transmission. Here we model the dynamics of vesicle recycling and find that the multiple timescales of the recycling steps are reflected in synaptic recovery. This leads to multi-timescale synapse dynamics, which can be described by a simplified synaptic model with 'power-law' adaptation. Using cultured hippocampal neurons, we test this model experimentally, and show that the duration of synaptic exhaustion changes the effective synaptic recovery timescale, as predicted by the model. Finally, we show that this adaptation could implement a specific function in the hippocampus, namely enabling efficient communication between neurons through the temporal whitening of hippocampal spike trains.

Novel verbal instructions recruit abstract neural patterns of time-variable information dimensionality
Human performance is endowed by neural representations of information that is relevant for the task, some of which are also activated in a preparatory fashion to optimize later execution. Most studies to date have focused on highly practiced actions, leaving largely unaddressed the configuration of neural information in novel settings, where unique task sets have to be generated from scratch. Using electroencephalography (EEG), this study investigated the dynamics of the content and geometry reflected on the neural patterns of control representations during novel instructed behavior. We designed a verbal instruction paradigm where each trial involved novel combinations of multi-component task information. By manipulating three task-relevant factors, we observed multiplexed coding of information throughout the trial, during both preparation and implementation stages. The temporal profiles were consistent with a hierarchical structure: higher-level task information was coded in a sustained manner, while lower-level variables were so more transiently. Data showed both high dimensionality and abstraction, particularly during instruction encoding and target processing. Our results suggest that whenever task content could be recovered from neural patterns of activity, it was structured in an abstract format, with an underlying structure that favored generalization. During target processing, where potential interference across factors increased, orthogonal configurations also appeared. Overall, our findings uncover the dynamic manner with which control representations operate during novel scenarios, with changes in dimensionality and abstraction adjusting to task needs.

Olfactory cortical outputs recruit and shape distinct brain-wide spatiotemporal networks
Odor information is transmitted from the olfactory bulb to several primary olfactory cortical regions in parallel, including the anterior olfactory nucleus (AON) and piriform cortex (Pir). However, the specific roles of the olfactory bulb and cortical outputs in wider interactions with other interconnected regions throughout the brain remain unclear due to the lack of suitable in vivo techniques. Furthermore, emerging associations between olfactory-related dysfunctions and neurological disorders underscore the need for examining olfactory networks at the systems level. Using optogenetics, fMRI, and computational modeling, we interrogated the spatiotemporal properties of brain-wide neural interactions in olfactory networks. We observed distinct downstream recruitment patterns. Specifically, stimulation of excitatory projection neurons in OB predominantly activates primary olfactory network regions, while stimulation of OB afferents in AON and Pir primarily orthodromically activates hippocampal/striatal and limbic networks, respectively. Temporally, repeated OB or AON stimulation diminishes neural activity propagation brain-wide in contrast to Pir stimulation. Dynamic causal modeling analysis reveals a robust inhibitory effect of AON outputs on striatal and limbic network regions. In addition, experiments in aged rat models show decreased brain-wide activation following OB stimulation, particularly in the primary olfactory and limbic networks. Modeling analysis identifies a dysfunctional AON to Pir connection, indicating the impairment of this primary olfactory cortical circuit that disrupts the downstream long-range propagation. Our study for the first time delineates the spatiotemporal properties of olfactory neural activity propagation in brain-wide networks and uncovers the roles of primary olfactory cortical, AON and Pir, outputs in shaping neural interactions at the systems level.

Structural diversity of mitochondria in the neuromuscular system across development
As an animal matures, its neural circuit undergoes alterations, leading to changes in both neuronal morphology and the connectivity between neurons. However, less is known about the mitochondrial structure changes across development to facilitate these changes, while mitochondria are highly dynamic organelles related to neuronal development. Here, we attempt to answer this question with a model organism C. elegans using 3D electron microscopy (EM). We developed semi-automated methods for reconstructing mitochondria in C. elegans EM images using deep learning. Consequently, we collected mitochondria reconstructions from normal reproductive stages and dauer, enabling comparative study on mitochondrial morphology and spatial organization within the neuromuscular system across different stages. We have identified that the mitochondria structural properties in neurons are correlated with synaptic properties. Neuronal compartments have distinct roles, leading axonal mitochondria to differ morphologically from dendritic mitochondria. We tested this by analyzing behavior in animals with a mutation in drp-1, required for proper mitochondrial fission, confirming that compartment-specific mitochondrial morphology is vital for effective functioning of synapses. Given that these functions are essential throughout development, the structural properties of mitochondria are preserved across development. We report that dauer inter- and motor neurons, predominantly cholinergic and glutamatergic, show distinctive mitochondrial structure and increased mitochondria density. In addition, mitochondria in dauer body wall muscles exhibit distinctive reticulum-like structure. We propose that the stage-specific mitochondrial structure observed in C. elegans dauer may constitute an adaptive mechanism to support stage-specific behavioral and physiological characteristics.

Adaptive Safety Coding in the Prefrontal Cortex
Pivotal to self-preservation is the ability to identify when we are safe and when we are in danger. Previous studies have focused on safety estimations based on the features of external threats and do not consider how the brain integrates other key factors, including estimates about our ability to protect ourselves. Here we examine the neural systems underlying the online dynamic encoding of safety. The current preregistered study used two novel tasks to test four facets of safety estimation: Safety Prediction, Meta-representation, Recognition, and Value Updating. We experimentally manipulated safety estimation changing both levels of external threats and self-protection. Data were collected in two independent samples (behavioral N=100; fMRI N=30). We found consistent evidence of subjective changes in the sensitivity to safety conferred through protection. Neural responses in the ventromedial prefrontal cortex (vmPFC) tracked increases in safety during all safety estimation facets, with specific tuning to protection. Further, informational connectivity analyses revealed distinct hubs of safety coding in the posterior and anterior vmPFC for external threats and protection, respectively. These findings reveal a central role of the vmPFC for coding safety.

A distinct down state assembly in retrosplenial cortex during slow-wave sleep
Understanding the intricate mechanisms underlying slow-wave sleep (SWS) is crucial for deciphering the brain's role in memory consolidation and cognitive functions. It is well-established that cortical delta oscillations (0.5-4 Hz) coordinate communications among various cortical, hippocampal, and thalamic regions during SWS. These delta oscillations have periods of Up and Down states, with the latter previously thought to represent complete cortical silence; however, new evidence suggests that Down states serve important functions for information exchange during memory consolidation. The retrosplenial cortex (RSC) stands out for its pivotal role in memory consolidation due to its extensive connectivity with memory-associated regions, although it remains unclear how RSC neurons engage in delta-associated consolidation processes. Here, we employed multi-channel in vivo electrophysiology to study RSC neuronal activity in freely behaving mice during natural SWS. We discovered that the RSC contains a discrete assembly of putative excitatory neurons (~20%) that initiated firing at SWS Down states and reached maximal firing at the Down-to-Up transitions. Therefore, we termed these RSC neurons the Down state assembly (DSA), and the remaining RSC excitatory neurons as non-DSA. Compared to non-DSA, DSA neurons exhibit a higher firing rate, larger cell body size, and no connectivity with nearby RSC neurons. Subsequently, we investigated RSC neuronal activity during a contextual fear conditioning paradigm and found that both DSA and non-DSA neurons exhibited increased firing activity during post-training sleep compared to pre-training sleep, indicating their roles in memory consolidation. Lastly, optogenetics combined with electrophysiology revealed that memory-associated inputs differentially innervated RSC excitatory neurons. Collectively, these findings provide insight on distinct RSC neuronal subpopulation activity in sleep and memory consolidation.

Return of intracranial beta oscillations and traveling waves with recovery from traumatic brain injury
Traumatic brain injury (TBI) remains a pervasive clinical problem associated with significant morbidity and mortality. However, TBI remains clinically and biophysically ill-defined, and prognosis remains difficult even with the standardization of clinical guidelines and advent of multimodality monitoring. Here we leverage a unique data set from TBI patients implanted with either intracranial strip electrodes during craniotomy or quad-lumen intracranial bolts with depth electrodes as part of routine clinical practice. By extracting spectral profiles of this data, we found that the presence of narrow-band oscillatory activity in the beta band (12-30 Hz) closely corresponds with the neurological exam as quantified with the standard Glasgow Coma Scale (GCS). Further, beta oscillations were distributed over the cortical surface as traveling waves, and the evolution of these waves corresponded to recovery from coma, consistent with the putative role of waves in perception and cognitive activity. We consequently propose that beta oscillations and traveling waves are potential biomarkers of recovery from TBI. In a broader sense, our findings suggest that emergence from coma results from recovery of thalamo-cortical interactions that coordinate cortical beta rhythms.

Robust and Memoryless Median Estimation for Real-Time Spike Detection
We propose a novel moving median estimator specifically designed for online detection of threshold crossings in multi-channel signals, such as extracellular neural recordings. This estimator offers two key advantages: a reduced sensitivity to outliers and the elimination of memory requirements for storing arrival times. Furthermore, its design facilitates parallel implementation on FPGAs, making it ideal for real-time processing of multi-channel recordings.

Neuro-immunology in a mouse model of anti-NMDAR encephalitis and assessment of treatment approaches
Anti-N-methyl-D-aspartate receptor (NMDAR) encephalitis is a disorder mediated by autoantibodies against the GluN1 subunit of NMDAR. It occurs with severe neuropsychiatric symptoms that often improve with immunotherapy. Clinical studies and animal models based on patients' antibody transfer or NMDAR immunization suggest that the autoantibodies play a major pathogenic role. Yet, there is an important need of models offering an all-inclusive neuro-immunobiology of the disease together with a clinical course long enough to facilitate the assessment of potential new treatments. Toward this end, eight-week-old female mice (C57BL/6J) were immunized (days 1 and 28) with GluN1356-385 peptide or saline with AddaVax adjuvant and pertussis toxin. After symptom development (~day 35), subsets of mice were treated with an anti-CD20 (day 35), a positive allosteric modulator (PAM) of NMDAR (NMDAR-PAM, SGE-301) from days 45 to 71, or both. GluN1-antibody synthesis, epitope spreading, effects of antibodies on density and function of NMDAR, brain immunological infiltrates, microglial activation and NMDAR phagocytosis, and antibody synthesis in cultured inguinal and deep cervical lymph nodes (DCLN) were assessed with techniques including immunohistochemistry, calcium imaging, confocal and super-resolution microscopy, electrophysiology, or flow cytometry. Changes of memory and behaviour were assessed with a panel of behavioural tests, and clinical/subclinical seizures with brainimplanted electrodes. Immunized mice, but not controls, developed serum and CSF NMDAR-antibodies (IgG1 predominant) against the immunizing peptide and other GluN1 regions (epitope spreading) resulting in a decrease of synaptic and extrasynaptic NMDAR clusters and reduction of hippocampal plasticity. These findings were associated with brain inflammatory infiltrates, mainly B- and plasma cells, microglial activation, colocalization of NMDAR-IgG complexes with microglia, and presence of these complexes within microglial endosomes. Cultures of DCLC showed GluN1-antibody production. These findings were associated with psychotic-like behaviour (predominant at disease onset), memory deficit, depressive-like behaviour, abnormal movements (15% of mice), and lower threshold for developing pentylenetetrazole-induced seizures (hypoactivity, myoclonic jerks, continuous tonic-clonic) which correlated with regional cFOS expression. Most symptoms and neurobiological alterations were reversed by the anti-CD20 and PAM, alone or combined. Initial repopulation of B cells, by the end of the study, was associated with re-emergence of clinical-neurobiological alterations, which were abrogated by PAM. Overall, this model offers an all-inclusive neuro-immunobiology of the disease, allowing testing novel treatments, supporting the potential therapeutic role of NMDAR-PAM, and suggesting an immunological paradigm of systemic antigen presentation and brain NMDAR epitope spreading, which along the DCLN might contribute to fine-tune the polyclonal immune response.

Long-lived adult-born hippocampal neurons promote successful cognitive aging
Aging is commonly associated with a decline in memory abilities, yet some individuals remain resilient with preserved memory abilities. Memory processing is critically dependent on adult neurogenesis, a unique form of plasticity in the hippocampus. However, it remains unknown if cognitive aging influences the integration and role of adult-born hippocampal neurons (ABNs) generated early in adult life. Here, we investigated the role of long-lived ABNs in rats characterized as either resilient or vulnerable to cognitive aging using a peudo-longitudinal approach. Our findings reveal that long-lived ABNs support successful cognitive aging by preserving their synaptic inputs onto the proximal segments of their dendrites, and that these proximal synaptic sites also demonstrate a maintenance of their mitochondrial homeostasis. Furthermore, by-passing the reduced inputs of ABNs in vulnerable rats through direct optogenetic stimulation successfully improved their memory abilities. Overall, our data indicate that the maintenance of long-lived ABNs integration within the neuronal network is essential for successful cognitive aging, highlighting their potential as a therapeutic target for restoring cognitive functions in old age.

Perception of audio-visual synchrony is modulated by walking speed and step cycle phase
Investigating sensory processes in active human observers is critical for a holistic understanding of perception. Recent research has demonstrated that locomotion can alter visual detection performance in a rhythmic manner, illustrating how a very frequent and natural behaviour can influence sensory performance. Here we extend this line of work to incorporate variations in walking speed, and test whether multi-sensory processing is impacted by the speed and phase of locomotion. Participants made audio-visual synchrony judgements while walking at two speeds over a range of stimulus onset asynchronies (SOAs). We find that sensitivity to multi-sensory synchrony decreases at slow walking speeds and is accompanied by an increase in reaction times, compared to when walking at a natural pace. A further analysis of the shortest SOAs was conducted to test whether subjective synchrony modulated over the step cycle. This revealed that synchrony judgements were quadratically modulated with perceived synchrony being higher in the swing phase of each step and lower when both feet were grounded during stance phase. Together, these results extend an earlier report that walking dynamically modulates visual sensitivity by contributing two new findings: first, that walking speed modulates perceived synchrony of audio-visual stimuli, and second, that modulations within the step-cycle extend to multisensory synchrony judgements which peak in the swing phase of each step.

Modulation Of SUDEP By Central Serotonergic Cooperating with Noradrenergic Circuits: A Synergistic-Dependent Manner
Sudden unexpected death in epilepsy (SUDEP) is the leading cause of death in refractory epilepsy patients. Despite previous accumulating evidence has shown that seizure-induced respiratory arrest (S-IRA) may play the main contributor to SUDEP as an initiating event preeminent cause of mortality, the specific underlying mechanism of action remains unclear. Based on our previous work, serotonin (5-HT) signaling in the dorsal raphe nucleus (DRN) is strongly implicated in S-IRA in animal models, including the DBA/1 mice, on the meanwhile, norepinephrine (NE) neurons of the locus coeruleus (LC) also plays a vital role in regulating respiratory function on its own. Superficially, monoaminergic neuron, as important neurotransmitters in the central nervous system, have similar modes of action in the maintenance of nervous system balance, and each of them has a regulatory effect on SUDEP. However, it remains to be investigated whether monoaminergic neuron family (NE and 5-HT) are related in the mechanism of regulating SUDEP, what is even more curious is whether the two are intrinsically linked. Thus, we hypothesize neural mechanism of central noradrenergic and serotonergic circuits in modulating SUDEP in a synergistic-dependent manner, this endeavor will culminate in a significant breakthrough in elucidating the precise mechanism of action underlying SUDEP. In our study, we will use chemogenetics, optogenetics, calcium signal recording, and bidirectional tracing to explore the internal mechanism of DR-LC regulating the occurrence of SUDEP, and by specifically injecting 5-HT2AR antagonist Ketanserin (KET) and/or NE-1R antagonist Prazosin into the pre-Botzinger complex (PBC), it was finally elucidate that the DR-LC-PBC network can effectively reduce the incidence of SIRA. We firstly proposed a powerful target for exploring the reduction of the incidence of SUDEP, which has great clinical translation potential.

Conscious and Unconscious Emotional Processing: Insights from Behavioral and Pupillary Responses
Emotions are crucial in social interactions, influencing communication and relationships. Distinguishing the perceived emotion in conscious and unconscious emotional processing is a key research area with cognitive and physiological implications. This study investigates conscious and unconscious emotional processing through behavioral and pupillary responses. Participants completed emotion recognition tasks under varying states, revealing higher accuracy in conscious emotion identification. Emotions like anger, happiness, fear, surprise, and neutral elicited distinct response patterns. Pupillometry data showed pupil size suppression in the conscious state and enhancement in the unconscious state, with differences in peak pupil size across emotions. Task-related components, amplitude, and latency parameters differed between conscious and unconscious states, highlighting the role of awareness in emotional regulation. These findings emphasize the complex interplay of cognitive and physiological processes in emotional responses, providing insights into emotional recognition mechanisms. This study contributes to understanding emotional processing dynamics and has implications for psychology and neuroscience research.

predicTTE: An accessible and optimal tool for time-to-event prediction in neurological diseases
Time-to-event prediction is a key task for biological discovery, experimental medicine, and clinical care. This is particularly true for neurological diseases where development of reliable biomarkers is often limited by difficulty visualising and sampling relevant cell and molecular pathobiology. To date, much work has relied on Cox regression because of ease-of-use, despite evidence that this model includes incorrect assumptions. We have implemented a set of deep learning and spline models for time-to-event modelling within a fully customizable app and accompanying online portal, both of which can be used for any time-to-event analysis in any disease by a non-expert user. Our online portal includes capacity for end-users including patients, Neurology clinicians, and researchers, to access and perform predictions using a trained model, and to contribute new data for model improvement, all within a data-secure environment. We demonstrate a pipeline for use of our app with three use-cases including imputation of missing data, hyperparameter tuning, model training and independent validation. We show that predictions are optimal for use in downstream applications such as genetic discovery, biomarker interpretation, and personalised choice of medication. We demonstrate the efficiency of an ensemble configuration, including focused training of a deep learning model. We have optimised a pipeline for imputation of missing data in combination with time-to-event prediction models. Overall, we provide a powerful and accessible tool to develop, access and share time-to-event prediction models; all software and tutorials are available at www.predictte.org.

Dopaminergic amacrine cells express HCN channels in the developing and adult mouse retina
Purpose: To determine the molecular and functional expression of hyperpolarization-activated cyclic nucleotide-gated (HCN) channels in developing and mature dopaminergic amacrine cells (DACs), the sole source of ocular dopamine that plays a vital role in visual function and eye development. Methods: HCN channels are encoded by isoforms 1-4. HCN1, HCN2, and HCN4 were immunostained in retinal slices obtained from mice at postnatal day 4 (P4), P8, and P12 as well as in adults. Each HCN channel isoform was also immunostained with tyrosine hydroxylase, a marker for DACs, at P12 and adult retinas. Genetically-marked DACs were recorded in flat-mount retina preparation using a whole-cell current-clamp technique. Results: HCN1 was expressed in rods/cones, amacrine cells, and retinal ganglion cells (RGCs) at P4, along with bipolar cells by P12. Different from HCN1, HCN2 and HCN4 were each expressed in amacrine cells and RGCs at P4, along with bipolar cells by P8, and in rods/cones by P12. Double immunostaining shows that each of the three isoforms was expressed in approximately half of DACs at P12 but in almost all DACs in adults. Electrophysiology results demonstrate that HCN channel isoforms form functional HCN channels, and the pharmacological blockade of HCN channels reduced the spontaneous firing frequency in most DACs. Conclusions: Each class of retinal neurons may use different isoforms of HCN channels to function during development. HCN1, HCN2, and HCN4 form functional HCN channels in DACs, which appears to modulate their spontaneous firing activity.

A high-performance genetically encoded sensor for cellular imaging of PKC activity in vivo
We report a genetically encoded fluorescence lifetime sensor for protein kinase C (PKC) activity, named CKAR3, based on Forster resonance energy transfer. CKAR3 exhibits a 10-fold increased dynamic range compared to its parental sensors and enables in vivo imaging of PKC activity during animal behavior. Our results reveal robust PKC activity in a sparse neuronal subset in the motor cortex during locomotion, in part mediated by muscarinic acetylcholine receptors.

A novel method (RIM-Deep) enhances imaging depth and resolution stability of deep-cleared brain tissue in inverted confocal microscopy
The increasing use of tissue clearing techniques underscores the urgent need for cost-effective and simplified deep imaging methods. While traditional inverted confocal microscopes excel in high-resolution imaging of tissue sections and cultured cells, they face limitations in deep imaging of cleared tissues due to refractive index mismatches between the immersion media of objectives and sample container. To overcome these challenges, the RIM-Deep was developed to significantly improve deep imaging capabilities without compromising the normal function of the confocal microscope. This system facilitates deep immunofluorescence imaging of the prefrontal cortex in cleared macaque tissue, extending imaging depth from 2 mm to 5 mm. Applied to an intact and cleared Thy1-EGFP mouse brain, the system allowed for clear axonal visualization at high imaging depth. Moreover, this advancement enables large-scale, deep 3D imaging of intact tissues. In principle, this concept can be extended to any imaging modality, including existing inverted wide-field, confocal, and two-photon microscopy. This would significantly upgrade traditional laboratory configurations and facilitate the study of connectomics in the brain and other tissues.

TDSTDP
This is a preliminary thesis on Temporal Difference Spike-Timing Dependent Plasticity (TDSTDP), a variation of STDP that considers dendritic potential. TDSTDP is capable of performing temporal difference (TD) learning without dopamine modulation. Major characteristics of TD learning, including value estimation, value propagation, and temporal shifting of dopamine, are demonstrated in simulations. Additionally, a synaptic calcium model demonstrates its biological plausibility.

ERβ mediates sex-specific protection in the App-NL-G-F mouse model of Alzheimer's disease
Menopausal loss of neuroprotective estrogen is thought to contribute to the sex differences in Alzheimer's disease (AD). Activation of estrogen receptor beta (ER{beta}) can be clinically relevant since it avoids the negative systemic effects of ER activation. However, very few studies have explored ER{beta}-mediated neuroprotection in AD, and no information on its contribution to the sex differences in AD exists. In the present study we specifically explored the role of ER{beta} in mediating sex-specific protection against AD pathology in the clinically relevant AppNL-G-F knock-in mouse model of amyloidosis, and if surgical menopause (ovariectomy) modulates pathology in this model. We treated male and female AppNL-G-F mice with the selective ER{beta} agonist LY500307 and subset of the females was ovariectomized prior to treatment. Memory performance was assessed and a battery of biochemical assays were used to evaluate amyloid pathology and neuroinflammation. Primary microglial cultures from male and female wild-type and ER{beta}-knockout mice were used to assess ER{beta}'s effect on microglial activation and phagocytosis. We find that ER{beta} activation protects against amyloid pathology and cognitive decline in male and female AppNL-G-F mice. Ovariectomy increased soluble amyloid beta (A{beta}) in cortex and insoluble A{beta} in hippocampus, but had otherwise limited effects on pathology. We further identify that ER{beta} does not alter APP processing, but rather exerts its protection through amyloid scavenging that at least in part is mediated via microglia in a sex-specific manner. Combined, we provide new understanding to the sex differences in AD by demonstrating that ER{beta} protects against AD pathology differently in males and females, warranting reassessment of ER{beta} in combating AD.