bioRxiv Subject Collection: Neuroscience's Journal

OLIGONUCLEOTIDES TARGETING THE SPLICE ACCEPTOR SITE DOWNSTREAM OF A MICROEXON AS AN INNOVATIVE THERAPY FOR AUTISM
Background: Microexons are highly conserved and mostly neuronal-specific 3-27 nucleotide exons, enriched in genes linked to autism spectrum disorders (ASD). We have previously shown decreased inclusion of a neuronal specific 24 bp microexon (exon 4) of the translational regulator CPEB4 in brains of idiopathic ASD cases and that this leads to CPEB4 aggregation and subsequent under-expression of multiple high confidence ASD-risk genes. Furthermore, enhanced skipping of the CPEB4 microexon is also a novel etiological mechanism in schizophrenia (SCZ). Methods: In this work we designed and tested in neuroblastoma cells a series of splice switching antisense oligonucleotides (SSO) targeting the CPEB4 genomic region surrounding the microexon. Results: SSOs targeting candidate intronic regions near the microexon resulted in a decrease in microexon inclusion by blocking hnRNPC/PTPB1 binding, thus mimicking the isoform imbalance observed in ASD. However, based on the kinetic coupling model correlating transcriptional elongation with splicing regulation, we identified SSOs targeting downstream splice acceptor site of exon 5 that favoured microexon inclusion in a dose-dependent manner and resulted in increased protein levels of FOXP1 and AUTS2, two high-confidence ASD risk genes that are known targets of CPEB4 and whose protein levels are reduced in ASD. Conclusions: These results deepen our understanding of the complex splicing regulation of microexons and open new applications of SSOs to treat diseases such as ASD and SCZ that are characterized by altered microexon inclusion

Microglial states determine lesion dynamics in multiple sclerosis
Multiple sclerosis (MS) is a neuroinflammatory disease of the central nervous system, characterized by demyelinating lesions 1. Lesion expansion contributes to progression and increased disability, while remyelination can recover neurological deficits. However, mechanisms driving lesion dynamics are largely unclear, hindering the development of effective therapeutics. We propose that distinct states of microglia are involved in lesion expansion and remyelination 2,3. Using Stereo-seq, an RNA capture based high-resolution spatial transcriptomics technology with single-cell resolution, on post-mortem human brain tissue, we compared mixed active/inactive lesions with lipid-laden foamy microglia with lesions containing ramified microglia. We identified distinct cellular and molecular mechanisms underlying lesion activity and remyelination, linked to microglia phenotypes and states. Lesions with foamy microglia were characterized by elevated immune activation, increased lymphocyte densities, upregulated immunoglobulin production (IGHG1, IGHG3), increased complement system activity, indication of iron dysregulation (FTL, FTH1), and increased demyelination. In contrast, lesions with ramified microglia exhibited gene expression profiles indicative of myelin stability (ABCA2, QKI) and neuro-axonal protection, fostering an environment conducive to repair and remyelination. Our findings highlight the role of microglial states in lesion expansion and repair in MS and offer promising avenues for the development of therapeutic approaches aimed at preventing MS disability progression.

Endogenous retrovirus-like proteins recruit UBQLN2 to stress granules and alter their functional properties
The human genome is replete with sequences derived from foreign elements including endogenous retrovirus-like proteins of unknown function. Here we show that UBQLN2, a ubiquitin-proteasome shuttle factor implicated in neurodegenerative diseases, is regulated by the linked actions of two retrovirus-like proteins, RTL8 and PEG10. RTL8 confers on UBQLN2 the ability to complex with and regulate PEG10. PEG10, a core component of stress granules, drives the recruitment of UBQLN2 to stress granules under various stress conditions, but can only do so when RTL8 is present. Changes in PEG10 levels further remodel the kinetics of stress granule disassembly and overall composition by incorporating select extracellular vesicle proteins. Within stress granules, PEG10 forms virus-like particles, underscoring the structural heterogeneity of this class of biomolecular condensates. Together, these results reveal an unexpected link between pathways of cellular proteostasis and endogenous retrovirus-like proteins.

Simulated microgravity accelerates alpha-synuclein aggregation and induces oxidative stress in an in vitro Parkinson disease model
Parkinson's disease (PD) is a neurodegenerative disorder characterized by the accumulation of alpha-synuclein aggregates and progressive neuronal loss in the substantia nigra, with aging being its primary risk factor. The current available models to study PD mechanisms are largely relying on genetic mutations to recapitulate PD typical hallmarks, such as increased alpha-synuclein aggregation. However, they do not model the aging features associated with the disease. Microgravity, a condition experience by astronauts during space missions, is known to induce ageing-like modifications on both systemic and cellular physiology. To replicate the aging-related stress observed in PD patients, we exposed SH-SY5Y and 3K-SNCA mutant cell lines to simulated microgravity. Our findings revealed that simulated microgravity enhanced PD alterations, with a significant increase in misfolded and phosphorylated a-syn. This was accompanied by heightened oxidative stress, as evidenced by increased levels of reactive oxygen species, without a sufficient antioxidant response. These results suggest that simulated microgravity effectively mimics and accelerate the stress associated with aging in PD cell models, regardless of the presence of PD mutation. This study highlights the potential of simulated microgravity as a tool for investigating aging processes in neurodegenerative diseases.

Principles and Operation of Virtual Brain Twins
Current clinical methods often overlook individual variability by relying on population-wide trials, while mechanism-based trials remain underutilized in neuroscience due to the brain's complexity. A Virtual Brain Twin (VBT) is a personalized digital replica of an individual's brain, integrating structural and functional brain data into advanced computational models and inference algorithms. By bridging the gap between molecular mechanisms, whole-brain dynamics, and imaging data, VBTs enhance the understanding of (patho)physiological mechanisms, advancing insights into both healthy and disordered brain function. Central to VBT is the network modeling that couples mesoscopic representation of neuronal activity through white matter connectivity, enabling the simulation of brain dynamics at a network level. This transformative approach provides interpretable predictive capabilities, supporting clinicians in personalizing treatments and optimizing interventions. This manuscript outlines the key components of VBT development, covering the conceptual, mathematical, technical, and clinical aspects. We describe the stages of VBT construction--from anatomical coupling and modeling to simulation and Bayesian inference--and demonstrate their applications in resting-state, healthy aging, epilepsy, and multiple sclerosis. Finally, we discuss potential extensions to other neurological disorders, such as Parkinson's disease, and explore future applications in consciousness research and brain-computer interfaces, paving the way for advancements in personalized medicine and brain-machine integration.

In Vivo Expression of an SCA27A-linked FGF14 Mutation Results in Haploinsufficiency and Impaired Firing of Cerebellar Purkinje Neurons
Autosomal dominant mutations in FGF14, which encodes intracellular fibroblast growth factor 14 (iFGF14), underlie spinocerebellar ataxia type 27A (SCA27A), a devastating multisystem disorder resulting in progressive deficits in motor coordination and cognitive function. Mice lacking iFGF14 (Fgf14-/-) exhibit similar phenotypes, which have been linked to iFGF14-mediated modulation of the voltage-gated sodium (Nav) channels that control the high frequency repetitive firing of Purkinje neurons, the main output neurons of the cerebellar cortex. To investigate the pathophysiological mechanisms underlying SCA27A, we developed a targeted knock-in strategy to introduce the first point mutation identified in FGF14 into the mouse Fgf14 locus (Fgf14F145S), we determined the impact of in vivo expression of the mutant Fgf14F145S allele on the motor performance of adult animals and on the firing properties of mature Purkinje neurons in acute cerebellar slices. Electrophysiological experiments revealed that repetitive firing rates are attenuated in adult Fgf14F145S/+ cerebellar Purkinje neurons, attributed to a hyperpolarizing shift in the voltage-dependence of steady-state inactivation of Nav channels. More severe effects on firing properties and Nav channel inactivation were observed in homozygous Fgf14F145S/F145S Purkinje neurons. Interestingly, the electrophysiological phenotypes identified in adult Fgf14F145S/+ and Fgf14F145S/F145S cerebellar Purkinje neurons mirror those observed in heterozygous Fgf14+/- and homozygous Fgf14-/- Purkinje neurons, respectively, suggesting that the mutation results in the loss of the iFGF14 protein. Western blot analysis of lysates from adult heterozygous Fgf14F145S/+ and homozygous Fgf14F145S/F145S animals revealed reduced or undetectable, respectively, iFGF14 expression, supporting the hypothesis that the mutant allele results in loss of the iFGF14 protein and that haploinsufficiency underlies SCA27A neurological phenotypes.

Dissociable Default Mode Network Connectivity Patterns Underlie Distinct Symptoms in Psychosis Risk
The Clinical High Risk (CHR) stage of psychosis is characterized by subthreshold symptoms of schizophrenia including negative symptoms, dysphoric mood, and functional deterioration. Hyperconnectivity of the default-mode network (DMN) has been observed in early schizophrenia, but the extent to which hyperconnectivity is present in CHR, and the extent to which such hyperconnectivity may underlie transdiagnostic symptoms, is not clear. As part of the Shanghai At-Risk for Psychosis (SHARP) program, resting-state fMRI data were collected from 251 young adults (158 CHR and 93 controls, M = 18.72, SD = 4.68, 129 male). We examined functional connectivity of the DMN by performing a whole-brain seed-to-voxel analysis with the MPFC as the seed. Symptom severity across a number of dimensions, including negative symptoms, positive symptoms, and affective symptoms were assessed. Compared to controls, CHRs exhibited significantly greater functional connectivity (p < 0.001 uncorrected) between the MPFC and 1) other DMN nodes including the posterior cingulate cortex (PCC), and 2) auditory cortices (superior and middle temporal gyri, STG/MTG). Furthermore, these two patterns of hyperconnectivity were differentially associated with distinct symptom clusters. Within CHR, MPFC-PCC connectivity was significantly correlated with anxiety (r= 0.23, p=0.006), while MPFC-STG/MTG connectivity was significantly correlated with negative symptom severity (r=0.26, p=0.001). Secondary analyses using item-level symptom scores confirmed a similar dissociation. These results demonstrate that two dissociable patterns of DMN hyperconnectivity found in the CHR stage may underlie distinct dimensions of symptomatology.

Auditory working memory mediates the relationship between musicianship and auditory stream segregation
This study investigates the interactions between musicianship and two auditory cognitive mechanisms: auditory working memory (AWM) and stream segregation. The primary hypothesis is that AWM mediates the relationship between musical training and enhanced stream segregation capabilities. Two groups of listeners were tested, the first to establish the relationship between the two variables and the second to replicate the effect in an independent sample. Music history and behavioural data were collected from a total of 145 healthy young adults with normal binaural hearing. They performed a task that requires manipulation of tonal patterns in working memory, and the Music-in-Noise Task (MINT), which measures stream segregation abilities in a musical context. The MINT task expands measurements beyond traditional Speech-in-Noise (SIN) assessments by capturing auditory subskills (e.g., rhythm, visual, spatial, prediction) relevant to stream segregation. Our results showed that musical training is associated with enhanced AWM and MINT task performance, and that this effect is replicable across independent samples. Moreover, we found in both samples that the enhancement of stream segregation was largely mediated by AWM capacity. The results suggest that musical training and/or aptitude enhances music-in-noise perception by way of improved AWM capacity.

F-BAR proteins CIP4 and FBP17 function in cortical neuron radial migration and process outgrowth
Neurite initiation from newly born neurons is a critical step in neuronal differentiation and migration. Neuronal migration in the developing cortex is accompanied by dynamic extension and retraction of neurites as neurons progress through bipolar and multipolar states. However, there is a relative lack of understanding regarding how the dynamic extension and retraction of neurites is regulated during neuronal migration. In recent work we have shown that CIP4, a member of the F-BAR family of membrane bending proteins, inhibits cortical neurite formation in culture, while family member FBP17 induces premature neurite outgrowth. These results beg the question of how CIP4 and FBP17 function in radial neuron migration and differentiation in vivo, including the timing and manner of neurite extension and retraction. Indeed, the regulation of neurite outgrowth is essential for the transitions between bipolar and multipolar states during radial migration. To examine the effects of modulating expression of CIP4 and FBP17 in vivo, we used in utero electroporation, in combination with our published Double UP technique, to compare knockdown or overexpression cells with control cells within the same mouse tissue of either sex. We show that either knockdown or overexpression of CIP4 and FBP17 results in the marked disruption of radial neuron migration by modulating neuronal morphology and neurite outgrowth, consistent with our findings in culture. Our results demonstrate that the F-BAR proteins CIP4 and FBP17 are essential for proper radial migration in the developing cortex and thus play a key role in cortical development.

Dopamine transmission in the anterior insula shapes the neural coding of anxiety
The insular cortex (or insula), and particularly its anterior region, plays a crucial role in the control of emotional valence and anxiety (Etkin & Wager, 2007; Mendez-Ruette et al., 2019; Nicolas et al., 2023). While dopamine neurotransmission is known to modulate anxiety levels in humans (Hjorth et al., 2021) and animal models (de la Mora et al., 2010; Bananej et al., 2012; Zarrindast & Khakpai, 2015; DeGroot et al., 2020; Godino et al., 2023), its regulatory effects on the anterior insula remained unexplored. Here, using a multifaceted approach, we uncovered how dopamine shapes anterior insula function in anxiety and valence processing. First, we revealed a high density of neurons expressing type-1 dopamine receptors (D1) in the insula, particularly important in the anterior insula, and seven times greater than the density of neurons expressing type-2 dopamine receptors (D2). Few neurons co-expressed Drd1 and Drd2 mRNAs in the anterior and posterior insula, and the density of Drd1+ neurons in the anterior insula was twice higher among inhibitory neurons than excitatory neurons. Second, we found that pharmacological activation of D1 in the anterior insula is anxiogenic, suggesting a direct link between insular dopamine signaling and anxiety-related behaviors. Using fiber-photometry recordings, we identified that the amplitude of dopamine release onto D1+ neurons in the anterior insula while mice were in anxiogenic spaces or receiving mild foot shocks was both positively correlated with mice level of trait anxiety. Population dynamics and deep-learning analyses of anterior insula single-unit recordings uncovered distinct coding patterns of anxiety-provoking and safe environments, as well as tastants of positive and negative valence. Remarkably, systemic D1 activation, which heightens anxiety-related behaviors, dampens this coding dichotomy by increasing coding variability for protected spaces while increasing the coding reliability for anxiogenic spaces. Interestingly, the coding reliability of anxiogenic areas was positively correlated with mice level of trait anxiety, and we observed a trend towards a positive correlation between the coding reliability of a negative tastants, and mice level of anxiety. Altogether, our findings provide a new model of neural population coding of anxiety and emotional valence and unravel D1-dependent coding mechanisms in the mouse anterior insula.

Dysfunction of the episodic memory network in the Alzheimer's disease cascade
Alzheimer's disease (AD) is a major cause of dementia and cognitive decline. Here we assessed how episodic memory circuit dysfunction, a hallmark of AD, is related to the longitudinal cascade of AD biomarkers, neurodegeneration and cognition using data from the DZNE Longitudinal Cognitive Impairment and Dementia study. This data set is unique by including over 1000 longitudinal functional magnetic resonance imaging (fMRI) measurements during episodic memory encoding. We leveraged a disease progression model (DPM) to obtain AD progression scores. Voxel-wise analyses revealed widespread loss of deactivation (hyperactivation) and activation (hypoactivation) with increasing disease stage. Hyperactivation trajectories were nonlinear and visually preceded trajectories of cognition. Overall, hyperactivation was independently associated with co-occurrence of amyloid- and tau-positivity and neurodegeneration, suggesting synaptic dysfunction and neurodegeneration as two independent drives of cognitive decline. Our results therefore provide evidence for a critical time window in which pharmacological treatments targeting the synapse may improve cognition.

String-pulling by the common marmoset
Coordinated hand movements used to grasp and manipulate objects are crucial for many daily activities, such as tying shoelaces or opening jars. Recently, the string-pulling task - which involves cyclically reaching, grasping and pulling a string - has been used to study coordinated hand movements in rodents and humans. Here we characterize how adult common marmosets perform the string-pulling task and describe changes in performance across the lifespan. Marmosets (n=15, 7 female) performed a string-pulling task for a food reward using an instrumented apparatus attached to their home-cage. Movement kinematics were acquired using markerless video tracking and we assessed individual hand movements and bimanual coordination using standard metrics. Marmosets appeared to guide their actions with vision and readily performed the string-pulling task regardless of sex or age. The task required very little training and animals routinely engaged in multiple pulling trials per session despite not being under water or food control. All marmosets showed consistent pulling speed and similar hand movements regardless of age. Adult marmosets exhibited a clear hand effect, performing straighter and faster movements with their right hand despite showing idiosyncratic hand preference according to a traditional food retrieval assay. Hand effects were also evident for younger animals but seemed attenuated in the older animals. In terms of bimanual coordination, all adult marmosets demonstrated an alternating movement pattern for vertical hand positions. Two younger and two older marmosets exhibited idiosyncratic coordination patterns even after substantial experience. In general, younger and older animals exhibited higher variability in bimanual coordination than did adults.

Inhibition of the RNA Regulator HuR mitigates spinal cord injury by potently suppressing post-injury neuroinflammation
Background: Neuroinflammation plays a significant role in promoting secondary tissue injury after spinal cord trauma. Within minutes after spinal cord injury (SCI), microglia and astrocytes become activated and produce inflammatory mediators such as TNF-, IL-6, iNOS and COX-2 which induce tissue injury through cytotoxicity, vascular hyperpermeability, and secondary ischemia. The inflammatory cascade is amplified by chemokines such as CCL2 and CXCL1 that promote recruitment of peripheral inflammatory cells into the injured spinal cord. HuR is a key post-transcriptional RNA regulator that controls glial expression of many pro-inflammatory factors by binding to adenylate- and uridylate-rich elements in 3' untranslated regions of the mRNA. SRI-42127 is a small molecule inhibitor that blocks HuR nucleocytoplasmic translocation, a process critical for its regulatory function. The goal of this study was to assess the potential of SRI-42127 for suppressing neuroinflammation after SCI and improving functional outcome. Methods: Adult female mice underwent a contusion injury at the T10 level. SRI-42127 or vehicle was administered intraperitoneally starting 1 h after injury and up to 5 days. Locomotor function was assessed by open field testing, balance beam and rotarod. Immunohistochemistry was used to assess lesion size, neuronal loss, myelin sparing, microglial activation and HuR localization. Molecular analyses of spinal cord and peripheral tissues for expression of inflammatory mediators included qPCR, immunohistochemistry, ELISA, or western blot. Post-SCI pain was assessed by the mouse grimace scale. Results: SRI-42127 significantly attenuated loss of locomotor function and post-SCI pain. Histologic correlates to these beneficial effects included reduced lesion size, neuronal loss, and an increase in myelin sparing. There was reduced microglial activation at the epicenter with concomitant attenuation of HuR nucleocytoplasmic translocation. Molecular analysis revealed a striking reduction of pro-inflammatory mediators at the epicenter including IL-6, MMP-12, IL-1{beta}, TNF-, iNOS, COX-2, and chemokines CCL2, CXCL1, and CXCL2. Suppression of inflammatory responses extended peripherally including serum, liver, and spleen. Conclusion: Targeting HuR after SCI is a viable therapeutic approach for suppressing neuroinflammatory responses after tissue injury and improving functional outcome.

Idiosyncrasy and generalizability of contraceptive- and hormone-related functional connectomes across the menstrual cycle
Neuroendocrinology has received little attention in human neuroscience research, resulting in a dearth of knowledge surrounding potent and dynamic modulators of cognition and behavior, as well as brain structure and function. This work addresses one such phenomenon by studying functional connectomics related to ovarian hormone fluctuations throughout the adult menstrual cycle. To do so, we applied predictive connectomics to functional magnetic resonance imaging (fMRI) and hormone assessments from two dense, longitudinal datasets to assess variations in functional connections with respect to underlying endocrine fluctuations throughout the menstrual cycle. These analyses support prior findings that common, group-level and individual specific factors have similar relative contributions to functional connectomics. Further, we found widespread connectivity changes related to hormonal contraceptive (HC) use, in addition to sparser estradiol- and progesterone-related connectivity, and differential generalizability of these subnetworks that hints at progestin-specific impacts on functional connectivity in HC users. These results provide novel insight into within-individual changes in brain organization across the menstrual cycle and the extent to which these changes are shared between individuals, illuminating understudied phenomena in reproductive health and important information for all neuroimaging studies that include participants who menstruate.

Shared and unique lifetime stressor characteristics and brain networks predict adolescent anxiety and depression
Exposure to major life stressors and aberrant brain functioning have been linked to anxiety and depression, especially during periods of heighted functional brain plasticity, such as adolescence. However, it remains unclear if specific characteristics of major life stressors and functional network disruptions differentially predict anxiety and depression symptoms over time and, if so, whether they act independently or jointly. We collected baseline lifetime stressor exposure data and resting-state functional magnetic resonance imaging data in a longitudinal sample of 107 adolescents enriched for anxiety and depressive disorders. We examined five stressor characteristics: physical danger, interpersonal loss, humiliation, entrapment, and role change/disruption. Anxiety and depression symptoms were assessed at baseline, 6-month and 12-month follow-ups. Linear mixed effect models tested if these stressor characteristics, functional connectivity within and between frontoparietal, default, and ventral attention networks, and their interactions differentially predicted anxiety and depression symptoms at 6-month and 12-month follow-ups. Greater lifetime severity of physical danger and humiliation prospectively predicted increased anxiety symptoms at both follow-ups, whereas greater lifetime entrapment severity prospectively predicted higher anxiety and depression symptoms. Only the effects of lifetime entrapment severity were robust to including within- and between-network functional connectivity metrics and other significantly predictive stressor characteristics. Lifetime entrapment severity more strongly predicted anxiety symptoms in youth with higher default network connectivity. Greater functional connectivity between frontoparietal and default networks prospectively predicted increased depression symptoms. Taken together, these results underscore the critical importance of using stressor characteristics and functional connectivity jointly to study predictors for adolescent anxiety and depression.

Artificial intelligence networks combining histopathology and machine learning can extract axon pathology in autism spectrum disorder
Axon features that underlie the structural and functional organization of cortical pathways have distinct patterns in the brains of neurotypical controls (CTR) compared to individuals with Autism Spectrum Disorder (ASD). However, detailed axon study demands labor-intensive surveys and time-consuming analysis of microscopic sections from post-mortem human brain tissue, making it challenging to systematically examine large regions of the brain. To address these challenges, we developed an approach that uses machine learning to automatically classify microscopic sections from ASD and CTR brains, while also considering different white matter regions: superficial white matter (SWM), which contains a majority of axons that connect nearby cortical areas, and deep white matter (DWM), which is comprised exclusively by axons that participate in long-range pathways. The result was a deep neural network that can successfully classify the white matter below the anterior cingulate cortex (ACC) of ASD and CTR groups with 98% accuracy, while also distinguishing between DWM and SWM pathway composition with high average accuracy, up to 80%. Multidimensional scaling analysis and sensitivity maps further underscored the reliability of ASD vs CTR classification, based on the consistency of axon pathology, while highlighting the important role of white matter location that constrains pathway dysfunction, based on several shared anatomical markers. Large datasets that can be used to expand training, validation, and testing of this network have the potential to automate high-resolution microscopic analysis of post-mortem brain tissue, so that it can be used to systematically study white matter across brain regions in health and disease.

A Three Dimensional Immunolabeling Method with Peroxidase-fused Nanobodies and Fluorochromized Tyramide-Glucose Oxidase Signal Amplification
Three dimensional immunohistochemistry (3D-IHC), immunolabeling of 3D tissues, reveals the spatial organization of molecular and cellular assemblies in the context of the tissue architecture. Deep and rapid penetration of antibodies into 3D tissues and highly sensitive detection are critical for high-throughput imaging analysis of immunolabeled 3D tissues. Here, we report a nanobody (nAb)-based 3D-IHC, POD-nAb/FT-GO 3D-IHC, for high-speed and high-sensitive detection of targets within 3D tissues. Peroxidase-fused nAbs (POD-nAbs) enhanced immunolabeling depth and allowed for highly sensitive detection by combined with a fluorescent tyramide signal amplification system, Fluorochromized Tyramide-Glucose Oxidase (FT-GO). Multiplex labeling was implemented to the 3D-IHC by quenching POD with sodium azide. Using the 3D-IHC technique, we successfully visualized somata and processes of neuronal and glial cells in millimeter-thick mouse brain tissues within three days. Given its high-speed and high-sensitive detection, our 3D-IHC protocol, POD-nAb/FT-GO 3D-IHC, would provide a useful platform for histochemical analysis in 3D tissues.

Decoding Olfactory Bulb Output: A Behavioral Assessment of Rate, Synchrony, and Respiratory Phase Coding
The olfactory system is a well-known model for studying the temporal encoding of sensory stimuli due to its rhythmic stimulus delivery through respiration. The sniff rhythm is considered critical to structuring the output of computation in the primary olfactory area, the olfactory bulb. Here, Neuropixels recording from awake, head-fixed mice confirmed that both the rate and sniff-locked spike timing are informative about odour identity. We tested the behavioural importance of these temporal features using simple closed-loop optogenetics embedded in custom behavioural paradigms. We found that mice perceive differences in evoked spike counts and discriminate between synchronous vs. asynchronous activations of the output neurons. Surprisingly, they failed to distinguish the timing of evoked activity relative to the sniff cycle. These results challenge the utility of internally generated rhythms as reference signals in the neural encoding of the environment.

A Novel Cyanine-Based Fluorescent Dye for Targeted Mitochondrial Imaging in Neurotoxic Conditions and In Vivo Brain Studies
Mitochondrial dysfunction is a key feature of neurodegenerative diseases, often preceding symptoms and influencing disease progression. However, real-time in vivo imaging of mitochondria in the brain is limited by existing dyes like MitoTrackers, which struggle with poor tissue penetration, phototoxicity, and inability to cross the blood-brain barrier (BBB). This study introduces Cy5-PEG4, a novel mitochondrial-targeting dye that overcomes these limitations, enabling high-resolution, non-invasive imaging of mitochondrial dynamics. Cy5-PEG4 effectively labels mitochondria in primary neuronal cells exposed to the SARS-CoV-2 RNYIAQVD peptide, revealing dose-dependent alterations in mitochondrial function that may contribute to COVID-19-related neurodegeneration. Importantly, Cy5-PEG4 crosses the BBB without causing neuroinflammation or toxicity, making it a safe tool for in vivo brain imaging and detailed studies of mitochondrial responses. In 3D cultured cells, Cy5-PEG4 captures dynamic changes in mitochondrial distribution and morphology as cell structures mature, highlighting its potential in neurobiological research, diagnostics, and therapeutic development. These findings support Cy5-PEG4 as a powerful tool for studying disease progression, identifying early biomarkers, and evaluating therapeutic strategies in neurodegenerative disorders and COVID-19.

Posterior parietal cortex mediates rarity-induced decision bias and learning under uncertainty
Making decisions when outcomes are uncertain requires accurate judgment of the probability of outcomes, yet such judgments are often inaccurate, owing to reliance on heuristics that introduce systematic errors like overweighting of low probabilities. Here, using a decision-making task in which the participants were unaware of outcome probabilities, we discovered that both humans and mice exhibit a rarity-induced decision bias (RIDB), i.e., a preference towards rare rewards, which persists across task performance. Optogenetics experiments demonstrated that activity in the posterior parietal cortex (PPC) is required for the RIDB. Using in vivo electrophysiology, we found that rare rewards bidirectionally modulate choice-encoding PPC neurons to bias subsequent decisions towards rare rewards. Learning enhances stimulus-encoding of PPC neurons, which plays a causal role in stimulus-guided decisions. We then developed a dual-agent behavioural model that successfully recapitulates the decision-making and learning behaviours, and corroborates the specific functions of PPC neurons in mediating decision-making and learning. Thus, beyond expanding understanding of rare probability overweighting to a context where the outcome probability is unknown, and characterizing the neural basis for RIDB in the PPC, our study reveals an evolutionarily conserved heuristic that persistently impacts decision-making and learning under uncertainty.

Early perturbations to fluid homeostasis alter development of hypothalamic feeding circuits with context-specific changes in ingestive behavior
Drinking and feeding are tightly coordinated homeostatic events and the paraventricular nucleus of the hypothalamus (PVH) represents a possible node of neural integration for signals related to energy and fluid homeostasis. We used TRAP2;Ai14 and Fos labeling to visualize neurons in the PVH and median preoptic nucleus (MEPO) responding to both water deprivation and hunger. Moreover, we determined that structural and functional development of dehydration-sensitive inputs to the PVH from the MEPO precedes those of agouti-related peptide (AgRP) neurons, which convey hunger signals and are known to be developmentally programmed by nutrition. We also determined that osmotic hyperstimulation of neonatal mice led to enhanced AgRP inputs to the PVH in adulthood, as well as disruptions to ingestive behaviors during high-fat diet feeding and dehydration anorexia. Thus, development of feeding circuits is impacted not only by nutritional signals, but also by early perturbations to fluid homeostasis with context-specific consequences for coordination of ingestive behavior.

EEG-VLM Toolbox: Extending voxel-based lesion mapping to multi-dimensional EEG data
Focal brain lesions (such as with stroke) cause functional changes in local and distributed neural systems. While there is a long history of post-stroke neurophysiological assessment using electroencephalography (EEG), the observed neurophysiological changes have rarely been related to specific lesion locations. Therefore, the relationships between anatomical injury and physiological changes after stroke remain unclear. Voxel-based lesion symptom mapping (VLSM) is a tool for statistically relating stroke lesion locations to "symptoms", but current VLSM methods are restricted to symptoms that can be defined by a single value. Therefore, current VLSM techniques are unable to map the relationships between anatomical injury and multidimensional neurophysiological data such as EEG, which contains rich spatio-temporal information across different channels and frequency bands. Here we present a novel algorithm, EEG Voxel-based Lesion Mapping (EEG-VLM), that produces the set of significant relationships between precise neuroanatomical injury locations and neurophysiology (defined by a cluster of adjacent EEG channels and frequency bands). Further, the algorithm provides statistical analyses to define the overall significance of each neural structure-function relationship by correcting for multiple comparisons using a permutation test. Applying EEG-VLM to a dataset of recordings from chronic stroke patients performing a cued upper extremity movement task, we found that subjects with lesions in frontal subcortical white matter have reduced ipsilesional parietal cue-evoked EEG responses. These results are consistent with damage to a frontal-parietal network that has been associated with impairments in attention. EEG-VLM is a novel and unbiased method for relating neurophysiologic changes after stroke with neuroanatomic lesions. In the context of focal brain lesions associated with neurological impairments, we propose that this method will enable improved mechanistic understanding, facilitate biomarker development, and guide neurorehabilitation strategies.

The Interaction of UBR4, LRP1, and OPHN1 in Refractory Epilepsy: Drosophila Model to Investigate the Oligogenic Effect on Epilepsy
Refractory epilepsy is an intractable neurological disorder that is currently difficult to achieve effective pharmacological control in clinical practice and can result in poor quality of life as well as increased mortality. Genetic factors are important causes of epilepsy, especially idiopathic epilepsy. In the clinical gene sequencing work, we identified one refractory epileptic patient who carried three epileptogenic candidate genes: UBR4, LRP1, and OPHN1 variants. To clarify the epileptogenicity and interactions of UBR4, LRP1, and OPHN1 variants, as well as explore the role of each mutant gene in eliciting epilepsy, we established single-knockdown, double-knockdown, and triple-knockdown Drosophila models by suppressing the gene expression of these three epileptogenic candidate genes. After conducting behavioral testing for epilepsy in the seven Drosophila knockdown models, regression equations illustrating the causal connection between genotype and phenotype were developed. The mutations of the three epileptogenic candidate genes: UBR4, LRP1, and OPHN1, were proved to be epileptogenic at the animal level both in seizure rates and logistic regression results. Moreover, significant negative interactions in UBR4-OPHN1 KD and LRP1-OPHN1 KD were found in the trigenic KD system as well as the UBR4-OPHN1 and LRP1-OPHN1 digenic KD system according to the logistic regression analysis result. However, despite the existence of negative interaction, three groups of digenic KD flies and one group of trigenic KD flies presented higher seizure rates than that of the corresponding monogenic KD flies. LRP1-OPHN1 KD together with its negative interaction was regarded as the main causative factors for seizure in the UBR4-LRP1-OPHN1 KD.

The Oviposition Inhibitory Neuron is a potential hub of multi-circuit integration in the Drosophila brain
Understanding how neural circuits integrate sensory and state information to support context-dependent behavior is a central issue in neuroscience. In Drosophila, oviposition is a complex process in which the fly integrates context and sensory information to choose an optimal location to lay her eggs. The circuit that controls the oviposition sequence is known, but how the circuit integrates multiple sensory modalities and internal states is not. We investigated the neural circuitry underlying high-level processing related to oviposition using the Hemibrain connectome. We identified the Oviposition Inhibitory Neuron (oviIN) as a key hub in the oviposition circuit and analyzed its inputs to uncover potential parallel pathways that may be responsible for computations related to high-level decision-making. We applied graph-theoretic analyses on the sub-connectome of inputs to the oviIN to identify modules of neurons that may constitute novel circuits. Our findings indicate that the inputs to oviIN form multiple parallel pathways from the unstructured neuropils of the Superior Protocerebrum where high-level computations have been known to occur.

Alternatives to Friction Coefficient: Fine Touch Perception Relies on Frictional Instabilities
Fine touch perception is often correlated to material properties and friction coefficients, but the inherent variability of human motion has led to low correlations and contradictory findings. Instead, we hypothesized that humans use frictional instabilities to discriminate between objects. We constructed a set of coated surfaces with physical differences which were imperceptible by touch but created different types of instabilities based on how quickly a finger is slid and how hard a human finger is pressed during sliding. We found that participant accuracy in tactile discrimination most strongly correlated with formations of steady sliding, and response times negatively correlated with stiction spikes. Conversely, traditional metrics like surface roughness or average friction coefficient did not predict tactile discriminability. Identifying the central role of frictional instabilities as an alternative to using friction coefficients should accelerate the design of tactile interfaces for psychophysics and haptics.

High-precision neurofeedback-guided meditation training optimises real-world self-guided meditation practice for well-being
Meditation can benefit well-being and mental health, but novices often struggle to effectively recognize and disengage from mental processes during meditation due to limited awareness, potentially diminishing meditation's benefits. We investigated whether personalised high-precision neurofeedback (NF) can improve disengagement from mental activity during meditation and enhance meditation's outcomes. In a single-blind, controlled, longitudinal paradigm, 40 novice meditators underwent two consecutive days of meditation training with intermittent visual feedback from either their own (N=20) or a matched participant's (N=20; control group) posterior cingulate cortex (PCC) activity measured using 7 Tesla functional magnetic resonance imaging. During training, the experimental group showed stronger functional decoupling of PCC from dorsolateral prefrontal cortex, indicating better control over disengagement from mental processes during meditation. This led to greater improvements in emotional well-being and mindful awareness of mental processes during a week of real-world self-guided meditation. We provide compelling evidence supporting the utility of high-precision NF-guided meditation training to optimise real-world meditation practice for well-being.

Multisensory integration in Peripersonal Space indexes consciousness states in sleep and disorders of consciousness
Conscious experience encompasses not only the awareness of external objects, but also a phenomenal representation of the embodied subject of the experience. The latter is mediated by the integration of multisensory stimuli between the body and the environment, a process mediated by the Peripersonal Space (PPS) system. Here we thus tested the hypothesis that a neural marker of PPS representation may index the presence of conscious experience. Using high-density EEG in awake participants, we identified a PPS index, characterized by high-beta oscillations in centroparietal regions during the integration of audiotactile stimuli presented near versus far from the body. We then examined this marker across two models of altered consciousness, i.e., sleep and disorders of consciousness. The PPS index persisted during dreaming and waking conscious states but was absent during dreamless, unconscious states. Moreover, the same index predicted behavioural measures of consciousness and clinical outcome in patients recovering from disorders of consciousness. These results suggest that multisensory integration within the PPS is tightly linked to the presence of conscious experience.

Explicitly Acquired Interrelations Among Mental Schema Reduces Cognitive Load and Facilitates Emergence of Novel Responses in Mice and Artificial Neural Networks.
Mammalian brain has evolved to infer from past experiences and elicit context relevant novel behavioural responses hitherto unexpressed by the animal. Little is known about if and how prior knowledge affect emergence of such novel responses. Remarkably, our brain not only arrives at these responses through logical inferences but can also preserve these related memories distinctly without catastrophic interference. Often mental schema has been proposed to be the framework for such phenomenon. In this study, using mice as a model animal, we show that schematic networks not only enhance the cognitive load handling capacity (CLHC) preventing catastrophic interference, but also enable the generation of novel responses that are context relevant. Interestingly, when the animals were trained in a paradigm that did not invoke the pre-formed mental schema, we observed neither an enhancement to CLHC nor a generation of novel context relevant responses. Using these principles of mental schema that we discovered from our animal experiments, we develop a neurologically relevant ANN that avoids catastrophic interference and captures all the properties associated with different modes of learning tested in our experiments. The custom architecture of the ANN enables it to generate responses similar to animals in novel scenario.

Sex Differences in Contextual Extinction Learning After Single Binge-Like EtOH Exposure in Adolescent C57BL/6J Mice
The relationship between chronic heavy drinking and post-traumatic stress disorder (PTSD) is well-documented; however, the impact of more common drinking patterns, such as a single episode leading to a blood alcohol concentration (BAC) of 0.09 g/dL (moderate intoxication), remains underexplored. Given the frequent co-occurrence of PTSD and alcohol misuse, it is essential to understand the biological and behavioral factors driving this comorbidity. We hypothesize that alcohol's immediate sedative effects are coupled with the development of persistent molecular alcohol tolerance, which may disrupt fear extinction learning. To investigate this, we employed a Single Episode Ethanol (SEE) in-vivo exposure to mimic binge-like alcohol consumption over a 6-hour period, following contextual conditioning trials. Extinction trials were conducted 24 hours later to assess the effects on extinction learning. Our findings reveal a significant deficit in fear extinction learning in alcohol-treated adolescent male mice compared to saline-treated controls, with no such effects observed in female adolescent mice. These results suggest that even non-chronic alcohol exposure may contribute to the development of trauma- and stress-related disorders, such as PTSD, in males. Additionally, histological analysis revealed significant alterations in FKBP5, beta-catenin, and GSK-3beta levels in the hippocampus, striatum, and basolateral amygdala of alcohol-treated mice following extinction. The insights gained from this study could reshape our understanding of the risk factors for PTSD and open new avenues for prevention and treatment, targeting the molecular mechanisms that mediate alcohol tolerance.

Microglia respond to elevated intraocular pressure and synapse loss in the visual thalamus in a mouse model of glaucoma.
Microglia are resident immune cells of the central nervous system and mediate a broad array of adaptations and responses during disease, injury, and development. Typically, microglia morphology is understood to provide a window into their functional state. However, it is apparent that they have the capacity to adopt a broad spectrum of functional phenotypes characterized by numerous morphological profiles and associated gene expression profiles. Glaucoma, which leads to blindness from retinal ganglion cell (RGC) degeneration, is commonly associated with elevated intraocular pressure and has been shown to trigger microglia responses within the retinal layers, at the optic nerve head, and in retinal projection targets in the brain. The goal of this study was to determine the relationship of microglia morphology to intraocular pressure and the loss of retinal ganglion cell output synapses in the dorsolateral geniculate nucleus (dLGN), a RGC projection target in the thalamus that conveys information to the primary visual cortex. We accomplished this by analyzing dLGN microglia morphologies in histological sections from DBA/2J mice, which develop a form of inherited glaucoma. Microglia morphology was analyzed using skeletonized Iba1-fluorescence images and fractal analyses of individually reconstructed microglia cells. We found that microglia adopted more simplified morphologies, characterized by fewer endpoints and less total process length per microglia cell. There was an age-dependent shift in microglia morphology in tissue from control mice (DBA/2JGpnmb+) that was accelerated in DBA/2J mice. Microglia morphological measurements correlated with cumulative intraocular pressure, immunofluorescence labeling for the complement protein C1q, and density of vGlut2-labeled RGC axon terminals. Additionally, fractal analysis revealed a clear distinction between control and glaucoma dLGN, with microglia from ocular hypertensive DBA/2J dLGN tissue showing an elongated rod-like morphology. RNA-sequencing of dLGN tissue samples showed an upregulation of immune system-related gene expression and several specific genes associated with microglia activation and potential neuroprotective functions. These results suggest that microglia in the dLGN alter their physiology to respond to RGC degeneration in glaucoma, potentially contributing to CNS adaptations to neurodegenerative vision loss.

Connexin 43 mediated mitochondrial transfer prevents cisplatin induced sensory neurodegeneration.
Platinum based chemotherapeutics cisplatin are front-line treatments for paediatric and adult cancer. Despite advancements in medical interventions chemotherapy-induced peripheral sensory neuropathy is a common adverse health related complication that can persist for the long-term and impacts upon individuals quality of life. Recently, the causes of chemotherapy induced sensory neurodegeneration has been linked to sensory neuronal mitochondrial dysfunction. Here this study investigated cisplatin induced sensory neurodegeneration and how donation of monocytic mitochondria to recipient cisplatin damaged dorsal root ganglia (DRG) sensory neurons prevent platinum-based chemotherapy-induced sensory neurotoxicity. Neuronal cell line, SH-SY5Y, or mouse DRG sensory neurons were treated with either vehicle or cisplatin, and co-cultured with mitotracker-labelled THP1 monocytes. Cisplatin induced dysmorphic mitochondria and shifted to a glycolytic dependent energy production, with diminishment in oxidative phosphorylation in cisplatin treated dorsal root ganglia sensory neurons. DRG sensory neurons exposed to cisplatin were recipients of monocyte mitochondria indicated by increased intracellular mitotracker fluorescent labelling. Mitochondrial transfer to sensory neurons was neuroprotective by preventing neurite loss and neuronal apoptosis. Vehicle treated DRG sensory neurons did not demonstrate significant mitochondrial uptake. Furthermore, cisplatin induced mitochondrial transfer was prevented by pharmacological inhibition of gap junction protein, connexin 43. Connexin 43 inhibition led to reduced neuroprotective capacity via mitochondrial transfer. These findings demonstrate that monocytic mitochondria transfer to DRG sensory neurons damaged by cisplatin is dependent upon gap junction intercellular communication to promote sensory neuronal survival. This novel process in sensory neuronal protection is a potential novel therapeutic intervention for alleviating neuropathic pain in individuals treated for cancer.

'Mini analysis' is an unreliable reporter of synaptic changes
Analysis of miniature postsynaptic currents (mPSCs, or 'minis') is one of the most extensively employed approaches to determine the functional properties of synaptic connections. The popularity of this technique stems from its simplicity. Patch-clamp recording is used to observe spontaneous transmission occurring at synapses throughout a neuron's dendritic tree. These events are analysed in an attempt to determine quantal synaptic parameters and changes during experimental manipulation. For decades, changes in the amplitude or frequency of mPSCs have been interpreted as evidence for specific synaptic modifications, including changes in presynaptic release sites, postsynaptic receptor abundance or even nanoscale changes in the alignment of synaptic machinery. However, at the majority of brain synapses, these events are small, with many undetectable due to recording noise. Here, using both simulated and experimental data, we demonstrate that interpreting synaptic changes from mPSC datasets is fundamentally fallible. Due to incomplete detection of event distributions, seemingly specific changes in mPSC amplitude or frequency falsely report actual synaptic changes. In addition, probabilistic detection of small events gives false confidence in the completeness of detection and inaccurate determination of quantal size. We not only demonstrate the dense pitfalls of mini analysis, but also establish a method for experimental detection of the detection limit, allowing more robust data analysis and scientific interpretation.

Imaging synaptic density in ageing and Alzheimer's Disease with -SynVesT-1
Monitoring synaptic injury in neurodegenerative diseases may provide new insights into the evolution of the degenerative process as well as a potential mechanism to target for preservation of function. Synaptic density imaging with PET is a relatively new approach to this issue. However, there are remaining questions about technical approaches to data analysis including reference region selection, and how specific phenotypic presentations and symptoms of Alzheimer's Disease (AD) are reflected in alterations in synaptic density. Methods: Using an SV2A PET ligand radiolabeled with the 18F isotope ([18F]-SynVesT-1) we performed sensitivity analyses to determine the optimal reference tissue modelling approach to derive whole brain ratio images. Using these whole brain images from a sample of young adults, older adults, and patients with varied phenotypic presentations of AD we then contrast regional SV2A density and in vivo AD biomarkers. Result: Reference tissue optimisation concluded that a cerebellar grey matter reference region is best for deriving whole brain ratio images. Using these whole brain ratio images, we find a strong inverse association between [18F]-SynVesT-1 PET uptake and amyloid beta and tau PET deposition. Finally, we find that individuals with lower temporal grey matter volume but higher temporal [18F]-SynVesT-1 PET uptake show preserved performance on the MMSE. Conclusions: [18F]-SynVesT-1 PET shows a close association with in vivo AD pathology and preserved SV2A density may be a possible marker for resilience to neurodegeneration.

Testing the Tests: Using Connectome-Based Predictive Models to Reveal the Systems Standardized Tests and Clinical Symptoms Are Reflecting
Neuroimaging has achieved considerable success in elucidating the neurophysiological underpinnings of various brain functions. Tools such as standardized cognitive tests and symptom inventories have played a crucial role in informing neuroimaging studies, helping to uncover the underlying brain systems associated with these measures. Substantial strides have been taken in developing models, such as connectome-based predictive modeling (CPM), that establish connections between external measures and the human connectome, offering insights into how the functional organization of the brain varies in relation to scores on external measures. Here, we depart from the conventional feed-forward approach and introduce a feed-back approach that allows testing of the tests. Since the inception of cognitive psychology over 60 years ago, cognitive tests have been meticulously developed to measure specific components of cognition. These tests, which have undergone extensive validation and have been standardized and administered to millions, operate on explicit assumptions about the cognitive components they assess. Rather than using external tests to identify the circuits supporting test scores, we a priori define networks of interest and quantify the extent to which these circuits support the test measure. To demonstrate this, we define functional connectivity networks for six cognitive constructs and quantify their contribution to performance across a spectrum of standardized cognitive tests and clinical measures. Employing robust machine learning in a predictive modeling framework, we show how this approach can be used to select tests according to the networks they rely upon. This establishes a biologically grounded metric for test comparison. This approach also yields a brain-driven process for forming composite tests by selecting test combinations that depend on the same proportional brain systems, or for a single network of interest, combining tests with the highest predictive power for that network. This brain-driven approach results in more robust behavioral assessments and enhanced predictive power for the network of interest. We illustrate how this methodology can be applied to evaluate the inclusion of specific sub-tests within a composite score, revealing instances where composite scores are reinforced or weakened by subtest inclusion in terms of the specificity of the brain network they interrogate. The brain-test score modeling approach presented here provides a biologically driven approach to the selection of external cognitive and symptom measures directed at specific brain systems. It opens new avenues of research by providing a framework for the development of new tests and measures guided by quantitative brain metrics.