bioRxiv Subject Collection: Neuroscience's Journal

Valine and Inflammation Drive Epilepsy in a Mouse Model of ECHS1 Deficiency
ECHS1 Deficiency (ECHS1D) is a rare and devastating pediatric disease that currently has no defined treatments. This disorder results from missense loss-of-function mutations in the ECHS1 gene that result in severe developmental delays, encephalopathy, hypotonia, and early death. ECHS1 enzymatic activity is necessary for the beta-oxidation of fatty acids and the oxidation of branched-chain amino acids within the inner mitochondrial matrix. The pathogenesis of disease remains unknown, however it is hypothesized that disease is driven by an accumulation of toxic metabolites from impaired valine oxidation. To expand our knowledge on disease mechanisms, a novel mouse model of ECHS1D was generated that possesses a disease-associated knock-in (KI) allele and a knock-out (KO) allele. To investigate the behavioral phenotype, a battery of testing was performed at multiple time points, which included assessments of learning, motor function, endurance, sensory responses, and anxiety. Neurological abnormalities were assessed using wireless telemetry EEG recordings, pentylenetetrazol (PTZ) seizure induction, and immunohistochemistry. Metabolic perturbations were measured within the liver, serum, and brain using mass spectrometry and magnetic resonance spectroscopy. To test disease mechanisms, mice were subjected to disease pathway stressors and then survival, body weight gain, and epilepsy were assessed. Mice containing KI/KI or KI/KO alleles were viable with normal development and survival, and the presence of KI and KO alleles resulted in a significant reduction in ECHS1 protein. ECHS1D mice displayed reduced exercise capacity and pain sensation. EEG analysis revealed increased slow wave power that was associated with perturbations in sleep. ECHS1D mice had significantly increased epileptiform EEG discharges, and were sensitive to seizure induction, which resulted in death of 60% of ECHS1D mice. Under basal conditions, brain structure was grossly normal, although histological analysis revealed increased microglial activation in aged ECHS1D mice. Increased dietary valine only affected ECHS1D mice, which significantly exacerbated seizure susceptibility and resulted in death. Lastly, acute inflammatory challenge drove regression and early lethality in ECHS1D mice. In conclusion, we developed a novel model of ECHS1D that may be used to further knowledge on disease mechanisms and to develop therapeutics. Our data suggests altered metabolic signaling and inflammation may contribute to epilepsy in ECHS1D, and these alterations may be attributed to impaired valine metabolism.

Comparative connectomics of two distantly related nematode species reveals patterns of nervous system evolution
Understanding the evolution of the bilaterian brain requires a detailed exploration of the precise nature of cellular and subcellular differences between related brains. To define the anatomical substrates of evolutionary change in the nervous system, we undertook an electron micrographic reconstruction of the brain of the predatory nematode Pristionchus pacificus. A comparison with the brain of Caenorhabditis elegans, which diverged at least 100 million years ago, reveals a conserved nematode core connectome and a wide range of specific substrates of evolutionary change. These changes include differences in neuronal cell death, neuronal cell position, axo-dendritic projection patterns and many changes in synaptic connectivity of homologous neurons that display no obvious changes in overall neurite morphology and projection patterns. Differences in connectivity are distributed throughout the nervous system arguing against specific hot spots of evolutionary change and extend to differences in neuro/glia connectivity. We observed examples of apparent circuit drift, where changes in morphology and connectivity of a neuron do not appear to alter its behavioral output. In conclusion, our comprehensive comparison of distantly related nematode species provides novel vistas on patterns of conservation as well as the substrates of evolutionary change in the brain that span multiple organizational levels.

A NEW POSTURAL MOTOR RESPONSE TO SPINAL CORD STIMULATION: POST-STIMULATION REBOUND EXTENSION
Spinal cord stimulation (SCS) has emerged as a therapeutic tool for improving motor function following spinal cord injury. While many studies focus on restoring locomotion, little attention is paid to enabling standing which is a prerequisite of walking. In this study, we fully characterize a new type of response to SCS, a long extension activated post-stimulation (LEAP). LEAP is primarily directed to ankle extensors and hence has great clinical potential to assist postural movements. To characterize this new response, we used the decerebrate cat model to avoid the suppressive effects of anesthesia, and combined EMG and force measurement in the hindlimb with intracellular recordings in the lumbar spinal cord. Stimulation was delivered as five-second trains via bipolar electrodes placed on the cord surface, and multiple combinations of stimulation locations (L4 to S2), amplitudes (50-600 uA), and frequencies (10-40 Hz) were tested. While the optimum stimulation location and frequency differed slightly among animals, the stimulation amplitude was key for controlling LEAP duration and amplitude. To study the mechanism of LEAP, we performed in vivo intracellular recordings of motoneurons. In 70% of motoneurons, LEAP increased at hyperpolarized membrane potentials indicating a synaptic origin. Furthermore, spinal interneurons exhibited changes in firing during LEAP, confirming the circuit origin of this behavior. Finally, to identify the type of afferents involved in generating LEAP, we used shorter stimulation pulses (more selective for proprioceptive afferents), as well as peripheral stimulation of the sural nerve (cutaneous afferents). The data indicates that LEAP primarily relies on proprioceptive afferents and has major differences from pain or withdrawal reflexes mediated by cutaneous afferents. Our study has thus identified and characterized a novel postural motor response to SCS which has the potential to expand the applications of SCS for patients with motor disorders.

Contribution of neurons that express fruitless and Clock transcription factors to behavioral rhythms and courtship
Animals need to integrate information across neuronal networks that direct reproductive behaviors and circadian rhythms. In Drosophila, the master regulatory transcription factors that direct courtship behaviors and circadian rhythms are co-expressed in a small set of neurons. In this study we investigate the role of these neurons in both males and females. We find sex-differences in the number of these fruitless and Clock -expressing neurons (fru {Omega} Clk neurons) that is regulated by male-specific Fru. We assign the fru {Omega} Clk neurons to the electron microscopy connectome that provides high resolution structural information. We also discover sex-differences in the number of fru-expressing neurons that are post-synaptic targets of Clk-expressing neurons, with more post-synaptic targets in males. When fru {Omega} Clk neurons are activated or silenced, males have a shorter period length. Activation of fru {Omega} Clk neurons also changes the rate a courtship behavior is performed. We find that activation and silencing fru {Omega} Clk neurons impacts the molecular clock in the sLNv master pacemaker neurons, in a cell-nonautonomous manner. These results reveal how neurons that subserve the two processes, reproduction and circadian rhythms, can impact behavioral outcomes in a sex-specific manner.

Automatic sleep scoring for real-time monitoring and stimulation in individuals with and without sleep apnea
Digital therapeutics, enabled by advanced machine learning algorithms and medical wearable devices, offer a promising approach to streamline diagnostics and improve access to healthcare. Within this framework, automatic sleep scoring can provide accurate and efficient sleep analysis from electrophysiological signals recorded with wearable sensors, such as electroencephalography (EEG). However, the optimal configuration and temporal dynamics of automatic sleep scoring systems remain unclear, especially concerning their performance across different population samples. This study systematically investigates the impact of electrode setup, temporal scope, and population characteristics on the performance of automatic sleep scoring algorithms. Utilizing a convolutional neural network (CNN) model, we analyzed various electrode configurations and temporal dynamics using datasets comprising both healthy participants and individuals with sleep apnea. Our findings reveal that sleep scoring based on a single frontal EEG channel demonstrates reliable congruency with human expert scorers, with minimal improvement observed with additional sensors. Moreover, we demonstrate that real-time sleep scoring can be achieved with comparable accuracy to offline methods, which rely on past and future information to classify a window of interest. Remarkably, a notable reduction in decoding accuracy is observed for individuals with sleep disorders compared to healthy participants, highlighting the challenges inherent in accurately assessing sleep stages in clinical populations. Digital solutions for automatic sleep scoring hold promise for facilitating timely diagnoses and personalized treatment plans, with applications extending beyond sleep analysis to include closed-loop neurostimulation interventions. Our findings provide valuable insights into the complexities of automatic sleep scoring and offer considerations for the development of effective and efficient sleep assessment tools in both clinical and research settings.

An optimized method to visualize lipid droplets in brain tissue demonstrates their substantial accumulation in aged brains
Lipid droplets (LDs) are cellular stores for lipids. These organelles have recently gained interest in neuroscience because they accumulate in various cell types in neurodegenerative diseases. However, their role under physiological conditions is still not fully understood. Classical LD staining methods, which use lipophilic dyes like BODIPY 493/503 (BD493) or antibodies against LD coat proteins, show very few LDs in healthy brain tissue. Our recently developed novel endogenous LD reporter mouse challenges this view. We have been able to detect numerous LDs in healthy brain tissue from both adult and developing mice without staining. To understand why classical staining and endogenous labeling yield different results, we thoroughly investigated the effects of tissue preparation and detergent used in LD detection. We found that BD493 works poorly in brain tissue, while other lipophilic dyes visualize many LDs. We also found that antibody-based LD detection depends on tissue pretreatment and detergent concentration but can reveal a similar number of LDs as observed with the endogenous LD reporter mouse. Taken together, we here present an optimized procedure for LD detection in brain tissue using commercially available dyes and antibodies. Using these methods, we demonstrate that LDs are numerous in healthy brain tissue and substantially accumulate in aged brains in various cell types, including neurons.

Consistency of affective responses to naturalistic stimuli across individuals using intersubject correlation analysis based on neuroimaging data
In this study, we used functional magnetic resonance imaging (fMRI) data obtained for naturalistic emotional stimuli to examine the consistency of neural responses among participants in specific regions related to valence. We reanalyzed fMRI data from 17 participants as they watched episodes of "Sherlock" and used emotional ratings from 125 participants. To determine regions where neural response patterns were synchronized across participants based on the pattern of valence changes, intersubject correlation analysis was conducted. As a validation analysis, multidimensional scaling was conducted to investigate emotional representation for significant regions of interest. The results revealed that the ventromedial prefrontal cortex, bilateral superior frontal cortices, left posterior cingulate cortex, thalamus, right anterior cingulate cortex, and bilateral inferior frontal cortices showed increased neural synchrony as positive scenes were presented. Also, the bilateral superior temporal gyrus and bilateral medial temporal gyrus exhibited increased neural synchrony as negative scenes were presented. Moreover, the left inferior frontal cortex and right superior frontal gyrus were found to be engaged in emotion representation and display increased neural synchrony. These findings provide insights into the differential neural responses to emotionally evocative naturalistic stimuli as compared to conventional experimental stimuli. Also, this study highlights the future potential for using intersubject correlation analysis for examining consistency of neural responses to naturalistic stimuli.

DySCo: a general framework for dynamic Functional Connectivity
A crucial challenge in neuroscience involves characterising brain dynamics from high-dimensional brain recordings. Dynamic Functional Connectivity (dFC) is an analysis paradigm that aims to address this challenge. dFC consists of a time-varying matrix (dFC matrix) expressing how pairwise interactions across brain areas change with time. However, the main dFC approaches have been developed and applied mostly empirically, lacking a unifying theoretical framework, a general interpretation, and a common set of measures to quantify the dFC matrices properties. Moreover, the dFC field has been lacking ad-hoc algorithms to compute and process the matrices efficiently. This has prevented the field to show its full potential with high-dimensional datasets and/or real time applications. With this paper, we introduce the Dynamic Symmetric Connectivity Matrix analysis framework (DySCo), with its associated repository. DySCo is a unifying approach that allows the study brain signals at different spatio-temporal scales, down to voxel level, that is computationally ultrafast. DySCo unifies in a single theoretical framework the most employed dFC matrices, which share a common mathematical structure. Doing so it allows: 1) A new interpretation of dFC that further justifies its use to capture the spatiotemporal patterns of data interactions in a form that is easily translatable across different imaging modalities. 2) The introduction of the the Recurrence Matrix EVD to compute and store the eigenvectors and eigenvalues of all types of dFC matrices in an efficent manner that is orders of magnitude faster than naive algorithms, and without loss of information. 3) To simply define quantities of interest for the dynamic analyses such as: the amount of connectivity (norm of a matrix) the similarity between matrices, their informational complexity. The methodology developed here is validated on both a synthetic dataset and a rest/N-back task experimental paradigm - the fMRI Human Connectome Project dataset. We demonstrate that all the measures proposed are highly sensitive to changes in brain configurations. To illustrate the computational efficiency of the DySCo toolbox, we perform the analysis at the voxel-level, a computationally very demanding task which is easily afforded by the RMEVD algorithm.

GABAB receptors mediate intracellular calcium release in astrocytes of the prefrontal cortex
The prefrontal cortex (PFC) is a cortical brain region whose multifaceted functions are based on a complex interplay between excitatory pyramidal neurons, inhibitory GABAergic interneurons and astrocytes maintaining a fine tuned excitation/inhibition balance (E/I balance). The regulation of the E/I balance in cortical network is crucial as the disruption leads to impairments in PFC associated behavior and pathologies. Astrocytes express specific GABA receptors that mediate intracellular Ca2+ signaling upon stimulation by GABA, resulting in the release of gliotransmitters directly impacting information processing. However, the signaling pathway leading to GABA-induced Ca2+ signaling in astrocytes of the PFC is not well understood. Here we took advantage of GLAST promoter driven GCaMP6s expression in astrocytes to study GABAergic Ca2+ signaling in PFC astrocytes by confocal microscopy. The results show that GABA induces Ca2+ signaling via the stimulation of the metabotropic GABAB receptor in astrocytes. GABAB receptor-mediated Ca2+ signals greatly depend on intracellular Ca2+ stores rather than on extracellular Ca2+. Additionally, antagonists of the PLC/IP3-signaling cascade significantly reduced GABAB receptor-mediated Ca2+ signaling in astrocytes, suggesting that astrocytic GABAB receptors in the PFC are coupled to the Gq-GPCR signaling pathway.

Anterior Cingulate Cortex Causally Supports Meta-Learning
In dynamic environments with volatile rewards the anterior cingulate cortex (ACC) is believed to determine whether a visual object is relevant and should be chosen. The ACC may achieve this by integrating reward information over time to estimate which objects are worth to explore and which objects should be avoided. Such a higher-order meta-awareness about which objects should be explored predicts that the ACC causally contributes to choices when the reward values of objects are unknown and must be inferred from ongoing exploration. We tested this suggestion in nonhuman primates using a learning task that varied the number of object features that could be relevant, and by controlling the motivational value of choosing objects. During learning the ACC was transiently micro-stimulated when subjects foveated the to-be-chosen stimulus. We found that stimulation selectively impaired learning when feature uncertainty and motivational value of choices were high, which was linked to a deficit in using reward outcomes for feature-specific credit assignment. Application of an adaptive reinforcement learning model confirmed a primary deficit in weighting prediction errors that led to a meta-learning impairment to adaptively increase exploration during learning and to an impaired use of working memory to support learning. These findings provide causal evidence that the reward history traces in ACC are essential for meta-adjusting the exploration-exploitation balance and the strength of working memory of object values during adaptive behavior.

Studying time-resolved functional connectivity via communication theory: on the complementary nature of phase synchronization and sliding window Pearson correlation.
Time-resolved functional connectivity (trFC) assesses the time-resolved coupling between brain regions using functional magnetic resonance imaging (fMRI) data. This study aims to compare two techniques used to estimate trFC, to investigate their similarities and differences when applied to fMRI data. These techniques are the sliding window Pearson correlation (SWPC), an amplitude-based approach, and phase synchronization (PS), a phase-based technique. To accomplish our objective, we used resting-state fMRI data from the Human Connectome Project (HCP) with 827 subjects (repetition time: 0.7s) and the Function Biomedical Informatics Research Network (fBIRN) with 311 subjects (repetition time: 2s), which included 151 schizophrenia patients and 160 controls. Our simulations reveal distinct strengths in two connectivity methods: SWPC captures high-magnitude, low-frequency connectivity, while PS detects low-magnitude, high-frequency connectivity. Stronger correlations between SWPC and PS align with pronounced fMRI oscillations. For fMRI data, higher correlations between SWPC and PS occur with matched frequencies and smaller SWPC window sizes (~30s), but larger windows (~88s) sacrifice clinically relevant information. Both methods identify a schizophrenia-associated brain network state but show different patterns: SWPC highlights low anti-correlations between visual, subcortical, auditory, and sensory-motor networks, while PS shows reduced positive synchronization among these networks. Our findings underscore the complementary nature of SWPC and PS, elucidating their respective strengths and limitations without implying the superiority of one over the other.

Sequential emergence and contraction of epithelial subtypes in the prenatal human choroid plexus revealed by a stem cell model
Despite the major roles of choroid plexus epithelial cells (CPECs) in brain homeostasis and repair, their developmental lineage and diversity remain undefined. In simplified differentiations from human pluripotent stem cells, derived CPECs (dCPECs) displayed canonical properties and dynamic multiciliated phenotypes that interacted with A{beta} uptake. Single dCPEC transcriptomes over time correlated well with human organoid and fetal CPECs, while pseudotemporal and cell cycle analyses highlighted the direct CPEC origin from neuroepithelial cells. In addition, time series analyses defined metabolic (type 1) and ciliogenic dCPECs (type 2) at early timepoints, followed by type 1 diversification into anabolic-secretory (type 1a) and catabolic-absorptive subtypes (type 1b) as type 2 cells contracted. These temporal patterns were then confirmed in independent derivations and mapped to prenatal stages using human tissues. In addition to defining the prenatal lineage of human CPECs, these findings suggest new dynamic models of ChP support for the developing human brain.

Leveraging the transient statistics of quantal content to infer neuronal synaptic transmission
Quantal parameters of synapses are fundamental for the temporal dynamics of neurotransmitter release, forming the basis of interneuronal communication. We propose a class of models that capture the stochastic dynamics of quantal content (QC) - the number of SV fusion events per action potential (AP). Considering the probabilistic and time-varying nature of SV docking, undocking, and AP-triggered fusion, we derive an exact statistical distribution for the QC over time. Analyzing this distribution at steady-state and its associated autocorrelation function, we show that QC fluctuation statistics can be leveraged for inferring key presynaptic parameters, such as the probability of SV fusion (release probability), and SV replenishment at empty docking sites (refilling probability). Our model predictions are tested with electrophysiological data obtained from 50-Hz stimulation of auditory MNTB-LSO synapses in brainstem slices of juvenile mice. Our results show that while synaptic depression can be explained by low and constant refilling/release probabilities, this scenario is inconsistent with the statistics of the electrophysiological data that show a low QC Fano factor and almost uncorrelated successive QCs. Our systematic analysis yields a model that couples a high release probability to a time-varying refilling probability to explain both the synaptic depression and its associated statistical fluctuations. In summary, we provide a general approach that exploits stochastic signatures in QCs to infer neurotransmission-regulating processes that are indistinguishable from just analyzing averaged synaptic responses.

Regional Brain Entropy During Movie-watching
Brain entropy (BEN) measures the irregularity or unpredictability of brain activity. Our previous studies have showcased the neurocorrelates and disease sensitivity of regional BEN. Task performance and neuromodulations as well as medications can modulate regional BEN. Movie-watching engages multiple-domain cognitions and complex brain activities mimicking the complex real world and has been increasingly used to probe brain state dynamics. The sustained multiple-domain cognitive activities would cause sustained changes to regional BEN, which however remains unknown. The purpose of this study was to address this gap. We first aimed to examine whether the fMRI-derived regional BEN represents a stable brain activity index during repeated measurement with or without movie-watching. We then assessed the movie-watching-induced regional BEN changes compared to resting state and regional BEN differences between different movie clips. we found higher reliability during movie-watching and movie-watching induced lower BEN in the sensory cortex and higher BEN in the association cortex compared to the resting state. We replicated and validated all findings in test-retest clips. This work systematically evaluated the regional BEN during movie-watching, providing a new direction for exploring brain activity under natural paradigms using BEN.

Single-Mitochondrion Sequencing Uncovers Distinct Mutational Patterns and Heteroplasmy Landscape in Mouse Astrocytes and Neurons.
Background: Mitochondrial (mt) heteroplasmy can cause adverse biological consequences when deleterious mtDNA mutations accumulate disrupting normal mt-driven processes and cellular functions. To investigate the heteroplasmy of such mtDNA changes we developed a moderate throughput mt isolation procedure to quantify the mt single-nucleotide variant (SNV) landscape in individual mouse neurons and astrocytes In this study we amplified mt-genomes from 1,645 single mitochondria (mts) isolated from mouse single astrocytes and neurons to 1. determine the distribution and proportion of mt-SNVs as well as mutation pattern in specific target regions across the mt-genome,2. assess differences in mtDNA SNVs between neurons and astrocytes, and 3. Study cosegregation of variants in the mouse mtDNA. Results: 1. The data show that specific sites of the mt-genome are permissive to SNV presentation while others appear to be under stringent purifying selection. Nested hierarchical analysis at the levels of mitochondrion, cell, and mouse reveals distinct patterns of inter- and intra-cellular variation for mt-SNVs at different sites. 2. Further, differences in the SNV incidence were observed between mouse neurons and astrocytes for two mt-SNV 9027:G>A and 9419:C>T showing variation in the mutational propensity between these cell types. Purifying selection was observed in neurons as shown by the Ka/Ks statistic, suggesting that neurons are under stronger evolutionary constraint as compared to astrocytes. 3. Intriguingly, these data show strong linkage between the SNV sites at nucleotide positions 9027 and 9461. Conclusion: This study suggests that segregation as well as clonal expansion of mt-SNVs is specific to individual genomic loci, which is important foundational data in understanding of heteroplasmy and disease thresholds for mutation of pathogenic variants.

Prosapip1 in the dorsal hippocampus mediates synaptic protein composition, long-term potentiation, and spatial memory
Prosapip1 is a brain-specific protein localized to the postsynaptic density, where it promotes dendritic spine maturation in primary hippocampal neurons. However, nothing is known about the role of Prosapip1 in vivo. To examine this, we utilized the Cre-loxP system to develop a Prosapip1 neuronal knockout mouse. We found that Prosapip1 controls the synaptic localization of its binding partner SPAR, along with PSD-95 and the GluN2B subunit of the NMDA receptor (NMDAR) in the dorsal hippocampus (dHP). We next sought to identify the potential contribution of Prosapip1 to the activity and function of the NMDAR and found that Prosapip1 plays an important role in NMDAR-mediated transmission and long-term potentiation (LTP) in the CA1 region of the dHP. As LTP is the cellular hallmark of learning and memory, we examined the consequences of neuronal knockout of Prosapip1 on dHP-dependent memory. We found that global or dHP-specific neuronal knockout of Prosapip1 caused a deficit in learning and memory whereas developmental, locomotor, and anxiety phenotypes were normal. Taken together, Prosapip1 in the dHP promotes the proper localization of synaptic proteins which, in turn, facilitates LTP driving recognition, social, and spatial learning and memory.

Miniscope Recording Calcium Signals at Hippocampus of Mice Navigating an Odor Plume
Mice are able to navigate an odor plume with a complex spatiotemporal structure in the dark to find the source of odorants. We developed a protocol to monitor behavior and record Ca2+ transients in dorsal CA1 stratum pyramidale neurons at the hippocampus (dCA1) in mice navigating an odor plume in a 50 cm x 50 cm x 25 cm odor arena. Ca2+ transients were imaged by an epifluorescence miniscope focused through a GRIN lens on dCA1 neurons expressing the calcium sensor GCaMP6f in Thy1-GCaMP6f mice. We describe the behavioral protocol to train the mice to perform this odor plume navigation task in an automated odor arena. We provide the step-by-step procedure for the surgery for GRIN lens implantation and baseplate placement for imaging GCaMP6f in CA1. We provide information on real time tracking of the mouse position to automate the start of the trials and delivery of a sugar water reward. In addition, we provide information on the use of an Intan board to synchronize metadata describing the automation of the odor navigation task and frame times for the miniscope and a FLIR camera tracking mouse position. Moreover, we delineate the pipeline used to process GCaMP6f fluorescence movies by motion correction using NorMCorre followed by identification of regions of interest (ROIs) with EXTRACT. Finally, we describe use of artificial neural network (ANN) machine learning to decode spatial paths from CA1 neural ensemble activity to predict mouse navigation of the odor plume.

Tripartite organization of brain state dynamics underlying spoken narrative comprehension
Speech comprehension involves the dynamic interplay of multiple cognitive processes, from basic sound perception, to linguistic encoding, and finally to complex semantic-conceptual interpretations. How the brain handles the diverse streams of information processing remains poorly understood. Applying Hidden Markov Modeling to fMRI data obtained during spoken narrative comprehension, we reveal that the whole brain networks predominantly oscillate within a tripartite latent state space. These states are respectively characterized by high activities in the sensory-motor (State #1), bilateral temporal (State #2), and DMN (State #3) regions, with State #2 acting as a transitional hub. The three states are selectively modulated by the acoustic, word-level semantic and clause-level semantic properties of the narrative. Moreover, the alignment with the best performer in brain state expression can predict participants' narrative comprehension scores. These results are reproducible with different brain network atlas and generalizable to two independent datasets consisting of young and older adults. Our study suggests that the brain underlies narrative comprehension by switching through a tripartite state space, with each state probably dedicated to a specific component of language faculty, and effective narrative comprehension relies on engaging those states in a timely manner.

Revealing heterogeneity in dementia using data-driven unsupervised clustering of cognitive profiles
Dementia is characterized by a decline in memory and thinking that is significant enough to impair function in activities of daily living. Patients seen in dementia specialty clinics are highly heterogenous with a variety of different symptoms that progress at different rates. Recent research has focused on finding data-driven subtypes for revealing new insights into dementia's underlying heterogeneity, compared to analyzing the entire cohort as a single homogeneous group. However, existing studies on dementia subtyping suffer from the following limitations: (i) focusing on AD-related dementia only and not examining heterogeneity within dementia as a whole, (ii) using only cross-sectional baseline visit information for clustering and (iii) predominantly relying on expensive imaging biomarkers as features for clustering. In this study, we used a data-driven unsupervised clustering algorithm named SillyPutty, in combination with hierarchical clustering on neuropsychological assessment scores to estimate subtypes within a real-world clinical dementia cohort. We incorporated all longitudinal patient visits into our clustering analysis, instead of relying only on baseline visits, allowing us to explore the ongoing relationship between subtypes and disease progression over time. Results showed evidence of (i) subtypes with very mild or mild dementia being more heterogenous in their cognitive profiles and risk of disease progression.

Pre-stimulus beta power encodes explicit and implicit perceptual biases in distinct cortical areas
Perception is biased by expectations and previous actions. Pre-stimulus brain oscillations are a potential candidate for implementing biases in the brain. In two EEG studies on somatosensory near-threshold detection, we investigated the pre-stimulus neural correlates of an (implicit) previous choice bias and an explicit bias. The explicit bias was introduced by informing participants about stimulus probability on a single-trial level (volatile context) or block-wise (stable context). Behavioural analysis confirmed adjustments in the decision criterion and confidence ratings according to the cued probabilities and previous choice-induced biases. Pre-stimulus beta power with distinct sources in sensory and higher-order cortical areas predicted explicit and implicit biases, respectively, on a single subject level and partially mediated the impact of previous choice and stimulus probability on the detection response. We suggest that pre-stimulus beta oscillations in different brain areas are neural correlates of explicit and implicit biases in somatosensory perception.

Mitochondrial oxidant stress promotes alpha-synuclein aggregation and spreading in mice with mutated glucocerebrosidase
Mutations of the glucocerebrosidase-encoding gene, GBA1, are common risk factors for Parkinson's disease. Although only a minority of mutation-carrying individuals develops the disease, the mechanisms of neuronal vulnerability predisposing to pathology conversion remain largely unclear. In this study, heterozygous expression of a common glucocerebrosidase variant, namely the L444P mutation, was found to exacerbate alpha-synuclein aggregation and spreading in a mouse model of Parkinson-like pathology targeting neurons of the medullary vagal system. These neurons are primary sites of alpha-synuclein lesions in Parkinson's disease and were shown here to become more vulnerable to oxidative stress after L444P expression. Nitrative burden paralleled the enhanced formation of reactive oxygen species within vagal neurons expressing mutated glucocerebrosidase, as indicated by pronounced accumulation of nitrated alpha-synuclein. A causal relationship linked mutation-induced oxidative stress to enhanced alpha-synuclein pathology that could indeed be rescued by neuronal overexpression of the mitochondrial antioxidant enzyme superoxide dismutase 2. Further evidence supported a key involvement of mitochondria as sources of reactive oxygen species as well as targets of oxidative and nitrative damage within L444P-expressing neurons. Scavenging of oxygen species by superoxide dismutase 2 effectively counteracted deleterious nitrative reactions and prevented nitrated alpha-synuclein burden. Taken together, these findings support the conclusion that enhanced vulnerability to mitochondrial oxidative stress conferred by glucocerebrosidase mutations should be considered an important mechanism predisposing to Parkinson's disease pathology, particularly in brain regions targeted by alpha-synuclein aggregation and involved in alpha-synuclein spreading.

The developing Human Connectome Project fetal functional MRI release: Methods and data structures
Recent advances in fetal fMRI present a new opportunity for neuroscience to study functional human brain connectivity at the time of its emergence. Progress in the field however has been hampered by the lack of openly available datasets that can be exploited by researchers across disciplines to develop methods that would address the unique challenges associated with imaging and analysing functional brain in utero, such as unconstrained head motion, dynamically evolving geometric distortions, or inherently low signal-to-noise ratio. Here we describe the developing Human Connectome Project's release of the largest open access fetal fMRI dataset to date, containing 275 scans from 255 fetuses and spanning the period of 20.86 to 38.29 post-menstrual weeks. We present a systematic approach to its pre-processing, implementing multi-band soft SENSE reconstruction, dynamic distortion corrections via phase unwrapping method, slice-to-volume reconstruction and a tailored temporal filtering model, with attention to the prominent sources of structured noise in the in utero fMRI. The dataset is accompanied with an advanced registration infrastructure, enabling group-level data fusion, and contains outputs from the main intermediate processing steps. This allows for various levels of data exploration by the imaging and neuroscientific community, starting from the development of robust pipelines for anatomical and temporal corrections to methods for elucidating the development of functional connectivity in utero. By providing a high-quality template for further method development and benchmarking, the release of the dataset will help to advance fetal fMRI to its deserved and timely place at the forefront of the efforts to build a life-long connectome of the human brain.

Months-long stability of the head-direction system
Spatial orientation is a universal ability that allows animals to navigate their environment. In mammals, the head-direction (HD) system is an essential component of the brain's navigation system, yet the stability of its underlying neuronal code remains unclear. Here, by longitudinally tracking the activity of the same HD cells in freely moving mice, we show that the internal organization of population activity in the HD system was preserved for several months. Furthermore, the HD system developed a unique mapping between its internal organization and spatial orientation in each environment. This was not affected by visits to other environments and was stabilized with experience. These findings demonstrate that stable neuronal code supports the sense of direction and forms long-lasting orientation memories.

Missing data approaches for longitudinal neuroimaging research: Examples from the Adolescent Brain and Cognitive Development (ABCD) Study
This paper addresses the challenges of managing missing values within expansive longitudinal neuroimaging datasets, using the specific example of data derived from the Adolescent Brain and Cognitive Development ABCD study. The conventional listwise deletion method, while widely used, is not recommended due to the risk that substantial bias can potentially be introduced with this method. Unfortunately, recommended alternative practices can be challenging to implement with large data sets. In this paper, we advocate for the adoption of more sophisticated statistical methodologies, including multiple imputation, propensity score weighting, and full information maximum likelihood (FIML). Through practical examples and code using ABCD data, we illustrate some of the benefits and challenges of these methods, with a review of how these advanced methodologies bolster the robustness of analyses and contribute to the integrity of research findings in the field of developmental cognitive neuroscience.

Co-administration of midazolam and psilocybin: Differential effects on subjective quality versus memory of the psychedelic experience
Aspects of the acute experience induced by the serotonergic psychedelic psilocybin predict symptomatic relief in multiple psychiatric disorders and improved well-being in healthy participants, but whether these therapeutic effects are immediate or are based on memories of the experience is unclear. To examine this, we co-administered psilocybin (25 mg) with the amnestic benzodiazepine midazolam in 8 healthy participants and assayed the subjective quality of, and memory for, the dosing-day experience. We identified a midazolam dose that allowed a conscious psychedelic experience to occur while partially impairing memory for the experience. Furthermore, midazolam dose and memory impairment tended to associate inversely with salience, insight, and well-being induced by psilocybin. These data suggest a role for memory in therapeutically relevant behavioral effects occasioned by psilocybin. Because midazolam blocks memory by blocking cortical neural plasticity, it may also be useful for evaluating the contribution of the pro-neuroplastic properties of psychedelics to their therapeutic activity.

Vestibular afferent neurons develop normally in the absence of quantal/glutamatergic input
The vestibular nerve is comprised of neuron sub-groups with diverse functions related to their intrinsic biophysical properties. This diversity is partly due to differences in the types and numbers of low-voltage-gated potassium channels found in the neurons membranes. Expression for some low-voltage gated ion channels like KCNQ4 is upregulated during early post-natal development, suggesting that ion channel composition and neuronal diversity may be shaped by hair cell activity. This idea is consistent with recent work showing that glutamatergic input from hair cells is necessary for the normal diversification auditory neurons. To test if biophysical diversity is similarly dependent on glutamatergic input in vestibular neurons, we examined the maturation of the vestibular epithelium and ganglion neurons in Vglut3-ko mice whose hair cell synapses lack glutamate. Despite lacking glutamatergic input, the knockout mice showed no notable balance deficits and crossed challenging balance beams with little difficulty. Immunolabeling of the Vglut3-ko vestibular epithelia showed normal development as indicated by an identifiable striolar zone with calyceal terminals labeled by molecular marker calretinin, and normal expression of KCNQ4 by the end of the second post-natal week. We found similar numbers of Type I and Type II hair cells in the knockout and wildtype animals, regardless of epithelial zone. Thus, the presumably quiescent Type II hair cells are not cleared from the epithelium. Patch-clamp recordings showed that biophysical diversity of vestibular ganglion neurons in the Vglut3-ko mice is comparable to that found in wildtype controls, with a similar range firing patterns at both immature and juvenile ages. However, our results suggest a subtle biophysical alteration to the largest ganglion cells (putative somata of central zone afferents); those in the knockout had smaller net conductance and were more excitable than those in the wild type. Thus, unlike in the auditory nerve, glutamatergic signaling is unnecessary for producing biophysical diversity in vestibular ganglion neurons. And yet, because the input signals from vestibular hair cells are complex and not solely reliant on quantal release of glutamate, whether diversity of vestibular ganglion neurons is simply hardwired or regulated by a more complex set of input signals remains to be determined.

Elevated phagocytic capacity directs innate spinal cord repair
Immune cells elicit a continuum of transcriptional and functional states after spinal cord injury (SCI). In mammals, inefficient debris clearance and chronic inflammation impede recovery and overshadow pro-regenerative immune functions. We found that, unlike mammals, zebrafish SCI elicits transient immune activation and efficient debris clearance, without causing chronic inflammation. Single-cell transcriptomics and inducible genetic ablation showed zebrafish macrophages are highly phagocytic and required for regeneration. Cross-species comparisons between zebrafish and mammalian macrophages identified transcription and immune response regulator (tcim) as a macrophage-enriched zebrafish gene. Genetic deletion of zebrafish tcim impairs phagocytosis and regeneration, causes aberrant and chronic immune activation, and can be rescued by transplanting wild-type immune precursors into tcim mutants. Conversely, genetic expression of human TCIM accelerates debris clearance and regeneration by reprogramming myeloid precursors into activated phagocytes. This study establishes a central requirement for elevated phagocytic capacity to achieve innate spinal cord repair.

15-Lipoxygenase-Mediated Lipid Peroxidation Regulates LRRK2 Kinase Activity
Mutations in leucine-rich repeat kinase 2 (LRRK2) that increase its kinase activity are strongly linked to genetic forms of Parkinson's disease (PD). However, the regulation of endogenous wild-type (WT) LRRK2 kinase activity remains poorly understood, despite its frequent elevation in idiopathic PD (iPD) patients. Various stressors such as mitochondrial dysfunction, lysosomal dyshomeostasis, or vesicle trafficking deficits can activate WT LRRK2 kinase, but the specific molecular mechanisms are not fully understood. We found that the production of 4-hydroxynonenal (4-HNE), a lipid hydroperoxidation end-product, is a common biochemical response to these diverse stimuli. 4-HNE forms post-translational adducts with Cys2024 and Cys2025 in the kinase activation loop of WT LRRK2, significantly increasing its kinase activity. Additionally, we discovered that the 4-HNE responsible for regulating LRRK2 is generated by the action of 15-lipoxygenase (15-LO), making 15-LO an upstream regulator of the pathogenic hyperactivation of LRRK2 kinase activity. Pharmacological inhibition or genetic ablation of 15-LO prevents 4-HNE post-translational modification of LRRK2 kinase and its subsequent pathogenic hyperactivation. Therefore, 15-LO inhibitors, or methods to lower 4-HNE levels, or the targeting of Cys2024/2025 could provide new therapeutic strategies to modulate LRRK2 kinase activity and treat PD.

Novel tools to quantify total, phospho-Ser129 and aggregated alpha-synuclein in the mouse brain
Assays for quantifying aggregated and phosphorylated (S129) human -synuclein protein are widely used to evaluate pathological burden in patients suffering from synucleinopathy disorders. Many of these assays, however, do not cross-react with mouse -synuclein or exhibit poor sensitivity for this target, which is problematic considering the preponderance of mouse models at the forefront of pre-clinical -synuclein research. In this project, we addressed this unmet need by reformulating two existing AlphaLISA SureFire Ultra total and pS129 -synuclein assay kits to yield robust and ultrasensitive (LLoQ [≤]0.5pg/mL) quantification of mouse and human wild-type and pS129 -synuclein protein. We then employed these assays, together with the BioLegend -synuclein aggregate ELISA, to assess the relationship between -synuclein S129 phosphorylation and aggregation in different mouse brain tissue preparations. Overall, we highlight the compatibility of these new immunoassays with rodent models and demonstrate their potential to advance knowledge surrounding -synuclein phosphorylation and aggregation in synucleinopathies.

Molecular profiling of frontal and occipital subcortical white matter hyperintensities in Alzheimer's disease
White matter hyperintensities (WMHs) are commonly detected on T2-weighted magnetic resonance imaging (MRI) scans, occurring in both typical aging and Alzheimer's disease. Despite their frequent appearance and their association with cognitive decline, the molecular factors contributing to WMHs remain unclear. In this study, we investigated the transcriptomic profiles of two commonly affected brain regions with coincident AD pathology--frontal subcortical white matter (frontal-WM) and occipital subcortical white matter (occipital-WM)--and compared with age-matched healthy controls. Through RNA-sequencing in frontal- and occipital-WM bulk tissues, we identified an upregulation of genes associated with brain vasculature function in AD white matter. To further elucidate vasculature-specific transcriptomic features, we performed RNA-seq analysis on blood vessels isolated from these white matter regions, which revealed an upregulation of genes related to protein folding pathways. Finally, comparing gene expression profiles between AD individuals with high- versus low-WMH burden showed an increased expression of pathways associated with immune function. Taken together, our study characterizes the diverse molecular profiles of white matter changes in AD compared to normal aging and provides new mechanistic insights processes underlying AD-related WMHs.

Improving the Reliability and Accuracy of Population Receptive Field Measures Using a Logarithmically Warped Stimulus.
The population receptive field method, which measures the region in visual space that elicits a BOLD signal in a voxel in retinotopic cortex, is a powerful tool for investigating the functional organization of human visual cortex with fMRI (Dumoulin & Wandell, 2008). However, recent work has shown that population receptive field (pRF) estimates for early retinotopic visual areas can be biased and unreliable, especially for voxels representing the fovea. Here, we show that a 'log-bar' stimulus that is logarithmically warped along the eccentricity dimension produces more reliable estimates of pRF size and location than the traditional moving bar stimulus. The log-bar stimulus was better able to identify pRFs near the foveal representation, and pRFs were smaller in size, consistent with simulation estimates of receptive field sizes in the fovea.

Dorso-ventral hippocampal neural assemblies are preferentially reactivated during NREM sleep following an aversive experience
Sleep plays a crucial role in memory stabilization. In the dorsal hippocampus (dHPC), fast oscillations (sharp-wave ripples) during non-REM sleep consolidate spatial memories through place cell reactivation. The hippocampal formation is heterogeneous; the dHPC processes mostly contextual information, while the ventral part (vHPC) encodes valence and anxiety. We propose that dorsal-ventral communication during sleep is involved in the consolidation of emotional memories, potentially integrating or segregating contextual and valence information. To test this, we recorded the electrophysiological activity in the dHPC and vHPC in rats during reward and aversion-motivated exploration of a linear track and subsequent sleep. We detected dorsal and ventral SWRs during NREM sleep as well as neuronal assemblies during each exploration type and identified dorsal, ventral, and joint (dorso-ventral) assemblies. We found that dorso-ventral hippocampal coordination involves coordinated ripples and bursts of ripples. Aversive joint assemblies exhibited higher reactivation during non-REM sleep than the joint assemblies from the reward condition. Interestingly, joint aversive assemblies reactivated selectively during dorso-ventral coordinated ripples. Furthermore, their reactivation strength positively correlated with their strength of activation during the task. These results suggest the existence of dorsal-ventral hippocampal functional communication capable of sustaining the selective reactivation of experiences based on their emotional valence.

Temporal Structure of Music Improves the Cortical Encoding of Speech
Long and short-term musical training has been proposed to improve efficiency of cortical tracking of speech, the mechanism through which brain oscillations synchronize to the acoustic temporal structure of external stimuli. Here, we study how different rhythm structures of the musical signal can guide the temporal dynamics of auditory oscillations phase-aligned to the speech envelope. For this purpose, we investigated the effects of prior exposure to rhythmically structured musical sequences on cortical tracking of speech in Basque-Spanish bilingual adults. We conducted two EEG experiments where participants were presented with sentences in Basque and Spanish preceded by musical sequences that differed in their beat structure. The beat structure of the musical sequences was created to 1) reflect and match the syllabic structure of the sentences, 2) reflect a regular rhythm but not match the syllabic structure of the sentences, and 3) follow an irregular rhythm. First, we showed that the regularity found in the rhythmic structure of music acts as a temporal guide for brain oscillations. Second, our findings suggest that not only the regularity in music is crucial but so is adjusting this regularity to optimally reflect the rhythmic characteristics of the language. Third, despite finding some differences across frequencies for each language, we still found a strong effect of rhythm regularity on cortical tracking of speech. We showed that rhythm, inherent in musical signals, guides the adaptation of brain oscillations, by adapting the temporal dynamics of the oscillatory activity to the rhythmic scaffolding of the musical signal.

A sensorimotor-association axis of thalamocortical connection development
Human cortical development follows a sensorimotor-to-association sequence during childhood and adolescence. The brain's capacity to enact this sequence over decades indicates that it relies on intrinsic mechanisms to regulate inter-regional differences in the timing of cortical maturation, yet regulators of human developmental chronology are not well understood. Given evidence from animal models that thalamic axons modulate windows of cortical plasticity, here we evaluate the overarching hypothesis that structural connections between the thalamus and cortex help to coordinate cortical maturational heterochronicity during youth. We first introduce, cortically annotate, and anatomically validate a new atlas of human thalamocortical connections using diffusion tractography. By applying this atlas to three independent youth datasets (ages 8-23 years; total N = 2,676), we reproducibly demonstrate that thalamocortical connections develop along a maturational gradient that aligns with the cortex's sensorimotor-association axis. Associative cortical regions with thalamic connections that take longest to mature exhibit protracted expression of neurochemical, structural, and functional markers indicative of higher circuit plasticity as well as heightened environmental sensitivity. This work highlights a central role for the thalamus in the orchestration of hierarchically organized and environmentally sensitive windows of cortical developmental malleability.

Electrophysiology and Morphology of Human Cortical Supragranular Pyramidal Cells in a Wide Age Range
The basic excitatory neurons of the cerebral cortex, the pyramidal cells, are the most important signal integrators for the local circuit. They have quite characteristic morphological and electrophysiological properties that are known to be largely constant with age in the young and adult cortex. However, the brain undergoes several dynamic changes throughout life, such as in the phases of early development and cognitive decline in the aging brain. We set out to search for intrinsic cellular changes in supragranular pyramidal cells across a broad age range: from birth to 85 years of age and we found differences in several biophysical properties between defined age groups. During the first year of life, subthreshold and suprathreshold electrophysiological properties changed in a way that shows that pyramidal cells become less excitable with maturation, but also become temporarily more precise. According to our findings, the morphological features of the three-dimensional reconstructions from different life stages showed consistent morphological properties and systematic dendritic spine analysis of an infantile and an old pyramidal cell showed clear significant differences in the distribution of spine shapes. Overall, the changes that occur during development and aging may have lasting effects on the properties of pyramidal cells in the cerebral cortex. Understanding these changes is important to unravel the complex mechanisms underlying brain development, cognition and age-related neurodegenerative diseases.

Cerebrospinal Fluid Dynamics: Uncovering Alternative Blood Vessel Clearance Mechanisms
The pathways that run along the olfactory nerves crossing the cribriform plate and connecting to lymphatic vessels in the nasal cavity, have been identified as a crucial route for cerebrospinal fluid (CSF) outflow. However, the presence of a CSF efflux pathway through blood vessels in this region has yet to be clarified. This study aimed to elucidate the anatomical connections between the subarachnoid space and the bloodstream at the nasal epithelium and the venous drainage routes of the nasal epithelium in mice. Our findings demonstrated that CSF tracers could be drained not only through lymphatic vessels in the nasal cavity and cervical lymph nodes (CLNs), but also through the blood vessels in this area that extend to its venous drainage routes, including the facial and jugular veins. Additionally, we showed that ligation of CLNs neither impeded the influx and efflux of CSF tracers nor exacerbated Alzheimer's disease (AD)-related pathology in AD mice. Our work reveals a previously unrecognized pathway for CSF drainage through blood vessels within the nasal mucosa. These findings provide insight into the efficient removal of waste products, facilitating optimal functioning of neural tissue within the susceptible tissue of our brains.

Kynurenic acid inflammatory signaling expands in primates and impairs prefrontal cortical cognition
Cognitive deficits from dorsolateral prefrontal cortex (dlPFC) dysfunction are common in neuroinflammatory disorders, including long-COVID, schizophrenia and Alzheimer's disease, and have been correlated with kynurenine inflammatory signaling. Kynurenine is further metabolized to kynurenic acid (KYNA) in brain, where it blocks NMDA and 7-nicotinic receptors (nic-7Rs). These receptors are essential for neurotransmission in dlPFC, suggesting that KYNA may cause higher cognitive deficits in these disorders. The current study found that KYNA and its synthetic enzyme, KAT II, have greatly expanded expression in primate dlPFC in both glia and neurons. Local application of KYNA onto dlPFC neurons markedly reduced the delay-related firing needed for working memory via actions at NMDA and nic-7Rs, while inhibition of KAT II enhanced neuronal firing in aged macaques. Systemic administration of agents that reduce KYNA production similarly improved cognitive performance in aged monkeys, suggesting a therapeutic avenue for the treatment of cognitive deficits in neuroinflammatory disorders.

Peak alpha frequency is not significantly altered by five days of experimental pain and repetitive transcranial stimulation of the left dorsolateral prefrontal cortex
Repetitive transcranial magnetic stimulation (rTMS) holds promise as a non-invasive pain treatment. Given the link between individual peak alpha frequency (PAF) of resting-state electroencephalographic recordings and pain sensitivity, and the potential for rTMS to modulate PAF, we investigated these relationships through a secondary analysis of established rTMS-induced analgesia in an experimental model of sustained muscle pain. In a randomised, single-blind, sham-controlled experiment, 30 healthy adults underwent either active (n=15) or sham (n=15) high-frequency rTMS (20 min) to the left dorsolateral prefrontal cortex for five consecutive days following induction of sustained experimental pain by nerve growth factor (NGF) injected into the right extensor carpi radialis brevis muscle. The pain intensity was assessed daily for 14 days on a numerical rating scale (NRS). PAF of the resting state electroencephalography (5 min) was assessed before and one day after the five rTMS treatment days. The pre-registered analysis revealed no significant changes in PAF following five consecutive days of active (from 9.90 +/- 0.39 Hz to 9.95 +/- 0.38 Hz) or sham (from 9.86 +/- 0.44 Hz to 9.81 +/- 0.35 Hz) rTMS, suggesting that the impact of rTMS on NGF-induced pain is independent of PAF modulation. However, exploratory analysis indicated an association between the absolute difference of baseline PAF to 10 Hz (i.e. the rTMS frequency) and higher NRS pain ratings at Day 5 in participants receiving active rTMS. This suggests that rTMS is more efficient when delivered close to the individual PAF and necessitates further exploration of PAF's role in rTMS-induced pain relief.

DeMBA: a developmental atlas for navigating the mouse brain in space and time
Studies of the adult mouse brain have benefited from three-dimensional atlases providing a standard frame of reference for data analysis and integration. Extending these resources to the developing mouse brain has been challenging due to the need to integrate time as a dimension of the atlas. To address this, we present the Developmental Mouse Brain Atlas, a four-dimensional atlas encompassing each postnatal day from 4 to 56.