bioRxiv Subject Collection: Neuroscience's Journal

Fusing multisensory signals across channels and time
Animals continuously combine information across sensory modalities and time, and use these combined signals to guide their behaviour. Picture a predator watching their prey sprint and screech through a field. To date, a range of multisensory algorithms have been proposed to model this process including linear and nonlinear fusion, which combine the inputs from multiple sensory channels via either a sum or nonlinear function. However, many multisensory algorithms treat successive observations independently, and so cannot leverage the temporal structure inherent to naturalistic stimuli. To investigate this, we introduce a novel multisensory task in which we provide the same number of task-relevant signals per trial but vary how this information is presented: from many short bursts to a few long sequences. We demonstrate that multisensory algorithms that treat different time steps as independent, perform sub-optimally on this task. However, simply augmenting these algorithms to integrate across sensory channels and short temporal windows allows them to perform surprisingly well, and comparably to fully recurrent neural networks. Overall, our work: highlights the benefits of fusing multisensory information across channels and time, shows that small increases in circuit/model complexity can lead to significant gains in performance, and provides a novel multisensory task for testing the relevance of this in biological systems.

Direct cryo-ET detection of native SNARE and Munc13 protein bridges using AI classification and preprocessing
Synaptic transmission requires Munc13 and SNARE proteins for synaptic vesicle priming and fusion, and cryo-electron tomography detected multiple types of Munc13- or SNARE-dependent dependent molecular bridges that tether synaptic vesicles to the presynaptic active zone plasma membrane. To integrate the molecular scenario with structural observations, we obtained de novo, in situ cryo-electron tomography averages of native, mammalian SNARE-dependent and Munc13-dependent synaptic vesicle tethers. These provide direct evidence that both Munc13 and a complex comprising SNARE proteins link synaptic vesicles to the active zone plasma membrane. Furthermore, we determined the plausibility of different molecular compositions of tethers, placed constraints on their conformations and positioning, and propose the existence of a complex downstream of Munc13 and upstream of SNARE complex formation. Because the detection and subtomogram averaging of membrane-bridging complexes is complicated by the presence of two lipid membranes and multiple protein species and conformations, we developed novel preprocessing methods and feature-based AI classifiers that outperformed the standard methods.

The impact of subunit type, alternative splicing, and auxiliary proteins on AMPA receptor trafficking
AMPA receptors underlie fast excitatory synaptic transmission in the mammalian nervous system and are critical for the expression of synaptic plasticity. Four genes encode the AMPA subunits, each subject to RNA editing and alternative splicing at multiple positions. In addition, each tetrameric AMPA receptor can harbor up to four auxiliary proteins, of which there are multiple types. Subunit type, alternative splicing, and auxiliary proteins are all known to affect AMPA receptor gating and trafficking. However, determining which factors dominate AMPA receptor trafficking requires high throughput assessment of trafficking across multiple conditions. Here, we deploy two such methods to assess the relative contribution of AMPA subunit type (GluA1 versus GluA2), alternative splicing (flip versus flop), and various transmembrane AMPA receptor regulatory proteins (TARPs) to AMPA receptor trafficking. We find that subunit type is the most important factor, with GluA2 showing much better surface expression than GluA1, and alternative splicing plays a secondary role, with flip subunits consistently outperforming flop variants in surface expression across all conditions. Type 1 TARPs ({gamma}2-4 and {gamma}8) enhance surface trafficking, while Type 2 TARPs ({gamma}5 and {gamma}7) reduced surface expression, although we could not detect differences within each type. These data will be a helpful resource in comparing surface expression across a variety of AMPA receptor compositions. Our assays will also enable high throughput assessment of novel disease-associated mutations, chimeras, and auxiliary and chaperone proteins.

Prefrontal gamma oscillations and fear extinction learning require early postnatal interneuron-oligodendroglia communication
Emerging evidence links oligodendrocyte (OL) lineage cells and myelin to cognitive processes, yet the role of myelination in shaping neuronal networks critical for cognitive tasks remains unknown. We demonstrate that early postnatal GABAergic signaling between interneurons and oligodendrocyte precursor cells (OPCs) is crucial for myelination of parvalbumin (PV) interneurons, which facilitates in vivo low-gamma oscillations in the medial prefrontal cortex (mPFC) and supports fear extinction learning. Disruption of this signaling resulted in PV interneuron dysmyelination, decreased low-gamma power, and impaired tone fear extinction. These deficits were specific to PV interneuron dysmyelination, as overall mPFC myelination, high-gamma oscillations and context fear extinction remained unaffected. Increasing PV interneuron activity or enhancing myelination did not reverse the deficits, indicating the long-term consequences of these early myelination impairments. Our findings reveal critical roles of OPC GABAergic signaling in PV interneuron myelination and mPFC circuit maturation, with lasting impacts on gamma rhythms and cognitive function.

Characterisation of transgenic lines labelling reticulospinal neurons in larval zebrafish
From lamprey to monkeys, the organization of the descending control of locomotion is conserved across vertebrates. Reticulospinal neurons (RSNs) form a bottleneck for descending commands, receiving innervation from diencephalic and mesencephalic locomotor centres and providing locomotor drive to spinal motor circuits. Given their optical accessibility in early development, larval zebrafish offer a unique opportunity to study reticulospinal circuitry. In fish, RSNs are a small, highly stereotyped, uniquely identifiable group of large neurons spanning from the midbrain to the medulla. Classically labelled by tracer dye injections into the spinal cord, recent advances in genetic tools have facilitated the targeted expression of transgenes in diverse brainstem neurons of larval zebrafish. Here, we provide a comparative characterization of four existing and three newly established transgenic lines in larval zebrafish. We determine which identified neurons are consistently labelled and offer projection-specific genetic access to subpopulations of RSNs. We showcase transgenic lines that label most or all RSNs (nefma, adcyap1bccu96Et) or subsets of RSNs, including ipsilateral (vsx2, calcaccu75Et), contralateral (pcp4accu97Tg) or all (tiam2ay264Et) components of the Mauthner array, or midbrain-only RSNs (s1171tEt). In addition to RSNs, selected transgenic lines (nefma, s1171tEt, calcaccu75Et) labelled other potential neurons of interest in the brainstem. For those, we performed in situ hybridisation to show expression patterns of several excitatory and inhibitory neurotransmitters at larval stages as well as glutamatergic expression patterns in juvenile fish. We provide an overview of transgene expression in the brainstem of larval zebrafish that serves to lay a foundation for future studies in the supraspinal control of locomotion.

Critical periods support representation learning in a model of cortical processing
Exposure of the brain to multiple stimuli drives the development of cortical representations, likely controlled by rules of synaptic plasticity. However, the type of developmental plasticity rules that lead to high-level representations of objects are unknown. Here we study a generalized Hebbian plasticity model that includes a predictive component. The learning rule uses only quantities that are locally available at the site of the synapse, is consistent with recent plasticity experiments in pyramidal neurons, and, as opposed to backpropagation learning, does not need a detailed feedback architecture. Our model shows that limiting plasticity in time to critical periods of development improves the quality and stability of sensory representation across different cortical areas described as layers of an artificial neural network. Our model achieves state-of-the-art performance for bio- plausible plasticity models on both an abstract hierarchical object database and a large image dataset designed for unsupervised learning.

Incomplete adaptation to surface movement during hand reaching
Humans can effectively adapt to changes in the environment to maintain adequate motor performance in a vast range of situations. However, residual errors tend to persist when strong a priori assumptions about the statistical regularities of the environment are violated. In our study, we challenged the expectation that inanimate objects are usually at rest. To this end, we used a robotic interface to move a plate over which participants slid their finger while reaching towards a target. We found limited evidence of adaptation after prolonged exposure to this perturbation, and only when visual feedback about hand position was provided. Although participants were aware of the motion of the contact surface, explicit knowledge about its direction was limited. Our results provide important insights on the limits of adaptation to motion perturbation in the somatosensory system, which can inform the design of technology applications such as haptic interfaces and collaborative robots.

Cerebellar organoids model cell type-specific FOXP2 expression during human cerebellar development
In this study, we demonstrate the potential of cerebellar organoids for studying features of early human cerebellar development. Forkhead box protein P2 (FOXP2) is a transcription factor associated with speech and language development that is highly expressed in the developing brain. However, little attention has been directed to the study of FOXP2 in the early developing cerebellum. We used CRISPR gene editing in human iPSCs to generate a fluorescent FOXP2-reporter line. By combining transcriptomic analysis of iPSC-derived cerebellar organoids with published cerebellar datasets, we describe the expression and identify potential downstream targets of FOXP2 in the early developing human cerebellum. Our results highlight expression of FOXP2 in early human Purkinje cells and cerebellar nuclei neurons, and the vulnerability of these cell populations to neurodevelopmental disorders. Our study demonstrates the power of cerebellar organoids to model early human developmental processes and disorders.

Ongoing loss of viable neurons for weeks after mild perinatal hypoxia-ischemia
Mild hypoxic-ischemic encephalopathy is common in neonates with no evidence-based therapies, and 30-40% of patients experience adverse outcomes. The nature and progression of mild injury is poorly understood. Thus, we studied the evolution of mild perinatal brain injury using longitudinal two-photon imaging of transgenic fluorescent proteins as a novel readout of neuronal viability and activity at cellular resolution. In vitro, perinatal murine organotypic hippocampal cultures underwent 15-20 minutes of oxygen-glucose deprivation. In vivo, mild hypoxia-ischemia was completed in post-natal day 10 mouse pups of both sexes with carotid ligation and 15 minutes of hypoxia. Consistent with a mild injury, minimal immediate neuronal death was seen and there was no volumetric evidence of injury by ex vivo MRI 2.5 weeks after injury. In both the hippocampus and neocortex, these mild injuries resulted in a significantly delayed and progressive neuronal loss in the second week after injury, measured by fluorophore quenching. Mild hypoxia-ischemia transiently suppressed cortical network activity followed by normal maturation. No post-injury seizures were seen. The participation in network activity of individual neurons destined to die was indistinguishable from those that survived for 4 days post-injury. In conclusion, our results showed that mild perinatal brain injury resulted in a prolonged increase of neuronal death. Neurons that died late were functioning normally for days after injury, suggesting a new pathophysiology of neuronal death. Critically, the neurons destined to die late demonstrated multiple biomarkers of viability long after mild injury, suggesting their later death may be modified with neuroprotective interventions.

Artificial Embodied Circuits Uncover Neural Architectures of Vertebrate Visuomotor Behaviors
All brains evolve within specific sensory and physical environments. Traditionally, neuroscience has focused on studying neural circuits in isolation, yet holistic characterization of their function requires integrative brain-body testing. To investigate the neural and biomechanical mechanisms of sensorimotor transformations, we constructed realistic neuromechanical simulations (simZFish) of the larval zebrafish optomotor response, a visual stabilization behavior. By computationally reproducing the body, physical body-water interactions, visual environments, and experimentally derived neural architectures, we closely replicated the behavior of real zebrafish6. Through systematic manipulation of physiological and circuit features, impossible in biological experiments, we demonstrate how embodiment shapes neural circuit architecture and behavior. When challenged with novel visual stimuli, simZFish predicted neuronal response types, which we identified via calcium imaging in the brain of real zebrafish and used to update the simZFish neural network. In virtual rivers, simZFish performed rheotaxis by using current-induced optic flow as navigational cues, compensating for the simulated water flow. Finally, a physical robot (ZBot) validated the role of embodied sensorimotor circuits in maintaining position in a real river with complex fluid dynamics and visual environments. Together, by iterating between simulations, behavioral observations, neural imaging, and robotic testing, we demonstrate the power of an integrative approach to investigating sensorimotor processing.

A Leadfield-Free Optimization Framework for Transcranially Applied Electric Currents
Background: Transcranial Electrical Stimulation (TES), Temporal Interference Stimulation (TIS), Electroconvulsive Therapy (ECT) and Tumor Treating Fields (TTFields) are based on the application of electric current patterns to the brain. Objective: The optimal electrode positions, shapes and alignments for generating a desired current pattern in the brain vary between persons due to anatomical variability. The aim is to develop a flexible and efficient computational approach to determine individually optimal montages based on electric field simulations. Methods: We propose a leadfield-free optimization framework that allows the electrodes to be placed freely on the head surface. It is designed for the optimization of montages with a low to moderate number of spatially extended electrodes or electrode arrays. Spatial overlaps are systematically prevented during optimization, enabling arbitrary electrode shapes and configurations. The approach supports maximizing the field intensity in target region-of-interests (ROI) and optimizing for a desired focality-intensity tradeoff. Results: We demonstrate montage optimization for standard two-electrode TES, focal center-surround TES, TIS, ECT and TTFields. Comparisons against reference simulations are used to validate the performance of the algorithm. The system requirements are kept moderate, allowing the optimization to run on regular notebooks and promoting its use in basic and clinical research. Conclusion(s): The new framework complements existing optimization methods that require small electrodes, a predetermined discretization of the electrode positions on the scalp and work best for multi-channel systems. It strongly extends the possibilities to optimize electrode montages towards application-specific aims and supports researchers in discovering innovative stimulation schemes. The framework is available in SimNIBS.

A FRET-Based FLIM Method to Probe Membrane-Induced Alpha-Synuclein Aggregation in Neurons
Parkinson's disease (PD) involves the aggregation of the protein alpha-synuclein, a process promoted by interactions with intracellular membranes. To study this phenomenon in neurons for the first time, we developed a fluorescence lifetime imaging (FLIM) method using Förster resonance energy transfer and self-quenching reporters, analyzed with a custom-built FLIM microscope. This method offers insights into aggregate formation in PD and can be broadly applied to probe protein-membrane interactions in neurons.

Tonic sound-evoked motility of cochlear outer hair cells in mice with impaired mechanotransduction
Cochlear outer hair cells (OHCs) transduce sound-induced vibrations of their stereociliary bundles into receptor potentials that drive changes in cell length. While fast, phasic OHC length changes are thought to underlie an amplification process required for sensitive hearing, OHCs also exhibit large tonic length changes. The origins and functional significance of this tonic motility are unclear. Here, in vivo cochlear vibration measurements reveal tonic, sound-induced OHC motility in mice with stereociliary defects that impair mechanotransduction and eliminate cochlear amplification. Tonic motility in impaired mice was physiologically vulnerable but weakly related to any residual phasic motility, possibly suggesting a dissociation between the underlying mechanisms. Nevertheless, a simple model demonstrates how tonic responses in both normal and impaired mice can result from asymmetric mechanotransduction currents and be large even when phasic motility is undetectable. Tonic OHC responses are therefore not unique to sensitive ears, though their potential functional role remains uncertain.

Contributions of temporal and spatial masking signals in perception of sequential visual events
Accurate perception of time and space is essential for moment-to-moment interactions with our surroundings. This process requires flexibility, as it integrates information from our actions and the external context. Probing the visual system during the updating process reveals spatiotemporal distortions, where sequential stimuli appear closer in time and space than they are. These effects occur perisaccadically or when a visual mask follows the stimuli. The study investigated whether non-overlapping visual masks could influence temporal inversion judgments (TOJs), suggesting that a temporal signal might act as an anchor during updating. In Experiment 1, participants judged the temporal order of two stimuli under three conditions: no mask, a full-field mask, or a partial mask avoiding stimuli's locations. Compared to no mask, both masks triggered TOJs when presented within 30 milliseconds of the second stimulus. In a control experiment, delaying mask onset by 30 milliseconds eliminated the inversion effect. In Experiment 2, TOJs were observed for both ipsilateral and contralateral masks, suggesting that long range inhibitory signals might also contribute to the effect. Together, these findings indicate that temporal inversions can occur with non-overlapping stimuli masks configuration, pointing to a non-spatial signal related to mask timing as the underlying mechanism.

Stability through plasticity: Finding robust memories through representational drift
Memories are believed to be stored in synapses and retrieved through the reactivation of neural ensembles. Learning alters synaptic weights, which can interfere with previously stored memories that share the same synapses, creating a tradeoff between plasticity and stability. Interestingly, neural representations exhibit significant dynamics, even in stable environments, without apparent learning or forgetting, a phenomenon known as representational drift. Theoretical studies have suggested that multiple neural representations can correspond to a memory, with post-learning exploration of these representation solutions driving drift. However, it remains unclear whether representations explored through drift differ from those learned or offer unique advantages. Here we show that representational drift uncovers noise-robust representations that are otherwise difficult to learn. We first define the non-linear solution space manifold of synaptic weights for a fixed input-output mapping, which allows us to disentangle drift from learning and forgetting and simulate representational drift as diffusion within this manifold. Solutions explored by drift have many inactive and saturated neurons, making them robust to weight perturbations due to noise or continual learning. Such solutions are prevalent and entropically favored by drift, but their lack of gradients makes them difficult to learn and non-conducive to further learning. To overcome this, we introduce an allocation procedure that selectively shifts representations for new information into a learning-conducive regime. By combining allocation with drift, we resolve the tradeoff between learnability and robustness.

Endocrine modulation of cortical and retinal blood flow across the menstrual cycle
The ovarian hormones, oestrogen and progesterone, have vaso- and neuroprotective effects, likely due to interactions with the cerebrovascular system. This study investigates their neuroendocrine influence on a range of cerebral and retinal vascular functions across a healthy menstrual cycle. Twenty-six healthy, menstruating females completed imaging sessions and assessment of circulating hormone levels during their early follicular, late follicular, and mid-luteal phase (1-4, 10-12 and 20-22 days after menses onset). Cerebral blood flow (CBF), arterial arrival time (AAT), global oxygen extraction fraction (OEF), cerebrovascular metabolic rate of oxygen (CMRO2), carotid artery radius and carotid pulsatility index (PI) were measured using 3T MRI. Retinal vessel density and blood flow resistance were assessed with optical coherence tomography angiography (OCT-A). Assessed with linear models, increased oestradiol was related to increased global CBF (Chi2(1)=35.05; p=3.2x10-9) and increased AAT (Chi2(1)=5.87; p=0.015). Increased progesterone was associated with increased global CBF (Chi2(1)=13.00; p=0.0003). In the retina, a relationship was found between oestradiol and decreased retinal blood flow resistance (Chi2(1)=5.28; p=0.0215), which was primarily driven by centrally localised vessels. This study finds that circulating oestrogen increases blood flow in the eye and brain, while progesterone significantly impacts the brain alone. These effects suggest a potential pathway for neuroprotective mechanisms.

Uncovering sex differences in Parkinson's Disease through metaanalysis of single cell transcriptomic studies
Abundant evidence supports the significant impact of biological sex on various aspects of Parkinson Disease (PD), including incidence, progression, symptoms or response to treatment. The incidence and prevalence of the disease is higher in males, while its age of onset is earlier than in females. There are also sex differences in the symptomatology, both motor and non-motor. In female PD, tremor, pain, depression and dysphagia are predominant, whereas in male PD, freezing of gait, camptocormia, cognitive impairment and urinary dysfunction are more common. Likewise, there are sex differences in the pathophysiology of the disease, related to most of the pathological processes of PD, as is the case of the greater activation of microglia in males or the lower oxidative stress in females. All these findings support the idea that different molecular mechanisms may be involved in PD depending on the sex of the patient. Some explanations for these events are related to biological, genetic, hormonal or environmental factors, such as the possible anti-inflammatory and neuroprotective effect of estrogens. However, the underlying molecular mechanisms have not yet been fully described. Our results show sex differences in gene expression, cell-cell communication and pathway activation in all major brain cell types, highlighting the presence of greater neuroinflammation in men and greater neurodegeneration in the SNpc in men, with the latter appearing to be inverted between sexes when observed in the cortical zone. Finally, we have made all the results available in a publicly accessible webtool, in order to allow the exploration of results to other researchers and to broaden the molecular-level understanding of PD sex differences.

Cleavage of the TrkB-FL Receptor During Epileptogenesis: Insights from a Kainic Acid-Induced Model of Epilepsy and Human Samples
Brain-derived neurotrophic factor (BDNF) is essential for neuronal survival, differentiation, and plasticity. In epilepsy, BDNF exhibits a dual role, exerting both antiepileptic and pro-epileptic effects. The cleavage of its main receptor, full-length tropomyosin-related kinase B (TrkB-FL), was suggested to occur in status epilepticus (SE) in vitro. Moreover, under excitotoxic conditions, TrkB-FL was found to be cleaved, resulting in the formation of a new intracellular fragment, TrkB-ICD. Thus, we hypothesized that TrkB-FL cleavage and TrkB-ICD formation could represent an uncovered mechanism in epilepsy. We used a rat model of mesial temporal lobe epilepsy (mTLE) induced by kainic acid (KA) to investigate TrkB-FL cleavage and TrkB-ICD formation during SE and established epilepsy (EE). Animals treated with 10 mg/kg of KA exhibited TrkB-FL cleavage during SE, with hippocampal levels of TrkB-FL and TrkB-ICD correlating with seizure severity. Notably, TrkB-FL cleavage and TrkB-ICD formation were also detected in animals with EE, which exhibited spontaneous recurrent convulsive seizures, neuronal death, mossy fiber sprouting, and long-term memory impairment. Importantly, hippocampal samples from patients with refractory epilepsy also showed TrkB-FL cleavage with increased TrkB-ICD levels. Additionally, overexpression of TrkB-ICD in the hippocampus of healthy rodents resulted in long-term memory impairment. Our findings suggest that TrkB-FL cleavage and the subsequent TrkB-ICD production occur throughout epileptogenesis, with the extent of cleavage correlating positively with seizure occurrence. Moreover, we found that TrkB-ICD impairs memory. This work uncovers a novel mechanism in epileptogenesis that could serve as a potential therapeutic target in mTLE, with implications for preserving cognitive function.

Neddylation regulates the development and function of excitatory neurons
The development and function of neurons is orchestrated by a plethora of regulatory mechanisms that control the abundance, localization, interactions, and function of pro-teins. A key role in this regard is assumed by post-translational protein modifications (PTMs). While some PTM types, such as phosphorylation or ubiquitination, have been explored comprehensively, PTMs involving ubiquitin-like modifiers (Ubls) have remained comparably enigmatic (Ubls). This is particularly true for the Ubl Nedd8 and its conjuga-tion to proteins, i.e. neddylation, in nerve cells. In the present study, we generated a con-ditional Nedd8 knock-out mouse line and examined the consequences of Nedd8-deletion in cultured postmitotic glutamatergic neurons. Our findings reveal that Nedd8-ablation in young glutamatergic neurons causes alterations in the expression of devel-opmental transcription factors that control neuronal differentiation, ultimately leading to defects in the development of a mature glutamatergic neuronal phenotype. Apparent manifestations of these defects include increased vGlut2 expression levels, reduced vGlut1 and endophilin 1 expression levels, reduced dendrite complexity, and increased transmitter release probability. Collectively, our results highlight a pivotal role for neddyla-tion in controlling the fate of glutamatergic neurons and excitatory synaptic transmission.

Identifying the Brain Circuits that Regulate Pain-Induced Sleep Disturbances
Pain therapies that alleviate both pain and sleep disturbances may be the most effective for pain relief, as both chronic pain and sleep loss render the opioidergic system, targeted by opioids, less sensitive and effective for analgesia. Therefore, we first studied the link between sleep disturbances and the activation of nociceptors in two acute pain models. Activation of nociceptors in both acute inflammatory (AIP) and opto-pain models led to sleep loss, decreased sleep spindle density, and increased sleep fragmentation that lasted 3 to 6 hours. This relationship is facilitated by the transmission of nociceptive signals through the spino-parabrachial pathways, converging at the wake-active PBelCGRP (parabrachial nucleus expressing Calcitonin Gene-Related Peptide) neurons, known to gate aversive stimuli. However, it has never been tested whether the targeted blocking of this wake pathway can alleviate pain-induced sleep disturbances without increasing sleepiness. Therefore, we next used selective ablations or optogenetic silencing and identified the key role played by the glutamatergic PBelCGRP in pain-induced sleep disturbances. Inactivating the PBelCGRP neurons by genetic deletion or optogenetic silencing prevented these sleep disturbances in both pain models. Furthermore, to understand the wake pathways underlying the pain-induced sleep disturbances, we silenced the PBelCGRP terminals at four key sites in the substantia innominata of the basal forebrain (SI-BF), the central nucleus of Amygdala (CeA), the bed nucleus of stria terminalis (BNST), or the lateral hypothalamus (LH). Silencing of the SI-BF and CeA also significantly reversed pain-induced sleep loss, specifically through the action on the CGRP and NMDA receptors. This was also confirmed by site-specific blockade of these receptors pharmacologically. Our results highlight the significant potential for selectively targeting the wake pathway to effectively treat pain and sleep disturbances, which will minimize risks associated with traditional analgesics. .

Structural and genetic determinants of zebrafish functional brain networks
Network science has significantly advanced our understanding of brain networks across species, revealing universal connectivity principles. While human studies based on magnetic resonance imaging (MRI) have established several network principles at macroscopic scales, recent breakthroughs, including high-amplitude regional co-activation patterns and spatially contiguous functional gradients, remain unexplored at cellular resolution in animal models. Here, we employ whole-brain functional imaging at cellular resolution in larval zebrafish, combined with anatomical and spatial genetic expression profile databases, to investigate the structural and genetic basis of functional brain networks. We show that mesoscopic functional connectivity (FC) is a robust measure of brain activity that captures the individuality of larvae. Using a public dataset of thousands of single-neuron reconstructions, we reveal a strong coupling between FC and structural connectivity (SC). Numerous properties of the connectome that account for indirect pathways and diffusion mechanisms individually and collectively predict interregional correlations. The hierarchical modular structure of SC and FC significantly overlaps in space, and modules identified within the connectome constrain the shape of both spontaneous and stimulus-driven activity patterns. Using visual stimuli and tail monitoring, we identify a functional network gradient that maps onto the sensorimotor function of brain regions. Finally, we identify a set of genes whose co-expression in brain regions significantly predicts regional FC. Our findings reproduce several key features of mammalian brain networks in zebrafish, demonstrating the potential for studying large-scale network phenomena in smaller, optically accessible vertebrate brains.

Temporal evolution of color representations measured with MEG reveals a 'coarse to fine' dynamic
Color perception is based on the differential spectral responses of the L, M and S-cones, subsequent subcortical and cortical computations, and may include the influence of higher order factors such as language. Although the early subcortical stages of color vision are well characterised, the organization of cortical representations of color remain elusive, despite numerous models based on discrimination thresholds, appearance and categorization. An underexplored aspect of cortical color representations is their dynamic evolution. Here we compare the evolution of three different color representations over time using magnetoencephalography (MEG). We measured neural responses to 14 hues at each of 3 achromatic offsets (increment, isoluminant and decrement) while participants attended either to the exact color of the stimulus or its color category. We used a series of classification analyses, combined with multidimensional scaling (MDS) and Representational Similarity Analysis, to ask how cortical representations of color unfold over time from stimulus onset. We compared the performance of 'higher order' models based on hue and color category with a model based simply on stimulus cone contrast and found that all models had significant correlations with the data. However, the unique variance accounted for by each model revealed a dynamic change in hue responses over time, that was consistent with a 'coarse to fine' transition from a broad clustering into categorical groups to a finer within category representation. Notably, these dynamics were replicated across datasets from both tasks, suggesting they reflect a robust reorganization of cortical hue responses over time.

The relationship between auditory brainstem responses, cognitive ability, and speech-in-noise perception among young adults with normal hearing thresholds
Purpose: The goal of this research was to determine the contributions of auditory neural processing and cognitive abilities to predict performance on a competing talker task in young, normal hearing adults. Methods: Two experiments were performed, each with separate cohorts of ~30 young adults with normal hearing who performed a competing talker task which included a high-pass filtered condition that was designed to be more sensitive to auditory nerve functioning than are commonly used speech-in-noise perception tests. Predictors of performance on this speech-in-speech task included ABR waves I and V metrics and cognitive task performance. Experiment one included click ABRs at a moderate level commensurate with the level of the competing talker task, as well as the cognitive digit span working memory task. Experiment two included high-intensity click clinical ABRs and three cognitive tasks from the NIH Toolbox V3 that assessed working memory, cognitive flexibility and attention, and inhibitory control: List Sorting Working Memory, Dimensional Change Card Sort, and Flanker Inhibitory Control and Attention tests, respectively. Results: Performance on the high-pass competing talker task varied across participants in both experiments. This variability was predicted by performance on the inhibitory control task, but not the tasks involving working memory or cognitive flexibility, nor by any of the auditory processing metrics from moderate or high-intensity click ABRs. Conclusions: Among two groups of young adults with normal hearing, cognitive factors with very similar demands to the competing talker task seem to play the greatest role in speech-in-noise perception.

Large-scale infra-slow dynamics of extracellular potentials linked to synchronous states revealed by graphene neural probes
Brain states exhibit slow transitions that are coordinated by slowly varying homeostatic and neuromodulatory factors. These slow dynamics modulate neuronal excitability, giving rise to brain state-specific synchronous oscillatory patterns across brain regions, which in turn could reflect local infra-slow variations in the extracellular potential. Such a relationship may provide new insights into the organisation of spontaneous brain dynamics beyond the established fast time scales. However, mapping of the LFP across brain regions with high spatio-temporal resolution remains challenging, with the infra-slow component particularly elusive. To overcome these limitations, we developed neural probes based on arrays of up to 512 multiplexed graphene transistors, which enable DC-coupled, high density, and large-scale recordings of surface and depth activity in freely behaving rats. Analysis of cortex-wide oscillation dynamics improves segmentation, provides new insights into global brain states and allows detection of the local oscillatory states. Brain state transitions related to changes in neuronal synchrony are found to correlate with topographically structured infra-slow dynamics. Furthermore, transregional infra-slow waves during non-REM sleep are globally coupled to diverse sleep spindle oscillatory modes independent of their localization while slow oscillations locally modulate spindles occurence. This study shows that spatio-temporal patterns of infra-slow and slow LFP parallel the spatially organized oscillatory dynamics, reflecting the interplay between sub-cortical inputs and cortical excitability across brain states.

Transient receptor potential vanilloid channel 2 contributes to multi-modal endoplasmic reticulum and perinuclear space dilations that can also be observed in prion-infected mice
Our recent work on the prion protein and Na+,K+-ATPases (NKAs) led us to revisit data from over 50 years ago, which suggested a similarity between vacuolation phenotypes in rodents poisoned with cardiac glycosides (CGs) and spongiform degeneration in prion disease. At that time, this hypothesis was dismissed because the vacuolation observed in prion diseases affects neurons, whereas CG poisoning in rodent brains led to swellings of the endoplasmic reticulum (ER) in astrocytes. We speculated that this difference might be specific to rodents and document here that the vacuolation shifts to neurons in mice expressing a humanized NKA 1 subunit. Next, we investigated the molecular mechanisms that could cause similar ER vacuolation in human cells in vitro. We found that certain stressors, such as overexpression of NKA subunits and exposure to specific toxins known to trigger the unfolded protein response, can induce a phenotype characterized by profound ER dilation that is most strikingly observed for the perinuclear space (PNS). The ion imbalance typically caused by functional NKAs does not contribute to this phenotype. In fact, it can occur even with the overexpression of catalytically inactive NKAs. Several lines of evidence, generated with pharmacological agents, ion-specific dyes, antagonists, and truncated expression constructs, suggest a calcium leak channel in the ER, known as transient receptor potential vanilloid 2 (TRPV2), plays a role in this ER and PNS dilation. Additionally, we observed that the formation of these vacuoles coincides with a decrease in steady-state levels of the lipid kinase PIKFYVE, which is recognized for its role in endolysosomal fission and fusion processes. Finally, we found evidence of vacuoles in cryo-sectioned brains of prion-infected mice that can be filled with a fluorescent marker targeted to the ER and PNS. This raises the possibility that this vacuolation phenomenon contributes to spongiform degeneration seen in prion diseases.

Frequency-tagged fMRI: A platform for fine-grained spatiotemporal analysis of cortical function
Frequency tagging with functional MRI (ft-fMRI) enables precise mapping of neural dynamics by synchronizing oscillatory stimuli to stimulus-driven blood-oxygen-level-dependent (BOLD) responses. We developed and validated a dual-frequency tagging protocol to dissociate fundamental, multiplexed, and nonlinear intermodulation frequency responses across the human visual cortex at high spatial resolution. Using 3T and 7T fMRI, we reliably detected frequency-tagged BOLD responses at the level of individual vertices, revealing fine-grained cortical topographies and robust temporal synchronization to driving frequencies. Multiplexed responses, encoding multiple frequencies simultaneously, and nonlinear intermodulation components, were spatially dissociable and exhibited reproducible dynamics within and across experimental sessions. These findings establish ft-fMRI as a powerful tool for investigating fine-grained cortical computations, previously inaccessible to traditional fMRI. By bridging the spatiotemporal resolution gap between electrophysiology and fMRI, ft-fMRI provides a versatile platform for studying perception, attention, and multisensory integration in health and disease.

CHARACTERISING REPRESENTATIONS OF HUE AND SATURATION IN THE CORTEX USING INFORMATION DECODING
One of the enduring questions in the field of colour vision research revolves around how features of colour appearance, such as hue and saturation are represented in the brain. While considerable progress has been made in understanding the transformation of physical colour signals during early processing stages, the mechanisms by which these signals are recombined in later processing, ultimately giving rise to our perceptual experience of colour, remain elusive. A promising avenue for capturing these representations involves decoding from EEG signals. We captured EEG signals in response to 8 evenly spaced isoluminant colours at two saturation levels, taken from a perceptually uniform CIE Lab colour space. Surprisingly, our main finding challenges the expectation that representations of colours that are perceptually more similar elicit more similar signals. Instead, our results show that isoluminant hues perceived as maximally dissimilar tend to evoke the most similar EEG signals, which is in line with predictions derived from opponent theory. Additionally, decoding performs better for lower saturation than for higher saturation hues, contrary to expectations that more distinct hue representations would be associated with highly saturated hues but in line with prediction of magnified differences in latency and amplitude of EEG signals between low-level opponent mechanisms at lower contrast levels. Finally, our findings also highlight the non-uniformity of the cortical representation space for isoluminant colour, indicating that neighbouring hues exhibit varying degrees of similarity. Put together, the results show that low-level features, such as contrast and cone-opponency, drive the EEG response to colour.

Visualizing Functional Network Connectivity Differences Using an Explainable Machine-learning Method
Functional network connectivity (FNC) estimated from resting-state functional magnetic resonance imaging showed great information about the neural mechanism in different brain disorders. But previous research has mainly focused on standard statistical learning approaches to find FNC features separating patients from control. Although machine learning approaches provide better models separating controls from patients, it is not straightforward for these approaches to provide intuition on the model and the underlying neural process of each disorder. Explainable machine learning offers a solution to this problem by applying machine learning to understand the neural process behind brain disorders. In this study, we introduce a novel framework leveraging SHapley Additive exPlanations (SHAP) to identify crucial Functional Network Connectivity (FNC) features distinguishing between two distinct population classes. Initially, we validate our approach using synthetic data. Subsequently, applying our framework, we ascertain FNC biomarkers distinguishing between, controls and schizophrenia patients with accuracy of 81.04% as well as middle aged adults and old aged adults with accuracy 71.38%, respectively, employing Random Forest (RF), XGBoost, and CATBoost models. Our analysis underscores the pivotal role of the cognitive control network (CCN), subcortical network (SCN), and somatomotor network (SMN) in discerning individuals with schizophrenia from controls. In addition, our platform found CCN and SCN as the most important networks separating young adults from older.

Time-resolved neural and experience dynamics of medium- and high-dose DMT
N,N-Dimethyltryptamine (DMT) is a potent and fast-acting psychedelic drug that induces a radical reorganisation of the contents of consciousness, comprising the dissolution of time and space and perceptual immersion into an "alternate reality". While contemporary research has somewhat advanced our understanding of DMT, and psychedelics more broadly, there is little research that integrates time-resolved measures of subjective experience with temporally fine-grained brain imaging. We therefore present the current study, a repeated-measures dose-dependent study of the subjective and neural dynamics induced through DMT under naturalistic conditions. Nineteen participants received either a 20mg or 40mg dose of freebase DMT across two dosing sessions in a blinded, counterbalanced order, with blinding rates consistent across doses. Electroencephalography (EEG) data was collected, as well as time-resolved retrospective measures of subjective experience (Temporal Experience Tracing). Both doses of DMT induced rapid changes in experience dimensions. However, the 40mg dose induced significantly more extreme visual hallucinations and emotionally intense experiences. Further, we computed a variety of neural markers on the EEG data, and found that oscillatory alpha power and permutation entropy were most strongly associated with continuous subjective experience dimensions. Strikingly, lempel-ziv complexity, a previously hailed as a robust correlate of subjective experiences within the psychedelic-state, was the least strongly associated neural marker. These findings provide an important insight into how distinct neural dynamics may contribute to this radical and intense altered state of consciousness.

Towards the implementation and interpretation of masked ICA for identifying signatures of autonomic activation in the brainstem with resting-state BOLD fMRI
The brainstem is the site of key exchanges between the autonomic and central nervous systems but has historically presented a challenging target for study with BOLD fMRI. A potentially powerful although under-characterized approach to identifying nucleic activation within the brainstem is masked independent component analysis (mICA), which restricts signal decomposition to the brainstem itself, thus aiming to reduce the strong effect of physiological noise in nearby regions such as ventricles and large arteries. In this study, we systematically investigate the use of mICA to uncover signatures of autonomic activation in the brainstem at rest. We apply mICA on 40 subjects in a high-resolution resting state 7T dataset following different strategies for dimensionality selection, denoising, and component classification. We show that among the noise mitigation techniques investigated, cerebrospinal fluid denoising makes the largest impact in terms of mICA outcomes. We further demonstrate that across preprocessing pipelines and previously reported results the majority of components are spatially reproducible, but temporal outcomes differ widely depending on denoising strategy. Evaluating both hand-labelling and whole-brain specificity criteria, we develop an intuitive framework for mICA classifications. Finally, we make a comparison between mICA and atlas-based segmentations of brainstem nuclei, finding little consistency between these two approaches. Based on our evaluation of the effects of methodology on mICA and its relationship to other signals of interest in the brainstem, we provide recommendations for future uses of mICA to identify autonomically-relevant BOLD fluctuations in subcortical structures.

Circuit-Level Dynamics of Slow Wave Activity and Propagation During the Awakening Process
Slow-wave activity (SWA) is a hallmark of the loss of consciousness in non-REM sleep and anesthesia. The mechanistic underpinnings of SWA, and its evolution when transitioning towards the conscious brain state is poorly understood. We address this topic by recording multi-area and laminar activity in posterior parietal (PPC) and primary visual (V1) cortices of mice spontaneously awakening from isoflurane anesthesia. Spectral power is stronger in PPC (especially in superficial layers) during deep unconsciousness, but stronger in V1 when awakening. Rostro-caudal (feedback-like) propagation of SWA also shows state-dependent modulation, particularly in layer 5. The excitability of layer 2/3 neurons, hindered at high isoflurane, recovers during awakening, when V1 and the feedforward pathway reacquire a strong role. Detailing the hierarchical and laminar properties of spontaneous traveling oscillations, we provide evidence that SWA is a multiscale phenomenon. Explicating the functional role of these processes is critical to understand the neuronal mechanisms of consciousness.

Psychedelic enhancement of flexible learning weeks after a single dose
Psychedelic drugs have shown therapeutic potential for the treatment of multiple neuropsychiatric disorders chiefly by promoting long-lasting plasticity in the prefrontal cortex (PFC). A critical function of the PFC is the ability to apply previously learned rules to novel scenarios, a skill known as cognitive flexibility. Here, we show that a single dose of 25CN-NBOH, a serotonin 2A receptor-preferring psychedelic, improves performance on a relatively complex flexible reversal learning task in mice, measured 2-3 weeks after the dose. This effect was seen in both male and female mice. This behavioral finding complements previous cellular results showing that a single psychedelic dose induces long-term structural changes in the PFC and uniquely demonstrates sustained improvements in cognitive flexibility in a novel behavioral paradigm weeks after the initial psychedelic dose in mice. This high throughput task also provides a rapid, automated way to assess other candidate psychedelics for their impact on cognitive flexibility in mice.

Online interference of declarative memory on fast and slow adaptive processes in force field motor learning
Error-based motor adaptation is currently understood as a dual-rate process involving a fast adaptive process that learns quickly but also decays rapidly and a slow process that learns slowly but has good retention. While the fast process is typically categorized as procedural learning, recent evidence suggests that it relies on the declarative memory system. To test this hypothesis, we investigated in what manner a declarative memory task interferes with two processes that supposedly underly force field adaptation in reaching. This declarative memory task, which involved learning of a list of words, was assessed through either recognition or recall, and was compared to a non-declarative, vowel counting task, using a within-subject design (n=32). We employed a Bayesian hierarchical dual-rate process model to capture the observed force compensation across trials, expecting that the parameters of the fast process would be affected by the declarative memory task. We examined the 95% highest density interval of the posterior distribution of the difference between the experimental and control condition for each parameter. While most parameters remained unaffected by the declarative memory task, the retention rate of the fast process showed a hint of reduction, suggesting a complex interplay between declarative memory and ongoing motor adaptation processes.

Neuronal fatty acid oxidation fuels memory after intensive learning
Metabolic flexibility allows cells to adapt to different fuel sources, which is particularly important for cells with high metabolic demands. In contrast, neurons, which are major energy consumers, are considered to rely almost solely on glucose and its derivatives to support their metabolism [ref 1-3]. Here, using Drosophila melanogaster, we show memory formed after intensive massed training is dependent on mitochondrial fatty acid (FA) {beta}-oxidation to produce ATP in neurons of the mushroom bodies (MB), a major integrative center in insects' brain. We identify neuronal lipid droplets as the main source of FAs for this type of memory. Furthermore, we demonstrate that this intensive massed training is associated with mitochondria network remodeling in the soma of MB neurons, resulting in increased mitochondrial size. Artificially increasing mitochondria size in adult MB neurons increases ATP production in their soma and, at the behavioral level, strikingly results in improved memory performance after massed training. These findings challenge the prevailing view that neurons are unable to use FAs for energy production, and importantly revealing on the contrary that in vivo neuronal FA oxidation has an essential role in cognitive function, including memory formation.

Temporal dynamics of energy-efficient coding in mouse primary visual cortex
Sparse coding enables cortical populations to represent sensory inputs efficiently, yet its temporal dynamics remain poorly understood. Consistent with theoretical predictions, we show that stimulus onset triggers broad cortical activation, initially reducing sparseness and increasing mutual information. Subsequently, competitive interactions sustain mutual information as activity declines and sparseness increases. Notably, coding efficiency, defined as the ratio of mutual information to metabolic cost, progressively increases, demonstrating the dynamic optimization of sensory representations.

Cell type transcriptional identities are maintained in cultured ex vivo human brain tissue
It is becoming more broadly accepted that human-based models are needed to better understand the complexities of the human nervous system and its diseases. The recently developed human brain organotypic culture model is one highly promising model that requires the involvement of neurosurgeons and neurosurgical patients. Studies have investigated the electrophysiological properties of neurons in such ex vivo human tissues, but the maintenance of other cell types within explanted brain remains largely unknown. Here, using single-nucleus RNA sequencing, we systematically evaluate the transcriptional identities of the various cell types found in six patient samples after fourteen days in culture (83,501 nuclei from day 0 samples and 45,738 nuclei from day 14 samples). We used two pediatric temporal lobectomy samples, an adult frontal cortex sample, two IDH wild-type glioblastoma samples, and one medulloblastoma sample. We found remarkably high correlations of day 14 transcriptional identities to day 0 tissue, especially in tumor cells (r = 0.87 to 0.95), though microglia (r = 0.86), inhibitory neurons (r = 0.80), and oligodendrocytes (r = 0.75) showed strong preservation of their transcriptional profiles as well. Astrocytes and excitatory neurons showed more moderate preservation (r = 0.65 and 0.54, respectively). Because the main difficulty with organotypic brain cultures is the acquisition of human tissue, which is readily available to neurosurgeons, this model is easily accessible to neurosurgeon-scientists and neurosurgeons affiliated with research laboratories. Broad uptake of this more representative model should prompt advances in our understanding of these uniquely human diseases, lead to more reliable clinical trial performance, and ultimately yield better therapies for our patients.

Task and Behavior-Related Variables Are Encoded by the Postrhinal and Medial Entorhinal Cortex During Non-Spatial Associative Learning
The medial entorhinal cortex (MEC) is pivotal in spatial computations and episodic memory. However, it remains elusive whether MEC could play a more general role in different types of associative learning and how the representations develop during the learning process. It has been shown that the postrhinal cortex (POR), which is directly connected to MEC, integrates visual stimuli with salient outcomes. Here, we use a non-spatial visual association task to investigate whether MEC neurons represent low-level visual cues during learning. Using a Go/NoGo visual association task, we recorded neural activity in MEC and POR throughout the learning phase as mice associated drifting gratings with rewarded, aversive, or neutral outcomes. Our findings reveal that the neural tuning curves in both the POR and MEC change with the learning of the task. From the start of training, the POR neurons exhibited response tuning to the visual cues, and the tuning was stable to cue orientations during learning. In contrast, MEC neurons did not initially respond very strongly to visual cues but developed a robust tuning toward the rewarded trials. While the MEC representation of visual information was limited, it encoded other task elements. A large fraction of the neurons formed distinct functional clusters that were either activated or suppressed by reward-related behavior. Remarkably, these clusters segregated anatomically in MEC and maintained strong within-cluster correlations before and after training. Notably, although the same functional clusters were apparent in the POR, they did not show any anatomical structure as in the MEC. Task reversal induced significant changes in network responses across both regions, with a decrease in overall task-responsive neurons but a slight increase in stimulus representation. Strikingly, information about the choice to lick emerged with learning in both brain areas, and most significantly within the functional cell clusters representing reward consumption and plus-cue stimulus. Our results demonstrate that although neurons in MEC and POR develop behavior-modulated tuning during learning of a non-spatial visual association task, the MEC exhibits stronger within-cluster correlations and anatomical organization. Conversely, the POR population exhibits less structural organization and more specific stimulus-tuning, which is reflective of being a higher visual association area. Our findings reveal that the MEC can encode task- and behavior-related variables beyond spatial information.

Capturing Dynamic Neuronal Responses to Dominant and Subordinate Social Hierarchy Members with catFISH
Dominance hierarchies are key to social organization in group-living species, requiring individuals to recognize their own and others' ranks. This is particularly complex for intermediate-ranking animals, who navigate interactions with higher- and lower-ranking individuals. Using in situ hybridization, we examined how the brains of intermediate-ranked mice in hierarchies respond to dominant and subordinate stimuli by labeling activity-induced immediate early genes and neuronal markers. We show that distinct neuronal populations in the amygdala and hippocampus respond differentially across social contexts. In the basolateral amygdala, glutamatergic Slc17a7+ neurons, particularly dopamine-receptive Slc17a7+Drd1+ neurons, show elevated IEG expression in response to social stimuli, with a higher response to dominant over subordinate animals. Similar patterns are observed among Slc17a7+Oxtr+ neurons in the dorsal endopiriform nucleus and GABAergic Slc32a+ neurons in the medial amygdala. We also identified distinct neural ensembles selectively active in response to dominant and subordinate hierarchy members. We find a higher degree of reactivation among Slc17a7+Oxtr+ ensembles in the dorsal endopiriform nucleus in animals repeatedly presented with the same hierarchy member, as opposed to those presented with a dominant and subordinate member. We observe a similar pattern among Oxtr+ neurons in the dentate gyrus hilus, while the inverse is observed among Slc17a7+ Avrp1b+Oxtr+ neurons in the distal CA2CA3 region. Collectively, our findings reveal how social context is associated with activity changes in social, olfactory, and memory systems in the brain at the neuronal cell type level. This work lays the foundation for further precise cell-type investigation into how the brain processes social information.

Theory of axo-axonic inhibition
The axon initial segment of principal cells of the cortex and hippocampus is contacted by GABAergic interneurons called chandelier cells. The anatomy, as well as alterations in neurological diseases such as epilepsy, suggest that chandelier cells exert an important inhibitory control on action potential initiation. However, their functional role remains unclear, including whether their effect is indeed inhibitory or excitatory. One reason is that there is a relative gap in electrophysiological theory about the electrical effect of axo-axonic synapses. This contribution uses resistive coupling theory, a simplification of cable theory based on the observation that the small initial segment is resistively coupled to the large cell body acting as a current sink, to fill this gap. The main theoretical finding is that a synaptic input at the proximal axon shifts the action potential threshold by an amount equal to the product of synaptic conductance, driving force at threshold, and axial axonal resistance between the soma and either the synapse or of the middle of the initial segment, whichever is closer. The theory produces quantitative estimates useful to interpret experimental observations, and supports the idea that axo-axonic cells can potentially exert powerful inhibitory control on action potential initiation.

Widespread Distribution of α-Synuclein Oligomers in LRRK2-related Parkinson's Disease
Mutations in leucine-rich repeat kinase 2 (LRRK2) are the most common cause of familial and sporadic Parkinson's disease (PD). While the clinical features of LRRK2-PD patients resemble those of typical PD, there are significant differences in the pathological findings. The pathological hallmark of definite PD is the presence of -synuclein (SYN)-positive Lewy-related pathology; however, approximately half of LRRK2-PD cases do not have Lewy-related pathology. Lewy-related pathology is a late-stage SYN aggregation that can be visualized with hematoxylin and eosin stains or conventional immunohistochemistry (IHC). Increasing evidence has indicated that SYN oligomers, which represent the early-stage of SYN aggregation, may have neurotoxicity. Visualization of SYN oligomers requires specialized staining techniques, such as SYN-proximity ligation assay (PLA). The distribution and severity of SYN oligomers in the human brain of LRRK2-PD patients remain unknown. In this study, we performed phosphorylated SYN-IHC and SYN-PLA staining on postmortem brain sections of patients with three pathogenic LRRK2 mutants: p.G2019S (n=5), p.I2020T (n=5), and p.R1441C (n=4). The severity of Lewy-related pathology and SYN oligomers were assessed semi-quantitatively in the brainstem, limbic lobe, basal ganglia, and cerebral cortex. SYN oligomers were detected in LRRK2-PD cases even in cases without Lewy-related pathology; a negative correlation was observed between Lewy-related pathology and SYN oligomers (r=-0.26 [-0.39, -0.12]; P<0.0001). Our findings suggest that SYN oligomers may represent a common pathological feature of LRRK2-PD. Notably, patients harboring p.G2019S and p.I2020T had significantly higher levels of SYN oligomers in those without Lewy-related pathology compared to those with Lewy-related pathology. These cases also had a trend toward shorter disease duration. These results imply that in LRRK2-PD, SYN oligomers may initially accumulate in the brain but do not progress to form Lewy-related pathology. The present study suggests that targeting SYN oligomers may be a therapeutic strategy for LRRK2-PD even if there is no Lewy-related pathology.

Abundant non-inclusion α-synuclein pathology in Lewy body-negative LRRK2-mutant cases
Lewy body diseases are common neurodegenerative diseases, including Parkinson's disease (PD) and dementia with Lewy bodies, which lead to both motor and non-motor symptoms. They are neuropathologically characterized by loss of neuromelanized neurons in the substantia nigra pars compacta and -synuclein-immunopositive inclusions (Lewy bodies) in several types of neurons in the brain. A fraction of monogenic PD cases, however, represent a conundrum, as they can present with clinical Lewy body disease but do not have Lewy bodies upon neuropathological examination. For LRRK2, the presence or absence of Lewy bodies is not related to any specific mutation in the gene and different clinical presentation and neuropathology can be present even in the same family. Here, we present the first evidence of widespread -synuclein accumulation detected with proximity ligation assay (PLA) using the MJFR14-6-4-2 antibody in six Lewy body-negative LRRK2 cases and compare the levels with five patients with neuropathologically-verified Lewy body disease cases and six healthy controls. We show that non-inclusion, aggregated -synuclein PLA signal is dominant in the LRRK2 cases, while Lewy-like PLA signal is predominant in late-stage Lewy body disease. Furthermore, LRRK2 cases displayed prominent PLA signal in pontocerebellar tracts and inferior olivary nuclei in the brainstem, which was not seen in idiopathic PD cases. These results suggest that Lewy-body negative -synuclein aggregation in neurons but rather a deficiency in the formation of inclusions. Keywords: -synuclein, Lewy body disease, LRRK2, neurodegeneration, non-inclusion pathology, proximity ligation assay

Birthdate aligns vestibular sensory neurons with central and motor partners across a sensorimotor reflex circuit for gaze stabilization
Developing populations of connected neurons often share spatial and/or temporal features that anticipate their assembly. A unifying spatiotemporal motif might link sensory, central, and motor populations that comprise an entire circuit. In the sensorimotor reflex circuit that stabilizes vertebrate gaze, central and motor partners are paired in time (birthdate) and space (dorso-ventral). To determine if birthdate and/or dorso-ventral organization could align the entire circuit, we measured the spatial and temporal development of the sensory circuit node: the vestibular ganglion neurons. We discovered progressive dorsal-to-ventral development in the vestibular ganglion that diverges from its functional (rostrocaudal) organization. With an acute optical lesion and calcium imaging paradigm, we found that this common spatiotemporal axis anticipated functional sensory-to-central partner matching. We propose a "first-come, first-served" model in which birthdate organizes the sensory, central, and motor populations that comprise the gaze stabilization circuit. Our work suggests a general means for poly-synaptic circuit assembly across embryonically-diverse neural populations.

Postnatal Sensory Experience and Barrel Cortex Alterations Anticipate Autistic Traits in a Mouse Model of Cdkl5 Deficiency Disorder
Autistic traits may arise from atypical sensory experience during postnatal life, but whether there is a causal link between defects in cortical circuitry in the brain, altered sensory processing and social behavior remains unknown. Here, we studied tactile stimuli processing in the barrel cortex (BC) and social interactions in juvenile male mice lacking Cyclin-dependent kinase-like 5 (CDKL5), a model of a severe neurodevelopmental disease showing autistic traits and sensory impairments. We identified in these mice defects of whisker-dependent postnatal sensorimotor reflexes, NMDA receptors-dependent signaling, and dendritic orientation in thalamic inputs-receiving spiny stellate neurons. We also found that CDKL5 is required for mapping and processing whisker-derived tactile stimuli in the BC. Intriguingly, KO mice show autistic traits at p21 that are rescued by neonatal CDKL5 replacement in the BC. Our data suggest that CDKL5 is required to link tactile processing in the BC to the onset of social interaction abilities.

A hybrid micro-ECoG for functionally targeted multi-site and multi-scale investigation
Brain function relies on the coordination of activity across a wide range of spatial and temporal scales. The activity of single neurons depends on their unique pattern of local and long-range connectivity and thus on the coordination of local activity with large-scale patterns of distributed activity across brain-wide networks. Understanding integrated, whole brain function requires new tools capable of recording from anatomically connected populations in distributed brain areas to bridge local and global dynamics. Here, we present high-density, micro-electrocorticography arrays that facilitate multi-scale studies of brain activity. The arrays are hybrid designs that integrate the desirable features of silicone elastomers and polyimide films. The silicone elastomer superstructure provides optical transparency and permits repeated mechanical penetration with rigid linear electrode arrays. The polyimide films provide the capacity for fine feature definition through photolithography. This combination facilitates high-throughput functional mapping of areas of interest to target functionally characterized populations for refined, dense sampling. We demonstrate the suitability of the technique for functional mapping of cortical regions in rats, cats and marmosets and the benefit of the resulting functional maps for targeting functionally defined populations for dense, multi-area laminar recordings. Finally, we demonstrate the utility of the hybrid micro-ECoG to localize optogenetically evoked feedforward excitation in down-stream cortical regions to investigate cortico-cortical interactions. Together, these capabilities make the hybrid micro-ECoG a compelling tool for systems neuroscience.

Cortical connectivity, local dynamics and stability correlates of global conscious states
Consciousness emerges from complex neural processes, yet its precise neurobiological correlates remain uncertain. Here a space-time-resolved inference-based framework is applied to estimate the neurophysiological variables of a whole-cortex model and analyze the neural mechanism correlates of global consciousness by way of a correlation analysis between behavioural and neural variable time-series. Using magnetoencephalography (MEG) data from 15 participants under Xenon-induced anesthesia, interconnected neural mass models (NMMs) were developed and time-evolving regional neurophysiological variables and inter-regional connectivity strengths were inferred from the data. Analyses revealed significant correlations between consciousness levels and inter-regional connectivity, particularly in posterior parietal, occipital, and prefrontal regions. Moreover, results support a parietal, rather than frontal, network backbone to facilitate global consciousness. Regional-level analyses further identified correlates of consciousness within the posterior parietal and occipital regions. Lastly, reductions in consciousness were linked to stabilized cortical dynamics, reflected by changes in the eigenmodes of the system. This framework provides a novel, inference-based approach to investigating consciousness, offering a time-resolved perspective on neural mechanism correlates during altered states.

Test-retest reliability of TMS-evoked potentials over fMRI-based definitions of non-motor cortical targets
Objective: This study assessed the test-retest reliability of TMS evoked potentials (TEPs) across two cortical regions: dorsolateral prefrontal cortex (DLPFC), and angular gyrus in comparison to motor cortex (M1), using individualized and literature based targeting approaches. The study compared the reliability of single pulse TMS, short interval intracortical inhibition (SICI), and long-interval intracortical inhibition (LICI) protocols to evaluate TEP consistency in these regions. Methods: Seventeen healthy participants underwent two TMS EEG sessions spaced by at least one week, with targets for DLPFC and angular gyrus identified using resting-state functional connectivity (RS) and Neurosynth based functional overlays. Motor cortex was targeted using resting motor threshold (RMT). Early TEPs were quantified as peak-to-peak amplitude. Test retest reliability of early TEPs was calculated using the concordance correlation coefficient (CCC) for each region and protocol. Results: M1 demonstrated the highest TEP reliability (CCCmean = 0.59), while DLPFC (CCCmean = 0.40) and angular gyrus (CCCmean = 0.45) showed lower reliability, particularly for anterior DLPFC targets. Neurosynth-based DLPFC targets exhibited slightly higher CCC values (mean CCC = 0.57) compared to RS-based targets (mean CCC = 0.30), but the difference was not statistically significant. No significant differences in reliability were found across single pulse and paired pulse protocols. Lateral targets, DLPFC and angular gyrus, showed lower reliability in comparison to motor cortex which might have been caused by muscle artifacts. Conclusion: While individualized functional targeting methods provide advantages in engaging specific brain networks, their reliability for TEP measurements remains lower than the RMT-based approach for motor cortex. Future studies should integrate neuroimaging-based targeting with real time TEP monitoring to enhance reliability in non-motor regions. This approach could enhance the precision of TMS EEG protocols, especially for clinical applications targeting cortical regions like the DLPFC and angular gyrus.

The impact of human agents on spatial navigation and knowledge acquisition in a Virtual Environment
Concepts of spatial navigation rest on the idea of landmarks, which are immobile features or objects in the environment. However, behaviorally relevant objects or fellow humans are often mobile. This raises the question of how the presence of human agents influences spatial exploration and knowledge acquisition. Here, we investigate exploration and performance in subsequent spatial tasks within a virtual environment containing numerous human avatars. In the exploration phase, agents had a locally limited effect on navigation. They prompted participants to revisit locations with agents during their initial exploration without significantly altering overall exploration patterns or the extent of the area covered. However, agents and buildings competed for visual attention. When spatial recall was tested, pointing accuracy toward buildings improved when participants directed their attention to the buildings and nearby agents. In contrast, pointing accuracy for agents showed weaker performance and did not benefit from visual attention directed toward the adjacent building. Active agents and incongruent agent-environment pairings further enhanced pointing accuracy, revealing that violations of expectations by agents can significantly shape navigational knowledge acquisition. Overall, agents influenced spatial exploration by directing attention locally, with the interaction between agent salience and environmental features playing a key role in shaping navigational knowledge acquisition.

Parental kynurenine 3-monooxygenase genotype in mice directs sex-specific behavioral outcomes in offspring
Background: Disruptions in brain development can impact behavioral traits and increase the risk of neurodevelopmental conditions such as autism spectrum disorder, attention-deficit/hyperactivity disorder (ADHD), schizophrenia, and bipolar disorder, often in sex-specific ways. Dysregulation of the kynurenine pathway (KP) of tryptophan metabolism has been implicated in cognitive and neurodevelopmental disorders. Increased brain kynurenic acid (KYNA), a neuroactive metabolite implicated in cognition and sleep homeostasis, and variations in the Kmo gene, which encodes kynurenine 3-monooxygenase (KMO), have been identified in these patients. We hypothesize that parental Kmo genetics influence KP biochemistry, sleep behavior and brain energy demands, contributing to impairments in cognition and sleep in offspring through the influence of parental genotype and genetic nurture mechanisms. Methods: A mouse model of partial Kmo deficiency, Kmo heterozygous (HET-Kmo+/-), was used to examine brain KMO activity, KYNA levels, and sleep behavior in HET-Kmo+/- compared to wild-type control (WT-Control) mice. Brain mitochondrial respiration was assessed, and KP metabolites and corticosterone levels were measured in breast milk. Behavioral assessments were conducted on wild-type offspring from two parental groups: i) WT-Control from WT-Control parents, ii) wild-type Kmo (WT-Kmo+/+) from Kmo heterozygous parents (HET-Kmo+/-). All mice were C57Bl/6J background strain. Adult female and male offspring underwent behavioral testing for learning, memory, anxiety-like behavior and sleep-wake patterns. Results: HET-Kmo+/- mice exhibited reduced brain KMO activity, increased KYNA levels, and disrupted sleep architecture and electroencephalogram (EEG) power spectra. Mitochondrial respiration (Complex I and complex II activity) and electron transport chain protein levels were impaired in the hippocampus of HET-Kmo+/- females. Breast milk from HET-Kmo+/- mothers increased kynurenine exposure during lactation but corticosterone levels were unchanged. Compared to WT-Control offspring, WT-Kmo+/+ females showed impaired spatial learning, heightened anxiety, reduced sleep and abnormal EEG spectral power. WT-Kmo+/+ males had deficits in reversal learning but no sleep disturbances or anxiety-like behaviors. Conclusions: These findings suggest that Kmo deficiency impacts KP biochemistry, sleep behavior, and brain mitochondrial function. Even though WT-Kmo+/+ inherit identical genetic material as WT-Control, their development might be shaped by parental physiology, behavior, or metabolic state influenced by their Kmo genotype, leading to phenotypic sex-specific differences in offspring.

Neurons and molecules involved in noxious light sensation in Caenorhabditis elegans
Ultraviolet (UV) light is dangerous to unpigmented organisms, inducing photodamage of cells and DNA. The transparent nematode Caenorhabditis elegans, despite having no eyes, detects light and exhibits negative phototaxis in order to evade sunlight. UV absorption is detected by the photosensor protein LITE-1, that also responds to reactive oxygen species. We investigated which neurons act as noxious photosensors and how they transmit the sensation to the nervous system to evoke escape behavior. We identified the interneuron AVG as a main focus of LITE-1 function in mediating the noxious light evoked escape behavior, with minor roles of the interneuron PVT, the sensory ASK neurons and touch receptor neurons. AVG is activated by blue light, and its optogenetic stimulation causes escape behavior. Signaling from AVG involves chemical neurotransmission, likely directly to premotor interneurons, and to other cells, by extrasynaptic signaling through the neuropeptide NLP-10. NLP-10 signaling is not required for the acute response, but for maintaining responsiveness to repeated noxious stimuli. The source of NLP-10 is largely AVG, however, also other cells contribute, possibly PVT, expressing both LITE-1 and NLP-10. This work uncovers entry points of sensory information to the neuronal circuits mediating the behavioral response to noxious UV/blue light.

Upright stance is controlled close to critical stability across different postures
Feedback stabilization of upright standing postures should be reflected by a time-lagged relationship between the ground reaction force (GRF) and the center of mass (COM) state. In this study, we propose a model relating corrective ground reaction forces (Fcorr) to preceding COM position (PCOM) and velocity (VCOM). We first checked the model's validity by simulating an inverted pendulum model with known intrinsic and feedback parameters, to see if we could identify the feedback parameters. Next, we tested this model in 14 young adult volunteers standing in different postures. Our model effectively reconstructed Fcorr in both simulations (R2: 0.50~0.99) and human experimental data (R2: 0.76~0.99). Strikingly, estimated position and velocity gains were similar across postures even between bipedal and unipedal standing, with the position gain slightly above critical stiffness. The estimated delay in normal standing (246{+/-}21ms) was significantly larger than that in unipedal standing and step posture (204{+/-}24ms and 193{+/-}29ms, respectively). In conclusion, our results support that an estimate of the COM state is used to generate corrective ground reaction forces to stabilize upright posture, and our feedback model can be used to characterize this control mechanism. The proposed model requires only easily measurable inputs which may yield value in assessment of balance disorders. Notably, our results showed that stability of upright stance is achieved by maintaining feedback gains at levels just above critical stability.

Does Precision Grip Research Extend to Unconstrained, Multidigit Grasping?
Most daily tasks require using our hands. Whether taking a sip from a glass or throwing a ball, we effortlessly select appropriate grasps. Yet, despite many possible hand configurations, most grasping research has focused on the finger-and-thumb precision grip. We thus questioned whether findings on precision grip hold under unconstrained grasping conditions. To test this, we compared how participants grasped 3D objects made of brass and wood, with both precision grip and unconstrained grasps. When unconstrained, participants rarely selected precision grips, favoring multi-digit grasps. Nevertheless, in both conditions, participants shifted grasps towards the objects center of mass and, when grasp factors conflicted, the variability in their selections increased, indicating greater uncertainty about the optimal strategy. Further, despite favoring multidigit grasps, participants consistently placed the thumb and index finger on the same positions on the objects, suggesting that in multidigit grasps, the additional fingers primarily provided support. Our findings thus reveal that object material affects unconstrained grasping similarly to precision grip and imply that previous precision grip research may extend to unconstrained, multidigit conditions.

Binding items to contexts through conjunctive neural representations with the Method of Loci
Schematic prior knowledge can provide a powerful scaffold for episodic memories, yet the neural mechanisms underlying this scaffolding process are still poorly understood. A crucial step of the scaffolding process is the way in which details of a new episode are connected to an existing schema, forming a robust memory representation that can be easily accessed in the future. A unique testbed for studying this binding process is a mnemonic technique called the Method of Loci (MoL), in which people meaningfully connect items to be remembered with a well-learned list of imagined loci. We collected fMRI data from participants in 3 longitudinal sessions while they were enrolled in a month-long MoL training course, all of whom showed dramatic improvements in their ability to remember lists of 20 or 40 words. We obtained neural patterns when the loci and objects are presented by themselves, when they are combined into an integrated representation at encoding, and when the integrated representation was subsequently retrieved, as well as verbal descriptions from the participants about the way they associated each item to each locus. We found that in default mode network regions, including medial prefrontal cortex (mPFC), the combined representations of loci and items are highly conjunctive: the unified locus-item representation was substantially different from a linear combination of the isolated locus and item representation, reflecting the addition of new integrative details specific to each combined pair. The conjunctive component of the representation reflected the particular creative details generated by individual participants and increased over time as participants gained expertise in MoL. Our findings reveal a critical role for the default mode network in creating meaningful connections between new information and well-learned schematic contexts.

Aberrant Neuronal Synchronization Associated with Cognitive Deficits in a Rodent Model of Childhood Cranial Irradiation
Cranial radiation can be a life-saving intervention in pediatric brain cancer therapy but often results in debilitating cognitive decline. To clarify the underlying mechanisms of these side-effects we have here recorded neurophysiological activity in distributed brain networks involved in decision-making and memory functions in adult rats exposed to cranial irradiation on postnatal day 21. Multi-structure local field potential (LFP) recordings revealed decreased power in irradiated animals in the 4-9 Hz frequency band. Additionally, a distinct slowing of the oscillatory activity was observed preceding erroneous choice in a decision-making task. Moreover, irradiated rats showed reduced dynamics and a fragmented pattern of inter-structural coherence across different phases of the task. Our results suggest that the cognitive deficits and reduced processing speed following irradiation of the juvenile brain arise as a consequence of changes in long-range functional connectivity, including thalamocortical circuits, causing abnormally slow and spatially fractionated patterns of coordinating LFP activity.

Distinct roles for MNK1 and MNK2 in social and cognitive behavior through kinase-specific regulation of the synaptic proteome and phosphoproteome
Local mRNA translation is required for adaptive changes in the synaptic proteome. The mitogen-activated protein kinase (MAPK) interacting protein kinases 1 and 2 (MNK1 and MNK2) have emerged as key regulators of neuronal translation, primarily through phosphorylation of the eukaryotic initiation factor 4E (eIF4E). The therapeutic benefits of targeting the MNKs are being investigated for nervous system conditions and disorders that affect translation, including autism, pain, and cancer. However, it is still unclear if MNK1 and MNK2 regulate distinct aspects of neuronal translation and how the activity of each kinase is associated with the synaptic and behavioral features linked to MNK signaling. To examine the individual neurobiological functions of each kinase, we used knockout mice lacking either MNK1 or MNK2. We found that the knockout of MNK1 and MNK2 leads to different social and cognitive behavioral profiles and distinct alterations of the cortical synaptic proteome, transcriptome, and phosphoproteome. Loss of MNK1 was associated with an increase in ribosomal protein expression, whereas deletion of MNK2 decreased the expression and phosphorylation of synaptic proteins. Together, our findings provide evidence for a high degree of functional specialization of the MNKs in synaptic compartments and suggest that pharmacological inhibition of individual MNK may provide more specific targets for neurological disorders.

Molecular architecture of human dermal sleeping nociceptors
Human dermal sleeping nociceptors display ongoing activity in neuropathic pain, affecting 10% of the population. Despite advances in rodents, a molecular marker for these mechano-insensitive C-fibers (CMis) in human skin remains elusive, preventing targeted therapy. In this translational Patch-seq study, we combine single-cell transcriptomics following electrophysiological characterization with single-nucleus and spatial transcriptomics from pigs and humans. We functionally identified CMis in pig sensory neurons with patch-clamp using adapted protocols from human microneurography. We identified oncostatin-M-receptor (OSMR) and somatostatin (SST) as marker genes for CMis. Following dermal injection in healthy human volunteers, oncostatin-M, the ligand of OSMR, exclusively modulates CMis. We identified the entire molecular architecture of human dermal sleeping nociceptors, providing new therapeutic targets and the basis for a mechanistic understanding of neuropathic pain.

Stimulation parameters shape effective connectivity pathways: insights from microstate analysis on TMS-evoked potentials
Transcranial magnetic stimulation (TMS)-evoked potentials (TEPs) represent an innovative measure for examining brain connectivity and developing biomarkers of psychiatric conditions. Minimising TEP variability across studies and participants, which may stem from methodological choices, is therefore vital. By combining classic peak analysis and microstate investigation, we tested how TMS pulse waveform and current direction may affect effective connectivity when targeting the primary motor cortex (M1). We aim to disentangle whether changing these parameters affects the degree of activation of the same neural circuitry or may lead to changes in the pathways through which the induced activation spreads. Thirty-two healthy participants underwent a TMS-EEG experiment in which the pulse waveform (monophasic, biphasic) and current direction (posterior-anterior, anterior-posterior, latero-medial) were manipulated. We assessed the latency and amplitude of M1-TEP components and employed microstate analyses to test differences in topographies. Results revealed that TMS parameters strongly influenced M1-TEP components' amplitude but had a weaker role over their latencies. Importantly, microstate analysis showed that the current direction in monophasic stimulations changed the pattern of evoked microstates at the early TEP latencies, as well as their duration and the overall amount of activated brain resources associated. This study shows that the current direction of monophasic pulses may modulate cortical sources contributing to TEP signals, activating neural populations and cortico-cortical paths more selectively. Biphasic stimulation reduces the variability associated with current direction and may be better suited when TMS targeting is blind to anatomical information.

Food-entrainment of circadian timekeeping in the dorsal vagal complex
The dorsal vagal complex (DVC) is a multi-component brainstem satiety centre which has gained attention as a key target of anti-obesity pharmacotherapies. Our recent studies revealed its circadian timekeeping properties, with molecular and electrophysiological 24h rhythms persisting independently of the primary hypothalamic clock. However, the factors entraining these brainstem oscillators, and the downstream transcriptional targets of the DVC molecular clock remain unclear. Here, using fluorescent in situ hybridisation, we demonstrate core clock gene expression in inhibitory and excitatory neuronal populations of the DVC, as well as in its output cholinergic vagal neurons. We further reveal that the molecular clock is associated with rhythmic expression of numerous neurotransmitter receptor genes in the DVC in vivo, with the phase of both clock and clock-controlled gene expression tightly regulated by meal timing. These findings uncover food-entrained circadian rhythms in the DVC and have important implications for clinical studies targeting brainstem satiety mechanisms.

Dietary iron deficiency in the adult mouse increases brain endothelial uptake and blood-brain barrier transport of a high-affinity, anti-transferrin receptor antibody
Background and objectives: Brain capillary endothelial cells (BCECs) express transferrin receptor 1 (TfR1) to ensure sufficient iron transport into the brain across the blood-brain barrier (BBB). Our main objective was to examine adult mice subjected to dietary iron deficiency (ID) for possible changes in the content of TfR1 in BCECs and the influence thereof on the uptake and transport of high-affinity anti-transferrin receptor IgG1 antibodies (clone Ri7217). Material and methods: We subjected adult, female mice to dietary ID for 8 weeks. Iron and copper were measured using inductively coupled plasma mass spectrometry (ICP-MS) in various tissues, including total brain and isolated brain capillaries. Possible effects of ID on cerebral angioarchitecture were estimated using 3D confocal microscopy of optically cleared brain samples with endothelium labelled using intravenous injection of wheat germ agglutinin with subsequent machine learning-based segmentation and vascular tracing. TfR1 was quantified using ELISA. Ri7217 antibodies were conjugated with 1 nm nanogold and brain uptake quantified using ICP-MS. Results: ID significantly reduced the iron content in isolated brain capillaries, liver, spleen, kidney, heart and skeletal muscles. ID increased the copper content in the brain. Analysis of cerebral cortex angioarchitecture revealed no changes following dietary ID except for a minor increase in tortuosity of small-caliber vessels. TfR1 protein was unchanged in the total brain and isolated brain capillaries. In contrast, uptake of nanogold-conjugated Ri7217 increased in the total brain, the supernatant fraction of isolated brain capillaries representing the post-vascular compartment, liver, spleen, and dissected retinae. Conclusions: Targeting TfR1 in ID revealed increased uptake and transport across the BBB of Ri7217 antibodies. Possibly the elevated transport of transferrin receptors through BCECs is due to the increased trafficking of transferrin receptor-containing vesicles in ID, which appeared to have no major effects on the brain angioarchitecture.

Source to sensor coupling (SoSeC) as an effective tool to localize interacting sources from EEG and MEG data
A standard approach to estimate interacting sources from EEG or MEG data is to first calculate a coupling between all pairs of voxels on a predefined grid within the brain and then average or maximize this coupling matrix along each column or row. Depending on the chosen coupling measure and grid size this approach can be computationally very costly, in particular when a bias is supposed to be removed. We here suggest to replace this approach by a maximization of coupling between each source and the signal in sensor space. The idea is that any neuronal activity which can be estimated from recorded data must be present in sensor space in the first place. Using the imaginary part of coherency as coupling measure makes sure that we do not confuse this source to sensor coupling with a coupling of a source to itself. We found that this approach is hundreds of times faster than the conventional approach. Results for EEG resting state data indicate that the new approach has more statistical power than the conventional approach. The presentation of this specific method is augmented with a discussion of conceptual issues for various forms of vector beamformers and eLoreta.

A comprehensive spatiotemporal map of dystrophin isoform expression in the developing and adult human brain
Mutations in the dystrophin gene (DMD) cause the severe muscle-wasting disease Duchenne Muscular Dystrophy (DMD). Additionally, there is a high incidence of intellectual disability and neurobehavioural comorbidities in individuals with DMD. Similar behavioural abnormalities are found in mdx dystrophic mouse models. Unlike muscle, several dystrophin isoforms are expressed in the human brain, but a detailed map of regional and cellular localisation of dystrophin isoforms is missing. This is crucial in understanding the neuropathology of DMD individuals, and for evaluating the translatability of pre-clinical findings in DMD mouse models receiving genetic therapy interventions. Here, we provide a comprehensive dystrophin expression profile in human brains from early development to adulthood. We reveal expression of dp427p2, dp427c, dp427m and dp40 isoforms in embryonic brains, not previously reported. Dp427p2 and dp140 were greatly downregulated in adult brains, although the latter continued to be expressed across several regions. Importantly, we demonstrate for the first-time expression of DMD transcripts in human motor neurons and co-expression of different dystrophin isoforms within single neurons in both developing and adult brains. Finally, we show localisation of DMD transcripts with GAD1+ GABAergic-associated transcripts in neurons including cerebellar Purkinje cells and interneurons, as well as in the majority of neocortical and hippocampal SLC17A7+ glutamatergic neurones, suggesting a role for dystrophin in signalling at the neuronal inhibitory and excitatory synapses.

Increased cerebrospinal fluid and plasma apoE glycosylation is associated with reduced levels of Alzheimer's disease biomarkers
The apolipoprotein E (APOE4) allele is the strongest genetic risk factor for Alzheimers disease (AD). ApoE is glycosylated with an O-linked Core-1 sialylated glycan at several sites, yet the impact and function of this glycosylation on AD biomarkers remains unclear. We examined apoE glycosylation in a cohort of cerebrospinal fluid (CSF, n=181) and plasma (n= 178) samples from the Alzheimers Disease Neuroimaging Initiative (ADNI) stratified into 4 groups: cognitively normal (CN), Mild Cognitive Impairment (MCI), progressors and non-progressors based on delayed word recall performance over 4 years. We observed decreasing glycosylation from apoE2 > apoE3 > apoE4 in CSF, and in plasma (apoE3 > apoE4). ApoE glycosylation was reduced in the MCI compared with CN groups, and in progressors compared to non-progressors. In CSF, higher apoE glycosylation associated cross-sectionally with lower total tau (t-tau), p-tau181, and with higher Abeta1-42. Similar associations of apoE glycosylation with higher Abeta1-42 were observed in plasma. In CSF, greater apoE4 glycosylation was associated with lower t-tau and p-tau181. Over a 6-year period, higher baseline levels of CSF apoE glycosylation predicted lower rates of increase in CSF t-tau and p-tau181 and lower rates of decrease in CSF Abeta1-42. These results indicate strong associations of apoE glycosylation with biomarkers of AD pathology independent of apoE genotype, warranting a deeper understanding of the functional role of apoE glycosylation on AD tau pathology.

Coordinated spinal locomotor network dynamics emerge from cell-type-specific connectivity patterns
Even without detailed instruction from the brain, spinal locomotor circuitry generates coordinated behavior characterized by left-right alternation, segment-to-segment propagation, and variable-speed control. While existing models have emphasized the contributions of cellular- and network-level properties, the core mechanisms underlying rhythmogenesis remain incompletely understood. Further, neither family of models has fully accounted for recent experimental results in zebrafish and other organisms pointing to the importance of long-range, cell-type-specific connectivity patterns and recruitment of speed-selective subpopulations of interneurons. Informed by these experimental findings and others, we developed a hierarchy of increasingly detailed models of the locomotor circuit. Coordinated locomotion emerged in an inhibition-dominated network in which connectivity is determined by desired phase relationships among interneurons and variable-speed control is implemented by recruitment of speed-selective subpopulations. Further, while structured excitatory connections were not necessary for rhythmogenesis, they were useful for increasing the peak locomotion frequency, albeit at the cost of losing some control at intermediate frequencies, suggesting a basic computational trade-off between speed and control. Together, this family of models shows that network-level interactions are sufficient to generate coordinated, variable-speed locomotion, providing new interpretations of intersegmental excitatory and inhibitory connectivity, as well as the basic, recruitment-based mechanism of speed control.

Intrinsic functional connectivity delineates transmodal language functions
Communication involves the translation of sensory information (e.g., heard words) into abstract concepts according to abstract rules (e.g., the meaning of those words). Accordingly, using language involves an interplay between unimodal brain areas that process sensory information and transmodal areas that respond to linguistic input regardless of the input modality (e.g., reading sentences vs. listening to speech). Previous work has shown that intrinsic functional connectivity (iFC), when performed within individuals, can delineate a distributed language network that overlaps in detail with regions activated by a reading task. The network was widely distributed across multiple brain regions, recapitulating an organization that is characteristic of association cortex, and which suggests that the distributed language network serves transmodal, not unimodal, functions. Here, we tested whether the distributed language network encapsulates transmodal functions by assessing its degree of overlap with two language tasks, one auditory (i.e., listening to speech) and one visual (i.e., reading sentences). The results show that the distributed language network aligns well with regions activated by both tasks, supporting a transmodal function. Further, the boundaries of the distributed language network along the lateral temporal cortex serve as a good proxy for the division between transmodal language and auditory functions: presentation of sounds (i.e., filtered, incomprehensible speech) evoked activity that was largely outside of the distributed language network but closely followed the network boundaries. These findings support that individualized iFC estimates can delineate the division between sensory-linked and abstract linguistic functions. We conclude that within-individual iFC may be viable for language mapping in individuals with aphasia who cannot perform language tasks in the scanner.

Retinotopic mapping data permit accurate matching of participants across different datasets
Public sharing of neuroimaging data is becoming increasingly common for the advancement and validation of scientific research. However, this sharing poses challenges regarding privacy and data safety, and associated questions about the ownership of research data. Here we show that a simple pattern correlation algorithm can match nominally deidentified participants across two separate functional magnetic resonance imaging (fMRI) experiments. This re-identification procedure is effective despite functional maps being spatially warped to a common template brain. This work highlights the need for appropriate safeguards against possible misuse of shared neuroimaging data.

Not all cross-modal responses are explained by face movements
Recent work has claimed that most apparently cross-modal responses in sensory cortex are instead caused by the face movements evoked by stimuli of the non-dominant modality. We show that visual stimuli rarely trigger face movements in awake mice; when they occur, such movements do not explain visual responses in auditory cortex; and in simultaneous recordings, face movements drove artifactual cross-modal responses in visual but not auditory cortex. Thus face movements do not broadly explain cross-modal activity across all stimulus modalities.

The genetic architecture of cortical similarity networks
The genetic architecture of human brain networks is central to understanding the organization and evolution of the cortex, the causal relationships between brain structure and function, and the pathogenesis of heritable neuropsychiatric disorders. However, the current understanding of the genetics of brain networks remains fragmented. Here, we investigated common genetic effects on Morphometric INverse Divergence (MIND), a biologically-validated, heritable, and multimodal MRI metric of inter-areal similarity and connectivity. Using a discovery dataset (N>30,000 adults), we estimated subject-specific MIND networks from the multivariate distributions of four MRI features at each of 23 cortical areas and performed genome-wide association studies (GWAS) at each of the 276 inter-areal edges. These edge-level genetic effects were highly replicated by parallel GWAS of an independent validation dataset (N>18,000 adults). We found that strong genetic correlations between multiple edges were largely reducible to two gradients of genetically-determined cortical similarity, each of which was aligned with geodesic distance from one of the two phylogenetically primitive areas (paleocortex and archicortex) predicted by the dual origin theory of cortical evolution. Genetic MIND gradients were more heritable than comparable gradients derived from GWAS of functional MRI connectivity networks; and the paleocortical trend was genetically correlated with, and causally predictive of, functional connectivity. Finally, we identified multiple global and local genetic correlations between both MIND gradients and nine clinical diagnoses or biomedical traits, indicating that the normative genetic architecture of human brain networks is pleiotropically associated with inherited risk of neuropsychiatric disorders and systemic metabolic and immune traits. These results provide fresh insight into the dual origins of the human cortex and their implications for brain function and health.

Transcriptomic disruption and functional hypoactivity in DYT-SGCE MGE-patterned inhibitory neurons
Myoclonus Dystonia is a dystonic movement disorder caused by SGCE mutations, the underlying pathophysiology for which remains unclear. Here, we evaluated the impact of SGCE mutations on medial ganglionic eminence (MGE)-derived GABAergic neurons using patient-derived induced pluripotent and gene edited embryonic stem cell lines, each compared to their isogenic wild-type control. No significant differences were observed in markers of neuronal development however, single-cell RNA sequencing demonstrated transcriptomic dysregulation in genes related to axonal organization, synaptic signalling, and action potential generation in the SGCE-mutation harbouring neurons. Functional assays demonstrated reduced neurite outgrowth, lower calcium responses to GABA, and decreased neuronal excitability and network activity in the SGCE-mutant neurons. These findings contrast with the hyperexcitable phenotype previously observed in SGCE-mutant cortical glutamatergic neurons. Collectively, this supports loss of neuronal inhibitory activity, and disruption to the neuronal excitatory/inhibitory balance in motor circuits, in contributing to the overall hyperkinetic clinical phenotype in Myoclonus Dystonia.

Time restricted feeding with or without ketosis influences metabolism-related gene expression in a tissue-specific manner in aged rats
Many of the hallmarks of aging involve alterations in cellular and organismal metabolism. One pathway with the potential to impact several traditional markers of impaired function with aging is the PI3K/AKT metabolic pathway. Regulation of this pathway includes many aspects of cellular function, including protein synthesis, proliferation and survival, as well as many downstream targets, including mTOR and FOXOs. Importantly, this pathway is pivotal to the function of every organ system in the human body. Thus, we investigated the expression of several genes along this pathway in multiple organs, including the brain, liver and skeletal muscle, in aged subjects that had been on different experimental diets to regulate metabolic function since mid-life. Specifically, rats were fed a control ad lib diet (AL), a time restricted feeding diet (cTRF), or a time restricted feeding diet with ketogenic macronutrients (kTRF) for the majority of their adult lives (from 8-25 months). We previously reported that regardless of macronutrient ratio, TRF-fed rats in both macronutrient groups required significantly less training to acquire a biconditional association task than their ad lib fed counterparts. The current experiments expand on this work by quantifying metabolism-related gene expression across tissues and interrogating for potential relationships with cognitive performance. AKT expression was significantly reduced in kTRF fed rats within liver and muscle tissue. However, AKT expression within the perirhinal cortex (PER) was higher in kTRF rats with the best cognitive performance. Within CA3, higher levels of FOXO1 gene expression correlated with poorer cognitive performance in ad libitum fed rats. Together, these data demonstrate diet- and tissue-specific alterations in metabolism-related gene expression and their correlation with cognitive status.

Sound-Evoked Plasticity Differentiates Tinnitus from Non-Tinnitus Mice
Tinnitus is the perception of non-meaningful sound in the absence of external stimuli. Although tinnitus behavior in animal models is associated with altered central nervous system activity, it is not currently possible to identify tinnitus using neuronal activity alone. In the mouse inferior colliculus (IC), a subpopulation of neurons demonstrates a sustained increase in spontaneous activity after a long-duration sound (LDS). Here, we use the 'LDS test' to reveal tinnitus-specific differences in sound-evoked plasticity through IC extracellular recordings and the auditory brainstem response (ABRLDS) in CBA/CaJ mice after sound exposure and behavioral tinnitus assessment. Sound-exposed mice showed stronger and shorter tone-evoked responses in the IC compared to unexposed controls, but these differences were not strong predictors of tinnitus. In contrast, in the LDS test, non-tinnitus mice had a significantly stronger suppression in tone-evoked spike rate compared to tinnitus and unexposed control mice. ABR peak amplitudes also revealed robust differences between tinnitus and non-tinnitus mice, with ABR peaks from non-tinnitus mice exhibiting significantly stronger suppression in the LDS test compared to tinnitus and control mice. No significant differences were seen between cohorts in ABR amplitude, latency, wave V:I ratio, wave V:III ratio, I-V intra-peak latency, and I-VI intra-peak latency. We found high-frequency tone stimuli better suited to reveal tinnitus-specific differences for both extracellular IC and ABR recordings. We successfully used the LDS test to demonstrate that tinnitus-specific differences in sound-evoked plasticity can be shown using both multi-unit near-field recordings in the IC and non-invasive far-field recordings, providing a foundation for future electrophysiological research into the causes and treatment of tinnitus.

Joint models reveal human subcortical underpinnings of choice and learning behaviour
Decision making and learning processes together enable adaptive goal-oriented behaviour. Animal studies demonstrated the importance of subcortical regions in these cognitive processes, but the human subcortical contributions remain poorly characterised. Here, we study choice and learning processes in the human subcortex, using a tailored ultra-high field 7T fMRI imaging protocol combined with joint models. Joint models provide unbiased estimates of brain-behaviour relations by simultaneously including behavioural and neural data at the participant and group level. Results demonstrate relations between subcortical regions and the adjustment of decision urgency. Value-related BOLD differences were found with opposite BOLD polarity in different parts of the striatum. Multiple sub- cortical regions showed BOLD signatures of reward prediction error processing, but contrary to expectations, these did not include the dopaminergic midbrain. Combined, this study characterises the human subcortical contributions to choice and learning, and demonstrates the feasibility and value of joint modelling in facilitating our understanding of brain-behaviour relationships.