bioRxiv Subject Collection: Neuroscience's Journal

BrainUnit: Integrating Physical Units into High-Performance AI-Driven Scientific Computing
Artificial intelligence (AI) is revolutionizing scientific research across various disciplines. The foundation of scientific research lies in rigorous scientific computing based on standardized physical units. However, current mainstream high-performance numerical computing libraries for AI generally lack native support for physical units, significantly impeding the integration of AI methodologies into scientific research. To fill this gap, we introduce BrainUnit, a unit system designed to seamlessly integrate physical units into AI libraries, with a focus on compatibility with JAX. BrainUnit offers a comprehensive library of over 2000 physical units and more than 300 unit-aware mathematical functions. It is fully compatible with JAX transformations, allowing for automatic differentiation, just-in-time compilation, vectorization, and parallelization while maintaining unit consistency. We demonstrate BrainUnit's efficacy through several use cases in brain dynamics modeling, including detailed biophysical neuron simulations, multiscale brain network modeling, neuronal activity fitting, and cognitive task training. Our results show that BrainUnit enhances the accuracy, reliability, and interpretability of scientific computations across scales, from ion channels to whole-brain networks, without significantly impacting performance. By bridging the gap between abstract computational frameworks and physical realities, BrainUnit represents a crucial step towards more robust and physically grounded AI-driven scientific computing.

Resting-state hyper- and hypo-connectivity in early schizophrenia: which tip of the iceberg should we focus on?
In this study, we explore the intricate landscape of brain connectivity in the early stages of schizophrenia, focusing on the patterns of hyper- and hypoconnectivity. Despite existing literature's support for altered functional connectivity (FC) in schizophrenia, inconsistencies and controversies persist regarding specific dysconnections. Leveraging a large sample of 100 first-episode schizophrenia patients (42 females/58 males) and 90 healthy controls (50 females/40 males), we compare the functional connectivity (FC) across 90 brain regions of the Automated Anatomical Labeling atlas. We inspected the effects of medication and examined the association between FC changes and duration of illness as well as symptom severity of the disorder. Our approach also includes a comparative analysis of two denoising strategies for functional magnetic resonance imaging data. In the group of patients, 247 region pairs exhibited greater FC, while 134 region pairs showed reduced FC compared to healthy controls. We found a significant correlation between patients' FC and symptom severity, and antipsychotic medication. However, when a more moderate denoising scheme was used, the results became significantly skewed towards hypoconnectivity in patients. Moreover, there was no relationship between FC and medication or symptom severity in the case of the moderate denoising scheme. Altogether, we found an overall balanced picture of both hyper- and hypoconnectivity in patients with schizophrenia compared to the healthy controls and unraveled a link between FC in patients and the severity of symptoms and medication. Notably, the balanced picture of FC gets significantly disrupted when less stringent data denoising is applied.

Organ-specific Sympathetic Innervation Defines Visceral Functions
The autonomic nervous system orchestrates the brain and body functions through the sympathetic and parasympathetic pathways. However, our understanding of the autonomic system, especially the sympathetic system, at the cellular and molecular levels is severely limited. Here, we show unique topological representations of individual visceral organs in the major abdominal sympathetic ganglion complex. Using multi-modal transcriptomic analyses, we identified distinct sympathetic populations that are both molecularly and spatially separable in the celiac-superior mesenteric ganglia (CG-SMG). Notably, individual CG-SMG populations exhibit selective and mutually exclusive axonal projections to visceral organs, targeting either the gastrointestinal (GI) tract or secretory areas including the pancreas and bile tract. This combinatorial innervation pattern suggests functional segregation between different CG-SMG populations. Indeed, our neural perturbation experiments demonstrated that one class of neurons selectively regulates GI food transit. Another class of neurons controls digestion and glucagon secretion independent of gut motility. These results reveal the molecularly diverse sympathetic system and suggest modular regulations of visceral organ functions through distinct sympathetic populations.

Decoding Parametric Grip-Force Anticipation from fMRI-Data
Previous functional magnetic resonance imaging (fMRI) studies have shown that activity in premotor and parietal brain-regions covaries with the intensity of upcoming grip-force. However, it remains unclear how information about the intended grip-force intensity is initially represented and subsequently transformed into a motor code before motor-execution. In this fMRI study, we used multivoxel pattern analysis (MVPA) to decode where and when information about grip-force intensities is parametrically coded in the brain. Human participants performed a delayed grip-force task in which one of four cued levels of grip-force intensity had to be maintained in working memory (WM) during a 9-second delay-period preceding motor execution. Using time-resolved MVPA, with a searchlight approach and support vector regression (SVR), we tested which brain regions exhibit multivariate WM codes of anticipated grip-force intensities. During an early delay-period, we observed above-chance decoding in the ventromedial prefrontal cortex (vmPFC). During a late delay-period, we found a network of action-specific brain regions, including the bilateral intraparietal sulcus (IPS), left dorsal premotor cortex (l-PMd) and supplementary motor areas (SMA). Additionally, cross-regression decoding was employed to test for temporal generalization of activation patterns between early and late delay-periods with those during cue presentation and motor execution. Cross-regression decoding indicated temporal generalization to the cue-period in the vmPFC, and to motor-execution in the l-IPS and l-PMd. Together, these findings suggest that the WM representation of grip-force intensities undergoes a transformation where the vmPFC encodes information about the intended grip-force, which is subsequently converted into a motor code in the l-IPS and l-PMd before execution.

Eigengene reveals invariant global spatial patterns across mouse and fish brain development
Development from a zygote to an adult organism involves complex interactions among thousands of genes. These genes exhibit highly dynamic expression across space and time. Here we report a striking simplicity amidst this complexity: Despite individual gene expression variability, the eigengene--the principal component of gene expression--exhibits an invariant global spatial pattern throughout the embryonic and post-natal stages of the mouse brain. Furthermore, the mouse pattern is observed also in the larval zebrafish, suggesting that eigengene expression is conserved over 400 million years of evolution. We show that the eigengene pattern can be explained by a simple mitotic lineage model in which daughter cells' gene expression is similar to that of their parent, but cannot be explained by one in which gene expression arises through local cellular signaling. The constrained mitotic lineage gives rise naturally to a global eigengene expression hierarchy that could provide a bias toward the formation of its dual: a spatial hierarchy of long-range signal gradients. We propose that mitosis thus induces an address-like organization, which could have been co-opted by evolution for developmental processes that require positional information over a wide range of spatial scales, such as tissue patterning and axon navigation.

Increased neuronal expression of the early endosomal adaptor APPL1 leads to endosomal and synaptic dysfunction with cholinergic neurodegeneration
Dysfunction of the endolysosomal system within neurons is a prominent feature of Alzheimer's disease (AD) pathology. Multiple AD-risk factors are known to cause hyper-activity of the early-endosome small GTPase rab5, resulting in neuronal endosomal pathway disruption. APPL1, an important rab5 effector protein, is an interface between endosomal and neuronal function through a rab5-activating interaction with the BACE1-generated C-terminal fragment ({beta}CTF or C99) of the amyloid precursor protein (APP), a pathogenic APP fragment generated within endolysosomal compartments. To better understand the role of APPL1 in the AD endosomal phenotype, we generated a transgenic mouse model over-expressing human APPL1 within neurons (Thy1-APPL1 mice). Consistent with the important endosomal regulatory role of APPL1, Thy1-APPL1 mice have enlarged neuronal early endosomes and increased synaptic endocytosis due to increased rab5 activation. We additionally demonstrate pathological consequences of APPL1 overexpression, including functional changes in hippocampal long-term potentiation (LTP) and long-term depression (LTD), as well as degeneration of the large projection cholinergic neurons of the basal forebrain and impairment of hippocampal-dependent memory. Our findings show that increased neuronal APPL1 levels lead to a cascade of pathological effects within neurons, including early endosomal alterations, synaptic dysfunction, and neurodegeneration. Multiple risk factors and molecular regulators, including APPL1 activity, are known to contribute to the endosomal dysregulation seen in the early stages of AD, and these findings further highlighting the shared pathobiology and consequences to a neuron of early endosomal pathway disruption.

Dichotomous impact of afferent sensory noise on grid-patterned firing and path integration in a continuous attractor network model
Background: The continuous attractor network (CAN) model has been effective in explaining grid-patterned firing in the rodent medial entorhinal cortex, with strong lines of experimental evidence and widespread utilities in understanding spatial navigation and path integration. A surprising lacuna in CAN analyses is the paucity of quantitative studies on the impact of afferent sensory noise on path integration. Here, we evaluate the impact of afferent sensory noise on grid-patterned firing and on the accuracy of position estimates derived from network pattern flow velocity. Motivated by the ability of border cells to act as an error-correction mechanism, we also assess the impact of interaction between afferent noise and border cell inputs on CAN performance. Methodology: We used an established 2D CAN model that received velocity inputs from a virtual animal traversing a 2D arena to generate grid-patterned firing. We estimated network pattern flow velocity from network activity and used that to compute an activity-based position estimate at each time step. We tracked the difference between the real and the estimated positions as a function of time and called it the deviation in integrated path (DIP). We defined afferent sensory noise to be additive Gaussian, with different noise levels achieved by changing the variance. We introduced north and east border cells and connected them to grid cells based on co-activity patterns. For different levels of noise, we computed DIP and metrics for grid-patterned activity in the presence vs. absence of border cells. Importantly, to avoid potential bias owing to the use of a single trajectory in computing these measurements, we performed all simulations across 50 different trajectories. Results: The computed grid scores and position accuracy (as DIP) showed pronounced trajectory-to-trajectory variability, even in a noise-free network. With the introduction of sensory noise, the variability prevailed and unveiled a dichotomous impact of afferent sensory noise on position accuracy vs. grid-patterned activity. Specifically, low levels of sensory noise improved position estimation accuracy without altering the ability of the network to generate grid-patterned activity. In contrast, high levels of sensory noise impaired position estimates as well as grid-patterned activity, although position estimates were more sensitive to sensory noise compared to grid-patterned activity. The stochastic resonance observed in the relationship between position accuracy and sensory noise level was partially explained by the interaction of noisy inputs with the rectification nonlinearity in the neural transfer function. Finally, across noise levels, pronounced trajectory-to-trajectory variability in grid-score and position accuracy was observed with the addition of border inputs. Across the population of trajectories, addition of border inputs yielded modest changes in both measurements across noise levels. Implications: Our analyses demonstrate that the robustness of grid-patterned activity in CAN models to noise does not extend to other functions of the CAN model. Stochastic resonance with reference to position estimation and sensory noise implies that biological CANs could evolve to yield optimal performance (path integration) in the presence of noise in biological sensory systems. An important methodological implication that emerges from our observations is the critical need to account for trajectory-to-trajectory variability in position estimates and path integration. Given the pronounced nature of trajectory-to-trajectory variability, conclusions based on a single trajectory are bound to be erroneous thereby warranting analyses with multiple trajectories. Together, our analyses unveil important roles for sensory noise in improving position estimates obtained from activity in CAN models.

Evidence that Dmrta2 acts as a transcriptional repressor of Pax6 in murine cortical progenitors and identification of a mutation crucial for DNA recognition associated with microcephaly in human
Dmrta2 (also designated Dmrt5) is a transcriptional regulator expressed in cortical progenitors in a caudomedial-high/rostrolateral-low gradient with important roles at different steps of cortical development. Dmrta2 has been suggested to act in cortex development mainly by differential suppression of Pax6 and other homeobox transcription factors such as the ventral telencephalic regulator Gsx2, which remains to be fully demonstrated. Here we have addressed the epistatic relation between Pax6 and Dmrta2 by comparing phenotypes in mutant embryos or embryos overexpressing both genes in various allelic combinations. We showed that Dmrta2 cooperates with Pax6 in the maintenance of cortical identity in dorsal telencephalic progenitors and that it acts as a transcriptional repressor of Pax6 to control cortical patterning. Mechanistically, we show that in P19 cells, Dmrta2 can act as a DNA-binding dependent repressor on the Pax6 E60 enhancer and that a point mutation that affects its DNA binding properties leads to agenesis of the corpus callosum, pachygyria, and the absence of the cingulate gyrus. Finally, we provide evidence that Dmrta2 binds to the Zfp423 zinc finger protein and that it enhances its ability to recruit the NurD repressor complex. Together, our results highlight the importance and conserved function of Dmrta2 in cortical development and provide novel insights into its mechanism of action.

Mammalian Retinal Bipolar Cells: Morphological Identification and Systematic Classification in Rabbit Retina, with a Comparative Perspective
Retinal bipolar cells (BCs) convey visual signals from photoreceptors to more than 50 types of rabbit retinal ganglion cells (Famiglietti, 2020). More than 40 years ago, 10-11 types of bipolar cell were recognized in rabbit and cat retinas (Famiglietti, 1981). Twenty years later 10 were identified in mouse, rat, and monkey (Gosh et al., 2004), while recent molecular genetic studies indicate that there are 15 types of bipolar cell in mouse retina (Shekhar et al., 2016). The present detailed study of more than 800 bipolar cells in ten Golgi-impregnated rabbit retinas indicates that there are 14-16 types of cone bipolar cell and one type of rod bipolar cell in rabbit retina. These have been carefully analyzed in terms of dendritic and axonal morphology, and axon terminal stratification with respect to fiducial starburst amacrine cells. In fortuitous proximity, several types of bipolar cell can be related to identified ganglion cells by stratification and by contacts suggestive of synaptic connection. These results are compared with other studies of rabbit bipolar cells. Homologies with bipolar cells of mouse and monkey are considered in functional terms.

Capillary-scale Microvessel Imaging with High-frequency Ultrasound Localization Microscopy in Mouse Brain
Ultrasound localization microscopy is a super-resolution vascular imaging technique which has garnered substantial interest as a tool for small animal neuroimaging, neuroscience research, and the characterization of vascular pathologies. In the pursuit of increasingly high-fidelity reconstructions of microvasculature, there remains several outstanding questions concerning this sub-diffraction imaging technology, including the accurate reconstruction of microvessels approaching the capillary scale and the pragmatic challenges associated with long data acquisition times. In the context of small animal neurovascular imaging, we posit that increasing the ultrasound imaging frequency is a straightforward approach to enable higher concentrations of microbubble contrast agents, thus increasing the likelihood of microvascular/capillary mapping and decreasing the imaging duration. We demonstrate that higher frequency imaging results in improved ULM fidelity and more efficient microbubble localization due to a smaller microbubble point-spread function that is easier to localize, and which can achieve a higher localizable concentration within the same unit volume of tissue. A select example of in vivo capillary-level vascular reconstruction is demonstrated for the highest frequency imaging probe, which has substantial implications for neuroscientists investigating microvascular function in disease states, regulation, and brain development. High frequency ULM yielding a spatial resolution of 7.1m, as measured by Fourier ring correlation, throughout the entire depth of the brain, highlighting this technology as a highly relevant tool for neuroimaging research.

Patterned wireless transcranial optogenetics generates artificial perception
Synthesizing perceivable artificial neural inputs independent of typical sensory channels remains a fundamental challenge in the development of next-generation brain-machine interfaces. Establishing a minimally invasive, wirelessly effective, and miniaturized platform with long-term stability is crucial for creating a clinically meaningful interface capable of mediating artificial perceptual feedback. In this study, we demonstrate a miniaturized fully implantable wireless transcranial optogenetic encoder designed to generate artificial perceptions through digitized optogenetic manipulation of large cortical ensembles. This platform enables the spatiotemporal orchestration of large-scale cortical activity for remote perception genesis via real-time wireless communication and control, with optimized device performance achieved by simulation-guided methods addressing light and heat propagation during operation. Cue discrimination during operant learning demonstrates the wireless genesis of artificial percepts sensed by mice, where spatial distance across large cortical networks and sequential order-based analyses of discrimination performance reveal principles that adhere to general perceptual rules. These conceptual and technical advancements expand our understanding of artificial neural syntax and its perception by the brain, guiding the evolution of next-generation brain-machine communication.

The macaque ventral intraparietal functional connectivity patterns reveal an anterio-posterior specialization mirroring that described in human ventral intraparietal area
The macaque monkey's ventral intraparietal area (VIP) in the intraparietal sulcus (IPS) responds to visual, vestibular, tactile and auditory signals and is involved in higher cognitive functions including the processing of peripersonal space. In humans, VIP appears to have expanded into three functionally distinct regions. Macaque VIP has been divided cytoarchitonically into medial and lateral parts; however, no functional specialization has so far been associated with this anatomical division. Functional MRI suggests a functional gradient along the anterior-posterior axis of the macaque IPS: anterior VIP shows visio-tactile properties and face preference, whereas posterior VIP responds to large-field visual dynamic stimuli. This functional distinction matches with functional differences among the three human VIP regions, suggesting that a regional specialization may also exist within macaque VIP. Here, we characterized the ipsilateral, whole-brain functional connectivity, assessed during awake resting state, along VIP's anterior-posterior axis by dividing VIP into three regions of interest (ROIs). The functional connectivity profiles of the three VIP ROIs resembled anatomical connectivity profiles obtained by chemical tracing. Anterior VIP was functionally connected to regions associated with motor, tactile, and proprioceptive processing and with regions involved in reaching, grasping, and processing peripersonal space. Posterior VIP had the strongest functional connectivity to regions involved in motion processing and eye movements. These profiles are consistent with the connectivity profiles of the anterior and posterior VIP areas identified in humans. Viewed together, resting state functional connectivity, task-related fMRI and anatomical tracing consistently suggest specific functional specializations of macaque anterior and posterior VIP. This specialization corroborates the distinction of VIP into three anatomically and functionally separate VIP areas in humans.

Spatial Development of Brain Networks During The First Six Postnatal Months
The initial months of life constitute a crucial period for human development. A comprehensive understanding of this early phase is essential for unraveling the origins of neurodevelopmental disorders and promoting infant brain health. This study uniquely focuses on the spatial development of intrinsic brain connectivity networks during infancy, which has been less explored compared to functional connectivity. We utilized independent component analysis (ICA) on resting-state fMRI data from 74 infants to assess how the spatial organization of infant brain networks evolves between birth and six months. Our findings reveal significant changes in spatial characteristics, including an a notable rise in the network-averaged spatial similarity across age, reflecting how closely each participant-specific spatial map aligns with the group-level map for each network. We also observed a marked reduction in the network engagement range by age, representing the extent of voxel intensity range fluctuation within each network. This suggests a continuing process of consolidation, where voxel contributions to the network become more uniform, as indicated by the narrowing of intensity values. The network strength, calculated as the average of all the voxel intensities in the network, indicating the degree of involvement to the specific functional network, increased across age in several networks, such as frontal-mPFC, primary, and secondary visual networks. The network size, along with the network center of mass, illustrating spatial distribution alterations of brain networks by age, varied across different networks. For instance, both metrics increased across age in the secondary visual network but decreased in the temporal network. Additionally, we examined the networks in relation to their linear versus non-linear developmental trajectories across all spatial characteristics, providing a deeper understanding of how these patterns evolve during early infancy. These findings contribute to early brain development understanding and offer insights into potential markers of consolidation and spatial reorganization in large-scale brain networks during infancy.

Simulated ischemia in live cerebral slices is mimicked by opening the Na+/K+ pump: clues to the generation of spreading depolarization.
The gray matter of the higher brain undergoes spreading depolarization (SD) in response to the increased metabolic demand of ischemia, promoting acute neuronal injury and death. The mechanism linking ischemic failure of the Na+/K+ ATPase (NKA) to the subsequent onset of a large inward current driving SD in neurons has remained a mystery because blockade of conventional channels does not prevent SD nor ischemic death. The marine poison palytoxin (PLTX) specifically binds the NKA transporter at extremely low concentrations, converting it to an open cationic channel, causing sudden neuronal Na+ influx and K+ efflux. Pump failure and induction of a strong inward current should induce dramatic SD-like activity. Indeed,1-10 nM PLTX applied to live coronal brain slices induces a propagating depolarization remarkably like SD induced by oxygen/glucose deprivation (OGD) as revealed by imaging. This PLTX depolarization (PD) mimicked other effects of OGD. In neocortex, as the elevated LT front passed by an extracellular pipette, a distinct negative DC shift was recorded, indicating cell depolarization, whether induced by OGD or by bath PLTX. Either treatment induced strong SD-like responses in the same higher and lower brain regions. Further, we imaged identical real-time OGD-SD or PD effects upon live pyramidal neurons using 2-photon microscopy. Taken together, these findings support our proposal that, like most biological poisons, PLTX mimics (and takes advantage of) a biological process,i.e., brain ischemia. An endogenous PLTX-like molecule may open the NKA to evoke Na+ influx/K+ efflux that drive SD and the ensuing neuronal damage in its wake.

T1234: A distortion-matched structural scan solution to misregistration of high resolution fMRI data
Purpose: High-resolution fMRI at 7T is challenged by suboptimal alignment quality between functional data and structural scans. This study aims to develop a rapid acquisition method that provides distortion-matched, artifact-mitigated structural reference data. Methods: We introduce an efficient sequence protocol termed T1234, which offers adjustable distortions. This approach involves a T1-weighted 2-inversion 3D-EPI sequence with four spatial encoding directions optimized for high-resolution fMRI. A forward Bloch model was used for T1 quantification and protocol optimization. Twenty participants were scanned at 7T using both structural and functional protocols to evaluate the utility of T1234. Results: Results from two protocols are presented. A fast distortion-free protocol reliably produced whole-brain segmentations at 0.8mm isotropic resolution within 3:00-3:40 minutes. It demonstrates robustness across sessions, participants, and three different 7T SIEMENS scanners. For a protocol with geometric distortions that matched functional data, T1234 facilitates layer-specific fMRI signal analysis with enhanced laminar precision. Conclusion: This structural mapping approach enables precise registration with fMRI data. T1234 has been successfully implemented, validated, and tested, and is now available to users at our center and at over 50 centers worldwide.

Probing the edge of synchronization: Slow waves erode resting activity in behaving monkeys
Brain networks oscillate between sleep and wakefulness, following circadian rhythms. Theoretical models suggest distinct phases within this cycle, separated by a critical point where long-range activity patterns emerge, an advantageous condition for information processing in cortical networks. However, the exact nature of this critical dynamics remains elusive. A key question is whether the brain operates at this critical point during cognitive tasks or only during resting wakefulness. Here, we analyzed neural signals from the premotor cortex (PMC) of two macaque monkeys engaged in a delayed-reaching task and under drug-induced unconsciousness. We found evidence of criticality during resting periods at the end of behavioral trials in the awake state. This scale-free activity appeared as coordinated traveling waves, like those observed during anesthesia. As predicted by spiking networks models, activity-dependent adaptation influences wave size, supporting the hypothesis that the PMC operates near a synchronization phase transition while avoiding it during active behaviors.

Neuronal lipid droplets play a conserved and sex-biased role in maintaining whole-body energy homeostasis
Lipids are essential for neuron development and physiology. Yet, the central hubs that coordinate lipid supply and demand in neurons remain unclear. Here, we combine invertebrate and vertebrate models to establish the presence and functional significance of neuronal lipid droplets (LD) in vivo. We find that LD are normally present in neurons in a non-uniform distribution across the brain, and demonstrate triglyceride metabolism enzymes and lipid droplet-associated proteins control neuronal LD formation through both canonical and recently-discovered pathways. Appropriate LD regulation in neurons has conserved and male-biased effects on whole-body energy homeostasis across flies and mice, specifically neurons that couple environmental cues with energy homeostasis. Mechanistically, LD-derived lipids support neuron function by providing phospholipids to sustain mitochondrial and endoplasmic reticulum homeostasis. Together, our work identifies a conserved role for LD as the organelle that coordinates lipid management in neurons, with implications for our understanding of mechanisms that preserve neuronal lipid homeostasis and function in health and disease.

Arterial spin labelling perfusion MRI analysis for the Human Connectome Project Lifespan Ageing and Development studies
The Human Connectome Project Lifespan studies cover the Development (5-21) and Aging (36-100+) phases of life. Arterial spin labelling (ASL) was included in the imaging protocol, resulting in one of the largest datasets collected to-date of high spatial resolution multiple delay ASL covering 3,000 subjects. The HCP-ASL minimal processing pipeline was developed specifically for this dataset to pre-process the image data and produce perfusion estimates in both volumetric and surface template space. Applied to the whole dataset, the outputs of the pipeline revealed significant and expected differences in perfusion between the Development and Ageing cohorts. Visual inspection of the group average surface maps showed that cortical perfusion often followed cortical areal boundaries, suggesting differential regulation of cerebral perfusion within brain areas at rest. Group average maps of arterial transit time also showed differential transit times in core and watershed areas of the cerebral cortex, which are useful for interpreting haemodynamics of functional MRI images. The pre-processed dataset will provide a valuable resource for understanding haemodynamics across the human lifespan.

Tetanizing wakeful consolidation: ten-hertz repetitive visual stimulation enhances the offline gain of visual learning
Consolidation of encoded information is vital for learning and memory, often explored during sleep. However, the consolidation during post-encoding offline wakefulness remains largely uncharted, especially regarding its modulation and brain mechanisms. Here, we unraveled frequency-dependent modulatory effects of repetitive visual stimulation (RVS) on wakeful consolidation of visual learning and investigated the underlying neural substrates. After training on an orientation discrimination task, exposure to 10-Hz grating-form RVS enhanced, while 1-Hz RVS deteriorated, the discrimination performance in a subsequent retest. However, 10-Hz uniform-disk RVS failed to facilitate wakeful consolidation, suggesting that alpha entrainment alone was not the facilitative mechanism. Using neuroimaging of multiple modalities, we observed augmented event-related potential and heightened neural excitation in the early visual cortex after 10-Hz grating-form RVS, implying an involvement of long-term potentiation-like (LTP-like) plasticity. Collectively, we provide a new photic method for modulating the offline processing of encoded sensory information and suggest a role of sensory tetanization in the modulation.

The Cellular and Extra-Cellular Proteomic Signature of Human Dopaminergic Neurons Carrying the LRRK2 G2019S Mutation
Extracellular vesicles are easily accessible in various biofluids and allow the assessment of disease-related changes of the proteome. This has made them a promising target for biomarker studies, especially in the field of neurodegeneration where access to diseased tissue is very limited. Genetic variants in the LRRK2 gene have been linked to both familial and sporadic forms of Parkinson's disease. With LRRK2 inhibitors entering clinical trials, there is an unmet need for biomarkers that reflect LRRK2-specific pathology and target engagement. In this study, we used induced pluripotent stem cells derived from a patient with Parkinson's disease carrying the LRRK2 G2019S mutation and an isogenic gene corrected control to generate human dopaminergic neurons. We isolated extracellular vesicles and neuronal cell lysates and characterized their proteomic signature using data-independent acquisition proteomics. We performed differential expression analysis and identified 595 significantly differentially regulated proteins in extracellular vesicles and 3205 in cell lysates. Next, we performed gene ontology enrichment analyses on the dysregulated proteins and found close association to biological processes relevant in neurodegeneration and Parkinson's disease. Finally, we focused on proteins that were dysregulated in both the extracellular and cellular proteomes and provide a list of ten promising biomarker candidates that are functionally relevant in neurodegeneration and linked to LRRK2 associated pathology. Among those was the sonic hedgehog signaling molecule, a protein that has tightly been linked to LRRK2-related disruption of cilia function. In conclusion, we characterized the cellular and extracellular proteome of dopaminergic neurons carrying the LRRK2 G2019S mutation and propose an experimentally based list of promising biomarker candidates for future studies.

Morphological profiling in human dopaminergic neurons identifies mitochondrial uncoupling as a neuroprotective effect
Multiple pathological cell biological processes in midbrain dopaminergic (mDA) neurons contribute to Parkinson's disease (PD). Described disease mechanisms converge upon defects in protein degradation, disruption of vesicular trafficking, endolysosomal function, mitochondrial dysfunction and oxidative stress. Current cellular PD models for in vitro drug discovery are often of non-neuronal origin and do not take complex pathological interactions into account and focus on a single readout or phenotype. Here, we used patient-derived SNCA triplication (SNCA-4x) and isogenic control (SNCA-corr) mDA neurons and applied high-content imaging-based morphological profiling with the goal to determine and rescue multiple phenotypes simultaneously. We performed compound screening using a total of 1,020 compounds with biological activity annotations relevant to PD pathobiology including some FDA-approved drugs. We scored compounds based on their ability to revert the SNCA-4x mDA neuron morphological profile towards a healthy-like isogenic control neuronal profile. Top-scoring compounds led to a morphological rescue in SNCA-4x mDA neurons including increased Tyrosine hydroxylase (TH) level and decreased total -synuclein (Syn) protein levels. Multiple hit compounds were also linked to mitochondrial biology and we further evaluated them by determining their effect on neuronal mitochondrial membrane potential and cytoplasmic ROS levels. Additional biochemical analysis of the protonophore and mitochondrial uncoupler Tyrphostin A9 showed decreased total ROS levels and normalized mitochondrial membrane potential, and an increase in mitochondrial respiration. We confirmed this effect in mDA neurons by using five structurally related molecules and measuring mitochondrial activity and membrane potential. Additionally, Western blotting indicated that mitochondrial uncouplers, such as Tyrphostin A9, can decrease both low and high molecular weight forms of Syn. Based on target agnostic morphological profiling in human mDA neurons, we therefore identified a connection between the compound-induced rescue of multiple morphological features, mild mitochondrial uncoupling, and a Syn protein level decrease.

Novel insights into Emx2 and Dmrta2 cooperation during cortex development and evidence for Dmrta2 function in choroid plexus
Early dorsal telencephalon development is coordinated by an interplay of transcription factors that exhibit a graded expression pattern in neural progenitors. How they function together to orchestrate cortical development remains largely unknown. The Emx2 and Dmrta2 genes encode TFs that are expressed in a similar caudomedial-high/ rostrolateral-low gradient in the ventricular zone of the developing dorsal telencephalon with, in the medial pallium, Dmrta2 but not Emx2 expressed in the developing choroid plexus. Their constitutive loss has been shown to impart similar cortical abnormalities, and their combined deletion exacerbates the phenotypes, suggesting possible cooperation during cortex development. In this study, we utilized molecular and genetic approaches to dissect how Emx2 functions with Dmrta2 during cortical development. Our results show that while they regulate a similar set of genes, their common direct targets are limited but include key regulators of cortical development. Identification of the interaction partners of Emx2 suggests that it coordinates with the LIM-domain binding protein Ldb1 to execute the activation and repression of some of its downstream targets. Finally, while Emx2 is known to suppress choroid plexus development, we also provide evidence that Dmrta2 is in contrast required for choroid plexus since in its absence in medial telencephalic progenitors, mice develop hydrocephalous postnatally, a phenotype that appears to be due to a compromised cytoarchitecture. Together, these data indicate that Emx2 and Dmrta2 have similar but also distinct functions in telencephalon development and provide the first insights into Emx2 mechanism of action.

A neural mechanism for compositional generalization of structure in humans
An exceptional human ability to adapt to the dynamics of novel environments relies on abstracting and generalizing past experiences. While previous research has examined how humans generalize isolated sequential processes, we know little concerning the neural mechanisms that enable adaptation to the more complex dynamics that govern everyday experience. Here, we deployed a novel sequence learning task based on graph factorization, coupled with simultaneous magnetoencephalography (MEG) recordings, to ask whether reuse of experiential 'building blocks' provides an abstract structural scaffolding that enables inference and generalization. We provide behavioral evidence that participants decomposed task experience into subprocesses, abstracted dynamical subprocess structures away from sensory specifics, and transferred these to a new task environment. Neurally we show this transfer is underpinned by a representational alignment of abstract subprocesses across task phases, where this included enhanced neural similarity among stimuli that adhered to the same subprocess, a temporally evolving mapping between predictive representations of subprocesses and a generalization of the precise dynamical roles that stimuli occupy within graph structures. Crucially, decoding strength for dynamical role representations predicted behavioral success in transfer of subprocess knowledge, consistent with a role in supporting behavioral adaptation in new environments. We propose a structural scaffolding mechanism enables compositional generalization of dynamical subprocesses that facilitate efficient adaptation within new contexts.

Biases in population codes with a few active neurons
Throughout the brain information is coded in the activity of multiple neurons at once, so called population codes. Population codes are a robust and accurate way of coding information. One can evaluate the quality of population coding by trying to read out the code with a decoder, and estimate the encoded stimulus. Coding quality has traditionally been evaluated in terms of the trial-to-trial variation in the estimate. However, codes can also display biases. While most decoders yield unbiased estimators in the limit of many active neurons, we find that when only few neurons are active, biases readily emerge for many decoders. We show that the biases turn out to have a non-trivial dependence on noise and tuning curve properties. We also introduce a technique to estimate the bias and variance of Bayesian decoders. Overall, the work expands our understanding of population coding.

Exercise Evokes Retained Motor Performance without Neuroprotection in a Mouse Model of Parkinson's Disease
Exercise has been extensively studied in Parkinson's Disease, with a particular focus on the potential for neuroprotection that has been demonstrated in animal models. While this preclinical work has provided insight into the underlying molecular mechanisms, it has not addressed the neurophysiological changes during exercise. Here, first, we tested for neuroprotective effects of adaptive wheel exercise in the 6-hydroxydopamine mouse model of Parkinson's disease. Finding none, we probed the neurophysiology of exercise as a state of high motor function amidst an unameliorated Parkinsonian lesion. Exercise was associated with characteristic, excitatory changes in the dopamine-depleted substantia nigra, which could be suppressed along with exercise itself by dopamine receptor blockade. Going forward, the functional state evoked by exercise merits further study, as it may represent an optimal target for neuromodulation, even if the underlying pathology cannot be averted.

Chromatin remodeler BRG1 recruits huntingtin to repair DNA double-strand breaks in neurons
Persistent DNA double-strand breaks (DSBs) are enigmatically implicated in neurodegenerative diseases including Huntingtons disease (HD), the inherited late-onset disorder caused by CAG repeat elongations in Huntingtin (HTT). Here we combine biochemistry, computation and molecular cell biology to unveil a mechanism whereby HTT coordinates a Transcription-Coupled Non-Homologous End-Joining (TC-NHEJ) complex. HTT joins TC-NHEJ proteins PNKP, Ku70/80, and XRCC4 with chromatin remodeler Brahma-related Gene 1 (BRG1) to resolve transcription-associated DSBs in brain. HTT recruitment to DSBs in transcriptionally active gene-rich regions is BRG1-dependent while efficient TC-NHEJ protein recruitment is HTT-dependent. Notably, mHTT compromises TC-NHEJ interactions and repair activity, promoting DSB accumulation in HD tissues. Importantly, HTT or PNKP overexpression restores TC-NHEJ in a Drosophila HD model dramatically improving genome integrity, motor defects, and lifespan. Collective results uncover HTT stimulation of DSB repair by organizing a TC-NHEJ complex that is impaired by mHTT thereby implicating dysregulation of transcription-coupled DSB repair in mHTT pathophysiology.

Functional localization of visual motion area FST in humans
The fundus of the superior temporal sulcus (FST) in macaques is implicated in the processing of complex motion signals, yet a human homolog remains elusive. Here we considered potential localizers and evaluated their effectiveness in delineating putative FST (pFST), from hMT and MST, two nearby motion-sensitive areas in humans. Nine healthy participants underwent scanning sessions with 2D and 3D motion localizers, as well as population receptive field (pRF) mapping. We observed consistent anterior and inferior activation relative to hMT and MST in response to stimuli that contained coherent 3D, but not 2D, motion. Motion opponency and myelination measures further validated the functional and structural distinction between pFST and hMT/MST. At the same time, standard pRF mapping techniques that reveal the visual field organization of hMT/MST proved suboptimal for delineating pFST. Our findings provide a robust framework for localizing pFST in humans, and underscore its distinct functional role in motion processing.

A unified rodent atlas reveals the cellular complexity and evolutionary divergence of the dorsal vagal complex
The dorsal vagal complex (DVC) is a region in the brainstem comprised of an intricate network of specialized cells responsible for sensing and propagating many appetite-related cues. Understanding the dynamics controlling appetite requires deeply exploring the cell types and transitory states harbored in this brain site. We generated a multi-species DVC cell atlas using single nuclei RNAseq (sn-RNAseq), thorough curation and harmonization of mouse and rat data which includes >180,000 cells and 123 cell identities at 5 granularities of cellular resolution. We report unique DVC features such as Kcnj3 expression in Ca-permeable astrocytes as well as new cell populations like neurons co-expressing Th and Cck, and a leptin receptor-expressing neuron population in the rat area postrema which is marked by expression of the progenitor marker, Pdgfra. In summary, our findings suggest there are distinct cellular populations specific to the DVC compared to other brain sites and our comprehensive atlas is a valuable tool for the study of this metabolic center.

Hippocampal γCaMKII dopaminylation promotes synaptic-to-nuclear signaling and memory formation
Protein monoaminylation is a class of posttranslational modification (PTM) that contributes to transcription, physiology and behavior. While recent analyses have focused on histones as critical substrates of monoaminylation, the broader repertoire of monoaminylated proteins in brain remains unclear. Here, we report the development/implementation of a chemical probe for the biorthogonal labeling, enrichment and proteomics-based detection of dopaminylated proteins in brain. We identified 1,557 dopaminylated proteins - many synaptic - including {gamma}CaMKII, which mediates Ca2+-dependent cellular signaling and hippocampal-dependent memory. We found that {gamma}CaMKII dopaminylation is largely synaptic and mediates synaptic-to-nuclear signaling, neuronal gene expression and intrinsic excitability, and contextual memory. These results indicate a critical role for synaptic dopaminylation in adaptive brain plasticity, and may suggest roles for these phenomena in pathologies associated with altered monoaminergic signaling.

IGF-1 and insulin receptors in LepRb neurons jointly regulate body growth, bone mass, reproduction, and metabolism
Leptin receptor (LepRb)-expressing neurons are known to link body growth and reproduction, but whether these functions are mediated via insulin-like growth factor 1 receptor (IGF1R) signaling is unknown. IGF-1 and insulin can bind to each other's receptors, permitting IGF-1 signaling in the absence of IGF1R. Therefore, we created mice lacking IGF1R exclusively in LepRb neurons (IGF1RLepRb mice) and simultaneously lacking IGF1R and insulin receptor (IR) in LepRb neurons (IGF1R/IRLepRb mice) and then characterized their body growth, bone morphology, reproductive and metabolic functions. We found that IGF1R and IR in LepRb neurons were required for normal timing of pubertal onset, while IGF1R in LepRb neurons played a predominant role in regulating adult fertility and exerted protective effects against reproductive aging. Accompanying these reproductive deficits, IGF1RLepRb mice and IGF1R/IRLepRb mice had transient growth retardation. Notably, IGF1R in LepRb neurons was indispensable for normal trabecular and cortical bone mass accrual in both sexes. These findings suggest that IGF1R in LepRb neurons is involved in the interaction among body growth, bone development, and reproduction. Though only mild changes in body weight were detected, simultaneous deletion of IGF1R and IR in LepRb neurons caused dramatically increased fat mass composition, decreased lean mass composition, lower energy expenditure, and locomotor activity in both sexes. Male IGF1R/IRLepRb mice exhibited impaired insulin sensitivity. These findings suggest that IGF1R and IR in LepRb neurons jointly regulated body composition, energy balance, and glucose homeostasis. Taken together, our studies identified the sex-dependent complex roles of IGF1R and IR in LepRb neurons in regulating body growth, reproduction, and metabolism.

Increased protein kinase Mζ expression by Minocycline and N-acetylcysteine restoreslate-phase long-term potentiation and spatial learning after closed head injury in mice
Cognitive deficits frequently arise after traumatic brain injury. The murine closed head injury (CHI) models these deficits since injured mice cannot acquire Barnes maze. Dosing of minocycline plus N-acetylcysteine beginning 12 hours post-CHI (MN12) restores Barnes maze acquisition by an unknown mechanism. Increased hippocampal synaptic efficacy is needed to acquire Barnes maze, synaptic long-term potentiation (LTP) models this increased synaptic efficacy in vitro. LTP has an early phase (E-LTP) lasting up to one hour that is mediated by second messengers that is followed by a late phase (L-LTP) that needs new synthesis of protein kinase M zeta (PKM{zeta}). PKM{zeta} has constitutive kinase activity because it lacks the autoinhibitory regulatory domain found in other PKCs. Due to its constitutive activity, the amount of PKM{zeta} kinase activity is determined by PKMz protein levels. We report that CHI bilaterally decreases PKM{zeta} levels in the CA3 and CA1 hippocampus. MN12 increases CA1 PKM{zeta} expression. CHI inhibits E-LTP in slices from the ipsilesional hippocampus and inhibits L-LTP in slices from both hippocamppi. MN12 treatment reestablishes both E-LTP and L-LTP in slices from the injured MN12-treated hippocampus. The restoration of L-LTP from injured MN12-treated hippocampus is mediated by PKM{zeta} because L-LTP is blocked by the specific PKM{zeta} inhibitor, {zeta}-stat. Hippocampal {zeta}-stat infusions also prevent Barnes maze acquisition in injured, MN12-treated mice. These data suggest that post-injury minocycline plus N-acetylcysteine targets PKM{zeta} to improve synaptic plasticity and cognition in mice with closed-head injury.

EFFECTS OF SPINAL TRANSECTION AND LOCOMOTOR SPEED ON MUSCLE SYNERGIES OF THE CAT HINDLIMB
It was suggested that during locomotion, the nervous system controls movement by activating groups of muscles, or muscle synergies. Analysis of muscle synergies can reveal the organization of spinal locomotor networks and how it depends on the state of the nervous system, such as before and after spinal cord injury, and on different locomotor conditions, including a change in speed. The goal of this study was to investigate the effects of spinal transection and locomotor speed on hindlimb muscle synergies and their time-dependent activity patterns in adult cats. EMG activities of 15 hindlimb muscles were recorded in 9 adult cats of either sex during tied-belt treadmill locomotion at speeds of 0.4, 0.7, and 1.0 m/s before and after recovery from a low thoracic spinal transection. We determined EMG burst groups using cluster analysis of EMG burst onset and offset times and muscle synergies using non-negative matrix factorization. We found five major EMG burst groups and five muscle synergies in each of six experimental conditions (2 states x 3 speeds). In each case, the synergies accounted for at least 90% of muscle EMG variance. Both spinal transection and locomotion speed modified subgroups of EMG burst groups and the composition and activation patterns of selected synergies. However, these changes did not modify the general organization of muscle synergies. Based on the obtained results, we propose an organization for a pattern formation network of a two-level central pattern generator that can be tested in neuromechanical simulations of spinal circuits controlling cat locomotion.

Working memory predicts long-term recognition of auditory sequences: Dissociation between confirmed predictions and prediction errors
Memory is a crucial cognitive process involving several subsystems: sensory memory (SM), short-term memory (STM), working memory (WM), and long-term memory (LTM). While each has been extensively studied, the interaction between WM and LTM, particularly in relation to predicting temporal sequences, remains largely unexplored. This study investigates the relationship between WM and LTM, and how these relate to aging and musical training. Using three datasets with a total of 244 healthy volunteers across various age groups, we examined the impact of WM on LTM recognition of novel and previously memorized musical sequences. Our results show that WM abilities are significantly related to recognition of novel sequences, with a more pronounced effect in older compared to younger adults. In contrast, WM did not similarly impact the recognition of memorized sequences, which implies that different cognitive processes are involved in handling prediction errors compared to confirmatory predictions, and that WM contributes to these processes differently. Additionally, our findings confirm that musical training enhances memory performance. Future research should extend our investigation to populations with cognitive impairments and explore the underlying neural substrates.

Qualitative EEG abnormalities signal a shift towards inhibition-dominated brain networks. Results from the EU-AIMS LEAP studies
Qualitative EEG abnormalities are common in Autism Spectrum Disorder (ASD) and hypothesized to reflect disrupted excitation/inhibition balance. To test this, we recently introduced a functional measure of network-level E/I ratio (fE/I). Here, we applied fE/I and other quantitative EEG measures to alpha oscillations from source-reconstructed data in the EU-AIMS compilation of 267 EEG recordings from children-adolescents and adults with ASD and 209 controls. We analyzed these quantitative measures alongside evaluating for qualitative EEG abnormalities ranging from slowing of activity to epileptiform patterns aiming to replicate the findings from the SPACE-BAMBI study (Bruining et al., 2020). EEG abnormalities were only identified in a few adults and could not be statistically assessed. ASD children-adolescents with EEG abnormalities exhibited lower relative alpha power and lower fE/I compared to children-adolescents without abnormalities; however, the EEG-abnormality scoring did not stratify the behavioral heterogeneity of ASD using clinical measures. Surprisingly, several controls presented with qualitative EEG abnormalities and showed a strikingly similar anatomical distribution of lower fE/I to the one observed in the ASD group, suggesting a shift towards inhibition-dominated network dynamics, in regions associated with altered sensory processing. The robustness of this association between EEG abnormalities and reduced fE/I was further supported by re-analysis of the SPACE-BAMBI study in source space. Stratification by the presence of EEG abnormalities and their associated effects on network activity may help understand neurodevelopmental physiological heterogeneity and the difficulties in implementing E/I targeting treatments in unselected cohorts.