bioRxiv Subject Collection: Neuroscience's Journal

Genetic risk in endolysosomal network genes correlates with endolysosomal dysfunction across neural cell types in Alzheimer's disease
Late-onset Alzheimer's disease (LOAD) has a complex genomic architecture with risk variants in multiple pathways, including the endolysosomal network (ELN). Whether genetic risk in specific pathways correlates with corresponding biological dysfunction remains largely unknown. We developed an endolysosomal pathway-specific polygenic risk score (ePRS) using 13 established AD GWAS loci containing ELN genes. We investigated the association between ePRS and AD neuropathology, then examined cell-specific endolysosomal morphology and transcriptomic profiles in post-mortem dorsolateral prefrontal cortex samples from donors stratified by ePRS burden. We found that the ePRS was significantly associated with AD diagnosis and neuropathological measures, comparable to a pathway-agnostic PRS despite representing far fewer loci. High ePRS correlated with increased neuronal endosome number and perinuclear aggregation, as well as enlarged microglial lysosomes, independent of AD pathology. Single-nucleus RNA sequencing revealed cell-type specific transcriptomic changes in high ePRS donors, including downregulation of endolysosomal function pathways (macroautophagy, synaptic vesicle acidification) and altered metabolic signatures across multiple cell types. Neurons, astrocytes, oligodendrocytes, and microglia each showed distinct gene expression patterns associated with ePRS burden. Conclusions: This study provides direct evidence that AD genetic risk variants in ELN genes correlate with endolysosomal dysfunction in human brain tissue. These findings suggest that pathway-specific genetic risk contributes to corresponding cellular pathology in AD, supporting the potential for more targeted therapeutic approaches based on individual genetic risk profiles.

Non-linear effects of evening light exposure on cognitive performance
In humans, exposure to light can impact alertness and cognitive performance. These cognitive effects of light are mediated by the intrinsically photosensitive retinal ganglion cells (ipRGCs) expressing the photopigment melanopsin, which signals environmental light in addition to the cone- and rod-mediated pathways. Most studies investigating the cognitive effects of light have focused on alertness, raising the question how higher-level cognitive tasks such as working memory are modulated by light. This study investigated the dose-response relationship for alertness, cognitive performance and mental workload. Each level of melanopic illuminance (ranging from 1 lx to 595 lx melanopic EDI) was evaluated over separate days with a six-hour exposure in a controlled climate chamber with artificial lighting. Participants (n=16, 10 female, 27.4 {+/-}2.5 years), completed the Psychomotor Vigilance Test (PVT) and n-back task every 30 minutes to assess reaction time, attention, and working memory, alongside subjective evaluations through questionnaires. The results suggest an inverted U-shaped correlation between cognitive functions and melanopic EDI and a U-shaped relationship between subjective assessments and melanopic EDI. Extreme lighting conditions in our stimulus set -- both dim (1 lx melanopic EDI) and bright (595 lx melanopic EDI) -- were associated with increased sleepiness and perceived workload, quicker reaction times, and diminished cognitive performance. Conversely, moderate illuminance levels (10 lx melanopic EDI and 70 lx melanopic EDI) positively influenced cognitive performance and mental workload but resulted in slower reaction times. This study illustrates that the relationship between melanopic EDI levels and cognitive performance does not follow a linear dose-response pattern, indicating a complex strategy for resource allocation in cognition.

Mapping Brain Growth and Sex Differences Across Prenatal to Postnatal Development
The perinatal period, encompassing both prenatal and early postnatal stages, is a highly dynamic and foundational phase of brain development. Despite its significance, limited work has tracked brain growth continuously across prenatal to postnatal development. In this study, we analysed one of the largest perinatal MRI datasets from the Developing Human Connectome Project (798 scans from 699 unique individuals: 263 prenatal and 535 neonatal; 380 males and 319 females) to model age-related changes and sex differences in brain volumes from 21 to 45 weeks postconceptional age. We found that total brain volume grew at an increasing rate, with white matter dominating mid-gestational growth and gray matter dominating late-gestational and postnatal growth. Subcortical gray matter structures showed distinct trajectories and earlier peak growth rates compared to cortical gray matter structures. Additionally, sex differences in brain growth patterns were observed, with males showing greater volumetric increases with age compared with females. The findings demonstrate the evolving structural dynamics of perinatal brain development as well as the importance of integrating prenatal and postnatal neuroimaging to map continuous early brain growth trajectories.

Sensory prediction errors predict motor prediction errors
When sensory inputs can be predicted by an organism's own actions or external environmental cues, neural activity is often attenuated compared to sensory inputs that are unpredictable. We have recently demonstrated that attenuation to predictable inputs is also observed when stimulating the motor system with transcranial magnetic stimulation (TMS). Akin to sensory attenuation, predictable TMS excites the motor system less effectively than unpredicted TMS. However, it remains unclear whether these motor prediction signals are related to, or even dependent on, sensory prediction. Using dual-site TMS to target two brain regions, we arranged different warning cues to predict different regions of stimulation and measured motor attenuation using motor-evoked potentials. We found that expecting TMS over the motor cortex produced stronger attenuation than expecting TMS over a non-motor region, confirming that the attenuation observed is directly linked to activation of the motor system and not due to the sensory by-products of TMS. Using combined TMS-EEG, we measured motor attenuation with motor-evoked potentials, and simultaneously measured sensory attenuation to the sound of TMS (a coil "click") with auditory-evoked potentials. We found that both motor and auditory potentials were attenuated to predictable TMS compared to unpredictable TMS. Critically, the magnitude of auditory attenuation predicted the magnitude of motor attenuation. Our results reveal a close correspondence between error processing in the sensory and motor systems. The findings provide compelling evidence that predictive coding is governed by domain-general properties across distinct neural systems, which share common mechanisms responsible for all forms of predictive learning.

The alpha-Synuclein Proteostasis Network and its Translational Applications in Parkinson's disease
Parkinson's disease (PD) is debilitating neurodegenerative condition that results in the loss of mobility and muscle control. A neuropathological hallmark of PD is the presence aberrant inclusions, known as Lewy pathology, of which alpha-synuclein (a-Syn) is a major component. The accumulation of a-Syn is a likely consequence of an age-related impairment of the proteostasis system regulating a-Syn. To investigate this phenomenon, we map the proteostasis network (PN) of a-Syn in the Substania nigra at the proteomic and transcriptomic levels. We then define a a-Syn proteostasis activity score (PAS) that quantifies the activity of the PN in regulating a-Syn. We thus obtain a PAS signature indicative of the disease state, as well as the age-of-death in PD patients, and the brain regional vulnerability to a-Syn aggregation. We then outline a digital twin of the a-Syn PN in the Substantia nigra cells by training a model on single-cell data. This digital twin is applied towards target identification for PD. In addition, we further describe the application of the PN to facilitate drug repurposing. Overall, our study highlights the implication of the a-Syn PN in PD and how simulations and measurements of its activity can help efforts in translational research for PD.

Fast in vivo deep-tissue 3D imaging with selective-illumination NIR-II light-field microscopy and aberration-corrected implicit neural representation
Near-infrared II (NIR-II) microscopy, which enables in vivo deep-tissue visualization of vasculature and cell activities, has been a promising tool for understanding physiological mechanisms. However, the volumetric image speed of the current NIR-II microscopy is hindered by scanning strategy, causing limitations for observing instantaneous biological dynamics in 3D space. Here, we developed a NIR-II light-field microscopy (LFM) based on selective illumination and self-supervised implicit neural representation (INR)-reconstruction, which allows ultra-fast 3D imaging (20 volumes/s) in deep tissue. Through integrating INR with view-wise aberration correction, our strategy could conquer the artifacts induced by the angular subsampling and refractive index variation problems, achieving single-cell resolution at a reconstruction volume of 550 m diameter and 200 m thickness. The volumetric selective illumination overcomes the influence of out-of-focus background on reconstruction, together with the low scattering advantage of NIR-II wavelength, extending the imaging depth to 600 m. The developed aberration-corrected implicit neural representation reconstruction (AIR) NIR-II LFM showcases its capability by monitoring hemodynamics of mouse brain under norepinephrine and flow redistribution of ischemic stroke in 3D vasoganglion, as well as noninvasively tracking immune cell activities inside subcutaneous solid tumor through intact skin. This approach represents a significant advancement in 3D in vivo imaging, holding great potential in both biomedical research and preclinical studies.

Resource-dependent heterosynaptic spike-timing-dependent plasticity in recurrent networks with and without synaptic degeneration
Many computational models that incorporate spike-timing-dependent plasticity (STDP) have shown the ability to learn from stimuli, supporting theories that STDP is a sufficient basis for learning and memory. However, to prevent runaway activity and potentiation, particularly within recurrent networks, additional global mechanisms are commonly necessary. A STDP-based learning rule, which involves local resource-dependent potentiation and heterosynaptic depression, is shown to enable stable learning in recurrent spiking networks. A balance between potentiation and depression facilitates synaptic homeostasis, and learned synaptic characteristics align with experimental observations. Furthermore, this resource-based STDP learning rule demonstrates an innate compensatory mechanism for synaptic degeneration.

Information processing in the Hand Laterality Judgement Task: Fundamental differences between dorsal and palmar views revealed by a Forced Response paradigm
Imagining performing movements (motor imagery) has broad applications from fundamental neuroscience to sports and rehabilitation. However, measuring motor imagery ability is challenging due to its covert nature. While the Hand Laterality Judgement Task (HLJT) has been investigated as a measure of implicit motor imagery ability, our understanding of mechanisms underlying performance of the task is limited. We used a forced response paradigm to study the time-course of information processing in the HLJT. Participants (N=54) performed a modified HLJT where the time they had to process the stimulus was manipulated on a trial-by-trial basis, allowing us to reconstruct the time-course of information processing. Generalised Additive Mixed Models assessed the relationship between processing time and accuracy, which varied across rotation angles (0 to 180 in 45 steps), hand views (dorsal or palmar) or directions (medial or lateral). Stimulus rotation substantively increased the time needed to produce a correct response, although this effect was non-monotonic. Computational modelling confirmed a crucial interaction between hand view and rotation angle, identifying fundamental differences in processing for palmar stimuli with more extreme rotations (greater than 135) compared to other stimuli. Finally, a biomechanical constraints effect (i.e. faster processing of medial vs laterally rotated stimuli) was present in both views, but was only statistically significant in palmar views, again suggesting differences in processing palmar and dorsal stimuli. These results improve our understanding of the cognitive processes underlying the HLJT and may have broader importance for our understanding of mental processes implicated in motor imagery.

Electrical Spinal Imaging (ESI): Analysing spinal cord activity with non-invasive, high-resolution mapping
The spinal cord is the key bridge between the brain and the body. However, scientific understanding of healthy spinal cord function has historically been limited because noninvasive measures of its neural activity have proven exceptionally challenging. In this work, we describe a novel recording and analysis approach to obtain non-invasive, high-resolution images of the electrical activity of the spinal cord in humans (Electrical Spinal Imaging, ESI). ESI is analytically simple, easy to implement, and data-driven: it does not involve template-based strategies prone to produce spurious signals. Using this approach we provide a detailed description and physiological characterization of the spatiotemporal dynamics of the peripheral, spinal and cortical activity elicited by somatosensory stimulation. We also demonstrate that attention modulates post-synaptic activity at spinal cord level. Our method has enabled four new insights regarding spinal cord activity. (1) We identified three distinct responses in the time domain: sP9, sN13 and sP22. (2) The sP9 is a traveling wave reflecting the afferent volley entering the spinal cord through the dorsal root. (3) In contrast, the sN13 and sP22 reflect segmental post-synaptic activity. (4) While the sP9 response is first seen on the dorsal electrodes ipsilateral to the stimulated side, the sN13 and sP22 were not lateralised with respect to the side of stimulation. (5) Unimodal attention strongly modulates the amplitude of the sP22, but not that of the sP9 and sN13 components. The proposed method offers critical insights into the spatiotemporal dynamics of somatosensory processing within the spinal cord, paving the way for precise non-invasive functional monitoring of the spinal cord in basic and clinical neurophysiology.

A parsimonious model for learning order relations provides a principled explanation of diverse experimental data
A cornerstone of higher cognitive function is the ability to learn relations between objects, and to use this relational information for inference. A concrete challenge is learning an order relation, and the use of resulting internal representations for transitive inference. It is known that order relations are represented in the parietal cortex both by a summation code, where the firing rates of neurons indicate the rank of an item in the order, and by a heterogeneous code where neurons are selective for specific rank values. But it remains open how these neural codes are learned. We show that the summation code emerges through a simple rule for synaptic plasticity in a single layer of synaptic connections. The resulting neural representation enables transitive inference and gives rise to the terminal item effect observed in human behavior. We also show that the simultaneous presence of a heterogeneous code gives rise to the commonly observed curvature of 2D projections of fMRI (functional magnetic resonance imaging) signals for items of increasing rank: They tend to lie on a horseshoe-shaped curved line. Our models are supported by a rigorous theory.

Comparing a computational model of visual problem solving with human vision on a difficult vision task.
Human vision is not merely a passive process of interpreting sensory input but incorporates generative mechanisms that infer and synthesize plausible interpretations of ambiguous or noisy data. This synergy between the generative and discriminative components, often described as analysis-by-synthesis, enables robust perception and rapid adaptation to out-of-distribution inputs. By leveraging top-down feedback, human vision excels in constructing meaningful interpretations even in challenging scenarios. In this work, we investigate a computational implementation of the analysis-by-synthesis paradigm using search in a generative model applied to an underspecified image dataset inspired by star constellations. The search is guided by low-level cues based on the structural fitness of solutions to the test images. This dataset serves as a testbed for exploring how inferred signals can guide the synthesis of suitable solutions in ambiguous conditions. Drawing on insights from human experiments, we develop a generative search algorithm and compare its performance to humans, examining factors such as accuracy, reaction time, and overlap in drawings. Our results shed light on possible mechanisms of human visual inference and highlight the potential of generative search models to emulate aspects of this process.

Overcoming sensory-memory interference in working memory circuits
Memories of recent stimuli are crucial for guiding behavior, but the sensory pathways responsible for encoding these memories are continuously bombarded by new sensory experiences. How the brain overcomes interference between sensory input and working memory representations remains largely unknown. To formalize the solution space, we examined recurrent neural networks that were either hand-designed or trained using gradient descent methods, and compared these models with neural data from two different macaque experiments. Here we report mechanisms by which neural networks overcome sensory-memory interference using both static and dynamic coding strategies: gating of the sensory inputs, modulating synapse strengths to achieve a strong attractor solution, and dynamic strategies - including the extreme solution in which cells invert their feature preference during working memory. Neural data from the medial superior temporal (MST) area of macaques, where sensory and working memory signals first interact along the dorsal pathway, best aligned with a solution that combined input gating and tuning inversion. Behavioral predictions from this model also matched error patterns observed in monkeys performing a working memory task with distractors. Taken together, our results help elucidate how working memory circuits preserve information as we continue to interact with the world, and suggest intermediate cortical visual areas like MST may play a critical role in this computation.

Galectin-3 deletion modulates microglial phenotype and Aβ response via TREM2 activation while attenuating neuroinflammation
Galectin-3 (Gal3) is a regulator of microglial activation implicated in Alzheimer's disease (AD). However, Gal3 role in modulating microglial phenotype towards amyloid-beta (A{beta}) remains poorly understood. We demonstrate that Gal3 affects several microglial functions and binds A{beta} fibrils with high affinity, stabilizing aggregation intermediates that alter fibril kinetics and morphology. Furthermore, Gal3 deletion affects the direct relationship between microglia and A{beta}, reducing its uptake and increasing its compaction. AlphaFold modeling predicts direct Gal3-TLR4 interactions, suggesting a molecular link to inflammatory pathways. In vivo, Gal3 deletion reduces A{beta} plaque burden in APP mice while suppressing interferon-alpha signaling and the neurodegenerative microglial (MGnD) phenotype. Moreover, microglia lacking Gal3 show enhanced TREM2 activation around plaques, a key mediator of protective microglial responses, while reducing dystrophic neurites. These findings position Gal3 as a nexus between A{beta} aggregation and microglial phenotype, proposing its inhibition as a strategy to concurrently target neurotoxic inflammation in AD.

Leaky evidence accumulation accounts for perceptual confidence and subjective duration
Perceptual consciousness is defined as the subjective experience associated with the processing of sensory cues from the environment. Subjective experience unfolds over time and is accompanied by a sense of confidence, yet the mechanisms underlying these two properties remain elusive. Here, we propose a computational mechanism that accounts not only for the onset of subjective experience but also its subjective duration and associated feeling of confidence. Our model assumes that a percept becomes conscious when an ongoing, leaky accumulation of sensory evidence surpasses a perceptual threshold and stops being conscious when it falls back below the threshold due to leakage. Crucially, this perceptual threshold can be lower than the decision threshold for reporting the percept. Moreover, our model derives confidence in accurately detecting sensory evidence from the maximum reached by the evidence accumulation process following stimulus onset. We conducted a preregistered study in which three distinct models of evidence accumulation were fitted to behavioral reports of detection, confidence, and subjective duration during a face detection task under temporal uncertainty. The leaky evidence accumulation model accounted for the observed behavioral data best and outperformed alternative models without leakage. In a follow-up experiment, we investigated the impact of leakage adaptation on detection and subjective duration. We found that changes in leakage induced by contextual variations of face duration influenced both detection rates and subjective duration, as predicted by our model. Altogether, our findings suggest that leaky evidence accumulation is a suitable candidate mechanism to explain qualitative aspects of subjective experience, including subjective duration and feelings of confidence.

Intracortical transplantation of human induced pluripotent stem cell-derived progenitors ameliorates delayed thalamic degeneration following cortical stroke
Ischemic stroke, a leading cause of death and disability worldwide, frequently results in cortical damage. Due to disrupted neural connectivity, cortical lesions often trigger secondary neurodegeneration in remote brain regions, such as the thalamus. This secondary thalamic injury exacerbates neurological deficits, leading to long-term sensory, motor, and cognitive impairments. Although animal models have demonstrated that secondary thalamic damage is driven by retrograde degeneration, excitotoxicity, apoptosis, blood-brain barrier disruption, and neuroinflammation, the mechanisms linking cortical stroke to thalamic degeneration remain poorly understood. In this study, we investigated the dynamics of secondary thalamic injury in a rat model of cortical stroke. We evaluated the therapeutic potential of intracortical transplantation of human induced pluripotent stem cell iPSC)-derived neuronal progenitors. Cortical ischemic stroke was induced via distal middle cerebral artery occlusion, and animals were assessed at multiple time points post-stroke. We observed stable cortical infarcts by 2 weeks, followed by progressive thalamic degeneration, particularly in the ventral posterior nucleus (VPN), which began at 3 months and persisted up to 6 months. Neuronal loss in the VPN correlated with the size of the cortical lesion, and microglial activation in the thalamus peaked at 2-4 months, suggesting a role for neuroinflammation in secondary degeneration. Intracortical transplantation of cortically primed iPSC-derived progenitors 48 hours post-stroke did not alter the cortical infarct volume but significantly reduced thalamic neuronal loss. Grafted cells integrated into the host tissue and presumably established functional connections, potentially mitigating secondary thalamic injury. These findings highlight the therapeutic potential of stem cell-based interventions to prevent secondary neurodegeneration and improve long-term outcomes after cortical stroke. This study provides critical insights into the mechanisms of secondary thalamic injury and demonstrates the feasibility of intracortical transplantation as a strategy to enhance post-stroke recovery.

Chemical targeting of the ATXN1 aa99-163 interaction site suppresses polyQ-expanded protein dimerization
Spinocerebellar ataxia type 1 (SCA1) is a neurodegenerative disease caused by the expansion of a polyglutamine (polyQ) tract in the ATXN1 protein. This expansion is thought to be responsible for the gradual aggregation of the mutant protein, which is associated with increased cytotoxicity and neuronal cell death. Apart from the polyQ tract, other domains in ATXN1 are also involved in the initial events of protein aggregation such as a dimerization domain that promotes protein oligomerization. ATXN1 interacts with various proteins; among them, MED15 that significantly enhances the aggregation of the polyQ-expanded protein. Therefore, we set to identify the interaction site between ATXN1 and MED15 and assess whether its chemical targeting would affect polyQ protein aggregation. First, we predicted the structure of ATXN1 and MED15 and simulated their interaction. We experimentally validated that amino acids (aa) 99-163 of ATXN1 and aa548-665 of MED15 are critical for this protein-protein interaction (PPI). We also show that the aa99-163 domain in ATXN1 is involved in the dimerization of the mutant isoform. Targeting this domain with a chemical compound identified through virtual screening (Chembridge ID: 5755483) inhibited both the interaction of ATXN1 with MED15 and the dimerization of polyQ-expanded ATXN1. These results strengthen our assumption that the aa99-163 domain of ATXN1 may be involved in polyQ protein aggregation and highlight compound 5755483 as a potent first-in-class therapeutic agent for SCA1.

FM-dye inhibition of Piezo2 relieves acute inflammatory and osteoarthritis knee pain in mice of both sexes
Musculoskeletal pain is a significant burden affecting billions of people with little progress in the development of pharmaceutical pain relief options. The mechanically-activated ion channel Piezo2 has been shown to play a role in mechanical sensitization; however there has been little progress in examining therapeutics that target this molecule. The goal of this study was to assess the effect of two FM-dyes, FM1-43 or FM4-64, in reducing acute inflammatory and osteoarthritis knee joint pain in mice of both sexes. In our acute model of Complete Freund's adjuvant (CFA)-induced joint pain, mice intra-articularly injected with FM1-43 exhibited an attenuation of knee hyperalgesia 90 minutes following injection. In vivo calcium imaging of the dorsal root ganglion (DRG) also demonstrated a reduction in nociceptor responses to mechanical forces applied to the knee joint of CFA mice following FM-dye injection. Male and female WT mice subjected to partial medial meniscectomy (PMX) surgery as a model of osteoarthritis developed more severe knee hyperalgesia than nociceptor-specific Piezo2 conditional knock-out mice. Intra-articular injection of FM1-43 reduced both knee hyperalgesia and weight-bearing asymmetry in this model and had no effect in Piezo2 conditional knock-out mice. Finally, in mice with spontaneous osteoarthritis associated with aging, intra-articular injection of FM-dyes also reduced knee hyperalgesia. In conclusion, inhibiting Piezo2 genetically or pharmacologically was effective in reducing pain-related behaviors in mice of both sexes in the setting of inflammatory and osteoarthritis knee pain. These studies provide evidence of the therapeutic potential of targeting Piezo2 in musculoskeletal pain conditions.

A NaV1.8FlpO mouse enabling selective intersectional targeting of low threshold C fiber mechanoreceptors and nociceptors
Genetic targeting of select populations of cells in the mouse nervous system is often hampered by a lack of selectivity, as candidate genes for such targeting are commonly expressed by multiple cell populations, also in the same region. Intersectional targeting using two or more genes has been enabled by the development of reporter tools dependent on more than one recombinase or gene regulator. Still, widespread adoption of intersectional tools is complicated by a scarcity of driver mice expressing recombinases otherthan Cre. Here we report the generation and characterization of a new driver mouse that expresses the FlpO recombinase from the endogenous locus of the Scn10a gene encoding NaV1.8, a voltage-gated sodium channel that is almost exclusively expressed in the afferent limb of the peripheral nervous system. Moreover, among sensory neurons the channel is preferentially expressed in nociceptors and in low-threshold C-fiber mechanoreceptors (C-LTMRs). The mouse showed high recombination efficiency (97 %) and selectivity (93 %) in dorsal root ganglia. Reporter-expressing fibers were observed in a variety of peripheral tissues, including skin, skeletal muscle, genitalia, bladder and intestines. To validate the suitability of the FlpO mouse line for intersectional targeting, we crossed it with a mouse line expressing CreERT2 from the Th (tyrosine hydroxylase) locus. This approach resulted in strikingly selective and efficient targeting of C-LTMRs, showing robust visualization of nerve endings of these fibers in skin and spinal cord at the light and electron microscopic level. Thus, the NaV1.8Flpo mouse line presented here constitutes a selective and versatile tool for intersectional genetic targeting of NaV1.8 expressing primary afferent neurons.

Eye movements anticipate target rebounds in an interception task
Predictive control in humans enables anticipatory behavior by combining sensory feedback with internal forward models. In interception tasks, such predictive processing could enable the visual system to estimate future target positions, thereby facilitating precise and timely motor responses. This study investigated the existence of predictive fixations during a visuomotor task where participants used a joystick to intercept a target that rebounded within a circular arena. We categorized eye movements into fixations, smooth pursuits, and saccades using a threshold-based classification method. The task's circular geometry simplified trajectory analysis by consistently redirecting the target toward the arena's center after rebounds, enabling clear identification of predictive fixations. Results showed that participants consistently aligned their gaze and joystick movements with the target's anticipated trajectory before rebounds. Similarly, fixation and gaze onsets showed pre-rebound adjustments, using learned statistical regularities of rebounds to anticipate and prepare for changes in the target's trajectory. Directional cues from the target's entry angles just before rebounding influenced gaze alignment and prediction accuracy, while target speeds affected fixation locations. Moreover, masking the target disrupted gaze alignment and increased variability, whereas masking the user had minimal effects, highlighting the importance of target visibility in predictive control. These findings demonstrate the crucial role of predictive fixations in visuomotor coordination, offering a broader understanding of anticipatory behaviors and their applications in dynamic tasks. Our task's design offers a robust framework for studying predictive processing across individuals, with implications for sports performance, clinical diagnostics, and human-computer interaction.

PACAP Signaling Network in the Nucleus Accumbens Core Regulates Reinstatement Behavior in Rat
Cocaine use disorder (CUD) lacks FDA-approved treatments, partly due to the difficulty of creating therapeutics that target behavior-related neural circuits without disrupting signaling throughout the brain. Recent evidence highlights the therapeutic potential of targeting gut-brain axis components, such as GLP-1 receptors, to modulate neural circuits with minimal central nervous system disruption. Like GLP-1, pituitary adenylate cyclase polypeptide (PACAP) is a component of the gut-brain axis that regulates behavior through a network spanning the gut and brain. Here, we investigated the potential existence and function of an endogenous PACAP signaling network within the nucleus accumbens core (NAcc), which is a structure that integrates emotional, cognitive, and reward processes underlying behavior. We found that PACAP and its receptor, PAC1R, are endogenously expressed in the rat NAcc and that PACAP mRNA is present in medial prefrontal cortical projections to the NAcc. Behaviorally, intra-NAcc infusions of PACAP (100 pm) did not induce seeking behavior but blocked cocaine-primed reinstatement (10 mg/kg, IP). Intra-NAcc PACAP also inhibited reinstatement driven by co-infusion of the D1 receptor agonist (SKF 81297, 3 microg) but not the D2 receptor agonist (sumanirole, 10 ng). These findings are significant since D1 and D2 receptor activities in the NAcc govern distinct behavioral mechanisms indicating precise actions of PACAP even within the NAcc. Future research should examine whether NAcc PACAP signaling can be selectively engaged by peripheral gut-brain axis mechanisms, potentially unveiling novel therapeutic approaches for CUD and related disorders.

Role of CaMKIIa reticular neurons of caudal medulla in control of posture
Terrestrial quadrupeds actively stabilize dorsal-side-up orientation of the body in space due to activity of the postural control system. Supraspinal influences, including those from the reticular formation, play a crucial role in the operation of this system. However, the role of specific molecularly identified populations of reticular neurons in control of posture remains unknown. The aim of the present study was to reveal the role of CaMKIIa reticular neurons (CaMKIIa-RNs) located in the caudal medulla in control of posture. For this purpose, the effects of unilateral chemogenetic activation/inactivation of CaMKII-RNs on different aspects of postural control were studied in mice. It was found that unilateral activation of CaMKIIa-RNs evoked ipsilateral roll tilt of the head and trunk, caused by flexion/adduction of the ipsilateral limbs and extension/abduction of the contralateral limbs. The body roll tilt was actively stabilized on the tilting platform and maintained during walking. Unilateral inactivation of CaMKIIa-RNs evoked the opposite effects. Histological analyses showed that the population of CaMKIIa-RNs in the caudal medulla contains reticulospinal neurons that project to the spinal cord mainly through ipsilateral lateral funiculus and terminate in the intermediate area of the gray matter. We demonstrated that although the population of CaMKIIa-RNs contains both excitatory and inhibitory neurons, the excitatory ones dominate. Thus, CaMKIIa-RNs located in the caudal medulla play a crucial role for maintenance of the dorsal-side-up body orientation in different environments. Left/right symmetry and asymmetry in activity of CaMKIIa-RNs allows animals to maintain dorsal-side-up body orientation on horizontal and laterally inclined surfaces, respectively.

Mapping energy metabolism systems in the human brain
Energy metabolism involves a network of biochemical reactions that generate ATP, utilizing substrates such as glucose and oxygen supplied via cerebral blood flow. Energy substrates are metabolized in multiple interrelated pathways that are cell- and organelle-specific. These pathways not only generate energy but are also fundamental to the production of essential biomolecules required for neuronal function and survival. How these complex biochemical processes are distributed over the cortex is integral to understanding the structure and function of the brain. Here, using curated gene sets and whole-brain transcriptomics, we generate maps of five fundamental energy metabolic pathways: glycolysis, pentose phosphate pathway, tricarboxylic acid cycle, oxidative phosphorylation and lactate metabolism. We find consistent divergence between primarily energy-producing pathways and anabolic pathways, particularly in unimodal sensory cortices. We then explore the spatial alignment of these maps with multi-scale structural and functional attributes, including metabolic uptake, neurophysiological oscillations, cell type composition, laminar organization and macro-scale connectivity. Finally, we show that metabolic pathways exhibit unique developmental trajectories from the fetal stage to adulthood. The primary energy-producing pathways peak in late childhood, while the anabolic pentose phosphate pathway shows pronounced expression in the fetal stage and declines throughout life. Together, these results highlight the rich biochemical complexity of energy metabolism organization in the brain.

SYSTEM XC- AS A MOLECULAR MECHANISM FOR EVOLUTIONARY NEW FORMS OF ADVANCED COGNITION
Human cognitive abilities are deeply rooted in evolutionary building blocks that maximize computation while maintaining efficiency. These abilities are not without evolutionary signatures; conserved processes like vision have undergone continual phylogenetic adjustments to better serve ecological niches. Conversely, more sophisticated forms of cognition may have required evolutionary innovations to transform existing neuronal processing to expand computational abilities. One such innovation is system xc- (Sxc), a cystine-glutamate antiporter predominantly localized to astrocytes that emerged in deuterostomes (e.g., vertebrates) after their divergence from protostomes over 550 million years ago. Previous evidence suggests that genetically modified rats that lack functional Sxc (MSxc) exhibit enhanced cocaine-seeking behavior. In this study, we deconstructed drug-seeking into its component behaviors, categorizing them as reliant on evolutionary conserved or newly evolved cognitive processes. Our results reveal that Sxc function is dispensable for conserved processes like visual, emotional, and hedonic processing, but critical for advanced, evolutionary new cognitive functions, particularly impulse control and decision making. Notably, we demonstrate a temporally specific reliance on Sxc during the learning phase of optimal decision-making, but not in maintaining established strategies. This is an important addition to our current understanding of astrocytes in non-homeostatic functions, indicating their critical role in computationally demanding phases of learning and memory. Unraveling evolutionary innovations like Sxc not only deepens our understanding of cognitive evolution but also paves the way for revolutionary, precision-targeted therapies in neuropsychiatric disorders, potentially transforming treatment paradigms and patient outcomes.

Transcriptional Profiles in Nucleus Accumbens of Antidepressant Resistance in Chronically Stressed Mice
Unsuccessful response to several courses of antidepressants is a core feature of treatment-resistant depression (TRD), a severe condition that affects a third of patients with depression treated with conventional pharmacotherapy. However, the molecular mechanisms underlying TRD remain poorly understood. Here, we assessed the successful vs. unsuccessful response to ketamine (KET) in chronically stressed mice that failed to respond to initial treatment with fluoxetine (FLX) as a rodent model of TRD and characterized the associated transcriptional profiles in the nucleus accumbens (NAc) using RNA-sequencing. We observed that failed treatment with FLX exerts a priming effect that promotes behavioral and transcriptional responses to subsequent ketamine treatment. We also identified specific gene networks that are linked to both susceptibility to stress and resistance to antidepressant response. Collectively, these findings offer valuable insights into the molecular mechanisms underlying antidepressant resistance and help address a critical gap in preclinical models of TRD.

How the dynamic interplay of cortico-basal ganglia-thalamic pathways shapes the time course of deliberation and commitment
Although the cortico-basal ganglia-thalamic (CBGT) network is identified as a central circuit for decision-making, the dynamic interplay of multiple control pathways within this network in shaping decision trajectories remains poorly understood. Here we develop and apply a novel computational framework --- CLAW (Circuit Logic Assessed via Walks) --- for tracing the instantaneous flow of neural activity as it progresses through CBGT networks engaged in a virtual decision-making task. Our CLAW analysis reveals that the complex dynamics of network activity is functionally dissectible into two critical phases: deliberation and commitment. These two phases are governed by distinct contributions of underlying CBGT pathways, with indirect and pallidostriatal pathways influencing deliberation, while the direct pathway drives action commitment. We translate CBGT dynamics into the evolution of decision-related policies, based on three previously identified control ensembles (responsiveness, pliancy, and choice) that encapsulate the relationship between CBGT activity and the evidence accumulation process. Our results demonstrate two contrasting strategies for decision-making. Fast decisions, with direct pathway dominance, feature an early response in both boundary height and drift rate, leading to a rapid collapse of decision boundaries and a clear directional bias. In contrast, slow decisions, driven by indirect and pallidostriatal pathway dominance, involve delayed changes in both decision policy parameters, allowing for an extended period of deliberation before commitment to an action. These analyses provide important insights into how the CBGT circuitry can be tuned to adopt various decision strategies and how the decision-making process unfolds within each regime.

CDKL5 modulates structural plasticity of excitatory synapses via liquid-liquid phase separation
Activity-dependent synaptic remodeling, essential for neural circuit plasticity, is orchestrated by central organizers within the postsynaptic density (PSD), including the scaffolding protein PSD95. However, the molecular mechanisms driving this process remain incompletely understood. Here, we identify CDKL5, a protein associated with a severe neurodevelopmental condition known as CDKL5 deficiency disorder (CDD), as a critical regulator of structural plasticity at excitatory synapses. We show that CDKL5 undergoes liquid-liquid phase separation (LLPS) in vitro and in cultured neurons, forming co-condensates with PSD95. This LLPS-driven process spatially organizes synaptic components, specifically enabling the synaptic recruitment of Kalirin7 to promote dendritic spine enlargement. Pathogenic mutations disrupt condensate formation by impairing the LLPS capacity of CDKL5, directly linking phase separation defects to the pathogenesis of CDD. Our findings reveal a crucial role for CDKL5 in synaptic plasticity and establish LLPS as a fundamental mechanism by which CDKL5 coordinates molecular events to reorganize PSD architecture during synaptic remodeling.

Neural and computational evidence for a predictive learning account of the testing effect
Testing enhances memory more than studying. Although numerous studies have demonstrated the robustness of this classic effect, its neural and computational origin remains debated. Predictive learning is a potential mechanism behind this phenomenon: Because predictions and prediction errors (mismatch between predictions and feedback) can only be generated in testing (and not in studying), testing can benefit from predictive learning. We shed light on the testing effect from a multi-level analysis perspective via a combination of cognitive neuroscience experiments (fMRI) and computational modeling. At the neural level, we find that testing activates the canonical brain area related to reward prediction error, namely the ventral striatum. Crucially, activation in the ventral striatum fully mediates the testing effect. Computationally, only a model incorporating predictive learning can account for the full breadth of behavioral patterns observed in the data. These results provide strong and converging evidence for a predictive learning account of the testing effect.

Hippocampal sequences represent working memory and implicit timing
Working memory (WM) and timing are considered distinct cognitive functions, yet the neural signatures underlying both can be similar. To address the hypothesis that WM and timing may be multiplexed we developed a novel rodent task where 1st odor identity predicts the delay duration. We found that WM performance decreased when delay expectations were violated. Performance was worse for unexpected long delays than for unexpected short delays, suggesting that WM may be tuned to expire in a delay-dependent manner. Calcium imaging of dorsal CA1 neurons revealed odor-specific sequential activity tiling the short and long delays. Neural sequence structure also reflected expectation of the timing of the 2nd odor - i.e., of the expected delay. Consistent with the hypothesis that WM and timing may be multiplexed, our findings suggest that neural sequences in dorsal CA1 may encode cues and cue-specific elapsed time during the delay period of a WM task.

Proteomic Analysis of Endemic Viral Infections in Neuronsoffers Insights into Neurodegenerative Diseases
Endemic viral infections with low pathogenicity are often overlooked due to their mild symptoms, yet they can exert long-term effects on cellular function and contribute to disease pathogenesis. While viral infections have been implicated in neurodegenerative disorders, their impact on the neuronal proteome remains poorly understood. Here, we differentiated human induced pluripotent stem cells (KOLF2.1J) into mature neurons to investigate virus-induced proteomic changes following infection with five neurotropic endemic human viruses: Herpes simplex virus 1 (HSV-1), Human coronavirus 229E (HCoV-229E), Epstein-Barr virus (EBV), Varicella-Zoster virus (VZV), and Influenza A virus (H1N1). Given that these viruses can infect adults and have the potential to cross the placental barrier, their molecular impact on neurons may be relevant across the lifespan. Using mass spectrometry-based proteomics with a customized library for simultaneous detection of human and viral proteins, we confirmed successful infections and identified virus-specific proteomic signatures. Notably, virus-induced protein expression changes converged on key neuronal pathways, including those associated with neurodegeneration. Gene co-expression network analysis identified protein modules correlated with viral proteins. Pathway enrichment analysis of these modules revealed associations with the nervous system, including pathways linked to Alzheimer's and Parkinson's disease. Remarkably, several viral-induced proteomic alterations overlapped with changes observed in postmortem Alzheimer's patient brains, suggesting a mechanistic connection between viral exposure and neurodegenerative disease progression. These findings provide molecular insights into how common viral infections perturb neuronal homeostasis and may contribute to neurodegenerative pathology, highlighting the need to consider endemic viruses as potential environmental risk factors in neurological disorders.

Transcranial electrical stimulation for memory enhancement: A systematic review and meta-analysis
Background Non-invasive brain stimulation techniques have received increasing interest for their potential to enhance memory function, a fundamental cognitive aspect of daily life. Methods This systematic review and meta-analysis investigated the efficacy of transcranial electrical stimulation (tES) in enhancing memory function in healthy adults, following the pre-registered strategy at PROSPERO (CRD42022353630). Results A total of 66 articles (119 trials, 3,786 participants) focusing on transcranial direct current stimulation and transcranial alternating current stimulation were identified. Meta-analysis revealed a significant overall effect of tES on memory function compared with sham stimulation (standardized mean difference [95% confidence interval] = 0.19 [0.12-0.27]), with anodal transcranial direct current stimulation showing the most consistent enhancement. In particular, stimulation of the frontal regions effectively improved working and declarative memories. While the effects remained significant within hours post stimulation, they diminished after one day or longer. Regarding adverse events, tingling and itching sensations on the scalp occurred more frequently in the active group than in the sham group, but no severe adverse events were reported. Challenges, including publication bias, heterogeneity, and bias toward specific aspects of memory were noted, emphasizing the need for improved experimental rigor and diversification of memory tasks. Conclusion These findings highlight the potential of tES as a safe and effective tool for memory enhancement while emphasizing areas for future research to develop its applications.

Single-cell Spatial Transcriptomics Reveals Disease-specificMicroenvironmental Niches in Neurodegeneration and COVID-19
Neurodegenerative diseases and infections can produce lasting effects on brain function, yet the spatial molecular mechanisms underlying these changes remain poorly understood. Here, we present high-resolution spatial transcriptomics of 40 postmortem brain samples from patients with Parkinson's disease, frontotemporal dementia, dementia with Lewy bodies, and severe COVID-19. Analyzing over 1.5 million spatially resolved cells across dorsolateral prefrontal cortex and anterior cingulate cortex revealed disease-specific transcriptional signatures with pronounced layer- and region-specificity. In Parkinson's disease, we identified stressed neurons creating distinctive microenvironmental gradients where metabolic and protein degradation pathways are elevated near stress epicenters, while regenerative processes increase with distance. COVID-19 brains displayed extensive peripheral immune cell infiltration, particularly in the subcortical white matter, accompanied by compromised blood-brain barrier and coordinated neuroinflammatory responses from microglia, astrocytes, and endothelial cells. Integration of miRNA sequencing with spatial transcriptomics uncovered layer-specific regulatory patterns, including neuroinflammation-associated miR-155. This atlas provides unprecedented insights into disease pathology and highlights the critical importance of spatial molecular context in understanding brain disorders.

Complementary roles for hippocampus and anterior cingulate in composing continuous choice
Naturalistic, goal directed behavior often requires continuous actions directed at dynamically changing goals. In this context, the closest analogue to choice is a strategic reweighting of multiple goal-specific control policies in response to shifting environmental pressures. To understand the algorithmic and neural bases of choice in continuous contexts, we examined behavior and brain activity in humans performing a continuous prey-pursuit task. Using a newly developed control-theoretic decomposition of behavior, we find pursuit strategies are well described by a meta-controller dictating a mixture of lower-level controllers, each linked to specific pursuit goals. Examining hippocampus and anterior cingulate cortex (ACC) population dynamics during goal switches revealed distinct roles for the two regions in parameterizing continuous controller mixing and meta-control. Hippocampal ensemble dynamics encoded the controller blending dynamics, suggesting it implements a mixing of goal-specific control policies. In contrast, ACC ensemble activity exhibited value-dependent ramping activity before goal switches, linking it to a meta-control process that accumulates evidence for switching goals. Our results suggest that hippocampus and ACC play complementary roles corresponding to a generalizable mixture controller and meta-controller that dictates value dependent changes in controller mixing.

Neotenic expansion of adult-born dentate granule cells reconfigures GABAergic inhibition to enhance social memory consolidation
Adult-born dentate granule cells (abDGCs) contribute to hippocampal dentate gyrus (DG)-CA3/CA2 circuit functions in memory encoding, retrieval and consolidation. Heightened synaptic and structural plasticity of immature abDGCs is thought to govern their distinct contributions to circuit and network mechanisms of hippocampal-dependent memory operations. Protracted maturation or neoteny of abDGCs in higher mammals is hypothesized to offset decline in adult hippocampal neurogenesis by expanding the capacity for circuit and network plasticity underlying different memory operations. Here, we provide evidence for this hypothesis by genetically modelling the effective impact of neoteny of abDGCs on circuitry, network properties and social cognition in mice. We show that selective synchronous expansion of a single cohort of 4 weeks old immature, but not 8 weeks old mature abDGCs, increases functional recruitment of fast spiking parvalbumin expressing inhibitory interneurons (PV INs) in CA3/CA2, number of PV IN-CA3/CA2 synapses, and GABAergic inhibition of CA3/CA2. This transient increase in feed-forward inhibition in DG-CA2 decreased social memory interference and enhanced social memory consolidation. In vivo local field potential recordings revealed that the expansion of a single cohort of 4-week-old abDGCs increased baseline power, amplitude, and duration, as well as sensitivity to social investigation-dependent rate changes of sharp-wave ripples (SWRs) in CA1 and CA2, a neural substrate for memory consolidation. Inhibitory neuron-targeted chemogenetic manipulations implicate CA3/CA2 INs, including PV INs, as necessary and sufficient for social memory consolidation following neotenic expansion of the abDGC population and in wild-type mice, respectively. These studies suggest that neoteny of abDGCs may represent an evolutionary adaptation to support cognition by reconfiguring PV IN-CA3/CA2 circuitry and emergent network properties underlying memory consolidation.

From comparative connectomics to large-scale working memory modeling in macaque and marmoset
Although macaques and marmosets are both primates of choice for studying the brain mechanisms of cognition, they differ in key aspects of anatomy and behavior. Interestingly, recent connectomic analysis revealed that strong top-down projections from the prefrontal cortex to the posterior parietal cortex, present in macaques and important for executive function, are absent in marmosets. Here, we propose a consensus mapping that bridges the two species' cortical atlases and allows for direct area-to-area comparison of their connectomes, which are then used to build comparative computational large-scale modeling of the frontoparietal circuit for working memory. We found that the macaque model exhibits resilience against distractors, a prerequisite for normal working memory function. By contrast, the marmoset model is sensitive to distractibility commonly observed behaviorally in this species. Surprisingly, this contrasting trend can be swapped by scaling intrafrontal and frontoparietal connections. Finally, the relevance to primate ethology and evolution is discussed.

A fast nociceptive subsystem mediating rapid reflexive behavior but not affective pain
Spinal nociceptive withdrawal reflexes are widely believed to rely on unmyelinated and thinly myelinated nociceptive fibers that also signal affective and motivational aspects of pain. Here we discover a population of myelinated mechanoreceptive nociceptor that forms free nerve endings as well as circumferential endings around hair follicles, and exclusively terminate in the deep spinal dorsal horn. Optogenetic activation of these fibers triggers rapid withdrawal reflexes that are precise and selective for the targeted limb, while silencing increases the threshold of mechanical nociceptive withdrawal reflexes. By contrast, optogenetic stimulation of the fibers is not associated with place aversion nor with changes in facial expression. Thus, we conclude that this nerve fiber population is uniquely positioned to rapidly respond to mechanical threats via selective withdrawal of the targeted body part, whereas other fast and slow nociceptive pathways are required for affective-motivational aspects of pain.

Characterization and targeting of the endosomal signaling of the gastrin releasing peptide receptor in pruritus.
Chronic pruritus is a major unmet clinical problem affecting one in four adults. G protein-coupled receptors (GPCRs) are key receptors driving itch signaling and are a therapeutic target for itch relief. The endosomal signaling of GPCRs provides new challenges for understanding how GPCR signaling is regulated, how endosomal signaling of GPCRs contributes to disease states like chronic pruritus and opens new targets for therapeutic development. The Gastrin releasing peptide receptor (GRPR) is a key mediator of pruritus in the spinal cord. Yet, little is known about the molecular mechanisms regulating GRPR signaling in pruritus, if GRPR can signal from endosomes, or the role of endosomal GRPR in the development of pruritus. Here we show the importance of internalization and endosomal signaling of GRPR in pruritus. Agonist induced GRPR internalization and trafficking was quantified using BRET or microscopy while endosomal-mediated ERK signaling was measured using compartmentalized FRET biosensors. Recruitment of G proteins to endosomes was measured with NanoBit BRET. pH sensitive mesoporous silica nanoparticles (MSN) which accumulated in endosomes were used to deliver RC-3095, a GRPR specific antagonist, intracellularly to block endosomal signaling of GRPR. MSN-RC proved more effective than free RC-3095 at inhibiting chloroquine scratching in mice. Our results demonstrate a critical role for GRPR endosomal signaling in itch sensation. These results highlight the ability of endosomally targeted antagonist to inhibit GRPR signaling and provide a new target for developing therapeutics that block GRPR mediated pruritus.

Differential Effects of Cocaine Self-Administration Regimens on Incubation of Cocaine Craving and Nucleus Accumbens Neuronal Ensembles Activated by Cocaine-Associated Context
Drug addiction develops in a subset of users following repeated exposure, influenced by biopsychosocial factors. Rodent self-administration protocols, varying in drug access times, are used to study both controlled and compulsive drug-taking behaviors and their neurobiological underpinnings. Drug-associated cues and environmental contexts are well-established triggers for relapse, with susceptibility to these stimuli peaking during early abstinence and remaining elevated, thereby increasing relapse risk. This phenomenon, known as incubation of craving, has been replicated across substances in animal models. The associative learning between drug effects and contextual cues is encoded by neuronal ensembles activated by drug-associated stimuli, driving craving, seeking, and relapse. Neuronal ensembles in the nucleus accumbens (NAcc) are strongly involved in drug seeking, with parvalbumin-expressing fast-spiking interneurons playing a key role in this associative learning process. We investigated activation patterns in the NAcc triggered by cocaine-related cues following restricted- or extended-access self-administration and examined how forced abstinence alters these patterns, contributing to the incubation of cocaine craving. We also analyzed the engagement of parvalbumin-positive interneurons in NAcc neuronal ensembles before and after forced abstinence. Our findings show that the extended access protocol more effectively induced the incubation of cocaine craving. Neuronal activation in the NAcc core increased after thirty days of forced abstinence in both groups, with extended access rats showing consistently higher activation. Forced abstinence also increased NAcc shell activation, with no differences between protocols. NAcc core activation, but not shell, was influenced by cocaine consumption during training. Notably, extended access rats exhibited reduced parvalbumin interneurons activation following thirty days of forced abstinence. Based on these findings, we speculate that the transition from occasional to compulsive drug-taking may be driven by molecular changes in the NAcc core that enhance its responsiveness to drug-related cues. Additionally, the incubation of craving could be linked to impaired inhibitory control of NAcc core medium spiny neurons by PV interneurons.

Markov models bridge behavioral strategies and circuit principles facilitating thermoregulation
Behavioral thermoregulation is critical for survival across animals, including endothermic mammals. However, we do not understand how neural circuits control navigation towards preferred temperatures. Zebrafish exclusively regulate body temperature via behavior, making them ideal for studying thermal navigation. Here, we combine behavioral analysis, machine learning and calcium imaging to understand how larval zebrafish seek out preferred temperatures within thermal gradients. By developing a stimulus-controlled Markov model of thermal navigation we find that hot avoidance largely relies on the modulation of individual swim decisions. The avoidance of cold temperatures, a particular challenge in ectotherms, however relies on a deliberate strategy combining gradient alignment and directed reversals. Calcium imaging identified neurons within the medulla encoding thermal stimuli that form a place-code like representation of the gradient. Our findings establish a key link between neural activity and thermoregulatory behavior, elucidating the neural basis of how animals seek out preferred temperatures.

Investigating the temporal dynamics and modelling of mid-level feature representations in humans
Scene perception is a key function of biological visual systems. According to the hierarchical processing view, scene perception in the human brain begins with low-level features, progresses to mid-level features, and ends with high-level features. While low- and high-level feature processing is well-studied, research on mid-level features remains limited. Here, we addressed this gap by investigating when mid-level features are processed in humans using a novel stimulus set of naturalistic scenes as images and videos, accompanied with ground-truth annotations for five mid-level features (reflectance, lighting, world normals, scene depth and skeleton position), and two framing features: one low-level (edges) and one high-level feature (action). To reveal when low-, mid- and high-level features are represented in the brain, we collected electroencephalography (EEG) data from human participants during stimulus presentation and trained encoding models to predict EEG data from ground-truth annotations. We revealed that mid-level features were best represented between ~100 and ~250 ms post-stimulus, between low- and high-level features. Moreover, we assessed scene- and action-trained convolutional neural networks (CNNs) as models of mid-level feature processing in humans. We found a comparable processing order for mid- but not low- or high-level features with humans. Overall, our results characterize mid-level feature processing in humans in the temporal domain and reveal CNNs as suitable models of the processing hierarchy of mid-level vision in humans.

Dissecting heterogeneity in cortical thickness abnormalities in major depressive disorder: a large-scale ENIGMA MDD normative modelling study
Importance: Major depressive disorder (MDD) is highly heterogeneous, with marked individual differences in clinical presentation and neurobiology, which may obscure identification of structural brain abnormalities in MDD. To explore this, we used normative modeling to index regional patterns of variability in cortical thickness (CT) across individual patients. Objective: To use normative modeling in a large dataset from the ENIGMA MDD consortium to obtain individualised CT deviations from the norm (relative to age, sex and site) and examine the relationship between these deviations and clinical characteristics. Design, setting, and participants: A normative model adjusting for age, sex and site effects was trained on 35 CT measures from FreeSurfer parcellation of 3,181 healthy controls (HC) from 34 sites (40 scanners). Individualised z-score deviations from this norm for each CT measure were calculated for a test set of 2,119 HC and 3,645 individuals with MDD. For each individual, each CT z-score was classified as being within the normal range (95% of individuals) or within the extreme range (2.5% of individuals with the thinnest or thickest cortices). Main outcome measures: Z-score deviations of CT measures of MDD individuals as estimated from a normative model based on HC. Results: Z-score distributions of CT measures were largely overlapping between MDD and HC (minimum 92%, range 92-98%), with overall thinner cortices in MDD. 34.5% of MDD individuals, and 30% of HC individuals, showed an extreme deviation in at least one region, and these deviations were widely distributed across the brain. There was high heterogeneity in the spatial location of CT deviations across individuals with MDD: a maximum of 12% of individuals with MDD showed an extreme deviation in the same location. Extreme negative CT deviations were associated with having an earlier onset of depression and more severe depressive symptoms in the MDD group, and with higher BMI across MDD and HC groups. Extreme positive deviations were associated with being remitted, of not taking antidepressants and less severe symptoms. Conclusions and relevance: Our study illustrates a large heterogeneity in the spatial location of CT abnormalities across patients with MDD and confirms a substantial overlap of CT measures with HC. We also demonstrate that individualised extreme deviations can identify protective factors and individuals with a more severe clinical picture.

The Cortical Output System that Controls a Single Vibrissa Muscle
What is the neural substrate that enables the cerebral cortex to control a single mystacial vibrissa and orchestrate its movement? To answer this question, we injected rabies virus into the intrinsic muscle that protracts the rat C3 vibrissa and used retrograde transneuronal transport to identify the cortical neurons that control the muscle. A surprisingly diverse set of cortical areas is the origin of disynaptic control over the motoneurons that influence the C3 protractor. More than two thirds of these layer 5 pyramidal neurons (L5PNs) are dispersed in frontal and parietal areas outside the primary motor cortex (vM1). This observation emphasizes the importance of descending commands from non-primary motor areas. More than a third of the L5PNs originate from somatosensory areas, such as the barrel field (vS1). The barrel field has been long considered a prototypic model system for studying sensory processing at the level of the cerebral cortex. Even so, we find that the number of L5PNs in vS1, and even their peak density, rivals the number and peak density of L5PNs in vM1. Thus, our results emphasize the importance of the barrel field in processing motor output. The distribution of L5PNs in vM1 and vS1 leads us to propose a new model of vibrissa protraction in which vM1 output results in protraction, and vS1 output results in reciprocal inhibition (suppression) of protraction. This paired initiation and suppression of complementary movements may be a general feature of the descending control signals from the rodent M1 and S1.

Varicose-projection astrocytes: a reactive phenotype associated with neuropathology
Glial cells are fundamental for the pathophysiology of all neurological disorders. Astrocytes, the primary homeostatic cells of the central nervous system (CNS), exhibit species-specific characteristics, with human astrocytes specifically displaying unique structural and functional features. It is thus essential to investigate human-specific astrocytic responses to neuropathology using human-relevant models. Varicose projection (VP) astrocytes, traditionally considered specific to humans and apes, were suggested to reflect pathological burden, albeit direct evidence linking them to neurological diseases has been lacking. Here, we demonstrate for the first time that VP astrocytes are present in mice and tigers (Panthera tigris) and we provide evidence from four distinct human-based models that VP astrocytes are not a distinct physiological astrocyte subtype but rather a novel class of reactive astrocytes associated with neuropathology. Using human induced pluripotent stem cell (hiPSC)-derived astrocytes, mixed neural cultures, and cortical organoids, we showed that VP astrocytes are induced by pro-inflammatory cytokines interleukin-1{beta} (IL-1{beta}) and tumor necrosis factor- (TNF-) or LPS. Notably, cytokine withdrawal reverses the VP phenotype of astrocytes, indicating that it is a transient, inflammation-dependent state. We characterized the distinctive components of varicosities, including markers for extracellular vesicles, mitochondria, Golgi and endoplasmic reticulum components, suggesting roles in cellular stress responses and metabolic dysregulation. We further validated the pathological relevance of VP astrocytes by documenting their significant enrichment in postmortem brain samples from patients with several neurodegenerative diseases including as Alzheimer's disease, Parkinson's disease, and multiple sclerosis, as well as in surgical resections from patients with epilepsy due to hippocampal sclerosis or brain tumors, including previously unreported subcortical regions such as basal ganglia. Additionally, we identified a higher number of VP astrocytes also in mouse astrocytes upon treatment with pro-inflammatory cytokines, suggesting that the formation of VP astrocytes is an evolutionarily conserved astrocytic response to neuroinflammation. Our findings point to VP astrocytes as a novel reactive astrocyte subtype closely linked to neuropathology, highlighting their potential as biomarkers and therapeutic targets in neurological diseases. This study lays the groundwork for future investigations into the mechanisms driving VP astrocyte formation and their broader implications in neuropathology.

Interleaving asynchronous and synchronous activity in balanced cortical networks with short-term synaptic depression
Cortical populations are in a broadly asynchronous state that is sporadically interrupted by brief epochs of coordinated population activity. Cortical models are at a loss to explain this combination of states. At one extreme are network models where recurrent inhibition dynamically stabilizes an asynchronous low activity state. While these networks are widely used, they cannot produce the coherent population-wide activity that is reported in a variety of datasets. At the other extreme are models in which strong recurrent excitation that is quickly tamed by short term synaptic depression between excitatory neurons leads to short epochs of population-wide activity. However, in these networks, inhibition plays only a perfunctory role in network stability, which is at odds with many reports across cortex. In this study we analyze spontaneously active in vitro preparations of primary auditory cortex that show dynamics that are emblematic of this mixture of states. To capture this complex population activity we use firing rate-based networks as well as biologically realistic networks of spiking neuron models where large excitation is balanced by recurrent inhibition, yet we include short-term synaptic depression dynamics of the excitatory connections. These models give very rich nonlinear behavior that mimics the core features of the in vitro data, including the possibility of low frequency (2-12 Hz) rhythmic dynamics within population events. In these networks, synaptic depression enables activity fluctuations to induce a weakening of inhibitory recruitment, which in turn triggers population events. In sum, our study extends balanced network models to account for nonlinear, population-wide correlated activity, thereby providing a critical step in a mechanistic theory of realistic cortical activity.

Alterations in background ECoG activity and behavioral deficits in a mouse model of CHD2-related developmental delay
Heterozygous loss of function mutations in the CHD2 gene, encoding for chromodomain helicase DNA-binding protein 2, are associated with severe childhood-onset epilepsy, global developmental delay, and autistic features. Here, we characterized the behavioral and epileptic phenotypes of a mouse model harboring a frameshift truncating mutation in the Chd2 gene (Chd2WT/m and Chd2m/m mice). Genetic background dramatically affected the phenotypes. While no phenotypes were observed on the pure C57BL/6J background, crossing these mice onto the 129X1/SvJ genetic background gradually uncovered neurodevelopmental phenotypes. Transcriptomic analysis identified Kcnj11 as a potential genetic modifier. On the 129X1/SvJ background, Chd2m/m mice demonstrated growth retardation, and both Chd2WT/m and Chd2m/m showed motor deficits, including clasping behavior and reduced abilities to balance on a rotating rod. Autistic-like features were also observed, with Chd2m/m showing reduced nest-building abilities and Chd2WT/m demonstrating increased repetitive-like behavior in the marble burying test and altered social behavior. Quantitative analysis of electrocorticographic (ECoG) recordings revealed neuronal changes consisting of a global reduction in the total power of background activity in Chd2WT/m and Chd2m/m mice, as well as increased susceptibility to seizures induced by acute administration of 4-aminopyridine. Overall, this mouse model recapitulates multiple key phenotypes observed in CHD2 patients, providing a valuable platform to study the molecular basis and treatment options for this intractable disease.

A pivotal contribution of proteostasis failure and mitochondrial dysfunction to chromosomal instability-induced microcephaly
Mosaic variegated aneuploidy (MVA), a rare human congenital disorder that causes microcephaly, is characterized by extensive abnormalities in chromosome number and results from mutations in genes involved in accurate mitotic chromosome segregation. To characterize the cellular mechanisms underlying this disease, here we generated a Drosophila model of microcephaly caused by the depletion of a single spindle assembly checkpoint (SAC) gene in the neural stem cell (NSC) compartment. We present evidence that loss of stemness (compromised identity and proliferative capacity of NSCs) is the underlying cause of MVA and results in a reduced number of neurons and glial cells. We show that loss of stemness arises from the accumulation over time of an unbalanced number of gains and losses of more than one chromosome, rather than a direct consequence of chromosomal instability-induced DNA damage or the production of simple aneuploidies. We unravel that the negative impact of complex aneuploidies on stemness, a highly energy demanding cellular state, is a result of proteostasis failure and mitochondrial dysfunction. We identify autophagy activation, either directly or through TOR depletion, overexpression of Radical Oxygen Species scavengers, and restoration of mitochondria proteostasis as genetic interventions capable of dampening the deleterious effects of aneuploidy on NSC identity and brain development.

High-Quality Cell Capture Reveals Transcriptomic Changes After Single-Axon Injury of Mauthner Cells
In vivo single-cell capture methods based on micropipettes are essential for correlating morphological characteristics with transcriptomic profiling under physiological conditions. However, they often suffer from significant contamination of off-target cells. Consequently, we developed Hip-seq, which significantly reduces heavily contaminated cells, decreases contamination levels, improves cell reproducibility, and enhances data analysis accuracy compared to patch-seq. Using Hip-seq, we found that axon regeneration failure could be due to abnormal activation of translation and the circadian clock. Axon-regenerable central neurons reactivated axon development-related genes during regeneration. And one-to-one associated analysis helped identify pro-regenerative genes.

Optimising 7T-fMRI for imaging regions of magnetic susceptibility
The temporal signal-to-noise ratio (tSNR) of functional magnetic resonance imaging (fMRI) is particularly poor in ventral anterior temporal and orbitofrontal regions because of magnetic field inhomogeneity, a problem that is exacerbated at higher field strengths. In this 7T-fMRI study we compared three methods of improving sensitivity in these areas: parallel transmit, which uses multiple transmit elements, controlled independently, to homogenise the flip angle experienced by the tissue; multi-echo, which entails collection of multiple volumes at different echo times following a single radiofrequency pulse; and multiband, in which multiple slices are acquired simultaneously. We found that parallel transmit and multi-echo increased the magnitude of the BOLD signal change, but only multi-echo increased BOLD magnitude in areas prone to susceptibility artefacts. Multiband and denoising of multi-echo data with independent components analysis (ICA) both improved precision of GLM fit. Exploratory results suggested that multi-echo and ICA denoising can both benefit multivariate analyses. In conclusion, a multi-echo, multiband sequence improved fMRI quality in areas prone to susceptibility artefacts while maintaining sensitivity across the whole brain. We recommend this approach for studies investigating the functional roles of ventral temporal and orbitofrontal regions with 7T fMRI.