bioRxiv Subject Collection: Neuroscience's Journal

Novel Approaches to Track Neurodegeneration in Murine Models of Alzheimer's Disease Reveal Previously Unknown Aspects of Extracellular Aggregate Deposition
This paper describes a novel transgenic-based platform to track degeneration of specific populations of neurons in 5xFAD mice, a murine model of Alzheimer's disease. We created a new double transgenic model by crossing 5xFAD mice with RosatdT reporter mice. 5xFAD+/-/RosatdT mice received intra-spinal cord injections of AAV-retrograde(rg)/Cre at 2-3 months of age to permanently label corticospinal neurons (CSNs). Brains and spinal cords were retrieved 2-3 weeks post-injection or at 12-14 months of age. Immunohistochemical studies of transgene expression throughout the brain and spinal cord, using an antibody selective for hAPP, revealed age-dependent accumulation of hAPP in extracellular aggregates in regions containing hAPP expressing neuronal cell bodies and in regions containing axons and synaptic terminals from hAPP expressing neurons. Permanent labeling of CSNs with tdT confirmed extensive loss of CSNs in old mice. Surprisingly, we discovered that tdT expressed by CSNs accumulated in extracellular aggregates that persisted after the neurons that expressed tdT degenerated. Extracellular aggregates of tdT also contained hAPP and co-localized with other markers of AD pathology. Overall, deposition of hAPP in extracellular aggregates in areas containing axons and synaptic terminals from hAPP expressing neurons is a prominent feature of AD pathophysiology in 5xFAD mice. In addition, accumulation of hAPP and reporter proteins in extracellular aggregates provides a secondary measure to track neurodegeneration of identified populations of neurons in these mice.

A persistent increase in gut permeability correlates with emotional dysregulation following maternal separation in male and female mice.
Early life stress (ELS) can significantly influence vulnerability to the development of psychiatric disorders in adulthood. One of the most widely used preclinical models for investigating ELS is maternal separation with early weaning (MSEW), which mimics early-life neglect. The objective of this study was to evaluate the impact of ELS induced by MSEW on the emotional behaviour of male and female mice, as well as its relationship with intestinal permeability and neuroinflammatory markers in the hippocampus. Our results show that MSEW leads to increased anxiety-like behaviours in the adulthood, particularly in females, and exacerbates depression-like behaviours and anhedonia in both sexes. Notably, increased intestinal permeability was observed, which correlated with higher anxiety and depression-like responses, suggesting that gut health plays a crucial role in emotional regulation. These alterations in intestinal permeability were long-lasting, indicating persistent effects on gut function following ELS. Additionally, we observed that MSEW animals showed higher BDNF expression in the hippocampus, particularly in males. However, we did not find significant differences in the long-term survival of adult-born hippocampal cells, as measured by BrdU+ labeling. Furthermore, upon exposure to MSEW, both sexes showed increased NF-{kappa}B protein levels. However, only MSEW male mice exhibited changes in TNF- and BDNF levels, suggesting a sex-specific regulatory mechanism in response to chronic stress. The novel contribution of this study is its exploration of intestinal permeability as a mechanism linking ELS to emotional and behavioural dysregulation, particularly anxiety and depression. By showing a long-lasting increase in intestinal permeability and its correlation with mood disorders, our study extends the gut-brain axis hypothesis to ELS. Additionally, the inclusion of both male and female mice offers a more comprehensive understanding of the sex-specific effects of early stress, often overlooked in other studies. These findings suggest that intestinal permeability could serve as a biomarker for stress-related psychiatric conditions.

Cell-to-cell signalling mediated via CO2: activity dependent CO2 production in the axonal node opens Cx32 in the Schwann cell paranode.
Loss of function mutations of Cx32, which is expressed in Schwann cells, cause X-linked Charcot Marie Tooth disease, a slowly progressive peripheral neuropathy. Cx32 is thus essential for the maintenance of myelin. During action potential propagation, Cx32 hemichannels in the Schwann cell paranode are thought to open and release ATP. As Cx32 hemichannels are directly sensitive to CO2, we have tested whether CO2 produced in the axonal node, as a consequence of the energetic demands of action potential propagation, might gate Cx32 hemichannels. Using isolated sciatic nerve from the mouse, we have shown that the critical components required for intercellular CO2 signalling are present (nodal mitochondria, the source of CO2; a CO2-permeable aquaporin, AQP1; paranodal Cx32; and carbonic anhydrase). We have used a membrane impermeant fluorescent dye FITC, which can permeate Cx32 hemichannels, to demonstrate the opening of Cx32 in Schwann cells in response to an external CO2 stimulus or during action potential propagation in the isolated nerve. Pharmacological blockade of APQ1 or allosteric enhancement of carbonic anhydrase activity greatly reduced Cx32 gating during action potential firing. By contrast, inhibition of carbonic anhydrase with acetazolamide greatly increased Cx32 gating. Cx32 gating was unaffected by the G-protein blocker GDP{beta}S, indicating that it was not mediated by G protein coupled receptors. This CO2-dependent opening of Cx32 also mediates an activity dependent Ca2+ influx into the paranode and, by increasing the leak current across the myelin sheath, slows the conduction velocity. Our data demonstrate that CO2 can act via connexins to mediate neuron-to-glia signalling and that CO2 permeable aquaporins and carbonic anhydrase are key components of this signalling mechanism.

Associations between fluid biomarkers and PET imaging (UCB-J) of synaptic pathology in Alzheimer's disease
INTRODUCTION: Positron Emission Tomography (PET) imaging with ligands for synaptic vesicle glycoprotein 2A (SV2A) has emerged as a promising methodology for measuring synaptic density in Alzheimer's disease (AD). We investigate the relationship between SV2A PET and CSF synaptic protein changes of AD patients. METHOD: Twenty-one participants with early AD and 7 cognitively normal (CN) individuals underwent [11C]UCB-J PET. We used mass spectrometry to measure a panel of synaptic proteins in CSF. RESULTS: In the AD group, higher levels of syntaxin-7 and PEBP-1 were associated with lower global synaptic density. In the total sample, lower global synaptic density was associated with higher levels of AP2B1, neurogranin, beta;-synuclein, GDI-1, PEBP-1, syntaxin-1B, and syntaxin-7 but not with the levels of the neuronal pentraxins or 14-3-3 zeta/delta. CONCLUSION: Reductions of synaptic density found in AD compared to CN participants using [11C]UCB-J PET were observed to be associated with CSF biomarker levels of synaptic proteins.

Functional synaptic connectivity of engrafted spinal cord neurons with locomotor circuitry in the injured spinal cord
Spinal cord injury (SCI) results in significant neurological deficits, with no currently available curative therapies. Neural progenitor cell (NPC) transplantation has emerged as a promising approach for neural repair, as graft-derived neurons (GNs) can integrate into the host spinal cord and support axon regeneration. However, the mechanisms underlying functional recovery remain poorly understood. In this study, we investigate the synaptic integration of NPC-derived neurons into locomotor circuits, the projection patterns of distinct neuronal subtypes, and their potential to modulate motor circuit activity. Using transsynaptic tracing in a mouse thoracic contusion SCI model, we found that NPC-derived neurons form synaptic connections with host locomotor circuits, albeit at low frequencies. Furthermore, we mapped the axon projections of V0C and V2a interneurons, revealing distinct termination patterns within host spinal cord laminae. To assess functional integration, we employed chemogenetic activation of GNs, which induced muscle activity in a subset of transplanted animals. However, NPC transplantation alone did not significantly improve locomotor recovery, highlighting a key challenge in the field. Our findings suggest that while GNs can integrate into host circuits and modulate motor activity, synaptic connectivity remains a limiting factor in functional recovery. Future studies should focus on enhancing graft-host connectivity and optimizing transplantation strategies to maximize therapeutic benefits for SCI.

An engine for systematic discovery of cause-effect relationships between brain structure and function
Characterising how perturbations of brain architecture influence brain function is essential to understand the origins of brain dysfunction, and devise potential avenues of treatment. Here we introduce a computational engine for systematic causal discovery of the functional consequences of altering network architecture and local biophysics in the brain. We integrate multimodal anatomical and functional neuroimaging to implement over 2,000 in-silico brains, and provide mechanistic insight into the functional consequences of local lesions, global wiring, and empirically-derived maps of regional cytoarchitecture and chemoarchitecture. We comprehensively assess how each manipulation of brain macrostructure reshapes spatial and temporal signal coordination, information dynamics, and functional hierarchy - as well as spontaneous co-activation of meta-analytic cognitive circuits, and >6,000 dimensions of local neural dynamics. Our computational model systematically identifies which features of brain architecture have overlapping or antagonistic causal influence over each dimension of brain function, and how functional properties are traded off against each other across disorders and neuromodulation. We find that regions' functional vulnerability to lesions in silico recapitulates their vulnerability to neurodevelopmental and psychiatric in vivo, along a core-periphery organisation. We provide convergent evidence that the brain's wiring diagram is finely tuned to favour the hierarchical integration of information. Notably, our model successfully recapitulates known empirical results that have not been modelled before, including desynchronisation and flattening of the brain's functional hierarchy induced by psychedelic 5HT2A agonists. To catalyse future discoveries, we make this resource freely available to the neuroscience community through an interactive website (https://systematic-causal-mapping.up.railway.app/), where users can interrogate our systematic database of simulated cause-effect relationships. Altogether, we provide a powerful computational engine to predict the functional consequences of experimental or clinical interventions, and drive neuroscientific hypothesis-generation.

A Tonotopic Regulatory Axis Governing Isoform-Specific MYO7A Expression in Cochlear Hair Cells
Myo7a, a gene mutated in Usher syndrome and non-syndromic deafness, encodes an unconventional myosin essential for hair cell function. Our previous work revealed that cochlear hair cells express distinct Myo7a isoforms with distinct spatial and cell type-specific patterns. The canonical isoform (Myo7a-C) and a novel isoform (Myo7a-N) are co-expressed in outer hair cells (OHCs) but exhibit opposing tonotopic gradients, while inner hair cells (IHCs) primarily express Myo7a-C. These isoforms arise from distinct transcriptional start sites, indicating separate regulatory inputs. Here, we identify an intronic cis-regulatory element, EnhancerA, essential for tonotopically graded Myo7a expression. EnhancerA deletion reduces MYO7A protein levels, disrupts hair bundle morphogenesis, alters OHC mechanotransduction, and leads to hair cell degeneration and hearing loss. We further identify SIX2, a tonotopically expressed transcription factor that may interact with EnhancerA to regulate Myo7a-N in OHCs. These findings define a cis-trans regulatory axis critical for isoform-specific Myo7a expression and cochlear function.

Contribution of S1pr1-featured astrocyte subpopulation to cisplatin-induced neuropathic pain
Chemotherapy-induced peripheral neuropathy accompanied by neuropathic pain (CIPN) is a major neurotoxicity of cisplatin, a platinum-based drug widely used for lung, ovarian, and testicular cancer treatment. CIPN causes drug discontinuation and severely impacts life quality with no FDA-approved interventions. We previously reported that platinum-based drugs increase levels of sphingosine 1-phosphate (S1P) in the spinal cord and drive CIPN through activating the S1P receptor subtype 1 (S1PR1). However, the mechanisms engaged downstream of S1PR1 remain poorly understood. Using single cell transcriptomics on mouse spinal cord, our findings uncovered subpopulation-specific responses to cisplatin associated with CIPN. Particularly, cisplatin increased the proportion of astrocytes with high expression levels of S1pr1 (S1pr1high astrocytes), specific to which a Wnt signaling pathway was identified. To this end, several genes involved in Wnt signaling, such as the fibroblast growth factor receptor 3 gene (Fgfr3), were highly expressed in S1pr1high astrocytes. The functional S1PR1 antagonist, ozanimod, prevented cisplatin-induced neuropathic pain and astrocytic upregulation of the Wnt signaling pathway genes. FGFR3 belongs to the FGF/FGFR family which often signals to activate Wnt signaling. Intrathecal injection of the FGFR3 antagonist, PD173074, prevented CIPN. These data not only highlight FGFR3 as one of the astrocytic targets of S1PR1 but raise the possibility that S1PR1-induced engagement of Wnt signaling in S1pr1high astrocytes may contribute to CIPN. Overall, our results provide a comprehensive mapping of cellular and molecular changes engaged in cisplatin-induced neuropathic pain and decipher novel S1PR1-based mechanisms of action.

Modeling dynamic inflow effects in fMRI to quantify cerebrospinal fluid flow
Cerebrospinal fluid (CSF) flow in the brain is tightly regulated and essential for brain health, and imaging techniques are needed to quantitatively establish the properties of this flow system. Flow-sensitive fMRI has recently emerged as a tool to measure large scale CSF flow dynamics with high sensitivity and temporal resolution; however, the measured signal is not quantitative. Here, we developed a dynamic model to simulate and infer time varying flow velocities from fMRI data. We validated the model in both human and phantom data, and used it to identify important properties of the fMRI inflow signal that inform how the signal should be interpreted. Additionally, we developed a physics-based deep learning framework to invert the model, which enables direct estimation of velocity using fMRI inflow data. This work allows new quantitative information to be obtained from fMRI, which will enable neuroimaging researchers to take advantage of the high sensitivity, high temporal resolution, and wide availability of fMRI to obtain flow signals that are physically interpretable.

PrPC-induced signaling in human neurons activates phospholipase Cγ1 and an Arc/Arg3.1 response
Synaptic dysfunction and loss correlate with cognitive decline in neurodegenerative diseases, including Alzheimer disease (AD) and prion disease. Neuronal hyperexcitability occurs in the early stages of AD and experimental prion disease, prior to the onset of dementia, yet the underlying drivers are unclear. Here we identify an increase in the immediate early gene, Arc/Arg3.1, in the human prion disease-affected frontal cortex, suggestive of neuronal hyperactivity. To investigate early signaling events initiated by prion aggregates (PrPSc) in human neurons, we stimulated PrPC in human iPSC-derived excitatory neurons (iNs) with a known PrPSc-mimetic antibody (POM1), which recapitulated the Arc/Arg3.1 response within two hours. Proteomics, RNAseq, and a phosphokinase array in iNs revealed alterations in the EGF receptor and increased phosphorylated phospholipase C (PLC)-{gamma}1 (Y783), which was also observed in the cerebral cortex of prion-infected mice. Thus, PrPC ligands can induce a PLC-{gamma}1 intracellular signaling cascade together with an Arc response, mimicking a neuronal activity response.

The Arousal-Regulated Filter: Modulating Feedforward and Recurrent Dynamics for Adaptive Neural Tracking
Classic behavioral studies have identified an inverted-U relationship between arousal and performance, while neurophysiology studies have shown that the arousal-related neuromodulator norepinephrine (NE) increases the signal-to-noise ratio (SNR) of neural responses to extrinsic inputs. More recently, abstract computational models suggest that arousal signals uncertainty in predictive internal models and increases the influence of new observations. Here, I present the arousal-regulated filter (ARF), a novel computational model of neural state estimation designed to bridge abstract algorithms, behavioral findings, and basic neural mechanisms. According to the ARF, arousal selectively amplifies feedforward synapses relative to recurrent synapses, consistent with findings from neurophysiology. Computationally, the ARF integrates predictions of an internal model, implemented in recurrent connections, with extrinsic observations, relayed by feedforward projections, to adaptively track dynamic systems. The ARF resembles a Kalman filter but replaces dynamic updating of the Kalman gain matrix with modulation of a scalar gain parameter influenced by arousal, and incorporates a potentially nonlinear activation function. Computational simulations demonstrate ARFs versatility across binary, multi-unit categorical, and continuous neural network architectures that track diffusion and drift-diffusion processes. When the internal model is aligned with environmental dynamics, arousal exhibits an inverted-U relationship with accuracy due to a bias-variance tradeoff, consistent with behavioral results. However, when the internal model is misaligned with the true dynamics (i.e. the true state is unpredictable), increased arousal monotonically improves accuracy. Optimal arousal levels vary systematically, being lower in noisy sensory contexts and higher in volatile environments or when unmodeled dynamics exist. Thus, the ARF provides a unifying framework that links abstract computational algorithms, behavioral phenomena, and neurophysiological mechanisms. The model also offers potential insights into the computational effects of altered arousal states in mental health conditions, with potential implications for new approaches to assessment and treatment.

Transcriptional downregulation of rhodopsin is associated with desensitization of rods to light-induced damage in a murine model of retinitis pigmentosa.
Class I rhodopsin mutations are known for some of the most severe forms of vision impairments in dominantly inherited rhodopsin retinitis pigmentosa. They disrupt the VxPx transport signal, which is required for the proper localization of rhodopsin to the outer segments. While various studies have focused on the light-dependent toxicity of mutant rhodopsin, it remains unclear whether and how these mutations exert dominant-negative effects. Using the class I RhoQ344X rhodopsin knock-in mouse model, we characterized the expression of rhodopsin and other genes by RNA sequencing and qPCR. Those studies indicated that rhodopsin is the most prominently downregulated photoreceptor-specific gene in RhoQ344X/+ mice. Rhodopsin is downregulated significantly prior to the onset of rod degeneration, whereas downregulation of other phototransduction genes, transducin, and Pde6, occurs after the onset and correlate with the degree of rod cell loss. Those studies indicated that the mutant rhodopsin gene causes downregulation of wild-type rhodopsin, imposing an mRNA-level dominant negative effect. Moreover, it causes downregulation of the mutant mRNA itself, mitigating the toxicity. The observed dominant effect is likely common among rhodopsin retinitis pigmentosa as we found a similar rhodopsin downregulation in the major class II rhodopsin mutant model, RhoP23H/+ mice, in which mutant rhodopsin is prone to misfold. Potentially due to mitigated toxicity by reduced rhodopsin expression, RhoQ344X/+ mice did not exhibit light-dependent exacerbation of rod degeneration, even after continuous exposure of mice for 5 days at 3000 lux. Thus, this study describes a novel form of dominant negative effect in inherited neurodegenerative disorders.

Listening to the room: disrupting activity of dorsolateral prefrontal cortex impairs learning of room acoustics in human listeners
Navigating complex sensory environments is critical to survival, and brain mechanisms have evolved to cope with the wide range of surroundings we encounter. To determine how listeners learn the statistical properties of acoustic spaces, we assessed their ability to perceive speech in a range of noisy and reverberant rooms. Listeners were also exposed to repetitive transcranial stimulation (rTMS) to disrupt the dorsolateral prefrontal cortex (dlPFC) activity, a region believed to play a role in statistical learning. Our data suggest listeners rapidly adapt to statistical characteristics of an environment to improve speech understanding. This ability is impaired when rTMS is applied bilaterally to the dlPFC. The data demonstrate that speech understanding in noise is best when exposed to a room with reverberant characteristics common to human-built environments, with performance declining for higher and lower reverberation times, including fully anechoic (non-reverberant) environments. Our findings provide evidence for a reverberation-sweet-spot and the presence of brain mechanisms that might have evolved to cope with the acoustic characteristics of listening environments encountered every day.

Neuronal expression of S100B triggered by oligomeric Aβ peptide protects against cytoskeletal damage and synaptic loss
Alzheimer's disease (AD) is a complex neurodegenerative disorder characterized by the intracellular deposition of Tau protein and extracellular deposition of amyloid-{beta} peptide (A{beta}). AD is also characterized by neuroinflammation and synapse loss, among others. The S100 family is a group of calcium-binding proteins with intra- and extracellular functions, that are important modulators of inflammatory responses. S100B, which is upregulated in AD patients and the most abundant member of this family, was shown to inhibit in vitro the aggregation and toxicity of A{beta}42, acting as a neuroprotective holdase-type chaperone. Although S100B is primarily produced by astrocytes, it is also expressed by various cells, including neurons. In this work, we investigated if S100B neuronal expression is triggered as a response to A{beta} toxic species, to provide protection during disease progression. We used the AD mouse model A{beta}PPswe/PS1A246E to show that neuronal S100B levels are significantly higher in 10-month-old animals, and cellular assays to demonstrate that A{beta} oligomers significantly increase S100B expression in SH-SY5Y cells, but not monomeric or fibrillar A{beta}. Using primary cultures of rat hippocampal neurons, we showed that S100B partially reverts A{beta}-induced cofilin-actin rods (synapse disruptors), and rescues the decrease in active synapses and post- (PSD-95) synaptic marker, imposed by A{beta} peptide. Altogether, these findings establish the neuroprotective activity of S100B in response to proteotoxic stress in cells, highlighting its chaperone function as a crucial factor in understanding proteostasis regulation in the diseased brain and identifying potential therapeutic targets.

Ethologically relevant behavioural assay for investigating reach and grasp kinematics during whole-body motor control in mice
Reach and grasp are critical components of skilled mammalian motor control and their detailed analysis in rodents has been key to deepening our understanding of prehension in the context of health and disease. However, most studies investigating these behaviours focus on isolating forelimb movements with little regard to the whole-body movements that are key for effective behaviour. To address this issue, we designed a novel behavioural approach to investigate reach and grasp during whole-body, vertical locomotion in mice. Using a customizable transparent climbing surface, we show that our behavioural approach can extract key kinematic features of climbing. Mouse climbing gait reflects aspects of quadrupedal locomotion, showing similar phase dependencies on increasing speed, including reduced stance (i.e. grasp) time and duty factor. Analysis of multi-limb coordination indicated that climbing revolves around anti-phasic forepaw movements with less consistency in interlimb coordination in the hindpaws. Fore- and hindpaws also differed in their reach trajectories and velocity profiles. The flexibility of this approach also allows for tailored climbing configurations, which we use to show that mice can adapt to and overcome vertical obstacles. By leveraging naturalistic climbing, our modular behavioural approach enables investigation of complex prehensile behaviours and facilitates new study into the neural circuits underlying whole-body skilled motor control.

Reverse Double-Dipping: When Data Dips You, Twice--Stimulus-Driven Information Leakage in Naturalistic Neuroimaging
This article elucidates a methodological pitfall of cross-validation for evaluating predictive models applied to naturalistic neuroimaging data--namely, 'reverse double-dipping' (RDD). In a broader context, this problem is also known as 'leakage in training examples', which poses challenges in detecting it in practice. This issue can occur when predictive modeling is employed with data from a conventional neuroscientific design, characterized by a limited set of stimuli repeated across trials and/or participants, resulting in spurious predictive performances due to overfitting to repeated signals, even in the presence of independent noise. Through comprehensive simulations and real-world examples following theoretical formulation, the article underscores how such information leakage can occur and how severely it could compromise the analysis when it is combined with widely spread informal reverse inference. The article concludes with practical recommendations for researchers to avoid RDD in their experiment design and analysis.

Unbiased Population-Based Statistics to Obtain Pathologic Burden of Injury after Experimental TBI
Reproducibility of scientific data is a current concern throughout the neuroscience field. There are multiple on-going efforts to help resolve this problem. Within the preclinical neuroimaging field, the continued use of a region-of interest (ROI) type approaches combined with the well-known spatial heterogeneity of traumatic brain injury pathology is a barrier to the replicability and repeatability of data. Here we propose the conjoint use of an unbiased analysis of the whole brain after injury together with a population-based statistical analysis of sham-control brains as one approach that has been used in clinical research to help resolve this issue. The approach produces two volumes of pathology that are outside the normal range of sham brains, and can be interpreted as whole brain burden of injury. Using diffusion weighted imaging derived scalars from a tensor analysis of data acquired from adult, male rats at 2, 9 days, 1 and 5 months after lateral fluid percussion injury (LFPI) and in shams (n=73 and 12, respectively), we compared a data-driven, z-score mapping method to a whole brain and white matter-specific analysis, as well as an ROI-based analysis with brain regions preselected by virtue of their large group effect sizes. We show that the data-driven approach is statistically robust, providing the advantage of a large group effect size typical of a ROI analysis of mean scalar values derived from the tensor in regions of gross injury, but without the large multi-region statistical correction required for interrogating multiple brain areas, and without the potential bias inherent with using preselected ROIs. We show that the technique correctly captures the expected longitudinal time-course of the diffusion scalar volumes based on the spatial extent of the pathology and the known temporal changes in scalar values in the LFPI model.

Loudness and sound category: Their distinct roles in shaping perceptual and physiological responses to soundscapes
When compared to nature sounds, exposure to mechanical sounds evokes higher levels of perceptual and physiological arousal, prompting the recruitment of attentional and physiological resources to elicit adaptive responses. However, it is unclear whether these attributes are solely related to the sound intensity of mechanical sounds, since in most real-world scenarios, mechanical sounds are present at high intensities, or if other acoustic or semantic factors are also at play. We measured the Skin Conductance Response (SCR), reflecting sympathetic nervous system (SNS) activity as well as the pleasantness and eventfulness of the soundscape across two passive and active listening tasks in (N = 25) healthy subjects. The auditory stimuli were divided into two categories, nature, and mechanical sounds, and were manipulated to vary in three perceived loudness levels. As expected, we found that the sound category influenced perceived soundscape pleasantness and eventfulness. SCR was analysed by taking the mean level across the stimulus epoch, and also by quantifying its dynamic. We found that mean SCR was modulated by loudness only. SCR rise-time (a measure of speed of the skin response) correlated significantly with soundscape pleasantness and eventfulness for nature and mechanical sounds. This study highlights the importance of considering both loudness level and sound category in evaluating the perceptual soundscape, highlighting SCR as a valuable tool for such assessments.

Large-scale 3D EM connectomics dataset of mouse hippocampal area CA1
The hippocampal formation is thought to be crucial for memory and learning, with subarea cornu ammonis 1 (CA1) considered to play a major role in spatial and episodic memory formation, and for evaluating the match between retrieved memories and current sensory information. While enormous progress has been made in classifying CA1 neurons based on molecular, morphological, and functional properties, and in identifying their role in behavioral tasks, a clear understanding of the underlying circuits is still missing. Here, we present the first large-scale three dimensional (3D) electron microscopy dataset of mouse CA1 at nanometer-scale resolution. The dataset is available online and can be readily used for circuit reconstructions, as demonstrated for inputs to CA1 superficial layers. Example volume segmentations show that automated reconstruction detection is feasible. Using these data, we find evidence against the long-held assumption of a homogeneous pyramidal cell population. Furthermore we find substantial possibly long-range axonal innervation of stratum- lacunosum interneurons, suggested previously to originate in L2 of MEC. These first analyses illustrate the usability of this dataset for finally clarifying the connectomic properties of mouse CA1, a key structure in mammalian brains.

Cortical markers of PAS-induced long-term potentiation and depression in the motor system: A TMS-EEG Registered Report
Paired associative stimulation (PAS), a neurostimulation protocol combining transcranial magnetic stimulation (TMS) pulses to the primary motor cortex (M1) with electrical median nerve stimulation, may promote synaptic plasticity (long-term potentiation - LTP, long-term depression - LTD) in the motor system. To date, PAS effects have been mainly investigated at the corticospinal level in the human motor system. In the present Registered Report, we leveraged TMS and electroencephalography (TMS-EEG) co-registration to track the cortical dynamics related to M1-PAS, aiming to characterize the neurophysiological substrates better, grounding the effectiveness of such protocol. In two within-subject sessions, 30 healthy participants underwent the standard M1-PAS protocols inducing LTP (PASLTP) and LTD (PASLTD) while measuring motor-evoked potentials (MEPs) and TMS-evoked potentials (TEPs) from M1 stimulation before, immediately after, and 30 minutes from the end of the PAS, applied both at supra- (i.e., 110%) and sub- (i.e., 90%) resting motor threshold intensities. Besides replicating MEPs enhancement and inhibition after PASLTP and PASLTD, our results showed that the P30 and N100 M1-TEPs components were significantly modulated immediately following PASLTP and PASLTD administration. These effects were detectable only in suprathreshold conditions, suggesting that M1 subthreshold stimulation could not be optimal for tracking cortical effects of PAS. Furthermore, exploratory analyses showed that P60 amplitude at baseline successfully predicted the magnitude of P30 modulations after PASLTP administration. Our findings provide compelling evidence about the specificity of early TEP components in reflecting changes in M1 reactivity underpinning PAS effects. From a broader perspective, our study fosters evidence about using TMS-EEG biomarkers to track complex plastic changes induced in the human brain, exploiting neuromodulatory non-invasive brain stimulation protocols based on associative mechanisms, like PAS.

A mechanism linking dopamine's roles in reinforcement, movement and motivation
Dopamine neurons (DANs) play seemingly distinct roles in reinforcement, motivation, and movement, and DA-modulating therapies relieve symptoms across a puzzling spectrum of neurologic and psychiatric symptoms. Yet, the mechanistic relationship among these roles is unknown. Here, we show DA's tripartite roles are causally linked by a process in which phasic striatal DA rapidly and persistently recalibrates the propensity to move, a measure of vigor. Using a self-timed movement task, we found that single exposures to reward-related DA transients (both endogenous and exogenously-induced) exerted one-shot updates to movement timing--but in a surprising fashion. Rather than reinforce specific movement times, DA transients quantitatively changed movement timing on the next trial, with larger transients leading to earlier movements (and smaller to later), consistent with a stochastic search process that calibrates the frequency of movement. Both abrupt and gradual changes in external and internal contingencies--such as timing criterion, reward content, and satiety state--caused changes to the amplitude of DA transients that causally altered movement timing. The rapidity and bidirectionality of the one-shot effects are difficult to reconcile with gradual synaptic plasticity, and instead point to more flexible cellular mechanisms, such as DA-dependent modulation of neuronal excitability. Our findings shed light on how natural reinforcement, as well as DA-related disorders such as Parkinson's disease, could affect behavioral vigor.

Theoretical physical color gamuts define luminosity and naturalness perceptual limits in natural scenes
Realism in augmented reality (AR) hinges on the seamless blending of virtual elements into real-world environments. One possible factor influencing this realism may be the physical gamut: an internal representation of all perceivable colors within a natural scene. Previous studies on luminosity thresholds suggest that this gamut, rooted in optimal colors theory, constrains perceptual judgments. While promising, such findings were based on abstract and two-dimensional stimuli only. Before extending this framework to more realistic AR scenarios, an essential next step is to assess whether the physical gamut theory also applies to naturalistic stimuli. This study addresses that gap. Our results reveal that the physical gamut remains a valid construct for natural objects viewed in realistic scenes. Moreover, observers' judgments of luminosity thresholds appear guided not only by a criterion of self-luminosity, but also by an implicit sense of naturalness. These insights pave the way for exploring AR realism through the lens of physical gamut theory.

A transcriptomic comparison of the HD10.6 human sensory neuron-derived cell line with primary and iPSC sensory neurons
A key concern in early-stage analgesic discovery efforts is the extent to which mechanisms identified in rodents will translate to humans. To evaluate an alternative approach to the use of rodent dissociated DRG neurons for in vitro analyses of nociceptive signaling, we performed a transcriptomic analysis of the HD10.6 human dorsal root ganglion (DRG)-derived immortalized cell line. We conducted RNA-seq on proliferating and mature HD10.6 cells to characterize transcriptional changes associated with maturation. We then compared the transcriptomes of HD10.6 cells and several recently developed lines of human induced pluripotent stem cell-derived sensory neurons (iPSC-SN) to single-nucleus RNA-seq data from human DRGs. HD10.6 cells showed the highest correlation with 3 human sensory neuron subtypes associated with nociception and pruriception. Each of the iPSC-SN lines evaluated showed a distinct pattern of correlation with human sensory neuron subtypes. We identified G protein-coupled receptors (GPCRs) and ion channels that are expressed in both HD10.6 cells and human DRG neurons, as well as numerous genes that are expressed in human DRG but not in rodent, underscoring the need for human sensory neuron in vitro models. Proof-of-concept evaluations of protein kinase A, protein kinase C and Erk signaling provide examples of scalable assays using HD10.6 cells to investigate well-established GPCR signaling pathways. We conclude that HD10.6 cells provide a versatile model for exploring human neuronal signaling mechanisms.

The Mismatch Negativity compared: EEG, SQUID-MEG and novel 4Helium-OPMs
Magneto-encephalography (MEG) provides a higher spatial resolution than electro-encephalography (EEG) to measure human auditory responses. However, conventional cryogenic MEG systems (SQUID-MEG) suffer from severe technological restrictions limiting, for instance, routine clinical use. Fortunately, a new generation of MEG sensors, optically pumped magnetometers (OPMs), have been developed to bridge the gap, combining the wearability of EEG with the benefits of MEG signal acquisition. We aim to assess their potential for studying auditory mismatch processing. The auditory Mismatch Negativity (MMN) is a well-characterized evoked component observable using a passive oddball paradigm with two-tone sound sequences. It has been extensively described using both EEG and MEG and is part of many EEG-based clinical applications, such as the assessment of patients with disorders of consciousness. MMN is therefore a relevant candidate to evaluate OPM performance. We use recently developed Helium-OPMs, which are high dynamic range MEG sensors that operate at room temperature. We compare their performance with cryogenic SQUID-MEG and EEG in a passive frequency oddball paradigm. Results show a significant MMN across subjects in all modalities as well as a high temporal similarity between modalities. Signal-to-noise ratios were also similar, and detection of significant individual MMN (within-subjects) using the OPM system was equal or better than EEG. Given that the OPM system tested here is a prototype comprised of only five sensors, these results are a promising step towards wearable MEG that combines the advantages of MEG and EEG.

Context modulates brain state dynamics and behavioral responses during narrative comprehension
Narrative comprehension is inherently context-sensitive, yet the brain and cognitive mechanisms by which brief contextual priming shapes story interpretation remain unclear. Using hidden Markov modeling (HMM) of fMRI data, we identified dynamic brain states as participants listened to an ambiguous spoken story under two distinct narrative contexts (affair vs. paranoia). We uncovered both context-invariant states, engaging auditory, language, and default mode networks, and context-specific states characterized by differential recruitment of control, salience, and visual networks. Narrative context selectively modulated the influence of character speech and linguistic features on brain state expression, with the central character's speech enhancing activation in shared states but suppressing activation in context-specific ones. Independent behavioral analyses revealed parallel context-dependent effects, with character-driven features exerting strong, selectively modulated influences on participants' judgments of narrative evidence. These findings demonstrate that brief narrative priming actively reshapes brain state dynamics and feature sensitivity during story comprehension, revealing how context guides moment-by-moment interpretive processing in naturalistic settings.