bioRxiv Subject Collection: Neuroscience's Journal

Neural Dynamics of Object Manifold Alignment in the Ventral Stream
Visual neurons respond across a vast landscape of images, comprising objects, textures, and places. Natural images can be parameterized using deep generative networks, raising the question of whether latent factors learned by some networks control images in ways that better align with visual neurons. We studied neurons in areas V1, V4 and posterior IT, optimizing images using a closed-loop evolutionary algorithm. We used two generative image models: (1) DeePSim, which parameterizes local image patterns, and (2) BigGAN which parameterizes object identity and nuisance variables. We found that neurons could guide image optimization on both pattern- and object-based image manifolds across areas; V1 aligned best with the DeePSim image space, whereas PIT aligned well with both DeePSim and BigGAN spaces. While initially PIT neurons responded well to the textural manifold, their responses to objects also emerged over time, suggesting that object-like responses required further processing. We identified similar local features common to both textural and object images, but not optimal global configuration. We conclude that visual cortex neurons are aligned to a representational space not yet captured by current artificial model of the visual system.

Sliding window functional connectivity inference with nonstationary autocorrelations and cross-correlations
Functional connectivity (FC) is the degree of synchrony of time series between distinct, spatially separated brain regions. While traditional FC analysis assumes the temporal stationarity throughout a brain scan, there is growing recognition that connectivity can change over time and is not stationary, leading to the concept of dynamic FC (dFC). Resting-state functional magnetic resonance imaging (fMRI) can assess dFC using the sliding window method with the correlation analysis of fMRI signals. Accurate statistical inference of sliding window correlation must consider the autocorrelated nature of the time series. Currently, the dynamic consideration is mainly confined to the point estimation of sliding window correlations. Using in vivo resting-state fMRI data, we first demonstrate the non-stationarity in both the cross-correlation function (XCF) and the autocorrelation function (ACF). Then, we propose the variance estimation of the sliding window correlation considering the nonstationary of XCF and ACF. This approach provides a means to dynamically estimate confidence intervals in assessing dynamic connectivity. Using simulations, we compare the performance of the proposed method with other methods, showing the impact of dynamic ACF and XCF on connectivity inference. Accurate variance estimation can help in addressing the critical issue of false positivity and negativity.

Common and unique neurophysiological signatures for the stopping and revising of actions reveal the temporal dynamics of inhibitory control
Inhibitory control is a crucial cognitive-control ability for behavioral flexibility that has been extensively investigated through action-stopping tasks. Multiple neurophysiological features have been proposed to represent 'signatures' of inhibitory control during action-stopping, though the processes signified by these signatures are still controversially discussed. The present study aimed to disentangle these processes by comparing simple stopping situations with those in which additional action revisions were needed. Three experiments in female and male humans were performed to characterize the neurophysiological dynamics involved in action-stopping and -changing, with hypotheses derived from recently developed two-stage 'pause-then-cancel' models of inhibitory control. Both stopping and revising an action triggered an early broad 'pause'-process, marked by frontal EEG Beta-bursts and non-selective suppression of corticospinal excitability. However, partial-EMG responses showed that motor activity was only partially inhibited by this 'pause', and that this activity can be further modulated during action-revision. In line with two-stage models of inhibitory control, subsequent frontocentral EEG activity after this initial 'pause' selectively scaled depending on the required action revisions, with more activity observed for more complex revisions. This demonstrates the presence of a selective, effector-specific 'retune' phase as the second process involved in action-stopping and -revision. Together, these findings show that inhibitory control is implemented over an extended period of time and in at least two phases. We are further able to align the most commonly proposed neurophysiological signatures to these phases and show that they are differentially modulated by the complexity of action-revision.

Phasic alertness generates urgency and amplifies competition between evidence accumulators
Although phasic alertness generally benefits cognitive performance, it often increases the interference caused by distracting information, resulting in impaired decision-making and cognitive control. However, it is unclear why phasic alertness has these negative effects. Here, we present a novel, biologically-informed account, according to which phasic alertness generates an evidence-independent urgency signal. This urgency signal shortens overall response times, but also amplifies competition between evidence accumulators, thus slowing down decision-making and impairing cognitive control. The key assumptions of this account are supported with pupil measurements and electrophysiological data from human decision-makers performing an arrow flanker task. We also show that a computational model of the flanker task that incorporates time-varying urgency can reproduce the behavioral effects of phasic alertness, but only when the evidence accumulators compete with each other through lateral inhibition. Our results reveal a close interplay between dynamic changes in urgency, cognitive control and evidence accumulation.

Extracting Auditory Emotion in Noise: A distributed auxiliary auditory network supporting affect processing of non-predictably obscured vocalisations
Decoding affect information encoded within a vocally produced signal is a key part of daily communication. The acoustic channels that carry the affect information, however, are not uniformly distributed across a spectrotemporal space meaning that natural listening environments with dynamic, competing noise may unpredictably obscure some spectrotemporal regions of the vocalisation, reducing the potential information available to the listener. In this study, we utilise behavioural and functional MRI investigations to first assess which spectrotemporal regions of a human vocalisation contribute to affect perception in the listener, and then use a reverse-correlation fMRI analysis to see which structures underpin this perceptually challenging task when categorisation relevant acoustic information is unmasked by noise. Our results show that, despite the challenging task and non-uniformity of contributing spectral regions of affective vocalizations, a distributed network of (non-primary auditory) brain regions in the frontal cortex, basal ganglia, and lateral limbic regions supports affect processing in noise. Given the conditions for recruitment and previously established functional contributions of these regions, we propose that this task is underpinned by a reciprocal network between frontal cortical regions and ventral limbic regions that assist in flexible adaptation and tuning to stimuli, while a hippocampal and parahippocampal regions support the auditory systems processing of the degraded auditory information via associative and contextual processing.

Dissociation of novel open loop from ventral putamen to motor areas from classic closed loop in humans II: task-based function
Humans ubiquitously increase the speed of their movements when motivated by incentives (i.e., capturing reward or avoiding loss). The complex interplay between incentivization and motor output is pertinent for unpacking the functional profiles of different circuits that link the basal ganglia with motor cortical areas. Here, we analyzed the functional profile of nodes forming two circuits involving putamen and motor cortical areas: the traditional "closed-loop circuit" (CLC) from sensorimotor dorsal putamen (PUTd) and a putative "open-loop circuit" (OLC) from ventral putamen (PUTv). Establishing differential function between CLC and OLC is particularly relevant for therapeutic approaches to Parkinson's disease, where OLC function is hypothesized to be relatively spared by the disease process. In a large sample fMRI study, 68 healthy controls executed speeded reaches with a joystick under different levels of incentivization to accurately hit precision targets. We dissociated effects of "incentive per se" (i.e., changes in brain activity when an upcoming movement obtains a reward or avoids a loss) from "RT effects" (i.e., brain activity that directly scales with adjustments to movement initiation time). Incentive per se was observed across sites in both CLC and OLC. However, RT effects were primarily in nodes of the OLC and motor sites, consistent with the hypothesized anatomy and function of OLC. Our findings additionally suggest valence might mediate when incentives recruit OLC to more prominent control of motor behavior.

AAV-mediated gene transfer of WDR45 corrects neurologic deficits in the mouse model of beta-propeller protein-associated neurodegeneration
Beta-propeller protein-associated neurodegeneration (BPAN) is an ultra-rare, X-linked dominant, neurodegenerative disease caused by loss-of-function mutations in the WDR45 gene. It manifests in neurodevelopmental delay and seizures followed by secondary neurologic decline with dystonia/parkinsonism and dementia in adolescence and early adulthood and is characterized by progressive accumulation of iron in the basal ganglia. WDR45 encodes {beta}-propeller-shaped scaffold protein, or WIPI4, which plays an important role in autophagosome formation. While the mechanisms of how WIPI4 loss of function results in neurologic decline and brain pathology have not yet been established, findings of lower autophagic activity provide a direct link between impaired autophagy and neurologic disease in BPAN. Here we performed phenotypical characterization of a novel mouse model of BPAN, Wdr45_ex9+1g>a mouse. We identified hyperactive behavior and reduction of autophagy markers in brain tissue in Wdr45_ex9+1g>a hemizygous males as early as at 2 months of age. Given the early onset and spectrum of neurologic symptoms such as hyper-arousal and attention deficits in human patients, this model presents a disease-relevant phenotype and can be used in preclinical studies. We used this mouse model for a proof-of-concept study to evaluate whether AAV-mediated CNS-targeted gene transfer of WDR45 can provide therapeutic benefit and be considered a therapeutic paradigm for BPAN. We observed successful expression of human WDR45 transcripts and WIPI4 protein in the brain tissue, rescue of hyperactive behavior, and correction of autophagy markers in the brain tissue. This data demonstrates that WDR45 gene transfer can be a promising therapeutic strategy for BPAN.

Decoding in the fourth dimension: Classification of temporal patterns and their generalization across locations
Neuroscience research has increasingly used decoding techniques, in which multivariate statistical methods identify patterns in neural data that allow the classification of experimental conditions or participant groups. Typically, the features used for decoding are spatial in nature, including voxel patterns and electrode locations. However, the strength of many neurophysiological recording techniques such as electroencephalography or magnetoencephalography is in their rich temporal, rather than spatial, content. The present report proposes a new decoding method that relies on the time information contained in neural time series. This information is then used in a subsequent step, generalization across location (GAL), which characterizes the relationship between sensor locations based on their ability to cross-decode. Two datasets are used to demonstrate usage of this method, referred to as time-GAL, involving (1) event-related potentials in response to affective pictures and (2) steady-state visual evoked potentials in response to aversively conditioned grating stimuli. In both cases, experimental conditions were successfully decoded based on the temporal features contained in the neural time series. Cross-decoding occurred in regions known to be involved in visual and affective processing. We conclude that the time-GAL approach holds promise for analyzing neural time series from a wide range of paradigms and measurement domains providing an assumption-free method to quantifying differences in temporal patterns of neural information processing and whether these patterns are shared across sensor locations.

The role of liprin-α1 phosphorylation in its liquid-liquid phase separation: regulation by PPP2R5D/PP2A holoenzyme
Liprin-alpha1 is a widely expressed scaffolding protein responsible for regulating cellular processes such as focal adhesion, cell motility, and synaptic transmission. Liprin-alpha1 interacts with many proteins including ELKS, GIT1, liprin-beta, and LAR-family receptor tyrosine protein phosphatase. Through these protein-protein interactions, liprin-alpha1 assemble large higher-order molecular complexes; however, the regulation of this complex assembly/disassembly is unknown. Liquid-liquid phase separation (LLPS) is a process that concentrates proteins within cellular nano-domains to facilitate efficient spatiotemporal signaling in response to signaling cascades. While there is no report that liprin-alpha1 spontaneously undergoes LLPS, we found that GFP-liprin-alpha1 expressed in HEK293 cells occasionally forms droplet-like condensates. MS-based interactomics identified Protein Phosphatase 2A (PP2A)/B56delta (PPP2R5D) trimers as specific interaction partners of liprin-alpha1 through a canonical Short Linear Interaction Motif (SLiM) in its N-terminal dimerization domain. Mutations of this SLiM nearly abolished PP2A interaction and resulted in significantly increased LLPS. GFP-liprin-alpha1 showed significantly increased droplet formation in HEK293 cells devoid of B56delta (PPP2R5D knockout), suggesting that PPP2R5D/PP2A holoenzyme inhibits liprin-alpha1 LLPS. Guided by reported liprin-alpha1 Ser/Thr phosphorylation sites, we found liprin-alpha1 phospho-mimetic mutant at serine 763 (S763E) is sufficient to drive its LLPS. Domain mapping studies of liprin-alpha1 indicated that the intrinsically disordered region, the N-terminal dimerization domain, and the SAM domains are all necessary for liprin-alpha1 LLPS. Finally, expression of p.E420K, a human PPP2R5D variant causing Houge-Janssens Syndrome type 1(also known as Jordan Syndrome), significantly compromised suppression of liprin-alpha1 LLPS. Our work identified B56delta-PP2A holoenzyme as an inhibitor of liprin-alpha LLPS via regulation at multiple phosphorylation sites.

An improved method for sampling and quantitative protein analytics of cerebrospinal fluid of single mice
Mice are the most commonly used preclinical animal model, but protein analytics of murine cerebrospinal fluid (CSF) remains challenging because of low CSF volume (often <10 microL) and frequent blood contaminations. We developed an improved CSF sampling method that allows routine collection of increased volumes (20-30 microL) of pure CSF from individual mice, enabling multiple protein analytical assays from a single sample. Based on cell counts and hemoglobin ELISAs, we provide an easy quality control workflow for obtaining cell- and blood-free murine CSF. Through mass spectrometry-based proteomics using an absolutely quantified external standard, we estimated concentrations for hundreds of mouse CSF proteins. While repeated CSF sampling from the same mouse was possible, it induced CSF proteome changes. Applying the improved method, we found that the mouse CSF proteome remains largely stable over time in wild-type mice, but that amyloid pathology in the 5xFAD mouse model of Alzheimer's disease massively changes the CSF proteome. Neurofilament light chain and TREM2, markers of neurodegeneration and activated microglia, respectively, were strongly upregulated and validated using immunoassays. In conclusion, our refined murine CSF collection method overcomes previous limitations, allowing multiple quantitative protein analyses for applications in biomedicine.

Skull bone marrow-derived immune cells infiltrate the damaged cortex and exhibit anti-inflammatory properties
Identifying the origins and contributions of different immune cell populations following brain injury is crucial for understanding their roles in inflammation and tissue repair. This study investigated the infiltration and phenotypic characteristics of skull bone marrow-derived immune cells in the murine brain after TBI. We performed calvarium transplantation from GFP donor mice and subjected the recipients to controlled cortical impact (CCI) injury 14 days post-transplant. Confocal imaging at 3 days post-CCI revealed GFP+ calvarium-derived cells infiltrating the ipsilateral core lesional area, expressing CD45 and CD11b immune markers. These cells included neutrophil (Ly6G+) and monocyte (Ccr2+) identities. Calvarium-derived GFP+/Iba1+ monocyte/macrophages expressed the efferocytosis receptor MerTK and displayed engulfment of NeuN+ and caspase 3+ apoptotic cells. Phenotypic analysis showed that greater calvarium-derived monocyte/macrophages disproportionately express the anti-inflammatory arginase-1 marker than pro-inflammatory CD86. To differentiate the responses of blood- and calvarium-derived macrophages, we transplanted GFP calvarium skull bone into tdTomato bone marrow chimeric mice, then performed CCI injury 14 days post-transplant. Calvarium-derived GFP+ cells predominantly infiltrated the lesion boundary, while blood-derived TdTomato+ cells dispersed throughout the lesion and peri-lesion. Compared to calvarium-derived cells, more blood-derived cells expressed pro-inflammatory CD86 and displayed altered 3D morphologic traits. These findings uniquely demonstrate that skull bone-derived immune cells infiltrate the brain after injury and contribute to the neuroinflammatory milieu, representing a novel immune cell source that may be further investigated for their causal role in functional outcomes.

Interaction between mitochondrial translocator protein and aging in inflammatory responses in mouse hippocampus
The mitochondrial translocator protein (TSPO) is a biomarker of inflammation which is upregulated in the brain in aging and associated neurodegenerative diseases, such as Alzheimer's disease (AD). Here we investigated the interaction between aging and TSPO immunomodulatory function in mouse hippocampus, a region severely affected in AD. Aging resulted in a reversal of TSPO knockout transcriptional signatures following inflammatory insult, with TSPO deletion drastically exacerbating inflammatory transcriptional responses in the aging hippocampus whilst dampening inflammation in the young hippocampus. Drugs that disrupt cell cycle and induce DNA-damage such as heat shock protein and topoisomerase inhibitors were identified to mimic the inflammatory transcriptional signature characterizing TSPO-dependent aging most closely. This TSPO-aging interaction is an important consideration in the interpretation of TSPO-targeted biomarker and therapeutic studies, as well as in vitro studies which cannot model the aging brain.

Stimulus-specific processing of auditory deviants and repetitive stimulus sequences in the human brainstem
Detecting unexpected events, also known as deviant stimuli, is essential for survival. Research on the neural mechanisms that underlie deviance detection has gained momentum in the last decades. One major discovery from this research is that deviance detection is not limited to high-order cortical areas but is also present in evolutionary older subcortical structures. However, most of the research studying subcortical deviance detection has so far been limited to animal experiments, with studies in humans mostly focussing on cortical effects. It is therefore still mostly unknown how and to what extend deviance detection manifests in the human brainstem. Here, we aimed to tackle this issue by measuring auditory brainstem responses (ABRs) to investigate the earliest correlates of deviance detection in the human brain. We demonstrate that the human brainstem is sensitive to auditory deviants and that the measured effects depend on the carrier frequency of the stimuli. We found the strongest and fastest deviance detection responses when low-frequency chirps occurred as deviants in a context of high-frequency stimuli. A second experiment revealed that the larger deviant ABR amplitudes can be explained by repetition suppression effects of the more frequent standard stimulus. On the contrary, high-frequency chirps did not elicit deviance detection and caused repetition enhancement instead of suppression. These results show that the human auditory brainstem is sensitive to the probability of occurrence of the stimulus and can use different, stimulus-specific processing mechanisms. Our results reveal a previously unknown complexity of advanced auditory signal processing in the human brainstem.

Embracing naturalistic paradigms: substituting GPT predictions for human judgments
Naturalistic paradigms can assure ecological validity and yield novel insights in psychology and neuroscience. However, using behavioral experiments to obtain the human ratings necessary to analyze data collected with these paradigms is usually costly and time-consuming. Large language models like GPT have great potential for predicting human-like behavioral judgments. The current study evaluates the performance of GPT as a substitute for human judgments for affective dynamics in narratives. Our results revealed that GPT's inference of hedonic valence dynamics is highly correlated with human affective perception. Moreover, the inferred neural activity based on GPT derived valence ratings is similar to inferred neural activity based on human judgments, suggesting the potential of using GPT's prediction as a reliable substitute for human judgments.

Noradrenergic tuning of arousal is coupled to coordinatedmovements
Matching arousal level to the motor activity of an animal is important for efficiently allocating cognitive resources and metabolic supply in response to behavioral demands, but how the brain coordinates changes in arousal and wakefulness in response to motor activity remains an unclear phenomenon. We hypothesized that the locus coeruleus (LC), as the primary source of cortical norepinephrine (NE) and promoter of cortical and sympathetic arousal, is well-positioned to mediate movement-arousal coupling. Here, using a combination of physiological recordings, fiber photometry, optogenetics, and behavioral tracking, we show that the LCNE activation is tightly coupled to the return of organized movements during waking from an anesthetized state. Moreover, in an awake animal, movement initiations are coupled to LCNE activation, while movement arrests, to LCNE deactivation. We also report that LCNE activity covaries with the depth of anesthesia and that LCNE photoactivation leads to sympathetic activation, consistent with its role in mediating increased arousal. Together, these studies reveal a more nuanced, modulatory role that LCNE plays in coordinating movement and arousal.

The Retrosplenial Cortical Role in Delayed Spatial Alternation.
The retrosplenial cortex (RSC) plays an important role in spatial cognition. RSC neurons exhibit a variety of spatial firing patterns and lesion studies have found that the RSC is necessary for spatial working memory tasks. However, little is known about how RSC neurons might encode spatial memory during a delay period. In the present study, we trained control rats and rats with excitotoxic lesions of the RSC on spatial alternation task with varying delay durations and in a separate group of rats, we recorded RSC neuronal activity as the rats performed the alternation task. We found that RSC lesions significantly impaired alternation performance, particularly at the longest delay duration. We also found that RSC neurons exhibited reliably different firing patterns throughout the delay periods preceding left and right trials, consistent with a working memory signal. These differential firing patterns were absent during the delay periods preceding errors. We also found that many RSC neurons exhibit a large spike in firing rate leading up to the start of the trial. Many of these trial start responses also differentiated left and right trials, suggesting that they could play a role in priming the 'go left' or 'go right' behavioral responses. Our results suggest that these firing patterns represent critical memory information that underlies the RSC role in spatial working memory.

Acute nicotine vapor normalizes sensorimotor gating and reduces locomotor activity deficits in HIV-1 transgenic rats
Rationale: Despite improved life expectancy of people with HIV (PWH), HIV-associated neurocognitive impairment (NCI) persists, alongside deficits in sensorimotor gating and neuroinflammation. PWH exhibit high smoking rates, possibly due to neuroprotective, anti-inflammatory, and cognitive-enhancing effects of nicotine, suggesting potential self-medication. Objectives: Here, we tested the effects of acute nicotine vapor exposure on translatable measures of sensorimotor gating and exploratory behavior in the HIV-1 transgenic (HIV-1Tg) rat model of HIV. Methods: Male and female HIV-1Tg and F344 control rats (n=57) were exposed to acute nicotine or vehicle vapor. Sensorimotor gating was assessed using prepulse inhibition (PPI) of the acoustic startle response, and exploratory behavior was evaluated using the behavioral pattern monitor (BPM). Results: Vehicle-treated HIV-1Tg rats exhibited PPI deficits at low prepulse intensities compared to F344 controls, as seen previously. No PPI deficits were observed in nicotine-treated HIV-1Tg rats, however. HIV-1Tg rats were hypoactive in the BPM relative to controls, whilst nicotine vapor increased activity and exploratory behavior across genotypes. Cotinine analyses confirmed comparable levels of the primary metabolite of nicotine across genotypes. Conclusions: Previous findings of PPI deficits in HIV-1Tg rats were replicated and, importantly, attenuated by acute nicotine vapor. Evidence for similar cotinine levels suggest a nicotine-specific effect in HIV-1Tg rats. HIV-1Tg rats had reduced exploratory behavior compared to controls, attenuated by acute nicotine vapor. Therefore, acute nicotine may be beneficial for remediating sensorimotor and locomotor activity deficits in PWH. Future studies should determine the long-term effects of nicotine vapor on similar HIV/NCI-relevant behaviors.

Post-encoding administration of oxytocin selectively enhances memory consolidation of male faces in females
Oxytocin plays a critical role in modulating social cognition and enhancing human memory for faces. However, it remains unclear which stage of memory oxytocin affects to enhance face memory. Our study explored oxytocin's potential to selectively enhance the consolidation of social memories, specifically human faces, and whether this effect varies between genders. In two preregistered, randomized, double-blind, placebo-controlled trials with heterosexual participants (total N=294, comprising 149 males and 145 females), we explored how oxytocin affects memory consolidation. We administered oxytocin immediately after encoding (i.e., Study1) and 30 minutes before retrieval in a parallel study (i.e., Study2). This design allowed us to confirm that oxytocin's effects were indeed due to consolidation rather than retrieval. We found that administering oxytocin post-encoding, but not before-retrieval, significantly improved female participants' ability to recognize male faces 24 hours later, with no similar enhancement observed in males recognizing opposite-gender faces. Together with our analyses of social placebo effects and approachability rating during encoding, we concluded that oxytocin enhanced consolidation of long-term social memories in humans. Our results not only advance the understanding of the neurobiological mechanisms underlying social memory consolidation but also highlight oxytocin as a pharmacological tool for selectively enhancing human memory consolidation.

UltraCortex: Submillimeter Ultra-High Field 9.4 T Brain MR Image Collection and Manual Cortical Segmentations
The UltraCortex repository (https:/www.ultracortex.org) houses magnetic resonance imaging data of the human brain obtained at an ultra-high field strength of 9.4 T. It contains 86 structural MR images with spatial resolutions ranging from 0.6 to 0.8 mm. Additionally, the repository includes segmentations of 12 brains into gray and white matter compartments. These segmentations have been independently validated by two expert neuroradiologists, thus establishing them as a reliable gold standard. This resource provides researchers with access to high-quality brain imaging data and validated segmentations, facilitating neuroimaging studies and advancing our understanding of brain structure and function. Existing repositories do not accommodate field strengths beyond 7 T, nor do they offer validated segmentations, underscoring the significance of this new resource.

Mouse models of non-dystrophic and dystrophic myotonia exhibit nociplastic pain-like behaviors
Pain is a prominent and debilitating symptom in myotonic disorders, yet its physiological mechanisms remain poorly understood. This study assessed preclinical pain-like behavior in murine models of pharmacologically induced myotonia and myotonic dystrophy type 1 (DM1). In both myotonia congenita and DM1, impairment of the CLCN1 gene, which encodes skeletal muscle voltage-gated CLC-1 chloride channels, reduces chloride ion conductance in skeletal muscle cells, leading to prolonged muscle excitability and delayed relaxation after contraction. We used the CLC-1 antagonist anthracene-9-carboxylic acid (9-AC) at intraperitoneal doses of 30 or 60 mg/kg and HSA LR20b DM1 mice to model CLC-1-induced myotonia. Our experimental approach included in vivo pain behavioral testing, ex vivo calcium imaging, and whole-cell current-clamp electrophysiology in mouse dorsal root ganglion (DRG) neurons. A single injection of 9-AC induced myotonia in mice, which persisted for several hours and resulted in long-lasting allodynic pain-like behavior. Similarly, HSA LR20b mice exhibited both allodynia and hyperalgesia. Despite these pain-like behaviors, DRG neurons did not show signs of hyperexcitability in either myotonic model. These findings suggest that myotonia induces nociplastic pain-like behavior in preclinical rodents, likely through central sensitization mechanisms rather than peripheral sensitization. This study provides insights into the pathophysiology of pain in myotonic disorders and highlights the potential of using myotonic mouse models to explore pain mechanisms and assess novel analgesics. Future research should focus on the central mechanisms involved in myotonia-induced pain and develop targeted therapies to alleviate this significant clinical burden.

Functionally Adaptive Structural Basis Sets of the Brain: A Dynamic Fusion Approach
The precise relationship between brain structure and dynamic neural function has long been an open area of research, and recently, a topic of much debate. Whether investigated through the lens of interregional white matter connectivity or cortical surface morphology, the common thread that links many studies in this subfield of research is the focus on identifying a singular structural basis set, upon which functional activation signals are reconstructed to define the linkage between structure and function. Such approaches are limited in two respects; first, these basis sets are defined solely upon structural data and ignore the influence of functional coupling entirely, and second, these approaches operate on the somewhat narrow assumption that a single structure-function coupling governs the activity of the whole brain at all times. The first limitation can be addressed with the use of multimodal data fusion, which identifies hidden linkages between structural and functional brain imaging data; however, many multimodal fusion approaches still necessitate functional data to be heavily summarized over the time dimension, resulting in temporally rigid structure-function linkages. Regarding the second limitation, given that functional brain activity and connectivity vary over multiple timescales, it is natural to consider this also might be true of structure-function couplings. Here, we introduce dynamic fusion, implemented as an ICA-based symmetric fusion approach, which enables flexible, time-resolved linkages between structure and function utilizing dynamic functional connectivity (dFNC) states. We show evidence that challenges current claims regarding structural basis sets and suggests that temporally evolving structural basis sets can better reflect dynamic functional manifolds and better capture diagnostically relevant structure-functional coupling than traditionally computed structural bases. Lastly, differential analysis of component stability across repeated scans from a control cohort reveals organization of static and dynamic structure/function coupling falls along unimodal/transmodal hierarchical lines.

Association between Adolescent Brain Morphometry and Cognitive Function: Insights from a Cross-Sectional Analysis of ABCD Data from 9 to 15 Years Old
During the adolescent developmental stage, significant changes occur in both brain structure and cognitive function. Brain structure serves as the foundation for cognitive function and can be accurately assessed using a comprehensive set of brain cortical and subcortical morphometry measures. Exploring the association between whole-brain morphometry and cognitive function during adolescence can help elucidate the underlying relationship between brain structural development and cognitive development. Despite extensive research in this area, previous studies have two main limitations. Firstly, they often use a limited number of brain morphometry measures, which do not provide a comprehensive representation of brain structure. Secondly, most previous studies rely on relatively small sample sizes, increasing the risk of sampling error, low statistical power, and even overestimation of effects. To address these limitations, we analyzed the Adolescent Brain Cognitive Development (ABCD) dataset, which includes 8543 subjects (13,992 scans) aged 9-15 years. These scans were categorized into six groups with one-year intervals based on their ages for independent age-specific analysis. We computed 16 brain regional morphometry measures derived from Structural Magnetic Resonance Imaging (SMRI), Diffusion Tensor Imaging (DTI), and Restriction Spectrum Imaging (RSI), and integrated them with morphometric similarity networks (MSNs). This approach enabled us to compute 16,563 morphometry measures encompassing brain region, connection, and hub aspects. Subsequently, these measures were input into a robust large-scale computational model to investigate their relationship with cognitive performances. We found that brain regions making the most significant contributions to cognitive function during adolescence, and those exhibiting the greatest variability in their contributions over time, were primarily situated in the frontal and temporal lobes. Subcortex were the least involved. We also observed strong correlations between key brain morphometry measures related to different cognitive performances within same domain. Furthermore, SMRI measures demonstrated stronger associations with cognitive performances compared to DTI and RSI measures. Overall, our study aims to facilitate a comprehensive and reliable understanding of the association between adolescent brain morphometry and cognitive function.

Long-term perceptual priors drive confidence bias which favors prior-congruent evidence
Within a Bayesian framework, both our perceptual decisions and confidence about those decisions are based on the precision-weighted integration of prior expectations and incoming sensory information. This assumes priors to influence both decisions and confidence in the same way. Against this assumption, asymmetries have been found in the influence that priors have on confidence compared to discrimination decisions. However, these patterns were found for high-level probabilistic expectations that are flexibly induced in the task context. It remains unclear whether this generalizes to low-level perceptual priors that are naturally formed through long term exposure. Here we investigated human participants confidence in decisions made under the influence of a long-term perceptual prior: the slow-motion prior. Participants viewed moving line stimuli for which the slow-motion prior biases the perceived motion direction. On each trial, they made two consecutive motion direction decisions followed by a confidence decision. We contrasted two conditions - one in which the prior biased perceptual decisions and one in which decisions were driven by the sensory information alone. We found a confidence bias favoring the condition in which the prior influenced decisions, even when accounting for performance differences. Computational modeling revealed this effect to best be explained by confidence using the prior-congruent evidence as an additional cue, beyond the posterior evidence used in the perceptual decision. This suggests a confirmatory confidence bias favoring evidence congruent with low-level perceptual priors, revealing that, in line with high-level expectations, even long-term priors have a particularly strong influence at the metacognitive level.

Spinal interneuron population dynamics underlying flexible pattern generation
The mammalian spinal locomotor network is composed of diverse populations of interneurons that collectively orchestrate and execute a range of locomotor behaviors. Despite the identification of many classes of spinal interneurons constituting the locomotor network, it remains unclear how the networks collective activity computes and modifies locomotor output on a step-by-step basis. To investigate this, we analyzed lumbar interneuron population recordings and multi-muscle electromyography from spinalized cats performing air stepping and used artificial intelligence methods to uncover state space trajectories of spinal interneuron population activity on single step cycles and at millisecond timescales. Our analyses of interneuron population trajectories revealed that traversal of specific state space regions held millisecond-timescale correspondence to the timing adjustments of extensor-flexor alternation. Similarly, we found that small variations in the path of state space trajectories were tightly linked to single-step, microvolt-scale adjustments in the magnitude of muscle output.

One sentence summaryFeatures of spinal interneuron state space trajectories capture variations in the timing and magnitude of muscle activations across individual step cycles, with precision on the scales of milliseconds and microvolts respectively.

Neocortical long-range inhibition promotes cortical synchrony and sleep
Behavioral states such as sleep and wake are highly correlated with specific patterns of rhythmic activity in the cortex. During low arousal states such as slow wave sleep, the cortex is synchronized and dominated by low frequency rhythms coordinated across multiple regions. Although recent evidence suggests that GABAergic inhibitory neurons are key players in cortical state modulation, the in vivo circuit mechanisms coordinating synchronized activity among local and distant neocortical networks are not well understood. Here, we show that somatostatin and chondrolectin co-expressing cells (Sst-Chodl cells), a sparse and unique class of neocortical inhibitory neurons, are selectively active during low arousal states and are largely silent during periods of high arousal. In contrast to other neocortical inhibitory neurons, we show these neurons have long-range axons that project across neocortical areas. Activation of Sst-Chodl cells is sufficient to promote synchronized cortical states characteristic of low arousal, with increased spike co-firing and low frequency brain rhythms, and to alter behavioral states by promoting sleep. Contrary to the prevailing belief that sleep is exclusively driven by subcortical mechanisms, our findings reveal that these long-range inhibitory neurons not only track changes in behavioral state but are sufficient to induce both sleep-like cortical states and sleep behavior, establishing a crucial circuit component in regulating behavioral states.