bioRxiv Subject Collection: Neuroscience's Journal

Connectomics Reveals a Feed-Forward Swallowing Circuit Driving Protein Appetite
Nutrient state shapes not only what animals eat, but how they eat it. In Drosophila, protein deprivation prolongs protein-specific feeding bursts, yet the motor mechanism underlying this change remains unknown. Using EM connectomics, we identified a feed-forward pathway from protein-sensitive gustatory receptor neurons to swallowing motor neurons. At its core is the Sustain neuron, which coordinates multiple swallowing motor neurons to move food efficiently through the cibarium and pharynx. This nutrient-dependent facilitation of swallowing sustains long feeding bursts, directly linking internal state to the temporal structure of feeding. Our findings reveal how a dedicated sensorimotor circuit translates physiological need into precise motor control to drive nutrient specific feeding appetite.

Investigating Neural Correlates of Emotional Regulation as a Function of Age, Race, and Socioeconomic Status
Older adults often show improved emotional regulation with age, a phenomenon known as the aging paradox. This age-related increase in emotional regulation capacity is attributed to enhanced prefrontal cortex control over amygdala reactivity. However, because racial discrimination and economic disadvantage cause chronic stress, typical age-related neural associations may be altered in marginalized groups. Using task-functional MRI data from 8,711 UK Biobank participants aged 50-78, we investigated whether age-related associations in emotion-related brain function, specifically amygdala activation and vmPFC-amygdala connectivity, varied across racial and socioeconomic status (SES) groups. We found that older age was associated with decreased amygdala activation, which is consistent with improved emotional regulation. Yet, lower socioeconomic status was associated with increased amygdala activation, suggesting heightened stress-related reactivity. No significant age-related effects on vmPFC-amygdala connectivity were observed at the population level. Black participants showed a stronger age-related decline in functional connectivity compared to other racial groups. These findings call for more inclusive and diverse neuroimaging studies to better understand brain health across marginalized groups.

Remote magnetomechanical neuromodulation uncovers a novel therapeutic mechanism for alleviating Parkinsonian symptoms in freely moving mice
To overcome the limitations of invasive neuromodulation systems, we introduce a wireless magnetomechanical approach for remote, minimally invasive deep brain stimulation (DBS) without chronically implanted electrodes. This method leverages biocompatible nanoscale magnetite nanodiscs (MNDs) with ground vortex magnetisation, which undergo in-plane transitions under low-frequency alternating magnetic fields, thereby generating localised piconewton-scale torques. These torques engage endogenous mechanosensory pathways to modulate neural activity, enabling reversible stimulation without the need for genetic modifications. Calcium imaging validated the rapid neuromodulatory effects of MNDs in vitro and ex vivo, which motivated the subsequent application of magnetomechanical DBS to the subthalamic nucleus in mice. We demonstrated the remote control of motor behaviour in wild-type mice and significant restoration of motor function in a severe hemiparkinsonian model. This study established the first wireless therapeutic magnetomechanical neuromodulation platform that leverages biocompatible nanomaterials and endogenous mechanosensory ion channels, representing a promising step toward untethered, clinically translatable neurotechnology.

Metformin decreases RAN proteins, rescues splicing abnormalities and improves behavioral phenotypes in SCA8 BAC mice
Spinocerebellar ataxia type 8 is one member of a larger group of dominantly inherited, debilitating neurological diseases caused by CTG*CAG expansions for which there are no effective disease-targeting treatments. RAN translation, which was discovered in SCA8, has previously been shown to occur across CAG and CUG expansion transcripts, making treatments that work for SCA8 potentially relevant to a much broader group of diseases, including SCA1, 2, 3, 6, 7, 12, Huntington's Disease (HD) Fuch's endothelial corneal dystrophy (FECD), and myotonic dystrophy type 1 (DM1). The FDA-approved drug, metformin, has been previously shown to reduce RAN protein levels in cells overexpressing SCA8 CAG repeats. Here we show, using SCA8 BAC transgenic mice, that metformin treatment improves ambulatory performance, including rotarod, DigiGait, and open field measures. At the molecular level, metformin-treated mice show reduced RAN protein levels and improved splicing abnormalities without changing the levels of the expanded RNAs. Metformin-treated mice also show decreased neuroinflammation with reduced levels of astrogliosis and reduced numbers of activated microglia. Taken together, these data provide strong support for testing FDA-approved metformin in clinical trials for SCA8 and potentially the broader group of CAG*CTG repeat expansion disorders.

An emergent disease-associated motor neuron state precedes cell death in a mouse model of ALS
To uncover molecular determinants of motor neuron degeneration and selective vulnerability in amyotrophic lateral sclerosis (ALS), we generated longitudinal single-nucleus transcriptomes and chromatin accessibility profiles of spinal motor neurons from the SOD1-G93A ALS mouse model. Vulnerable alpha motor neurons showed thousands of molecular changes, marking a transition into a novel cell state we named 'disease-associated motor neurons' (DAMNs). We identified transcription factor regulatory networks that govern how healthy cells transition into DAMNs as well as those linked to vulnerable and resistant motor neuron subtypes. Using spatial transcriptomics, we found reactive glia located near motor neurons early in disease, suggesting early signaling events between motor neurons and glia. Finally, we found that the human orthologs of genomic regions with differential accessibility in SOD1-G93A alpha motor neurons are enriched for single nucleotide polymorphisms associated with human ALS, providing evidence that the genetic underpinnings of motor neuron vulnerability are conserved.

AETA peptide drives Alzheimer's disease signature of synapse dysfunction
INTRODUCTION: Alzheimer's disease (AD), the leading cause of dementia, is marked by early synaptic dysfunction preceding cognitive decline. While amyloid-{beta} ; and Tau remain central to AD research, other pathogenic factors are emerging. We investigated AETA, a novel amyloid precursor protein (APP)-derived peptide, as a mediator of synaptic pathology. METHODS: AETA levels were measured in human AD brains, and the AETA-m mouse model expressing secreted human AETA was assessed at molecular, functional, and behavioral levels for AD-like phenotypes. RESULTS: AETA was significantly elevated in AD brains, especially in females. AETA-m mice displayed hippocampal synaptic gene expression patterns resembling vulnerable human AD regions, disrupted NMDA receptor signaling, dendritic spine loss, and mild hippocampal memory impairments, particularly in females, reflecting prodromal AD pathology. DISCUSSION: These findings identify AETA as an additional driver of synaptic dysfunction and suggest its potential as a therapeutic target for early intervention in AD.

Neural voice activity detection with high-gamma ECoG signal correlation structure using a chronically implanted brain-computer interface in an individual with ALS
Chronically implanted brain-computer interfaces (BCIs) for speech decoding hold promise for individuals with severe motor impairment. A key translational challenge to wider adoption is understanding and mitigating long-term neural signal variability. This study evaluated whether correlation-based features of electrocorticographic (ECoG) high-gamma signals (HG-C) provide greater long-term stability and robustness than high-gamma log-power (HGLP) features for neural voice activity detection (NVAD). We analyzed an open-source dataset from Angrick et al. [1] of an individual with amyotrophic lateral sclerosis performing a syllable repetition task. Long short-term memory (LSTM) models were trained on HGLP or HG-C features and evaluated across sessions separated from training by up to six months. Feature importance was estimated with permutation-based marginal effects analysis and robustness was tested by simulated electrode disconnections. HG-C achieved comparable to superior NVAD performance, with reduced temporal degradation (-8% vs. -23% F1 score decline). HG-C models leveraged distributed correlation structure and remained stable under both random and systematic electrode disconnections. These findings support HG-C as a candidate neural signal representation for speech BCIs which require long-term stability and robustness while maintaining ease of use for users and caregivers.

Temporal constraints of conscious tactile perception in the primary somatosensory cortex
The primary somatosensory cortex (S1) has long been implicated in tactile perception, yet its precise role in conscious tactile detection remains uncertain. The current study investigated the causal and time-specific involvement of S1 in tactile detection using single-pulse transcranial magnetic stimulation (spTMS). In two experiments, spTMS was applied over contralateral S1, an active control site (inferior parietal lobe; IPL), or under a sham condition at short (25 & 75 ms; Experiment 1) and longer (130 ms; Experiment 2) intervals following electrotactile stimulation of the finger. Participants performed a go/no-go detection task at sensory threshold. In Experiment 1, tactile sensitivity was significantly reduced following early S1 stimulation compared to both active control and sham conditions. However, no such effect was observed in Experiment 2, indicating a temporally limited role of S1 in conscious detection. Moreover, self-reported TMS-related distraction ratings did not account for the observed sensitivity differences, suggesting sensitivity-specific modulation by early TMS rather than general task disruption. These findings support a causal role for early S1 activity in conscious tactile detection. We propose that disruption at this early stage interferes with the initial encoding of tactile input, thereby attenuating not only immediate perceptual awareness, but also subsequent functions such as discrimination and retention. Overall, the results underscore the constrained role of S1 in conscious stimulus detection and highlight the importance of neural networks beyond S1.

A fast and child-friendly localizer for the identification of ITG-math based on its preference for mathematical processing
The visual number form area (here referred to as ITG-math) has gained recent attention as a neural substrate of mathematical cognition. However, research on this region has been hindered by difficulties identifying it and its precise function hence remains debated. THere we aimed to: 1) Provide an efficient and child-friendly localizer for the region and 2) explore the impact of different tasks and stimuli on its responses. In the developed localizer, participants are presented with digits and UFOs, while performing a 1-back task either on stimulus numerosity or on stimulus color. We collected two sessions of the localizer from 17 healthy adults. From the localizer data, we could identify ITG-math based on higher responses in the numerosity than the color task in 92% of the participants, whereas contrasting digits with UFOs lead to selective responses in only 32% of the participants. Accordingly, in independent data, ITG-math showed a task preference, but no stimulus preference. Multivariate analyses further revealed task encoding, and a combination of task and stimulus encoding, in the left and right ITG-math, respectively. Our work facilitates further research on ITG-math and suggests that the role of ITG-math in mathematical cognition goes beyond the visual encoding of digits.

Determining perception thresholds of young adults to small continuous moving platform perturbations
Detecting external disturbances is vital for maintaining balance, as corrective actions are initiated to prevent falls. Quantifying people's ability to perceive such disturbances improves our understanding of how balance is maintained. This study aims to: 1) quantify healthy young adults' ability to perceive external perturbations while balancing on a stabilometer, and 2) understand the relationship between balance performance and perturbation magnitude relative to participants' perception threshold. Participants (n=22; 20-35 years) completed a multiple staircase protocol. While standing on a stabilometer mounted on a moving platform, they attempted to keep it horizontal during 10-second trials with small continuous perturbations. After each trial, participants were asked whether they perceived the platform movement. Perturbation magnitudes were adjusted for the next trial based on their response. This process continued for each staircase until the termination criteria were met, at which point participants' individual perception threshold was determined. Participants then performed ten 40-second trials on the stabilometer, two trials in each condition: without perturbation, perturbation at the 100%, 80%, and 50% of the individual's perception threshold, and the pilot study's minimum threshold. Balance performance was defined as time-in-balance ratio and RMS deviation angle from horizontal. Perception thresholds varied significantly between participants individuals, with an RMS acceleration ranging from 2.67 and 12.80 cm/s^2. The results showed that perturbation magnitude has a significant correlation with variability in deviation angle (R=0.24, p=0.0038). The results suggest that some participants can perceive very small perturbations during a challenging balance task. Subthreshold perturbations, although very small, can influence balance performance.

Hippocampal theta sweeps indicate goal direction
Successful spatial navigation requires rapid evaluation of potential future trajectories. Hippocampal "theta sweeps", sequential activation of place cells within individual theta cycles, exhibit predictive dynamics within the ideal timeframe to fulfill this role. However, whether these sequences simply reflect movement-related variables or afford more cognitive goal-directed planning remains unresolved. Using data from a navigation task on the "Honeycomb" maze that allows dissociation of head-, movement- and goal-direction correlates, we found that hippocampal theta sweeps exhibit robust goal-oriented directional biases, independent of movement- or head-direction. An existing model of theta sweeps, with an additional goal-oriented directional input, reproduces these findings and predicts goal-oriented theta phase precession, which we confirm empirically. Replay events during immobility-related sharp wave/ripples are also goal-directed, and therefore more aligned with theta sweeps than experience. Our findings indicate that hippocampal theta sweeps provide a neural substrate for online goal-directed spatial planning.

M5 positive allosteric modulation alleviates parkinsonian motor deficits
Parkinsons disease is a neurodegenerative movement disorder which is characterized by cardinal motor symptoms of tremor at rest, rigidity, bradykineasia, and postural instability. Underlying these cardinal motor symptoms is thought to be death and dysfunction of nigrostriatal dopamine neurons, and the gold-standard treatment of Parkinsons disease is dopamine replacement therapy with the dopamine precursor L-DOPA. While efficacious, L-DOPA does not treat all motor symptoms and can have serious treatment-related side effects called L-DOPA induced dyskinesias, indicating an immense need for new targets to modulate dopaminergic function for anti-parkinsonian efficacy. One such potential target is the M5 muscarinic acetylcholine receptor, which has a unique expression profile where it is selectively expressed in midbrain dopaminergic neurons and their terminals in the striatum, and previous studies have indicated that M5 can modulate dopamine release and patterning of firing of dopamine neurons. Given this unique expression profile and function of M5, this receptor has an untested potential to modulate parkinsonian motor phenotypes. To test the potential for M5 to modulate Parkinsonian-like motor deficits and dyskinesia, we employed the unilateral 6-OHDA lesioned mouse model to create a hemi-parkinsonian state. Using multiple behavioral assays, including the cylinder test, forepaw adjusting steps assay, and in the Erasmus ladder, in conjunction with prototypical M5 pharmacological tool compounds, we investigated the ability of M5 to modulate parkinsonian motor deficits. Additionally, we tested the ability of M5 to modulate established L-DOPA induced dyskinesia or cause dyskinesia on its own. Overall, we found that M5 PAM alleviates forepaw asymmetry, bradykinesia, and spatial aspects of gait in the Erasmus ladder. Excitingly, M5 PAM does not cause robust dyskinesia, does not affect already established L-DOPA-induced dyskinesia, and does not affect L-DOPA motor efficacy. Taken together with previous findings, the current study suggests that M5 receptors are an exciting novel therapeutic strategy for ameliorating parkinsonian motor deficits even in late-stage models of severe PD without lessening L-DOPAs motor benefit and without affecting existing symptoms of L-DOPA-induced dyskinesia.

Similar destabilization of neural dynamics under different general anesthetics
Different classes of anesthetics can induce unconsciousness despite acting through distinct biological mechanisms. This raises the possibility that they produce a convergent effect on the dynamics or temporal evolution of neural population activity. To explore this, we analyzed intracortical electrophysiological recordings during infusions of propofol, ketamine, and dexmedetomidine, using a rigorous method to estimate dynamical stability. We found that all three anesthetics, despite their molecular differences, similarly affect cortical states by destabilizing their dynamics. This destabilization matched the slower recovery from sensory perturbations and longer stimulus-induced autocorrelation times observed during the anesthetic infusions. The destabilization was also reflected predominantly in lower-frequency ranges, linking it to the well-known increase in low-frequency power during anesthesia. Finally, destabilization closely tracked real-time fluctuations in consciousness. Together, these findings suggest that cortical destabilization may be a shared neural correlate of anesthetic-induced unconsciousness, offering a mechanistic explanation for low-frequency oscillations observed during anesthesia.

Modeling 3D Mesoscaled Neuronal Complexity through Learning-based Dynamic Morphometric Convolution
Accurate reconstruction of neuronal morphology from three-dimensional (3D) light microscopy is fundamental to neuroscience. Nevertheless, neuronal arbors intrinsically exhibit slender, tortuous geometries with high orientation variability, posing significant challenges for standard 3D convolutions whose static, axis-aligned receptive fields lack adaptability to such complex morphology. To address this, we propose the Dynamic Morph-Aware Convolution (DMAC) framework, which incorporates inherent geometric priors into convolution by jointly adapting both the shape and orientation of the kernel. This enables morphology-aware feature extraction tailored to arborized and variably oriented neuronal trajectories. Specifically, we first apply dynamic tubular convolutions to bridge the structural mismatch between isotropic convolution kernels and the slender morphology of neurons. To sufficiently accommodate the 3D orientation variability of neuronal branches, we further introduce a rotation mechanism that dynamically reorients the tubular kernel via two learnable angles (elevation and azimuth), enabling precise alignment with local neuronal directions. We validate our method through extensive experiments on four mesoscaled neuronal imaging datasets, including two from the BigNeuron project (Drosophila and Mouse) and two additional benchmarks (NeuroFly and CWMBS). Our approach consistently outperforms state-of-the-art methods, achieving average improvements of 5.4% in Entire Structure Average (ESA), 6.9% in Different Structure Average (DSA), and 7.5% in Percentage of Different Structure (PDS). These results demonstrate the effectiveness of our proposed DMAC in capturing complex morphological variations and enhancing structural fidelity across diverse mesoscaled neuronal morphologies.

Pigs' brain responses to stroking after long-term positive human interactions: An fMRI exploratory study
Positive interactions with humans can induce pleasurable experiences in animals, but their underlying neurobiology mechanisms are unknown. We investigated the brain responses (Functional Magnetic Resonance Imaging) to stroking by a human in 20 pigs under general anaesthesia. Ten pigs received positive human contacts over 9 weeks post-weaning (POS) and 10 pigs did not (CTL). Images from CTL pigs showed peaks of activation in the primary somatosensory cortex, caudate nucleus, anterior prefrontal cortex, and dorsal anterior cingulate cortex during stroking. Greater peaks of activation in the anterior prefrontal, ventral anterior cingulate, primary somatosensory and somatosensory association cortices were observed in POS pigs; whereas greater peaks of activation in the amygdala were observed in CTL pigs. Therefore, stroking is perceived and possibly elicited positive emotions in anesthetised pigs, and it may be perceived as more pleasant by experienced pigs than naive pigs, which may rather perceive it as a novel stimulus.

Post-synaptic facilitation and network dynamics underlying stimulus-specific combination sensitivity
Combination-sensitive neurons (CSNs) integrate multiple stimulus features to generate behaviorally meaningful responses. While such neurons are well studied in fast timescale systems such as bat echolocation, the mechanisms enabling extended temporal integration in species like songbirds remain poorly understood. Using a computational model, we show that syllable-specific neurons in the songbird auditory system function as coincidence detectors whose selectivity depends on both post-inhibitory facilitation and persistent network activity. This persistence serves as a "memory trace", allowing precise association of sequential syllables across hundreds of milliseconds. We propose that this dynamic interplay between intrinsic neuronal properties and convergent synaptic inputs gives rise to a higher-order "meta-combination sensitivity" enabling the auditory system to transform discrete acoustic events into temporally extended percepts. Our findings provide a mechanistic framework that bridges theories of coincidence detection with longer-timescale working memory, highlighting the importance of distributed network mechanisms for auditory temporal coding.

40 Hz Audiovisual Stimulation Improves Sustained Attention and Related Brain Oscillations
Gamma oscillations (30-100 Hz) have long been theorized to play a key role in sensory processing and attention by coordinating neural firing across distributed neurons. Gamma oscillations can be generated internally by neural circuits during attention or exogenously by stimuli that turn on and off at gamma frequencies. However, it remains unknown if driving gamma activity via exogenous sensory stimulation affects attention. We tested the hypothesis that non-invasive audiovisual stimulation in the form of flashing lights and sounds (flicker) at 40 Hz improves attention in an attentional vigilance task and affects neural oscillations associated with attention. We recorded scalp EEG activity of healthy adults (n=62) during one hour of either 40 Hz audiovisual flicker, no flicker as control, or randomized flicker as sham stimulation, while subjects performed a psychomotor vigilance task. Participants exposed to 40 Hz flicker stimulation had better accuracy and faster reaction times than participants in the control groups. The 40 Hz group showed increased 40 Hz activity compared to the control groups in agreement with previous studies. Surprisingly, 40 Hz subjects had significantly lower delta power (2-4 Hz), which is associated with arousal, and higher functional connectivity in lower alpha (8-10 Hz), which is associated with attention processes. Furthermore, decreased delta power and increased lower alpha functional connectivity were correlated with better attention task performance. This study reveals how gamma audiovisual stimulation improves attention performance with potential implications for therapeutic interventions for attention disorders and cognitive enhancement.

Thalamo-insular pathway regulates tic generation via motor-limbic crosstalk
Tic disorders accompanied by premonitory urges are the hallmark symptoms of Tourette syndrome (TS), but the neuronal mechanism remains unsolved. Here, we show that striatal disinhibition induces motor tics in mice. This model exhibits c-Fos activation in both motor and limbic structures, such as the insular cortex (IC). Viral tracing demonstrates that aberrant striatal activity is ultimately transmitted to the insular cortex via the intralaminar thalamic nuclei, a potential target of deep brain stimulation in TS patients. We further identify tic-associated activity in the IC as well as the primary motor cortex (M1). Chemogenetic inhibition of the thalamo-insular pathway suppresses M1 synchronization and alleviates tic-like behaviors. These findings reveal motor-limbic circuit dysfunction as a key mechanism underlying tic disorders.

Longitudinal Associations Between Screen Time, Brain Development, and Language Outcomes in Early Childhood
Language development during toddlerhood is supported by both neurobiological maturation and environmental experiences. It relies on reciprocal interaction, and excessive screen time exposure may have a negative impact. In the current study, we investigated how screen time at age two relates to language outcomes and brain development at ages two and three. Seventy toddlers underwent MRI scanning and neurodevelopmental testing, and brain volumes in language-related areas were extracted. Structural equation modelling showed that at age two, there was a negative relationship between screen time and pars triangularis volumes. Importantly, smaller volumes at age two predicted greater screen time usage at age three, mediated by poorer language outcomes. These results suggest that over time, children with smaller volumes and weaker language skills at age 2 became more likely to rely on screens at age 3, suggesting that early vulnerabilities amplify later screen use, highlighting the sensitivity of language networks to environmental input and the potential for screen exposure to alter developmental trajectories.

Circuits activated by psychiatric-associated behavior: from brain-wide labeling to regional assessment using Psych-TRAP.
Background: Neuropsychiatric disorders, such as schizophrenia and autism, affect a substantial portion of the global population, 1 in 8 individuals. Genetic risk factors have been the major contribution to neuropsychiatric disorders; however, there is limited knowledge of how risk factors lead to brain circuit impairment and neuropsychiatric phenotypes. Rationale: Understanding how risk factors impact brain circuitry in the whole brain level at cellular resolution and their connection to neuropsychiatric phenotypes should help develop specific drug targets and therapeutics targeting precisely the affected cell types and circuits. Methods: We employ a clinically relevant mouse model of one of the major neuropsychiatric genetic risk factors - microdeletion in the 15q13.3 locus. Using the model, we developed a novel technique, Psych-TRAP, to label psychiatric behavior-associated circuits at whole brain level and at cellular level. We validated the genetic mouse model with clinical phenotypes and labelled transiently active cells, using TRAP2, and quantified cell densities in the whole brain using an automated pipeline, ABBA. This is the first ever approach to validate a triple transgenic mouse line with psychiatric microdeletion and understanding the cellular activation pattern and differential recruitment of cells immediately after a psychiatric-like behavior. Key findings: Further, we validated Psych-TRAP by understanding the activation of cells in already known brain areas and novel brain areas and confirmed no direct involvement of non-neuronal cells right after 3-chmabered social interaction (3-CSI). Lastly, we discovered the involvement of a dominant GABAergic component in the prefrontal cortex (PFC), mainly mediated by reelin positive (REL+) neurons and by somatostatin positive (SST+) neurons in the primary somatosensory area-trunk (SSp-tr), in mice harboring 15q13.3 microdeletion. Future implications: Thus, Psych-TRAP is a robust technique to generate mice line with disrupted copy-number variations, label transiently active cells permanently for future circuit manipulations in an unbiased manner and reveal the underlying molecular markers mediating psychiatric behaviors. This can be extended further to understand the molecular mechanisms of active cells from a particular brain area, identified from Psych-TRAP, using spatial transcriptomics and promises a potential technique for translation research targeting specific manifestations.

Independence and Coherence in Temporal Sequence Computation across the Fronto-Parietal Network
Time processing requires distributed and coordinated cortical dynamics. Flexible yet robust temporal representations can arise from two distinct computational modes: a coherence mode, where multiple cortical areas hold the same elapsed-time estimate, and an independence mode, where each area maintains its own local estimate. However, how the brain switches between these modes has remained unknown. Using mesoscale two-photon calcium imaging, we simultaneously recorded neuronal populations in the secondary motor cortex (M2) and posterior parietal cortex (PPC) of mice performing a novel alternating-interval timing task. Both areas encoded elapsed time through similar high-dimensional sequential activity. Decoding analyses revealed that the fronto-parietal network has both independent and coherent temporal codes. Communication-subspace analysis showed that temporal information was distributed across multiple low-variance subspaces, whereas the largest subspace preferentially encoded behaviour. A twin recurrent neural network (RNN) model with sparse inter-RNN connections and shared high-variance noise reproduced these experimental findings. Moreover, perturbations applied along the dominant shared subspace paradoxically enhanced independence between the two networks. Through a mathematical formalization based on the local Lyapunov exponents, we uncovered how perturbations along different subspaces selectively evoke either independent or coherent communication mode. Together, these results reveal a principle by which fronto-parietal circuits achieve robust yet flexible computation through the interplay of sparse coupling and shared global fluctuations.

Electrical coupling within thalamocortical networks cumulatively reduces cortical correlation to sensory inputs
Thalamocortical (TC) cells relay sensory information to the cortex, as well as driving their own feedback inhibition through collateral excitation of the thalamic reticular nucleus (TRN). The GABAergic cells of the TRN are extensively coupled through electrical synapses. While electrical synapses are most often noted for their roles in synchronizing rhythmic forms of neuronal activity, they are also positioned to modulate responses to transient information flow across and throughout the brain, although this effect is seldom explored. Here we sought to understand how electrical synapses embedded within a network of TRN neurons regulate the processing of ongoing sensory inputs during relay from thalamus to cortex. We used Hodgkin-Huxley point models to construct a network of a 9 TC and 9 TRN cells, with one cortical output neuron summing the TC activity. Each pair of TC and TRN cells was reciprocally coupled by chemical synapses. TRN cells were each electrically coupled to two neighboring cells, forming a ring topology. TC cells received synaptic inputs in sequence, with intervals between inputs varying from 10 to 50 ms across simulations. This architecture and sequence of inputs allowed us to assess the functional radius of an electrical synapse by comparing the cumulative effects of each additional TRN electrical synapse on the responses of the TRN and TC cells and the cortical output. Effects of electrical synapses on TRN cell activity were strongest for smaller intervals between inputs, and cumulative with additional synapses. In contrast, effects in TC neurons were strongest for larger intervals between inputs and also increased with coupling strength. Coupling within TRN modulated cortical integration of TC inputs by unexpectedly increasing response rates, duration and reducing spike correlation to the input sequence that was presented to the TC layer. Thus, embedded TRN electrical synapses exert powerful influence on thalamocortical relay, in a cumulative manner. These results highlight the multi-synaptic influences of electrically coupled cells and reinforce that they should be included in more complex and realistic networks of the brain.

Psychological scales in the brain: Trait-linked questionnaire items evoke similar neural patterns in the mPFC
Self-report questionnaires are widely used across psychology and related disciplines, yet the cognitive and neural processes underlying how individuals generate responses to such items remain poorly understood. Here, we investigated whether items from the same psychological scale evoke similar neural activation patterns in the medial prefrontal cortex (mPFC), a region consistently implicated in self-referential processing. While undergoing functional magnetic resonance imaging (fMRI), participants completed a self-reference task in which they judged how well 72 personality-related questionnaire items (e.g., from the Big Five, emotion regulation, and well-being scales) described themselves. Using representational similarity analysis (RSA), we found that items from the same scale elicited more similar multivoxel activation patterns in the mPFC compared to items from different scales. This effect was specific to the self-reference task and was not observed during a semantic judgment control task using the same items. Furthermore, the mPFC encoded not only categorical scale membership but also graded psychological similarity among scales, as reflected in inter-scale behavioral correlations. Importantly, these effects remained significant even after controlling for sentence-level semantic similarity using multiple regression RSA, indicating that the observed neural structure reflects psychological rather than linguistic similarity. These findings suggest that the mPFC integrates internally constructed evidence in a construct-sensitive manner during self-report, and they open new avenues for linking psychological assessment with neural representation. We discuss the implications for understanding self-report as a cognitive process and for future work on neuroimaging-informed scale validation.

Genome-edited retinal organoids restore host bipolar connectivity in the primate macula
Retinal organoids (ROs) represent a promising regenerative strategy for restoring vision in retinal degenerative diseases, but whether host cone bipolar cells (BCs) in the primate macula can rewire with transplanted photoreceptors remains unresolved. Here, we transplanted genome-edited human retinal organoids lacking ON-BCs (Islet-1-/-ROs) into a non-human primate macular degeneration model. Remarkably, host rod and cone BCs extended dendrites toward grafted photoreceptors, forming functional synapses confirmed by immunohistochemistry, ultrastructural imaging, and focal macular electroretinography. Both ON- and OFF-pathway connectivity was rebuilt, providing the first demonstration of host-graft synaptic integration in the primate macula. These results establish that primate cone circuits retain a surprising capacity for rewiring and highlight genome-edited ROs as a powerful platform for vision restoration. Our findings represent a critical translational step toward stem cel-based therapies capable of repairing central vision in patients with advanced macular degeneration.

A molecularly defined basalo-prefrontal-thalamic circuit regulates sensory and affective dimensions of pain
Both the medial prefrontal cortex (mPFC) and thalamus have been implicated in pain regulation. However, the roles of the mPFC-thalamus connection in pain and how the mPFC modulates nociceptive processing within the brain remain unclear. Here, we show that the mPFC neurons that project to thalamus are marked by Foxp2 expression and deactivated in both acute and chronic pain. Persistent inactivation of the mPFC Foxp2+ neurons enhances nociceptive sensitivity, while their activation alleviates multiple aspects of pain. Circuit-specific manipulations revealed that the projections to parataenial nucleus, mediodorsal and ventromedial thalamus differentially modulate sensory and affective pain. Additionally, the mPFC Foxp2+ neurons receive cholinergic input from the basal forebrain, particularly the horizonal diagonal band (HDB). Notably, activation of the 4{beta}2-containing nicotinic acetylcholine receptor in mPFC exerts antinociceptive effects in Foxp2+ neuron-dependent manner. Together, our study defines an HDB[->]mPFCFoxp2[->]thalamus circuit essential for sensory and affective pain modulation and underscores the therapeutic potential of targeting mPFC cholinergic signaling in chronic pain management.