bioRxiv Subject Collection: Neuroscience's Journal

Monovision-induced motion illusions in presbyopic and non-presbyopic populations
Monovision is a common correction for presbyopia that focuses one eye at far distances and the other at near distances, resulting in an interocular difference in blur between the eyes. Because blur increases the speed of visual processing by a few milliseconds, these optical conditions can induce dramatic misperceptions of the distances and 3D directions of moving objects. To date, however, the illusion has been demonstrated in only non-presbyopic individuals. We analyze the prevalence of both the processing speed differences and the visibility of the resulting illusions in the presbyopic and general populations.17 presbyopes (54.4 +/- 5.9years) and 36 non-presbyopes (22.2 +/- 5.0years) participated. The proportions of these participant populations approximately match their proportions in the general population. Two strips of horizontally moving bars were presented on an autostereoscopic display with interocular blur and light-level differences. The task was to report which strip appeared closer in depth. Blur- and light-level differences caused illusions that are respectively known as the reverse and classic Pulfrich effects. Interocular delay and an illusion visibility index - the ratio of interocular delay and the detection threshold-were obtained from each participant for both blur and light-level differences between the eyes. Blur- and light-level differences cause highly significant changes in processing speed at the individual and group levels. (The two populations were statistically indistinguishable in their susceptibility to stimulus-induced processing speed differences.) The reverse and classic Pulfrich effects occurred in 94% and in 96%, respectively, of the general participant population. The visibility index showed that the processing speed discrepancy exceeded the detection threshold in a smaller number of participants - 30% and 43%, respectively. Interocular differences in optical blur reliably cause interocular differences in processing speed across presbyopic and non-presbyopic populations, although they create visible (suprathreshold) illusions in only a subset of participants. However, this subset included individuals with processing delays that were many times larger than the detection threshold. These latter participants are likely to be afflicted by large, highly visible illusions in real-world conditions. Methods for reducing or eliminating these illusions are discussed.

Environmental Novelty Modulates Rapid Cortical Plasticity During Navigation
In novel environments, animals quickly learn to navigate, and position-correlated spatial representations rapidly emerge in both the retrosplenial cortex (RSC) and primary visual cortex (V1). However, the role of plasticity in building these spatial representations, and how experience modulates this process, are not well understood. Here, we investigated the plasticity of spatial representations with real-time, cellular-resolution read and write control of neural activity using two-photon calcium imaging combined with holographic optogenetic stimulation in mice navigating virtual reality environments. Targeted stimulation of individual layer 2/3 neurons rapidly biased neural activity towards stimulation-paired locations in novel, but not familiar, environments. In contrast, RSC layer 5 neurons exhibited stimulation-induced plasticity regardless of environmental familiarity. These findings reveal a layer-specific, experience-dependent modulation of plasticity and offer a framework for how neocortical spatial representations strike a balance between stability of familiar environments with flexibility for continuous updates of relevant context information.

Canonical Hidden Markov Model Networks for Studying M/EEG
Dynamic brain networks identified in magneto/encephalography (M/EEG) recordings provide new insights into human brain activity. One established method uses Hidden Markov Models (HMMs) and has been shown to infer reproducible, fast-switching brain networks in a variety of cognitive and disease conditions. Often these studies are done on small bespoke (boutique) datasets (N<100) and analysed in isolation of other M/EEG datasets. Instead of training a new model for each boutique study, which is computationally expensive, we propose the use of a canonical HMM. This provides a common reference through which different studies can be described using the same set of networks. We provide HMMs for a range of model orders (4-16 states) in parcellated source space and sensor space. These HMMs were trained on 1849 MEG recordings (N=621, 18-88 years old, 194 hours), capturing population variability in both rest and task data. We illustrate applications of this canonical HMM approach in parcellated source space using boutique MEG and EEG datasets. Applying the canonical HMM in parcel space requires the boutique dataset to be preprocessed and source reconstructed in the same way as the canonical HMM training data. Apply the canonical HMM in the sensor space requires the same sensor layout and preprocessing as the canonical HMM training data. The canonical HMMs have been made publicly available as an open-access resource, providing sets of canonical brain networks that can be used to compare individuals within and across a range of datasets.

Large-scale cellular-resolution read/write of activity enables discovery of cell types defined by complex circuit properties
The complexity of the mammalian brain's vast population of interconnected neurons poses a formidable challenge to elucidate its underlying mechanisms of coordination and computation. A key step forward will be technologies that can perform large-scale, cellular-resolution monitoring and interrogation of distributed brain circuit activity in behaving animals. Here, we present an all-optical strategy for precise optogenetic activity control of [~]10^3 neurons and simultaneous activity monitoring of [~]10^4 neurons within and across areas of mouse cortex--an order-of-magnitude leap beyond previous capabilities. Tracking population responses following delivery of precisely-defined widely-distributed activity patterns to the visual cortex of awake mice, we were surprised to identify neurons robustly responsive to stimulation of diverse ensembles, defying conventional like-to-like wiring rules. These cells were primarily deep L2/3 somatostatin-positive (SST) interneurons with functional properties distinct from other SST neurons, and appeared to play a role in brain dynamics that could only have been identified through broad cellular-resolution circuit interrogation. Our work reveals the value of measuring large-scale circuit-dynamical properties of functionally-resolved single cells, beyond genetic and anatomical classification, to define and explore the roles of cell types in brain function.

Imbalanced Brain Connectome: A Novel Link between Functional Somatic Disorders, Multiple Chemical Sensitivity, and Post-COVID patients
This study aimed to investigate and assess shared patterns of structural brain connectivity across three clinical populations. Despite significant advancements in neuroimaging, structural connectivity alterations have been underexplored in functional somatic disorders (FSDs), multiple chemical sensitivity (MCS), and post-COVID-19 conditions (PC). Clinical observations suggest that olfactory symptoms may represent a missing link between these three patient groups. Using diffusion-weighted MRI and voxel-based probabilistic tractography, structural connectivity was analysed in 57 females (MCS: 16, FSD: 15, PC: 11, and 15 matched healthy controls). Independent-sample t-tests (with FDR correction) and permutation testing were applied to assess group-level differences, particularly in inter- and intra-hemispheric connectivity. A marked decrease in inter-hemispheric connectivity was observed in patients (70.9%) compared with controls (29.1%; p < 0.001). The finding was consistent across all diagnostic groups. These alterations remained stable following reanalysis and aggregation, reliably distinguishing patients from controls. No significant differences were found in intra-hemispheric connectivity across the patient groups. Additionally, out of 12 predefined interregional connections, ten showed significant alterations in at least one patient group. The findings reveal robust and consistent reduced inter-hemispheric connectivity in patients with MCS, FSD, and PC, highlighting a potentially shared neurobiological signature among the patient groups.

A splice-switching antisense oligonucleotide approach for pediatric genetic epilepsies
Variants in ion channel genes are common causes of pediatric epilepsy, often leading to intractable seizures, developmental delay and other comorbidities, which increases risk of death. Pathogenic variants in the SCN8A gene, which encodes a voltage-gated sodium channel critical for action potential generation in the brain, account for ~1% of genetic epilepsies. The voltage sensor in SCN8A domain 1 is encoded by one of two developmentally-regulated mutually exclusive alternative exons, 5N and 5A. We observe that variants in these exons are more likely to cause infantile spasms, a severe seizure type, than variants elsewhere in SCN8A, and that some pathogenic variants affect exon 5 splicing, impacting patient phenotype. Molecular and evolutionary analyses implicate the exon sequences of these and other voltage-gated ion channel alternative exons in splicing regulation. We identified antisense oligonucleotides (ASOs) that shift splicing of SCN8A exon 5N to 5A or vice versa. These ASOs normalize neuronal activity in patient-derived iPSC neurons, and reduce seizures and motor impairment and extend lifespan in a new exon 5N mutant mouse model. Our results demonstrate that splice-switching ASOs can effectively reduce the expression of pathogenic isoforms and rescue both seizure and non-seizure phenotypes. Similar approaches should be applicable to pediatric genetic epilepsies caused by mutations in other ion channel alternative exons.

{triangleup}FOSB in the nucleus accumbens core is required for increased anxiety, but not decreased social motivation, following estrogen withdrawal in female mice
During pregnancy, estrogen levels rise dramatically, but quickly drop to prepartum levels following birth, and remain suppressed until ovulation resumes. This postpartum estrogen withdrawal state has been linked to changes in the brain and behavior in humans and rodents. Previous research has demonstrated that following a hormone-simulated pseudopregnancy (HSP), an experimental model of postpartum estrogen withdrawal, female mice show increased anxiety-like behaviors and decreased social motivation. Further, these behavioral changes occur concurrently with an increase in {Delta}FOSB, a transcription factor associated with stable long-term plasticity, in the nucleus accumbens core. To test whether this increase in {Delta}FOSB is required for these behavioral changes, we used a viral-mediated gene transfer approach to prevent {Delta}FOSB-mediated transcription in the NAcC during HSP and found that it reduced the high-anxiety behavioral phenotype in estrogen-withdrawn females. However, preventing {Delta}FOSB-mediated transcription had little effect on social motivation. Together, these results suggest that postpartum estrogen withdrawal increases {Delta}FOSB in the NAc core to impact anxiety-like behaviors, but not social motivation, following estrogen withdrawal.

Networks of sexually dimorphic neurons that regulate social behaviors in Drosophila
Neural mechanisms underlying sexually dimorphic social behaviors remain enigmatic in most species. In Drosophila, sexually dimorphic P1/pC1x neurons have been described as a site of sensory integration that regulates mating and aggressive behaviors. We show that the male P1/pC1x population forms a highly intertwined network with male-specific mAL and aSP-a neurons that is poised to regulate male behavior. The 48 P1/pC1x cell types exhibit heterogeneous synaptic connections with a subset receiving strong input from identified sensory pathways. We also describe circuit motifs by which P1 and sexually dimorphic aIPg neurons co-regulate social behaviors. Genetic driver lines for these cell types were generated and used to discover distinct roles for P1/pC1x cell types in promoting social acoustic signaling and male-male interactions. Our results reveal unexpected diversity in the connectivity and behavioral roles of the P1/pC1x cell types and provide essential genetic tools for interrogating their neurophysiological and behavioral functions.

Visceral signaling of post-ingestive malaise directs memory updating in Drosophila
Consolidation is a time when labile memories transition to a stable form. Malaise learning in Drosophila reveals consolidation to also permit memory updating. Flies taught to associate one of two odors with toxin-tainted sugar initially express conditioned odor approach, that following consolidation switches to avoidance. Behavioral reversal emerges from dopaminergic update of parallel memories for the two trained odors. Differential serotoninergic modulation of specific aversive and rewarding dopaminergic neuron subtypes permits post-ingestive intoxication to suppress consolidation of initial odor-sugar memory and simultaneously invert reward memory plasticity into "safety" memory for the odor experienced without food. Fat body release of the Toll-ligand activating protease modSP, and resilience factor Turandot A, instruct malaise updates by triggering autocrine Toll signaling in the same brain dopaminergic neurons that form and consolidate initial sugar memory. This neural mechanism overcomes the credit assignment problem of delayed post-ingestive reinforcement by updating earlier memories of the trained odors.

Dorsal Raphe Nucleus Enkephalin Peptide Modulates Behavioral Preference
The endogenous opioid system is a powerful modulator of motivation and affect. The dorsal raphe nucleus (DRN) in the midbrain has been established as an important site of opioid action and is an integral hub in behavioral modulation. To investigate the functional significance of DRN opioid signaling in aversive and appetitive behaviors we disrupted preproenkephalin (Penk) in DRN using CRISPR-Cas9 technology in Penk-Cre mice. We found that CRISPR mediated knockdown of enkephalin peptide in the DRN (DRNPenk) enhanced inflammation-induced mechanical sensitivity and odor avoidance. Additionally, loss of DRNPenk diminished sucrose preference and engagement with a novel social stimulus. To further characterize the opioid system within the DRN, we performed Hiplex in situ hybridization of 12 genes in the same tissue. This revealed that DRNPenk is largely separate from DRN serotonin cells and is instead distributed on glutamatergic and GABAergic cells. However, subtype-specific knockdown of DRNPenk from glutamatergic and GABAergic cells did not replicate the behavioral effects of general DRNPenk knockdown. This suggests that these neurons represent a novel population that mediate motivated behaviors distinctly from canonical DRN mechanisms.

Dual Role of LH-GABA Neurons in Encoding Alcohol Reward and Aversive Memories
One of the core aspects of alcohol use disorder is continued use despite negative consequences. Individuals with an alcohol use disorder typically engage in behaviors which represent a failure to integrate the aversive consequences of their actions. The neural mechanisms of learning about conflicting rewarding and aversive experiences remain poorly understood. Previous research has highlighted the critical role of GABAergic neurons in the Lateral Hypothalamus (LH-GABA) in rewarding memories and motivation. However, whether this role extends to aversive outcomes, and competition between rewarding and aversive outcomes remains unexplored. In this study, we sought to elucidate the role of LH-GABA neurons in encoding and expressing alcohol reward and aversive memories using fiber photometry calcium imaging. We used a dual-virus approach to confine expression of the fluorescent calcium indicator jGCaMP7f to GABAergic neurons in LH of Long-Evans rats. In our first experiment, following acquisition of a cue-alcohol association, a mild foot shock was introduced on 50% of the trials. In the second experiment, we trained rats to associate three different cues with either alcohol, foot-shock, or no consequence. Subsequently, we combined these conditioned stimuli in pairs to evoke motivational conflict. Our results reveal that LH-GABA activity is associated with cues predictive of both appetitive and aversive outcomes and is highest to a cue predictive of an aversive outcome. Additionally, LH-GABA activity responds to an aversive shock stimulus, but this response is attenuated in the presence of alcohol. In summary, our findings show the activity of LH-GABA neurons is involved in learning both appetitive and aversive associations, and their interaction in conflict.

PSD-95 drives binocular vision maturation critical for predation
Postsynaptic density protein 95 (PSD-95) is a signalling scaffold within the postsynaptic density of excitatory synapses which drives silent synapse maturation during critical periods (CP). Binocularity develops during visual CPs and matures before its closure. Despite lifelong critical period plasticity, PSD-95 knock-out (KO) mice exhibit relatively subtle sensory phenotypes as adult mice in standard cage housing. To assess PSD-95s role in ethologically relevant binocular visual processing, we compared prey capture behaviour in PSD-95 KO and wild-type (WT) mice. KO mice were profoundly impaired in diverse epochs of predatory behaviour, but exhibited improved prey localisation under monocular conditions, indicating impaired binocular integration. This was confirmed in an orientation discrimination task, where KO mice were impaired binocularly but performed monocularly like WT mice. Our results depict a critical role of PSD-95 to drive binocular maturation which becomes evident under ethologically demanding behaviours.

Expression and localization of NMDA receptor GluN2 subunits in dorsal horn pain circuits across sex, species, and late postnatal development
Despite being essential mediators of pain processing, the molecular identity of N-methyl-D-aspartate receptor (NMDAR) subtypes in nociceptive dorsal horn circuits is poorly understood, especially between sexes and in humans. Given the importance of GluN2 subunits in shaping NMDAR function and plasticity, we investigated the expression and localization of specific GluN2 NMDAR variants in the dorsal horn of viable spinal cord tissue from male and female rodents and human organ donors. Analysis of single-cell/nuclei sequencing datasets revealed that the GluN2A (GRIN2A) and GluN2B (GRIN2B) subunits are robustly expressed in dorsal horn neurons of both mice and humans, with moderate expression of GluN2D (GRIN2D) and minimal expression of GluN2C (GRIN2C). Immunohistochemistry with antigen retrieval demonstrated that GluN2A, GluN2B, and GluN2D proteins are all preferentially localized to the superficial dorsal horn of both adult rats and humans, which is conserved between males and females. Surprisingly, we found that these GluN2 NMDAR subunits are enriched in the lateral superficial dorsal horn for rats but not for humans, while presynaptic and neuronal markers are symmetrically distributed across the rat mediolateral axis. A dramatic shift in localization of GluN2A to the lateral superficial dorsal horn was observed across later postnatal development (PD21-PD90) in both male and female rats, with a corresponding change in synaptic NMDAR currents. This discovery of changes in NMDAR subunit distribution into rodent adulthood and between species will shed light on the physiological roles of NMDARs and their utility as potential therapeutic targets for pain.

Coupled rhythms in early auditory cortex mirror speech acoustics
Theta and gamma neural dynamics dominate the human auditory cortex during speech perception and have been proposed to track syllable boundaries and encode phonemic information, respectively. To what extent these rhythms engage intrinsic mechanisms or mirror the phase and frequency of the speech acoustics remains unsolved. Applying signal processing techniques from neuroscience to speech audio corpora from 17 languages, we found that canonical brain features (theta, gamma, and their phase-amplitude coupling) are distinctive and visible in the speech envelope. They represent syllabic rate (between 2 and 6 Hz), vocalic features (between 30 and 50 Hz), and fundamental frequency (between 100 and 150 Hz). Intracerebral (sEEG) recordings from the auditory cortex of 18 epilepsy patients revealed that theta-gamma dynamics and their coupling are absent at rest but emerge during speech perception, linearly driven by the acoustic envelope. These responses originate from distinct neural populations within overlapping auditory regions. Thus, theta-gamma auditory dynamics primarily mirror speech acoustics rather than being generated by endogenous mechanisms.

Canonical decision computations underlie behavioral and neural signatures of cooperation in primates
Successful cooperation requires dynamic integration of social cues. However, the neural mechanisms supporting this complex process remain unknown. Here, we reveal that the primate dorsomedial prefrontal cortex (dmPFC) implements a gaze-dependent social evidence accumulation process to guide cooperative decisions in freely moving marmoset dyads. A drift-diffusion process in which the partner's action variability is accumulated by social gaze best explains the cooperative actions of the actor. Single-neuron recordings in dmPFC revealed a direct neural correlate: the slope of predictive ramping activity mapped directly onto the rate of evidence accumulation, while baseline firing, modulated by prior outcomes, mapped onto the initial bias. At the population level, the geometry of dmPFC neural trajectories reflected the strength of social evidence and was linked to cooperative success. Together, these findings establish a multi-level neural mechanism for transforming active sensing into a decision variable, linking a canonical computation to cooperative behavior in a naturalistic setting.

Bridging Histology and Tractography: First Visualization of the Short-Range Prefrontal Connections in the Human Brain
Decades of histological research in non-human primates have revealed a dense web of short-range connections underpinning prefrontal cortex (PFC) function. However, translating this anatomical ground-truth to the living human brain has been a major challenge, leaving our understanding of the PFC's intrinsic wiring incomplete. These short-range fibers are difficult to resolve with non-invasive methods like diffusion tractography, which are often hampered by false positives. Here, we provide the first systematic in-vivo visualization of these pathways in the human brain. By guiding high-resolution probabilistic tractography with established histological findings, we mapped the short-range connections within and between five major PFC subdivisions in 1,003 individuals (547 F, 456 M). Our anatomically-guided approach successfully reconstructed these intricate connections with high precision (>80%) and accuracy (>70%) relative to histological findings. The resulting tracts not only captured broad organizational principles but also replicated fine-grained patterns previously only seen in invasive studies. Furthermore, these connections showed high test-retest reliability within individuals alongside significant variability between them, highlighting a stable yet unique anatomical fingerprint. Ultimately, this study shows how linking histology to tractography provides a powerful framework to advance our understanding of the human connectome and opens avenues to investigate local circuitry that underpins cognition and disease.

Individual Differences in Speech Monitoring: Functional and Structural Correlates of Delayed Auditory Feedback
Speech production relies on continuous self-monitoring to ensure that produced sounds match intended targets. Delayed auditory feedback (DAF) disrupts speech fluency by perturbing this alignment and offers a powerful tool to study the sensorimotor control of speech. Here, we combined functional and diffusion-weighted MRI in 31 participants producing words with and without DAF. Participants showed substantial variability in how much their speech slowed under DAF, quantified by a continuous susceptibility index (SI). At the group level, DAF elicited increased activation in a right-lateralized speech motor network encompassing the superior temporal, supramarginal, inferior frontal, precentral, and supplementary motor areas, along with engagement of the left cerebellum. In contrast, individual differences revealed the opposite pattern: higher susceptibility was associated with stronger activation in left-hemisphere speech motor homologues. Diffusion analyses of the arcuate fasciculus (AF) further showed that greater fiber density in the right posterior AF predicted lower susceptibility, whereas larger right long AF volume predicted higher susceptibility. Together, these findings identify a lateralized and tract-specific organization of speech monitoring: fluency under perturbation depends on a right-lateralized monitoring network that supports integration of auditory and somatosensory feedback through the right posterior AF, while stronger auditory-motor coupling via the right long AF and excessive left-hemisphere activation predict greater vulnerability to feedback disruption.

Evolving learning state reactivation and value encoding neural dynamics in multi-step planning
Planning in value-based decision making is often dynamic, with reinforcement learning (RL) providing a powerful framework for investigating how value and action at each step change across trials. Surprisingly, the evolving neural signatures of value estimation and state reactivation in multi-step planning, both within and across trials, have received little consideration. Here, using magnetoencephalography (MEG), we detail neural dynamics associated with planning, wherein subjects were tasked to find an optimal path in order to maximise reward. Behavioural evidence showed improved performance across trials, including subjects showing an increasing disregard for low-value states. MEG data captured evolving value estimation signals such that, across trials, there was an emergence of stronger and earlier within trial value encoding linked to boosted vmPFC activity. Value encoding signals showed a positive correlation and individual performance metrics, as reflected in overall task-related reward earnings. Strikingly, across trials, there was an attenuation of state reactivation for negative-value states, an effect that positively correlated with evolving negative-value state avoidance behaviour. The finding linking neural dynamics, including a valence-dependent selective reactivation of negative states, to across-trial behavioural improvement advances an understanding of learning during multi-step planning.

Response expectations shape serial dependence and stimulus processing
Perceptual decisions are biased by recent history, yet the balance between attractive and repulsive effects varies across contexts. Here, we tested whether trial by trial response expectations shape the direction of history biases in serial dependence during orientation reproduction. Behaviorally, we found that no response trials, especially when rare, reduced attractive biases and enhanced repulsive biases. EEG results revealed stronger evoked responses and amplified neural representations for stimuli following no-response trials. Together, these findings suggest that interrupting the perception action cycle fosters a state of re-engagement with current input and disengagement from past stimuli, indicating that serial dependence is a flexible process dynamically modulated by task expectations and transient shifts in sensory processing.

Lamin B1 physically regulates neuronal migration by modulating nuclear deformability in the developing cortex
Neuronal migration is a vital process that positions billions of neurons to create a functional brain. To navigate the constrained microenvironments within the cortex, precise control over the nuclear mechanics in migrating neurons is indispensable. Here, we show that Lamin B1 (LB1) regulates neuronal migration by modulating nuclear deformability. Excess LB1 in neurons halted migration without altering laminar identity or overall gene expressions in vivo, while in vitro, it elevated nuclear stiffness and impaired neuronal motility in confined spaces. Moreover, mispositioned neurons resulted in electrophysiological defects in the brain. Computational modeling predicted a temporal relationship between nuclear deformation and enhanced migration velocity, which was validated experimentally through live imaging. Notably, cerebral organoid assays using iPS cells established from patients with LMNB1 duplication exhibited impaired neuronal migration in a human model. Collectively, these findings demonstrate that LB1 is a critical regulator of nuclear mechanics, ensuring the accurate spatiotemporal positioning of neurons.

BACE: Behavior-Adaptive Connectivity Estimation for Interpretable Graphs of Neural Dynamics
Understanding how distributed brain regions coordinate to produce behavior requires models that are both predictive and interpretable. We introduce Behavior-Adaptive Connectivity Estimation (BACE), an end-to-end framework that learns phase-specific, directed inter-regional connectivity directly from multi-region intracranial local field potentials (LFP). BACE aggregates many micro contacts within each anatomical region via per-region temporal encoders, applies a learnable adjacency specific to each behavioral phase, and is trained on a forecasting objective. On synthetic multivariate time series with known graphs, BACE accurately recovers ground-truth directed interactions while achieving forecasting performance comparable to state-of-the-art baselines. Applied to human subcortical LFP recorded simultaneously from eight regions during a cued reaching task, BACE yields an explicit connectivity matrix for each within trial behavioral phase. The resulting behavioral phase specific graphs reveal behavior-aligned reconfiguration of inter-regional influence and provide compact, interpretable adjacency matrices for comparing network organization across behavioral phases. By linking predictive success to explicit connectivity estimates, BACE offers a practical tool for generating data-driven hypotheses about the dynamic coordination of subcortical regions during behavior.

Efficient in vivo pharmacological inhibition of deltaFOSB, an AP1 transcription factor, in brain
DeltaFOSB, an unusually stable member of the AP1 family of transcription factors, mediates long-term maladaptations that play a key role in the pathogenesis of drug addiction, cognitive decline, dyskinesias, and several other chronic neurological and psychiatric conditions. We have recently identified that 2-phenoxybenzenesulfonic acid-containing compounds disrupt the binding of deltaFOSB to DNA in vitro in cell-based assays, and one such compound, JPC0661, disrupts deltaFOSB binding to genomic DNA in vivo in mouse brain with partial efficiency. JPC0661 binds to a groove outside of the DNA-binding cleft of the deltaFOSB/JUND bZIP heterodimer in the co-crystal structure. Here, we generated a panel of analogs of JPC0661 with the goal of establishing structure-activity relationships and improving its in vivo efficacy by replacing the amino-pyrazolone cap moiety with various substituents. We show that one such analog, YL0441, disrupts the binding of deltaFOSB to DNA in vitro and in vivo, and suppresses deltaFOSB-function in cell-based assays. Importantly, infusion of YL0441 into the hippocampus of APP mice (a mouse model for Alzheimer's disease) leads to virtually complete loss of deltaFOSB bound to genomic DNA by CUT&RUN sequencing. Our findings corroborate that DNA binding/release of AP1 transcription factors can be controlled via small molecules, even by analogs of a compound that binds to a groove outside of the DNA-binding cleft, and that our lead can be optimized via medicinal chemistry to yield a highly efficacious inhibitor of deltaFOSB function in vivo. These findings define a strategy to design small-molecule inhibitors for other AP1- and AP1-related transcription factors.

A unique neural signature of long-term memory encoding from EEG inter-electrode correlation
Classic memory models proposed that the encoding process involved in visual working memory (VWM) controls the bandwidth of encoding in long-term memory (LTM). Behaviorally, VWM and LTM accuracies are reliably correlated at the behavioral level, raising the question of whether LTM encoding uniquely engages processes that are distinct from VWM encoding. To investigate this, we recorded EEG activity as participants completed recognition memory tasks with set sizes of 32 and 128, far beyond typical VWM capacity. Using interelectrode correlation (IC) analysis, we found that IC patterns reliably predicted individual differences in LTM encoding across both set sizes, indicating a robust, domain-general neural signature. Importantly, this predictive power remained even after controlling for VWM and attentional control performance, suggesting that the model captures variance specific to LTM encoding. Temporally, predictive signals emerged only after stimulus onset and persisted for 500-600 ms. Early and late encoding phases involved distinct network structures, reflecting dynamic neural processes underlying individual differences in LTM encoding. Together, our findings reveal a unique and temporally dynamic neural signature that supports individual differences in LTM encoding, independent of general cognitive abilities.

Discovery of Small Molecules and a Druggable Groove That Regulate DNA Binding and Release of the AP1 Transcription Factor DeltaFOSB
DeltaFOSB, a member of the AP1 family of transcription factors, mediates long-term neuroadaptations underlying drug addiction, seizure-related cognitive decline, dyskinesias, and several other chronic conditions. AP1 transcription factors are notoriously difficult to modulate pharmacologically due to the absence of well-defined binding pockets. Here, we identify a novel site on deltaFOSB, located outside the DNA-binding cleft, that accommodates small molecules. We show that sulfonic acid-containing compounds bind to this site via an induced-fit mechanism, reorienting side chains critical for DNA binding, and that they may hinder the deltaFOSB bZIP alpha-helix from binding to the major groove of DNA. In vivo, direct administration of one such compound, JPC0661, into the brain reduces deltaFOSB occupancy at genomic AP1 consensus sites by approximately 60% as determined by CUT&RUN-sequencing. These findings suggest that DNA binding and release by AP1 transcription factors can be controlled via small molecules that dock into a novel site that falls outside of the DNA-binding cleft. Minimal sequence conservation across 29 bZIP domain-containing transcription factors in this druggable groove suggests that it can be exploited to develop AP1-subunit-selective compounds. Our studies thus reveal a novel strategy to design small-molecule inhibitors of deltaFOSB and other members of the bZIP transcription factor family.

Abnormally increased intrinsic neural timescales in sensory and default mode networks in cocaine use disorder
Cocaine use disorder (CUD) is associated with abnormal structural and functional brain changes. However, the neurodynamics and molecular underpinnings remain unclear. In this study, we mapped whole-brain intrinsic neural timescales (INTs), reflecting temporal neural processing, using resting-state functional magnetic resonance imaging data from 44 CUD patients and 44 healthy controls (HC). CUD showed increased INTs in visual, somatomotor, and default mode networks compared with HC. Mediation analysis linked local INTs abnormalities to altered dorsal attention network neurodynamics, associated with inhibitory control deficits. Notably, these changes were primarily correlated with alterations in gamma-aminobutyric acid type A receptors and the noradrenaline transporter. Machine learning classifiers based on INTs achieved a maximum accuracy of 75.5% in distinguishing CUD from HC, with a generalization accuracy of 65.0% on an independent dataset. This study elucidates aberrant neural mechanisms underlying CUD and highlights INTs as promising diagnostic biomarkers for clinical detection and intervention.

Emotional amnesia in humans with focal temporal pole lesions
Memory is typically better for emotional relative to neutral events, a process involving amygdala modulation of hippocampal activity. These structures, however, form part of a larger emotional brain network, which in humans includes the temporal pole, a cortical node whose functional role in emotional cognition remains poorly understood. Here, we show, in pharmaco-resistant epilepsy patients performing verbal and visual emotional episodic memory tasks, a selective impairment in recalling verbal emotional memories in left ventral temporal pole (vTP) lesioned patients compared with control patients. Memory for neutral words, and verbal comprehension performance on standard neuropsychological testing, were intact in these patients, indicating absence of general episodic memory or semantic impairment. All patients underwent recordings with intracranial electrodes during memory task performance. Left vTP lesioned patients showed no differences in amygdala or hippocampal electrophysiological responses to emotional words, compared with control patients, putatively isolating a vTP role in emotional memory. Unlike verbal emotional recall, left vTP lesioned patients showed memory enhancement for emotional vs. neutral pictures, whereas two patients with right vTP lesions showed the opposite pattern: impaired memory for emotional pictures but intact verbal emotional memory. These observations establish a critical, lateralized, modality-specific role for human vTP in emotional memory, imply emotional memory deficits in neurological conditions affecting this region, and advance the vTP as a target for neuromodulation in diseases characterized by maladaptive emotional memories.

Is the whole more than the sum of its parts? Considering global and local features of the connectome improves prediction of individuals and phenotype
Popular methods for analyzing the brain's functional connectome examine statistical associations between pairs of atlas-defined brain regions, viewing the strength of these links as independent values. However, edges within a standard connectivity matrix, i.e., correlations between individual regions or nodes, are not independent. They are part of an interconnected system. Here, we propose that consideration of both independent, linear relationships (as in standard approaches such as linear kernel ridge regression and connectome-based predictive modeling) as well as higher order statistical associations - such as tertiary interactions between matrix components and global features of the matrix space - will enhance identification of meaningful individual differences. To test this, we adopt a geometrically grounded measure of similarity that accounts for higher-order local statistical relationships and global interactions, the Wasserstein metric. Results indicate that considering connectivity matrices as representations of their associated Gaussian distributions significantly improves both identification of individuals based on their connectivity matrices (aka, 'fingerprinting') and prediction of individual differences in phenotypes such as fluid intelligence and openness to experience. Thus, both pairwise local and global brain connectivity properties encode for meaningful individual differences that relate to phenotypic expressions and should be considered in brain-behavior predictive models.

Infinite horizon control captures modulation of movement duration in reaching movements
Movement duration, a fundamental aspect of motor control, is often viewed as a pre-programmed parameter requiring dedicated selection mechanisms. An alternative view posits that movement duration emerges from the control policy itself. Here, we demonstrate, using infinite horizon optimal feedback control (IHOFC) and nonlinear limb dynamics that this alternative hypothesis successfully captures diverse aspects of human reaching behavior, including tradeoffs between movement duration and task parameters. Specifically, we reproduced the modulation of movement duration with varying reach distances and accuracy (Fitts' law), and extended the infinite horizon framework to include the effect of rewards and biomechanical costs. Furthermore, our model also featured a temporal evolution of feedback responses to perturbations that resembles experimental observations, and naturally accounted for motor decisions observed when participants select one among multiple goals in dynamic environments. Together, these developments show that in many cases, movement duration may not need to be specified a priori, but instead could result from task-dependent control policies. This framework validates a candidate explanation for varied movement durations, which invites to reconsider the nature and strength of evidence for the finite horizon formulation.

Neural Inflammation in Thoracic Dorsal Root Ganglia Mediates Cardiopulmonary Spinal Afferent Sensitization in Chronic Heart Failure
The cardiac sympathetic afferent reflex (CSAR) and pulmonary spinal afferent reflex (PSAR) amplify sympathetic activity and may contribute to chronic heart failure (CHF). We hypothesized that neural inflammation in thoracic dorsal root ganglia (DRGs) drives cardiopulmonary afferent sensitization through suppression of voltage-gated potassium (Kv) channels after myocardial infarction (MI). MI was induced in rats by coronary ligation. Molecular profiling, immunofluorescence, tissue clearing, and functional assays were used to assess neuroinflammation and reflex responses. Post MI, thoracic DRGs showed macrophage infiltration, glial activation, cytokine upregulation, and reduced Kv channel expression. Bulk RNAseq identified enrichment of macrophage activation related genes, and in vitro studies confirmed that pro-inflammatory cytokines and activated macrophages suppressed Kv channels and increased DRG neuron excitability. Epicardial injection of biotinylated TNFalpha; demonstrated cardiac afferent mediated cytokine transport to DRGs, inducing macrophage infiltration via a cytokine receptor-dependent mechanism. Anti-inflammatory interventions including oral minocycline, systemic macrophage depletion, and local epidural delivery of thermoresponsive hydrogel forming dexamethasone prodrug (ProGel Dex) significantly reduced DRG neuroinflammation, restored Kv channel levels, and attenuated exaggerated CSAR and PSAR responses. ProGel Dex also improved cardiac chamber dilation in the post-MI rats. These findings identify a cytokine uptake/glial activation/macrophage activation pathway as a driver of cardiopulmonary afferent sensitization after MI. Targeting DRG inflammation, particularly with sustained local dexamethasone delivery using ProGel Dex, offers a precision medicine to dampen pathological sympathetic activation and improve cardiac outcomes in CHF.

Associations Between Frailty and Cognitive Outcomes Across the Lifespan of Mice
Advancements in monitoring biological and brain aging with precise measures of health and longevity have the potential to accelerate research on pharmacological, genetic, and aging-related interventions. Over the past decade, frailty index has been used as an assessment tool for rodents, evaluating more than 30 non-invasive parameters that are strongly associated with chronological age, correlated with mortality, and sensitive to lifespan-altering interventions. However, whether aging phenotypes captured by the frailty index reflect brain aging remains unclear. In this study, we examined the relationship between frailty index and cognitive ability in young (3-4 months), middle-aged (12 months), and old (24 months) male and female C57BL/6J mice using a battery of behavioral and locomotor assays to determine whether frailty index scores can predict performance in tasks evaluating behavioral and cognitive function. Among the behavioral assays tested, frailty index scores had good correlation with the percentage of time spent in the center of the open-field apparatus, the duration spent in the open arms of the elevated plus maze, and the time spent in the target hole of the Barnes maze. These findings indicate that the frailty index not only reflects general physiological aging but may also serve as a reliable predictor of age-related cognitive decline in mice, providing a valuable tool for studies of interventions targeting brain aging.

Individual cortical neurons innervating large proportions of the neocortical areas in the MouseLight database
The general notion of the extent of cortical areal interconnectivity in the neuroscience community can in part be due to results from traditional neuroanatomical studies, which later insights have shown to systematically represent underestimates of the extent of the axonal arborizations. But any underestimate of this interconnectivity could in turn be a factor in strengthening the notion of functional localization in the cortex, i.e. the idea that there are circumscribed cortical areas with specific functions that do not to a large extent depend on information being processed in other such cortical areas. Recent advances in neuroanatomical techniques have greatly improved the possibilities to follow the axonal projections of individual neurons in full, and many reconstructed neurons are made available by the MouseLight database. We sampled individual cortical neurons with the majority of their axons within the neocortex and explored the extent of their axonal connections. We found that the efferent axon of individual cortical neurons can commonly cover as much as 30-40% of all types of cortical areas, with a coverage of up to 80% for a single neuron also being demonstrated. Combining the distributions of the axonal trees of more than one cortical neuron, we found that as few as three neurons within one area could reach 100% of the other cortical areas.

Multimodal Connectivity-based Cortical Segmentation with Graph Neural Networks
Due to the significant amount of time and expertise needed for manual segmentation of the brain cortex from magnetic resonance imaging (MRI) data, there is a substantial need for efficient and accurate algorithms to replace the need for human involvement. In this work, we explore the capabilities of Graph Neural Networks (GNNs) to segment the brain surface based on structural brain connectivity. We train three different GNN architectures, the Graph Convolutional Network (GCN), the Graph Attention Network (GAT), and the Graph U-Net, and evaluate their performances when trained on silver-standard cortical region labels created by FreeSurfer. We take a multimodal approach to brain segmentation by examining the influence of the structural connectivity values inferred from diffusion MRI (dMRI) in addition to using values from structural MRI (sMRI). Our results demonstrate the utility of GNN models, particularly the GAT architecture, which achieved Dice scores competitive to those reported in the literature with non-graph methods. Additionally, structural connectivity derived from dMRI revealed significant value in improving automatic segmentation, as models trained on combined attributes from dMRI and sMRI outperformed those trained only on sMRI. Finally, we compared the GNN-based and the FreeSurfer segmentations in their ability to predict demographic characteristics, where neither of the two approaches was statistically significantly superior to the other.

Auditory network persistence of stimulus representation in awake and naturally sleeping mice
Persistent neural activity often outlasts sensory stimulation, bridging perception and action. While commonly linked to working memory and decision making, its existence during passive states and sleep remains unclear. Using chronic high-density electrophysiology in freely behaving mice, we show that population spiking activity across the auditory cortical hierarchy enables decoding of past stimuli long after their offset, during both wakefulness and sleep. Time-resolved decoding revealed that in wakefulness, persistent representations decay uniformly across sensory and association cortices, whereas during sleep, persistence is prolonged in association cortex but remains brief in early auditory regions. Recurrent neural network modeling showed that higher internal noise during wakefulness reproduces this pattern, suggesting that reduced interference during sleep stabilizes sensory traces in associative areas. Our results demonstrate that persistent representation is a passive, state-dependent feature of sensory processing, supporting sensory maintenance even in the absence of active engagement.