bioRxiv Subject Collection: Neuroscience's Journal

A lateralized sensory signaling pathway mediates context-dependent olfactory plasticity in C. elegans
Lateralization of neuronal functions plays a critical role in regulating behavioral flexibility, but the underlying molecular mechanisms are challenging to establish at a single-neuron level. We previously showed that attraction of C. elegans to a medium-chain alcohol switches to avoidance in a uniform background of a second attractive odorant. This context-dependent behavioral plasticity is mediated by symmetric inversion of the odor-evoked response sign in the bilateral AWC olfactory neurons. Here we show that this symmetric response plasticity is driven by asymmetric molecular mechanisms in the AWC neuron pair. Mutations in the gcy-12 receptor guanylyl cyclase abolish odor response plasticity only in AWCOFF; the opposing odor-evoked response signs in AWCOFF and AWCON in gcy-12 mutants results in these animals being behaviorally indifferent to this chemical. We find that gcy-12 is expressed, and required, in both AWC neurons to regulate odor response plasticity only in AWCOFF. We further show that disruption of AWC fate lateralization results in loss of asymmetry in the response plasticity in gcy-12 mutants. Our results indicate that symmetric neuronal response plasticity can arise from asymmetry in underlying molecular mechanisms, and suggest that lateralization of signaling pathways in defined conditions may enhance neuronal and behavioral flexibility.

Dynamic Inter-Modality Source Coupling Reveals Sex Differences in Children based on Brain Structural-Functional Network Connectivity: A Multimodal MRI Study of the ABCD Dataset
Background: Sex differences in brain development have been widely reported in both structural and functional domains, particularly during late childhood and adolescence. Prior studies have shown that males and females differ in gray matter volume, network connectivity profiles, and their associations with behavior and cognition. However, how these sex differences manifest in the coupling between brain structure and function remains less understood. In this study, we introduce dynamic inter-modality source coupling (dIMSC), an extension of our earlier inter-modality source coupling method (IMSC). While IMSC evaluates the coupling between source-based morphometry (SBM) from structural MRI (sMRI) and static functional network connectivity from resting-state fMRI (rs-fMRI), dIMSC incorporates the temporal dimension by linking SBM with dynamic functional network connectivity (dFNC). Objectives: This study investigated the transient coupling between dynamic FNC (dFNC) and sMRI gray matter volume over time, and compared sex differences in dFNC-sMRI coupling across brain regions in children. Methods: We used data from the Adolescent Brain Cognitive Development (ABCD) study, focusing on children aged 9-11 years. Structural MRI data were analyzed using SBM, applying independent component analysis (ICA) to extract gray matter sources. Resting-state fMRI data were processed to compute dFNC using a sliding window approach. For each subject, dIMSC was computed as the cross-correlation between the dFNC matrix and the SBM vector, resulting in a time-resolved vector that reflects the strength of structure-function coupling across components. Coupling values were categorized into positive, neutral, or negative based on a specific threshold. Sex differences in dFNC-sMRI coupling were evaluated using two-sample t-tests with correction for multiple comparisons. Results: Our analysis revealed significant sex-specific patterns, with males exhibiting stronger positive coupling in the postcentral gyrus and precuneus, whereas females showed stronger coupling in the inferior parietal lobule and middle frontal gyrus. Additional sex differences emerged in the neutral and negative coupling domain, with males demonstrating stronger coupling in the superior temporal gyrus, calcarine gyrus, and superior parietal lobule, whereas females exhibited stronger coupling in the caudate nucleus, cerebellum, and inferior parietal lobule. Conclusion: Together these findings suggest distinct coupling in brain structure-function coupling between sexes, potentially reflecting sex-specific organization of functional networks and their structural substrates. The dIMSC method advances our earlier work by enabling time-resolved analysis of brain structure-function coupling, providing a powerful framework for investigating neurodevelopmental processes.

A Mechanistic Whole Brain Model to Capture Simultaneous EEG-fMRI Data
This study introduces a novel oscillatory network model to simulate simultaneous EEG-fMRI data, addressing the reconstruction challenge that arises due to their contrasting spatiotemporal scales. Here, each brain region is modelled by two oscillator clusters: a cluster of low-frequency (LFO) and high-frequency Hopf oscillators (HFO) coupled with an innovative power-coupling rule, facilitating cross-frequency interactions. The model is trained in two stages: learning oscillator frequencies and phase relations using a biologically plausible complex-Hebbian rule in the first stage, followed by a modified complex backpropagation for amplitude approximation, overcoming limitations of poor accuracy and computational complexity in existing models. This framework outperforms current methods in replicating empirical Functional Connectivity (FC), Functional Connectivity Dynamics (FCD), and modularity over disparate spatio-temporal scales. The correlation between the FC of fMRI and the FCs of various EEG frequency bands is reflected in the strengths of the LFO-HFO coupling. Furthermore, in-silico structural perturbation studies quantified the effect of pruning of the anatomical connectivity on spatiotemporal dynamics in terms of FC, FCD, modularity, and integration level (ISOR). The model's ability to reconstruct simultaneous EEG-fMRI data showcases significant advancement in understanding the resting-state brain's functionality from multimodal settings and deciphering neurological disorders in diverse spatiotemporal scales.

Subunit-specific roles of LRRC8 proteins in determining glutamate permeability of astrocytic volume-regulated anion channels
Volume-regulated anion channels (VRACs) are ubiquitous chloride channels that play a crucial role in cell volume regulation but are also involved in many other physiological processes. VRACs are heteromers of proteins from the leucine-rich repeat-containing family 8 (LRRC8A-E), with LRRC8A being essential. Other LRRC8 subunits are expressed in a cell type-specific manner and modulate the biophysical properties of VRACs, including permeability to small signaling molecules. Here, we used primary astrocyte cultures from wild-type and genetically modified C57BL/6 mice to investigate (i) LRRC8 subunit composition of endogenous VRACs in the brain and (ii) the subunit determinants of VRAC permeability to the excitatory neurotransmitter glutamate. qPCR and RNA-seq revealed high expression of Lrrc8a-d in mouse forebrain and astrocytes. As expected, Lrrc8a deletion abolished VRAC activity, measured as swelling-activated release of the glutamate analogue D-[3H]aspartate. RNAi knockdown of individual subunits established that LRRC8A and LRRC8C are key components of astrocytic glutamate-permeable VRACs, with their siRNAs reducing radiotracer release by 85% and 56%, respectively. Downregulation of LRRC8D had a moderate effect, which depended on the severity of swelling. Combined silencing of LRRC8C and LRRC8D suggested that these subunits act in distinct channel populations. LRRC8B silencing alone was ineffective but partially rescued glutamate release in LRRC8C- or LRRC8D-knockdown cells. Overall, these findings indicate that astrocytic glutamate-permeable VRACs are primarily composed of LRRC8A and LRRC8C, with a possible structural role for LRRC8B. The refined understanding of VRAC subunit composition may inform the development of targeted VRAC inhibitors to mitigate glutamate excitotoxicity in neurological disorders.

Reducing type II error: Sample size affects fMRI cluster-extent threshold to correct for multiple comparisons
Many procedures to correct for multiple comparisons in functional magnetic resonance imaging (fMRI) analysis require a minimum cluster-extent threshold; however, sample size is often not modeled. In the present study, a series of simulations was conducted where sample size was varied to determine whether this parameter affected cluster threshold. The primary hypothesis was that modeling sample size in the simulations would reduce cluster thresholds. A secondary hypothesis was that this reduction in cluster size was due to between-subject variability, which was tested by eliminating the corresponding standard error term. Whole-brain acquisition volume parameters were fixed, while the following key parameters were varied to reflect commonly employed ranges: sample size (N = 10, 20, or 30), corrected p-value (.05, .01, or .001), individual-voxel p-value (.01, .005, or .001), FWHM (3, 5, or 7 mm), and voxel resolution (2 or 3 mm). Each simulation consisted of 100 iterations repeated 100 times, with a total of 4,860,000 iterations and 66,420,000 simulated subjects. There was a significant effect of condition; clusters were approximately 18% smaller with versus without N modeled (and there was a significant increase in cluster thresholds for larger sample sizes). Bayesian analysis provided very strong support for the secondary hypothesis. The present findings indicate that sample size should be incorporated into all methods to provide the most accurate thresholds possible and reduce type II error. A broader range of topics is discussed including balancing type I and type II error along with the fallacy that non-task fMRI activity reflects null data.

A left-to-right bias in spatial numerical associations with dots and symbols
Number and space are intertwined in human and non-human cognition. A substantial body of research has shown that numerical magnitudes are mentally represented along a spatial continuum, akin to a ''mental number line''. Some suggested that its directionality is determined by culture and context. Nevertheless, evidence from preverbal infants and non-human animals indicates a consistent left-to-right directional mapping of numerosities, suggesting a biologically predisposed Spatial-Numerical Association (SNA) that may precede cultural factors. A recent study has shown that an implicit association between ''left'' and ''small''emerges not only in literate adults, but also in unschooled indigenous populations and preschool Western children. This finding suggests that SNAs may originate from universal innate mechanisms rather than being solely a by-product of cultural learning. However, while the study reported a strong association between ''left'' and ''decreasing'' numerosity, there was only a very weak association between ''right'' and ''increasing'' numerosity. This asymmetry was not predicted and needs further investigations to be understood. Here we further investigated the number/space association in implicit tasks in educated Western adults by using more variable and better controlled stimuli compared to the ones used in the previous study, and also manipulating stimulus format, using both dot patterns and symbolic numbers. Fifty-one adult participants performed a numerical comparison task within a Go-No-Go paradigm on subsequent pairs of visual stimuli (with ratios spanning from 0.75 to 0.94) that could appear on the left or on the right of a fixation point and completed two different tasks: ''press when more'' and ''press when less''. Results revealed distinct response patterns depending on the symbolic/non-symbolic nature of the stimuli. When non-symbolic stimuli were used, a consistent association between small numerosities and the left side and large numerosities and the right side was observed. When symbolic stimuli were used, only an association between large numerosities and the right side was observed. These findings support the hypothesis that SNAs may reflect a biological predisposition associated with brain asymmetry, and that task demands may interact with the underlying hemispheric specializations

Neurotrophin-3 produced by motor neurons non-cell autonomously regulate the development of pre-motor interneurons in the developing spinal cord
The development of multicellular organisms requires proper interplays between cell-autonomous genetic programs controlled by combinations of transcription factors that regulate the differentiation of distinct cell populations and non-cell autonomous processes that coordinate the proliferation, the fate, the survival, the respective location, and the proper interactions of these populations. During the development of the nervous system, non-cell autonomous mechanisms determine neuronal fate, survival, distribution, axon guidance, and connectivity. Although similar processes are suggested to be at work in the formation of spinal motor circuits, the molecular mechanisms involved remain mostly elusive. Here, we provide evidence that the Onecut transcription factors regulate a non-cell autonomous mechanism that modulate pre-motor interneuron development. We show that conditional inactivation of the Onecut factors in spinal motor neurons affects the differentiation and the positioning of pre-motor interneuron populations. We identify that Neurotrophin-3 produced by motor neurons under the control of the Onecut factors non-cell autonomously regulate the production and the distribution of pre-motor interneuron populations. Thus, we elucidated one of the non-cell autonomous mechanisms that coordinate the formation of the spinal motor circuits.

Hippocampal Synchrony Dynamically Gates Cortical Connectivity Across Brain States
Memory consolidation is thought to rely on hippocampo-cortical dialogue orchestrated by three cardinal sleep oscillations: cortical slow oscillations, thalamic spindles, and hippocampal sharp-wave ripples. However, how hippocampal outputs are routed to specific cortical targets and dynamically regulated across brain states remains incompletely understood. Here, we performed simultaneous multisite recordings from the dorsal and ventral hippocampus, and frontal and parietal cortex in rats alternating between wakefulness and sleep. Frontal slow oscillations operated as a global clock, resetting thalamic circuits and initiating spindle volleys that propagated from anterior to posterior cortex, while parietal slow oscillations more effectively recruited hippocampal ripples. Hippocampal ripples reflected anatomical connectivity, as dorsal ripples preferentially enhanced parietal spindles, whereas ventral ripples engaged mainly frontal spindling. Notably, when ripples synchronized in dorsal and ventral hippocampus, local excitatory drive sharply decreased and neuronal spiking redistributed, associated cortical slow oscillations and spindle responses diminished, and cortical neuronal reactivation was suppressed, indicating that dorso-ventral ripple synchrony gates, rather than amplifies, hippocampo-cortical communication. This gating effect was most evident through interactions with brain state, as dorsal-driven reactivation persisted across vigilance states, while ventral pathways were more pronounced during sleep. Collectively, our results outline a multilayer architecture in which slow oscillations provide a global temporal scaffold, spindles implement anatomically specific reactivation channels, and ripple coordination gates hippocampo-cortical communication, likely shaping the precision and specificity of memory consolidation within a highly variable neural substrate.

Glucose Metabolism echoes Long-Range Temporal Correlations in the Human Brain
Intrinsic brain activity is characterized by pervasive long-range temporal correlations. While these scale-invariant dynamics are a fundamental hallmark of brain function, their implications for individual-level metabolic regulation remain poorly understood. Here, we address this gap by integrating resting-state functional Magnetic Resonance Imaging (fMRI) and dynamic [18F]FDG Positron Emission Tomography (PET) data acquired from the same cohort of participants. We uncover a systematic relationship between long-range temporal correlations, quantified via the Hurst exponent, and glucose metabolism. Our findings reveal that persistent temporal dependencies impose a measurable metabolic cost, with brains exhibiting higher long-range temporal correlations incurring greater energetic demands. Beyond glucose metabolism, we also show that these dynamics are likely supported by continuous biosynthetic processes, such as protein synthesis, which are critical for neural circuit maintenance and remodeling. Overall, our results suggest that a significant fraction of the brains so-called "Dark Energy" is actively spent to power spontaneous long-range temporal correlations.

Striatal pathways oppositely shift cortical activity along the decision axis
The cortex and basal ganglia are organized into multiple parallel loops that serve motor, limbic, and cognitive functions. The classic model of cortico-basal ganglia interactions posits that within each loop, the direct pathway of the basal ganglia activates the cortex and the indirect pathway inhibits it. While this model has found support in the motor domain, whether opponent control by the two pathways extends to the cognitive domain remains unknown. Here, we record from anterior cingulate cortex (ACC) and dorsomedial striatum (DMS) while inhibiting direct or indirect pathway neurons in DMS, as mice perform an accumulation-of-evidence task. Inconsistent with the classic model, the manipulations do not produce opponent changes in overall ACC activity. Instead, the pathways exert opponent influence over a subpopulation of ACC neurons that encode accumulated sensory evidence, the task-relevant decision variable. The direction of the modulation depends on a neurons tuning to ipsilateral versus contralateral evidence, such that the two pathways generate opponent shifts in coding specifically along the decision axis. Thus, our results uncover unexpected specificity in the effects of basal ganglia pathways on the cortex, with the two pathways of the DMS exerting opponent control not on overall activity but on coding of the relevant task variable. This functional specificity may extend to other basal ganglia loops to support different aspects of adaptive behavior, with the pathways serving a general role in selecting and shifting cortical representations to subserve circuit-specific functions.

Motor prediction reduces beta-band power and enhances cerebellar-somatosensory connectivity before self-touch to enable its attenuation
Prevailing theories suggest that the brain uses an internal forward model to predict tactile input during voluntary movements, thereby reducing the intensity of the reafferent tactile sensation, a phenomenon known as self-touch attenuation. Although self-touch attenuation is a well-documented effect, it remains unclear how prediction-related neural mechanisms drive the attenuation prior to the actual self-touch input. In this study, we used magnetoencephalography (MEG) to examine the neural correlates of self-touch prediction. Participants performed a self-touch task with two control conditions. In one control, the touch was externally generated without any movement. In the other, the moving and the touched hands were spatially misaligned, thereby disrupting the sensorimotor alignment of self-touch. Self-touch evoked weaker early somatosensory activity (M50 component) than both control conditions. A psychophysics task also mirrored the pattern of neural attenuation, as the perception of self-touch was attenuated compared to the two control conditions. To isolate predictive neural mechanisms from general movement-related activity, we subtracted activity from corresponding stimulus-absent trials. To further refine the signal specific to predictive processing in self-touch, we compared self-touch with misaligned touch, the two conditions that both involved voluntary movement but differed in their prediction of self-touch. This revealed greater pre-stimulus beta-band desynchronization and increased cerebellar-to-somatosensory connectivity prior to self-touch compared to misaligned touch. Our results provide the first evidence of predictive neural activity that shapes the sensory consequences of self-touch, offering insight into the mechanisms through which predictive models modulate somatosensory processing.

UBR-1 enzyme network regulates glutamate homeostasis to affect organismal behavior and developmental viability
Johanson-Blizzard Syndrome (JBS) is an autosomal recessive spectrum disorder associated with the UBR-1 ubiquitin ligase that features developmental delay including motor abnormalities. Here, we demonstrate that C. elegans UBR-1 regulates high-intensity locomotor behavior and developmental viability via both ubiquitin ligase and scaffolding mechanisms. Super-resolution imaging with CRISPR-engineered UBR-1 and genetic results demonstrated that UBR-1 is expressed and functions in the nervous system including in pre-motor interneurons. To decipher mechanisms of UBR-1 function, we deployed CRISPR-based proteomics using C. elegans which identified a cadre of glutamate metabolic enzymes physically associated with UBR-1 including GLN-3, GOT-2.2, GFAT-1 and GDH-1. Similar to UBR-1, all four glutamate enzymes are genetically linked to human developmental and neurological deficits. Proteomics, multi-gene interaction studies, and pharmacological findings indicated that UBR-1, GLN-3 and GOT-2.2 form a signaling axis that regulates glutamate homeostasis. Developmentally, UBR-1 is expressed in embryos and functions with GLN-3 to regulate viability. Overall, our results suggest UBR-1 is an enzyme hub in a GOT-2.2/UBR-1/GLN-3 axis that maintains glutamate homeostasis required for efficient locomotion and organismal viability. Given the prominent role of glutamate within and outside the nervous system, the UBR-1 glutamate homeostatic network we have identified could contribute to JBS etiology.

Engineering substantia nigra-like dopaminergic neurons in human midbrain organoids through WNT modulation and bioreactor culture
Human midbrain organoids (hMOs) derived from induced pluripotent stem cells represent a promising model for Parkinson's disease (PD). However, current protocols often fall short in producing mature, regionally specified dopaminergic (DA) neurons that faithfully recapitulate disease-relevant vulnerabilities. Here, we present a differentiation strategy combining tri-phasic WNT signaling modulation with dynamic bioreactor culture to enhance DA neuron yield, regional identity, and functional maturation within hMOs. This approach generated DA neurons with enriched substantia nigra-like features, increased dopamine release, and robust electrophysiological activity. Single-cell transcriptomic analysis revealed upregulation of synaptic, metabolic, and neuroprotective pathways, alongside reduced expression of stress and pro-apoptotic signatures in DA neurons. Importantly, these hMOs demonstrated vulnerability upon exposure to alpha-synuclein preformed fibrils and proteinase K-resistant aggregates, effectively modeling PD-associated pathology. Altogether, our platform offers a scalable and physiologically relevant system for investigating PD mechanisms, enabling therapeutic screening, and supporting the advancement of cell replacement strategies.

Metabolic and behavioral effects of neurofibromin result from differential recruitment of MAPK and mTOR signaling
Neurofibromatosis type 1 results from mutations in the Neurofibromin 1 gene and its encoded neurofibromin protein. This condition produces multiple symptoms, including tumors, behavioral alterations, and metabolic changes. Molecularly, neurofibromin mutations affect Ras activity, influencing multiple downstream signaling pathways, including MAPK (Raf/MEK/ERK) and PI3K/Akt/mTOR signaling. This pleiotropy raises the question of which pathways could be targeted to treat the disease symptoms, and whether different phenotypes driven by neurofibromin mutations exhibit similar or diverging dependence on the signaling pathways downstream of Ras. To test this, we examined metabolic and behavioral alterations in the genetically tractable Drosophila neurofibromatosis type 1 model. In vivo genetic analysis revealed that behavioral effects of neurofibromin were mediated by MEK signaling, with no necessity for Akt. In contrast, metabolic effects of neurofibromin were mediated by coordinated actions of MEK/ERK and Akt/mTOR/S6K/4E-BP signaling. At the systemic level, neurofibromin dysregulated metabolism via molecular effects of Nf1 in interneurons and muscle. These changes were accompanied by altered muscle mitochondria morphology, with no concomitant changes in neuronal ultrastructure or neuronal mitochondria. Overall, this suggests that neurofibromin mutations affect multiple signaling cascades down-stream of Ras, which differentially affect metabolic and behavioral neurofibromatosis type 1 phenotypes.

A spinal origin for the obligate flexor synergy in the non-human primate: Implications for control of reaching
Stroke survivors frequently develop the flexor synergy, an obligate co-contraction of shoulder abductors and elbow flexors; the neural substrate has proven elusive. Here we trained healthy monkeys to generate isometric elbow and shoulder torques to move an on-screen cursor, and recorded neuron firing from motor cortical areas and the reticular formation. In all regions we found cells correlated with activity around a single joint. Neurons coding co-contractions showed a bias towards combinations orthogonal to the post-stroke flexor synergy, e.g. shoulder abduction with elbow extension. Threshold microstimulation in the spinal cord but not in either motor cortex or the reticular formation generated coactivation aligned to the flexor synergy. We suggest the evolution of prehension required descending systems either to control or bypass locomotion-dedicated spinal circuits. Loss of descending input after stroke constrains the upper limb to spinal synergies best suited to primitive locomotor functions.

Norepinephrine stimulates protein synthesis in astrocytes
Norepinephrine is a neuromodulator that can activate multiple subcellular signalling pathways to regulate various physiological responses in different cell types. In astrocytes, it is known to have a wide range of metabolic effects, including regulation of glucose uptake and glycolysis, glycogen breakdown and lactate production. Here we report that norepinephrine stimulates protein synthesis in rat primary cortical astrocytes and the C6 glioma cell line. The mTOR-pS6K pathway is engaged during the norepinephrine-mediated induction of protein synthesis, which is abolished by mTOR inhibition and appears to be mediated mainly by {beta}-adrenergic receptors. We show that blocking glycolysis with 2-deoxy-D-glucose inhibits both basal and norepinephrine-induced translation in astrocytes. Finally, we demonstrate that the norepinephrine-mediated increase in protein synthesis is preceded by a decrease in astrocytic ATP levels. Our results reveal a novel regulatory role for norepinephrine in the central nervous system, tightly controlling protein synthesis in astrocytes.

NanoString Technologies Neuropathology Panel Produces Unreliable Measurements of Mouse Hippocampal Gene Expression
Technologies for measuring gene expression (i.e., the number of RNA transcripts) of large numbers of genes simultaneously in specific tissues have exploded in recent years. Current methods include high-throughput RNA sequencing (RNA-seq), transcript counting platforms like NanoStrings nCounter, and spatially resolved techniques based on fluorescent in situ hybridization (FISH). Several studies have evaluated the reliability of these different methods and performance in comparison to one another. Typically, technical reliability, as measured by Pearsons correlation of two measurements of the same sample, is usually well above 90%, and is statistically significant even for small sample sizes (e.g., 8 samples measured twice). We performed an experiment where we aimed to compare hippocampal gene expression between 3 groups (n=5 per group) of young adult male C57BL/6J mice. Before sampling, the groups were treated with either repeated injections of PBS (vehicle), extracellular vesicles taken from the blood plasma of sedentary mice (SedVs) or exercising mice (ExerVs). The hippocampus was dissected, and RNA purified using standard methods. The samples were analyzed using the NanoString Neuropathology panel, that measures 770 genes simultaneously. To estimate reliability, we measured 8 of the samples twice in two separate assays. Surprisingly, only 85 genes showed a significant Pearsons correlation (p<0.05), and none of these met false discovery significance (all q<0.05). To confirm that no errors were made transferring labels, the individual samples were permuted to see whether a different assignment could recover a greater number of positive correlations. Results showed that the original assignment was best suggesting no errors in sample assignments were made. We conclude that the Nanostring neuropathology panel produces unreliable data for mouse hippocampal gene expression.

Disruption of Reelin signaling in a dual-hit mouse model of schizophrenia: impact of postnatal Δ9-tetrahydrocannabinol exposure in a maternal immune activation model
Since the discovery of the first antipsychotic, pharmacological treatment of schizophrenia (SCZ) has primarily relied on agents that block D2 dopamine receptors. However, due to variability in patient responses, there is a pressing need to identify new biomarkers and therapeutic strategies. In this context, we have developed a dual-hit mouse model that combines maternal immune activation (MIA) induced by polyinosinic-polycytidylic acid (Poly(I:C)) and postnatal exposure to {Delta}9-tetrahydrocannabinol (THC), the psychoactive component of cannabis. We assessed the face validity of this model and investigated potential alterations in the Reelin signaling pathway. Our findings show a reduction in Reelin levels, a new potential key biomarker of SCZ, in the prefrontal cortex of male mice treated with THC compared to the dual-hit group, and across all treatment groups compared to controls in females. Additionally, a decrease in the number of Reelin+ cells was observed across these groups. The dual-hit model exhibited phenotypes indicative of positive symptoms in males, as well as phenotypes associated with negative symptoms in both sexes. Furthermore, the model demonstrated reduced cortical thickness in THC-treated groups, alongside decreased dendritic spine density in both the prefrontal cortex and hippocampus in the dual-hit group.

MeCP2 regulates cell type-specific functions of depressive-like symptoms in the nucleus accumbens
MeCP2 (methyl CpG binding protein 2) is a transcriptional regulator that modulates gene expression in response to environmental stimuli. Although recent studies have implicated MeCP2 in stress responses and depression, its precise role is not completely understood. In this study, we identify a cell type-specific function of MeCP2 in the regulation of depression-like symptoms within the nucleus accumbens (NAc), a key brain region for emotional and stress processing. We observed differential MeCP2 expression in distinct cell populations of the NAc following chronic restraint stress (CRS) and investigated the behavioral and electrophysiological consequences of cell type-specific MeCP2 manipulation. We also explored the molecular mechanisms by which MeCP2 alleviates depression-like symptoms in the NAc and associated neural circuit regions through cell type-specific profiling of the spatial transcriptome. Our findings demonstrate that MeCP2 contributes to synaptic and circuit-level regulation in a cell type-specific manner within the NAc and ultimately mitigates CRS-induced depression-like behaviors.

The Alzheimer's-Associated SORL1 p.Y1816C Variant Impairs APP Sorting, Axonal Trafficking, and Neuronal Activity in iPSC-Derived Brain Models
Background: SORL1, encoding the sorting receptor SORLA, is now recognized as the fourth autosomal dominant Alzheimer's disease (AD) gene. Loss of SORLA function is known to disrupt endosomal trafficking and enhance amyloidogenic APP processing, two key aspects of the onset and progression of AD. However, the pathogenic consequences of disrupted endolysosomal pathways, deregulated protein sorting, as well as the effects of specific SORL1 missense variants on human neuronal function, still remain understudied. Methods: Our investigations were performed using two complementary human iPSC-derived models: 2D NGN2-induced neurons and 3D cerebral organoids established from isogenic wild-type (WT), SORL1 p.Y1816C (KI) missense variant, and SORL1 knock-out (KO) cells. We analyzed SORLA maturation and ectodomain shedding, APP localization, and amyloid-{beta} secretion. Endosomal morphology and neuritic swellings were assessed via electron microscopy, while axonal transport of APP and Rab5+ endosomes was evaluated through live-cell imaging. Neuronal network activity was measured using multielectrode array recordings. Results: Our results demonstrate that the p.Y1816C variant leads to impaired SORLA maturation and reduced shedding, without affecting neuronal or organoid differentiation. Notably, we show an ultrastructure of endosomes, including their content, and demonstrate that both KO and KI models exhibit early endosome enlargement, increased APP retention in endosomes, elevated A{beta}40/42 secretion, and amyloid-{beta} deposition in 3D organoids. Importantly, we identified previously uncharacterized functional consequences of abolished SORLA activity, including axonal swellings and significantly impaired transport of Rab5+ endosomes and APP, characterized by deregulated velocities, directionality of transport, and increased stalling. Additionally, we discovered that both KO and p.Y1816C KI neurons exhibit abnormal electrophysiological activity, including increased spontaneous firing, burst frequency, and network synchrony. Conclusions: Our study defines the mechanistic consequences of the SORL1 p.Y1816C variant and demonstrates its pathogenicity in human neurons. Importantly, we also identify novel roles for SORLA in maintaining axonal transport homeostasis and regulating neuronal excitability, expanding its functional relevance beyond endosomal APP processing. These findings reinforce the central role of endosomal trafficking disruption in AD and support the use of isogenic human models for evaluating AD risk variants.

Recurrent connectivity supports carbon dioxide sensitivity in Aedes aegypti mosquitoes
The mosquito Aedes aegypti's human host-seeking behavior depends on the integration of multiple sensory cues. One of these cues, carbon dioxide (CO2), gates odorant and heat pathways and activates host-seeking behavior. The neuronal circuits underlying processing of CO2 information remain unclear. We used automated serial-section transmission electron microscopy (EM) to image and reconstruct the circuitry of the glomeruli that are innervated by the Ae. aegypti maxillary palp, including the glomerulus that responds to CO2. Notably, CO2-sensitive olfactory sensory neurons (OSNs) make high levels of recurrent synaptic connections with one another, while making a low density of feedforward synapses. At some of these contacts between CO2 OSNs, we observe ribbon-like presynaptic structures, which may further enhance recurrent signaling. We compared both feedforward and recurrent connectivity with all olfactory glomeruli in Drosophila melanogaster, and we found more recurrent connections between the Ae. aegypti CO2-responsive OSNs than in any D. melanogaster glomeruli. We developed a computational circuit model that demonstrates recurrent synapses are necessary for robust CO2 detection under normal physiological conditions. Together, elevated levels of recurrent connectivity and ribbon-like structures may amplify sensory information detected by CO2-sensitive OSNs to support mosquito activation and sensitization by CO2, even in the presence of high levels of other odorants in the environment. We propose that this circuit organization supports the salience of CO2 as a mosquito host cue.

Minimal Impact of Low Vision on Explicit Sensorimotor Adaptation
Rehabilitation from motor system dysfunction relies on learning deliberate motor corrections through practice and feedback. This is called explicit motor adaptation. One key source of feedback for this adaptation is the visual error signal between the intended movement and the achieved movement. As people age, both motor dysfunction and visual impairment become more common, potentially compromising the visual feedback signal. Previous work has shown that visual impairment can disrupt the implicit, automatic adjustments made by the sensorimotor system. But how visual impairment influences the explicit motor adaptation, a cornerstone of rehabilitation, remains unknown. To address this gap, we recruited individuals with low vision - defined as uncorrectable visual impairment resulting in functional vision loss - and age-matched controls to complete a visuomotor task designed to isolate two components of explicit motor adaptation: discovering a new deliberate sensorimotor strategy and recalling a previously learned one. Surprisingly, low vision had no measurable impact on either component. Despite reduced visual fidelity, individuals with low vision were as effective as controls in both discovering and retrieving successful explicit sensorimotor strategies. These results highlight potential mechanisms that can be leveraged in rehabilitation.

Vision and touch used for catching small balls with a power grip and large balls with a precision grip supports dual visuomotor channel theory
The dual visuomotor channel theory of grasping posits that distinct neural pathways mediate hand shaping in response to a target's extrinsic (e.g., location) and intrinsic (e.g., size and shape) properties. To evaluate this theory, we examined grasp behavior in human participants as they caught balls of four diameters (2.5 to 9 cm) thrown toward them. Hand shaping during catching was compared with that observed during the pickup of stationary balls and the interception of rolling balls. Kinematic measures included digit opposition distance (thumb pad to index finger pad) and prehension span (digit pad to palm distance), obtained using electromagnetic sensors, 3D video capture, and frame-by-frame video analysis. Participants displayed significantly greater hand opening when catching thrown balls than when interacting with static or rolling balls. Nonetheless, the maximum pregrasp aperture (MPA), contact grasp aperture (CGA), and terminal grasp aperture (TGA) scaled proportionally with ball size across all conditions. Ball size further influenced grasp type: small thrown balls were caught with power grips, while larger balls were caught with precision grips. In contrast, precision grips were used consistently when picking up stationary balls or grasping intercepting rolling ones. In the catching condition, grasp type and the trajectory of digit closure were also affected by the location of ball to hand contact. These findings support the dual visuomotor channel theory by demonstrating that anticipatory hand opening reflects target location, whereas grip selection reflects target size. Moreover, the modulation of grasp type and digit closure by tactile contact suggests that somatosensory input may operate within a dual-channel framework analogous to that of vision.

Low-frequency brain oscillations reflect the dynamics of the oculomotor system: a new perspective on subsequent memory effects
Neural activity and eye movements are two well-established predictors of memory performance in humans. Successful memory formation is typically associated with reduced alpha/beta power (i.e., the alpha/beta subsequent memory effect) and an increased number of eye movements. However, the functional relevance of these two memory correlates has primarily been investigated in isolation, leaving their coupling and combined contribution to memory formation largely unknown. Here, we address this gap through four experiments involving simultaneous eye-tracking and scalp or intracranial electroencephalography recordings while participants viewed scenes either freely or under varying levels of visual constraint. Across experiments and cohorts, we identified the degree of visual exploration, rather than subsequent memory performance, as the consistent and robust modulator of alpha/beta power reductions. Moreover, we show that saccade parameters predicted the dynamics of alpha/beta activity, and that the accumulation of saccades over time accounted for the reduced alpha/beta power. Our work demonstrates that neglecting eye movements results in an incomplete understanding of the alpha/beta subsequent memory effect. Together, the evidence points at alpha/beta activity directly reflecting eye movements, and only indirectly, memory formation. The current study thus bridges two lines of previous research and advocates for new perspectives on the specific interpretation of the alpha/beta subsequent memory effect and on the function of alpha/beta activity in general.