bioRxiv Subject Collection: Neuroscience's Journal

Adaptation in somatosensory afferents improves rate and temporal coding of vibrotactile stimulus features
Adaptation is a common neural phenomenon wherein sustained stimulation evokes fewer action potentials (spikes) over time. Rather than simply reduce firing rate, adaptation may help neurons form better (i.e. more discriminable) representations of sensory input. To study effects of adaptation in low-threshold mechanoreceptors (LTMRs), we recorded single unit LTMR responses to 30-second-long vibrotactile stimuli with different intensities and frequencies applied to the hind paw of rats. To assess the impact of adaptation on somatosensory encoding, decoders were applied to the initial and late (adapted) phases of population-level responses to assess the decodability (discrimination) of stimulus intensity and frequency. Adaptation-mediated changes in the rate and timing (phase-locking) of spikes were quantified. Rate coding of stimulus intensity was improved by the nonuniform reduction in firing rate across responses to different stimuli, and across neurons. This improvement was absent in simulations with uniform reductions in firing rate, thus revealing the necessity of stimulus-dependent variability in adaptation effects. Spike timing (quantified as interspike intervals) remained highly informative about stimulus frequency throughout stimulation despite the progressive reduction in spike count over time. When the drop in spike count was accounted for, adaptation was found to improve temporal coding of stimulus frequency by increasing the precision of phase-locking. In other words, adaptation improved the precision of spike timing, and this increased the information about stimulus frequency conveyed by each spike. These results show that adaptation, by modulating spiking in different ways, can improve encoding of different stimulus features using different coding schemes.

Unveiling the Developmental Dynamics and Functional Role of Odorant Receptor Co-receptor (Orco) in Aedes albopictus: A Novel Mechanism for Regulating Tuning Odorant Receptor Expression
As one of the most aggressive disease vectors, the Asian tiger mosquito Aedes albopictus relies heavily on its olfactory system to search for food in the larval stage, locate hosts after eclosion, and identify suitable oviposition sites after blood feeding. In mosquitoes and other insects, the olfactory system detects environmental odors primarily through a diverse repertoire of tuning odorant receptors (ORs), which require the highly conserved odorant receptor co-receptor (Orco) to function. While Orco's role in enabling tuning receptor function is well established, its cellular localization patterns, developmental expression dynamics, and system-wide impact on olfactory physiology and behavior remain understudied in Ae. albopictus. To address this knowledge gap, we leveraged the Q-system to systematically characterize Orco-expressing neurons (ORNs) across embryonic, larval, pupal and adult stages of Ae. albopictus. We uncovered a dramatic reorganization of the olfactory system during metamorphosis: ORNs were observed as early as the embryonic stage and expanded during larval development before rapid degeneration and re-generation in the pupal stage resulting in the final population of adult ORNs. Orco expression in adults spanned the olfactory neurons of the antennae, labella, and maxillary palps in both male and female mosquitoes, consistent with its conserved peripheral distribution. To further investigate the functional implications of Orco, we generate Orco knockout mutants and strikingly discovered that Orco knockout mutants displayed significant widespread downregulation of tuning Ors, suggesting that Orco may influence OR expression or stability. Electrophysiological recordings confirmed significantly attenuated responses to human volatiles in Orco mutants, and behavioral assays demonstrated a marked decline in blood-feeding efficiency and elimination of host preference in females. Together, these findings reveal dynamic reorganization of ORNs during mosquito development and uncover the critical role of Orco in maintaining the integrity and function of the olfactory system, providing insights which may inform novel, next-generation vector control strategies.

NT5DC2 downregulation suppresses monoamine oxidase activity and increases catecholamine levels in PC12D cells
Back ground Genome-wide association studies have revealed the involvement of 5'-nucleotidase domain-containing protein 2 (NT5DC2) in neuropsychiatric disorders such as schizophrenia and bipolar disorder; however, its function remains unclear. Recently, we found that NT5DC2 downregulation in PC12D cells increases catecholamine synthesis by promoting the activity of tyrosine hydroxylase and that monoamine oxidase A (MAO A) might bind to NT5DC2 using Affinity Purification-Mass Spectroscopy. Methods and Results We investigated the role of NT5DC2 for MAO A activity in PC12D cells. Western blot analysis revealed that NT5DC2 primarily binds to the non-phosphorylated form of MAO A. siRNA-mediated NT5DC2 downregulation reduced MAO A activity, leading to decreased dopamine metabolism and increased noradrenaline synthesis. Conclusion Our findings suggest that NT5DC2 could affect both tyrosine hydroxylase and MAO A activity to control catecholamine synthesis. Therefore, our study provides valuable insights into disorders associated with catecholamine dysregulation, such as Parkinson's disease and neuropsychiatric disorders.

Region-specific Brain Targets Drive Circuit Formation and Maturation of Human Retinal Ganglion Cells
Human vision relies on retinal ganglion cells (RGCs), and their connectivity with distinct brain regions enables higher order visual processing. RGCs vary considerably between species, and small model organisms display distinct RGC innervation patterns from that in humans. There is thus a need for robust models of human RGC circuit formation that preserves innervation specificity. Here, we developed an in vitro microfluidics eye-to-brain connectivity model using human pluripotent stem cell (hPSC)-derived RGCs to assess brain region-specific connectivity features. We find that cultured human RGCs segregate their dendrites and axons and display axonal features that align with that of their in vivo human RGC counterparts. The addition of region-specific brain targets to human RGC axons terminals resulted in differential RGC connectivity with distinct retinorecipient brain regions. Increased synapse formation occurred between RGCs and lateral geniculate neurons relative to that with superchiasmatic nucleus neurons, mirroring in vivo innervation differences. Both retinorecipient partners induced the formation of more synapses relative to non-retinorecipient brain target controls. These results suggest that human RGC innervation properties are preserved in culture systems and that human RGCs can differentially sense and respond to retinorecipient targets to control wiring outcomes. These systems may aid in the discovery of human-specific wiring factors for potential therapeutic applications.

Spatial Richness of Neural Magnetic Fields
Brain implants that measure neural magnetic fields, rather than electrical potentials, are expected to confer significant clinical advantages related to implant longevity and signal fidelity due to the elimination of the electrode-tissue interface. However, the informational differences between neural electrical potentials and magnetic fields remain poorly understood. Using a mathematical formalism based on neuronal current sources, we directly establish the complementary informational content of extracellular magnetic fields and electrical potentials. We then use computational modeling to illustrate how dense networks of neurons are easier to distinguish and spike sort on the basis of their magnetic, rather than electrical, spike templates. Lastly, we show how the solenoidal nature of neural magnetic fields facilitates approximate morphological reconstruction, even with sparse sensor arrays. Our findings highlight the unique experimental advantages of neural magnetic field sensing, motivating the development of compact, low-noise devices capable of meeting the stringent sensitivity requirements for single-shot cortical recordings.

Expectation modulates the hedonic experiences of and midbrain responses to sweet flavour
Non-nutritive sweeteners are sugar substitutes that may promote weight management by reducing an individual's calorie intake. It is, however, unclear whether (i) sugar and non-nutritive sweetener elicit distinct orosensory responses in the human brain, and (ii) whether the neural responses to these flavours are modulated by expectancy. Addressing these questions has direct relevance to our understanding of food choice behaviour and how it may be modified in dietary interventions. We screened N=99 healthy adults to select a sample (N=27, M[SD]age = 24.25[2.94] years) who reported similar perceptual experiences of sugar and sweetener, thus removing a potential confound of sensory differences, for fMRI scanning. While scanning, they received sugar- and artificially-sweetened beverages in two conditioning paradigms, which both manipulated participants expectation of flavour delivery: first in a probabilistic and second in a deterministic way. Participants ability to accurately distinguish sugar from non-nutritive sweetener depended largely on their expectations, which also significantly affected the perceived pleasantness of each flavour. Expectation altered brain responses to flavour delivery during the deterministic task only, where the (mistaken) expectation of sugar significantly increased midbrain responses to sweetener compared to when sweetener was expected. Trial-wise confidence and pleasantness ratings differentially augmented brain responses to sugar and sweetener delivery. These results highlight the importance of expectancy in both the behavioural and neural encoding of sweet flavour, particularly in the context of unreliable sensory information. The expectation of sugar appears to increase the subjective value of noncaloric sweetener, which may result from flavour-nutrient conditioning that preferentially reinforcers sugar.

Trpv1-dependent Cacna1b gene inactivation reveals cell-specific functions of CaV2.2 channels in vivo
Voltage-gated CaV2.2 channels underlie the N-type current, and they regulate calcium entry at many presynaptic nerve endings to control transmitter release. A role for CaV2.2 channels has been well-established in the transmission of pain information using pharmacological and global gene inactivated mouse models. However, investigation of the cell-specific actions of CaV2.2 channels would benefit from the availability of cell-restricted knockout mouse models and particularly in dissecting behavioral responses that depend on CaV2.2 channel activity. Here, we show the importance of CaV2.2 channels in Trpv1-lineage neurons in behavioral responses to sensory stimuli using Cre-dependent inactivation of the Cacna1b gene. Our work shows the cell-type specificity of CaV2.2 channels in mediating rapidly developing heat hypersensitivity and the utility of Cre-dependent inactivation of Cacna1b to discern cell-specific CaV2.2 channel functions.

Disruption of grin2A, an epilepsy-associated gene, produces altered spontaneous swim behavior in zebrafish
N-methyl-D-aspartate receptors (NMDARs) control synaptic plasticity and brain development in a manner determined by receptor subunit composition. Pathogenic variants in GRIN2A gene, encoding the NMDAR GluN2A subunit, can cause gain or loss of function of receptors containing the affected subunit, and are associated with intellectual disability and epilepsy in patients. While in-vitro studies of recombinant receptors have yielded some insights, animal experimental models are essential to better understand the relationship between the molecular pathology of the variants and the disease. Here we introduce a zebrafish model of GluN2A loss of function to study system-level effects of zebrafish grin2Aa and grin2Ab gene deletion. Our electrophysiological analysis revealed functional differences between receptors containing zebrafish GluN2Aa/b and GluN2Bb paralogs comparable to mammalian receptors containing GluN2A vs. GluN2B subunits. Both grin2Aa-/- and grin2Ab-/-, as well as double-knockout grin2A-/- zebrafish larvae showed increased locomotor activity in a novel environment. Proteomic analysis suggested that the relative proportion of GluN2B-containing NMDARs may be increased in grin2A mutant fish. Our results highlight fundamental similarities between zebrafish and mammalian NMDAR signaling and validate the use of zebrafish as a model organism to study the neurodevelopmental role of NMDARs. The newly created transgenic zebrafish strains complement the rodent models of GluN2A loss of function and can be used for high-throughput testing of pharmacological or genetic treatment strategies for patients with GRIN2A gene variants.

MAPT Splicing Modulators as a Therapeutic Strategy for Tauopathies
Tauopathies are neurodegenerative diseases characterized by the abnormal accumulation of microtubule-associated protein tau (MAPT) in the brain. These disorders, like frontotemporal dementia (FTD-Tau), currently lack effective therapies and can occur sporadically or be inherited when associated with MAPT gene mutations. The MAPT gene region encompassing exon 10 and adjacent introns is a hotspot for pathogenic variants, including splicing mutations that enhance exon 10 inclusion and increase 4R tau expression, and gain-of-function mutations that generate aggregation-prone mutant 4R tau protein. For these 4R-specific tauopathies, a targeted mRNA splicing approach that promotes exon 10 exclusion may offer therapeutic benefit. In this study, we discovered novel splicing modulator compounds (SMCs) that promote MAPT exon 10 exclusion, and demonstrated their efficacy in FTD patient-derived neuronal models carrying the tau-P301L gain-of-function mutation or the tau-S305N splicing mutation. Treatment with SMC reduced 4R tau expression and decreased the accumulation of hyperphosphorylated tau (pTau), oligomeric and insoluble tau, thereby rescuing tau-associated neuronal toxicity. Importantly, our lead SMC corrected the 3R/4R splice ratio in vivo and significantly reduced pTau in the brain of a gene-replacement (GR) mouse model expressing the human tau-N279K splicing mutation. These findings support the therapeutic potential of this class of small molecules and establish MAPT pre-mRNA splicing modulation as a promising strategy for the treatment of 4R tauopathies.

Repeated restraint stress-induced increase in post-surgical somatosensory hypersensitivity and affective responding is mediated by β-adrenergic receptor activation and spinal NLRP3-IL1β signalling in male rats
Pre-surgical stress is a well-recognised risk factor for persistent post-surgical pain, and while the precise underlying neurobiological mechanisms remain unknown, neuro-immune interactions are believed to play a pivotal role. Here, we investigated the effect of repeated restraint stress (RRS) on post-surgical somatosensory hypersensitivity and affective responding in male rats and examined underlying mechanisms mediating these effects. We showed that RRS induced behavioural despair in the forced swim test, reduced body weight gain and elevated faecal corticosterone levels in male Sprague-Dawley rats. Following paw-incision surgery, animals pre-exposed to RRS exhibited exacerbated mechanical and heat hypersensitivity, pain-related aversion, and anxiety-like behaviour compared to non-stress counterparts. RNAseq analysis revealed alterations in glial and neuro-immune pathways in the dorsal horn of the spinal cord in the RRS + paw incision group compared to paw incision alone, data further confirmed by increased microglial activity and inflammatory gene expression (iba1, itgam, il-1{beta} and nlrp3). Intrathecal administration of IL-1Ra or MCC950 (an NLRP3 inhibitor) attenuated the RRS-induced increase in pain-related aversion and mechanical hypersensitivity post-surgery. Chronic administration of RU486, a glucocorticoid receptor antagonist, prevented RRS-induced despair-like behaviour but did not alter the effects of RRS on pain-related aversion or mechanical hypersensitivity post-surgery. In contrast, chronic administration of propranolol, a {beta}-adrenergic receptor antagonist and sympathetic nervous system inhibitor, not only prevented the RRS-induced despair-like behaviour but also attenuated exacerbation of mechanical hypersensitivity, pain-related aversion, and anxiety-like behaviour post-surgery. These findings suggest that RRS exacerbates and prolongs post-surgical somatosensory and affective pain responding via {beta}-adrenergic receptor activation and increased spinal microglial NLRP3-IL1{beta} signalling. These data provide further insight into the mechanisms by which chronic stress and mood disorders exacerbate and prolong post-surgical pain.

Neural Networks and Foundation Models: Two Strategies for EEG-to-fMRI Prediction
Electroencephalography (EEG) and functional Magnetic Resonance Imaging (fMRI) are two widely used neuroimaging techniques, with complementary strengths and weaknesses. Predicting fMRI activity from EEG activity could give us the best of both worlds, and open new horizons for neuroscience research and neurotechnology applications. Here, we formulate this prediction objective both as a classification task (predicting whether the fMRI signal increases or decreases) and a regression task (predicting the value of this signal). We follow two distinct strategies: training classical machine learning and deep learning models (including MLP, CNN, RNN, and transformer) on an EEG-fMRI dataset, or leveraging the capabilities of pre-trained large language models (LLMs) and large multimodal models. We show that predicting fMRI activity from EEG activity is possible for the brain regions defined by the Harvard-Oxford cortical atlas, in the context of subjects performing a neurofeedback task. Interestingly, both strategies yield promising results, possibly highlighting two complementary paths for our prediction objective. Furthermore, a Chain-of-Thought approach demonstrates that LLMs can infer the cognitive functions associated with EEG data, and subsequently predict the fMRI data from these cognitive functions. The natural combination of the two strategies, i.e., fine-tuning an LLM on an EEG-fMRI dataset, is not straightforward and would certainly require further study. These findings could provide important insights for enhancing neural interfaces and advancing toward a multimodal foundation model for neuroscience, integrating EEG, fMRI, and possibly other neuroimaging modalities.

Functional organization of the spinal locomotor network based on analysis of interneuronal activity
Locomotion is a vital motor function for any leaving being. In vertebrates, a basic locomotor pattern is generated by the spinal locomotor network (SLN). Although SLN has been extensively studied, due to technical difficulties, most data were obtained during fictive locomotion, and data about activity of spinal neurons during locomotion with intact sensory feedback from limbs are extremely limited. Here, we overcame the technical problems and recorded activity of putative spinal interneurons from spinal segments L4-L6 during treadmill locomotion (with intact sensory feedback from limbs) evoked by stimulation of the mesencephalic locomotor region in the decerebrate cat. We analyzed activity phases of recorded interneurons, by using a new method that took into account the previously ignored information about stability of neuronal modulation in the sequential locomotor cycles. We suggested that neurons with stable modulation (i.e. small dispersion of their activity phase in sequential cycles) represent the core of SLN. Our analysis allowed to reveal functional groups of neurons with stable modulation presumably generating the vertical and horizontal components of the step, and to characterize their location in the spinal cord. Analysis of relationships between activity phases of these groups revealed possible connections between them, suggesting a novel model for generation of locomotion that combines reciprocally active half-centers with a ring consisting of four sequentially active groups, each inactivating the preceding one and activating the next one.

The Parkinsons disease associated Leucine-rich repeat kinase 2 affects expression of Transferrin receptor 1 and phosphorylation of key signaling proteins in human iPSC-derived dopaminergic neurons
Several variants in the Leucine-rich repeat kinase 2 (LRRK2) gene account for familiar and sporadic late-onset Parkinsons disease (PD). LRRK2 is a large, multifunctional kinase involved in different intracellular pathways crucial for homeostasis and cell survival. One of the poorly understood mechanisms of Parkinsonism is the iron accumulation in Substantia nigra pars compacta (SNc). Transferrin receptor 1 (TfR) plays a significant role for iron uptake into the cell. Here, we investigated the expression of TfR in human induced pluripotent stem cell (iPSC)-derived dopaminergic neurons (hDANs) generated from PD patients carrying the LRRK2 p.G2019S form and found dysregulated TfR levels. In addition, we found gene status depending variations of LRRK2 expression in differentiated hDANs, while neuronal progenitor cells (NPCs) did not display these changes. This suggests an unknown regulatory mechanism of LRRK2 expression during dopaminergic differentiation. Further investigations showed dysregulated phosphorylation of the PD-associated GSK-3{beta} und the key signaling factor Akt.

A theory and recipe to construct general and biologically plausible integrating continuous attractor neural networks
Across the brain, circuits with continuous attractor dynamics underpin the representation and storage in memory of continuous variables for motor control, navigation, and mental computations. The represented variables have various dimensions and topologies (lines, rings, euclidean planes), and the circuits exhibit continua of fixed points to store these variables, and the ability to use input velocity signals to update and maintain the representation of unobserved variables, effectively integrating the incoming velocity signal. Integration constitutes a general computational strategy that enables variable state estimation when direct observation of the variable is not possible, suggesting that it may play a critical role in other cognitive processes. While some neural network models for integration exist, a comprehensive theory for constructing neural circuits with a given topology and integration capabilities is lacking. Here, we present a theoretically-driven design framework, Manifold Attractor Direct Engineering (MADE), to automatically, analytically, and explicitly construct biologically plausible continuous attractor neural networks with diverse user-specified topologies. We show how these attractor networks can be endowed with accurate integration functionality through biologically realistic circuit mechanisms. MADE networks closely resemble biological circuits where the attractor mechanisms have been characterized. Additionally, MADE offers innovative and minimal circuit models for uncharacterized topologies, enabling a systematic approach to developing and testing mathematical theories related to cognition and computation in the brain.

Whole brain dimensional approach identifies shared and sex-specific networks of stress susceptibility in male and female mice.
Background: Stress is a significant risk factor for depression and anxiety, two highly comorbid disorders with sex differences in symptom presentation and prevalence. The Chronic Variable Stress (CVS) mouse model is a useful method for examining sex-specific susceptibility, as stress can be titrated in a sex-specific manner to produce depressive- and anxiety-like behaviours across both sexes. However, the sex-specific mechanisms regarding how CVS reorganizes brain anatomy remain unclear. Methods: Using structural magnetic resonance imaging (MRI), we provide the first whole-brain characterization of neuroanatomical changes induced by 6 or 28 days of exposure to CVS in female and male mice, respectively, and their association to behavior. We then examined the structural connectome underlying sex-specific latent dimensions of stress-susceptibility and potential molecular mechanisms using spatial gene expression analyses. Results: CVS induced significant neuroanatomical changes in regions already implicated in depression in both sexes (e.g. nucleus accumbens and hippocampus) as well as female- and male-specific neuroanatomical changes. In females, these changes were associated with both depressive- and anxiety-like behavior. While in males, we identified two orthogonal dimensions of neuroanatomical changes associated with anxiety-like behavior or social preference. These latent dimensions are associated with sex-specific hub regions and, in females, were associated with genes enriched for protein localization to the cell surface. Conclusion: Our findings indicate that different durations of CVS result in similar neuroanatomical changes in both sexes, however the direction of change and association to behavior is sex-specific. In females, these changes may be attributed to alterations in synaptic connectivity.

Excess prenatal folic acid supplementation alters cortical gene expression networks and electrophysiology
Folate is crucial for various biological processes, with deficiencies during pregnancy being linked to increased risk for neural tube defects and neurodevelopmental disorders. As a proactive measure, folic acid fortification in foods has been mandated in many countries, in addition to dietary supplementation recommendations during pregnancy. However, the risks of excess prenatal folic acid supply have yet to be fully understood. To better appreciate in utero molecular changes in mouse brain exposed to 5-fold folic acid excess over normal supplementation, we investigated the transcriptome and methylome for alterations in gene networks. RNA-seq analysis of cerebral cortex collected at birth, revealed significant expression differences in 646 genes with major roles in protein translation. Whole genome bisulfite sequencing revealed 910 significantly differentially methylated regions with functions enriched in glutamatergic synapse and glutathione pathways. To explore the physiological consequences of excess prenatal folic acid exposure, we applied high-density microelectrode arrays to record network-level firing patterns of dissociated cortical neurons. Folic acid excess-derived cortical neurons exhibited significantly altered network activity, characterized by reduced burst amplitude and increased burst frequency, indicating compromised network synchronization. These functional deficits align with the observed molecular alterations in glutamatergic synapse pathways, underscoring the potential for excess prenatal folic acid exposure to disrupt developing metabolic and neurological pathways.

Arousal state fluctuations are a source of internal noise underlying age-related declines in speech intelligibility
Understanding speech in noisy, multi-talker environments is crucial for social communication but becomes increasingly challenging and frustrating as we age. Here, we simulated the acoustic challenges of multi-talker listening and found that adults over 50 years old (N = 76) recognized speech more slowly, less accurately, and less consistently than younger adults (N = 107). While peripheral hearing status accounted for average differences in speech intelligibility by age, it did not account for moment-to-moment variability in speed and accuracy - fluctuations central to the frustration experienced by older listeners in challenging environments. We hypothesized that age-related changes in brain arousal systems might account for the fluctuant 'noise' in speech processing observed in older listeners. To isolate the contribution of arousal state independent of hearing status and cognitive load, we measured the pre-stimulus pupil-indexed arousal state (PPAS) immediately prior to speech onset. Older - but not younger - adults exhibited a striking inverted-U relationship between PPAS and speech recognition accuracy. Notably, pupil-indexed listening effort measured seconds later during speech encoding was not associated with trial-to-trial performance. Moreover, older adults exhibited altered arousal regulation, occupying a lower PPAS extremum not observed in younger listeners that was specifically associated with performance deficits and subjective listening difficulties reported in hearing health questionnaires. These findings show that age-related changes in central arousal states interact with peripheral hearing status to offer a more complete explanation for why older adults find speech processing in social setting so challenging.

Locus coeruleus-related insula activation supports implicit learning
The noradrenergic locus coeruleus and its neuromodulatory cortical projections are critical for adaptive behavior, yet their contributions to implicit learning in novel environments remain incompletely understood, due to challenges in non-invasive assessment. Here, we combined multimodal neuroimaging -- including locus-coeruleus-sensitive structural MRI, concurrent pupillometry--fMRI, and PET-derived noradrenergic transporter maps -- with repeated behavioral assessments to investigate noradrenergic contributions to implicit learning across younger and older adults (n = 77). Salient expectation-violating stimuli elicited pupil dilation, indicating enhanced neuromodulation, activated the action-mode network and deactivated the default-mode network. Pupil-linked BOLD responses suggested a functional coupling between the locus coeruleus and action-mode network, further supported by spatial overlap of activation patterns with PET-derived noradrenergic transporter maps. Locus coeruleus MRI-guided functional connectivity analyses demonstrated that locus coeruleus activity is coupled to anterior insula activation, suggesting a noradrenergic role in shifting cortical dynamics toward action-oriented processing. Behaviorally, participants implicitly learned the statistical task structure over time, as evidenced by reaction time adjustments based on stimulus probabilities. Critically, stronger locus coeruleus integrity, greater task-related anterior insula activation, and more pronounced pupil dilation were associated with enhanced implicit learning, highlighting the behavioral relevance of noradrenergic neuromodulation. Notably, noradrenergic responses and their link to learning were preserved across age groups, suggesting a robust noradrenergic role in supporting adaptive behavior throughout adulthood. These findings provide novel insights into the neuromodulatory mechanisms underlying learning and cognitive flexibility, emphasizing the pivotal role of locus coeruleus--action-mode network interactions in behavioral adaptation.

Structure and function of otoferlin, a synaptic protein of sensory hair cells essential for hearing
Our sense of hearing relies upon speedy synaptic transmission of sound information from cochlear inner hair cells (IHCs) to spiral ganglion neurons (SGNs). To accomplish this, IHCs employ a sophisticated presynaptic machinery including the multi-C2-domain protein otoferlin which is affected by human deafness mutations. Otoferlin is essential for IHC-exocytosis but how it binds Ca2+ and the target membrane to serve synaptic vesicle (SV) tethering, docking and fusion remained unclear. Here, we obtained cryo-electron-microscopy structures of Ca2+-bound otoferlin and employed molecular dynamics simulations of membrane binding. We show that membrane binding involves C2B-C2G-domains and repositions C2F- and C2G-domains. Progressive disruption of Ca2+-binding by the C2D-domain in mice increasingly altered synaptic sound encoding and eliminated the Ca2+-cooperativity of SV-exocytosis, indicating that this Ca2+-cooperativity reflects binding of several Ca2+-ions to otoferlin. Together, our findings elucidate molecular mechanisms underlying otoferlin-mediated SV-docking and support a role of otoferlin as Ca2+-sensor of SV-fusion in IHCs.

A Foraging-Theory Based Model Captures The Full Spectrum of Human Behavioral Diversity in a Classic RL Task
Decision-making tasks involving multiple, simultaneously presented options are mainstays of cognitive neuroscience and psychology, and are increasingly important to the emerging field of computational psychiatry. Modeling approaches to these tasks overwhelmingly assume that participants make choices based on explicitly comparing the values of the presented options. Contrary to this long-held assumption, we found instead that humans employ a compare-to-threshold decision process, similar to theories of foraging, when making sequential decisions about concurrently available options. We confirmed this result in a large (1000 participant) dataset with multiple converging lines of evidence comparing both model fits and model generative performance. Value-comparison models were restricted to a reduced area of the potential space of single-trial outcome-dependent behavior, demonstrating an intrinsic limitation in the ability to reproduce strategy diversity. Furthermore, we found that using even the best-fit value-comparison model led to a substantial, systematic bias and a compression of individual differences in reconstructed behavior compared to the foraging-based model, leading to weaker predictions of behavioral health measures. Our results imply that studies using value-comparison models to link behavior with neural activity or psychiatric symptoms may be less sensitive to individual differences than a simple alternative based on ethological foraging.

Triple-N Dataset: Non-human Primate Neural Responses to Natural Scenes
Understanding the neural mechanisms of visual perception requires data that encompass both large-scale cortical activity and the fine-grained dynamics of individual neurons. While the Natural Scenes Dataset (NSD) has provided substantial insights into visual processing in humans (Allen et al., 2022), its reliance on functional magnetic resonance imaging (fMRI) limits the exploration of individual neuron contributions. To bridge this gap, we present a new dataset: the Triple-N (Non-human Primate Neural Responses to Natural Scenes) dataset, which extends the NSD framework to non-human primates, incorporating single-neuron activity and fMRI recorded from the inferotemporal (IT) cortex. Using Neuropixels probes, we recorded neural responses from five macaques as they passively viewed 1,000 shared NSD images. The dataset includes 59 sessions across 27 sub-regions, capturing over 30,000 visual responsive units. Many recordings were obtained from fMRI-defined category-selective regions, such as face-, body-, scene-, and color-selective areas. Our dataset enables in-depth exploration of neural responses at multiple levels - from population dynamics to single-neuron activity, providing new insights into various aspects of visual processing, including the heterogeneity of object selectivity within functional regions and the temporal dynamics of responses to natural images. Furthermore, the dataset enables joint cross-species analyses, by integrating the macaque neural recordings with human fMRI data, offering a framework for comparing and aligning visual representations across primate species. Overall, our dataset provides a valuable resource for advancing our understanding of visual perception, bridging the gap between large-scale neuroimaging and fine-grained electrophysiological signals, while also facilitating the development of computational models of the high-level visual system.