eneuro

BackgroundHow does neuronal activity change as an animal transitions from being awake to a state of general anesthesia? Previous studies used C. elegans to investigate awake and anesthetized states, emergence from anesthesia, and to establish metrics characterizing how system-wide neuronal dynamics differ under these conditions. This study employs a new technique to image pan-neuronal activity in C. elegans continuously during induction of anesthesia with isoflurane. MethodsC. elegans worms expressing pan-neuronal nuclear RFP and cytosolic GCaMP6s were imaged with light sheet microscopy to measure single cell activity in the majority of neurons in the animals head during induction via isoflurane exposure. Stable concentrations of isoflurane were maintained throughout the experiment by measured flow vaporization of isoflurane into a specially designed gas enclosure compatible with the imaging system. Building on our previous work investigating emergence from anesthesia, we analyzed ensemble neuronal activity, spectrograms of frequency over time, and metrics of information flow between neurons. ResultsInduction of isoflurane anesthesia caused a progressive reduction in neuronal activity over the course of 40 minutes. Spectrograms indicated a loss of bulk signal power across all frequencies, notably in low frequencies too. State Decoupling and Internal Predictability were among the most useful metrics for discriminating the anesthetized state, demonstrating induction kinetics that are the inverse of emergence. However, each animal does not arrive at the anesthetized state at the same time; response times are highly individualized. ConclusionsInformation metrics of neurodynamic activity demonstrate that isoflurane induction results in a gradual increase in neuronal disconnection and disorganization. Thus, at the level of individual neuron connectivity and system dynamics, the induction of anesthesia in C. elegans nematodes is in essence the reverse of emergence. Induction however occurs more rapidly and shows marked variability between individuals. Future genetic studies will show which molecular targets define sensitivity to volatile anesthetics like isoflurane. Summary StatementIsoflurane-induced unconsciousness is a common phenomenon across species. Does the induction of anesthesia arise by distinct state transitions, or through gradual changes in system dynamics when activity is measured at the level of individual neurons?

People encounter AI voices daily. Existing behavioral studies suggest listeners rely on prosodic cues such as intonation and expressiveness to detect audio deepfakes, reporting that AI voices sound prosodically less rich than human voices. To test whether prosodic processing drives deepfake discrimination in the neural time course of voice processing, we recorded electroencephalographic (EEG) data while participants listened to human and AI-generated speakers producing utterances in confident vs. doubtful prosody (tone of voice), with attention directed toward memorizing speaker names. We used voice cloning to control for speaker identity confounds between human and AI voices. Multivariate pattern analysis revealed that neural discrimination of human vs. AI voices emerged rapidly regardless of prosody (confident: 176 ms; doubtful: 134 ms), substantially preceding prosody discrimination (confident vs. doubtful within human voices: 2066 ms; within AI voices: 1366 ms). Acoustic analysis confirmed that prosodic distinctions became classifiable only at utterance offset (90% normalized duration), converging with neural evidence that prosody requires near-complete temporal integration. This temporal dissociation between rapid voice source discrimination and late-emerging prosody decoding suggests that prosody plays a smaller role in audio deepfake detection than listeners retrospectively report. Representational similarity analysis further revealed that spectral envelope features (mel-frequency cepstral coefficients; MFCC), rather than the visually salient high-frequency energy differences, drove neural human-AI discrimination, with MFCCs earliest independent contribution (228 ms) closely following the MVPA decoding onset (134-176 ms). Future studies may manipulate specific acoustic components to establish the causal sources of this rapid and sustained neural discrimination. Significance StatementPeople encounter AI voices daily, in phone calls, navigation apps, supermarket checkouts, and subway announcements. Using electroencephalography, we show that the human brain automatically and rapidly distinguishes everyday AI voices from human speech, even without conscious attention to voice source. Although people may attribute this ability to AI voices sounding monotone or prosodically unnatural, the brain relies on subtler acoustic signatures, enabling discrimination before prosodic information becomes available. Attempts to identify the specific acoustic features driving this neural detection were inconclusive, pointing to the need for future causal investigations. We encourage engineers and policymakers to ensure AI voices remain perceptually detectable, as increasingly humanlike AI voices could cognitively disadvantage the general public if they become indistinguishable from human speech.

A central question in neuroscience is how neural processing generates or encodes behavior. Caenorhabditis elegans is well suited to addressing this question, given its compact nervous system and near-complete structural connectome. Despite this, findings from previous studies remain inconclusive. While some have shown that the connectome can robustly encode specific behaviors such as locomotion, others report that functional connectivity can be reconfigured across behaviors. We aim to understand the relationship between structural connectivity, functional connectivity and biological behavior in silico by using an experimentally motivated computational model leveraging the structural connectome. Stimulation of specific neurons in the model induces oscillatory neural responses, enabling us to infer neuronal functional connectivity. Functional connectivity is found to be stronger among some neurons, allowing us to identify functional communities. We find that electrical synapses play a critical role in determining functional communities, and the resulting mesoscale functional architecture is predominantly gap junctionally assortative. Furthermore, comparison with behavioral circuits shows that locomotion circuits are largely segregated into distinct functional communities while other circuits are more distributed across multiple functional communities. We also observe that stimulation of neurons belonging to these distributed circuits elicits a more synchronized neuronal response compared to stimulation of neurons within the more segregated circuits. This is consistent with the presence of behavioral patterns that originate in one circuit and terminate in another (e.g., chemosensation leading to locomotion), such that stimulation of one circuit can activate the other and eventually result in a synchronized response. We also find a large repertoire of chimera-like synchronization patterns upon stimulation of certain behavioral circuits (chemosensation, mechanosensation) indicating high dynamical flexibility. Overall, our results demonstrate that while certain behaviors are governed by functionally segregated circuits, others emerge from the synchronization of multiple functional communities, which are, to begin with, influenced by the underlying structural connectivity. Author summaryAnimals constantly transform sensory inputs into actions, but it is still unclear how this mapping from neural activity to behavior is implemented in a real nervous system. Caenorhabditis elegans offers a unique testbed for this question because its entire wiring diagram is nearly completely mapped. Yet, previous works have reached mixed conclusions about how well this anatomical circuit diagram predicts actual patterns of activity and behavior. Here, we use a biologically inspired computational model of the C. elegans nervous system to bridge this gap between structure, function, and behavior. By virtually stimulating individual neurons and observing the resulting network-wide oscillations, we infer how strongly different pairs and groups of neurons interact in functional terms. We then use network analysis tools to identify groups of neurons that tend to co-activate, and relate these functional communities to known behavioral circuits for locomotion and sensory processing. We find that gap junctions play a key role in shaping functional communities, and that locomotion-related neurons are more functionally segregated than neurons involved in other behaviors, which are more functionally distributed. Our results suggest that some behaviors rely on specialized, functionally isolated circuits, whereas others emerge from the coordinated activity of multiple functional communities.

To compensate for self-generated movement-induced postural disturbances, the brain generates anticipatory postural adjustments (APA), ensuring smooth, coordinated actions. APA development continues into late adolescence, yet the specific pathways and mechanisms that remain immature in children are poorly understood. We studied APA mechanisms in 24 children (7-12 years old) using magnetoencephalography (MEG) while they performed the naturalistic bimanual load-lifting task (BLLT). In the BLLT, participants lift a load placed on one forearm with the contralateral hand while keeping the postural forearm horizontal, as if lifting a glass from a tray. To counteract forearm deflection caused by unloading, the brain generates APAs, which involve anticipatory inhibition of the postural Biceps brachii. We found that stronger anticipatory Biceps brachii inhibition was associated with reduced excitability, as indexed by high-gamma (90-130 Hz) suppression, and increased high-beta power (19-29 Hz) in the contralateral Supplementary Motor Area (SMA). Analysis of transient beta events revealed two functionally distinct burst types: (1) 19-24 Hz bursts: time-locked to immediate high-gamma suppression correlated with 26-28 Hz beta power; predicted stronger muscle inhibition and received directed input from middle frontal cortex and precentral gyrus; (2) 24-29 Hz bursts: linked to delayed ([~]100 ms) high-gamma suppression correlated with 8 Hz alpha power; predicted earlier and prolonged muscle inhibition and better forearm stabilization, but did not show directional influence from other regions. Results on anticipatory inhibition-related beta bursts replicated mechanisms reported in adults, suggesting that the efferent pathways and transient inhibitory processes underlying APA may already be mature in children. In contrast, higher-frequency beta bursts revealed a child-specific, complementary APA mechanism that may compensate for imprecise anticipatory inhibition. These results reveal two oscillatory mechanisms supporting APA in children and indicate that beta bursts may reflect both immediate cortical inhibition linked to muscle control and indirect alpha-mediated inhibition likely compensating for forearm instability.

Play is a fundamental aspect of childhood and plays a crucial role in the development of creativity, yet its neural mechanisms remain poorly understood. We tested the hypothesis that more frequent play is associated with stronger functional integration among the default mode network (DMN), executive control network (CN), and salience network (SAL), as these cortical networks have been implicated in creativity in adults. In a preregistered study of infants and toddlers (Study 1; N = 143, 10 months-3 years, 67 boys, Baby Connectome Project), parent-reported play and imitation behaviors increased sharply from 1 to 2 years, and were associated with stronger within-DMN connectivity and DMN-CN coupling, controlling for age, sex, and head motion. In middle childhood (Study 2; N = 108, ages 4-11 years, 52 boys), parent-reported play frequency declined with age, as did cross-network coupling involving SAL. However, children who engaged more frequently in play showed higher DMN-SAL and CN-SAL connectivity. Finally, in a quasi-experimental comparison (Study 3; N = 45; ages 4-12 years, 20 boys), children enrolled in a curriculum that includes guided play (Montessori) showed higher DMN-SAL and DMN-CN connectivity than peers in traditional schools, suggesting that pedagogies that center child-led exploration might enable protracted brain network integration. Across these three studies, play was consistently associated with greater integration among DMN, SAL, and CN, a pattern previously linked to creativity in adults. Our findings offer a potential mechanism linking childhood play to later creativity through its role in supporting brain integration during development. Public Significant StatementO_LIPlay is widely believed to nurture childrens creativity, yet the brain mechanisms behind this link are not well understood. C_LIO_LIAcross three studies from infancy to middle childhood, we found that more frequent play was associated with stronger integration among brain networks tied to imagination, attention, and control. C_LIO_LIThese findings suggest that play may help build the neural foundation for later creative thinking. C_LI

Alternative polyadenylation (APA) is a common posttranscriptional mechanism to regulate gene expression. APA generates mRNAs with varying lengths of 3' UTRs or transcripts that encode distinct protein carboxy-terminal ends. APA is especially important in neurons, where different mRNA variants are often asymmetrically localized to dendrites and axons, and can be locally translated into proteins. Local protein synthesis is crucial for axon guidance, synaptic plasticity, and learning and memory, key processes associated with the development of alcohol use disorder (AUD). We investigated the role of APA in AUD using a mouse model of alcohol dependence characterized by increased voluntary drinking after chronic intermittent ethanol (CIE) exposure. We examined APA during protracted withdrawal from alcohol in three brain regions of male and female mice. Our analyses revealed hundreds of genes undergoing APA in males, but substantially fewer in females, suggesting sex-specific effects of CIE on APA. Notably, male and female mice displayed distinct APA signatures. APA genes were different from differentially expressed genes (DEGs), suggesting that these molecular processes are regulated independently. We also determined that the expression of APA genes was associated with neurons, while DEGs were associated with non-neuronal cells. Many of the APA genes were involved in synaptic integrity, neuroplasticity, and neuronal maintenance, which was consistent with their enrichment in neurons. Our study suggests that APA is a crucial sex- and cell type-specific mechanism in AUD with the potential to influence localized neuronal protein expression during protracted withdrawal and to modify alcohol consumption behavior. HIGHLIGHTSO_LIChronic ethanol exposure in mice results in profound changes of APA genes in brain. C_LIO_LICommonly regulated cleavage and polyadenylation sites and genes were identified in male but not in female mice. C_LIO_LIThere was a minimal overlap between APA and differentially expressed genes (DEGs). C_LIO_LIAPA genes were primarily associated with neurons, whereas DEGs were associated with non-neuronal cells. C_LI

Accurate quantification of rodent licking behavior is essential for studies of fluid intake, including investigations of alcohol use disorder and obesity. Existing lickometry systems vary widely in sensing modality, cost, scalability, and data resolution, and many available systems either require specialized housing or store only binary lick/no lick data based on thresholding. Here we present CLiQR (Capacitive Lick Quantification in Rodents), an open-source capacitive lickometry system designed for high-throughput recording of licking behavior in home-cage environments while preserving the full capacitance time series. The system uses MPR121 capacitive sensors connected to custom metal-tipped serological pipette sippers and a centralized desktop computer to record data from up to 24 animals concurrently, with capacity for two-bottle choice experiments. Validation experiments demonstrated that the capacitive signals reliably distinguish licking from non-licking interactions. Total lick counts showed a strong positive correlation with measured fluid consumption (r = 0.827, p < 0.0001), confirming that detected events provide a meaningful proxy for intake. All information necessary to reproduce the system is shared openly in this manuscript and online. By combining scalability, full-trace data acquisition, and low cost, CLiQR provides a flexible and extensible platform for high-throughput behavioral neuroscience experiments and enables retrospective improvement of lick-detection algorithms. Significance StatementUnderstanding ingestive behavior requires measuring both total consumption and consumption pattern. Licking microstructure provides information about motivation, palatability, and behavioral strategies (i.e., binge-like front-loading); yet many existing lickometry systems are limited by high cost, low scalability, specialized housing requirements, or loss of information due to event-only data storage. We introduce CLiQR, an open-source capacitive lickometry system that enables high-throughput, home-cage recording from dozens of animals while preserving the full time series of capacitance data. By retaining raw data, CLiQR allows post hoc validation and reanalysis of licking behavior, addressing a key limitation of many current systems. This approach increases experimental flexibility, improves data transparency, and lowers barriers to large-scale studies of ingestive behavior.

Neuroscience needs observation. Observation lets us evaluate data quality, judge whether models are biologically realistic, and generate new hypotheses. However, high-dimensional behavioral and neural data are too complex to be easily displayed and eye-tested. Computational methods can reduce the dimensionality of data and reveal statistically robust dynamical structure but often yield results that are difficult to relate back to the underlying biology. In addition, the choice of what parameters to quantify may not capture unexpectedly relevant aspects of the data. To supplement quantification with enhanced qualitative observation, we developed Visualization and Sonification of NeuroData (ViSoND), an open-source approach for displaying multiple data streams using video and sonification. Sonification is nothing new to neuroscience. Scientists have sonified their physiological preparations since Lord Adrians earliest recordings. We extend this tradition by mapping multiple physiological datastreams to musical notes using MIDI. Synchronizing MIDI to video provides an opportunity to watch an animals movement while listening to physiological signals such as action potentials. Here we provide two demonstrations of this approach. First, we used ViSoND to interpret behavioral structure revealed by a computational model trained on the breathing rhythms of freely behaving mice. Second, ViSoND revealed patterns of neural activity in mouse visual cortex corresponding to eye blinks, events that were previously filtered out of analysis. These use cases show that ViSoND can supplement quantitative rigor with observational interpretability. Additionally, ViSoND provides an accessible way to display data which may broaden the audience for communication of neuroscientific findings.

Animals produce different vocalization types, which differ in their acoustic features and are produced in different behavioral contexts. How vocalization-related brain circuits are organized to enable the production of different vocalization types remains poorly understood. The nucleus retroambiguus is a hindbrain premotor region that regulates the production of both ultrasonic vocalizations (USVs) and distress calls (squeaks) in adult mice, but whether distinct or overlapping populations of RAm neurons are recruited during the production of these two vocalization types is unknown. In the current study, we used Fos immunohistochemistry to compare the counts and spatial distributions of Fos-positive RAm neurons in males and females that produced USVs and females that produced courtship squeaks. We also combined in vivo activity-dependent (TRAP2) labeling with Fos immunohistochemistry to directly compare Fos expression associated with the production of USVs and courtship squeaks in the same females. Our findings suggest that RAm contains three vocalization-related populations of neurons: squeak-related neurons, USV-related neurons, and shared neurons that are recruited during both vocalization types. These findings refine current models of the premotor control of vocalization and set the stage for future work to explore anatomical and functional heterogeneity within RAm.

HighlightsBinocular rotational stimulation enhances OKR in wild-type mice along both axes. Chrnb2tm mice show spontaneous horizontal eye oscillations regardless of input. Frmd7tm mice lack binocular enhancement of vertical OKR. The optokinetic reflex (OKR) stabilizes retinal images during global motion and depends on retinal direction-selective (DS) circuits. Although multiple mutant mouse strains exhibit impaired DS circuits via distinct mechanisms, differences in OKR phenotypes remain unexplained. Here, we developed a behavioral system to quantify mouse eye movements under controlled rotational and translational visual stimuli. Using this platform, we examined OKR in wild-type (WT) mice and two DS circuit mutants: Frmd7tm mice, which lack horizontal DS tuning and horizontal OKR, and Chrnb2tm mice, which have disrupted {beta}2-nAChR-dependent cholinergic spontaneous activity during development. Consistent with previous research, both mutants lacked horizontal OKR across conditions, while vertical OKR was preserved. We found that Chrnb2tm mice exhibited spontaneous horizontal eye oscillations regardless of visual input. This phenotype was absent in Frmd7tm mice, suggesting that defective retinal waves in Chrnb2tm mice may induce circuit-level instability distinct from the loss of horizontal DS tuning alone. In addition, WT mice showed enhanced vertical OKR under binocular rotational stimulation, which was absent in Frmd7tm mice. Together, these findings provide a functional comparison of Frmd7tm and Chrnb2tm mice and establish a quantitative framework for dissecting how specific genetic perturbations alter the retinal computations underlying horizontal and vertical OKR.

Oligodendrocyte precursor cells (OPCs) are unique glial cells that communicate bidirectionally with neurons. Neuronal inputs drive various OPC behaviors, including proliferation and differentiation, immunomodulation, blood brain barrier regulation, synapse engulfment and axonal remodeling. OPCs are implicated in numerous stress and pain conditions, where their involvement is likely driven by neuronal activity (ie. neurotransmitter and neuropeptide signaling). One neuropeptide causally involved in chronic pain and stress conditions is calcitonin gene-related peptide (CGRP). Here, we tested the hypothesis that OPCs receive direct inputs from CGRP-containing neurons in the adult brain. Using RNAscope, immunofluorescence and analysis of single-cell datasets, we find that OPCs express receptors for CGRP and we identify close spatial contacts between CGRP and OPCs, with nearly half of CGRP puncta occurring within 1 {micro}m of an OPC. Some of these contacts appear to be synaptic, with CGRP-OPC contacts colocalizing with the presynaptic protein Bassoon and the postsynaptic protein PSD-95. This work suggests the presence of both diffuse and more direct forms of CGRP signaling to OPCs, raising the importance of future experiments to identify both the mode of CGRP release onto OPCs and the functional effects of these different contact types.

Practice enhances motor acuity, enabling movement execution with greater speed and accuracy. However, the learning principles underlying improvements in speed, accuracy, and efficiency remain less understood than those supporting motor skill acquisition and adaptation. Here, we examined motor execution in a skill-based practice task to characterize learning, retention, and generalization of motor acuity. Using a gamified two-dimensional racing task, right-handed participants controlled a stylus-driven car along a curved track as quickly and accurately as possible. Across two studies (N = 83 total, 54 females), participants completed 300 training laps on Session 1 and returned for Session 2 to assess retention and generalization to novel track configurations: one with altered spatial configuration (rotated track) and one requiring movement in the opposite direction of training (reverse track). Movement speed improved rapidly and showed robust, though incomplete, retention across sessions. Speed improvements generalized substantially to both novel tracks. Accuracy was high at training onset and showed strong retention. However, we do not observe offline gains between sessions. Notably, accuracy declined transiently for the novel track configurations, suggesting interference from prior training. Movement efficiency, indexed by path length, was retained and generalized to the rotated track. However, reversing movement direction impaired efficiency, revealing a movement direction effect. This effect persisted when training direction was reversed in a second study, with counterclockwise movements remaining slower and less efficient than clockwise movements. These findings show that practice produces durable and broadly transferable motor execution improvements, while inherent movement direction biases constrain how improvements generalize across contexts. New & NoteworthyThe learning principles underlying improvements in motor acuity remain less well understood than those governing other forms of motor learning. Prior work suggests that motor execution improvements show limited generalization. In contrast, the present findings demonstrate that execution-based practice can produce robust, transferable gains, while also revealing a key constraint: inherent movement direction biases that limit generalization. By characterizing learning, retention, and generalization, this work provides new insight into how motor acuity improvements compare with skill acquisition and adaptation.

Serotonin is one of the main neuromodulators in the brain, involved in regulating mood, complex behaviors and sensory input. Serotonin reaches primary somatosensory cortex (S1) via axons of neurons located in the dorsal raphe nucleus (DRN). DRN neurons can be modulated, amongst others, by reward, sensory stimulation, or movement but the activity pattern of serotonergic neurons targeting S1 is not known. Therefore, it is unclear under which circumstances serotonin is released in S1. Here, we expressed GCaMP8 in serotonergic neurons of the DRN to analyze the activity of their axons in S1 using two-photon Ca2+-imaging. Cluster analysis of axonal activities suggests that one to four functional groups of serotonergic axon segments project to a 0.3 mm2 horizontal plane of S1. We show that activity in serotonergic axons is strongly driven by reward and weakly by sensory stimulation of the whiskers. Movement, however, is preceded by a modulation, up and down, of the serotonergic signal seconds before the running onset. In summary, rewards and sensory stimulation lead to activity in serotonergic axons which is likely to adjust signal processing in S1 upon these events. The serotonergic signal changes seconds before movement onset probably preparing the neural network in S1 for the state change that accompanies running.

Hierarchy in the brain emerges across spatial and temporal scales, enabling transformations from rapid sensory encoding to sustained cognitive control. Hierarchical gradients are well established in sensory systems. In contrast, the hierarchical organization of the primate motor cortex remains debated, partly due to its agranular architecture and the absence of clear laminar input-output projections, that obscures the distinction between feedforward and feedback pathways. In particular, the relative hierarchical position of the dorsal premotor cortex (PMd) and the primary motor cortex (M1) cannot be resolved from anatomy alone. To investigate their relative organization, we here adopted a multimodal approach using intrinsic timescales derived from both single-unit spiking activity (SUA) and local field potentials (LFPs) in macaques performing a delayed-match-to-sample reaching task. We found convergent evidence for inter-areal temporal hierarchy, with longer spiking timescales and smaller LFP aperiodic spectral exponents in M1. Across cortical depth, however, temporal organization depended on signal modality. LFP spectral exponents were significantly smaller in deep than superficial layers in both areas, and LFP-autocorrelation timescales were longer in deep layers in M1. In contrast, spiking activity did not show significant laminar differences in intrinsic timescales. Functionally, neurons with longer timescales exhibited more stable representations of the planned movement direction during motor preparation in PMd and slower temporal evolution of movement encoding during execution in both areas. In conclusion, multimodal temporal measures converge on the same hierarchical organization across these two motor areas, with M1 placed higher than PMd. Our study provides the first characterization of intrinsic spiking timescales across cortical layers in any cortical area and shows that laminar temporal organization depends on the neural signal analyzed. This divergence likely reflects their distinct physiological origins. Spikes capture neuronal output, whereas LFPs primarily reflect synaptic and dendritic population activity, potentially integrating differential contributions from apical and basal dendritic inputs.

Successful goal-directed movements depend on the central nervous systems (CNS) ability to handle diverse physical interactions. The CNS is thought to handle different dynamical contexts through three mechanisms: (i) trial-by-trial adaptation when forces are predictable, (ii) a model-free robust control strategy, and (iii) online adaptation of feedback responses. While each has been studied independently, their relative contributions and the possibility that they are recruited to different extents across contexts is unknown. Here, we quantified all three strategies within the same individuals to examine how CNS exploits them under varying environmental conditions. Participants (19 female, 15 male) performed reaching tasks while interacting with robot-generated force-fields that were either consistent or varied unpredictably. Trial-by-trial adaptation was measured using standard force channels to isolate anticipatory compensation. Robust control was assessed through movement velocity and corrective force magnitude. Online adaptive control was quantified by the temporal alignment between commanded and measured forces within a movement. Results showed that participants improved anticipatory compensation in consistent environments and relied on both robust and online adaptation when perturbations were unpredictable. Crucially, markers of robust control dominated the early movement phase, whereas online adaptation dominated later corrections. This temporal dissociation was confirmed by electromyographic recordings. Markers of robust and online adaptive feedback strategies also statistically predicted participants ability to adapt across trials in consistent environments, revealing a common trait linking online control and adaptation. These findings reveal a rich and flexible combination of control mechanisms, offering a new framework for understanding the neurophysiological bases of reaching control. Significance StatementHuman reaching control is a complex behavior resulting from several mechanisms that orchestrate feedback responses to mechanical perturbations and adaptation to changes in the environment. Here we combine previously studied paradigms to highlight within the same groups of healthy volunteers that three major components are recruited to different extents dependent on the context: unpredictable environment promote concomitant use of robust control and online adaptation whereas predictable environments recruit standard adaptation based on anticipatory compensation. Remarkably, individuals adaptive capabilities correlated across consistent and inconsistent environments, suggesting a key involvement of adaptive mechanisms in both online control and trial-by-trial adaptation. Robust control, online adaptation, and anticipatory compensation are dissociable behaviorally, and are used to varying levels as a result of individual traits.

The nasal epithelium is a complex tissue composed of both respiratory and olfactory tissue, and is constantly exposed to environmental insults, including toxins and pathogens. The main olfactory epithelium (MOE) serves as the critical site for olfaction, or sense of smell. Dysfunction at this critical barrier tissue can result in partial or total loss of olfactory function, resulting in significant impact to quality of life. The MOE is heterogeneous, comprised of many cell types including olfactory sensory neurons, support cells, and immune cells. It is not well understood how these diverse cell types in the MOE interact to regulate this tissue during homeostasis, and during times of injury and inflammation. We investigated how environmental olfactory exposures impact cell type specific transcriptional responses in the mouse MOE. We performed single-cell RNA sequencing (scRNA-seq) of the MOE following controlled environmental exposure to both well-known odorants and allergens. We identified major cell types and subtypes within the MOE, and identified transcriptional changes in response to the olfactory exposures. We identified transcriptional changes in OSNs, sustentacular cells, and resident immune cells to each condition. This indicated that environmental olfactory exposures drive changes to multiple cell types in the MOE. To our knowledge, this is the first study to identify effects of environmental olfactory exposures on cell-type specific transcription at homeostasis. These findings highlight the potential importance of multi-cellular interactions and communication in regulation of the olfactory epithelium.

Reaction time is a measure of the speed of our response to stimuli in the environment. Even for a well-trained task, a subjects reaction time varies. One source of this variability is internal state fluctuations (such as changes in arousal). There are few studies that systematically quantify the extent to which reaction time varies across different timescales and link this to measures of systemic physiology associated with arousal. In much of the literature, it is assumed but not demonstrated that behavioral and systemic measurements associated with arousal will be consistently linked because both estimate a common underlying arousal process. In this work, we examined this assumption by simultaneously measuring reaction time, heart rate, and pupil diameter in rhesus macaque monkeys performing several visual tasks over hours and across hundreds of sessions. We found a portion of the variability in reaction time could be linked to systemic physiological signatures of arousal on fast timescales from second to second and slower timescales from minute to minute. This link between reaction time and systemic physiology was also present for different biomarkers of arousal (heart rate and pupil). However, the strength of this relationship varied depending on the arousal biomarker. Our findings support the conclusion that there are multiple arousal mechanisms that act simultaneously to influence behavior and multiple timescales at which they operate.

Gymnotiform fish emit electric organ discharges (EODs) for both active electroreception and electrocommunication. EOD waveform and rhythm can be modified to cope with diverse environmental challenges. In pulse-type species, EODs are generated by a hierarchical electromotor network controlled by a medullary pacemaker nucleus (PN), which comprises intrinsic pacemaker cells (PM-cells) and projecting relay cells (R-cells). Active electroreception requires the emission of stereotyped EODs, an electromotor output that implies a functional PN configuration in which PM-cells rhythmically time EODs and R-cells transmit coordinated commands to downstream components of the electromotor system. To test whether electrical coupling (EC) between PN neurons supports this functional organization, intrinsic connectivity of the PN in Gymnotus omarorum was examined in brainstem slices using electrophysiology, immunohistochemistry, and dye-coupling analysis. Homotypic connections (PM-PM and R-R) exhibited low-magnitude, bidirectional EC with symmetrical, low-pass filter properties, supporting synchronous yet adaptable pacemaker activity and coordinated descending commands. Heterotypic connections (PM-R) also displayed bidirectional, symmetrical coupling but revealed direction-dependent filtering: an apparent high-pass behavior from PM- to R-cells and a low-pass behavior in the opposite direction. Together with precise PM-to-R discharge timing, direction-dependent filtering suggests a role of PM-cell axons in shaping signal flow. Dye coupling and immunohistochemical evidence further indicate that PN neurons are interconnected via gap junctions, likely formed by connexin 35. Thus, EC-based connectivity endows the PN with crucial functional attributes of its exploration mode of operation while preserving the capacity to organize communication signals under the influence of descending inputs, revealing remarkable functional versatility. Summary statementGap junction-mediated intrinsic connections within the electromotor nucleus of electric fish may sustain the emission of signals essential for sensory sampling as well as those supporting communication.

Spiral ganglion neurons (SGNs) are the primary auditory afferents in the inner ear. These neurons degenerate in response to a number of conditions, including auditory neuropathies, concussions, and aging. Research to assess the extent of degeneration and to test the efficacy of protective or rehabilitative strategies requires quantification of SGNs from tissue sections. However, manual counting of SGNs can be arduous and time-consuming due to dense crowding and the lack of reliable nuclear-specific labels. SGNs receive afferent input via GluA2-containing AMPA receptors. As the Gria2 transcripts that code for GluA2 must undergo RNA editing to ensure calcium impermeability, we hypothesized that SGNs would express high levels of the adenosine deaminase acting on RNA (ADAR) enzyme ADARB1. Here we confirm enriched expression of Adarb1 in SGNs via in situ hybridization and show that anti-ADARB1 antibodies robustly label the nuclei of both type I and type II SGNs in cochlear sections from young and aged mice. Neuronal specificity was confirmed using antibodies against neurofilament heavy chain (NFH), human antigen D (HuD), GATA binding protein 3 (GATA3), and SRY-box 2 (SOX2). A blinded investigator manually counted SGNs via NFH staining, and these were compared to automated counts of ADARB1-positive nuclei using the analyze particles function in ImageJ. A concordance correlation coefficient and Bland-Altman analysis demonstrated strong agreement between the manual and automated counts. Additionally, immunolabeling of ADARB1 in macaque and human temporal bone sections confirm robust labeling of SGN nuclei, suggesting broad utility of ADARB1 immunolabeling for automated counts of SGNs across species.

We explored processes within and orthogonal to the solution space (uncontrolled manifold, UCM) as superposition of fast random walk (RW) and slow drifts during multi-finger force production. Healthy participants performed two-hand (using the index and middle fingers per hand) accurate total force production task with different initial sharing of the force between the hand. After 5 s, visual feedback was manipulated - kept for both force and sharing, for only one of those variables, or turned off. The subjects tried to continue "doing what they have been doing" for 55 s. Trajectories both along and orthogonal to the UCM for total force showed fast RW and slow drifts. The diffusion plots confirmed persistent RW within the first 0.2 s and anti-persistent RW after 0.5 s. Persistent RW was similar across visual feedback conditions and larger orthogonal to the UCM. Its Hurst index correlated between the UCM and orthogonal to the UCM direction across participants. Anti-persistent RW depended strongly on visual feedback. Drift magnitude and characteristic time depended strongly on visual feedback, being similar along and orthogonal to the UCM. We conclude that RW destabilizes the state of the system thus encouraging exploration of nearby states over short time intervals and contributes to its stability over larger time intervals. Visual feedback plays a more important role in structuring stability of performance compared to the explicit task formulation. RW exploration promises new insights into the organization of stability in abundant systems and a potential biomarker for clinical studies. HighlightsO_LIStability during a multi-element action is structured in a feedback-specific way; C_LIO_LIRandom walk and drift characteristics of force depend not on the task but on salient feedback; C_LIO_LIRandom walk destabilizes steady state within a short range and stabilizes it within a long range; C_LIO_LIThe control of an action encourages exploration but limits its range. C_LI