eneuro

The lateral reticular nucleus (LRN) is thought to contribute to skilled forelimb control but its specific contributions to reaching and grasping remain unclear. In this paper, we examine skilled reaching in intact adult female Long-Evans rats after bilateral LRN ablation through single-pellet reaching tasks. Tasks were analyzed using sensitive quantitative kinematic analyses and qualitative behavioral scoring. Overall, limb transport was largely preserved after ablation, with results appearing in temporally restricted differences. The clearest deficits emerged in pellet-directed endpoint control. LRN-ablated animals showed broad variability in end-point covariance, endpoint spread, and increased trial-to-trial variability, indicating that the movement became less precise and less consistent. These effects were more consistent than any single spatial difference seen, suggesting that ablation of the LRN impairs movement refinement rather than inducing a simple directional bias, although the paw height during the reach was significantly effected. Reach duration also changed, but this temporal difference emerged later and was less prominent. Our results suggest that the LRN acts as an important contributor to endpoint stabilization and reach timing during skilled forelimb behavior.

The rodent accessory olfactory system (AOS) detects chemosignals emitted by conspecifics and other species to support beneficial behaviors. Peripheral vomeronasal sensory neurons (VSNs), the AOS chemical sensors, detect fecal bile acids in patterns that have unknown significance to the animal. We used a combination of mass spectrometry and VSN calcium imaging to investigate the AOS capacity to use bile acid information to discriminate between fecal samples from captive reptiles and mice with varying gut microbiome states. Mass spectrometry analysis revealed bile acid patterns that distinguished biologically relevant samples from one another, representing theoretical discrimination axes. We measured VSN response patterns to bile acid stimuli aligned with theoretical discrimination axes. We found that VSNs perform stimulus "whitening" via an inverse relationship between natural bile acid abundance and population response magnitude. VSNs showed maximum sensitivity to taurine-conjugated bile acids, which have high theoretical discriminatory value, but were found at low natural abundance levels. Individual taurine-conjugated bile acids drove threat assessment behavior when added to familiar mouse fecal extracts, suggesting high behavioral significance. Finally, we analyzed the degree to which the AOS utilizes the theoretical information about species, diet, and gut microbiome status from bile acids. We found that VSN tuning patterns align with theoretical axes for discriminating reptilian predators from vegetarians, and between mice with different gut microbiome states. VSN tuning was especially well-aligned with the information available about conspecific gut microbiome status. These results show that AOS bile acid chemosensation supports discrimination of multiple biologically relevant states. Short abstractThe rodent accessory olfactory system (AOS) detects fecal bile acids via combinatorial codes with unknown biological significance. We investigated whether AOS bile acid chemosensation supports species and gut microbiome evaluation using mass spectrometry, calcium imaging in vomeronasal sensory neurons (VSNs), and analytical modeling. Bile acid excretion patterns theoretically supported discrimination of reptilian predators from vegetarians, and germ-free mice from conventionally raised counterparts. VSNs demonstrated stimulus "whitening" via an inverse relationship between natural bile acid abundance and population response magnitude. VSNs had highest sensitivity to taurine-conjugated bile acids, a novel class of chemosignals that elicited behavioral aversion. VSN tuning aligned with ideal discrimination axes, which was especially strong for gut microbiome-associated bile acid abundance patterns. These results show that AOS bile acid chemosensation supports discrimination of multiple biologically relevant states.

Sympathetic preganglionic neurons (SPNs) provide the final pathway through which the central nervous system regulates autonomic function. SPN axons projecting to paravertebral sympathetic chain ganglia branch extensively and diverge across multiple segments, enabling amplification of central sympathetic commands through extensive postganglionic neuronal populations. Spike propagation along these projections has generally been assumed to occur reliably. However, most SPN axons are extremely small unmyelinated fibers, a structural feature predicted to reduce the safety factor for spike propagation. Using an isolated mouse thoracic sympathetic chain preparation, we combined anatomical tracing with multi-site compound action potential recordings to assess conduction across SPN axons. Neurobiotin labeling revealed widespread rostrocaudal divergence through interganglionic nerves, while axon measurements confirmed that most SPN axons are small unmyelinated fibers. Across preparations, supramaximal recruitment of SPNs revealed substantial intertrial variability in compound responses, indicating frequent conduction failures. Failures were most prominent in slow-conducting axons and occurred in both branching interganglionic pathways and the unbranching axons within the splanchnic nerve. During repetitive activation, frequency dependent depression was observed at 1, 5 and 10Hz, but only slow-conducting branching axons exhibited pronounced depression. Overall, these findings indicate that spike propagation in SPN axons may operate probabilistically rather than deterministically, with reliability strongly dependent on axonal subtype and recent activity history. We conclude that axonal conduction variability constitutes an intrinsic and dynamically regulated mechanism that shapes sympathetic output. By varying the recruitment of postganglionic populations, unreliable spike propagation in SPN axons introduces a previously unrecognized presynaptic gain-control mechanism, operating independently of central spike generation to modulate sympathetic output. SIGNIFICANCESympathetic preganglionic neurons provide the final pathway through which the central nervous system controls end-organs. These neurons project through the sympathetic chain where their axons branch extensively to recruit more numerous paravertebral postganglionic neurons. Spike propagation along these projections has generally been assumed to occur reliably. Here we show that this assumption is incorrect. Using anatomical tracing and electrophysiological recordings in mouse sympathetic chain preparations, we demonstrate that spike conduction in sympathetic preganglionic axons is frequently variable and prone to failure, particularly in the slowest-conducting unmyelinated fibers. Conduction variability was preferentially enhanced in branching axonal pathways during repetitive activation. These findings reveal that axonal conduction reliability represents an important presynaptic mechanism regulating the magnitude and variability of sympathetic output.

The short-latency stretch reflex (SLR) is the fastest sensorimotor response in human limbs. The spinal SLR is traditionally viewed as automatic and resistant to rapid plasticity, while adaptive feedback is often attributed to transcortical mechanisms underlying the long-latency reflex. Using high-density surface electromyography (64-channel arrays) from the pectoralis major and posterior deltoid during an instructed-delay reaching task, we probed reflex gains with brief perturbations delivered during action preparation. Pre-perturbation muscle activity showed no systematic goal-directed change. After task familiarization and with sufficient preparation time, SLR gains decreased progressively (logarithmically) with experience when the planned movement was expected to stretch the homonymous muscle. This tuning occurred both with and without agonist muscle pre-loading and predicted the observed improvements in reaching performance. Early transcortical responses showed comparable tuning across load conditions. Our study shows that spinal feedback circuits can progressively adapt within a single session to support the performance of goal-directed movements. HighlightsO_LIThe short-latency stretch reflex adapts rapidly with experience in planned reaching C_LIO_LISpinal reflex tuning occurs with and without agonist muscle pre-loading C_LIO_LIReflex tuning evolves logarithmically and predicts reaching performance C_LIO_LIEarly transcortical reflex gains show comparable experience-dependent tuning C_LI

Lick microstructure is a term used in behavioural neuroscience to describe the information that can be obtained from a detailed examination of rodent drinking behaviour. Rather than simply recording total intake (volume consumed), lick microstructure examines how licks are grouped, and the spacing of these groups of licks. This type of analysis can provide important insights into why an animal is drinking, for example, whether it is influenced by taste or affected by consequences of consumption (e.g., feeling "full"). Here we present a software package, lickcalc, that allows detailed microstructural analysis of licking patterns. The software is browser-based and is hosted at https://lickcalc.uit.no or the repository can be downloaded and installed locally. Lick timestamps can be loaded from a variety of formats and different analysis and plotting options allow quality control of data and determining critical parameters for microstructural analysis number and size of lick bursts. Data can be divided into epochs for detailed examination of changes across session. Batch processing and custom configurations are supported. In this manuscript, we demonstrate use of the functions exposed by lickcalc by analysing data comparing lick patterns between mice on a protein-restricted and control (non-restricted diet). We show that lickcalc allows quality control of the data and uncovering of subtle differences in lick behaviour that are not apparent when just considering the total number of licks. This software makes microstructural analysis accessible to any researchers who wish to employ it while providing sophisticated analyses with high scientific value.

The rostral nucleus of the solitary tract (rNST) is the initial central site for taste processing. This nucleus has a complex circuitry and multiple cell types with different response properties, connectivity, and morphology (Travers and Travers 2018). However, unlike its visceral counterpart, the caudal NST, neurochemical phenotypes in rNST are poorly defined. Recent studies have begun to probe this gap. Based on fiber photometry, optogenetics, and cell-type specific deletion. For example, one group proposed that somatostatin (SST) rNST neurons, neither calbindin or dynorphin cells, responded specifically to bitter stimuli and that these neurons were necessary for suppression of quinine-induced licking (Jin, Fishman et al. 2021) (Zhang, Jin et al. 2019). The present study employed in situ hybridization, optotagging, and chemogenetic suppression in male and female mice to demonstrate that SST neuron function is more complex. Although most SST neurons responded optimally to bitter stimuli, many others were activated by different qualities and some non-SST neurons responded to bitter tastants. Moreover, roughly equal proportions of SST neurons expressed excitatory (VGLUT2) or inhibitory (VGAT) markers. Suppressing SST neural activity with DREADDS enhanced licking to both quinine and sucrose suggesting that neural activity elicited by the aversive bitter stimulus was suppressed whereas licking elicited by the sweet, preferred stimulus was increased. We hypothesize that these effects arise from suppressing excitatory quinine-responsive SST neurons but that a separate population of inhibitory SST neurons synapse on sucrose-responsive cells. Significance StatementRecent studies have revealed molecular heterogeneity of gustatory system neurons. However, it is unclear whether molecularly-distinct cells are associated with specific roles. The current study investigated somatostatin (SST) neurons in rNST, the first central hub for taste processing. Well over half were inhibitory, expressing VGAT, but a substantial proportion were excitatory, expressing VGLUT2. A narrow majority responded optimally to the bitter quality and none to NaCl, but other SST cells responded most vigorously to sweet, umami, or sour stimuli. Subsets of neurons not expressing SST responded best to each quality, including bitter. Suppressing activity in SST neurons dampened behavioral avoidance to quinine but enhanced consummatory responses to sucrose. Thus, SST rNST neurons exhibited varied functional characteristics but also clear distinctiveness.

In natural environments, animals must effectively maneuver around obstacles to reach goals such as food or shelter. Recent work has demonstrated that laboratory mice use vision for naturalistic behavior such as prey capture, escape, and distance estimation. However, it is unknown to what extent mice use vision relative to other senses such as touch for obstacle avoidance, a critical natural behavior. In this study we developed an obstacle avoidance task in freely moving mice to investigate how vision is used to guide paths around an obstacle obstructing a goal. We found that mice clearly use vision to avoid an obstacle, steering around the obstacle at distances where tactile information isnt available. By comparing trajectories for mice performing obstacle avoidance in the light versus the dark, we found that vision contributes to more spatially efficient trajectories and paths directed to the open edge of the obstacle. When vision is available, mice make large orienting movements towards the opening of the obstacle at about 10 cm from its edge, suggesting that mice are actively using visual information to direct these movements. Finally, by occluding one eye, we found that mice were still able to avoid obstacles with primarily monocular information. Taken together, these results demonstrate that laboratory mice use vision to avoid an obstacle, taking directed paths that are initiated by large orienting movements. In addition to demonstrating the visual behavioral capabilities of the mouse, this paradigm can serve as a foundation to study the neural circuits that mediate visually guided orienting and locomotion. HighlightsO_LIWe developed a simple obstacle avoidance task for freely moving mice that requires minimal training C_LIO_LIVision is necessary for efficient and directed paths around an obstacle C_LIO_LIMice steer around obstacles by performing directed head movements towards clear paths C_LIO_LIMice do not require binocular vision for obstacle avoidance C_LI

Presynaptic homeostatic plasticity (PHP) is a potent form of homeostatic plasticity that has been documented at synapses as diverse as the glutamatergic Drosophila neuromuscular junction (NMJ), cholinergic mammalian NMJ (including human), and glutamatergic synapses in the mammalian brain. Published experimental evidence in favor of PHP in adult hippocampus and cerebellum includes patch-clamp electrophysiology, presynaptic capacitance measurement, calcium imaging, optical reporters of vesicle release and correlated three-dimensional electron microscopy. These studies are grounded in newly optimized experimental protocols that differ substantively from those typically used to study activity-dependent plasticity in neonatal and juvenile slice preparations. Here, we elaborate and extend our assays and methodologies for the study of PHP in the adult mammalian brain. Our assays are designed to optimize synapse, cell and tissue health and minimize the incorporation of unintended adverse experimental conditions that may interfere with the induction and/or expression of PHP. In addition, we provide benchmark criteria for assessment of cell health, necessary for analysis of PHP and, in so doing, advance our understanding of postsynaptic conditions necessary for PHP induction in the adult brain. Our data underscore why PHP may have been previously overlooked, inclusive of a recent manuscript challenging the robust expression of PHP in the mammalian brain (Dou et al., 2026 BioRxiv [preprint]).

There is a dearth of information on how different cocktails sweetened with different sugars impact brain activity. Glucose enters the brain faster and in greater concentration than fructose and directly affects neuronal activity of melanin-concentrating hormone (MCH) neurons. MCH signaling promotes both glucose drinking and alcohol intake by integrating central and sensory inputs, but it is currently unknown how MCH neuronal activity relates to sweetened cocktail drinking. This study sought to investigate the relationship between MCH activity and sugar-sweetened alcoholic cocktail drinking. We also sought to compare MCH neuronal responses to the sugar solutions without alcohol as well as their response to sensory stimuli. In female and male rats, we used fiber photometry to monitor MCH neurons in response to sensory stimuli and during drinking of 10% glucose, 10% fructose, and glucose or fructose cocktails with 1.25% or 10% alcohol. We found that MCH activity rises in response to a variety of sensory stimuli and peaks before the start of drinking for all cocktails, before returning to baseline near the start of drinking. The cocktail type impacted the dynamics of MCH activity, where increased alcohol concentration resulted in earlier MCH activity for fructose but not glucose cocktails. Finally, we found that peak MCH activity during drinking is correlated with approach behavior for all sugar and cocktail types. These findings suggest that glucose and alcohol may interact to directly influence MCH activity. Further, MCH neurons may regulate cocktail drinking in response to sugar type and alcohol concentration. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=118 SRC="FIGDIR/small/719280v1_ufig1.gif" ALT="Figure 1"> View larger version (17K): org.highwire.dtl.DTLVardef@54685org.highwire.dtl.DTLVardef@59003eorg.highwire.dtl.DTLVardef@11f0358org.highwire.dtl.DTLVardef@114b524_HPS_FORMAT_FIGEXP M_FIG C_FIG New and noteworthyFiber photometry was used to monitor lateral hypothalamic melanin-concentrating hormone (MCH) neurons in male and female rats during sensory stimuli and drinking of glucose, fructose, or glucose- or fructose-sweetened alcoholic cocktails. Subsecond-scale changes in MCH activity occurred after stimuli. Peak MCH activity during drinking was correlated with approach behavior. Alcohol concentration only impacted MCH activity with fructose cocktails. We discuss the implications of MCH dynamics towards brain function, associative learning, and alcohol use disorder.

ObjectivePrecision grip tasks require complex coordination of intrinsic hand muscles, yet how common synaptic inputs to motor neurons are modulated during functionally different tasks remain unclear. This study investigated whether neural coupling between motor unit spike trains in the first dorsal interosseous (FDI) muscle differs between isolated index finger flexion and precision pinch tasks. ApproachSixteen healthy participants performed isolated index finger flexion and pinch tasks at 10% and 20% of maximal voluntary contraction while high-density surface electromyography was recorded from the FDI. Motor unit spike trains were decomposed and tracked across tasks. Neural coupling was assessed using complementary methods: coherence analysis and Proportion of Common Input (PCI) index to quantify linear common oscillations in delta (1-5 Hz), alpha (5-15 Hz), and beta (15-35 Hz) frequency bands, and mutual information-based network analysis to capture nonlinear interactions. Main results.Coherence analysis and PCI revealed no significant differences between tasks across all frequency bands. In contrast, network density derived from mutual information analysis showed significantly stronger nonlinear motor unit coupling during pinch compared to isolated finger flexion (p = 0.013), independent of force level. Significance.These findings demonstrate a dissociation between linear and nonlinear measures of motor unit coupling. In particular, precision pinch tasks appear to rely on stronger higher-order common inputs and distinct neural control strategies that are not fully captured by traditional linear coherence measures. This highlights that functionally relevant precision behaviors engage additional layers of nonlinear neural coupling, offering new insight into how the nervous system adaptively modulates motor unit coordination to meet complex task demands.

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.

Microglia are the brains resident immune cells that exhibit complex signaling behavior, including phagocytic activity in response to threats and prolonged neuronal activity. Adenosine triphosphate (ATP) is a chemoattractant for microglia. In the nucleus accumbens (NAc), ATP is co-packaged and released with DA, and microglia express dopamine (DA) receptors and ATP receptors. The present work examines microglia chemotactic motility for these transmitters using iontophoresis and multiphoton microscopy approaches in NAc brain slices from GFP-monocyte labeled transgenic mice. ATP chemoattraction was more regularly observed than DA chemoattraction, and DA chemoattraction occurred in only a small subset of microglia. The DA chemoattraction of this subset was blocked by DA D1 antagonism. Microglia are reactive oxygen species (ROS) scavengers. Application of glucose oxidase produces mild but consistent increases in ROS and induced inflammatory-related changes in microglial morphology and motility. Glucose oxidase application decreased DA release but had variable effects on ATP release. The toll-like receptor 4 (TLR4) agonist lipopolysaccharide (LPS) transitioned microglia from ramified to amoeboid morphology over a period of 4 hours, and increased DA and ATP release across this same period. These studies highlight the complex relationship between local immune activation and DA terminal functionality.

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

Neural circuit assembly relies on different neuronal subtypes coming together to form a functional circuit. The question of how the appropriate number of each subtype is integrated into an emerging circuit remains relatively unknown. To answer this question, we used the mouse retina to uncover the molecular mechanisms responsible for neuron subtype integration in a developing circuit. In the mammalian retina, bipolar neurons are a class of interneurons that relay visual information from photoreceptors to ganglion cells. Extensive studies have shown there are 15 distinct bipolar subtypes: 6 types of OFF cone bipolars, 8 types of ON cone bipolars, and 1 type of rod bipolar. During retinal development, bipolar neurons are born in excess and through programmed cell death, a precise number of each subtype remains to give rise to the retinal circuit. Although this process has been well-described, little is known about the key molecules responsible for bipolar subtype integration in the developing retina. Our work uncovered a new role for the autism-associated risk gene, Protocadherin 9 (Pcdh9) in bipolar subtype integration. Deletion of Pcdh9 using a floxed allele leads to loss of OFF and ON cone bipolars; however, disruption in the extracellular binding of Pcdh9 leads to selective loss of ON cone bipolars but not rod bipolars. Moreover, we found this later function of Pcdh9 is mediated by homophilic interactions between ON cone bipolars and their known synaptic partners. Taken together, our work revealed a new role for Pcdh9 in bipolar subtype integration during retinal development. SUMMARY STATEMENTNeural circuits are comprised of multiple neuronal subtypes where a specific number need to come together to give rise to a functional circuit. Although this is a critical process during neurodevelopment, little is known about the molecular mechanisms that determines the precise number of each subtype during circuit development. In the present study, we identified the autism risk gene, Protocadherin 9 as a critical molecule in subtype integration of bipolar neurons within the developing mouse retina. Using newly generated mouse lines, we found distinct requirements of Pcdh9 to promote survival in different bipolar subtypes during retinal circuit assembly. The significance of this work is that it shed lights into how different neuronal subtypes are integrated in nascent neural circuits.

Convolutional neural networks (CNNs) are a class of artificial neural networks (ANNs). Since the early 2010s, they have been widely adopted as models of primate vision and classifiers of neuroimaging data, becoming relevant for a wealth of neuroscientific fields. However, the majority of neuroscience researchers come from soft-science backgrounds (like medicine, biology, or psychology) and do not have enough quantitative skills to understand the inner workings of A/CNNs. To avoid undesirable black boxes, neuroscientists should acquire some rudiments of computational neuroscience and machine learning. However, most researchers do not have the time nor the resources to make big learning investments, and self-study materials are hardly tailored to people with little mathematical background. This paper aims to fill this gap by providing a concise but accurate introduction to CNNs and their use in neuroscience -- using the minimum required mathematics, neuroscientific analogies, and Python code examples. A companion Jupyter Notebook guides readers through code examples, translating theory into practice and providing visual outputs. The paper is organised in three sections: The Concepts, The Implementation, and The Biological Plausibility of A/CNNs. The three sections are largely independent, so readers can either go through the entire paper or select a section of interest.

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

The striatum is a major cortical input site of the basal ganglia and plays a critical role in the control of orofacial movements such as licking. However, how striatal activity relates to the spatial features of licking behavior remains unclear. In this study, we examined whether neural activity in the striatal matrix and striosomal compartments is associated with the spatial position of a licking target during an operant task. Head-fixed mice performed a licking task in which the target positions were varied across three spatial dimensions. Using fiber photometry in Calb1-IRES-Cre and Pdyn-IRES-Cre mice, we recorded calcium signals from matrix and striosomal neurons. Associations between neural activity, target position, and behavioral variables were quantified using linear mixed-effects modeling with cross-validation. Matrix activity prior to licking onset was primarily associated with the dorsal-ventral target position and reaction time. During licking, matrix activity was modulated by anterior-posterior and medial-lateral positions, independent of reaction time and lick count. In contrast, striosomal activity during licking was predominantly associated with the dorsal-ventral position. These findings demonstrate that neural matrix activity is systematically associated with spatial features of licking behavior, with distinct contributions before and during movement. Our results suggest that striatal matrix circuits provide task-relevant spatial signals for the control of orofacial actions. Significant StatementWe show that neural activity in the striatal matrix is associated with the three-dimensional position of a licking target during an operant task. Activity prior to licking onset reflects dorsal-ventral position, whereas activity during licking is modulated by the anterior-posterior and medial-lateral positions. These findings indicate that matrix activity represents spatial aspects of licking behavior, supporting a role for the striatum in integrating motor execution with task-specific spatial information and pointing to the matrix compartment as a substrate for transforming spatial coordinates into action-specific motor commands.