bioRxiv Subject Collection: Neuroscience's Journal

Task-specific topographical maps of neural activity in the primate lateral prefrontal cortex
Neurons in the primate lateral prefrontal cortex (LPFC) flexibly adapt their activity to support a wide range of cognitive tasks. Whether and how the topography of LPFC neural activity changes as a function of task is unclear. In the present study, we address this issue by characterizing the functional topography of LPFC neural activity in awake behaving macaques performing three distinct cognitive tasks. We recorded from chronically implanted multi-electrode arrays and show that the topography of LPFC activity is stable within a task, but adaptive across tasks. The topography of neural activity exhibits a spatial scale compatible with that of cortical columns and prior anatomical tracing work on afferent LPFC inputs. Our findings show that LPFC maps of neural population activity are stable for a specific task, providing robust neural codes that support task specialization. Moreover, the variability in functional topographies across tasks indicates activity landscapes can adapt, providing flexibility to LPFC neural codes.

Neuron Derived Cytokine Interleukin-34 Controls Developmental Microglia Function
Neuron-microglia interactions dictate the development of neuronal circuits in the brain. However, the factors that support and broadly regulate these processes across developmental stages are largely unknown. Here, we find that IL34, a neuron-derived cytokine, is upregulated in development and plays a critical role in supporting and maintaining neuroprotective, mature microglia in the anterior cingulate cortex (ACC) of mice. We show that IL34 mRNA and protein is upregulated in neurons in the second week of postnatal life and that this increase coincides with increases in microglia number and expression of mature, homeostatic markers, e.g., TMEM119. We also found that IL34 mRNA is higher in more active neurons, and higher in excitatory (compared to inhibitory) neurons. Genetic KO of IL34 prevents the functional maturation of microglia and results in an anxiolytic phenotype in these mice by adulthood. Acute, low dose blocking of IL34 at postnatal day (P)15 in mice decreased microglial TMEM119 expression and increased aberrant microglial phagocytosis of thalamocortical synapses within the ACC. In contrast, viral overexpression of IL34 early in life (P1-P8) caused early maturation of microglia and prevented microglial phagocytosis of thalamocortical synapses during the appropriate neurodevelopmental refinement window. Taken together, these findings establish IL34 as a key regulator of neuron-microglia crosstalk in postnatal brain development, controlling both microglial maturation and synapse engulfment.

Cell-type specific auditory responses in the striatum are shaped by feed forward inhibition
The posterior "tail" region of the striatum receives dense innervation from sensory brain regions and has been demonstrated to play a role in behaviors that require sensorimotor integration including discrimination avoidance and defense responses. The output neurons of the striatum, the D1 and D2 striatal projection neurons (SPNs) that make up the direct and indirect pathways, respectively, are thought to play differential roles in these behavioral responses, although it remains unclear if or how these neurons display differential responsivity to sensory stimuli. Here, we used whole-cell recordings in vivo and ex vivo to examine the strength of excitatory and inhibitory synaptic inputs onto D1 and D2 SPNs following the stimulation of upstream auditory pathways. While D1 and D2 SPNs both displayed stimulus-evoked depolarizations, D1 SPN responses were stronger and faster for all stimuli tested in vivo as well as in brain slices. This difference did not arise from differences in the strength of excitatory inputs but from differences in the strength of feed forward inhibition. Indeed, fast spiking interneurons, which are readily engaged by auditory afferents exerted stronger inhibition onto D2 SPNs compared to D1 SPNs. Our results support a model in which differences in feed forward inhibition enable the preferential recruitment of the direct pathway in response to auditory stimuli, positioning this pathway to initiate sound-driven actions.

Intracranial substrates of meditation-induced neuromodulation in amygdala and hippocampus
Meditation is an accessible mental practice associated with emotional regulation and well-being. Loving-kindness meditation (LKM), a specific sub-type of meditative practice, involves focusing attention on thoughts of well-being for oneself and others. Meditation has been proven to be beneficial in a variety of settings, including therapeutical applications, but the neural activity underlying meditative practices and their positive effects are not well understood. In particular, it has been difficult to understand the contribution of deep limbic structures given the difficulty of studying neural activity directly in the human brain. Here, we leverage a unique patient population, epilepsy patients chronically implanted with responsive neurostimulation device that allow chronic, invasive electrophysiology recording to investigate the physiological correlates of loving-kindness meditation in the amygdala and hippocampus of novice meditators. We find that LKM-associated changes in physiological activity specific to periodic, but not aperiodic, features of neural activity. LKM was associated with an increase in gamma (30-55 Hz) power and an alternation in the duration of beta (13-30 Hz) and gamma; oscillatory bursts in both the amygdala and hippocampus, two regions associated with mood disorders. These findings reveals the nature of LKM-induced modulation of limbic activity in first-time meditators.

Maximising the translational potential of neurophysiology in amyotrophic lateral sclerosis: a study on compound muscle action potentials
Transgenic mouse models of amyotrophic lateral sclerosis, such as the widely used SOD1G93A mouse, enable investigation of disease mechanisms and testing of novel therapeutic interventions. However, treatments that have been considered successful in mice have often failed to translate into human benefit in clinical trials, particularly when relying on the so-called 'survival' read-out. Compound muscle action potentials (CMAPs), are a simple neurophysiological test that measures the summation of muscle fibre depolarisation in response to maximal stimulation of the innervating nerve. CMAPs can be measured in both mice and humans and decline with motor axon loss in ALS, making them a potential translational read-out of disease progression which could help bridge the preclinical and clinical divide. Herein we assess the translational potential of CMAPs and ascertain at what time points human and mouse data aligned most closely. We extracted data from 18 human studies and compared with results generated from SOD1G93A and control mice at different ages across different muscles. We found that the relative CMAP amplitude difference between SOD1G93A and control mice in tibialis anterior and gastrocnemius muscles at 70 days of age was most similar to the relative difference between baseline ALS patient CMAP measurements and healthy controls in the abductor pollicis brevis (APB) muscle. We also found that the relative decline in SOD1G93A tibialis anterior CMAP amplitude between 70-140 days was similar to that observed in 12 month human longitudinal studies in APB. Our findings suggest CMAP amplitudes can provide a 'translational window', from which to make comparisons between the SOD1G93A model and human ALS patients. CMAPs are easy to perform and can help determine the most clinically relevant starting/end points for preclinical studies and provide a basis for predicting potential clinical effect sizes.

Augmenting visual errors or variability does not enhance motor learning in remote web application tasks
Laboratory experiments employing robotic manipulandum are far from achieving their goal of helping people improve their motor learning. Remote experiments using web applications are an effective tool for bridging the gap between robotic manipulandum experiments in the laboratory and general motor tasks outside. However, the influence of interventions that increase error or variability in remote motor tasks on motor learning has not yet been determined. In this study, we aimed to elucidate the effects of interventions that visually increase errors and variability in remote experiments using web applications. In particular, 48 people participated in a web-based study on the cursor-manipulation of motor tasks using laptops. Three motor tasks (visuomotor-rotation reaching, virtual curling, and virtual ball-throwing tasks) were conducted, and each task consisted of 120 trials a day conducted for three days in this study. For each task, no intervention was provided on Day 1 and the intervention to augment motor error or variability was provided on Days 2 and 3. Differences between the groups in post-intervention test trials were examined using statistical analyses. Contrary to our expectations, the interventions of error-augmentation did not exhibit positive effects in Experiments 1 and 2, which could be attributed to a lack of haptic and proprioceptive information or inaccuracies in movement kinematics. In addition, the interventions of variability-augmentation did not exhibit positive effects in Experiment 3, which could be attributed to the complex dynamics in the relationship between perceived body movements and motor outcomes. Further research is required to identify the differences between the conditions when the interventions are effective or ineffective. Moreover, interventions must be developed to further improve general motor skills.

Neuropeptide Y co-opts neuronal ensembles for memory lability and stability
Memory engrams are formed by activity-dependent recruitment of distinct subsets of excitatory principal neurons (or neuronal ensembles) whereas inhibitory neurons pivot memory lability and stability (1-5). However, the molecular logic for memory engrams to preferentially recruit specific type of interneurons over other subtypes remains enigmatic. Using activity-dependent single-cell transcriptomic profiling6-8 in mice with training of cued fear memory and extinction, we discovered that neuropeptide Y (NPY)-expressing (NPY+) GABAergic interneurons in the ventral hippocampal CA1 (vCA1) region exert fast GABAergic inhibition to facilitate the acquisition of memory, but bifurcate NPY-mediated slow peptidergic inhibition onto distinct sub-ensembles underlying the extinction of single memory trace. Genetically encoded calcium and NPY sensors revealed that both calcium dynamics of NPY+ neurons and their NPY release in vCA1 ramp up as extinction learning progresses while behavioral state switches from "fear-on" to "fear-off". Bidirectional manipulations of NPY+ neurons or NPY itself demonstrated NPY is both necessary and sufficient to control the rate and degree of memory extinction by acting on two physically non-overlapping sub-ensembles composed of NPY1R- and NPY2R-expressing neurons. CRISPR/Cas9-mediated knockout of NPY2R or NPY1R further unravels that NPY co-opts its actions on these two sub-ensembles to gate early fast and late slow stages of extinction. These findings exemplify the intricate spatiotemporal orchestration of slow peptidergic inhibitions from single subtype of GABAergic interneurons to fine-tune engram lability verse stability of memory.

Encoding of interdependent features of head direction and angular head velocity in navigation
To comprehend the complex world around us, our brains are tasked with the remarkable job of integrating multiple features into a cohesive whole. While previous studies have primarily focused on the processing and integration of independent features, here we investigated the simultaneous encoding of the interdependent features, specifically head direction (HD) and its temporal derivative, angular head velocity (AHV), by first employing computational modeling on HD systems to explore emergent algorithms and then validated its biological plausibility with empirical data from mice's HD systems. Our analysis revealed two distinct neuron populations: those with multiphasic tuning curves for HD compromised their HD encoding capacity to better capture AHV dynamics, while those with monophasic tuning curves primarily encoded HD. This pattern of functional dissociation was observed in both artificial HD systems and the cortical and subcortical regions upstream of biological HD systems, suggesting a general principle for encoding interdependent features. Further, exploration of the underlying mechanisms involved examining neural manifolds embedded within the representational space constructed by these neurons. We found that the manifold by neurons with multiphasic tuning curves was locally jagged and complex, which effectively expanded the dimensionality of the neural representation space and in turn facilitated a high-precision representation of AHV. Therefore, the encoding strategy for HD and AHV likely integrates characteristics of both dense and sparse coding schemes to achieve a balance between preserving specificity for individual features and maintaining their interdependency nature, marking a significant departure from the encoding of independent features and thus advocating future research delving into the encoding strategies of interdependent features.

Emerging neurodevelopmental mechanisms in patient induced pluripotent stem cells-derived spheroids modelling SCN1A Dravet Syndrome
SCN1A encodes Nav1.1, a voltage-gated sodium channel preferentially expressed in GABAergic interneurons, and it is the major cause of Dravet Syndrome (DS), a rare condition of developmental and epileptic encephalopathy (DEE). Among over 1000 DS mutations reported to date, almost all cause SCN1A loss-of function (LoF). A reduction in NaV1.1 function in inhibitory neurons would subsequently cause an over-excitation of glutamatergic neurons resulting in seizures, which are exacerbated by the use of sodium channel blocking common anti-seizure medications (ASM). In this study we generated and assessed 3D spheroids enriched with GABAergic neurons from SCN1A DS patient to establish a 3D human-derived DS model. To investigate developmental disruptions in DS pathophysiology we profiled the transcriptome of patient-derived spheroids and subsequently, tested the capability of this 3D in vitro model to reveal the cellular mechanisms of DS and predict drug response. In summary, our patient iPSC-derived neuronal model of SCN1A DS revealed a profound dysregulation of developmental processes which correlated with functional disruption in GABAergic neurons and predicted response to fenfluramine, an ASM increasingly used for the treatment of DS.

Individual differences in prefrontal coding of visual features
The lateral prefrontal cortex (LPFC) is commonly associated with high-level cognition, such as attention, language and cognitive control. However, recent work has demonstrated that it is also critical for basic perceptual functions including object recognition. Here we characterize the role of LPFC in visual processing with computational models. Using a dataset of human fMRI data at 7T, we built encoding models relating visual features extracted from a deep neural network (the image encoder of a CLIP [Contrastive Language-Image Pre-training] network) to brain responses to thousands of natural images. Within each of the eight subjects, we were able to robustly predict responses in patches of LPFC, most notably in FEF (frontal eye field) and vlPFC (ventrolateral PFC) regions. Leveraging these robust encoding models, we then explored the representational structures and screened for images with high predicted responses in LPFC . We found striking individual differences in the coding schemes of LPFC. In contrast, the coding scheme of the ventral visual stream remains more consistent across individuals. Overall, our study demonstrates the under-appreciated role of LPFC in visual processing and suggests that LPFC may underlie the idiosyncrasies in how different individuals experience the visual world. Methodologically, these findings may also explain why previous group studies have often failed to observe robust visual functions in LPFC, as subjects' responses may need to be calibrated individually.

Neuronal protein phosphatase 1β regulates glutamate release, cortical myelination, node of Ranvier formation, and action potential propagation in the optic nerve
Precise regulation of protein phosphorylation is critical for many cellular processes, and dysfunction in this process has been linked to various neurological disorders and diseases. Protein phosphatase 1 (PP1) is a ubiquitously expressed serine/threonine phosphatase with three major isoforms, (, {beta}, {gamma}) and hundreds of known substrates. Previously, we reported that PP1 and PP1{gamma} are essential for the known role of PP1 in synaptic physiology and learning/memory, while PP1{beta} displayed a surprising opposing function. De novo mutations in PP1{beta} cause neurodevelopmental disorders in humans, but the mechanisms involved are currently unknown. A Cre-Lox system was used to delete PP1{beta} specifically in neurons in order to study its effects on developing mice. These animals fail to survive to 3 postnatal weeks, and exhibit deficits in cortical myelination and glutamate release. There was defective compound action potential (CAP) propagation in the optic nerve of the null mice, which was traced to a deficit in the formation of nodes of Ranvier. Finally, it was found that phosphorylation of the PP1{beta}-specific substrate, myosin light chain 2 (MLC2), is significantly enhanced in PP1{beta} null optic nerves. Several novel important in vivo roles of PP1{beta} in neurons were discovered, and these data will aid future investigations in delineating the mechanisms by which de novo mutations in PP1{beta} lead to intellectual and developmental delays in patients.

Impairments in proprioceptively-referenced limb and eye movements in chronic stroke
Background: Upper limb proprioceptive impairments are common after stroke and can affect daily function. Recent work has shown that stroke survivors have difficulty using visual information to improve proprioception. It is unclear how eye movements are impacted to guide action of the arm after stroke. Here, we aimed to understand how upper limb proprioceptive impairments impact eye movements in individuals with stroke. Methods: Control (N=20) and stroke participants (N=20) performed a proprioceptive matching task with upper limb and eye movements. A KINARM exoskeleton with eye tracking was used to assess limb and eye kinematics. The upper limb was passively moved by the robot and participants matched the location with either an arm or eye movement. Accuracy was measured as the difference between passive robot movement location and the active limb matching (Hand-End Point Error) or the active eye movement matching (Eye-End Point Error). Results: We found that individuals with stroke had significantly larger Hand and Eye-End Point Errors compared to controls. Further, we found that stroke participants had proprioceptive errors of the hand and eye were highly correlated [r=0.67, p=0.001], a relationship not observed for controls. Conclusions: Eye movement accuracy declined as a function of proprioceptive impairment of the more-affected limb, which was used as a proprioceptive reference. The inability to use proprioceptive information of the arm to coordinate eye movements suggests that disordered proprioception impacts integration of sensory information across different modalities. These results have important implications for how vision is used to actively guide limb movement during rehabilitation.

EEG frequency tagging reveals the integration of dissimilar observed actions
Extensive research has demonstrated that visual and motor cortices can simultaneously represent multiple observed actions. This ability undoubtedly constitutes a crucial ingredient for the understanding of complex visual scenes involving different agents. However, it is still unclear how these distinct representations are integrated into coherent and meaningful percepts. In line with studies of perceptual binding, we hypothesized that similar movements would be more easily integrated. To test this hypothesis, we developed an EEG frequency tagging experiment in which two hand movements were displayed simultaneously at two different presentation rates. Crucially, the degree of similarity between the two movements varied along two dimensions, namely action identity (i.e., same or different performed movement), and agent identity (i.e., one agent performing a bimanual movement, or two agents moving each one hand). Contrary to our predictions, we found a larger intermodulation oscillatory component, indexing the integrated processing of the two individual movements, when they were less similar. We propose that integration-by-dissimilarity might serve as a top-down process to solve conflict caused by incongruent movements in a complex social scene.

Connecting the Dots: Approaching a Standardized Nomenclature for Molecular Connectivity Combining Data and Literature
PET-based connectivity computation is a molecular approach that complements fMRI-derived functional connectivity. However, the diversity of methodologies and terms employed in PET connectivity analysis has resulted in ambiguities and confounded interpretations, highlighting the need for a standardized nomenclature. Drawing parallels from other imaging modalities, we propose 'molecular connectivity' as an umbrella term to characterize statistical dependencies between PET signals across brain regions at the individual level (within-subject). Like fMRI resting-state functional connectivity, 'molecular connectivity' leverages temporal associations in the PET signal to derive brain network associations. Another within-subject approach evaluates regional similarities of tracer kinetics, which are unique in PET imaging, thus referred to as 'kinetic connectivity'. On the other hand, 'molecular covariance' denotes group-level computations of covariance matrices across-subject. Further specification of the terminology can be achieved by including the employed radioligand, such as 'metabolic connectivity/covariance' for [18F]FDG as well as 'tau/amyloid covariance' for [18F]flutemetamol / [18F]flortaucipir. To augment these distinctions, high-temporal resolution functional [18F]FDG PET scans from 17 healthy participants were analysed with common techniques of molecular connectivity and covariance, allowing for a data-driven support of the above terminology. Our findings demonstrate that temporal band-pass filtering yields structured network organization, whereas other techniques like 3rd order polynomial fitting, spatio-temporal filtering and baseline normalization require further methodological refinement for high-temporal resolution data. Conversely, molecular covariance from across-subject data provided a simple means to estimate brain region interactions through regularized or sparse inverse covariance estimation. A standardized nomenclature in PET-based connectivity research can reduce ambiguity, enhance reproducibility, and facilitate interpretability across radiotracers and imaging modalities. Via a data-driven approach, this work provides a transparent framework for categorizing and comparing PET-derived connectivity and covariance metrics, laying the foundation for future investigations in the field.

States of functional connectivity flow and their multiplex dynamics in human epilepsy and postictal aphasia
The mechanisms that cause aphasia as a transient post-seizure symptom in epileptic patients are yet unknown. We analyse intracranial EEG (sEEG) recordings of patients suffering from pharmaco- resistant epilepsy with postictal aphasia. We study the Functional Connectivity (FC) between different cortical sites in a time- and frequency-resolved manner, representing each recording as a time-varying, multilayer network (dynamic multiplex). We studied in particular: the rate of overall reconfiguration of links from one frame to the next, or dynamic Functional Connectivity (dFC) speed; and the stability of network modules through time, by means of a dynamic modular Allegiance (dA) analysis. The combination of these two approaches allows identifying states of "Functional Connectivity flow" (beyond connectivity states), defined as epochs in which network reconfiguration occurs with comparable speed and degree of spatio-temporal coordination. Our unsupervised analyses reveal then that high-frequency dFC is slowed down in a long postictal phase lasting well beyond the ictal episodes themselves. Furthermore, a pathological state of slow and poorly structured network flow consistently co-occurs with episodes of aphasia symptoms annotated by the clinicians. In conclusion, our multiplex network dynamics description cast light on functional mechanisms of postictal cognitive dysfunction at the level of individual patients.

25-hydroxycholesterol dysregulates brain endothelial cell function and exacerbates cerebral haemorrhage
Viral infection and hypocholesterolaemia are two independent risk factors for intracerebral haemorrhage (ICH), but the molecular mechanisms leading to vascular rupture via these risk factors remain unknown. We hypothesised that the enzyme cholesterol 25-hydroxylase (CH25H) and its metabolite 25-hydroxycholesterol (25HC), which modulates cholesterol metabolism during infection, may offer a mechanistic link between cholesterol dysregulation and infection during neurovascular dysfunction. We identified an upregulation of CH25H in infection-associated cerebral haemorrhage, in a SARS-CoV-2-induced zebrafish ICH model and foetal human SARS-CoV-2-associated cortical microbleeds. Using human brain endothelial cells and zebrafish ICH models, we show that 25HC promotes endothelial dysfunction and exacerbates brain bleeding. These effects involved cholesterol metabolism modulation, as cholesterol supplementation rescued these effects, while 25HC and statin treatments interacted to exacerbate dysfunction. We propose that the CH25H/25HC pathway represents an important component in the pathophysiology of brain vessel dysfunction associated with infection and cholesterol dysregulation in the context of ICH.

Cannabinoid receptor 1 positive allosteric modulator ZCZ011 shows differential effects on behavior and the endocannabinoid system in HIV-1 Tat transgenic female and male mice
The cannabinoid receptor type 1 (CB1R) is a promising therapeutic target for various neurodegenerative diseases, including HIV-1-associated neurocognitive disorder (HAND). However, the therapeutic potential of CB1R by direct activation is limited due to its psychoactive side effects. Therefore, research has focused on indirectly activating the CB1R by utilizing positive allosteric modulators (PAMs). Studies have shown that CB1R PAMs (ZCZ011 and GAT211) are effective in mouse models of Huntington's disease and neuropathic pain, and hence, we assess the therapeutic potential of ZCZ011 in a well-established mouse model of neuroHIV. The current study investigates the effect of chronic ZCZ011 treatment (14 days) on various behavioral paradigms and the endocannabinoid system in HIV-1 Tat transgenic female and male mice. Chronic ZCZ011 treatment (10 mg/kg) did not alter body mass, locomotor activity, or anxiety-like behavior regardless of sex or genotype. However, differential effects were noted in hot plate latency, motor coordination, and recognition memory in female mice only, with ZCZ011 treatment increasing hot plate latency and improving motor coordination and recognition memory. Only minor effects or no alterations were seen in the endocannabinoid system and related lipids except in the cerebellum, where the effect of ZCZ011 was more pronounced in female mice. Moreover, AEA and PEA levels in the cerebellum were positively correlated with improved motor coordination in female mice. In summary, these findings indicate that chronic ZCZ011 treatment has differential effects on antinociception, motor coordination, and memory, based on sex and HIV-1 Tat expression, making CB1R PAMs potential treatment options for HAND without the psychoactive side effects.

EVIDENCE OF SPATIAL PERIODIC FIRING IN THE SUBICULUM OF MICE
The subiculum (SUB) is a region located at the core of the hippocampal formation. The SUB receives inputs from grid cells located in the medial entorhinal cortex (MEC) and from place cells in the CA1 area. Moreover, this structure mediates the output from the hippocampus to cortical and sub-cortical areas involved in the processing of different types of information. Despite the potential relevance of the SUB, its role in memory and spatial coding remains poorly studied. Previous work described a heterogeneous population of SUB spatial neurons, with evidence of its role in coding the geometry of the environment and spatial navigation in darkness. With the aim of understanding further the properties of spatial coding in the SUB, we implanted mice with microdrives carrying tetrodes to target CA1 and the SUB. Apart from the classical place cells described before, we discovered a fraction of SUB pyramidal neurons that generated spatial periodic firing. SUB spatial neurons presented lower spatial resolution and spatial stability than CA1 place cells. The role of spatial periodic neurons in the SUB might be relevant in several computations through the interaction of this region with CA1, the pre-parasubiculum and the MEC.

Molecular Myelin Dysfunction in the Most Common Inherited Peripheral Neuropathies - CMT1A and HNPP
Increased and decreased dosage of the Peripheral Myelin Protein 22 (PMP22) gene cause dysmyelinating peripheral neuropathy. Charcot-Marie-Tooth Disease Type 1A (CMT1A, PMP22 duplication) and Hereditary Neuropathy with Liability to Pressure Palsies (HNPP, PMP22 deletion) are the most common inherited peripheral neuropathies, yet gaps remain about their pathophysiology and pathomechanims. Our previous results with CMT1A model mice demonstrate that muscle atrophy occurs without evidence of secondary axon degeneration suggesting that primary myelin dysfunction may contribute to functional deficits in CMT1A and motivating investigation of myelin dysfunction. Here we used CMT1A and HNPP model mice and confocal immunofluorescence imaging of teased tibial nerve fibers to determine how altered PMP22 expression disrupts myelin integrity and reveal CMT1A and HNPP pathomechanisms. We identified dramatic changes to molecular machinery at Schmidt-Lanterman incisures (SLIs) and Nodes of Ranvier that led us to propose two potential pathomechanisms for CMT1A and HNPP: impaired metabolic support and axonal ion disequilibrium. We also developed a working model for these pathomechanims that is driven by PMP22-mediated regulation of adherens junctions. Ongoing studies are aimed at testing these proposed pathomechanisms and determining how altered PMP22 and adherens junctions cause these defects. This work will provide insight into CMT1A and HNPP pathogenesis and may reveal novel approaches for developing therapeutics.

Two-photon voltage imaging with rhodopsin-based sensors
The recent advances in sophisticated optical techniques, coupled with two-photon sensitive genetic voltage indicators (GEVIs), have enabled in-depth voltage imaging in vivo at single spike and single-cell resolution. To date, these results have been only achieved using ASAP-type sensors, as the complex photocycle of rhodopsin-based voltage indicators posed challenges for their two-photon use, restricting their application to one-photon approaches. In this work, we demonstrate that rhodopsin-based GEVIs (FRET-opsin) can be used under two-photon illumination when their peculiar light intensity dependence of kinetics and sensitivity are considered. We rationally engineer a fully genetically-encoded, rhodopsin-based voltage indicator with the brightest known fluorophore AaFP1, Jarvis, and demonstrate its utility under both one- and two-photon illumination. We also showed two-photon usability of the similar FRET-opsin sensor pAce. Our comparison of 2P scanless with fast 2P scanning illumination revealed that the latter approach is less suitable for this class of indicators and, on the contrary, both sensors responded well when scanless approaches were used. Furthermore, utilising Jarvis, we demonstrated high-fidelity, high-SNR action potential detection at kilohertz-imaging rates both in mouse hippocampal slices and in zebrafish larvae. To the best of our knowledge, this study represents the first report of a fully genetically-encoded rhodopsin-based voltage indicator for high contrast action potential detection under two-photon illumination in vitro and in vivo.

Optimal AAV capsid/promoter combinations to target specific cell types in the common marmoset cerebral cortex
To achieve cell type-specific gene expression, using target cell-tropic AAV capsids is advantageous. However, their tropism across brain cell types remains unexplored in non-human primates. We assessed the tropism of nine AAV serotype capsids (AAV1, 2, 5, 6, 7, 8, 9, rh.10 (rh10), and DJ) on marmoset cerebral cortical cell types. Marmoset cerebral cortex was injected with different serotype AAVs expressing enhanced GFP (EGFP) by the ubiquitous chicken beta-actin hybrid (CBh) promoter. After 4 weeks, all nine AAV capsid vectors, especially AAV9 and AAVrh10, caused highly neuron-selective EGFP expression. Some AAV capsids, including AAV5, caused EGFP expression in oligodendrocytes to a lesser extent, with minimal or no expression in astrocytes and microglia. Different ubiquitous CMV and CAG promoters showed similar neuron-predominant transduction. Conversely, all nine AAV capsid vectors with the astrocyte-specific hGFA(ABC1D) promoter selectively transduced astrocytes, except AAV5, which transduced oligodendrocytes modestly. Oligodendrocyte-specific mouse myeline basic protein (mMBP) promoter in AAV5 vectors transduced oligodendrocytes specifically and efficiently. Our results suggest optimal combinations of capsids and promoters for cell type-specific expression: AAV9 or AAVrh10 and ubiquitous CBh, CMV, or CAG promoter for neuron-specific transduction; AAV2 or 7 and hGFA(ABC1D) promoter for astrocyte-specific transduction; and AAV5 and mMBP promoter for oligodendrocyte-specific transduction.

AVN: A Deep Learning Approach for the Analysis of Birdsong
Deep learning tools for behavior analysis have enabled important new insights and discoveries in neuroscience. Yet, they often compromise interpretability and generalizability for performance, making it difficult to quantitively compare phenotypes across datasets and research groups. We developed a novel deep learning-based behavior analysis pipeline, Avian Vocalization Network (AVN), for the learned vocalizations of the most extensively studied vocal learning model species - the zebra finch. AVN annotates songs with high accuracy across multiple animal colonies without the need for any additional training data and generates a comprehensive set of interpretable features to describe the syntax, timing, and acoustic properties of song. We use this feature set to compare song phenotypes across multiple research groups and experiments, and to predict a bird's stage in song development. Additionally, we have developed a novel method to measure song imitation that requires no additional training data for new comparisons or recording environments, and outperforms existing similarity scoring methods in its sensitivity and agreement with expert human judgements of song similarity. These tools are available through the open-source AVN python package and graphical application, which makes them accessible to researchers without any prior coding experience. Altogether, this behavior analysis toolkit stands to facilitate and accelerate the study of vocal behavior by enabling a standardized mapping of phenotypes and learning outcomes, thus helping scientists better link behavior to the underlying neural processes.

Depression in Parkinson's disease is associated with dopamine unresponsive reduced reward sensitivity during effort-based decision making
Willingness to exert effort for a given goal is dependent on the magnitude of the potential rewards and effort costs of an action. Such effort-based decision making is an essential component of motivation, in which the dopaminergic system plays a key role. Depression in Parkinson's disease (PD) is common, disabling and has poor outcomes. Motivational symptoms such as apathy and anhedonia, are prominent in PD depression and related to dopaminergic loss. We hypothesised that dopamine-dependent disruption in effort-based decision-making contributes to depression in PD. In the present study, an effort-based decision-making task was administered to 62 patients with PD, with and without depression, ON and OFF their dopaminergic medication across two sessions, as well as to 34 patients with depression and 29 matched controls on a single occasion. During the task, on each trial, participants decided whether to accept or reject offers of different levels of monetary reward in return for exerting varying levels of physical effort via grip force, measured using individually calibrated dynamometers. The primary outcome variable was choice (accept/decline offer), analysed using both logistic mixed-effects modelling and a computational model which dissected the individual contributions of reward and effort on depression and dopamine state in PD. We found PD depression was characterised by lower acceptance of offers, driven by markedly lower incentivisation by reward (reward sensitivity), compared to all other groups. Within-subjects analysis of the effect of dopamine medication revealed that, although dopamine treatment improves reward sensitivity in non-depressed PD patients, this therapeutic effect is not present in PD patients with depression. These findings suggest that disrupted effort-based decision-making, unresponsive to dopamine, contributes to PD depression. This highlights reward sensitivity as a key mechanism and treatment target for PD depression that potentially requires non-dopaminergic therapies.

"What" and "when" predictions jointly modulate speech processing
Adaptive behavior rests on forming predictions based on previous statistical regularities encountered in the environment. Such regularities pertain not only to the contents of the stimuli ("what") but also their timing ("when"), and both interactively modulate sensory processing. In speech streams, predictions can be formed at multiple hierarchical levels, both in terms of contents (e.g. single syllables vs. words) and timing (e.g., faster vs. slower time scales). Whether and how these hierarchies map onto each other in terms of integrating "what" and "when" predictions remains unknown. Under one hypothesis neural hierarchies may link "what" and "when" predictions within sensory processing areas: with lower cortical regions mediating interactions for smaller units e.g., syllables, and higher cortical areas mediating interactions for larger units e.g., words. Alternatively, interactions between "what" and "when" predictions might rest on a generic, sensory-independent mechanism, mediated by common attention-related (e.g., frontoparietal) networks. To address those questions, we manipulated "what" and "when" predictions at two levels - single syllables and disyllabic pseudowords - while recording neural activity using magnetoencephalography (MEG) in healthy volunteers (N=22). We studied how syllable and/or word deviants are modulated by "when" predictability, both analyzing event-related fields and using source reconstruction and dynamic causal modeling to explain the observed effects in terms of the underlying effective connectivity. "When" predictions modulated "what" mismatch responses in a specific way with regards to speech hierarchy, such that mismatch responses to deviant words (vs. syllables) were amplified by temporal predictions at a slower (vs. faster) time scale. However, these modulations were source-localized to a shared network of cortical regions, including frontal and parietal sources. Effective connectivity analysis showed that, while mismatch responses to violations of "what" predictions modulated connectivity between regions, the integration of "what" and "when" predictions selectively modulated connectivity within regions, consistent with gain effects. These results suggest that the brain integrates "what" and "when" predictions that are congruent with respect to their hierarchical level, but this integration is mediated by a shared and distributed cortical network. This contrasts with recent studies indicating separable networks for different levels of hierarchical speech processing.

Near infrared fluorescent nanosensors for high spatiotemporal oxytocin imaging
Oxytocin is a neuropeptide thought to play a central role in regulating social and emotional behavior. Current techniques for neuropeptide imaging are generally limited in spatial and temporal resolution, real-time imaging capacity, selectivity for oxytocin over vasopressin, and application in young and non-model organisms. To avoid the use of endogenous oxytocin receptors for oxytocin probe development, we employed a protocol to evolve purely synthetic molecular recognition on the surface of near-infrared fluorescent single-walled carbon nanotubes (SWCNT) using single-stranded DNA (ssDNA). This probe reversibly undergoes up to a 172% fluorescence increase in response to oxytocin with a Kd of 4.93 uM. Furthermore, this probe responds selectively to oxytocin over oxytocin analogs, receptor agonists and antagonists, and most other neurochemicals. Lastly, we show our probe can image synaptic evoked oxytocin release in live mouse brain slices. Optical probes with the specificity and resolution requisite to image endogenous oxytocin signaling can advance the study of oxytocin neurotransmission for its role in both health and disease.

Sex-dependent effects of early life stress on network and behavioral states.
BackgroundAdverse childhood experiences (ACEs) are associated with numerous detriments in health, including increased vulnerability to psychiatric illnesses. Early life stress (ELS) in rodents has been shown to effectively model several of the behavioral and endocrine impacts of ACEs and has been utilized to investigate the underlying mechanisms contributing to disease. However, the precise neural mechanisms responsible for mediating the impact of ELS on vulnerability to psychiatric illnesses remain largely unknown.

MethodsWe use behavior, immunoassay, in vivo LFP recording, histology, and patch clamp to describe the effects of ELS on stress behaviors, endocrinology, network states, protein expression, and cellular physiology in male and female mice.

ResultsWe demonstrate that a murine maternal separation (MS) ELS model causes sex-dependent alterations in behavioral and hormonal responses following an acute stressor. Local field potential (LFP) recordings in the basolateral amygdala (BLA) and frontal cortex (FC) reveal similar sex-dependent alterations at baseline, in response to acute ethological stress, and during fear memory extinction, supporting a large body of literature demonstrating that these network states contribute to stress reactivity and vulnerability to psychiatric illnesses. Sex differences were accompanied by altered physiology of BLA principal neurons in males and BLA PV interneurons in females.

ConclusionsCollectively, these results implicate novel, sex-dependent mechanisms through which ACEs may impact psychiatric health, involving altered cellular physiology and network states involved in emotional processing.

Developmental alterations of indirect-pathway medium spiny neurons in mouse models of Huntington's disease.
Huntingtons disease (HD) is an inherited neurodegenerative disorder caused by a mutation in the gene encoding the Huntingtin protein (Htt). While symptoms, primarily characterized by progressive deterioration of the striatum and motor and cognitive functions, typically manifest in adulthood, recent studies have also highlighted developmental defects in HD. Indeed, alterations in cortical and striatal development have been observed in individuals carrying the mutation as early as in embryonic stages. However, despite the striatum being one of the most affected regions in HD, few studies have investigated potential developmental alterations in this structure, especially in the early weeks after birth. To address this question, we compared striatal development between wild-type (WT) mice and two murine models of HD, R6/1 and CAG140 mice crossed with reporter mice to identify D1- and D2-expressing medium spiny neurons (D1- and D2-MSNs). Using ex vivo electrophysiology and neuronal reconstruction, we observed that the maturation of electrical properties was selectively disrupted in D2-MSNs of the matrix compartment of HD mice during the first post-natal days. D2-MSNs arbor also an increased dendritic complexity. When studying the establishment of striatal afferents, we observed that cortico-striatal glutamatergic transmission was specifically reduced in D2-MSNs during the second postnatal week. All these alterations were transient before the circuit normalized on its own after the second postnatal week. These anatomical and electrophysiological data highlight the significant impact of the Htt mutation on numerous striatal development processes during the postnatal period. Interestingly, we observed that these alterations specifically affect MSNs in the indirect pathway. This preferential vulnerability aligns with the early death of these neurons in adulthood, suggesting that early treatment of these alterations could potentially modify the diseases progression.

Human Substantia Nigra Neurons Encode Reward Expectations
Dopamine (DA) signals originating from substantia nigra (SN) neurons are centrally involved in the regulation of motor and reward processing. DA signals behaviorally relevant events where reward outcomes differ from expectations (reward prediction errors, RPEs). RPEs play a crucial role in learning optimal courses of action and in determining response vigor when an agent expects rewards. Nevertheless, how reward expectations, crucial for RPE calculations, are conveyed to and represented in the dopaminergic system is not fully understood, especially in the human brain where the activity of DA neurons is difficult to study. One possibility, suggested by evidence from animal models, is that DA neurons explicitly encode reward expectations. Alternatively, they may receive RPE information directly from upstream brain regions. To address whether SN neuron activity directly reflects reward expectation information, we directly examined the encoding of reward expectation signals in human putative DA neurons by performing single-unit recordings from the SN of patients undergoing neurosurgery. Patients played a two-armed bandit decision-making task in which they attempted to maximize reward. We show that neuronal firing rates (FR) of putative DA neurons during the reward expectation period explicitly encode reward expectations. First, activity in these neurons was modulated by previous trial outcomes, such that FR were greater after positive outcomes than after neutral or negative outcome trials. Second, this increase in FR was associated with shorter reaction times, consistent with an invigorating effect of DA neuron activity during expectation. These results suggest that human DA neurons explicitly encode reward expectations, providing a neurophysiological substrate for a signal critical for reward learning.

Striatal output regulates the postnatal maturation of cortical circuits
The dorsomedial prefrontal cortex (dmPFC) is interconnected with the basal ganglia (BG) through large-scale circuit loops that regulate critical motor and cognitive functions. In mice, these circuits undergo extensive postnatal maturation with marked changes in neural activity and expansion of synaptic connectivity. While cortical activity is known to regulate the development of downstream striatal circuits, the role of the basal ganglia in cortical maturation remains unknown. Here, we used mesoscale two-photon microscopy and whole-cell electrophysiology to examine whether striatal output during early postnatal development impacts the maturation of upstream dmPFC circuits. We found that ablating spiny projection neurons of the direct or indirect pathways of the striatum during the first two postnatal weeks causes bidirectional changes in dmPFC neural activity, similar to what is observed in mature circuits. In addition, these manipulations alter the maturation of synaptic connectivity of dmPFC layer 2/3 pyramidal neurons, shifting the balance of excitation and inhibition of cortical circuits. These findings demonstrate that striatal output regulates the activity of cortical circuits during early postnatal development and suggest a regulatory role of the basal ganglia in the establishment of cortical circuits.

Switching patterns of cortical-subcortical interaction in the human brain
Resting-state fMRI studies show that functional connectivity (FC), defined as the correlation between the blood-oxygen-level-dependent (BOLD) signals of different brain areas, undergoes rapid fluctuations, a phenomenon called dynamic or time-varying FC. Although the neural mechanisms underlying dynamic FC remain poorly understood, a recent contribution, based on a limited sample size, suggested that FC fluctuations are coordinated between cortex and subcortex, with rapidly switching FC patterns involving a dynamic reconfiguration of cortico-subcortical interactions (Favaretto et al., 2022). Here, building on the Human Connectome Projects database, we replicate those findings in a much larger cohort. Our analysis confirms that FC shifts are synchronized in cortex and subcortex, as two core subcortical clusters comprising, respectively, limbic regions (hippocampus and amygdala) and subcortical nuclei (thalamus and basal ganglia) change their connectivity pattern with cortical regions. In particular, we consistently identify two FC patterns (states). State 1 is characterized by a strong opposition of task-positive (sensorimotor networks, dorsal attention network) and task-negative networks (default mode network, limbic regions), State 2 by a strong segregation between sensorimotor networks and association networks, and a positive coupling of limbic regions with sensorimotor networks. Our findings are robust with respect to changes in the preprocessing pipeline and the precise choice of cortical or subcortical parcellation, and hint at a general relevance of cortico-subcortical interactions in the generation of whole-brain spontaneous FC patterns.