ScanImage: flexible software for operating laser scanning microscopes

Dynamics of glia and neurons regulate homeostatic rest, sleep and feeding behavior in Drosophila

Homeostatic processes, including sleep, are critical for brain function. Here we identify astrocyte-like glia (or astrocytes, AL) and ensheathing glia (EG), the two major classes of glia that arborize inside the brain, as brain-wide, locally acting homeostats for the short, naturally occurring rest and sleep bouts of Drosophila, and show that a subset of neurons in the fan-shaped body encodes feeding homeostasis. We show that the metabolic gas carbon dioxide, changes in pH and behavioral activity all induce long-lasting calcium responses in EG and AL, and that calcium levels in both glia types show circadian modulation. The homeostatic dynamics of these glia can be modeled based on behavior. Additionally, local optogenetic activation of AL or EG is sufficient to induce rest. Together, these results suggest that glial calcium levels are homeostatic controllers of metabolic activity, thus establishing a link between metabolism, rest and sleep.

Activity of human-specific Interlaminar Astrocytes in a Chimeric Mouse Model of Fragile X Syndrome

Astrocytes, a subtype of glial cells, have multiple roles in regulating neuronal development and homeostasis. In addition to the typical mammalian astrocytes, in the primate cortex interlaminar astrocytes are located in the superficial layer and project long processes traversing multiple layers of the cerebral cortex. Previously, we described a human stem cell based chimeric mouse model where interlaminar astrocytes develop. Here, we utilized this model to study the calcium signaling properties of interlaminar astrocytes. To determine how interlaminar astrocytes could contribute to neurodevelopmental disorders, we generated a chimeric mouse model for Fragile X syndrome. We report that FXS interlaminar astrocytes exhibit hyperexcitable calcium signaling and are associated with dendritic spines with increased turnover rate.

A subcortical switchboard for perseverative, exploratory and disengaged states

To survive in dynamic environments with uncertain resources, animals must adapt their behaviour flexibly, choosing strategies such as persevering with a current choice, exploring alternatives or disengaging altogether. Previous studies have mainly investigated how forebrain regions represent choice costs and values as well as optimal strategies during such decisions1-5. However, the neural mechanisms by which the brain implements alternative behavioural strategies such as persevering, exploring or disengaging remain poorly understood. Here we identify a neural hub that is critical for flexible switching between behavioural strategies, the median raphe nucleus (MRN). Using cell-type-specific optogenetic manipulations, fibre photometry and circuit tracing in mice performing diverse instinctive and learnt behaviours, we found that the main cell types of the MRN-GABAergic (γ-aminobutyric acid-expressing), glutamatergic (VGluT2+) and serotonergic neurons-have complementary functions and regulate perseverance, exploration and disengagement, respectively. Suppression of MRN GABAergic neurons-for instance, through inhibitory input from lateral hypothalamus, which conveys strong positive valence to the MRN-leads to perseverative behaviour. By contrast, activation of MRN VGluT2+ neurons drives exploration. Activity of serotonergic MRN neurons is necessary for general task engagement. Input from the lateral habenula that conveys negative valence suppresses serotonergic MRN neurons, leading to disengagement. These findings establish the MRN as a central behavioural switchboard that is uniquely positioned to flexibly control behavioural strategies. These circuits thus may also have an important role in the aetiology of major mental pathologies such as depressive or obsessive-compulsive disorders.

LRRK2 mediates haloperidol-induced changes in indirect pathway striatal projection neurons

Haloperidol is used to manage psychotic symptoms in several neurological disorders through mechanisms that involve antagonism of dopamine D2 receptors that are highly expressed in the striatum. Significant side effects of haloperidol, known as extrapyramidal symptoms, lead to motor deficits similar to those seen in Parkinson's disease and present a major challenge in clinical settings. The underlying molecular mechanisms responsible for these side effects remain poorly understood. Parkinson's disease-associated leucine-rich repeat kinase 2 (LRRK2) has an essential role in striatal physiology and a known link to dopamine D2 receptor signaling. Here, we systematically explore convergent signaling of haloperidol and LRRK2 through pharmacological or genetic inhibition of LRRK2 kinase, as well as knock-in mouse models expressing pathogenic mutant LRRK2 with increased kinase activity. Behavioral assays show that LRRK2 kinase inhibition ameliorates haloperidol-induced motor changes in mice. A combination of electrophysiological and anatomical approaches reveals that LRRK2 kinase inhibition interferes with haloperidol-induced changes, specifically in striatal neurons of the indirect pathway. Proteomic studies and targeted intracellular pathway analyses demonstrate that haloperidol induces a similar pattern of intracellular signaling as increased LRRK2 kinase activity. Our study suggests that LRRK2 kinase plays a key role in striatal dopamine D2 receptor signaling underlying the undesirable motor side effects of haloperidol. This work opens up new therapeutic avenues for dopamine-related disorders, such as psychosis, also furthering our understanding of Parkinson's disease pathophysiology.

Neural correlates of visual object recognition in rats

Invariant object recognition-the ability to recognize objects across size, rotation, or context-is fundamental for making sense of a dynamic visual world. Though traditionally studied in primates, emerging evidence suggests rodents recognize objects across a range of identity-preserving transformations. We demonstrate that rats robustly perform visual object recognition and explore a neural pathway that may underlie this capacity by developing a pipeline from high-throughput behavior training to cellular resolution imaging in awake, head-fixed animals. Leveraging our optical approach, we systematically profile neurons in primary and higher-order visual areas and their spatial organization. We find that rat visual cortex exhibits several features similar to those observed in the primate ventral stream but also marked deviations, suggesting species-specific differences in how brains solve visual object recognition. This work reinforces the sophisticated visual abilities of rats and offers the technical foundation to use them as a powerful model for mechanistic perception.

Ongoing loss of viable neurons for weeks after mild hypoxia-ischaemia

Mild hypoxic-ischaemic encephalopathy is common in neonates, and there are no evidence-based therapies. By school age, 30-40% of those patients experience adverse neurodevelopmental outcomes. The nature and progression of mild injury is poorly understood. We studied the evolution of mild perinatal brain injury using longitudinal two-photon imaging of transgenic fluorescent calcium-sensitive and insensitive proteins to provide a novel readout of neuronal viability and activity at cellular resolution in vitro and in vivo. In vitro, perinatal organotypic hippocampal cultures underwent 15-20 min of oxygen-glucose deprivation. In vivo, mild hypoxia-ischaemia was completed at post-natal day 10 with carotid ligation and 15 min of hypoxia (FiO2, 0.08). Consistent with a mild injury, minimal immediate neuronal death was seen in vitro or in vivo, and there was no volumetric evidence of injury by ex vivo MRI 2.5 weeks after injury (n = 3 pups/group). However, in both the hippocampus and neocortex, these mild injuries resulted in delayed and progressive neuronal loss by the second week after injury compared to controls; measured by fluorophore quenching (n = 6 slices/group in vitro, P < 0.001; n = 8 pups/group in vivo, P < 0.01). Mild hypoxia-ischaemia transiently suppressed cortical network calcium activity in vivo for over 2 h after injury (versus sham, n = 13 pups/group; P < 0.01). No post-injury seizures were seen. By 24 h, network activity fully recovered, and there was no disruption in the development of normal cortical activity for 11 days (n = 8 pups/group). The participation in network activity of individual neurons destined to die in vivo was indistinguishable from those that survived up to 4 days post-injury (n = 8 pups/group). Despite a lack of significant immediate neuronal death and only transient disruptions of network activity, mild perinatal brain injury resulted in a delayed and progressive increase of neuronal death in the hippocampus and neocortex. Neurons that died late were functioning normally for days after injury, suggesting a new pathophysiology of neuronal death after mild injury. Critically, the neurons destined to die late demonstrated multiple biomarkers of viability long after mild injury, suggesting their later death may be modified with neuroprotective interventions.

Classification of collagen remodeling in asthma using second-harmonic generation imaging, supervised machine learning and texture-based analysis

Airway remodeling is present in all stages of asthma severity and has been linked to reduced lung function, airway hyperresponsiveness and increased deposition of fibrillar collagens. Traditional histological staining methods used to visualize the fibrotic response are poorly suited to capture the morphological traits of extracellular matrix (ECM) proteins in their native state, hindering our understanding of disease pathology. Conversely, second harmonic generation (SHG), provides label-free, high-resolution visualization of fibrillar collagen; a primary ECM protein contributing to the loss of asthmatic lung elasticity. From a cohort of 13 human lung donors, SHG-imaged collagen belonging to non-asthmatic (control) and asthmatic donors was evaluated through a custom textural classification pipeline. Integrated with supervised machine learning, the pipeline enables the precise quantification and characterization of collagen, delineating amongst control and remodeled airways. Collagen distribution is quantified and characterized using 80 textural features belonging to the Gray Level Cooccurrence Matrix (GLCM), Gray Level Size Zone Matrix (GLSZM), Gray Level Run Length Matrix (GLRLM), Gray Level Dependence Matrix (GLDM) and Neighboring Gray Tone Difference Matrix (NGTDM). To denote an accurate subset of features reflective of fibrillar collagen formation; filter, wrapper, embedded and novel statistical methods were applied as feature refinement. Textural feature subsets of high predictor importance trained a support vector machine model, achieving an AUC-ROC of 94% ± 0.0001 in the classification of remodeled airway collagen vs. control lung tissue. Combined with detailed texture analysis and supervised ML, we demonstrate that morphological variation amongst remodeled SHG-imaged collagen in lung tissue can be successfully characterized.

Brain-wide microstrokes affect the stability of memory circuits in the hippocampus

Cognitive deficits affect over 70% of stroke survivors, yet the mechanisms by which multiple small ischemic events contribute to cognitive decline remain poorly understood. In this study, we employed chronic two-photon calcium imaging to longitudinally track the fate of individual neurons in the hippocampus of mice navigating a virtual reality environment, both before and after inducing brain-wide microstrokes. Our findings reveal that, under normal conditions, hippocampal neurons exhibit varying degrees of stability in their spatial memory coding. However, microstrokes disrupted this functional network architecture, leading to cognitive impairments. Notably, the preservation of stable coding place cells, along with the stability, precision, and persistence of the hippocampal network, was strongly predictive of cognitive outcomes. Mice with more synchronously active place cells near important locations demonstrated recovery from cognitive impairment. This study uncovers critical cellular responses and network alterations following brain injury, providing a foundation for novel therapeutic strategies preventing cognitive decline.

Psilocybin's lasting action requires pyramidal cell types and 5-HT2A receptors

Psilocybin is a serotonergic psychedelic with therapeutic potential for treating mental illnesses1-4. At the cellular level, psychedelics induce structural neural plasticity5,6, exemplified by the drug-evoked growth and remodelling of dendritic spines in cortical pyramidal cells7-9. A key question is how these cellular modifications map onto cell-type-specific circuits to produce the psychedelics' behavioural actions10. Here we use in vivo optical imaging, chemogenetic perturbation and cell-type-specific electrophysiology to investigate the impact of psilocybin on the two main types of pyramidal cells in the mouse medial frontal cortex. We find that a single dose of psilocybin increases the density of dendritic spines in both the subcortical-projecting, pyramidal tract (PT) and intratelencephalic (IT) cell types. Behaviourally, silencing the PT neurons eliminates psilocybin's ability to ameliorate stress-related phenotypes, whereas silencing IT neurons has no detectable effect. In PT neurons only, psilocybin boosts synaptic calcium transients and elevates firing rates acutely after administration. Targeted knockout of 5-HT2A receptors abolishes psilocybin's effects on stress-related behaviour and structural plasticity. Collectively, these results identify that a pyramidal cell type and the 5-HT2A receptor in the medial frontal cortex have essential roles in psilocybin's long-term drug action.

Learning produces an orthogonalized state machine in the hippocampus

Cognitive maps confer animals with flexible intelligence by representing spatial, temporal and abstract relationships that can be used to shape thought, planning and behaviour. Cognitive maps have been observed in the hippocampus1, but their algorithmic form and learning mechanisms remain obscure. Here we used large-scale, longitudinal two-photon calcium imaging to record activity from thousands of neurons in the CA1 region of the hippocampus while mice learned to efficiently collect rewards from two subtly different linear tracks in virtual reality. Throughout learning, both animal behaviour and hippocampal neural activity progressed through multiple stages, gradually revealing improved task representation that mirrored improved behavioural efficiency. The learning process involved progressive decorrelations in initially similar hippocampal neural activity within and across tracks, ultimately resulting in orthogonalized representations resembling a state machine capturing the inherent structure of the task. This decorrelation process was driven by individual neurons acquiring task-state-specific responses (that is, 'state cells'). Although various standard artificial neural networks did not naturally capture these dynamics, the clone-structured causal graph, a hidden Markov model variant, uniquely reproduced both the final orthogonalized states and the learning trajectory seen in animals. The observed cellular and population dynamics constrain the mechanisms underlying cognitive map formation in the hippocampus, pointing to hidden state inference as a fundamental computational principle, with implications for both biological and artificial intelligence.

A low-cost FPGA-based approach for pile-up corrected high-speed in vivo FLIM imaging

Significance

Intensity-based two-photon microscopy is a cornerstone of neuroscience research but lacks the ability to measure concentrations, a pivotal task for longitudinal studies and quantitative comparisons. Fluorescence lifetime imaging (FLIM) based on time-correlated single photon counting (TCSPC) can overcome those limits but suffers from "pile-up" distortions at high photon count rates, severely limiting acquisition speed.

Aim

We introduce the "laser period blind time" (LPBT) method to correct pile-up distortions in photon counting electronics, enabling reliable low-cost TCSPC-FLIM at high count rates.

Approach

Using a realistic simulation of the TCSPC data collection, we evaluated the LPBT method's performance in silico. The correction was then implemented on low-cost hardware based on a field programable gate array and validated using in vitro, ex vivo, and in vivo measurements.

Results

The LBPT approach achieves < 3 % error in lifetime measurements at count rates more than 10 times higher than traditional limits, allowing robust FLIM imaging of subsecond metabolite dynamics with subcellular resolution.

Conclusions

We enable high-precision, cost-effective FLIM imaging at acquisition speeds comparable with state-of-the-art commercial systems, facilitating the adoption of FLIM in neuroscience and other fields of research needing robust quantitative live imaging solutions.

Activity-dependent regulation of Cdc42 by Ephexin5 drives synapse growth and stabilization

Synaptic Rho guanosine triphosphatase (GTPase) guanine nucleotide exchange factors (RhoGEFs) play vital roles in regulating the activity-dependent neuronal plasticity that is critical for learning. Ephexin5, a RhoGEF implicated in the etiology of Alzheimer's disease and Angelman syndrome, was originally reported in neurons as a RhoA-specific GEF that negatively regulates spine synapse density. Here, we show that Ephexin5 activates both RhoA and Cdc42 in the brain. Furthermore, using live imaging of GTPase biosensors, we demonstrate that Ephexin5 regulates activity-dependent Cdc42, but not RhoA, signaling at single synapses. The selectivity of Ephexin5 for Cdc42 activation is regulated by tyrosine phosphorylation, which is regulated by neuronal activity. Last, in contrast to Ephexin5's role in negatively regulating synapse density, we show that, downstream of neuronal activity, Ephexin5 positively regulates synaptic growth and stabilization. Our results support a model in which plasticity-inducing neuronal activity regulates Ephexin5 tyrosine phosphorylation, driving Ephexin5-mediated activation of Cdc42 and the spine structural growth and stabilization vital for learning.

Broadband visual stimuli improve neuronal representation and sensory perception

Natural scenes consist of complex feature distributions that shape neural responses and perception. However, in contrast to single features like stimulus orientations, the impact of broadband feature distributions remains unclear. We, therefore, presented visual stimuli with parametrically-controlled bandwidths of orientations and spatial frequencies to awake mice while recording neural activity in their primary visual cortex (V1). Increasing orientation but not spatial frequency bandwidth strongly increased the number and response amplitude of V1 neurons. This effect was not explained by single-cell orientation tuning but rather a broadband-specific relief from center-surround suppression. Moreover, neurons in deeper V1 and the superior colliculus responded much stronger to broadband stimuli, especially when mixing orientations and spatial frequencies. Lastly, broadband stimuli increased the separability of neural responses and improved the performance of mice in a visual discrimination task. Our results show that surround modulation increases neural responses to complex natural feature distributions to enhance sensory perception.

Representational learning by optimization of neural manifolds in an olfactory memory network

Cognitive brain functions rely on experience-dependent internal representations of relevant information. Such representations are organized by attractor dynamics or other mechanisms that constrain population activity onto "neural manifolds". Quantitative analyses of representational manifolds are complicated by their potentially complex geometry, particularly in the absence of attractor states. Here we trained juvenile and adult zebrafish in an odor discrimination task and measured neuronal population activity to analyze representations of behaviorally relevant odors in telencephalic area pDp, the homolog of piriform cortex. No obvious signatures of attractor dynamics were detected. However, olfactory discrimination training selectively enhanced the separation of neural manifolds representing task-relevant odors from other representations, consistent with predictions of autoassociative network models endowed with precise synaptic balance. Analytical approaches using the framework of manifold capacity revealed multiple geometrical modifications of representational manifolds that supported the classification of task-relevant sensory information. Manifold capacity predicted odor discrimination across individuals better than other descriptors of population activity, indicating a close link between manifold geometry and behavior. Hence, pDp and possibly related recurrent networks store information in the geometry of representational manifolds, resulting in joint sensory and semantic maps that may support distributed learning processes.

Computational functions of precisely balanced neuronal microcircuits in an olfactory memory network

Models of balanced autoassociative memory networks predict that specific inhibition is critical to store information in connectivity. To explore these predictions, we characterized and manipulated different subtypes of fast-spiking interneurons in the posterior telencephalic area Dp (pDp) of adult zebrafish, the homolog of the piriform cortex. Modeling of recurrent networks with assemblies showed that a precise balance of excitation and inhibition is important to prevent not only excessive firing rates ("runaway activity") but also the stochastic occurrence of high pattern correlations ("runaway correlations"). Consistent with model predictions, runaway correlations emerged in pDp when synaptic balance was perturbed by optogenetic manipulations of feedback inhibition but not feedforward inhibition. Runaway correlations were driven by sparse subsets of strongly active neurons rather than by a general broadening of tuning curves. These results are consistent with balanced neuronal assemblies in pDp and reveal novel computational functions of inhibitory microcircuits in an autoassociative network.

Loss of endothelial CD2AP causes sex-dependent cerebrovascular dysfunction

Polymorphisms in CD2-associated protein (CD2AP) predispose to Alzheimer's disease (AD), but the underlying mechanisms remain unknown. Here, we show that loss of CD2AP in cerebral blood vessels is associated with cognitive decline in AD subjects and that genetic downregulation of CD2AP in brain vascular endothelial cells impairs memory function in male mice. Animals with reduced brain endothelial CD2AP display altered blood flow regulation at rest and during neurovascular coupling, defects in mural cell activity, and an abnormal vascular sex-dependent response to Aβ. Antagonizing endothelin-1 receptor A signaling partly rescues the vascular impairments, but only in male mice. Treatment of CD2AP mutant mice with reelin glycoprotein that mitigates the effects of CD2AP loss function via ApoER2 increases resting cerebral blood flow and even protects male mice against the noxious effect of Aβ. Thus, endothelial CD2AP plays critical roles in cerebrovascular functions and represents a novel target for sex-specific treatment in AD.

Luminos: open-source software for bidirectional microscopy

Bidirectional microscopy (BDM) combines simultaneous targeted optical perturbation and imaging of biophysical or biochemical signals (e.g. membrane voltage, Ca2+, or signaling molecules). A core challenge in BDM is precise spatial and temporal alignment of stimulation, imaging, and other experimental parameters. Here we present Luminos, an open-source MATLAB library for modular and precisely synchronized control of BDM experiments. The system supports hardware-triggered synchronization across stimulation, recording, and imaging channels with microsecond accuracy. Source code and documentation for Luminos are available online at https://www.luminosmicroscopy.com and https://github.com/adamcohenlab/luminos-microscopy. This library will facilitate development of bidirectional microscopy methods across the biological sciences.

Visual experience orthogonalizes visual cortical stimulus responses via population code transformation

Sensory and behavioral experience can alter visual cortical stimulus coding, but the precise form of this plasticity is unclear. We measured orientation tuning in 4,000-neuron populations of mouse V1 before and after training on a visuomotor task. Changes to single-cell tuning curves appeared complex, including development of asymmetries and of multiple peaks. Nevertheless, these complex tuning curve transformations can be explained by a simple equation: a convex transformation suppressing responses to task stimuli specifically in cells responding at intermediate levels. The strength of the transformation varies across trials, suggesting a dynamic circuit mechanism rather than static synaptic plasticity. The transformation results in sparsening and orthogonalization of population codes for task stimuli. It cannot improve the performance of an optimal stimulus decoder, which is already perfect even for naive codes, but it improves the performance of a suboptimal decoder model with inductive bias as might be found in downstream readout circuits.

A column-like organization for ocular dominance in mouse visual cortex

The columnar organization of response properties is a fundamental feature of the mammalian visual cortex. However, columns have not been observed universally across all mammalian species. Here, we report the discovery of clusters of ipsilateral eye preferring neurons in layer 4 of the mouse primary visual cortex. These clusters extend into layer 2/3 and upper layer 5, forming a column-like pattern for ocular dominance. Our observation of such structures in this minute cortical area sets a new boundary condition for models explaining the emergence of functional organizations in the neocortex.

Canalization of circuit assembly by δ-protocadherins in the zebrafish optic tectum

Neurons are precisely and reproducibly assembled into complex networks during development. How genes collaborate to guide this assembly remains an enduring mystery. In humans, large numbers of genes have been implicated in neurodevelopmental disorders that are characterized by variable and overlapping phenotypes. The complexity of the brain, the large number of genes involved and the heterogeneity of the disorders makes understanding the relationships between genes, development and neural function challenging. Waddington suggested the concept of canalization to describe the role of genes in shaping developmental trajectories that lead to precise outcomes1. Here, we show that members of the δ-protocadherin family of homophilic adhesion molecules, Protocadherin-19 and Protocadherin-17, contribute to developmental canalization of visual circuit assembly in the zebrafish. We provided oriented visual stimuli to zebrafish larvae and performed in vivo 2-photon calcium imaging in the optic tectum. The latent dynamics resulting from the population activity were confined to a conserved manifold. Among different wild type larvae, these dynamics were remarkably similar, allowing quantitative comparisons within and among genotypes. In both Protocadherin-19 and Protocadherin-17 mutants, the latent dynamics diverged from wild type. Importantly, these deviations could be averaged away, suggesting that the loss of these adhesion molecules leads to stochastic phenotypic variability and introduced disruptions of circuit organization that varied among individual mutants. These results provide a specific, quantitative example of canalization in the development of a vertebrate neural circuit, and suggest a framework for understanding the observed variability in complex brain disorders.

Postsynaptic spiking determines anti-Hebbian LTD in visual cortex basket cells

Long-term plasticity at pyramidal cell to basket cell (PC → BC) synapses is important for the functioning of cortical microcircuits. It is well known that at neocortical PC → PC synapses, dendritic calcium (Ca2+) dynamics signal coincident pre-and postsynaptic spiking which in turn triggers long-term potentiation (LTP). However, the link between dendritic Ca2+ dynamics and long-term plasticity at PC → BC synapses of primary visual cortex (V1) is not as well known. Here, we explored if PC → BC synaptic plasticity in developing V1 is sensitive to postsynaptic spiking. Two-photon (2P) Ca2+ imaging revealed that action potentials (APs) in dendrites of V1 layer-5 (L5) BCs back-propagated decrementally but actively to the location of PC → BC putative synaptic contacts. Pairing excitatory inputs with postsynaptic APs elicited dendritic Ca2+ supralinearities for pre-before-postsynaptic but not post-before-presynaptic temporal ordering, suggesting that APs could impact synaptic plasticity. In agreement, extracellular stimulation as well as high-throughput 2P optogenetic mapping of plasticity both revealed that pre-before-postsynaptic but not post-before-presynaptic pairing resulted in anti-Hebbian long-term depression (LTD). Our results demonstrate that V1 BC dendritic Ca2+ nonlinearities and synaptic plasticity at PC → BC connections are both sensitive to somatic spiking.

TWINKLE: An open-source two-photon microscope for teaching and research

Many laboratories use two-photon microscopy through commercial suppliers, or homemade designs of considerable complexity. The integrated nature of these systems complicates customization, troubleshooting, and training on the principles of two-photon microscopy. Here, we present "Twinkle": a microscope for Two-photon Imaging in Neuroscience, and Kit for Learning and Education. It is a fully open, high performing and easy-to-set-up microscope that can effectively be used for both education and research. The instrument features a >1 mm field of view, using a modern objective with 3 mm working distance and 2 inch diameter optics combined with GaAsP photomultiplier tubes to maximize the fluorescence signal. We document our experiences using this system as a teaching tool in several two week long workshops, exemplify scientific use cases, and conclude with a broader note on the place of our work in the growing space of open scientific instrumentation.

The developmental emergence of reliable cortical representations

The fundamental structure of cortical networks arises early in development before the onset of sensory experience. However, how endogenously generated networks respond to the onset of sensory experience and how they form mature sensory representations with experience remain unclear. In this study, we examined this 'nature-nurture transform' at the single-trial level using chronic in vivo calcium imaging in ferret visual cortex. At eye opening, visual stimulation evokes robust patterns of modular cortical network activity that are highly variable within and across trials, severely limiting stimulus discriminability. These initial stimulus-evoked modular patterns are distinct from spontaneous network activity patterns present before and at the time of eye opening. Within a week of normal visual experience, cortical networks develop low-dimensional, highly reliable stimulus representations that correspond with reorganized patterns of spontaneous activity. Using a computational model, we propose that reliable visual representations derive from the alignment of feedforward and recurrent cortical networks shaped by novel patterns of visually driven activity.

MouseGoggles: an immersive virtual reality headset for mouse neuroscience and behavior

Small-animal virtual reality (VR) systems have become invaluable tools in neuroscience for studying complex behavior during head-fixed neural recording, but they lag behind commercial human VR systems in terms of miniaturization, immersivity and advanced features such as eye tracking. Here we present MouseGoggles, a miniature VR headset for head-fixed mice that delivers independent, binocular visual stimulation over a wide field of view while enabling eye tracking and pupillometry in VR. Neural recordings in the visual cortex validate the quality of image presentation, while hippocampal recordings, associative reward learning and innate fear responses to virtual looming stimuli demonstrate an immersive VR experience. Our open-source system's simplicity and compact size will enable the broader adoption of VR methods in neuroscience.

Adaptation shapes the representational geometry in mouse V1 to efficiently encode the environment

Sensory adaptation dynamically changes neural responses as a function of previous stimuli, profoundly impacting perception. The response changes induced by adaptation have been characterized in detail in individual neurons and at the population level after averaging across trials. However, it is not clear how adaptation modifies the aspects of the representations that relate more directly to the ability to perceive stimuli, such as their geometry and the noise structure in individual trials. To address this question, we recorded from a population of neurons in the mouse visual cortex and presented one stimulus (an oriented grating) more frequently than the others. We then analyzed these data in terms of representational geometry and studied the ability of a linear decoder to discriminate between similar visual stimuli based on the single-trial population responses. Surprisingly, the discriminability of stimuli near the adaptor increased, even though the responses of individual neurons to these stimuli decreased. Similar changes were observed in artificial neural networks trained to reconstruct the visual stimulus under metabolic constraints. We conclude that the paradoxical effects of adaptation are consistent with the efficient coding framework, allowing the brain to improve the representation of frequent stimuli while limiting the associated metabolic cost.

Mixed representations of choice direction and outcome by GABA/glutamate cotransmitting neurons in the entopeduncular nucleus

The basal ganglia (BG) are an evolutionarily conserved and phylogenetically old set of sub-cortical nuclei that guide action selection, evaluation, and reinforcement. The entopeduncular nucleus (EP) is a major BG output nucleus that contains a population of GABA/glutamate cotransmitting neurons (EPSst+) that specifically target the lateral habenula (LHb) and whose function in behavior remains mysterious. Here, we use a probabilistic switching task that requires an animal to maintain flexible relationships between action selection and evaluation to examine when and how GABA/glutamate cotransmitting neurons contribute to behavior. We find that EPSst+ neurons are strongly engaged during this task and show bidirectional changes in activity during the choice and outcome periods of a trial. We then tested the effects of either permanently blocking cotransmission or modifying the GABA/glutamate ratio on behavior in well-trained animals. Neither manipulation produced detectable changes in behavior despite significant changes in synaptic transmission in the LHb, demonstrating that the outputs of these neurons are not required for ongoing action-outcome updating in a probabilistic switching task.

A synapse-specific refractory period for plasticity at individual dendritic spines

How newly formed memories are preserved while brain plasticity is ongoing has been a source of debate. One idea is that synapses which experienced recent plasticity become resistant to further plasticity, a type of metaplasticity often referred to as saturation. Here, we probe the local dendritic mechanisms that limit plasticity at recently potentiated synapses. We show that recently potentiated individual synapses exhibit a synapse-specific refractory period for further potentiation. We further found that the refractory period is associated with reduced postsynaptic CaMKII signaling; however, stronger synaptic activation fully restored CaMKII signaling but only partially restored the ability for further plasticity. Importantly, the refractory period is released after one hour, a timing that coincides with the enrichment of several postsynaptic proteins to preplasticity levels. Notably, increasing the level of the postsynaptic scaffolding protein, PSD95, but not of PSD93, overcomes the refractory period. Our results support a model in which potentiation at a single synapse is sufficient to initiate a synapse-specific refractory period that persists until key postsynaptic proteins regain their steady-state synaptic levels.

TWINKLE: An open-source two-photon microscope for teaching and research

Many laboratories use two-photon microscopy through commercial suppliers, or homemade designs of considerable complexity. The integrated nature of these systems complicates customization, troubleshooting, and training on the principles of two-photon microscopy. Here, we present "Twinkle": a microscope for Two-photon Imaging in Neuroscience, and Kit for Learning and Education. It is a fully open, high performing and easy-to-set-up microscope that can effectively be used for both education and research. The instrument features a > 1 mm field of view, using a modern objective with 3 mm working distance and 2 inch diameter optics combined with GaAsP photomultiplier tubes to maximize the fluorescence signal. We document our experiences using this system as a teaching tool in several two week long workshops, exemplify scientific use cases, and conclude with a broader note on the place of our work in the growing space of open scientific instrumentation.

The geometry of correlated variability leads to highly suboptimal discriminative sensory coding

The brain represents the world through the activity of neural populations; however, whether the computational goal of sensory coding is to support discrimination of sensory stimuli or to generate an internal model of the sensory world is unclear. Correlated variability across a neural population (noise correlations) is commonly observed experimentally, and many studies demonstrate that correlated variability improves discriminative sensory coding compared to a null model with no correlations. However, such results do not address whether correlated variability is optimal for discriminative sensory coding. If the computational goal of sensory coding is discriminative, than correlated variability should be optimized to support that goal. We assessed optimality of noise correlations for discriminative sensory coding in diverse datasets by developing two novel null models, each with a biological interpretation. Across datasets, we found that correlated variability in neural populations leads to highly suboptimal discriminative sensory coding according to both null models. Furthermore, biological constraints prevent many subsets of the neural populations from achieving optimality, and subselecting based on biological criteria leaves red discriminative coding performance suboptimal. Finally, we show that optimal subpopulations are exponentially small as the population size grows. Together, these results demonstrate that the geometry of correlated variability leads to highly suboptimal discriminative sensory coding.NEW & NOTEWORTHY The brain represents the world through the activity of neural populations that exhibit correlated variability. We assessed optimality of correlated variability for discriminative sensory coding in diverse datasets by developing two novel null models. Across datasets, correlated variability in neural populations leads to highly suboptimal discriminative sensory coding according to both null models. Biological constraints prevent the neural populations from achieving optimality. Together, these results demonstrate that the geometry of correlated variability leads to highly suboptimal discriminative sensory coding.

Rastermap: a discovery method for neural population recordings

Neurophysiology has long progressed through exploratory experiments and chance discoveries. Anecdotes abound of researchers listening to spikes in real time and noticing patterns of activity related to ongoing stimuli or behaviors. With the advent of large-scale recordings, such close observation of data has become difficult. To find patterns in large-scale neural data, we developed 'Rastermap', a visualization method that displays neurons as a raster plot after sorting them along a one-dimensional axis based on their activity patterns. We benchmarked Rastermap on realistic simulations and then used it to explore recordings of tens of thousands of neurons from mouse cortex during spontaneous, stimulus-evoked and task-evoked epochs. We also applied Rastermap to whole-brain zebrafish recordings; to wide-field imaging data; to electrophysiological recordings in rat hippocampus, monkey frontal cortex and various cortical and subcortical regions in mice; and to artificial neural networks. Finally, we illustrate high-dimensional scenarios where Rastermap and similar algorithms cannot be used effectively.

Repetitive transcranial magnetic stimulation increases synaptic plasticity of cortical axons in the APP/PS1 amyloidosis mouse model

Significance

Growing evidence highlights the therapeutic potential of repetitive transcranial magnetic stimulation (rTMS) in diseases causing dementias such as Alzheimer's disease (AD). However, individual responses to rTMS are variable, and its underlying neural mechanisms are not fully understood.

Aim

As synaptic dysfunction is one of the key mechanisms associated with cognitive deficits in dementia, we investigated the effect of rTMS on cortical synapses using an APP/PS1 amyloidosis mouse model of AD crossed with fluorescent reporters linked to the Thy-1 promoter.

Approach

Using in vivo two-photon imaging, we characterized the plasticity of excitatory terminaux (TB) and en passant (EPB) axonal boutons at 48-h intervals for 8 days on either side of a single session of rTMS.

Results

We found both types of axonal boutons preserved the overall number of their synaptic outputs in wild type (WT) and APP/PS1 groups, pre- and post-stimulation. Both synapse types also showed a significantly reduced dynamic fraction in APP/PS1 compared with WT axons pre-stimulation. Following stimulation, the TB, but not EPB, dynamic fraction increased in both WT and APP/PS1 groups.

Conclusions

This suggests possible mechanisms of rTMS action that are cell type-specific and, together with previous findings of improved functional performance, present a potential clinical avenue for rTMS in the management of AD.

Harnessing Raman spectroscopy and multimodal imaging of cartilage for osteoarthritis diagnosis

Osteoarthritis (OA) is a complex disease of cartilage characterised by joint pain, functional limitation, and reduced quality of life with affected joint movement leading to pain and limited mobility. Current methods to diagnose OA are predominantly limited to X-ray, MRI and invasive joint fluid analysis, all of which lack chemical or molecular specificity and are limited to detection of the disease at later stages. A rapid minimally invasive and non-destructive approach to disease diagnosis is a critical unmet need. Label-free techniques such as Raman Spectroscopy (RS), Coherent anti-Stokes Raman scattering (CARS), Second Harmonic Generation (SHG) and Two Photon Fluorescence (TPF) are increasingly being used to characterise cartilage tissue. However, current studies are based on whole tissue analysis and do not consider the different and structurally distinct layers in cartilage. In this work, we use Raman spectroscopy to obtain signatures from the superficial (top) and deep (bottom) layer of healthy and osteoarthritic cartilage samples from 64 patients (19 control and 45 OA). Spectra were acquired both in the 'fingerprint' region from 700 to 1720 cm- 1 and high-frequency stretching region from 2500 to 3300 cm- 1. Principal component and linear discriminant analysis was used to identify the peaks that contributed significantly to classification accuracy of the different samples. The most pronounced differences were observed at the proline (855 cm- 1 and 921 cm- 1) and hydroxyproline (877 cm- 1 and 938 cm- 1), sulphated glycosaminoglycan (sGAG) (1064 cm- 1 and 1380 cm- 1) frequencies for both control and OA as well as the 1245 cm- 1 and 1272 cm- 1, 1320 cm- 1 and 1345 cm- 1, 1451 cm- 1 collagen modes were altered in OA samples, consistent with expected collagen structural changes. Classification accuracy based on Raman fingerprint spectral analysis of superficial and deep layer cartilage for controls was found to be 97% and 93% on using individual/all spectra and, 100% and 95% on using mean spectra per patient, respectively. OA diseased cartilage was classified with an accuracy of 88% and 84% for individual/all spectra, and 96% and 95% for mean spectra per patient based on analysis of the superficial and the deep layers, respectively. Raman spectra from the C-H stretching region (2500-3300 cm- 1) resulted in high classification accuracy for identification of different layers and OA diseased cartilage but low accuracy for controls. Differential changes in superficial and deep layer cartilage signatures were observed with age (under 60 and over 60 years), in contrast, less significant differences were observed with gender. Prominent chemical changes in the different layers of cartilage were preliminarily imaged using CARS, SHG and TPF. Cell clustering was observed in OA together with differences in pericellular matrix and collagen structure in the superficial and the deep layers correlating with the Raman spectral analysis. The current study demonstrates the potential of Raman Spectroscopy and multimodal imaging to interrogate cartilage tissue and provides insight into the chemical and structural composition of its different layers with significant implications for OA diagnosis for an increasing aging demographic.

Ongoing loss of viable neurons for weeks after mild perinatal hypoxia-ischemia

Mild hypoxic-ischemic encephalopathy is common in neonates with no evidence-based therapies, and 30-40% of patients experience adverse outcomes. The nature and progression of mild injury is poorly understood. Thus, we studied the evolution of mild perinatal brain injury using longitudinal two-photon imaging of transgenic fluorescent proteins as a novel readout of neuronal viability and activity at cellular resolution. In vitro, perinatal murine organotypic hippocampal cultures underwent 15-20 minutes of oxygen-glucose deprivation. In vivo, mild hypoxia-ischemia was completed in post-natal day 10 mouse pups of both sexes with carotid ligation and 15 minutes of hypoxia. Consistent with a mild injury, minimal immediate neuronal death was seen and there was no volumetric evidence of injury by ex vivo MRI 2.5 weeks after injury. In both the hippocampus and neocortex, these mild injuries resulted in a significantly delayed and progressive neuronal loss in the second week after injury, measured by fluorophore quenching. Mild hypoxia-ischemia transiently suppressed cortical network activity followed by normal maturation. No post-injury seizures were seen. The participation in network activity of individual neurons destined to die was indistinguishable from those that survived for 4 days post-injury. In conclusion, our results showed that mild perinatal brain injury resulted in a prolonged increase of neuronal death. Neurons that died late were functioning normally for days after injury, suggesting a new pathophysiology of neuronal death. Critically, the neurons destined to die late demonstrated multiple biomarkers of viability long after mild injury, suggesting their later death may be modified with neuroprotective interventions.

SIGNIFICANCE STATEMENT

Neonatal encephalopathy due to peripartum hypoxia-ischemia (HI) is a major cause of neonatal mortality and morbidity worldwide. Of these infants, most are categorized as having mild HI. Infants with mild HI have significant long-term disabilities. There are currently no evidence-based therapies, largely because the progression and pathophysiology of mild injury is poorly understood. We have identified, for the first time, that mild perinatal HI results in a delayed and prolonged increase in neuronal death. The cortical and hippocampal neurons that die over a week after injury participate normally in neural network activity and exhibit robust viability for many days after injury, indicating a novel pathophysiology of neuronal death. Clinically, these data suggest an extended therapeutic window for mild perinatal HI.

Adaptation to visual sparsity enhances responses to isolated stimuli

Sensory systems adapt their response properties to the statistics of their inputs. For instance, visual systems adapt to low-order statistics like mean and variance to encode stimuli efficiently or to facilitate specific downstream computations. However, it remains unclear how other statistical features affect sensory adaptation. Here, we explore how Drosophila's visual motion circuits adapt to stimulus sparsity, a measure of the signal's intermittency not captured by low-order statistics alone. Early visual neurons in both ON and OFF pathways alter their responses dramatically with stimulus sparsity, responding positively to both light and dark sparse stimuli but linearly to dense stimuli. These changes extend to downstream ON and OFF direction-selective neurons, which are activated by sparse stimuli of both polarities but respond with opposite signs to light and dark regions of dense stimuli. Thus, sparse stimuli activate both ON and OFF pathways, recruiting a larger fraction of the circuit and potentially enhancing the salience of isolated stimuli. Overall, our results reveal visual response properties that increase the fraction of the circuit responding to sparse, isolated stimuli.

Perceptual constancy for an odor is acquired through changes in primary sensory neurons

The ability to consistently recognize an object despite variable sensory input is termed perceptual constancy. This ability is not innate; rather, it develops with experience early in life. We show that, when mice are naïve to an odor object, perceptual constancy is absent across increasing concentrations. The perceptual change coincides with a rapid reduction in activity from a single olfactory receptor channel that is most sensitive to the odor. This drop in activity is not a property of circuit interactions within the olfactory bulb; instead, it is due to a sensitivity mismatch of olfactory receptor neurons within the nose. We show that, after forming an association of this odor with food, the sensitivity of the receptor channel is matched to the odor object, preventing transmission failure and promoting perceptual stability. These data show that plasticity of the primary sensory organ enables learning of perceptual constancy.

Dendritic Spines of Layer 5 Pyramidal Neurons of the Aging Somatosensory Cortex Exhibit Reduced Volumetric Remodeling

Impairments in synaptic dynamics and stability are observed both in neurodegenerative disorders and in the healthy aging cortex, which exhibits elevated dendritic spine turnover and decreased long-term stability of excitatory connections at baseline, as well as an altered response to plasticity induction. In addition to the discrete gain and loss of synapses, spines also change in size and strength both during learning and in the absence of neural activity, and synaptic volume has been associated with stability and incorporation into memory traces. Furthermore, intrinsic dynamics, an apparently stochastic component of spine volume changes, may serve as a homeostatic mechanism to prevent stabilization of superfluous connections. However, the effects of age on modulation of synaptic weights remain unknown. Using two-photon excitation (2PE) microscopy of spines during chemical plasticity induction in vitro and analyzing longitudinal in vivo 2PE images after a plasticity-inducing manipulation, we characterize the effects of age on volumetric changes of spines of the apical tuft of layer 5 pyramidal neurons of mouse primary somatosensory cortex. Aged mice exhibit decreased volumetric volatility and delayed rearrangement of synaptic weights of persistent connections, as well as greater susceptibility to spine shrinkage in response to chemical long-term depression. These results suggest a deficit in the aging brain's ability to fine-tune synaptic weights to properly incorporate and retain novel memories. This research provides the first evidence of alterations in spine volumetric dynamics in healthy aging and may support a model of impaired processing and learning in the aged somatosensory system.

Genetic Downregulation of GABAB Receptors from Oligodendrocyte Precursor Cells Protects Against Demyelination in the Mouse Spinal Cord

GABAergic signaling and GABAB receptors play crucial roles in regulating the physiology of oligodendrocyte-lineage cells, including their proliferation, differentiation, and myelination. Therefore, they are promising targets for studying how spinal oligodendrocyte precursor cells (OPCs) respond to injuries and neurodegenerative diseases like multiple sclerosis. Taking advantage of the temporally controlled and cell-specific genetic downregulation of GABAB receptors from OPCs, our investigation addresses their specific influence on OPC behavior in the gray and white matter of the mouse spinal cord. Our results show that, while GABAB receptors do not significantly alter spinal cord myelination under physiological conditions, they distinctly regulate the OPC differentiation and Ca2+ signaling. In addition, we investigate the impact of OPC-GABAB receptors in two models of toxic demyelination, namely, the cuprizone and the lysolecithin models. The genetic downregulation of OPC-GABAB receptors protects against demyelination and oligodendrocyte loss. Additionally, we observe the enhanced resilience to cuprizone-induced pathological alterations in OPC Ca2+ signaling. Our results provide valuable insights into the potential therapeutic implications of manipulating GABAB receptors in spinal cord OPCs and deepen our understanding of the interplay between GABAergic signaling and spinal cord OPCs, providing a basis for future research.

An optical brain-machine interface reveals a causal role of posterior parietal cortex in goal-directed navigation

Cortical circuits contain diverse sensory, motor, and cognitive signals, and form densely recurrent networks. This creates challenges for identifying causal relationships between neural populations and behavior. We developed a calcium imaging-based brain-machine interface (BMI) to study the role of posterior parietal cortex (PPC) in controlling navigation in virtual reality. By training a decoder to estimate navigational heading and velocity from PPC activity during virtual navigation, we discovered that mice could immediately navigate toward goal locations when control was switched to BMI. No learning or adaptation was observed during BMI, indicating that naturally occurring PPC activity patterns are sufficient to drive navigational trajectories in real time. During successful BMI trials, decoded trajectories decoupled from the mouse's physical movements, suggesting that PPC activity relates to intended trajectories. Our work demonstrates a role for PPC in navigation and offers a BMI approach for investigating causal links between neural activity and behavior.

The sperm hook as a functional adaptation for migration and self-organized behavior

In most murine species, spermatozoa exhibit a falciform apical hook at the head end. The function of the sperm hook is not yet clearly understood. In this study, we investigate the role of the sperm hook in the migration of spermatozoa through the female reproductive tract in Mus musculus (C57BL/6), using a deep tissue imaging custom-built two-photon microscope. Through live reproductive tract imaging, we found evidence indicating that the sperm hook aids in the attachment of spermatozoa to the epithelium and facilitates interactions between spermatozoa and the epithelium during migration in the uterus and oviduct. We also observed synchronized sperm beating, which resulted from the spontaneous unidirectional rearrangement of spermatozoa in the uterus. Based on live imaging of spermatozoa-epithelium interaction dynamics, we propose that the sperm hook plays a crucial role in successful migration through the female reproductive tract by providing anchor-like mechanical support and facilitating interactions between spermatozoa and the female reproductive tract in the house mouse.

Representational learning by optimization of neural manifolds in an olfactory memory network

Higher brain functions depend on experience-dependent representations of relevant information that may be organized by attractor dynamics or by geometrical modifications of continuous "neural manifolds". To explore these scenarios we analyzed odor-evoked activity in telencephalic area pDp of juvenile and adult zebrafish, the homolog of piriform cortex. No obvious signatures of attractor dynamics were detected. Rather, olfactory discrimination training selectively enhanced the separation of neural manifolds representing task-relevant odors from other representations, consistent with predictions of autoassociative network models endowed with precise synaptic balance. Analytical approaches using the framework of manifold capacity revealed multiple geometrical modifications of representational manifolds that supported the classification of task-relevant sensory information. Manifold capacity predicted odor discrimination across individuals, indicating a close link between manifold geometry and behavior. Hence, pDp and possibly related recurrent networks store information in the geometry of representational manifolds, resulting in joint sensory and semantic maps that may support distributed learning processes.

Deciphering Peripheral Taste Neuron Diversity: Using Genetic Identity to Bridge Taste Bud Innervation Patterns and Functional Responses

Peripheral taste neurons exhibit functional, genetic, and morphological diversity, yet understanding how or if these attributes combine into taste neuron types remains unclear. In this study, we used male and female mice to relate taste bud innervation patterns to the function of a subset of proenkephalin-expressing (Penk+) taste neurons. We found that taste arbors (the portion of the axon within the taste bud) stemming from Penk+ neurons displayed diverse branching patterns and lacked stereotypical endings. The range in complexity observed for individual taste arbors from Penk+ neurons mirrored the entire population, suggesting that taste arbor morphologies are not primarily regulated by the neuron type. Notably, the distinguishing feature of arbors from Penk+ neurons was their propensity to come within 110 nm (in apposition with) different types of taste-transducing cells within the taste bud. This finding is contrary to the expectation of genetically defined taste neuron types that functionally represent a single stimulus. Consistently, further investigation of Penk+ neuron function revealed that they are more likely to respond to innately aversive stimuli-sour, bitter, and high salt concentrations-as compared with the full taste population. Penk+ neurons are less likely to respond to nonaversive stimuli-sucrose, umami, and low salt-compared with the full population. Our data support the presence of a genetically defined neuron type in the geniculate ganglion that is responsive to innately aversive stimuli. This implies that genetic expression might categorize peripheral taste neurons into hedonic groups, rather than simply identifying neurons that respond to a single stimulus.

PKA regulation of neuronal function requires the dissociation of catalytic subunits from regulatory subunits

Protein kinase A (PKA) plays essential roles in diverse cellular functions. However, the spatiotemporal dynamics of endogenous PKA upon activation remain debated. The classical model predicts that PKA catalytic subunits dissociate from regulatory subunits in the presence of cAMP, whereas a second model proposes that catalytic subunits remain associated with regulatory subunits following physiological activation. Here, we report that different PKA subtypes, as defined by the regulatory subunit, exhibit distinct subcellular localization at rest in CA1 neurons of cultured hippocampal slices. Nevertheless, when all tested PKA subtypes are activated by norepinephrine, presumably via the β-adrenergic receptor, catalytic subunits translocate to dendritic spines but regulatory subunits remain unmoved. These differential spatial dynamics between the subunits indicate that at least a significant fraction of PKA dissociates. Furthermore, PKA-dependent regulation of synaptic plasticity and transmission can be supported only by wildtype, dissociable PKA, but not by inseparable PKA. These results indicate that endogenous PKA regulatory and catalytic subunits dissociate to achieve PKA function in neurons.

Substance P and dopamine form a "push-pull" system that diurnally regulates retinal gain

The operation of the retina, like other brain circuits, is under modulatory control. One coordinator of changes in retinal function is dopamine, a neuromodulator released in a light-dependent way to adjust vision on a diurnal cycle. Here, we demonstrate that substance P is a similarly powerful retinal modulator that interacts with the dopamine system. By imaging glutamatergic synaptic transmission in larval zebrafish, we find that substance P decreases the contrast sensitivity of ON and OFF visual channels up to 8-fold, with suppression of visual signals being strongest through the "transient" pathway responding to higher frequencies. These actions are exerted in the morning, in large part by suppressing the amplification of visual signals by dopamine, but substance P is almost completely inactive in the afternoon. Modulation of retinal gain is accompanied by changes in patterns of vesicle release at the synapses of bipolar cells: increased gain shifts coding of stimulus strength from the rate of release events to their amplitude generated by a process of multivesicular release (MVR). Together, these actions of substance P reduce the flow of visual information, measured in bits, ∼3-fold. Thus, whereas dopamine "pushes" the retina to transmit information at higher rates in the afternoon, substance P acts in antiphase to suppress dopamine signaling and "pull down" information transmission in the morning.

Pyramidal cell types and 5-HT2A receptors are essential for psilocybin's lasting drug action

Psilocybin is a serotonergic psychedelic with therapeutic potential for treating mental illnesses1-4. At the cellular level, psychedelics induce structural neural plasticity5,6, exemplified by the drug-evoked growth and remodeling of dendritic spines in cortical pyramidal cells7-9. A key question is how these cellular modifications map onto cell type-specific circuits to produce psychedelics' behavioral actions10. Here, we use in vivo optical imaging, chemogenetic perturbation, and cell type-specific electrophysiology to investigate the impact of psilocybin on the two main types of pyramidal cells in the mouse medial frontal cortex. We find that a single dose of psilocybin increased the density of dendritic spines in both the subcortical-projecting, pyramidal tract (PT) and intratelencephalic (IT) cell types. Behaviorally, silencing the PT neurons eliminates psilocybin's ability to ameliorate stress-related phenotypes, whereas silencing IT neurons has no detectable effect. In PT neurons only, psilocybin boosts synaptic calcium transients and elevates firing rates acutely after administration. Targeted knockout of 5-HT2A receptors abolishes psilocybin's effects on stress-related behavior and structural plasticity. Collectively these results identify a pyramidal cell type and the 5-HT2A receptor in the medial frontal cortex as playing essential roles for psilocybin's long-term drug action.

Maintaining and updating accurate internal representations of continuous variables with a handful of neurons

Many animals rely on persistent internal representations of continuous variables for working memory, navigation, and motor control. Existing theories typically assume that large networks of neurons are required to maintain such representations accurately; networks with few neurons are thought to generate discrete representations. However, analysis of two-photon calcium imaging data from tethered flies walking in darkness suggests that their small head-direction system can maintain a surprisingly continuous and accurate representation. We thus ask whether it is possible for a small network to generate a continuous, rather than discrete, representation of such a variable. We show analytically that even very small networks can be tuned to maintain continuous internal representations, but this comes at the cost of sensitivity to noise and variations in tuning. This work expands the computational repertoire of small networks, and raises the possibility that larger networks could represent more and higher-dimensional variables than previously thought.

Improving the scan throughput of polygon scanners

Polygon scanners allow for some of the fastest available line rates for raster scanning imaging. Due to the optical invariant, however, there is a trade-off between the line rate and the number of resolvable points per line. Here, we describe a device that can increase the number of resolvable points per line of mirror-based scanners without sacrificing speed. We first theoretically model the effect of the device on the number of resolvable points per line of a polygon scanner, and then experimentally test this device with both a simplified facet system and a transmission microscope using a polygon scanner. We demonstrate an improvement in the field of view by 1.7 times without a reduction in spatial resolution.

Fine-grained descending control of steering in walking Drosophila

Locomotion involves rhythmic limb movement patterns that originate in circuits outside the brain. Purposeful locomotion requires descending commands from the brain, but we do not understand how these commands are structured. Here, we investigate this issue, focusing on the control of steering in walking Drosophila. First, we describe different limb "gestures" associated with different steering maneuvers. Next, we identify a set of descending neurons whose activity predicts steering. Focusing on two descending cell types downstream of distinct brain networks, we show that they evoke specific limb gestures: one lengthens strides on the outside of a turn, while the other attenuates strides on the inside of a turn. Our results suggest that a single descending neuron can have opposite effects during different locomotor rhythm phases, and we identify networks positioned to implement this phase-specific gating. Together, our results show how purposeful locomotion emerges from specific, coordinated modulations of low-level patterns.

Mixed representations of choice direction and outcome by GABA/glutamate cotransmitting neurons in the entopeduncular nucleus

The basal ganglia (BG) are an evolutionarily conserved and phylogenetically old set of sub-cortical nuclei that guide action selection, evaluation, and reinforcement. The entopeduncular nucleus (EP) is a major BG output nucleus that contains a population of GABA/glutamate cotransmitting neurons (EP Sst+ ) that specifically target the lateral habenula (LHb) and whose function in behavior remains mysterious. Here we use a probabilistic switching task that requires an animal to maintain flexible relationships between action selection and evaluation to examine when and how GABA/glutamate cotransmitting neurons contribute to behavior. We find that EP Sst+ neurons are strongly engaged during this task and show bidirectional changes in activity during the choice and outcome periods of a trial. We then tested the effects of either permanently blocking cotransmission or modifying the GABA/glutamate ratio on behavior in well-trained animals. Neither manipulation produced detectable changes in behavior despite significant changes in synaptic transmission in the LHb, demonstrating that the outputs of these neurons are not required for on-going action-outcome updating in a probabilistic switching task.

Sensory experience steers representational drift in mouse visual cortex

Representational drift-the gradual continuous change of neuronal representations-has been observed across many brain areas. It is unclear whether drift is caused by synaptic plasticity elicited by sensory experience, or by the intrinsic volatility of synapses. Here, using chronic two-photon calcium imaging in primary visual cortex of female mice, we find that the preferred stimulus orientation of individual neurons slowly drifts over the course of weeks. By using cylinder lens goggles to limit visual experience to a narrow range of orientations, we show that the direction of drift, but not its magnitude, is biased by the statistics of visual input. A network model suggests that drift of preferred orientation largely results from synaptic volatility, which under normal visual conditions is counteracted by experience-driven Hebbian mechanisms, stabilizing preferred orientation. Under deprivation conditions these Hebbian mechanisms enable adaptation. Thus, Hebbian synaptic plasticity steers drift to match the statistics of the environment.

Deep Mouse Brain Two-Photon Near-Infrared Fluorescence Imaging Using a Superconducting Nanowire Single-Photon Detector Array

Two-photon microscopy (2PM) has become an important tool in biology to study the structure and function of intact tissues in vivo. However, adult mammalian tissues such as the mouse brain are highly scattering, thereby putting fundamental limits on the achievable imaging depth, which typically reside at around 600-800 μm. In principle, shifting both the excitation as well as (fluorescence) emission light to the shortwave near-infrared (SWIR, 1000-1700 nm) region promises substantially deeper imaging in 2PM, yet this shift has proven challenging in the past due to the limited availability of detectors and probes in this wavelength region. To overcome these limitations and fully capitalize on the SWIR region, in this work, we introduce a novel array of superconducting nanowire single-photon detectors (SNSPDs) and associated custom detection electronics for use in near-infrared 2PM. The SNSPD array exhibits high efficiency and dynamic range as well as low dark-count rates over a wide wavelength range. Additionally, the electronics and software permit a seamless integration into typical 2PM systems. Together with an organic fluorescent dye emitting at 1105 nm, we report imaging depth of >1.1 mm in the in vivo mouse brain, limited mostly by available labeling density and laser properties. Our work establishes a promising, and ultimately scalable, new detector technology for SWIR 2PM that facilitates deep tissue biological imaging.