Cortical layer-specific critical dynamics triggering perception

Descanned fast light targeting (deFLiT) two-photon optogenetics

Two-photon light-targeting optogenetics allows controlling selected subsets of neurons with near single-cell resolution and high temporal precision. To push forward this approach, we recently proposed a fast light-targeting strategy (FLiT) to rapidly scan multiple holograms tiled on a spatial light modulator (SLM). This allowed generating sub-ms timely-controlled switch of light patterns enabling to reduce the power budget for multi-target excitation and increase the temporal precision for relative spike tuning in a circuit. Here, we modified the optical design of FLiT by including a de-scan unit (deFLiT) to keep the holographic illumination centered at the middle of the objective pupil independently of the position of the tiled hologram on the SLM. This enables enlarging the number of usable holograms and reaching extended on-axis excitation volumes, and therefore increasing even further the power gain and temporal precision of conventional FLiT.

Optogenetically mediated large volume suppression and synchronized excitation of human ventricular cardiomyocytes

A major challenge in cardiac optogenetics is to have minimally invasive large volume excitation and suppression for effective cardioversion and treatment of tachycardia. It is important to study the effect of light attenuation on the electrical activity of cells in in vivo cardiac optogenetic experiments. In this computational study, we present a detailed analysis of the effect of light attenuation in different channelrhodopsins (ChRs)-expressing human ventricular cardiomyocytes. The study shows that sustained illumination from the myocardium surface used for suppression, simultaneously results in spurious excitation in deeper tissue regions. Tissue depths of suppressed and excited regions have been determined for different opsin expression levels. It is shown that increasing the expression level by 5-fold enhances the depth of suppressed tissue from 2.24 to 3.73 mm with ChR2(H134R) (ChR2 with a single point mutation at position H134), 3.78 to 5.12 mm with GtACR1 (anion-conducting ChR from cryptophyte algae Guillardia theta) and 6.63 to 9.31 mm with ChRmine (a marine opsin gene from Tiarina fusus). Light attenuation also results in desynchrony in action potentials in different tissue regions under pulsed illumination. It is further shown that gradient-opsin expression not only enables suppression up to the same level of tissue depth but also enables synchronized excitation under pulsed illumination. The study is important for the effective treatment of tachycardia and cardiac pacing and for extending the scale of cardiac optogenetics.

Engineering luminopsins with improved coupling efficiencies

Significance

Luminopsins (LMOs) are bioluminescent-optogenetic tools with a luciferase fused to an opsin that allow bimodal control of neurons by providing both optogenetic and chemogenetic access. Determining which design features contribute to the efficacy of LMOs will be beneficial for further improving LMOs for use in research.

Aim

We investigated the relative impact of luciferase brightness, opsin sensitivity, pairing of emission and absorption wavelength, and arrangement of moieties on the function of LMOs.

Approach

We quantified efficacy of LMOs through whole cell patch clamp recordings in HEK293 cells by determining coupling efficiency, the percentage of maximum LED induced photocurrent achieved with bioluminescent activation of an opsin. We confirmed key results by multielectrode array (MEAs) recordings in primary neurons.

Results

Luciferase brightness and opsin sensitivity had the most impact on the efficacy of LMOs, and N-terminal fusions of luciferases to opsins performed better than C-terminal and multi-terminal fusions. Precise paring of luciferase emission and opsin absorption spectra appeared to be less critical.

Conclusions

Whole cell patch clamp recordings allowed us to quantify the impact of different characteristics of LMOs on their function. Our results suggest that coupling brighter bioluminescent sources to more sensitive opsins will improve LMO function. As bioluminescent activation of opsins is most likely based on Förster resonance energy transfer (FRET), the most effective strategy for improving LMOs further will be molecular evolution of luciferase-fluorescent protein-opsin fusions.

Monosynaptic inputs to ventral tegmental area glutamate and GABA co-transmitting neurons

A unique population of ventral tegmental area (VTA) neurons co-transmits glutamate and GABA as well as functionally signals rewarding and aversive outcomes. However, the circuit inputs to VTA VGluT2+VGaT+ neurons are unknown, limiting our understanding of the functional capabilities of these neurons. To identify the inputs to VTA VGluT2+VGaT+ neurons, we coupled monosynaptic rabies tracing with intersectional genetic targeting of VTA VGluT2+VGaT+ neurons in mice. We found that VTA VGluT2+VGaT+ neurons received diverse brain-wide inputs. The largest numbers of monosynaptic inputs to VTA VGluT2+VGaT+ neurons were from superior colliculus, lateral hypothalamus, midbrain reticular nucleus, and periaqueductal gray, whereas the densest inputs relative to brain region volume were from dorsal raphe nucleus, lateral habenula, and ventral tegmental area. Based on these and prior data, we hypothesized that lateral hypothalamus and superior colliculus inputs were glutamatergic neurons. Optical activation of glutamatergic lateral hypothalamus neurons robustly activated VTA VGluT2+VGaT+ neurons regardless of stimulation frequency and resulted in flee-like ambulatory behavior. In contrast, optical activation of glutamatergic superior colliculus neurons activated VTA VGluT2+VGaT+ neurons for a brief period of time at high stimulation frequency and resulted in head rotation and arrested ambulatory behavior (freezing). For both pathways, behaviors induced by stimulation were uncorrelated with VTA VGluT2+VGaT+ neuron activity. However, stimulation of glutamatergic lateral hypothalamus neurons, but not glutamatergic superior colliculus neurons, was associated with VTA VGluT2+VGaT+ footshock-induced activity. We interpret these results such that inputs to VTA VGluT2+VGaT+ neurons may integrate diverse signals related to the detection and processing of motivationally-salient outcomes. Further, VTA VGluT2+VGaT+ neurons may signal threat-related outcomes, possibly via input from lateral hypothalamus glutamate neurons, but not threat-induced behavioral kinematics.

A micro-LED array based platform for spatio-temporal optogenetic control of various cardiac models

Optogenetics relies on dynamic spatial and temporal control of light to address emerging fundamental and therapeutic questions in cardiac research. In this work, a compact micro-LED array, consisting of 16 × 16 pixels, is incorporated in a widefield fluorescence microscope for controlled light stimulation. We describe the optical design of the system that allows the micro-LED array to fully cover the field of view regardless of the imaging objective used. Various multicellular cardiac models are used in the experiments such as channelrhodopsin-2 expressing aggregates of cardiomyocytes, termed cardiac bodies, and bioartificial cardiac tissues derived from human induced pluripotent stem cells. The pacing efficiencies of the cardiac bodies and bioartificial cardiac tissues were characterized as a function of illumination time, number of switched-on pixels and frequency of stimulation. To demonstrate dynamic stimulation, steering of calcium waves in HL-1 cell monolayer expressing channelrhodopsin-2 was performed by applying different configurations of patterned light. This work shows that micro-LED arrays are powerful light sources for optogenetic control of contraction and calcium waves in cardiac monolayers, multicellular bodies as well as three-dimensional artificial cardiac tissues.

Rethinking Remapping: Circuit Mechanisms of Recovery after Stroke

Stroke is one of the most common causes of disability, and there are few treatments that can improve recovery after stroke. Therapeutic development has been hindered because of a lack of understanding of precisely how neural circuits are affected by stroke, and how these circuits change to mediate recovery. Indeed, some of the hypotheses for how the CNS changes to mediate recovery, including remapping, redundancy, and diaschisis, date to more than a century ago. Recent technological advances have enabled the interrogation of neural circuits with ever greater temporal and spatial resolution. These techniques are increasingly being applied across animal models of stroke and to human stroke survivors, and are shedding light on the molecular, structural, and functional changes that neural circuits undergo after stroke. Here we review these studies and highlight important mechanisms that underlie impairment and recovery after stroke. We begin by summarizing knowledge about changes in neural activity that occur in the peri-infarct cortex, specifically considering evidence for the functional remapping hypothesis of recovery. Next, we describe the importance of neural population dynamics, disruptions in these dynamics after stroke, and how allocation of neurons into spared circuits can restore functionality. On a more global scale, we then discuss how effects on long-range pathways, including interhemispheric interactions and corticospinal tract transmission, contribute to post-stroke impairments. Finally, we look forward and consider how a deeper understanding of neural circuit mechanisms of recovery may lead to novel treatments to reduce disability and improve recovery after stroke.

Fast 2-photon stimulation using holographic patterns

Two decades after its introduction, optogenetics - a biological technique to control the activity of neurons or other cell types with light - remains a cutting edge and promising tool to study biological processes. Its increasing usage in research varies widely from causally exploring biological mechanisms and neural computations, to neurostimulation and sensory restauration. To stimulate neurons in the brain, a variety of approaches have been developed to generate precise spatiotemporal light patterns. Yet certain constrains still exists in the current optical techniques to activate a neuronal population with both cellular resolution and millisecond precision. Here, we describe an experimental setup allowing to stimulate a few tens of neurons in a plane at sub-millisecond rates using 2-photon activation. A liquid crystal on silicon spatial light modulator (LCoS-SLM) was used to generate spatial patterns in 2 dimensions. The image of the patterns was formed on the plane of a digital micromirror device (DMD) that was used as a fast temporal modulator of each region of interest. Using fluorescent microscopy and patch-clamp recording of neurons in culture expressing the light-gated ion channels, we characterized the temporal and spatial resolution of the microscope. We described the advantages of combining the LCoS-SLM with the DMD to maximize the temporal precision, modulate the illumination amplitude, and reduce background activation. Finally, we showed that this approach can be extended to patterns in 3 dimensions. We concluded that the methodology is well suited to address important questions about the role of temporal information in neuronal coding.

Photochemistry of the Retinal Chromophore in Microbial Rhodopsins

Microbial rhodopsins are photoreceptive membrane proteins of microorganisms that express diverse photobiological functions. All-trans-retinylidene Schiff base, the so-called all-trans-retinal, is a chromophore of microbial rhodopsins, which captures photons. It isomerizes into the 13-cis form upon photoexcitation. Isomerization of retinal leads to sequential conformational changes in the protein, giving rise to active states that exhibit biological functions. Despite the rapidly expanding diversity of microbial rhodopsin functions, the photochemical behaviors of retinal were considered to be common among them. However, the retinal of many recently discovered rhodopsins was found to exhibit new photochemical characteristics, such as highly red-shifted absorption, isomerization to 7-cis and 11-cis forms, and energy transfer from a secondary carotenoid chromophore to the retinal, which is markedly different from that established in canonical microbial rhodopsins. Here, I review new aspects of retinal found in novel microbial rhodopsins and highlight the emerging problems that need to be addressed to understand noncanonical retinal photochemistry.

Preserved neural dynamics across animals performing similar behaviour

Animals of the same species exhibit similar behaviours that are advantageously adapted to their body and environment. These behaviours are shaped at the species level by selection pressures over evolutionary timescales. Yet, it remains unclear how these common behavioural adaptations emerge from the idiosyncratic neural circuitry of each individual. The overall organization of neural circuits is preserved across individuals1 because of their common evolutionarily specified developmental programme2-4. Such organization at the circuit level may constrain neural activity5-8, leading to low-dimensional latent dynamics across the neural population9-11. Accordingly, here we suggested that the shared circuit-level constraints within a species would lead to suitably preserved latent dynamics across individuals. We analysed recordings of neural populations from monkey and mouse motor cortex to demonstrate that neural dynamics in individuals from the same species are surprisingly preserved when they perform similar behaviour. Neural population dynamics were also preserved when animals consciously planned future movements without overt behaviour12 and enabled the decoding of planned and ongoing movement across different individuals. Furthermore, we found that preserved neural dynamics extend beyond cortical regions to the dorsal striatum, an evolutionarily older structure13,14. Finally, we used neural network models to demonstrate that behavioural similarity is necessary but not sufficient for this preservation. We posit that these emergent dynamics result from evolutionary constraints on brain development and thus reflect fundamental properties of the neural basis of behaviour.

Bayesian target optimisation for high-precision holographic optogenetics

Two-photon optogenetics has transformed our ability to probe the structure and function of neural circuits. However, achieving precise optogenetic control of neural ensemble activity has remained fundamentally constrained by the problem of off-target stimulation (OTS): the inadvertent activation of nearby non-target neurons due to imperfect confinement of light onto target neurons. Here we propose a novel computational approach to this problem called Bayesian target optimisation. Our approach uses nonparametric Bayesian inference to model neural responses to optogenetic stimulation, and then optimises the laser powers and optical target locations needed to achieve a desired activity pattern with minimal OTS. We validate our approach in simulations and using data from in vitro experiments, showing that Bayesian target optimisation considerably reduces OTS across all conditions we test. Together, these results establish our ability to overcome OTS, enabling optogenetic stimulation with substantially improved precision.

Knowledge mapping of the relationship between norepinephrine and memory: a bibliometric analysis

Introduction

Memory is a fundamental cognitive function for successful interactions with a complex environment. Norepinephrine (NE) is an essential component of catecholamine induced by emotional arousal, and numerous studies have demonstrated that NE is a key regulator in memory enhancement. We therefore conducted a bibliometric analysis to represent the knowledge pattern of the literature on the theme of NE-memory relationship.

Methods

The WOSCC database was selected to extract literature published during 2003-2022. The collected data of annual production, global cooperation, research structure and hotspots were analyzed and visualized.

Results

Our results showed that research on the links between NE and memory displayed a considerable development trend over the last two decades. The USA had a leading position in terms of scientific outputs and collaborations. Meanwhile, University of California Irvine contributed the most publications. Benno Roozendaal and James McGaugh were the most prolific authors in this field, and Neurobiology of Learning and Memory had the highest number of publications on this topic. The research emphasis has evolved from memory-related diseases and brain regions to neural mechanisms for different types of memory at neural circuit levels.

Conclusion

Our bibliometric analysis systematically analyzed the literature on the links between NE and memory from a bibliometric perspective. The demonstrated results of the knowledge mapping would provide valuable insights into the global research landscape.

Parietal stimulation reverses age-related decline in exploration, learning, and decision-making

Aging can compromise decision-making and learning, potentially due to reduced exploratory behaviors crucial for novel problem-solving. We posit that invigorating exploration could mitigate these declines. Supporting this hypothesis, we found that older mice mirrored human aging, displaying less exploration and learning during decision-making, but optogenetic stimulation of their posterior parietal cortex boosted initial exploration, subsequently improving learning. Thus, enhancing exploration-driven learning could be a key to countering cognitive aging.

Fast non-iterative algorithm for 3D point-cloud holography

Recently developed iterative and deep learning-based approaches to computer-generated holography (CGH) have been shown to achieve high-quality photorealistic 3D images with spatial light modulators. However, such approaches remain overly cumbersome for patterning sparse collections of target points across a photoresponsive volume in applications including biological microscopy and material processing. Specifically, in addition to requiring heavy computation that cannot accommodate real-time operation in mobile or hardware-light settings, existing sampling-dependent 3D CGH methods preclude the ability to place target points with arbitrary precision, limiting accessible depths to a handful of planes. Accordingly, we present a non-iterative point cloud holography algorithm that employs fast deterministic calculations in order to efficiently allocate patches of SLM pixels to different target points in the 3D volume and spread the patterning of all points across multiple time frames. Compared to a matched-performance implementation of the iterative Gerchberg-Saxton algorithm, our algorithm's relative computation speed advantage was found to increase with SLM pixel count, reaching >100,000x at 512 × 512 array format.

Single cell in vivo optogenetic stimulation by two-photon excitation fluorescence transfer

Optogenetic manipulation with single-cell resolution can be achieved by two-photon excitation. However, this frequently requires relatively high laser powers. Here, we developed a novel strategy that can improve the efficiency of current two-photon stimulation technologies by positioning fluorescent proteins or small fluorescent molecules with high two-photon cross-sections in the vicinity of opsins. This generates a highly localized source of endogenous single-photon illumination that can be tailored to match the optimal opsin absorbance. Through neuronal and vascular stimulation in the live mouse brain, we demonstrate the utility of this technique to achieve efficient opsin stimulation, without loss of cellular resolution. We also provide a theoretical framework for understanding the potential advantages and constrains of this methodology, with directions for future improvements. Altogether, this fluorescence transfer illumination method opens new possibilities for experiments difficult to implement in the live brain such as all-optical neural interrogation and control of regional cerebral blood flow.

Optogenetic control of neural activity: The biophysics of microbial rhodopsins in neuroscience

Optogenetics, the use of microbial rhodopsins to make the electrical activity of targeted neurons controllable by light, has swept through neuroscience, enabling thousands of scientists to study how specific neuron types contribute to behaviors and pathologies, and how they might serve as novel therapeutic targets. By activating a set of neurons, one can probe what functions they can initiate or sustain, and by silencing a set of neurons, one can probe the functions they are necessary for. We here review the biophysics of these molecules, asking why they became so useful in neuroscience for the study of brain circuitry. We review the history of the field, including early thinking, early experiments, applications of optogenetics, pre-optogenetics targeted neural control tools, and the history of discovering and characterizing microbial rhodopsins. We then review the biophysical attributes of rhodopsins that make them so useful to neuroscience - their classes and structure, their photocycles, their photocurrent magnitudes and kinetics, their action spectra, and their ion selectivity. Our hope is to convey to the reader how specific biophysical properties of these molecules made them especially useful to neuroscientists for a difficult problem - the control of high-speed electrical activity, with great precision and ease, in the brain.

Advocating for neurodata privacy and neurotechnology regulation

The ability to record and alter brain activity by using implantable and nonimplantable neural devices, while poised to have significant scientific and clinical benefits, also raises complex ethical concerns. In this Perspective, we raise awareness of the ability of artificial intelligence algorithms and data-aggregation tools to decode and analyze data containing highly sensitive information, jeopardizing personal neuroprivacy. Voids in existing regulatory frameworks, in fact, allow unrestricted decoding and commerce of neurodata. We advocate for the implementation of proposed ethical and human rights guidelines, alongside technical options such as data encryption, differential privacy and federated learning to ensure the protection of neurodata privacy. We further encourage regulatory bodies to consider taking a position of responsibility by categorizing all brain-derived data as sensitive health data and apply existing medical regulations to all data gathered via pre-registered neural devices. Lastly, we propose that a technocratic oath may instill a deontology for neurotechnology practitioners akin to what the Hippocratic oath represents in medicine. A conscientious societal position that thoroughly rejects the misuse of neurodata would provide the moral compass for the future development of the neurotechnology field.

Channelrhodopsins: From Phototaxis to Optogenetics

Channelrhodopsins stand out among other retinal proteins because of their capacity to generate passive ionic currents following photoactivation. Owing to that, channelrhodopsins are widely used in neuroscience and cardiology as instruments for optogenetic manipulation of the activity of excitable cells. Photocurrents generated by channelrhodopsins were first discovered in the cells of green algae in the 1970s. In this review we describe this discovery and discuss the current state of research in the field.

Structural basis for ion selectivity in potassium-selective channelrhodopsins

KCR channelrhodopsins (K+-selective light-gated ion channels) have received attention as potential inhibitory optogenetic tools but more broadly pose a fundamental mystery regarding how their K+ selectivity is achieved. Here, we present 2.5-2.7 Å cryo-electron microscopy structures of HcKCR1 and HcKCR2 and of a structure-guided mutant with enhanced K+ selectivity. Structural, electrophysiological, computational, spectroscopic, and biochemical analyses reveal a distinctive mechanism for K+ selectivity; rather than forming the symmetrical filter of canonical K+ channels achieving both selectivity and dehydration, instead, three extracellular-vestibule residues within each monomer form a flexible asymmetric selectivity gate, while a distinct dehydration pathway extends intracellularly. Structural comparisons reveal a retinal-binding pocket that induces retinal rotation (accounting for HcKCR1/HcKCR2 spectral differences), and design of corresponding KCR variants with increased K+ selectivity (KALI-1/KALI-2) provides key advantages for optogenetic inhibition in vitro and in vivo. Thus, discovery of a mechanism for ion-channel K+ selectivity also provides a framework for next-generation optogenetics.

Aberration-free holographic microscope for simultaneous imaging and stimulation of neuronal populations

A technical challenge in neuroscience is to record and specifically manipulate the activity of neurons in living animals. This can be achieved in some preparations with two-photon calcium imaging and photostimulation. These methods can be extended to three dimensions by holographic light sculpting with spatial light modulators (SLMs). At the same time, performing simultaneous holographic imaging and photostimulation is still cumbersome, requiring two light paths with separate SLMs. Here we present an integrated optical design using a single SLM for simultaneous imaging and photostimulation. Furthermore, we applied axially dependent adaptive optics to make the system aberration-free, and developed software for calibrations and closed-loop neuroscience experiments. Finally, we demonstrate the performance of the system with simultaneous calcium imaging and optogenetics in mouse primary auditory cortex in vivo. Our integrated holographic system could facilitate the systematic investigation of neural circuit function in awake behaving animals.

Neuron populations across layer 2-6 in the mouse visual cortex exhibit different coding abilities in the awake mice

Introduction

The visual cortex is a key region in the mouse brain, responsible for processing visual information. Comprised of six distinct layers, each with unique neuronal types and connections, the visual cortex exhibits diverse decoding properties across its layers. This study aimed to investigate the relationship between visual stimulus decoding properties and the cortical layers of the visual cortex while considering how this relationship varies across different decoders and brain regions.

Methods

This study reached the above conclusions by analyzing two publicly available datasets obtained through two-photon microscopy of visual cortex neuronal responses. Various types of decoders were tested for visual cortex decoding.

Results

Our findings indicate that the decoding accuracy of neuronal populations with consistent sizes varies among visual cortical layers for visual stimuli such as drift gratings and natural images. In particular, layer 4 neurons in VISp exhibited significantly higher decoding accuracy for visual stimulus identity compared to other layers. However, in VISm, the decoding accuracy of neuronal populations with the same size in layer 2/3 was higher than that in layer 4, despite the overall accuracy being lower than that in VISp and VISl. Furthermore, SVM surpassed other decoders in terms of accuracy, with the variation in decoding performance across layers being consistent among decoders. Additionally, we found that the difference in decoding accuracy across different imaging depths was not associated with the mean orientation selectivity index (OSI) and the mean direction selectivity index (DSI) neurons, but showed a significant positive correlation with the mean reliability and mean signal-to-noise ratio (SNR) of each layer's neuron population.

Discussion

These findings lend new insights into the decoding properties of the visual cortex, highlighting the role of different cortical layers and decoders in determining decoding accuracy. The correlations identified between decoding accuracy and factors such as reliability and SNR pave the way for more nuanced understandings of visual cortex functioning.

Improvement of sensory deficits in fragile X mice by increasing cortical interneuron activity after the critical period

Changes in the function of inhibitory interneurons (INs) during cortical development could contribute to the pathophysiology of neurodevelopmental disorders. Using all-optical in vivo approaches, we find that parvalbumin (PV) INs and their immature precursors are hypoactive and transiently decoupled from excitatory neurons in postnatal mouse somatosensory cortex (S1) of Fmr1 KO mice, a model of fragile X syndrome (FXS). This leads to a loss of parvalbumin INs (PV-INs) in both mice and humans with FXS. Increasing the activity of future PV-INs in neonatal Fmr1 KO mice restores PV-IN density and ameliorates transcriptional dysregulation in S1, but not circuit dysfunction. Critically, administering an allosteric modulator of Kv3.1 channels after the S1 critical period does rescue circuit dynamics and tactile defensiveness. Symptoms in FXS and related disorders could be mitigated by targeting PV-INs.

FIOLA: an accelerated pipeline for fluorescence imaging online analysis

Optical microscopy methods such as calcium and voltage imaging enable fast activity readout of large neuronal populations using light. However, the lack of corresponding advances in online algorithms has slowed progress in retrieving information about neural activity during or shortly after an experiment. This gap not only prevents the execution of real-time closed-loop experiments, but also hampers fast experiment-analysis-theory turnover for high-throughput imaging modalities. Reliable extraction of neural activity from fluorescence imaging frames at speeds compatible with indicator dynamics and imaging modalities poses a challenge. We therefore developed FIOLA, a framework for fluorescence imaging online analysis that extracts neuronal activity from calcium and voltage imaging movies at speeds one order of magnitude faster than state-of-the-art methods. FIOLA exploits algorithms optimized for parallel processing on GPUs and CPUs. We demonstrate reliable and scalable performance of FIOLA on both simulated and real calcium and voltage imaging datasets. Finally, we present an online experimental scenario to provide guidance in setting FIOLA parameters and to highlight the trade-offs of our approach.

Neuronal responses in mouse inferior colliculus correlate with behavioral detection of amplitude-modulated sound

Amplitude modulation (AM) is a common feature of natural sounds, including speech and animal vocalizations. Here, we used operant conditioning and in vivo electrophysiology to determine the AM detection threshold of mice as well as its underlying neuronal encoding. Mice were trained in a Go-NoGo task to detect the transition to AM within a noise stimulus designed to prevent the use of spectral side-bands or a change in intensity as alternative cues. Our results indicate that mice, compared with other species, detect high modulation frequencies up to 512 Hz well, but show much poorer performance at low frequencies. Our in vivo multielectrode recordings in the inferior colliculus (IC) of both anesthetized and awake mice revealed a few single units with remarkable phase-locking ability to 512 Hz modulation, but not sufficient to explain the good behavioral detection at that frequency. Using a model of the population response that combined dimensionality reduction with threshold detection, we reproduced the general band-pass characteristics of behavioral detection based on a subset of neurons showing the largest firing rate change (both increase and decrease) in response to AM, suggesting that these neurons are instrumental in the behavioral detection of AM stimuli by the mice.NEW & NOTEWORTHY The amplitude of natural sounds, including speech and animal vocalizations, often shows characteristic modulations. We examined the relationship between neuronal responses in the mouse inferior colliculus and the behavioral detection of amplitude modulation (AM) in sound and modeled how the former can give rise to the latter. Our model suggests that behavioral detection can be well explained by the activity of a subset of neurons showing the largest firing rate changes in response to AM.

Propagation of activity through the cortical hierarchy and perception are determined by neural variability

Brains are composed of anatomically and functionally distinct regions performing specialized tasks, but regions do not operate in isolation. Orchestration of complex behaviors requires communication between brain regions, but how neural dynamics are organized to facilitate reliable transmission is not well understood. Here we studied this process directly by generating neural activity that propagates between brain regions and drives behavior, assessing how neural populations in sensory cortex cooperate to transmit information. We achieved this by imaging two densely interconnected regions-the primary and secondary somatosensory cortex (S1 and S2)-in mice while performing two-photon photostimulation of S1 neurons and assigning behavioral salience to the photostimulation. We found that the probability of perception is determined not only by the strength of the photostimulation but also by the variability of S1 neural activity. Therefore, maximizing the signal-to-noise ratio of the stimulus representation in cortex relative to the noise or variability is critical to facilitate activity propagation and perception.

Prominent in vivo influence of single interneurons in the developing barrel cortex

Spontaneous synchronous activity is a hallmark of developing brain circuits and promotes their formation. Ex vivo, synchronous activity was shown to be orchestrated by a sparse population of highly connected GABAergic 'hub' neurons. The recent development of all-optical methods to record and manipulate neuronal activity in vivo now offers the unprecedented opportunity to probe the existence and function of hub cells in vivo. Using calcium imaging, connectivity analysis and holographic optical stimulation, we show that single GABAergic, but not glutamatergic, neurons influence population dynamics in the barrel cortex of non-anaesthetized mouse pups. Single GABAergic cells mainly exert an inhibitory influence on both spontaneous and sensory-evoked population bursts. Their network influence scales with their functional connectivity, with highly connected hub neurons displaying the strongest impact. We propose that hub neurons function in tailoring intrinsic cortical dynamics to external sensory inputs.

Differential optogenetic activation of the auditory midbrain in freely moving behaving mice

Introduction

In patients with severe auditory impairment, partial hearing restoration can be achieved by sensory prostheses for the electrical stimulation of the central nervous system. However, these state-of-the-art approaches suffer from limited spectral resolution: electrical field spread depends on the impedance of the surrounding medium, impeding spatially focused electrical stimulation in neural tissue. To overcome these limitations, optogenetic activation could be applied in such prostheses to achieve enhanced resolution through precise and differential stimulation of nearby neuronal ensembles. Previous experiments have provided a first proof for behavioral detectability of optogenetic activation in the rodent auditory system, but little is known about the generation of complex and behaviorally relevant sensory patterns involving differential activation.

Methods

In this study, we developed and behaviorally tested an optogenetic implant to excite two spatially separated points along the tonotopy of the murine inferior colliculus (ICc).

Results

Using a reward based operant Go/No-Go paradigm, we show that differential optogenetic activation of a sub-cortical sensory pathway is possible and efficient. We demonstrate how animals which were previously trained in a frequency discrimination paradigm (a) rapidly respond to either sound or optogenetic stimulation, (b) generally detect optogenetic stimulation of two different neuronal ensembles, and (c) discriminate between them.

Discussion

Our results demonstrate that optogenetic excitatory stimulation at different points of the ICc tonotopy elicits a stable response behavior over time periods of several months. With this study, we provide the first proof of principle for sub-cortical differential stimulation of sensory systems using complex artificial cues in freely moving animals.

Studying behavior under constrained movement

A new platform for studying how brain activity is linked to behavior enables researchers to perform diverse experiments on mice that have their heads immobilized.

All-optical recreation of naturalistic neural activity with a multifunctional transgenic reporter mouse

Determining which features of the neural code drive behavior requires the ability to simultaneously read out and write in neural activity patterns with high precision across many neurons. All-optical systems that combine two-photon calcium imaging and targeted photostimulation enable the activation of specific, functionally defined groups of neurons. However, these techniques are unable to test how patterns of activity across a population contribute to computation because of an inability to both read and write cell-specific firing rates. To overcome this challenge, we make two advances: first, we introduce a genetic line of mice for Cre-dependent co-expression of a calcium indicator and a potent soma-targeted microbial opsin. Second, using this line, we develop a method for read-out and write-in of precise population vectors of neural activity by calibrating the photostimulation to each cell. These advances offer a powerful and convenient platform for investigating the neural codes of computation and behavior.

Role of interneuron subtypes in controlling trial-by-trial output variability in the neocortex

Trial-by-trial variability is a ubiquitous property of neuronal activity in vivo which shapes the stimulus response. Computational models have revealed how local network structure and feedforward inputs shape the trial-by-trial variability. However, the role of input statistics and different interneuron subtypes in this process is less understood. To address this, we investigate the dynamics of stimulus response in a cortical microcircuit model with one excitatory and three inhibitory interneuron populations (PV, SST, VIP). Our findings demonstrate that the balance of inputs to different neuron populations and input covariances are the primary determinants of output trial-by-trial variability. The effect of input covariances is contingent on the input balances. In general, the network exhibits smaller output trial-by-trial variability in a PV-dominated regime than in an SST-dominated regime. Importantly, our work reveals mechanisms by which output trial-by-trial variability can be controlled in a context, state, and task-dependent manner.

Speckle suppression in arbitrary parallel holographic illumination by the spatial frequency regaining method

This Letter proposes a spatial frequency regaining method for parallel holographic illumination (SFR-PHI) to suppress speckle noise in phase-only computer-generated holography (CGH). Based on the accurate calculation of the beam bandwidth, this method uses the bandwidth-limited quadratic initial phase and weighted constraint iteration to generate the optimized phase hologram, which can provide the accurate spatial frequency of multiple illumination patterns. The results show that SFR-PHI performs superiorly in speckle suppression for generating dozens of illumination patterns in parallel and with arbitrary shapes and numbers. Compared with other speckle-suppression methods, it exhibits significant advantages in terms of accuracy and modulation efficiency.

Cell-type-specific plasticity shapes neocortical dynamics for motor learning

Neocortical spiking dynamics control aspects of behavior, yet how these dynamics emerge during motor learning remains elusive. Activity-dependent synaptic plasticity is likely a key mechanism, as it reconfigures network architectures that govern neural dynamics. Here, we examined how the mouse premotor cortex acquires its well-characterized neural dynamics that control movement timing, specifically lick timing. To probe the role of synaptic plasticity, we have genetically manipulated proteins essential for major forms of synaptic plasticity, Ca2+/calmodulin-dependent protein kinase II (CaMKII) and Cofilin, in a region and cell-type-specific manner. Transient inactivation of CaMKII in the premotor cortex blocked learning of new lick timing without affecting the execution of learned action or ongoing spiking activity. Furthermore, among the major glutamatergic neurons in the premotor cortex, CaMKII and Cofilin activity in pyramidal tract (PT) neurons, but not intratelencephalic (IT) neurons, is necessary for learning. High-density electrophysiology in the premotor cortex uncovered that neural dynamics anticipating licks are progressively shaped during learning, which explains the change in lick timing. Such reconfiguration in behaviorally relevant dynamics is impeded by CaMKII manipulation in PT neurons. Altogether, the activity of plasticity-related proteins in PT neurons plays a central role in sculpting neocortical dynamics to learn new behavior.

Feedforward amplification in recurrent networks underlies paradoxical neural coding

The activity of single neurons encodes behavioral variables, such as sensory stimuli (Hubel & Wiesel 1959) and behavioral choice (Britten et al. 1992; Guo et al. 2014), but their influence on behavior is often mysterious. We estimated the influence of a unit of neural activity on behavioral choice from recordings in anterior lateral motor cortex (ALM) in mice performing a memory-guided movement task (H. K. Inagaki et al. 2018). Choice selectivity grew as it flowed through a sequence of directions in activity space. Early directions carried little selectivity but were predicted to have a large behavioral influence, while late directions carried large selectivity and little behavioral influence. Consequently, estimated behavioral influence was only weakly correlated with choice selectivity; a large proportion of neurons selective for one choice were predicted to influence choice in the opposite direction. These results were consistent with models in which recurrent circuits produce feedforward amplification (Goldman 2009; Ganguli et al. 2008; Murphy & Miller 2009) so that small amplitude signals along early directions are amplified to produce low-dimensional choice selectivity along the late directions, and behavior. Targeted photostimulation experiments (Daie et al. 2021b) revealed that activity along the early directions triggered sequential activity along the later directions and caused predictable behavioral biases. These results demonstrate the existence of an amplifying feedforward dynamical motif in the motor cortex, explain paradoxical responses to perturbation experiments (Chettih & Harvey 2019; Daie et al. 2021b; Russell et al. 2019), and reveal behavioral relevance of small amplitude neural dynamics.

Tagging neurons with light

Molecular circuits for activity-guided optogenetics.

A cell-type-specific error-correction signal in the posterior parietal cortex

Neurons in the posterior parietal cortex contribute to the execution of goal-directed navigation1 and other decision-making tasks2-4. Although molecular studies have catalogued more than 50 cortical cell types5, it remains unclear what distinct functions they have in this area. Here we identified a molecularly defined subset of somatostatin (Sst) inhibitory neurons that, in the mouse posterior parietal cortex, carry a cell-type-specific error-correction signal for navigation. We obtained repeatable experimental access to these cells using an adeno-associated virus in which gene expression is driven by an enhancer that functions specifically in a subset of Sst cells6. We found that during goal-directed navigation in a virtual environment, this subset of Sst neurons activates in a synchronous pattern that is distinct from the activity of surrounding neurons, including other Sst neurons. Using in vivo two-photon photostimulation and ex vivo paired patch-clamp recordings, we show that nearby cells of this Sst subtype excite each other through gap junctions, revealing a self-excitation circuit motif that contributes to the synchronous activity of this cell type. These cells selectively activate as mice execute course corrections for deviations in their virtual heading during navigation towards a reward location, for both self-induced and experimentally induced deviations. We propose that this subtype of Sst neurons provides a self-reinforcing and cell-type-specific error-correction signal in the posterior parietal cortex that may help with the execution and learning of accurate goal-directed navigation trajectories.

Early developmental deletion of forebrain Ank2 causes seizure-related phenotypes by reshaping the synaptic proteome

Rare genetic variants in ANK2, which encodes ankyrin-B, are associated with neurodevelopmental disorders (NDDs); however, their pathogenesis is poorly understood. We find that mice with prenatal deletion in cortical excitatory neurons and oligodendrocytes (Ank2-/-:Emx1-Cre), but not with adolescent deletion in forebrain excitatory neurons (Ank2-/-:CaMKIIα-Cre), display severe spontaneous seizures, increased mortality, hyperactivity, and social deficits. Calcium imaging of cortical slices from Ank2-/-:Emx1-Cre mice shows increased neuronal calcium event amplitude and frequency, along with network hyperexcitability and hypersynchrony. Quantitative proteomic analysis of cortical synaptic membranes reveals upregulation of dendritic spine plasticity-regulatory proteins and downregulation of intermediate filaments. Characterization of the ankyrin-B interactome identifies interactors associated with autism and epilepsy risk factors and synaptic proteins. The AMPA receptor antagonist, perampanel, restores cortical neuronal activity and partially rescues survival in Ank2-/-:Emx1-Cre mice. Our findings suggest that synaptic proteome alterations resulting from Ank2 deletion impair neuronal activity and synchrony, leading to NDDs-related behavioral impairments.

Behavioral decomposition reveals rich encoding structure employed across neocortex in rats

The cortical population code is pervaded by activity patterns evoked by movement, but it remains largely unknown how such signals relate to natural behavior or how they might support processing in sensory cortices where they have been observed. To address this we compared high-density neural recordings across four cortical regions (visual, auditory, somatosensory, motor) in relation to sensory modulation, posture, movement, and ethograms of freely foraging male rats. Momentary actions, such as rearing or turning, were represented ubiquitously and could be decoded from all sampled structures. However, more elementary and continuous features, such as pose and movement, followed region-specific organization, with neurons in visual and auditory cortices preferentially encoding mutually distinct head-orienting features in world-referenced coordinates, and somatosensory and motor cortices principally encoding the trunk and head in egocentric coordinates. The tuning properties of synaptically coupled cells also exhibited connection patterns suggestive of area-specific uses of pose and movement signals, particularly in visual and auditory regions. Together, our results indicate that ongoing behavior is encoded at multiple levels throughout the dorsal cortex, and that low-level features are differentially utilized by different regions to serve locally relevant computations.

Learning in a sensory cortical microstimulation task is associated with elevated representational stability

Sensory cortical representations can be highly dynamic, raising the question of how representational stability impacts learning. We train mice to discriminate the number of photostimulation pulses delivered to opsin-expressing pyramidal neurons in layer 2/3 of primary vibrissal somatosensory cortex. We simultaneously track evoked neural activity across learning using volumetric two-photon calcium imaging. In well-trained animals, trial-to-trial fluctuations in the amount of photostimulus-evoked activity predicted animal choice. Population activity levels declined rapidly across training, with the most active neurons showing the largest declines in responsiveness. Mice learned at varied rates, with some failing to learn the task in the time provided. The photoresponsive population showed greater instability both within and across behavioral sessions among animals that failed to learn. Animals that failed to learn also exhibited a faster deterioration in stimulus decoding. Thus, greater stability in the stimulus response is associated with learning in a sensory cortical microstimulation task.

Cortical circuitry mediating inter-areal touch signal amplification

Sensory cortical areas are often organized into topographic maps which represent the sensory epithelium1,2. Individual areas are richly interconnected3, in many cases via reciprocal projections that respect the topography of the underlying map4,5. Because topographically matched cortical patches process the same stimulus, their interaction is likely central to many neural computations6-10. Here, we ask how topographically matched subregions of primary and secondary vibrissal somatosensory cortices (vS1 and vS2) interact during whisker touch. In the mouse, whisker touch-responsive neurons are topographically organized in both vS1 and vS2. Both areas receive thalamic touch input and are topographically interconnected4. Volumetric calcium imaging in mice actively palpating an object with two whiskers revealed a sparse population of highly active, broadly tuned touch neurons responsive to both whiskers. These neurons were especially pronounced in superficial layer 2 in both areas. Despite their rarity, these neurons served as the main conduits of touch-evoked activity between vS1 and vS2 and exhibited elevated synchrony. Focal lesions of the whisker touch-responsive region in vS1 or vS2 degraded touch responses in the unlesioned area, with whisker-specific vS1 lesions degrading whisker-specific vS2 touch responses. Thus, a sparse and superficial population of broadly tuned touch neurons recurrently amplifies touch responses across vS1 and vS2.

Identifying properties of pattern completion neurons in a computational model of the visual cortex

Neural ensembles are found throughout the brain and are believed to underlie diverse cognitive functions including memory and perception. Methods to activate ensembles precisely, reliably, and quickly are needed to further study the ensembles' role in cognitive processes. Previous work has found that ensembles in layer 2/3 of the visual cortex (V1) exhibited pattern completion properties: ensembles containing tens of neurons were activated by stimulation of just two neurons. However, methods that identify pattern completion neurons are underdeveloped. In this study, we optimized the selection of pattern completion neurons in simulated ensembles. We developed a computational model that replicated the connectivity patterns and electrophysiological properties of layer 2/3 of mouse V1. We identified ensembles of excitatory model neurons using K-means clustering. We then stimulated pairs of neurons in identified ensembles while tracking the activity of the entire ensemble. Our analysis of ensemble activity quantified a neuron pair's power to activate an ensemble using a novel metric called pattern completion capability (PCC) based on the mean pre-stimulation voltage across the ensemble. We found that PCC was directly correlated with multiple graph theory parameters, such as degree and closeness centrality. To improve selection of pattern completion neurons in vivo, we computed a novel latency metric that was correlated with PCC and could potentially be estimated from modern physiological recordings. Lastly, we found that stimulation of five neurons could reliably activate ensembles. These findings can help researchers identify pattern completion neurons to stimulate in vivo during behavioral studies to control ensemble activation.

Visual cortex: How mice learn to detect entirely novel inputs

A new study has revealed that neural amplification in mouse primary visual cortex substantially increases between training sessions as mice learn to detect novel optogenetic input directly into visual cortex, suggesting consolidation and recurrent network plasticity contribute to learning the behavior.

Amplified cortical neural responses as animals learn to use novel activity patterns

Cerebral cortex supports representations of the world in patterns of neural activity, used by the brain to make decisions and guide behavior. Past work has found diverse, or limited, changes in the primary sensory cortex in response to learning, suggesting that the key computations might occur in downstream regions. Alternatively, sensory cortical changes may be central to learning. We studied cortical learning by using controlled inputs we insert: we trained mice to recognize entirely novel, non-sensory patterns of cortical activity in the primary visual cortex (V1) created by optogenetic stimulation. As animals learned to use these novel patterns, we found that their detection abilities improved by an order of magnitude or more. The behavioral change was accompanied by large increases in V1 neural responses to fixed optogenetic input. Neural response amplification to novel optogenetic inputs had little effect on existing visual sensory responses. A recurrent cortical model shows that this amplification can be achieved by a small mean shift in recurrent network synaptic strength. Amplification would seem to be desirable to improve decision-making in a detection task; therefore, these results suggest that adult recurrent cortical plasticity plays a significant role in improving behavioral performance during learning.

A unifying perspective on neural manifolds and circuits for cognition

Two different perspectives have informed efforts to explain the link between the brain and behaviour. One approach seeks to identify neural circuit elements that carry out specific functions, emphasizing connectivity between neurons as a substrate for neural computations. Another approach centres on neural manifolds - low-dimensional representations of behavioural signals in neural population activity - and suggests that neural computations are realized by emergent dynamics. Although manifolds reveal an interpretable structure in heterogeneous neuronal activity, finding the corresponding structure in connectivity remains a challenge. We highlight examples in which establishing the correspondence between low-dimensional activity and connectivity has been possible, unifying the neural manifold and circuit perspectives. This relationship is conspicuous in systems in which the geometry of neural responses mirrors their spatial layout in the brain, such as the fly navigational system. Furthermore, we describe evidence that, in systems in which neural responses are heterogeneous, the circuit comprises interactions between activity patterns on the manifold via low-rank connectivity. We suggest that unifying the manifold and circuit approaches is important if we are to be able to causally test theories about the neural computations that underlie behaviour.

Practical considerations in an era of multicolor optogenetics

The ability to control synaptic communication is indispensable to modern neuroscience. Until recently, only single-pathway manipulations were possible due to limited availability of opsins activated by distinct wavelengths. However, extensive protein engineering and screening efforts have drastically expanded the optogenetic toolkit, ushering in an era of multicolor approaches for studying neural circuits. Nonetheless, opsins with truly discrete spectra are scarce. Experimenters must therefore take care to avoid unintended cross-activation of optogenetic tools (crosstalk). Here, we demonstrate the multidimensional nature of crosstalk in a single model synaptic pathway, testing stimulus wavelength, irradiance, duration, and opsin choice. We then propose a "lookup table" method for maximizing the dynamic range of opsin responses on an experiment-by-experiment basis.

De novo motor learning creates structure in neural activity space that shapes adaptation

Animals can quickly adapt learned movements in response to external perturbations. Motor adaptation is likely influenced by an animal's existing movement repertoire, but the nature of this influence is unclear. Long-term learning causes lasting changes in neural connectivity which determine the activity patterns that can be produced. Here, we sought to understand how a neural population's activity repertoire, acquired through long-term learning, affects short-term adaptation by modeling motor cortical neural population dynamics during de novo learning and subsequent adaptation using recurrent neural networks. We trained these networks on different motor repertoires comprising varying numbers of movements. Networks with multiple movements had more constrained and robust dynamics, which were associated with more defined neural 'structure'-organization created by the neural population activity patterns corresponding to each movement. This structure facilitated adaptation, but only when small changes in motor output were required, and when the structure of the network inputs, the neural activity space, and the perturbation were congruent. These results highlight trade-offs in skill acquisition and demonstrate how prior experience and external cues during learning can shape the geometrical properties of neural population activity as well as subsequent adaptation.

Distributing task-related neural activity across a cortical network through task-independent connections

Task-related neural activity is widespread across populations of neurons during goal-directed behaviors. However, little is known about the synaptic reorganization and circuit mechanisms that lead to broad activity changes. Here we trained a subset of neurons in a spiking network with strong synaptic interactions to reproduce the activity of neurons in the motor cortex during a decision-making task. Task-related activity, resembling the neural data, emerged across the network, even in the untrained neurons. Analysis of trained networks showed that strong untrained synapses, which were independent of the task and determined the dynamical state of the network, mediated the spread of task-related activity. Optogenetic perturbations suggest that the motor cortex is strongly-coupled, supporting the applicability of the mechanism to cortical networks. Our results reveal a cortical mechanism that facilitates distributed representations of task-variables by spreading the activity from a subset of plastic neurons to the entire network through task-independent strong synapses.

Targeting operational regimes of interest in recurrent neural networks

Neural computations emerge from local recurrent neural circuits or computational units such as cortical columns that comprise hundreds to a few thousand neurons. Continuous progress in connectomics, electrophysiology, and calcium imaging require tractable spiking network models that can consistently incorporate new information about the network structure and reproduce the recorded neural activity features. However, for spiking networks, it is challenging to predict which connectivity configurations and neural properties can generate fundamental operational states and specific experimentally reported nonlinear cortical computations. Theoretical descriptions for the computational state of cortical spiking circuits are diverse, including the balanced state where excitatory and inhibitory inputs balance almost perfectly or the inhibition stabilized state (ISN) where the excitatory part of the circuit is unstable. It remains an open question whether these states can co-exist with experimentally reported nonlinear computations and whether they can be recovered in biologically realistic implementations of spiking networks. Here, we show how to identify spiking network connectivity patterns underlying diverse nonlinear computations such as XOR, bistability, inhibitory stabilization, supersaturation, and persistent activity. We establish a mapping between the stabilized supralinear network (SSN) and spiking activity which allows us to pinpoint the location in parameter space where these activity regimes occur. Notably, we find that biologically-sized spiking networks can have irregular asynchronous activity that does not require strong excitation-inhibition balance or large feedforward input and we show that the dynamic firing rate trajectories in spiking networks can be precisely targeted without error-driven training algorithms.

Microstimulation of sensory cortex engages natural sensory representations

Cortical activity patterns occupy a small subset of possible network states. If this is due to intrinsic network properties, microstimulation of sensory cortex should evoke activity patterns resembling those observed during natural sensory input. Here, we use optical microstimulation of virally transfected layer 2/3 pyramidal neurons in the mouse primary vibrissal somatosensory cortex to compare artificially evoked activity with natural activity evoked by whisker touch and movement ("whisking"). We find that photostimulation engages touch- but not whisking-responsive neurons more than expected by chance. Neurons that respond to photostimulation and touch or to touch alone exhibit higher spontaneous pairwise correlations than purely photoresponsive neurons. Exposure to several days of simultaneous touch and optogenetic stimulation raises both overlap and spontaneous activity correlations among touch and photoresponsive neurons. We thus find that cortical microstimulation engages existing cortical representations and that repeated co-presentation of natural and artificial stimulation enhances this effect.

Cortico-cortical feedback engages active dendrites in visual cortex

Sensory processing in the neocortex requires both feedforward and feedback information flow between cortical areas¹. In feedback processing, higher-level representations provide contextual information to lower levels, and facilitate perceptual functions such as contour integration and figure-ground segmentation^2,3. However, we have limited understanding of the circuit and cellular mechanisms that mediate feedback influence. Here we use long-range all-optical connectivity mapping in mice to show that feedback influence from the lateromedial higher visual area (LM) to the primary visual cortex (V1) is spatially organized. When the source and target of feedback represent the same area of visual space, feedback is relatively suppressive. By contrast, when the source is offset from the target in visual space, feedback is relatively facilitating. Two-photon calcium imaging data show that this facilitating feedback is nonlinearly integrated in the apical tuft dendrites of V1 pyramidal neurons: retinotopically offset (surround) visual stimuli drive local dendritic calcium signals indicative of regenerative events, and two-photon optogenetic activation of LM neurons projecting to identified feedback-recipient spines in V1 can drive similar branch-specific local calcium signals. Our results show how neocortical feedback connectivity and nonlinear dendritic integration can together form a substrate to support both predictive and cooperative contextual interactions.

Adeno-associated virus 2 infection in children with non-A-E hepatitis

An outbreak of acute hepatitis of unknown aetiology in children was reported in Scotland1 in April 2022 and has now been identified in 35 countries2. Several recent studies have suggested an association with human adenovirus with this outbreak, a virus not commonly associated with hepatitis. Here we report a detailed case-control investigation and find an association between adeno-associated virus 2 (AAV2) infection and host genetics in disease susceptibility. Using next-generation sequencing, PCR with reverse transcription, serology and in situ hybridization, we detected recent infection with AAV2 in plasma and liver samples in 26 out of 32 (81%) cases of hepatitis compared with 5 out of 74 (7%) of samples from unaffected individuals. Furthermore, AAV2 was detected within ballooned hepatocytes alongside a prominent T cell infiltrate in liver biopsy samples. In keeping with a CD4+ T-cell-mediated immune pathology, the human leukocyte antigen (HLA) class II HLA-DRB1*04:01 allele was identified in 25 out of 27 cases (93%) compared with a background frequency of 10 out of 64 (16%; P = 5.49 × 10-12). In summary, we report an outbreak of acute paediatric hepatitis associated with AAV2 infection (most likely acquired as a co-infection with human adenovirus that is usually required as a 'helper virus' to support AAV2 replication) and disease susceptibility related to HLA class II status.

Neural engineering with photons as synaptic transmitters

Neuronal computation is achieved through connections of individual neurons into a larger network. To expand the repertoire of endogenous cellular communication, we developed a synthetic, photon-assisted synaptic transmission (PhAST) system. PhAST is based on luciferases and channelrhodopsins that enable the transmission of a neuronal state across space, using photons as neurotransmitters. PhAST overcomes synaptic barriers and rescues the behavioral deficit of a glutamate mutant with conditional, calcium-triggered photon emission between two neurons of the Caenorhabditis elegans nociceptive avoidance circuit. To demonstrate versatility and flexibility, we generated de novo synaptic transmission between two unconnected cells in a sexually dimorphic neuronal circuit, suppressed endogenous nocifensive response through activation of an anion channelrhodopsin and switched attractive to aversive behavior in an olfactory circuit. Finally, we applied PhAST to dissect the calcium dynamics of the temporal pattern generator in a motor circuit for ovipositioning. In summary, we established photon-based synaptic transmission that facilitates the modification of animal behavior.