Fast online deconvolution of calcium imaging data

Population dynamics of head-direction neurons during drift and reorientation

The head direction (HD) system functions as the brain's internal compass^1,2, classically formalized as a one-dimensional ring attractor network^3,4. In contrast to a globally consistent magnetic compass, the HD system does not have a universal reference frame. Instead, it anchors to local cues, maintaining a stable offset when cues rotate^5-8 and drifting in the absence of referents^5,8-10. However, questions about the mechanisms that underlie anchoring and drift remain unresolved and are best addressed at the population level. For example, the extent to which the one-dimensional description of population activity holds under conditions of reorientation and drift is unclear. Here we performed population recordings of thalamic HD cells using calcium imaging during controlled rotations of a visual landmark. Across experiments, population activity varied along a second dimension, which we refer to as network gain, especially under circumstances of cue conflict and ambiguity. Activity along this dimension predicted realignment and drift dynamics, including the speed of network realignment. In the dark, network gain maintained a 'memory trace' of the previously displayed landmark. Further experiments demonstrated that the HD network returned to its baseline orientation after brief, but not longer, exposures to a rotated cue. This experience dependence suggests that memory of previous associations between HD neurons and allocentric cues is maintained and influences the internal HD representation. Building on these results, we show that continuous rotation of a visual landmark induced rotation of the HD representation that persisted in darkness, demonstrating experience-dependent recalibration of the HD system. Finally, we propose a computational model to formalize how the neural compass flexibly adapts to changing environmental cues to maintain a reliable representation of HD. These results challenge classical one-dimensional interpretations of the HD system and provide insights into the interactions between this system and the cues to which it anchors.

Recurrent network interactions explain tectal response variability and experience-dependent behavior

Response variability is an essential and universal feature of sensory processing and behavior. It arises from fluctuations in the internal state of the brain, which modulate how sensory information is represented and transformed to guide behavioral actions. In part, brain state is shaped by recent network activity, fed back through recurrent connections to modulate neuronal excitability. However, the degree to which these interactions influence response variability and the spatial and temporal scales across which they operate, are poorly understood. Here, we combined population recordings and modeling to gain insights into how neuronal activity modulates network state and thereby impacts visually evoked activity and behavior. First, we performed cellular-resolution calcium imaging of the optic tectum to monitor ongoing activity, the pattern of which is both a cause and consequence of changes in network state. We developed a minimal network model incorporating fast, short range, recurrent excitation and long-lasting, activity-dependent suppression that reproduced a hallmark property of tectal activity - intermittent bursting. We next used the model to estimate the excitability state of tectal neurons based on recent activity history and found that this explained a portion of the trial-to-trial variability in visually evoked responses, as well as spatially selective response adaptation. Moreover, these dynamics also predicted behavioral trends such as selective habituation of visually evoked prey-catching. Overall, we demonstrate that a simple recurrent interaction motif can be used to estimate the effect of activity upon the incidental state of a neural network and account for experience-dependent effects on sensory encoding and visually guided behavior.

Neuronal Cultures: Exploring Biophysics, Complex Systems, and Medicine in a Dish

Neuronal cultures are one of the most important experimental models in modern interdisciplinary neuroscience, allowing to investigate in a control environment the emergence of complex behavior from an ensemble of interconnected neurons. Here, I review the research that we have conducted at the neurophysics laboratory at the University of Barcelona over the last 15 years, describing first the neuronal cultures that we prepare and the associated tools to acquire and analyze data, to next delve into the different research projects in which we actively participated to progress in the understanding of open questions, extend neuroscience research on new paradigms, and advance the treatment of neurological disorders. I finish the review by discussing the drawbacks and limitations of neuronal cultures, particularly in the context of brain-like models and biomedicine.

Delayed formation of neural representations of space in aged mice

Aging is associated with cognitive deficits, with spatial memory being very susceptible to decline. The hippocampal dentate gyrus (DG) is important for processing spatial information in the brain and is particularly vulnerable to aging, yet its sparse activity has led to difficulties in assessing changes in this area. Using in vivo two-photon calcium imaging, we compared DG neuronal activity and representations of space in young and aged mice walking on an unfamiliar treadmill. We found that calcium activity was significantly higher and less tuned to location in aged mice, resulting in decreased spatial information encoded in the DG. However, with repeated exposure to the same treadmill, both spatial tuning and information levels in aged mice became similar to young mice, while activity remained elevated. Our results show that spatial representations of novel environments are impaired in the aged hippocampus and gradually improve with increased familiarity. Moreover, while the aged DG is hyperexcitable, this does not disrupt neural representations of familiar environments.

Highly synchronized cortical circuit dynamics mediate spontaneous pain in mice

Cortical neural dynamics mediate information processing for the cerebral cortex, which is implicated in fundamental biological processes such as vision and olfaction, in addition to neurological and psychiatric diseases. Spontaneous pain is a key feature of human neuropathic pain. Whether spontaneous pain pushes the cortical network into an aberrant state and, if so, whether it can be brought back to a "normal" operating range to ameliorate pain are unknown. Using a clinically relevant mouse model of neuropathic pain with spontaneous pain-like behavior, we report that orofacial spontaneous pain activated a specific area within the primary somatosensory cortex (S1), displaying synchronized neural dynamics revealed by intravital two-photon calcium imaging. This synchronization was underpinned by local GABAergic interneuron hypoactivity. Pain-induced cortical synchronization could be attenuated by manipulating local S1 networks or clinically effective pain therapies. Specifically, both chemogenetic inhibition of pain-related c-Fos-expressing neurons and selective activation of GABAergic interneurons significantly attenuated S1 synchronization. Clinically effective pain therapies including carbamazepine and nerve root decompression could also dampen S1 synchronization. More important, restoring a "normal" range of neural dynamics through attenuation of pain-induced S1 synchronization alleviated pain-like behavior. These results suggest that spontaneous pain pushed the S1 regional network into a synchronized state, whereas reversal of this synchronization alleviated pain.

Early impairments of visually-driven neuronal ensemble dynamics in the rTg4510 tauopathy mouse model

Tau protein pathology is a hallmark of many neurodegenerative diseases, including Alzheimer's Disease or frontotemporal dementia. Synaptic dysfunction and abnormal visual evoked potentials have been reported in murine models of tauopathy, but little is known about the state of the network activity on a single neuronal level prior to brain atrophy. In the present study, oscillatory rhythms and single-cell calcium activity of primary visual cortex pyramidal neuron population were investigated in basal and light evoked states in the rTg4510 tauopathy mouse model prior to neurodegeneration. We found a decrease in their responsivity and overall activity which was insensitive to GABAergic modulation. Despite an enhancement of basal state coactivation of cortical pyramidal neurons, a loss of input-output synchronicity was observed. Dysfunction of cortical pyramidal function was also reflected in a reduction of basal theta oscillations and enhanced susceptibility to a sub-convulsive dose of pentylenetetrazol in rTg4510 mice. Our results unveil impairments in visual cortical pyramidal neuron processing and define aberrant oscillations as biomarker candidates in early stages of neurodegenerative tauopathies.

Hyperexcited limbic neurons represent sexual satiety and reduce mating motivation

Transient sexual experiences can have long-lasting effects on behavioral decisions, but the neural coding that accounts for this change is unclear. We found that the ejaculation experience selectively activated estrogen receptor 2 (Esr2)-expressing neurons in the bed nucleus of the stria terminalis (BNST)-BNST^Esr2-and led to persistent decreases in firing threshold for days, during which time the mice displayed sexual satiety. Inhibition of hyperexcited BNST^Esr2 elicited fast mating recovery in satiated mice of both sexes. In males, such hyperexcitability reduced mating motivation and was partially mediated by larger HCN (hyperpolarization-activated cyclic nucleotide-gated) currents. Thus, BNST^Esr2 not only encode a specific mating action but also represent a persistent state of sexual satiety, and alterations in a neuronal ion channel contribute to sexual experience-dependent long-term changes to mating drive.

New imaging instrument in animal models: Two-photon miniature microscope and large field of view miniature microscope for freely behaving animals

Over the past decade, novel optical imaging tools have been developed for imaging neuronal activities along with the evolution of fluorescence indicators with brighter expression and higher sensitivity. Miniature microscopes, as revolutionary approaches, enable the imaging of large populations of neuron ensembles in freely behaving rodents and mammals, which allows exploring the neural basis of behaviors. Recent progress in two-photon miniature microscopes and mesoscale single-photon miniature microscopes further expand those affordable methods to navigate neural activities during naturalistic behaviors. In this review article, two-photon miniature microscopy techniques are summarized historically from the first documented attempt to the latest ones, and comparisons are made. The driving force behind and their potential for neuroscientific inquiries are also discussed. Current progress in terms of the mesoscale, i.e., the large field-of-view miniature microscopy technique, is addressed as well. Then, pipelines for registering single cells from the data of two-photon and large field-of-view miniature microscopes are discussed. Finally, we present the potential evolution of the techniques.

Cortical VIP neurons locally control the gain but globally control the coherence of gamma band rhythms

Gamma band synchronization can facilitate local and long-range neural communication. In the primary visual cortex, visual stimulus properties within a specific location determine local synchronization strength, while the match of stimulus properties between distant locations controls long-range synchronization. The neural basis for the differential control of local and global gamma band synchronization is unknown. Combining electrophysiology, optogenetics, and computational modeling, we found that VIP disinhibitory interneurons in mouse cortex linearly scale gamma power locally without changing its stimulus tuning. Conversely, they suppress long-range synchronization when two regions process non-matched stimuli, tuning gamma coherence globally. Modeling shows that like-to-like connectivity across space and specific VIP→SST inhibition capture these opposing effects. VIP neurons thus differentially impact local and global properties of gamma rhythms depending on visual stimulus statistics. They may thereby construct gamma-band filters for spatially extended but continuous image features, such as contours, facilitating the downstream generation of coherent visual percepts.

Scale-free behavioral dynamics directly linked with scale-free cortical dynamics

Naturally occurring body movements and collective neural activity both exhibit complex dynamics, often with scale-free, fractal spatiotemporal structure. Scale-free dynamics of both brain and behavior are important because each is associated with functional benefits to the organism. Despite their similarities, scale-free brain activity and scale-free behavior have been studied separately, without a unified explanation. Here, we show that scale-free dynamics of mouse behavior and neurons in the visual cortex are strongly related. Surprisingly, the scale-free neural activity is limited to specific subsets of neurons, and these scale-free subsets exhibit stochastic winner-take-all competition with other neural subsets. This observation is inconsistent with prevailing theories of scale-free dynamics in neural systems, which stem from the criticality hypothesis. We develop a computational model which incorporates known cell-type-specific circuit structure, explaining our findings with a new type of critical dynamics. Our results establish neural underpinnings of scale-free behavior and clear behavioral relevance of scale-free neural activity.

A hardware system for real-time decoding of in vivo calcium imaging data

Epifluorescence miniature microscopes ('miniscopes') are widely used for in vivo calcium imaging of neural population activity. Imaging data are typically collected during a behavioral task and stored for later offline analysis, but emerging techniques for online imaging can support novel closed-loop experiments in which neural population activity is decoded in real time to trigger neurostimulation or sensory feedback. To achieve short feedback latencies, online imaging systems must be optimally designed to maximize computational speed and efficiency while minimizing errors in population decoding. Here we introduce DeCalciOn, an open-source device for real-time imaging and population decoding of in vivo calcium signals that is hardware compatible with all miniscopes that use the UCLA Data Acquisition (DAQ) interface. DeCalciOn performs online motion stabilization, neural enhancement, calcium trace extraction, and decoding of up to 1024 traces per frame at latencies of <50 ms after fluorescence photons arrive at the miniscope image sensor. We show that DeCalciOn can accurately decode the position of rats (n = 12) running on a linear track from calcium fluorescence in the hippocampal CA1 layer, and can categorically classify behaviors performed by rats (n = 2) during an instrumental task from calcium fluorescence in orbitofrontal cortex. DeCalciOn achieves high decoding accuracy at short latencies using innovations such as field-programmable gate array hardware for real-time image processing and contour-free methods to efficiently extract calcium traces from sensor images. In summary, our system offers an affordable plug-and-play solution for real-time calcium imaging experiments in behaving animals.

Dimensionality reduction of calcium-imaged neuronal population activity

Calcium imaging has been widely adopted for its ability to record from large neuronal populations. To summarize the time course of neural activity, dimensionality reduction methods, which have been applied extensively to population spiking activity, may be particularly useful. However, it is unclear if the dimensionality reduction methods applied to spiking activity are appropriate for calcium imaging. We thus carried out a systematic study of design choices based on standard dimensionality reduction methods. We also developed a method to perform deconvolution and dimensionality reduction simultaneously (Calcium Imaging Linear Dynamical System, CILDS). CILDS most accurately recovered the single-trial, low-dimensional time courses from simulated calcium imaging data. CILDS also outperformed the other methods on calcium imaging recordings from larval zebrafish and mice. More broadly, this study represents a foundation for summarizing calcium imaging recordings of large neuronal populations using dimensionality reduction in diverse experimental settings.

Topographically Localized Modulation of Tectal Cell Spatial Tuning by Complex Natural Scenes

The tuning properties of neurons in the visual system can be contextually modulated by the statistics of the area surrounding their receptive field (RF), particularly when the surround contains natural features. However, stimuli presented in specific egocentric locations may have greater behavioral relevance, raising the possibility that the extent of contextual modulation may vary with position in visual space. To explore this possibility, we utilized the small size and optical transparency of the larval zebrafish to describe the form and spatial arrangement of contextually modulated cells throughout an entire tectal hemisphere. We found that the spatial tuning of tectal neurons to a prey-like stimulus sharpens when the stimulus is presented against a background with the statistics of complex natural scenes, relative to a featureless background. These neurons are confined to a spatially restricted region of the tectum and have receptive fields centered within a region of visual space in which the presence of prey preferentially triggers hunting behavior. Our results suggest that contextual modulation of tectal neurons by complex backgrounds may facilitate prey-localization in cluttered visual environments.

Calcium activity is a degraded estimate of spikes

Recording action potentials extracellularly during behavior has led to fundamental discoveries regarding neural function-hippocampal neurons respond to locations in space,1 motor cortex neurons encode movement direction,2 and dopamine neurons signal reward prediction errors3-observations undergirding current theories of cognition,4 movement,5 and learning.6 Recently it has become possible to measure calcium flux, an internal cellular signal related to spiking. The ability to image calcium flux in anatomically7,8 or genetically9 identified neurons can extend our knowledge of neural circuit function by allowing activity to be monitored in specific cell types or projections, or in the same neurons across many days. However, while initial studies were grounded in prior unit recording work, it has become fashionable to assume that calcium is identical to spiking, even though the spike-to-fluorescence transformation is nonlinear, noisy, and unpredictable under real-world conditions.10 It remains an open question whether calcium provides a high-fidelity representation of single-unit activity in awake, behaving subjects. Here, we have addressed this question by recording both signals in the lateral orbitofrontal cortex (OFC) of rats during olfactory discrimination learning. Activity in the OFC during olfactory learning has been well-studied in humans,11,12,13,14 nonhuman primates,15,16 and rats,17,18,19,20,21 where it has been shown to signal information about both the sensory properties of odor cues and the rewards they predict. Our single-unit results replicated prior findings, whereas the calcium signal provided only a degraded estimate of the information available in the single-unit spiking, reflecting primarily reward value.

Forebrain Glucocorticoid Receptor Overexpression Alters Behavioral Encoding of Hippocampal CA1 Pyramidal Cells in Mice

Glucocorticoid signaling influences hippocampal-dependent behavior and vulnerability to stress-related neuropsychiatric disorders. In mice, lifelong overexpression of glucocorticoid receptor (GR) in forebrain excitatory neurons altered exploratory behavior, cognition, and dorsal hippocampal gene expression in adulthood, but whether GR overexpression alters the information encoded by hippocampal neurons is not known. We performed in vivo microendoscopic calcium imaging of 1359 dorsal CA1 pyramidal cells in freely behaving male and female wild-type (WT) and GR-overexpressing (GRov) mice during exploration of a novel open field, where most CA1 neurons are expected to respond to center location and mobility. Most neurons showed sensitivity to center location and/or mobility based on single-neuron calcium amplitude and event rate, but these sensitivity patterns differed between genotypes. GRov neurons were more likely than WT neurons to display center sensitivity and less likely to display mobility sensitivity. More than one-third of these responsive GRov neurons were sensitive only to center location and not mobility, while uniquely center-sensitive neurons were rare in WT. Most center-sensitive neurons exhibited anticipatory activity, suggesting they could drive behavior. We conclude that, compared with wild-type, dorsal CA1 pyramidal cells in GRov mice preferentially respond to center location rather than mobility in a novel open field. Such changes in the information encoded by individual hippocampal neurons in an aversive environment could underlie changes in stress vulnerability because of genetic or epigenetic variations in glucocorticoid receptor signaling.

Reduced excitatory neuron activity and interneuron-type-specific deficits in a mouse model of Alzheimer's disease

Alzheimer's disease (AD) is characterized by progressive memory loss and cognitive decline. These impairments correlate with early alterations in neuronal network activity in AD patients. Disruptions in the activity of individual neurons have been reported in mouse models of amyloidosis. However, the impact of amyloid pathology on the spontaneous activity of distinct neuronal types remains unexplored in vivo. Here we use in vivo calcium imaging with multiphoton microscopy to monitor and compare the activity of excitatory and two types of inhibitory interneurons in the cortices of APP/PS1 and control mice under isoflurane anesthesia. We also determine the relationship between amyloid accumulation and the deficits in spontaneous activity in APP/PS1 mice. We show that somatostatin-expressing (SOM) interneurons are hyperactive, while parvalbumin-expressing interneurons are hypoactive in APP/PS1 mice. Only SOM interneuron hyperactivity correlated with proximity to amyloid plaque. These inhibitory deficits were accompanied by decreased excitatory neuron activity in APP/PS1 mice. Our study identifies cell-specific neuronal firing deficits in APP/PS1 mice driven by amyloid pathology. These findings highlight the importance of addressing the complexity of neuron-specific deficits to ameliorate circuit dysfunction in Alzheimer's disease.

A deep learning framework for inference of single-trial neural population dynamics from calcium imaging with subframe temporal resolution

In many areas of the brain, neural populations act as a coordinated network whose state is tied to behavior on a millisecond timescale. Two-photon (2p) calcium imaging is a powerful tool to probe such network-scale phenomena. However, estimating the network state and dynamics from 2p measurements has proven challenging because of noise, inherent nonlinearities and limitations on temporal resolution. Here we describe Recurrent Autoencoder for Discovering Imaged Calcium Latents (RADICaL), a deep learning method to overcome these limitations at the population level. RADICaL extends methods that exploit dynamics in spiking activity for application to deconvolved calcium signals, whose statistics and temporal dynamics are quite distinct from electrophysiologically recorded spikes. It incorporates a new network training strategy that capitalizes on the timing of 2p sampling to recover network dynamics with high temporal precision. In synthetic tests, RADICaL infers the network state more accurately than previous methods, particularly for high-frequency components. In 2p recordings from sensorimotor areas in mice performing a forelimb reach task, RADICaL infers network state with close correspondence to single-trial variations in behavior and maintains high-quality inference even when neuronal populations are substantially reduced.

Neural circuit dynamics of drug-context associative learning in the mouse hippocampus

The environmental context associated with previous drug consumption is a potent trigger for drug relapse. However, the mechanism by which neural representations of context are modified to incorporate information associated with drugs of abuse remains unknown. Using longitudinal calcium imaging in freely behaving mice, we find that unlike the associative learning of natural reward, drug-context associations for psychostimulants and opioids are encoded in a specific subset of hippocampal neurons. After drug conditioning, these neurons weakened their spatial coding for the non-drug paired context, resulting in an orthogonal representation for the drug versus non-drug context that was predictive of drug-seeking behavior. Furthermore, these neurons were selected based on drug-spatial experience and were exclusively tuned to animals' allocentric position. Together, this work reveals how drugs of abuse alter the hippocampal circuit to encode drug-context associations and points to the possibility of targeting drug-associated memory in the hippocampus.

Neuronal signature of spatial decision-making during navigation by freely moving rats by using calcium imaging

A challenge in spatial memory is understanding how place cell firing contributes to decision-making in navigation. A spatial recency task was created in which freely moving rats first became familiar with a spatial context over several days and thereafter were required to encode and then selectively recall one of three specific locations within it that was chosen to be rewarded that day. Calcium imaging was used to record from more than 1,000 cells in area CA1 of the hippocampus of five rats during the exploration, sample, and choice phases of the daily task. The key finding was that neural activity in the startbox rose steadily in the short period prior to entry to the arena and that this selective population cell firing was predictive of the daily changing goal on correct trials but not on trials in which the animals made errors. Single-cell and population activity measures converged on the idea that prospective coding of neural activity can be involved in navigational decision-making.

Dose-dependent suppression of hippocampal contextual memory formation, place cells, and spatial engrams by the NMDAR antagonist (R)-CPP

We recently reported that the competitive NMDAR antagonist (R,S)-3-(2-carboxypiperazin-4-yl)-propyl-1-phosphonic acid (CPP) does not suppress NMDAR-mediated field EPSPs (fEPSPNMDA) or long-term potentiation (LTP) in vitro at concentrations that block contextual conditioning in vivo. Here we tested one possible explanation for the mismatch - that the hippocampus is relatively resistant to CPP compared to other brain structures engaged in contextual fear conditioning. Using the context pre-exposure facilitation effect (CPFE) paradigm to separate the hippocampal and extra-hippocampal components of contextual learning, we found that the active enantiomer (R)-CPP suppressed the hippocampal component with an IC50 of 3.1 mg/kg, a dose that produces brain concentrations below those required to block fEPSPNMDA or LTP. Moreover, using in-vivo calcium imaging of place cells and spatial engrams to directly assess hippocampal spatial coding, we found that (R)-CPP dose-dependently reduced the development of place cells and interfered with the formation of stable spatial engrams when it was administered prior to exposing mice to a novel context. Both effects occurred at doses that interfered with freezing to context in CPFE experiments. We conclude that (R)-CPP blocks memory formation by interfering with hippocampal function, but that it does so by modulating NMDARs at sites that are not engaged in vitro in the same manner that they are in vivo - perhaps through interneuron circuits that do not contribute to fEPSPs and are not required to elicit LTP using standard induction protocols in vitro, but are essential for successful mnemonic function in vivo.

A locus coeruleus-dorsal CA1 dopaminergic circuit modulates memory linking

Individual memories are often linked so that the recall of one triggers the recall of another. For example, contextual memories acquired close in time can be linked, and this is known to depend on a temporary increase in excitability that drives the overlap between dorsal CA1 (dCA1) hippocampal ensembles that encode the linked memories. Here, we show that locus coeruleus (LC) cells projecting to dCA1 have a key permissive role in contextual memory linking, without affecting contextual memory formation, and that this effect is mediated by dopamine. Additionally, we found that LC-to-dCA1-projecting neurons modulate the excitability of dCA1 neurons and the extent of overlap between dCA1 memory ensembles as well as the stability of coactivity patterns within these ensembles. This discovery of a neuromodulatory system that specifically affects memory linking without affecting memory formation reveals a fundamental separation between the brain mechanisms modulating these two distinct processes.

Innate frequency-discrimination hyperacuity in Williams-Beuren syndrome mice

Williams-Beuren syndrome (WBS) is a rare disorder caused by hemizygous microdeletion of ∼27 contiguous genes. Despite neurodevelopmental and cognitive deficits, individuals with WBS have spared or enhanced musical and auditory abilities, potentially offering an insight into the genetic basis of auditory perception. Here, we report that the mouse models of WBS have innately enhanced frequency-discrimination acuity and improved frequency coding in the auditory cortex (ACx). Chemogenetic rescue showed frequency-discrimination hyperacuity is caused by hyperexcitable interneurons in the ACx. Haploinsufficiency of one WBS gene, Gtf2ird1, replicated WBS phenotypes by downregulating the neuropeptide receptor VIPR1. VIPR1 is reduced in the ACx of individuals with WBS and in the cerebral organoids derived from human induced pluripotent stem cells with the WBS microdeletion. Vipr1 deletion or overexpression in ACx interneurons mimicked or reversed, respectively, the cellular and behavioral phenotypes of WBS mice. Thus, the Gtf2ird1-Vipr1 mechanism in ACx interneurons may underlie the superior auditory acuity in WBS.

Review on data analysis methods for mesoscale neural imaging in vivo

Significance: Mesoscale neural imaging in vivo has gained extreme popularity in neuroscience for its capacity of recording large-scale neurons in action. Optical imaging with single-cell resolution and millimeter-level field of view in vivo has been providing an accumulated database of neuron-behavior correspondence. Meanwhile, optical detection of neuron signals is easily contaminated by noises, background, crosstalk, and motion artifacts, while neural-level signal processing and network-level coordinate are extremely complicated, leading to laborious and challenging signal processing demands. The existing data analysis procedure remains unstandardized, which could be daunting to neophytes or neuroscientists without computational background. Aim: We hope to provide a general data analysis pipeline of mesoscale neural imaging shared between imaging modalities and systems. Approach: We divide the pipeline into two main stages. The first stage focuses on extracting high-fidelity neural responses at single-cell level from raw images, including motion registration, image denoising, neuron segmentation, and signal extraction. The second stage focuses on data mining, including neural functional mapping, clustering, and brain-wide network deduction. Results: Here, we introduce the general pipeline of processing the mesoscale neural images. We explain the principles of these procedures and compare different approaches and their application scopes with detailed discussions about the shortcomings and remaining challenges. Conclusions: There are great challenges and opportunities brought by the large-scale mesoscale data, such as the balance between fidelity and efficiency, increasing computational load, and neural network interpretability. We believe that global circuits on single-neuron level will be more extensively explored in the future.

Neural Decoding of Visual Information Across Different Neural Recording Modalities and Approaches

Vision plays a peculiar role in intelligence. Visual information, forming a large part of the sensory information, is fed into the human brain to formulate various types of cognition and behaviours that make humans become intelligent agents. Recent advances have led to the development of brain-inspired algorithms and models for machine vision. One of the key components of these methods is the utilization of the computational principles underlying biological neurons. Additionally, advanced experimental neuroscience techniques have generated different types of neural signals that carry essential visual information. Thus, there is a high demand for mapping out functional models for reading out visual information from neural signals. Here, we briefly review recent progress on this issue with a focus on how machine learning techniques can help in the development of models for contending various types of neural signals, from fine-scale neural spikes and single-cell calcium imaging to coarse-scale electroencephalography (EEG) and functional magnetic resonance imaging recordings of brain signals.

Review of data processing of functional optical microscopy for neuroscience

Functional optical imaging in neuroscience is rapidly growing with the development of optical systems and fluorescence indicators. To realize the potential of these massive spatiotemporal datasets for relating neuronal activity to behavior and stimuli and uncovering local circuits in the brain, accurate automated processing is increasingly essential. We cover recent computational developments in the full data processing pipeline of functional optical microscopy for neuroscience data and discuss ongoing and emerging challenges.

Task specificity in mouse parietal cortex

Parietal cortex is implicated in a variety of behavioral processes, but it is unknown whether and how its individual neurons participate in multiple tasks. We trained head-fixed mice to perform two visual decision tasks involving a steering wheel or a virtual T-maze and recorded from the same parietal neurons during these two tasks. Neurons that were active during the T-maze task were typically inactive during the steering-wheel task and vice versa. Recording from the same neurons in the same apparatus without task stimuli yielded the same specificity as in the task, suggesting that task specificity depends on physical context. To confirm this, we trained some mice in a third task combining the steering wheel context with the visual environment of the T-maze. This hybrid task engaged the same neurons as those engaged in the steering-wheel task. Thus, participation by neurons in mouse parietal cortex is task specific, and this specificity is determined by physical context.

Neural signatures of auditory hypersensitivity following acoustic trauma

Neurons in sensory cortex exhibit a remarkable capacity to maintain stable firing rates despite large fluctuations in afferent activity levels. However, sudden peripheral deafferentation in adulthood can trigger an excessive, non-homeostatic cortical compensatory response that may underlie perceptual disorders including sensory hypersensitivity, phantom limb pain, and tinnitus. Here, we show that mice with noise-induced damage of the high-frequency cochlear base were behaviorally hypersensitive to spared mid-frequency tones and to direct optogenetic stimulation of auditory thalamocortical neurons. Chronic two-photon calcium imaging from ACtx pyramidal neurons (PyrNs) revealed an initial stage of spatially diffuse hyperactivity, hyper-correlation, and auditory hyperresponsivity that consolidated around deafferented map regions three or more days after acoustic trauma. Deafferented PyrN ensembles also displayed hypersensitive decoding of spared mid-frequency tones that mirrored behavioral hypersensitivity, suggesting that non-homeostatic regulation of cortical sound intensity coding following sensorineural loss may be an underlying source of auditory hypersensitivity. Excess cortical response gain after acoustic trauma was expressed heterogeneously among individual PyrNs, yet 40% of this variability could be accounted for by each cell's baseline response properties prior to acoustic trauma. PyrNs with initially high spontaneous activity and gradual monotonic intensity growth functions were more likely to exhibit non-homeostatic excess gain after acoustic trauma. This suggests that while cortical gain changes are triggered by reduced bottom-up afferent input, their subsequent stabilization is also shaped by their local circuit milieu, where indicators of reduced inhibition can presage pathological hyperactivity following sensorineural hearing loss.

The spatial scale of somatostatin subnetworks increases from sensory to association cortex

Incoming signals interact with rich, ongoing population activity dynamics in cortical circuits. These intrinsic dynamics are the consequence of interactions among local excitatory and inhibitory neurons and affect inter-region communication and information coding. It is unclear whether specializations in the patterns of interactions among excitatory and inhibitory neurons underlie systematic differences in activity dynamics across the cortex. Here, in mice, we compare the functional interactions among somatostatin (SOM)-expressing inhibitory interneurons and the rest of the neural population in auditory cortex (AC), a sensory region of the cortex, and posterior parietal cortex (PPC), an association region. The spatial structure of shared variability among SOM and non-SOM neurons differs across regions: correlations decay rapidly with distance in AC but not in PPC. However, in both regions, activity of SOM neurons is more highly correlated than non-SOM neurons' activity. Our results imply both generalization and specialization in the functional structure of inhibitory subnetworks across the cortex.

Testing for a Change in Mean After Changepoint Detection

While many methods are available to detect structural changes in a time series, few procedures are available to quantify the uncertainty of these estimates post-detection. In this work, we fill this gap by proposing a new framework to test the null hypothesis that there is no change in mean around an estimated changepoint. We further show that it is possible to efficiently carry out this framework in the case of changepoints estimated by binary segmentation and its variants, ℓ 0 segmentation, or the fused lasso. Our setup allows us to condition on much less information than existing approaches, which yields higher powered tests. We apply our proposals in a simulation study and on a dataset of chromosomal guanine-cytosine content. These approaches are freely available in the R package ChangepointInference at https://jewellsean.github.io/changepoint-inference/.

Correcting motion induced fluorescence artifacts in two-channel neural imaging

Imaging neural activity in a behaving animal presents unique challenges in part because motion from an animal's movement creates artifacts in fluorescence intensity time-series that are difficult to distinguish from neural signals of interest. One approach to mitigating these artifacts is to image two channels simultaneously: one that captures an activity-dependent fluorophore, such as GCaMP, and another that captures an activity-independent fluorophore such as RFP. Because the activity-independent channel contains the same motion artifacts as the activity-dependent channel, but no neural signals, the two together can be used to identify and remove the artifacts. However, existing approaches for this correction, such as taking the ratio of the two channels, do not account for channel-independent noise in the measured fluorescence. Here, we present Two-channel Motion Artifact Correction (TMAC), a method which seeks to remove artifacts by specifying a generative model of the two channel fluorescence that incorporates motion artifact, neural activity, and noise. We use Bayesian inference to infer latent neural activity under this model, thus reducing the motion artifact present in the measured fluorescence traces. We further present a novel method for evaluating ground-truth performance of motion correction algorithms by comparing the decodability of behavior from two types of neural recordings; a recording that had both an activity-dependent fluorophore and an activity-independent fluorophore (GCaMP and RFP) and a recording where both fluorophores were activity-independent (GFP and RFP). A successful motion correction method should decode behavior from the first type of recording, but not the second. We use this metric to systematically compare five models for removing motion artifacts from fluorescent time traces. We decode locomotion from a GCaMP expressing animal 20x more accurately on average than from control when using TMAC inferred activity and outperforms all other methods of motion correction tested, the best of which were ~8x more accurate than control.

Single-cell activity and network properties of dorsal raphe nucleus serotonin neurons during emotionally salient behaviors

The serotonin system modulates a wide variety of emotional behaviors and states, including reward processing, anxiety, and social interaction. To reveal the underlying patterns of neural activity, we visualized serotonergic neurons in the dorsal raphe nucleus (DRN5-HT) of mice using miniaturized microscopy during diverse emotional behaviors. We discovered ensembles of cells with highly correlated activity and found that DRN5-HT neurons are preferentially recruited by emotionally salient stimuli as opposed to neutral stimuli. Individual DRN5-HT neurons responded to diverse combinations of salient stimuli, with some preference for valence and sensory modality. Anatomically defined subpopulations projecting to either a reward-related structure (the ventral tegmental area) or an anxiety-related structure (the bed nucleus of the stria terminalis) contained all response types but were enriched in reward- and anxiety-responsive cells, respectively. Our results suggest that the DRN serotonin system responds to emotional salience using ensembles with mixed selectivity and biases in downstream connectivity.

A molecularly defined D1 medium spiny neuron subtype negatively regulates cocaine addiction

The striatum plays a critical role in regulating addiction-related behaviors. The conventional dichotomy model suggests that striatal D1/D2 medium spiny neurons (MSNs) positively/negatively regulate addiction-related behaviors. However, this model does not account for the neuronal heterogeneity and functional diversity of the striatum, and whether MSN subtypes beyond the pan-D1/D2 populations play distinct roles in drug addiction remains unknown. We characterized the role of a tachykinin 2-expressing D1 MSN subtype (Tac2+), present in both rodent and primate striatum, using cocaine addiction mouse models. We found that acute cocaine administration reduces Tac2 neuronal activity, and cocaine conditioning alters neuronal response related to cocaine reward contextual associations. In addition, activation/inhibition of Tac2+ neurons attenuates/promotes cocaine-induced conditioned place preference and cocaine intravenous self-administration. Furthermore, stimulation of the NAc-to-lateral hypothalamic projection of Tac2+ neurons suppresses cocaine reward behavior. Our study reveals an unconventional negative regulatory function of D1 MSNs in drug addiction that operates in a subtype- and projection-specific manner.

Control of non-REM sleep by ventrolateral medulla glutamatergic neurons projecting to the preoptic area

Understanding the neural mechanisms underlying sleep state transitions is a fundamental goal of neurobiology and important for the development of new treatments for insomnia and other sleep disorders. Yet, brain circuits controlling this process remain poorly understood. Here we identify a population of sleep-active glutamatergic neurons in the ventrolateral medulla (VLM) that project to the preoptic area (POA), a prominent sleep-promoting region, in mice. Microendoscopic calcium imaging demonstrate that these VLM glutamatergic neurons display increased activity during the transitions from wakefulness to Non-Rapid Eye Movement (NREM) sleep. Chemogenetic silencing of POA-projecting VLM neurons suppresses NREM sleep, whereas chemogenetic activation of these neurons promotes NREM sleep. Moreover, we show that optogenetic activation of VLM glutamatergic neurons or their projections in the POA initiates NREM sleep in awake mice. Together, our findings uncover an excitatory brainstem-hypothalamic circuit that controls the wake-sleep transitions.

SmaRT2P: a software for generating and processing smart line recording trajectories for population two-photon calcium imaging

Two-photon fluorescence calcium imaging allows recording the activity of large neural populations with subcellular spatial resolution, but it is typically characterized by low signal-to-noise ratio (SNR) and poor accuracy in detecting single or few action potentials when large number of neurons are imaged. We recently showed that implementing a smart line scanning approach using trajectories that optimally sample the regions of interest increases both the SNR fluorescence signals and the accuracy of single spike detection in population imaging in vivo. However, smart line scanning requires highly specialised software to design recording trajectories, interface with acquisition hardware, and efficiently process acquired data. Furthermore, smart line scanning needs optimized strategies to cope with movement artefacts and neuropil contamination. Here, we develop and validate SmaRT2P, an open-source, user-friendly and easy-to-interface Matlab-based software environment to perform optimized smart line scanning in two-photon calcium imaging experiments. SmaRT2P is designed to interface with popular acquisition software (e.g., ScanImage) and implements novel strategies to detect motion artefacts, estimate neuropil contamination, and minimize their impact on functional signals extracted from neuronal population imaging. SmaRT2P is structured in a modular way to allow flexibility in the processing pipeline, requiring minimal user intervention in parameter setting. The use of SmaRT2P for smart line scanning has the potential to facilitate the functional investigation of large neuronal populations with increased SNR and accuracy in detecting the discharge of single and few action potentials.

Shared and specialized coding across posterior cortical areas for dynamic navigation decisions

Animals adaptively integrate sensation, planning, and action to navigate toward goal locations in ever-changing environments, but the functional organization of cortex supporting these processes remains unclear. We characterized encoding in approximately 90,000 neurons across the mouse posterior cortex during a virtual navigation task with rule switching. The encoding of task and behavioral variables was highly distributed across cortical areas but differed in magnitude, resulting in three spatial gradients for visual cue, spatial position plus dynamics of choice formation, and locomotion, with peaks respectively in visual, retrosplenial, and parietal cortices. Surprisingly, the conjunctive encoding of these variables in single neurons was similar throughout the posterior cortex, creating high-dimensional representations in all areas instead of revealing computations specialized for each area. We propose that, for guiding navigation decisions, the posterior cortex operates in parallel rather than hierarchically, and collectively generates a state representation of the behavior and environment, with each area specialized in handling distinct information modalities.

Ca2+ imaging of self and other in medial prefrontal cortex during social dominance interactions in a tube test

The study of social dominance interactions between animals offers a window onto the decision-making involved in establishing dominance hierarchies and an opportunity to examine changes in social behavior observed in certain neurogenetic disorders. Competitive social interactions, such as in the widely used tube test, reflect this decision-making. Previous studies have focused on the different patterns of behavior seen in the dominant and submissive animal, neural correlates of effortful behavior believed to mediate the outcome of such encounters, and interbrain correlations of neural activity. Using a rigorous mutual information criterion, we now report that neural responses recorded with endoscopic calcium imaging in the prelimbic zone of the medial prefrontal cortex show unique correlations to specific dominance-related behaviors. Interanimal analyses revealed cell/behavior correlations that are primarily with an animal's own behavior or with the other animal's behavior, or the coincident behavior of both animals (such as pushing by one and resisting by the other). The comparison of unique and coincident cells helps to disentangle cell firing that reflects an animal's own or the other's specific behavior from situations reflecting conjoint action. These correlates point to a more cognitive rather than a solely behavioral dimension of social interactions that needs to be considered in the design of neurobiological studies of social behavior. These could prove useful in studies of disorders affecting social recognition and social engagement, and the treatment of disorders of social interaction.

Transformations of neural representations in a social behaviour network

Mating and aggression are innate social behaviours that are controlled by subcortical circuits in the extended amygdala and hypothalamus1-4. The bed nucleus of the stria terminalis (BNSTpr) is a node that receives input encoding sex-specific olfactory cues from the medial amygdala5,6, and which in turn projects to hypothalamic nuclei that control mating7-9 (medial preoptic area (MPOA)) and aggression9-14 (ventromedial hypothalamus, ventrolateral subdivision (VMHvl)), respectively15. Previous studies have demonstrated that male aromatase-positive BNSTpr neurons are required for mounting and attack, and may identify conspecific sex according to their overall level of activity16. However, neural representations in BNSTpr, their function and their transformations in the hypothalamus have not been characterized. Here we performed calcium imaging17,18 of male BNSTprEsr1 neurons during social behaviours. We identify distinct populations of female- versus male-tuned neurons in BNSTpr, with the former outnumbering the latter by around two to one, similar to the medial amygdala and MPOA but opposite to VMHvl, in which male-tuned neurons predominate6,9,19. Chemogenetic silencing of BNSTprEsr1 neurons while imaging MPOAEsr1 or VMHvlEsr1 neurons in behaving animals showed, unexpectedly, that the male-dominant sex-tuning bias in VMHvl was inverted to female-dominant whereas a switch from sniff- to mount-selective neurons during mating was attenuated in MPOA. Our data also indicate that BNSTprEsr1 neurons are not essential for conspecific sex identification. Rather, they control the transition from appetitive to consummatory phases of male social behaviours by shaping sex- and behaviour-specific neural representations in the hypothalamus.

Aberrant neural activity in prefrontal pyramidal neurons lacking TDP-43 precedes neuron loss

Mislocalization of TAR DNA binding protein 43 kDa (TARDBP, or TDP-43) is a principal pathological hallmark identified in cases of neurodegenerative disorders such as amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD). As an RNA binding protein, TDP-43 serves in the nuclear compartment to repress non-conserved cryptic exons to ensure the normal transcriptome. Multiple lines of evidence from animal models and human studies support the view that loss of TDP-43 leads to neuron loss, independent of its cytosolic aggregation. However, the underlying pathogenic pathways driven by the loss-of-function mechanism are still poorly defined. We employed a genetic approach to determine the impact of TDP-43 loss in pyramidal neurons of the prefrontal cortex (PFC). Using a custom-built miniscope imaging system, we performed repetitive in vivo calcium imaging from freely behaving mice for up to 7 months. By comparing calcium activity in PFC pyramidal neurons between TDP-43 depleted and TDP-43 intact mice, we demonstrated remarkably increased numbers of pyramidal neurons exhibiting hyperactive calcium activity after short-term TDP-43 depletion, followed by rapid activity declines prior to neuron loss. Our results suggest aberrant neural activity driven by loss of TDP-43 as the pathogenic pathway at early stage in ALS and FTD.

Real-time visualization of mRNA synthesis during memory formation in live mice

Arc is one of the genes that are rapidly transcribed by neuronal activity and thus used as a marker for memory trace or engram cells. However, the dynamics of engram cell populations is not well-known because of the difficulty in monitoring the rapid and transient gene expression in live animals. Using a mouse model in which endogenous Arc messenger RNA (mRNA) is fluorescently labeled, we demonstrate that Arc-expressing neuronal populations have distinct dynamics in different brain regions and that only a small subpopulation that consistently expresses Arc during both memory encoding and retrieval exhibits context-specific calcium activity. This live-animal RNA-imaging technique will offer a powerful tool for connecting gene expression to neuronal activity patterns and to behavior.

Memories are thought to be encoded in populations of neurons called memory trace or engram cells. However, little is known about the dynamics of these cells because of the difficulty in real-time monitoring of them over long periods of time in vivo. To overcome this limitation, we present a genetically encoded RNA indicator (GERI) mouse for intravital chronic imaging of endogenous Arc messenger RNA (mRNA)—a popular marker for memory trace cells. We used our GERI to identify Arc-positive neurons in real time without the delay associated with reporter protein expression in conventional approaches. We found that the Arc-positive neuronal populations rapidly turned over within 2 d in the hippocampal CA1 region, whereas ∼4% of neurons in the retrosplenial cortex consistently expressed Arc following contextual fear conditioning and repeated memory retrievals. Dual imaging of GERI and a calcium indicator in CA1 of mice navigating a virtual reality environment revealed that only the population of neurons expressing Arc during both encoding and retrieval exhibited relatively high calcium activity in a context-specific manner. This in vivo RNA-imaging approach opens the possibility of unraveling the dynamics of the neuronal population underlying various learning and memory processes.

Long-term transverse imaging of the hippocampus with glass microperiscopes

The hippocampus consists of a stereotyped neuronal circuit repeated along the septal-temporal axis. This transverse circuit contains distinct subfields with stereotyped connectivity that support crucial cognitive processes, including episodic and spatial memory. However, comprehensive measurements across the transverse hippocampal circuit in vivo are intractable with existing techniques. Here, we developed an approach for two-photon imaging of the transverse hippocampal plane in awake mice via implanted glass microperiscopes, allowing optical access to the major hippocampal subfields and to the dendritic arbor of pyramidal neurons. Using this approach, we tracked dendritic morphological dynamics on CA1 apical dendrites and characterized spine turnover. We then used calcium imaging to quantify the prevalence of place and speed cells across subfields. Finally, we measured the anatomical distribution of spatial information, finding a non-uniform distribution of spatial selectivity along the DG-to-CA1 axis. This approach extends the existing toolbox for structural and functional measurements of hippocampal circuitry.

Toward an integrative neurovascular framework for studying brain networks

Brain functional connectivity based on the measure of blood oxygen level-dependent (BOLD) functional magnetic resonance imaging (fMRI) signals has become one of the most widely used measurements in human neuroimaging. However, the nature of the functional networks revealed by BOLD fMRI can be ambiguous, as highlighted by a recent series of experiments that have suggested that typical resting-state networks can be replicated from purely vascular or physiologically driven BOLD signals. After going through a brief review of the key concepts of brain network analysis, we explore how the vascular and neuronal systems interact to give rise to the brain functional networks measured with BOLD fMRI. This leads us to emphasize a view of the vascular network not only as a confounding element in fMRI but also as a functionally relevant system that is entangled with the neuronal network. To study the vascular and neuronal underpinnings of BOLD functional connectivity, we consider a combination of methodological avenues based on multiscale and multimodal optical imaging in mice, used in combination with computational models that allow the integration of vascular information to explain functional connectivity.

An Open-Source Real-Time Motion Correction Plug-In for Single-Photon Calcium Imaging of Head-Mounted Microscopy

Single-photon-based head-mounted microscopy is widely used to record the brain activities of freely-moving animals. However, during data acquisition, the free movement of animals will cause shaking in the field of view, which deteriorates subsequent neural signal analyses. Existing motion correction methods applied to calcium imaging data either focus on offline analyses or lack sufficient accuracy in real-time processing for single-photon data. In this study, we proposed an open-source real-time motion correction (RTMC) plug-in for single-photon calcium imaging data acquisition. The RTMC plug-in is a real-time subpixel registration algorithm that can run GPUs in UCLA Miniscope data acquisition software. When used with the UCLA Miniscope, the RTMC algorithm satisfies real-time processing requirements in terms of speed, memory, and accuracy. We tested the RTMC algorithm by extending a manual neuron labeling function to extract calcium signals in a real experimental setting. The results demonstrated that the neural calcium dynamics and calcium events can be restored with high accuracy from the calcium data that were collected by the UCLA Miniscope system embedded with our RTMC plug-in. Our method could become an essential component in brain science research, where real-time brain activity is needed for closed-loop experiments.

Cognitive experience alters cortical involvement in goal-directed navigation

Neural activity in the mammalian cortex has been studied extensively during decision tasks, and recent work aims to identify under what conditions cortex is actually necessary for these tasks. We discovered that mice with distinct cognitive experiences, beyond sensory and motor learning, use different cortical areas and neural activity patterns to solve the same navigation decision task, revealing past learning as a critical determinant of whether cortex is necessary for goal-directed navigation. We used optogenetics and calcium imaging to study the necessity and neural activity of multiple cortical areas in mice with different training histories. Posterior parietal cortex and retrosplenial cortex were mostly dispensable for accurate performance of a simple navigation task. In contrast, these areas were essential for the same simple task when mice were previously trained on complex tasks with delay periods or association switches. Multiarea calcium imaging showed that, in mice with complex-task experience, single-neuron activity had higher selectivity and neuron–neuron correlations were weaker, leading to codes with higher task information. Therefore, past experience is a key factor in determining whether cortical areas have a causal role in goal-directed navigation.

GABAergic CA1 neurons are more stable following context changes than glutamatergic cells

The CA1 region of the hippocampus contains both glutamatergic pyramidal cells and GABAergic interneurons. Numerous reports have characterized glutamatergic CAMK2A cell activity, showing how these cells respond to environmental changes such as local cue rotation and context re-sizing. Additionally, the long-term stability of spatial encoding and turnover of these cells across days is also well-characterized. In contrast, these classic hippocampal experiments have never been conducted with CA1 GABAergic cells. Here, we use chronic calcium imaging of male and female mice to compare the neural activity of VGAT and CAMK2A cells during exploration of unaltered environments and also during exposure to contexts before and after rotating and changing the length of the context across multiple recording days. Intriguingly, compared to CAMK2A cells, VGAT cells showed decreased remapping induced by environmental changes, such as context rotations and contextual length resizing. However, GABAergic neurons were also less likely than glutamatergic neurons to remain active and exhibit consistent place coding across recording days. Interestingly, despite showing significant spatial remapping across days, GABAergic cells had stable speed encoding between days. Thus, compared to glutamatergic cells, spatial encoding of GABAergic cells is more stable during within-session environmental perturbations, but is less stable across days. These insights may be crucial in accurately modeling the features and constraints of hippocampal dynamics in spatial coding.

Signatures of rapid plasticity in hippocampal CA1 representations during novel experiences

Neurons in the hippocampus exhibit a striking selectivity for specific combinations of sensory features, forming representations that are thought to subserve episodic memory. Even during completely novel experiences, hippocampal "place cells" are rapidly configured such that the population sparsely encodes visited locations, stabilizing within minutes of the first exposure to a new environment. What mechanisms enable this fast encoding of experience? Using virtual reality and neural population recordings in mice, we dissected the effects of novelty and experience on the dynamics of place field formation. During place field formation, many CA1 neurons immediately modulated the amplitude of their activity and shifted the location of their field, rapid changes in tuning predicted by behavioral timescale synaptic plasticity (BTSP). Signatures of BTSP were particularly enriched during the exploration of a novel context and decayed with experience. Our data suggest that novelty modulates the effective learning rate in CA1, favoring rapid mechanisms of field formation to encode a new experience.

An in vitro model of neuronal ensembles

Advances in 3D neuronal cultures, such as brain spheroids and organoids, are allowing unprecedented in vitro access to some of the molecular, cellular and developmental mechanisms underlying brain diseases. However, their efficacy in recapitulating brain network properties that encode brain function remains limited, thereby precluding development of effective in vitro models of complex brain disorders like schizophrenia. Here, we develop and characterize a Modular Neuronal Network (MoNNet) approach that recapitulates specific features of neuronal ensemble dynamics, segregated local-global network activities and a hierarchical modular organization. We utilized MoNNets for quantitative in vitro modelling of schizophrenia-related network dysfunctions caused by highly penetrant mutations in SETD1A and 22q11.2 risk loci. Furthermore, we demonstrate its utility for drug discovery by performing pharmacological rescue of alterations in neuronal ensembles stability and global network synchrony. MoNNets allow in vitro modelling of brain diseases for investigating the underlying neuronal network mechanisms and systematic drug discovery.

Minian an open-source miniscope analysis pipeline

Miniature microscopes have gained considerable traction for in vivo calcium imaging in freely behaving animals. However, extracting calcium signals from raw videos is a computationally complex problem and remains a bottleneck for many researchers utilizing single-photon in vivo calcium imaging. Despite the existence of many powerful analysis packages designed to detect and extract calcium dynamics, most have either key parameters that are hard-coded or insufficient step-by-step guidance and validations to help the users choose the best parameters. This makes it difficult to know whether the output is reliable and meets the assumptions necessary for proper analysis. Moreover, large memory demand is often a constraint for setting up these pipelines since it limits the choice of hardware to specialized computers. Given these difficulties, there is a need for a low memory demand, user-friendly tool offering interactive visualizations of how altering parameters at each step of the analysis affects data output. Our open-source analysis pipeline, Minian (Miniscope Analysis), facilitates the transparency and accessibility of single-photon calcium imaging analysis, permitting users with little computational experience to extract the location of cells and their corresponding calcium traces and deconvolved neural activities. Minian contains interactive visualization tools for every step of the analysis, as well as detailed documentation and tips on parameter exploration. Furthermore, Minian has relatively small memory demands and can be run on a laptop, making it available to labs that do not have access to specialized computational hardware. Minian has been validated to reliably and robustly extract calcium events across different brain regions and from different cell types. In practice, Minian provides an open-source calcium imaging analysis pipeline with user-friendly interactive visualizations to explore parameters and validate results.

CCR5 closes the temporal window for memory linking

Real-world memories are formed in a particular context and are often not acquired or recalled in isolation1-5. Time is a key variable in the organization of memories, as events that are experienced close in time are more likely to be meaningfully associated, whereas those that are experienced with a longer interval are not1-4. How the brain segregates events that are temporally distinct is unclear. Here we show that a delayed (12-24 h) increase in the expression of C-C chemokine receptor type 5 (CCR5)-an immune receptor that is well known as a co-receptor for HIV infection6,7-after the formation of a contextual memory determines the duration of the temporal window for associating or linking that memory with subsequent memories. This delayed expression of CCR5 in mouse dorsal CA1 neurons results in a decrease in neuronal excitability, which in turn negatively regulates neuronal memory allocation, thus reducing the overlap between dorsal CA1 memory ensembles. Lowering this overlap affects the ability of one memory to trigger the recall of the other, and therefore closes the temporal window for memory linking. Our findings also show that an age-related increase in the neuronal expression of CCR5 and its ligand CCL5 leads to impairments in memory linking in aged mice, which could be reversed with a Ccr5 knockout and a drug approved by the US Food and Drug Administration (FDA) that inhibits this receptor, a result with clinical implications. Altogether, the findings reported here provide insights into the molecular and cellular mechanisms that shape the temporal window for memory linking.

Evaluation of Recombinant Botulinum Neurotoxin Type A1 Efficacy in Peripheral Inflammatory Pain in Mice

Well-established efficacy of botulinum neurotoxin type A (BoNT/A) in aesthetic dermatology and neuromuscular hyperactivity disorders relies on canonical interruption of acetylcholine neurotransmission at the neuromuscular junction at the site of the injection. The mechanisms and the site of activity of BoNT/A in pain, on the other hand, remain elusive. Here, we explored analgesic activity of recombinant BoNT/A1 (rBoNT/A1; IPN10260) in a mouse model of inflammatory pain to investigate the potential role of peripheral sensory afferents in this activity. After confirming analgesic efficacy of rBoNT/A1 on CFA-induced mechanical hypersensitivity in C57Bl6J mice, we used GCaMP6s to perform in vivo calcium imaging in the ipsilateral dorsal root ganglion (DRG) neurons in rBoNT/A1 vs. vehicle-treated mice at baseline and following administration of a range of mechanical and thermal stimuli. Additionally, immunohisochemical studies were performed to detect cleaved SNAP25 in the skin, DRGs and the spinal cord. Injection of CFA resulted in reduced mechanical sensitivity threshold and increased calcium fluctuations in the DRG neurons. While rBoNT/A1 reduced mechanical hypersensitivity, calcium fluctuations in the DRG of rBoNT/A1- and vehicle-treated animals were similar. Cleaved SNAP25 was largely absent in the skin and the DRG but present in the lumbar spinal cord of rBoNT/A1-treated animals. Taken together, rBoNT/A1 ameliorates mechanical hypersensitivity related to inflammation, while the signal transmission from the peripheral sensory afferents to the DRG remained unchanged. This strengthens the possibility that spinal, rather than peripheral, mechanisms play a role in the mediation of analgesic efficacy of BoNT/A in inflammatory pain.