PatchWarp: Corrections of non-uniform image distortions in two-photon calcium imaging data by patchwork affine transformations

A comprehensive suite for extracting neuron signals across multiple sessions in one-photon calcium imaging

We developed CaliAli, a comprehensive suite designed to extract neuronal signals from one-photon calcium imaging data collected across multiple sessions in free-moving conditions in mice. CaliAli incorporates information from blood vessels and neurons to correct inter-session misalignments, making it robust against non-rigid brain deformations even after substantial changes in the field of view across sessions. This also makes CaliAli robust against high neuron overlap and changes in active neuron population across sessions. CaliAli performs computationally efficient signal extraction from concatenated video sessions that enhances the detectability of weak calcium signals. Notably, CaliAli enhanced the spatial coding accuracy of extracted hippocampal CA1 neuron activity across sessions. An optogenetic tagging experiment showed that CaliAli enhanced neuronal trackability in the dentate gyrus across a time scale of weeks. Finally, dentate gyrus neurons tracked using CaliAli exhibited stable population activity for 99 days. Overall, CaliAli advances our capacity to understand the activity dynamics of neuronal ensembles over time, which is crucial for deciphering the complex neuronal substrates of natural animal behaviors.

Long-term optical imaging of the spinal cord in awake behaving mice

Advances in optical imaging and fluorescent biosensors enable study of the spatiotemporal and long-term neural dynamics in the brain of awake animals. However, methodological difficulties and fibrosis limit similar advances in the spinal cord. Here, to overcome these obstacles, we combined in vivo application of fluoropolymer membranes that inhibit fibrosis, a redesigned implantable spinal imaging chamber and improved motion correction methods that together permit imaging of the spinal cord in awake behaving mice, for months to over a year. We demonstrated a robust ability to monitor axons, identified a spinal cord somatotopic map, performed months-long imaging in freely moving mice, conducted Ca2+ imaging of neural dynamics in behaving mice responding to pain-provoking stimuli and observed persistent microglial changes after nerve injury. The ability to couple in vivo imaging and behavior at the spinal cord level will drive insights not previously possible at a key location for somatosensory transmission to the brain.

Simultaneous removal of noise and correction of motion warping in neuron calcium imaging using a pipeline structure of self-supervised deep learning models

Calcium imaging is susceptible to motion distortions and background noises, particularly for monitoring active animals under low-dose laser irradiation, and hence unavoidably hinder the critical analysis of neural functions. Current research efforts tend to focus on either denoising or dewarping and do not provide effective methods for videos distorted by both noises and motion artifacts simultaneously. We found that when a self-supervised denoising model of DeepCAD [Nat. Methods18, 1359 (2021)10.1038/s41592-021-01225-0] is used on the calcium imaging contaminated by noise and motion warping, it can remove the motion artifacts effectively but with regenerated noises. To address this issue, we develop a two-level deep-learning (DL) pipeline to dewarp and denoise the calcium imaging video sequentially. The pipeline consists of two 3D self-supervised DL models that do not require warp-free and high signal-to-noise ratio (SNR) observations for network optimization. Specifically, a high-frequency enhancement block is presented in the denoising network to restore more structure information in the denoising process; a hierarchical perception module and a multi-scale attention module are designed in the dewarping network to tackle distortions of various sizes. Experiments conducted on seven videos from two-photon and confocal imaging systems demonstrate that our two-level DL pipeline can restore high-clarity neuron images distorted by both motion warping and background noises. Compared to typical DeepCAD, our denoising model achieves a significant improvement of approximately 30% in image resolution and up to 28% in signal-to-noise ratio; compared to traditional dewarping and denoising methods, our proposed pipeline network recovers more neurons, enhancing signal fidelity and improving data correlation among frames by 35% and 60% respectively. This work may provide an attractive method for long-term neural activity monitoring in awake animals and also facilitate functional analysis of neural circuits.

Meta-reinforcement learning via orbitofrontal cortex

The meta-reinforcement learning (meta-RL) framework, which involves RL over multiple timescales, has been successful in training deep RL models that generalize to new environments. It has been hypothesized that the prefrontal cortex may mediate meta-RL in the brain, but the evidence is scarce. Here we show that the orbitofrontal cortex (OFC) mediates meta-RL. We trained mice and deep RL models on a probabilistic reversal learning task across sessions during which they improved their trial-by-trial RL policy through meta-learning. Ca2+/calmodulin-dependent protein kinase II-dependent synaptic plasticity in OFC was necessary for this meta-learning but not for the within-session trial-by-trial RL in experts. After meta-learning, OFC activity robustly encoded value signals, and OFC inactivation impaired the RL behaviors. Longitudinal tracking of OFC activity revealed that meta-learning gradually shapes population value coding to guide the ongoing behavioral policy. Our results indicate that two distinct RL algorithms with distinct neural mechanisms and timescales coexist in OFC to support adaptive decision-making.

Exponential history integration with diverse temporal scales in retrosplenial cortex supports hyperbolic behavior

Animals use past experience to guide future choices. The integration of experiences typically follows a hyperbolic, rather than exponential, decay pattern with a heavy tail for distant history. Hyperbolic integration affords sensitivity to both recent environmental dynamics and long-term trends. However, it is unknown how the brain implements hyperbolic integration. We found that mouse behavior in a foraging task showed hyperbolic decay of past experience, but the activity of cortical neurons showed exponential decay. We resolved this apparent mismatch by observing that cortical neurons encode history information with heterogeneous exponential time constants that vary across neurons. A model combining these diverse timescales recreated the heavy-tailed, hyperbolic history integration observed in behavior. In particular, the time constants of retrosplenial cortex (RSC) neurons best matched the behavior, and optogenetic inactivation of RSC uniquely reduced behavioral history dependence. These results indicate that behavior-relevant history information is maintained across multiple timescales in parallel and that RSC is a critical reservoir of information guiding decision-making.

Recurrent activity within microcircuits of macaque dorsolateral prefrontal cortex tracks cognitive flexibility

Human and non-human primate data clearly implicate the dorsolateral prefrontal cortex (dlPFC) as critical for advanced cognitive functions 1,2 . It is thought that intracortical synaptic architectures within dlPFC are the integral neurobiological substrate that gives rise to these processes, including working memory, inferential reasoning, and decision-making 3-7 . In the prevailing model, each cortical column makes up one fundamental processing unit composed of dense intrinsic connectivity, conceptualized as the 'canonical' cortical microcircuit 3,8 . Each cortical microcircuit receives sensory and cognitive information from a variety of sources which are represented by sustained activity within the microcircuit, referred to as persistent or recurrent activity 4,9 . Via recurrent connections within the microcircuit, activity can propagate for a variable length of time, thereby allowing temporary storage and computations to occur locally before ultimately passing a transformed representation to a downstream output 4,5,10 . Competing theories regarding how microcircuit activity is coordinated have proven difficult to reconcile in vivo where intercortical and intracortical computations cannot be fully dissociated 5,9,11,12 . Here, we interrogated the intrinsic features of isolated microcircuit networks using high-density calcium imaging of macaque dlPFC ex vivo . We found that spontaneous activity is intrinsically maintained by microcircuit architecture, persisting at a high rate in the absence of extrinsic connections. Further, using perisulcal stimulation to evoke persistent activity in deep layers, we found that activity propagates through stochastically assembled intracortical networks, creating predictable population-level events from largely non-overlapping ensembles. Microcircuit excitability covaried with individual cognitive performance, thus anchoring heuristic models of abstract cortical functions within quantifiable constraints imposed by the underlying synaptic architecture.

Long-term optical imaging of the spinal cord in awake, behaving animals

Advances in optical imaging approaches and fluorescent biosensors have enabled an understanding of the spatiotemporal and long-term neural dynamics in the brain of awake animals. However, methodological difficulties and the persistence of post-laminectomy fibrosis have greatly limited similar advances in the spinal cord. To overcome these technical obstacles, we combined in vivo application of fluoropolymer membranes that inhibit fibrosis; a redesigned, cost-effective implantable spinal imaging chamber; and improved motion correction methods that together permit imaging of the spinal cord in awake, behaving mice, for months to over a year. We also demonstrate a robust ability to monitor axons, identify a spinal cord somatotopic map, conduct Ca2+ imaging of neural dynamics in behaving animals responding to pain-provoking stimuli, and observe persistent microglial changes after nerve injury. The ability to couple neural activity and behavior at the spinal cord level will drive insights not previously possible at a key location for somatosensory transmission to the brain.

Trigeminal afferents sense locomotion-related meningeal deformations

The trigeminal sensory innervation of the cranial meninges is thought to serve a nociceptive function and mediate headache pain. However, the activity of meningeal afferents under natural conditions in awake animals remains unexplored. Here, we used two- and three-dimensional two-photon calcium imaging to track the activity of meningeal afferent fibers in awake mice. Surprisingly, a large subset of afferents was activated during non-noxious conditions such as locomotion. We estimated locomotion-related meningeal deformations and found afferents with distinct dynamics and tuning to various levels of meningeal expansion, compression, shearing, and Z-axis motion. Further, these mechanosensitive afferents were often tuned to distinct directions of meningeal expansion or compression. Thus, in addition to their role in headache-related pain, meningeal sensory neurons track the dynamic mechanical state of the meninges under natural conditions.

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.

Longitudinal two-photon calcium imaging with ultra-large cranial window for head-fixed mice

Neural activity is heterogeneous across different cortical areas and can change during learning. Here, we describe a protocol for longitudinal in vivo two-photon calcium imaging with an ultra-large cranial window that exposes most of the dorsal cortex in head-fixed mice. The large cranial window allows optical access to any dorsal cortical areas in individual mice. This protocol enables longitudinal tracking of neural activity from various cortical areas at cellular resolution to understand the cortical computations during behavioral tasks. For complete details on the use and execution of this protocol, please refer to Hattori et al. (2019), and Hattori and Komiyama, 2022a.