Brain activity consists of neural signals dynamically coordinated across spatial and temporal scales. To sample distributed brain-wide activity, we combine chronically implanted ultra-flexible electrodes for subcortical recordings with simultaneous two-photon calcium imaging in mouse neocortex. Flexible electrodes preserve optical access even at steep insertion angles and enable weeks-long single-neuron tracking. With these combined recordings, we demonstrate how subcortical-cortical coupling is modulated across slow brain states and around fast ripple events.

Human surgery and autopsy specimens are routinely stored as formalin-fixed paraffin-embedded (FFPE) tissue blocks for decades, creating vast archives of healthy and diseased tissues. While tissue clearing and whole-mount microscopy enable 3D analysis, FFPE human tissue blocks are often unsuitable for clearing and immunolabeling due to their large size and extensive cross-linking. Here, we introduce "archival" DISCO (aDISCO), a clearing method designed to overcome these challenges. aDISCO achieves effective clearing and immunolabeling of large samples stored for 15 years or more. We applied aDISCO to human brain, spinal cord, peripheral nerve, skin, muscle, heart, kidney, liver, spleen, colon, and lung, using a broad range of antibodies. Combining aDISCO with deep learning-based analysis to study focal cortical dysplasia (FCD), we found disrupted cortical layering with both focal and global neuronal density variations, features likely to be overlooked by conventional histology. In summary, aDISCO delivers datasets suitable for deep learning-based processing, enabling the detection of subtle and sparse pathologies in large archival human tissue specimens.

During arousal and stress, the locus coeruleus (LC) releases noradrenaline (NA) throughout the brain, including hippocampus. It remains, however, unclear how LC activity contributes to the cellular response profiles observed during natural arousal. Here we directly compared effects of natural arousal and isolated LC activation in mouse CA1 using physiologically titrated optogenetics, combined with fiber photometry of NA and calcium signals, chronic two-photon imaging, and behavioral monitoring. We found that natural arousal robustly activated all three major cell types - astrocytes, pyramidal cells, and inhibitory interneurons - on a population level. In contrast, stimulation of the LC alone exerted a slow inhibitory influence on pyramidal cells and interneurons, with only a subset of interneurons exhibiting a transient activation by LC stimulation. Interneurons, but not pyramidal cells, segregated into functionally consistent LC-responsive subpopulations (activated vs inhibited) with distinct laminar positions in CA1. However, these LC-responsive subpopulations of interneurons did not reliably map onto response subpopulations defined by activity patterns during natural arousal. Astrocytes were strongly activated by both natural arousal and LC stimulation. However, single-cell responses of astrocytes to LC stimulation only partially aligned with their activity during natural arousal responses, indicating distinct driving forces across the two conditions. Together, these results show that LC-driven NA release produces distinct, cell-specific effects that do not align with hippocampal dynamics during natural arousal. Thus, our findings highlight the need to rethink how the locus coeruleus influences the main hippocampal cell types in vivo. ### Competing Interest Statement The authors have declared no competing interest. ETH Zurich, ETH-20 19-1 Swiss National Science Foundation, 310030_172889, 310030_204372, 310030B_170269, PZ00P3_209114 Botnar Research Center for Child Health Swiss 3R Competence Center Roche (Switzerland), https://ror.org/00by1q217 Hochschulmedizin Zürich Flagship project STRESS European Research Council, 670757

Calcium imaging is a central method in neuroscience but it records neuronal activity only indirectly and thereby produces results that are difficult to interpret. Here we evaluate the GCaMP8 calcium indicator variants, together with methods to infer neuronal spiking, and thus interpret GCaMP8 recordings. We find that the linearity of GCaMP8 indicators enables accurate detection of both single action potentials and high-frequency spiking events. Ground-truth recordings from mouse neocortex show that the most linear variants GCaMP8s and GCaMP8m (but not GCaMP6, GCaMP7f or GCaMP8f) robustly detect isolated spikes in cortical pyramidal neurons. In addition, we fine-tune and benchmark algorithms for spike inference (CASCADE, OASIS and MLSpike) with data from all GCaMP8 variants for pyramidal neurons and interneurons, and we demonstrate how the fast rise time of GCaMP8 indicators enables real-time detection of neuronal activity. Overall, we provide tools and guidelines to optimally process GCaMP8 calcium signals and highlight the key role of linearity in interpreting calcium imaging data.

The mammalian neocortex is highly organized in local microcircuits and through long-range projection patterns between different regions. Since various features of local and long-range connectivity are determined by the cortical layer in which the respective neurons reside, understanding the flow of cortical information within and across layers is essential. Wide-field calcium imaging enables mesoscale functional mapping of genetically identified neurons across cortical areas. However, it has been applied primarily to superficial cortical layers, and systematic comparisons of wide-field signals across cortical layers are scarce. Here, we apply wide-field calcium imaging to different cortical layers using transgenic mouse lines with selective expression of GCaMP6f in layers 2/3, 5, and 6. We address several challenges of layer-specific wide-field imaging and provide possible solutions. First, to improve the registration of functional data to standard atlases, we demonstrate the benefit of layer-specific registration maps that are warped on the basis of the depth-dependent surface projections of the labeled cell populations. These maps help to assign the imaged calcium signals to the specific regions from which they originate. Second, we measure the depth-dependent blurring of wide-field fluorescence signals induced by light scattering and reveal stronger blurring in deep vs. superficial layers, in line with previous theoretical predictions from simulations. We used measured point spread functions to deconvolve single-whisker-evoked calcium signals in the barrel cortex and demonstrate improved signal confinement to individual barrel columns across layers. Finally, we investigate cross-regional functional connectivity during awake resting state periods for distinct layers. We find that mesoscopic functional connectivity is largely conserved between the cortical layers, with subtle differences for key regions of the default mode network (retrosplenial cortex and medial prefrontal cortex). Our approaches facilitate the comprehensive characterization of layer-specific cortico-cortical interactions, expanding wide-field calcium imaging as a powerful tool to investigate the layered organization of distributed brain dynamics.

Efficient control of behavior requires multisensory learning from information distributed across senses. However, most neurocomputational studies have focused on unisensory signals. Here, we identify distinct but interacting neurocomputational mechanisms that support learn-ing of multisensory associations. We designed a task in which behaviorally relevant information was available only from combinations of visual cues with either auditory or tactile cues. In 58 participants undergoing fMRI, we dissociated three processes: multisensory statistical learning (SL), modeled as stimulus-locked Shannon surprise; reinforcement learning (RL), modeled as feedback-locked signed reward prediction errors (RPEs); and feedback-locked unsigned RPEs (uRPEs), reflecting surprise about reward outcomes. Behaviorally, response times scaled with Shannon surprise (SL) while accuracy improved with feedback (RL). Model-based fMRI re-vealed dissociable but complementary networks: RPEs engaged ventral striatum, vmPFC, and left angular gyrus; surprise recruited bilateral angular gyrus, dlPFC, and precuneus; and uRPEs involved insula, dorsomedial prefrontal, and lateral frontoparietal cortices. Several of these regions are not typically implicated in unisensory studies, suggesting specialization for multisensory learning. All three networks were modality-general, i.e., they showed comparable strength for audiovisual and visuotactile learning. Notably, left angular gyrus tracked both Shannon surprise and RPE, identifying it as a potential hub for integrating structural and value information. These findings reveal that the brain engages distinct but complementary systems for structure-based, reward-based, and outcome-surprise computations. By combining behavioral modeling and fMRI with a novel task design, we provide a principled framework for dissecting the neurocomputational architecture of multisensory learning. ### Competing Interest Statement The authors have declared no competing interest. University of Zurich, University Research Priority Program Adaptive Brain Circuits in Development and Learning (URPP AdaBD) Marlene Porsche Graduate School of Neuroeconomics Swiss National Science Foundation, SNSF, grant no. 100019L-173248

Calcium imaging is a key method to record the spiking activity of identified and genetically targeted neurons. However, the observed calcium signals are only an indirect readout of the underlying electrophysiological events (single spikes or bursts of spikes) and require dedicated algorithms to recover the spike rate. These algorithms for spike inference can be optimized using ground truth data from combined electrical and optical recordings, but it is not clear how such optimized algorithms perform on cell types and brain regions for which ground truth does not exist. Here, we use a state-of-the-art algorithm based on supervised deep learning (CASCADE) and a nonsupervised algorithm based on non-negative deconvolution (OASIS) to test spike rate inference in spinal cord neurons. To enable these tests, we recorded specific ground truth from glutamatergic and GABAergic somatosensory neurons in the superficial dorsal horn of the spinal cord in mice of both sexes. We find that CASCADE and OASIS algorithms designed for cortical excitatory neurons generalize well to both spinal cord cell types. However, CASCADE models retrained on our ground truth further improved the performance, resulting in a more accurate inference of spiking activity from spinal cord neurons. We openly provide retrained models that can be applied to spinal cord data with variable noise levels and frame rates. Together, our ground truth recordings and analyses provide a solid foundation for the interpretation of calcium imaging data from spinal cord dorsal horn and showcase how spike rate inference can generalize between different regions of the nervous system.

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

Hepatitis E virus (HEV) infection, one of the most common forms of hepatitis worldwide, is often associated with extrahepatic, particularly renal, manifestations. However, the underlying mechanisms are incompletely understood. Here, we report the development of a de novo immune complex-mediated glomerulonephritis (GN) in a kidney transplant recipient with chronic hepatitis E. Applying immunostaining, electron microscopy, and mass spectrometry after laser-capture microdissection, we show that GN developed in parallel with increasing glomerular deposition of a noninfectious form of HEV open reading frame 2 (ORF2, capsid) protein secreted in excess. HEV particles or RNA, however, were not detectable. Patients with acute hepatitis E displayed similar but less pronounced deposits. Our results elucidate an immunologic mechanism by which this hepatotropic virus causes variable renal manifestations and establish a link between the HEV ORF2 protein and hepatitis E-associated GN. They directly provide a tool for etiology-based diagnosis of HEV-associated GN as a distinct entity and suggest therapeutic implications.

Precise CRISPR-based DNA integration and editing remain challenging, largely because of insufficient control of the repair process. We find that repair at the genome–cargo interface is predictable by deep learning models and adheres to sequence-context-specific rules. On the basis of in silico predictions, we devised a strategy of base-pair tandem repeat repair arms matching microhomologies at double-strand breaks. These repeat homology arms promote frame-retentive cassette integration and reduce deletions both at the target site and within the transgene. We demonstrate precise integrations at 32 loci in HEK293T cells. Germline-transmissible transgene integration and endogenous protein tagging in Xenopus and adult mouse brains demonstrated precise integration during early embryonic cleavage and in nondividing, differentiated cells. Optimized repair arms also facilitated small edits for scarless single-nucleotide or double-nucleotide changes using oligonucleotide templates in vitro and in vivo. We provide the design tool Pythia to facilitate precise genomic integration and editing for experimental and therapeutic purposes for a wide range of target cell types and applications. Genomic integration of DNA templates is made more precise through microhomology-focused design.

Multiphoton imaging allows for the visualization of structural and functional plasticity within the central nervous system. However, gaining optical access to deep brain structures, such as the hippocampal dentate gyrus (DG), requires invasive approaches, causing brain damage. Here we optimize three-photon (3P) microscopy to perform longitudinal imaging of the DG in the intact brain at unprecedented depth of up to 1800 μm. We apply this approach to follow the dynamics of neural stem cells (NSCs) in the adult and developing DG, allowing for novel insights into structural plasticity deep within the intact mouse brain.

During human surgeries and autopsies, specimens are regularly sampled and stored as formalin-fixed paraffin-embedded (FFPE) tissue blocks. Diagnoses are rendered by microscopical examination of two-dimensional sections. Good clinical practice requires that samples be retained for decades, thus giving rise to enormous archives of healthy and diseased human tissues. Tissue-clearing technologies and whole-mount microscopy would enable 3D analyses, but whole FFPE tissue blocks are often unsuitable for clearing due to their size, their extensive covalent cross-linking, and their embedding in solid wax. Here, we present ‘archival DISCO’ (aDISCO), a versatile and robust clearing method for whole-mount archival FFPE human tissue blocks. aDISCO enabled complete clearing and consistent antibody staining of samples stored for at least 15 years. We show that aDISCO can be applied to human brain, spinal cord, peripheral nerve, skin, muscle, heart, kidney, liver, spleen, colon, and lung, and is compatible with a wide range of commonly used antibodies. We applied aDISCO to the 3D study of focal cortical dysplasia (FCD), a neurodevelopmental disease associated with epilepsy. We performed deep-learning-based segmentation and object detection to identify both focal and global neuronal density variations in FCD and to precisely quantify the disruption of cortical layering, features that are likely to be overlooked by conventional histology. When combined with selective-plane illumination microscopy, aDISCO delivers natively digital data suitable for deep-learning-based processing, thus enabling the detection of subtle and sparse pathologies in large archival human tissue specimens. ### Competing Interest Statement The authors have declared no competing interest. Filling-the-Gap grant, University of Zurich EMPIRIS and Lazarus grants, University Hospital Zurich Foundation Investment Fund, University of Zurich URPP Adaptive Brain Circuits in Development and Learning (AdaBD)?, University of Zurich

Large strokes frequently result in lasting motor deficits and trigger extensive reorganization within the brain and spinal cord. Altered neuronal activity in the contralesional hemisphere has been documented in both humans and rodent models, yet its role in functional recovery versus maladaptation remains unresolved. Here, we used chronic wide-field calcium imaging to monitor bilateral cortical activity in mice performing a skilled reach-to-grasp task before and days to weeks after stroke. Strokes produced persistent fine motor impairments, which were only partly alleviated by intensive rehabilitative training. While cortical activity was in particular suppressed in the ipsilesional cortex after stroke, training promoted sustained increases in contralesional sensorimotor activity. However, ridge regression analysis of neural and behavioral data indicated that this activity largely reflected compensatory use of the intact paw rather than recovery of the impaired forelimb. Axonal tracing nevertheless revealed enhanced projections from contralesional motor cortex to ipsilesional brainstem nuclei - including the midbrain and pontine reticular nucleus - specifically in trained animals. These findings identify a rehabilitation-induced corticofugal pathway supporting motor recovery, highlighting a target for neuromodulation strategies in chronic post-stroke impairment.

The coordinated changes of neural activity during learning, from single neurons to populations of neurons and their interactions across brain areas, remain poorly understood. To reveal specific learning-related changes, we applied multi-area two-photon calcium imaging in mouse neocortex during training of a sensory discrimination task. We uncovered coordinated adaptations in primary somatosensory area S1 and the anterior (A) and rostrolateral (RL) areas of posterior parietal cortex (PPC). At the single-neuron level, task-learning was marked by increased number and stabilized responses of task neurons. At the population level, responses exhibited decreased dimensionality and reduced trial-to-trial variability, paralleled by enhanced encoding of task information. The PPC areas became gradually engaged, opening additional within-area subspaces and inter-area subspaces with S1. Task encoding subspaces gradually aligned with these interaction subspaces. Behavioral errors correlated with decreased encoding accuracy and misaligned subspaces. Thus, multi-level adaptations within and across cortical areas contribute to learning-related refinement of sensory processing and decision-making.

Appropriate risk evaluation is essential for survival in complex, uncertain environments. Confronted with choosing between certain (safe) and uncertain (risky) options, animals show strong preference for either option consistently across extended time periods. How such risk preference is encoded in the brain remains elusive. A candidate region is the lateral habenula (LHb), which is prominently involved in value-guided behavior. Here, using a balanced two-alternative choice task and longitudinal two-photon calcium imaging in mice, we identify risk-preference-selective activity in LHb neurons reflecting individual risk preference before action selection. By using whole-brain anatomical tracing, multi-fiber photometry and projection-specific and cell-type-specific optogenetics, we find glutamatergic LHb projections from the medial (MH) but not lateral (LH) hypothalamus providing behavior-relevant synaptic input before action selection. Optogenetic stimulation of MH→LHb axons evoked excitatory and inhibitory postsynaptic responses, whereas LH→LHb projections were excitatory. We thus reveal functionally distinct hypothalamus–habenula circuits for risk preference in habitual economic decision-making. Groos et al. show that lateral habenula activity reflects individual risk preference before action selection. This activity is modulated by behavior-relevant synaptic input from the medial hypothalamus capable of glutamate and GABA co-release.

Neuroscience can only be reproducible when its key methods are quantitative and interpretable. Calcium imaging is such a key method which, however, records neuronal activity only indirectly and is therefore difficult to interpret. These difficulties arise primarily from the kinetics, nonlinearity, and sensitivity of the calcium indicator, but also depend on the methods for calcium signal analysis. Here, we evaluate the ability of the recently developed calcium indicator GCaMP8 to reveal neuronal spiking, and we investigate how existing spike inference methods (CASCADE, OASIS, MLSpike) should be adapted for optimal performance. We demonstrate, both for principal cells and interneurons, that algorithms require fine-tuning to obtain optimal results with GCaMP8 data. Specifically, supervised algorithms adapted for GCaMP8 result in more linear and therefore more accurate recovery of complex spiking events. In addition, our analysis of cortical ground truth recordings shows that GCaMP8s and GCaMP8m - but not GCaMP6, GCaMP7f or GCaMP8f - are able to reliably detect isolated action potentials for realistic noise levels. Finally, we demonstrate that, due to their fast rise times, GCaMP8 indicators support shorter closed-loop latencies for real-time detection of neuronal activity. Together, our study provides demonstrations, tools, and guidelines to optimally process and quantitatively interpret calcium signals obtained with GCaMP8. ### Competing Interest Statement The authors have declared no competing interest.

Sleep debt accumulates during wakefulness, leading to increased slow wave activity (SWA) during sleep, an encephalographic marker for sleep need. The use-dependent demands of prior wakefulness increase sleep SWA locally. However, the circuitry and molecular identity of this “local sleep” remain unclear. Using pharmacology and optogenetic perturbations together with transcriptomics, we find that cortical brain-derived neurotrophic factor (BDNF) regulates SWA via the activation of tyrosine kinase B (TrkB) receptor and cAMP-response element-binding protein (CREB). We map BDNF/TrkB-induced sleep SWA to layer 5 (L5) pyramidal neurons of the cortex, independent of neuronal firing per se. Using mathematical modeling, we here propose a model of how BDNF’s effects on synaptic strength can increase SWA in ways not achieved through increased firing alone. Proteomic analysis further reveals that TrkB activation enriches ubiquitin and proteasome subunits. Together, our study reveals that local SWA control is mediated by BDNF-TrkB-CREB signaling in L5 excitatory cortical neurons.