Deviance Distraction and Stimulus-Specific Adaptation in the Somatosensory Cortex Reduce with Experience.

Automatic detection of a surprising change in the sensory input is a central element of exogenous attentional control. Stimulus-specific adaptation (SSA) is a potential neuronal mechanism detecting such changes and has been robustly described across sensory modalities and different instances of the ascending sensory pathways. However, little is known about the relationship of SSA to perception. To assess how deviating stimuli influence target signal detection, we used a behavioral cross-modal paradigm in mice and combined it with extracellular recordings from the primary somatosensory whisker cortex. In this paradigm, male mice performed a visual detection task while task-irrelevant whisker stimuli were either presented as repetitive "standard" or as rare deviant stimuli. We found a deviance distraction effect on the animals' performance: Faster reaction times but worsened target detection was observed in the presence of a deviant stimulus. Multiunit activity and local field potentials exhibited enhanced neuronal responses to deviant compared with standard whisker stimuli across all cortical layers, as a result of SSA. The deviant-triggered behavioral distraction correlated with these enhanced neuronal deviant responses only in the deeper cortical layers. However, the layer-specific effect of SSA on perception reduced with increasing task experience as a result of statistical distractor learning. These results demonstrate a layer-specific involvement of SSA on perception that is susceptible to modulation over time.SIGNIFICANCE STATEMENT Detecting sudden changes in our immediate environment is behaviorally relevant and important for efficient perceptual processing. However, the connection between the underpinnings of cortical deviance detection and perception remains unknown. Here, we investigate how the cortical representation of deviant whisker stimuli impacts visual target detection by recording local field potential and multiunit activity in the primary somatosensory cortex of mice engaged in a cross-modal visual detection task. We find that deviant whisker stimuli distract animals in their task performance, which correlates with enhanced neuronal responses for deviants in a layer-specific manner. Interestingly, this effect reduces with the increased experience of the animal as a result of distractor learning on statistical regularities.

An optimized registration workflow and standard geometric space for small animal brain imaging.

The reliability of scientific results critically depends on reproducible and transparent data processing. Cross-subject and cross-study comparability of imaging data in general, and magnetic resonance imaging (MRI) data in particular, is contingent on the quality of registration to a standard reference space. In small animal MRI this is not adequately provided by currently used processing workflows, which utilize high-level scripts optimized for human data, and adapt animal data to fit the scripts, rather than vice-versa. In this fully reproducible article we showcase a generic workflow optimized for the mouse brain, alongside a standard reference space suited to harmonize data between analysis and operation. We introduce four separate metrics for automated quality control (QC), and a visualization method to aid operator inspection. Benchmarking this workflow against common legacy practices reveals that it performs more consistently, better preserves variance across subjects while minimizing variance across sessions, and improves both volume and smoothness conservation RMSE approximately 2-fold. We propose this open source workflow and the QC metrics as a new standard for small animal MRI registration, ensuring workflow robustness, data comparability, and region assignment validity, all of which are indispensable prerequisites for the comparability of scientific results across experiments and centers.

mRNA-engineered mesenchymal stem cells for targeted delivery of interleukin-10 to sites of inflammation.

Mesenchymal stem cells (MSCs) are promising candidates for cell-based therapy to treat several diseases and are compelling to consider as vehicles for delivery of biological agents. However, MSCs appear to act through a seemingly limited "hit-and-run" mode to quickly exert their therapeutic impact, mediated by several mechanisms, including a potent immunomodulatory secretome. Furthermore, MSC immunomodulatory properties are highly variable and the secretome composition following infusion is uncertain. To determine whether a transiently controlled antiinflammatory MSC secretome could be achieved at target sites of inflammation, we harnessed mRNA transfection to generate MSCs that simultaneously express functional rolling machinery (P-selectin glycoprotein ligand-1 [PSGL-1] and Sialyl-Lewis(x) [SLeX]) to rapidly target inflamed tissues and that express the potent immunosuppressive cytokine interleukin-10 (IL-10), which is not inherently produced by MSCs. Indeed, triple-transfected PSGL-1/SLeX/IL-10 MSCs transiently increased levels of IL-10 in the inflamed ear and showed a superior antiinflammatory effect in vivo, significantly reducing local inflammation following systemic administration. This was dependent on rapid localization of MSCs to the inflamed site. Overall, this study demonstrates that despite the rapid clearance of MSCs in vivo, engineered MSCs can be harnessed via a "hit-and-run" action for the targeted delivery of potent immunomodulatory factors to treat distant sites of inflammation.

Months-long tracking of neuronal ensembles spanning multiple brain areas with Ultra-Flexible Tentacle Electrodes.

We introduce Ultra-Flexible Tentacle Electrodes (UFTEs), packing many independent fibers with the smallest possible footprint without limitation in recording depth using a combination of mechanical and chemical tethering for insertion. We demonstrate a scheme to implant UFTEs simultaneously into many brain areas at arbitrary locations without angle-of-insertion limitations, and a 512-channel wireless logger. Immunostaining reveals no detectable chronic tissue damage even after several months. Mean spike signal-to-noise ratios are 1.5-3x compared to the state-of-the-art, while the highest signal-to-noise ratios reach 89, and average cortical unit yields are ~1.75/channel. UFTEs can track the same neurons across sessions for at least 10 months (longest duration tested). We tracked inter- and intra-areal neuronal ensembles (neurons repeatedly co-activated within 25 ms) simultaneously from hippocampus, retrosplenial cortex, and medial prefrontal cortex in freely moving rodents. Average ensemble lifetimes were shorter than the durations over which we can track individual neurons. We identify two distinct classes of ensembles. Those tuned to sharp-wave ripples display the shortest lifetimes, and the ensemble members are mostly hippocampal. Yet, inter-areal ensembles with members from both hippocampus and cortex have weak tuning to sharp wave ripples, and some have unusual months-long lifetimes. Such inter-areal ensembles occasionally remain inactive for weeks before re-emerging.

High-throughput in vivo vertebrate screening.

We demonstrate a high-throughput platform for cellular-resolution in vivo chemical and genetic screens on zebrafish larvae. The system automatically loads zebrafish from reservoirs or multiwell plates, and positions and rotates them for high-speed confocal imaging and laser manipulation of both superficial and deep organs within 19 s without damage. We performed small-scale test screening of retinal axon guidance mutants and neuronal regeneration assays in combination with femtosecond laser microsurgery.

Large-scale in vivo femtosecond laser neurosurgery screen reveals small-molecule enhancer of regeneration.

Discovery of molecular mechanisms and chemical compounds that enhance neuronal regeneration can lead to development of therapeutics to combat nervous system injuries and neurodegenerative diseases. By combining high-throughput microfluidics and femtosecond laser microsurgery, we demonstrate for the first time large-scale in vivo screens for identification of compounds that affect neurite regeneration. We performed thousands of microsurgeries at single-axon precision in the nematode Caenorhabditis elegans at a rate of 20 seconds per animal. Following surgeries, we exposed the animals to a hand-curated library of approximately one hundred small molecules and identified chemicals that significantly alter neurite regeneration. In particular, we found that the PKC kinase inhibitor staurosporine strongly modulates regeneration in a concentration- and neuronal type-specific manner. Two structurally unrelated PKC inhibitors produce similar effects. We further show that regeneration is significantly enhanced by the PKC activator prostratin.

Bayesian surprise shapes neural responses in somatosensory cortical circuits.

Numerous psychophysical studies show that Bayesian inference governs sensory decision-making; however, the specific neural circuitry underlying this probabilistic mechanism remains unclear. We record extracellular neural activity along the somatosensory pathway of mice while delivering sensory stimulation paradigms designed to isolate the response to the surprise generated by Bayesian inference. Our results demonstrate that laminar cortical circuits in early sensory areas encode Bayesian surprise. Systematic sensitivity to surprise is not identified in the somatosensory thalamus, rather emerging in the primary (S1) and secondary (S2) somatosensory cortices. Multiunit spiking activity and evoked potentials in layer 6 of these regions exhibit the highest sensitivity to surprise. Gamma power in S1 layer 2/3 exhibits an NMDAR-dependent scaling with surprise, as does alpha power in layers 2/3 and 6 of S2. These results show a precise spatiotemporal neural representation of Bayesian surprise and suggest that Bayesian inference is a fundamental component of cortical processing.

Projections from the five divisions of the orbital cortex to the thalamus in the rat.

The orbital cortex (ORB) of the rat consists of five divisions: the medial (MO), ventral (VO), ventrolateral (VLO), lateral (LO), and dorsolateral (DLO) orbital cortices. No previous report has comprehensively examined and compared projections from each division of the ORB to the thalamus. Using the anterograde anatomical tracer, Phaseolus vulgaris leucoagglutinin, we describe the efferent projections from the five divisions of the ORB to the thalamus in the rat. We demonstrated that, with some overlap, each division of the ORB distributed in a distinct (and unique) manner to nuclei of the thalamus. Overall, ORB projected to a relatively restricted number of sites in the thalamus, and strikingly distributed entirely to structures of the medial/midline thalamus, while completely avoiding lateral regions or principal nuclei of the thalamus. The main termination sites in the thalamus were the paratenial nucleus (PT) and nucleus reuniens (RE) of the midline thalamus, the medial (MDm) and central (MDc) divisions of the mediodorsal nucleus, the intermediodorsal nucleus, the central lateral, paracentral, and central medial nuclei of the rostral intralaminar complex and the submedial nucleus (SM). With some exceptions, medial divisions of the ORB (MO, VO) mainly targeted "limbic-associated" nuclei such as PT, RE, and MDm, whereas lateral division (VLO, LO, DLO) primarily distributed to "sensorimotor-associated" nuclei including MDc, SM, and the rostral intralaminar complex. As discussed herein, the medial/midline thalamus may represent an important link (or bridge) between the orbital cortex and the hippocampus and between the ORB and medial prefrontal cortex. In summary, the present results demonstrate that each division of the orbital cortex projects in a distinct manner to nuclei of the thalamus which suggests unique functions for each division of the orbital cortex.

Technologies for micromanipulating, imaging, and phenotyping small invertebrates and vertebrates.

Small multicellular model organisms such as the invertebrate nematode C. elegans and the vertebrate zebrafish provide unique opportunities for both basic science and pharmaceutical discovery. In recent years, there have been significant breakthroughs in technologies to manipulate and image these organisms for a variety of purposes ranging from behavioral studies of neuronal circuits to high-throughput screening. Here, we review these advancements with a particular focus on the optically transparent model organisms C. elegans and zebrafish.

Machine learning reveals interhemispheric somatosensory coherence as indicator of anesthetic depth.

The goal of this study was to identify features in mouse electrocorticogram recordings that indicate the depth of anesthesia as approximated by the administered anesthetic dosage. Anesthetic depth in laboratory animals must be precisely monitored and controlled. However, for the most common lab species (mice) few indicators useful for monitoring anesthetic depth have been established. We used electrocorticogram recordings in mice, coupled with peripheral stimulation, in order to identify features of brain activity modulated by isoflurane anesthesia and explored their usefulness in monitoring anesthetic depth through machine learning techniques. Using a gradient boosting regressor framework we identified interhemispheric somatosensory coherence as the most informative and reliable electrocorticogram feature for determining anesthetic depth, yielding good generalization and performance over many subjects. Knowing that interhemispheric somatosensory coherence indicates the effectively administered isoflurane concentration is an important step for establishing better anesthetic monitoring protocols and closed-loop systems for animal surgeries.

Deep-learning based identification, tracking, pose estimation, and behavior classification of interacting primates and mice in complex environments.

The quantification of behaviors of interest from video data is commonly used to study brain function, the effects of pharmacological interventions, and genetic alterations. Existing approaches lack the capability to analyze the behavior of groups of animals in complex environments. We present a novel deep learning architecture for classifying individual and social animal behavior, even in complex environments directly from raw video frames, while requiring no intervention after initial human supervision. Our behavioral classifier is embedded in a pipeline (SIPEC) that performs segmentation, identification, pose-estimation, and classification of complex behavior, outperforming the state of the art. SIPEC successfully recognizes multiple behaviors of freely moving individual mice as well as socially interacting non-human primates in 3D, using data only from simple mono-vision cameras in home-cage setups.

Neurosurgery: functional regeneration after laser axotomy.

Understanding how nerves regenerate is an important step towards developing treatments for human neurological disease, but investigation has so far been limited to complex organisms (mouse and zebrafish) in the absence of precision techniques for severing axons (axotomy). Here we use femtosecond laser surgery for axotomy in the roundworm Caenorhabditis elegans and show that these axons functionally regenerate after the operation. Application of this precise surgical technique should enable nerve regeneration to be studied in vivo in its most evolutionarily simple form.

An Automated Open-Source Workflow for Standards-Compliant Integration of Small Animal Magnetic Resonance Imaging Data.

Large-scale research integration is contingent on seamless access to data in standardized formats. Standards enable researchers to understand external experiment structures, pool results, and apply homogeneous preprocessing and analysis workflows. Particularly, they facilitate these features without the need for numerous potentially confounding compatibility add-ons. In small animal magnetic resonance imaging, an overwhelming proportion of data is acquired via the ParaVision software of the Bruker Corporation. The original data structure is predominantly transparent, but fundamentally incompatible with modern pipelines. Additionally, it sources metadata from free-field operator input, which diverges strongly between laboratories and researchers. In this article we present an open-source workflow which automatically converts and reposits data from the ParaVision structure into the widely supported and openly documented Brain Imaging Data Structure (BIDS). Complementing this workflow we also present operator guidelines for appropriate ParaVision data input, and a programmatic walk-through detailing how preexisting scans with uninterpretable metadata records can easily be made compliant after the acquisition.

Non-invasive molecularly-specific millimeter-resolution manipulation of brain circuits by ultrasound-mediated aggregation and uncaging of drug carriers.

Non-invasive, molecularly-specific, focal modulation of brain circuits with low off-target effects can lead to breakthroughs in treatments of brain disorders. We systemically inject engineered ultrasound-controllable drug carriers and subsequently apply a novel two-component Aggregation and Uncaging Focused Ultrasound Sequence (AU-FUS) at the desired targets inside the brain. The first sequence aggregates drug carriers with millimeter-precision by orders of magnitude. The second sequence uncages the carrier's cargo locally to achieve high target specificity without compromising the blood-brain barrier (BBB). Upon release from the carriers, drugs locally cross the intact BBB. We show circuit-specific manipulation of sensory signaling in motor cortex in rats by locally concentrating and releasing a GABAA receptor agonist from ultrasound-controlled carriers. Our approach uses orders of magnitude (1300x) less drug than is otherwise required by systemic injection and requires very low ultrasound pressures (20-fold below FDA safety limits for diagnostic imaging). We show that the BBB remains intact using passive cavitation detection (PCD), MRI-contrast agents and, importantly, also by sensitive fluorescent dye extravasation and immunohistochemistry.

Towards gecko-feet-inspired bandages.

A novel bandage inspired by gecko feet might one day be used during emergencies and internal surgeries. The bandage uses a combination of nanofabricated structures, biodegradable materials and adhesive surface chemistry that allows adhesion onto even wet, moving tissue.

Engineering brain activity patterns by neuromodulator polytherapy for treatment of disorders.

Conventional drug screens and treatments often ignore the underlying complexity of brain network dysfunctions, resulting in suboptimal outcomes. Here we ask whether we can correct abnormal functional connectivity of the entire brain by identifying and combining multiple neuromodulators that perturb connectivity in complementary ways. Our approach avoids the combinatorial complexity of screening all drug combinations. We develop a high-speed platform capable of imaging more than 15000 neurons in 50ms to map the entire brain functional connectivity in large numbers of vertebrates under many conditions. Screening a panel of drugs in a zebrafish model of human Dravet syndrome, we show that even drugs with related mechanisms of action can modulate functional connectivity in significantly different ways. By clustering connectivity fingerprints, we algorithmically select small subsets of complementary drugs and rapidly identify combinations that are significantly more effective at correcting abnormal networks and reducing spontaneous seizures than monotherapies, while minimizing behavioral side effects. Even at low concentrations, our polytherapy performs superior to individual drugs even at highest tolerated concentrations.

Sub-cellular precision on-chip small-animal immobilization, multi-photon imaging and femtosecond-laser manipulation.

Techniques for stable, rapid and repeatable small-animal immobilization are necessary for high-throughput in vivo genetic/drug screens using cellular and sub-cellular features in multi-cellular organisms. We demonstrate a method for non-invasive and high-throughput on-chip immobilization of physiologically active C. elegans without the use of anesthesia or cooling, but with comparable stability even for the most demanding purposes. We show observation and manipulation of sub-cellular features in immobilized animals using two-photon microscopy and femtosecond-laser microsurgery.

Combinatorial programming of human neuronal progenitors using magnetically-guided stoichiometric mRNA delivery.

Identification of optimal transcription factor expression patterns to direct cellular differentiation along a desired pathway presents significant challenges. We demonstrate massively combinatorial screening of temporally-varying mRNA transcription factors to direct differentiation of neural progenitor cells using a dynamically-reconfigurable magnetically-guided spotting technology for localizing mRNA, enabling experiments on millimetre size spots. In addition, we present a time-interleaved delivery method that dramatically reduces fluctuations in the delivered transcription factor copy numbers per cell. We screened combinatorial and temporal delivery of a pool of midbrain-specific transcription factors to augment the generation of dopaminergic neurons. We show that the combinatorial delivery of LMX1A, FOXA2 and PITX3 is highly effective in generating dopaminergic neurons from midbrain progenitors. We show that LMX1A significantly increases TH-expression levels when delivered to neural progenitor cells either during proliferation or after induction of neural differentiation, while FOXA2 and PITX3 increase expression only when delivered prior to induction, demonstrating temporal dependence of factor addition.

A Hippocampal Model for Behavioral Time Acquisition and Fast Bidirectional Replay of Spatio-Temporal Memory Sequences.

The hippocampus is known to play a crucial role in the formation of long-term memory. For this, fast replays of previously experienced activities during sleep or after reward experiences are believed to be crucial. But how such replays are generated is still completely unclear. In this paper we propose a possible mechanism for this: we present a model that can store experienced trajectories on a behavioral timescale after a single run, and can subsequently bidirectionally replay such trajectories, thereby omitting any specifics of the previous behavior like speed, etc, but allowing repetitions of events, even with different subsequent events. Our solution builds on well-known concepts, one-shot learning and synfire chains, enhancing them by additional mechanisms using global inhibition and disinhibition. For replays our approach relies on dendritic spikes and cholinergic modulation, as supported by experimental data. We also hypothesize a functional role of disinhibition as a pacemaker during behavioral time.

Brain activity patterns in high-throughput electrophysiology screen predict both drug efficacies and side effects.

Neurological drugs are often associated with serious side effects, yet drug screens typically focus only on efficacy. We demonstrate a novel paradigm utilizing high-throughput in vivo electrophysiology and brain activity patterns (BAPs). A platform with high sensitivity records local field potentials (LFPs) simultaneously from many zebrafish larvae over extended periods. We show that BAPs from larvae experiencing epileptic seizures or drug-induced side effects have substantially reduced complexity (entropy), similar to reduced LFP complexity observed in Parkinson's disease. To determine whether drugs that enhance BAP complexity produces positive outcomes, we used light pulses to trigger seizures in a model of Dravet syndrome, an intractable genetic epilepsy. The highest-ranked compounds identified by BAP analysis exhibit far greater anti-seizure efficacy and fewer side effects during subsequent in-depth behavioral assessment. This high correlation with behavioral outcomes illustrates the power of brain activity pattern-based screens and identifies novel therapeutic candidates with minimal side effects.