Mapping brain state-dependent sensory responses across the mouse cortex.

Sensory information must be integrated across a distributed brain network for stimulus processing and perception. Recent studies have revealed specific spatiotemporal patterns of cortical activation for the early and late components of sensory-evoked responses, which are associated with stimulus features and perception, respectively. Here, we investigated how the brain state influences the sensory-evoked activation across the mouse cortex. We utilized isoflurane to modulate the brain state and conducted wide-field calcium imaging of Thy1-GCaMP6f mice to monitor distributed activation evoked by multi-whisker stimulation. Our findings reveal that the level of anesthesia strongly shapes the spatiotemporal features and the functional connectivity of the sensory-activated network. As anesthesia levels decrease, we observe increasingly complex responses, accompanied by the emergence of the late component within the sensory-evoked response. The persistence of the late component under anesthesia raises new questions regarding the potential existence of perception during unconscious states.

Profiling wastewater characteristics in intra-urban catchments using online monitoring stations.

This study aims to investigate the differences in intra-urban catchments with different characteristics through real-time wastewater monitoring. Monitoring stations were installed in three neighbourhoods of Barcelona to measure flow, total chemical oxygen demand (COD), pH, conductivity, temperature, and bisulfide (HS-) for 1 year. Typical wastewater profiles were obtained for weekdays, weekends, and holidays in the summer and winter seasons. The results reveal differences in waking up times and evening routines, commuting behaviour during weekends and holidays, and water consumption. The pollutant profiles contribute to a better understanding of pollution generation in households and catchment activities. Flows and COD correlate well at all stations, but there are differences in conductivity and HS- at the station level. The article concludes by discussing the operational experience of the monitoring stations.

A modular and adaptable analysis pipeline to compare slow cerebral rhythms across heterogeneous datasets.

Neuroscience is moving toward a more integrative discipline where understanding brain function requires consolidating the accumulated evidence seen across experiments, species, and measurement techniques. A remaining challenge on that path is integrating such heterogeneous data into analysis workflows such that consistent and comparable conclusions can be distilled as an experimental basis for models and theories. Here, we propose a solution in the context of slow-wave activity (<1 Hz), which occurs during unconscious brain states like sleep and general anesthesia and is observed across diverse experimental approaches. We address the issue of integrating and comparing heterogeneous data by conceptualizing a general pipeline design that is adaptable to a variety of inputs and applications. Furthermore, we present the Collaborative Brain Wave Analysis Pipeline (Cobrawap) as a concrete, reusable software implementation to perform broad, detailed, and rigorous comparisons of slow-wave characteristics across multiple, openly available electrocorticography (ECoG) and calcium imaging datasets.

Simulations approaching data: cortical slow waves in inferred models of the whole hemisphere of mouse.

The development of novel techniques to record wide-field brain activity enables estimation of data-driven models from thousands of recording channels and hence across large regions of cortex. These in turn improve our understanding of the modulation of brain states and the richness of traveling waves dynamics. Here, we infer data-driven models from high-resolution in-vivo recordings of mouse brain obtained from wide-field calcium imaging. We then assimilate experimental and simulated data through the characterization of the spatio-temporal features of cortical waves in experimental recordings. Inference is built in two steps: an inner loop that optimizes a mean-field model by likelihood maximization, and an outer loop that optimizes a periodic neuro-modulation via direct comparison of observables that characterize cortical slow waves. The model reproduces most of the features of the non-stationary and non-linear dynamics present in the high-resolution in-vivo recordings of the mouse brain. The proposed approach offers new methods of characterizing and understanding cortical waves for experimental and computational neuroscientists.

Assessing brain state and anesthesia level with two-photon calcium signals.

Brain states, such as wake, sleep, or different depths of anesthesia are usually assessed using electrophysiological techniques, such as the local field potential (LFP) or the electroencephalogram (EEG), which are ideal signals for detecting activity patterns such as asynchronous or oscillatory activities. However, it is technically challenging to have these types of measures during calcium imaging recordings such as two-photon or wide-field techniques. Here, using simultaneous two-photon and LFP measurements, we demonstrate that despite the slower dynamics of the calcium signal, there is a high correlation between the LFP and two-photon signals taken from the neuropil outside neuronal somata. Moreover, we find the calcium signal to be systematically delayed from the LFP signal, and we use a model to show that the delay between the two signals is due to the physical distance between the recording sites. These results suggest that calcium signals alone can be used to detect activity patterns such as slow oscillations and ultimately assess the brain state and level of anesthesia.

Photothrombotic Middle Cerebral Artery Occlusion in Mice: A Novel Model of Ischemic Stroke.

Stroke is one of the main causes of death and disability worldwide. Over the past decades, several animal models of focal cerebral ischemia have been developed allowing to investigate pathophysiological mechanisms underlying stroke progression. Despite intense preclinical research efforts, the need for noninvasive mouse models of vascular occlusion targeting the middle cerebral artery yet avoiding mechanical intervention is still pressing. Here, by applying the photothrombotic stroke model to the distal branch of the middle cerebral artery, we developed a novel strategy to induce a targeted occlusion of a large blood vessel in mice. This approach induces unilateral damage encompassing most of the dorsal cortex from the motor up to the visual regions 1 week after stroke. Pronounced limb dystonia one day after the damage is partially recovered after one week. Furthermore, we observe the insurgence of blood vessel leakage and edema formation in the peri-infarct area. Finally, this model elicits a notable inflammatory response revealed as a strong increase in astrocyte density and morphologic complexity in the perilesional region of the cortex compared with both other regions of the ipsilesional and contralesional hemispheres, and in sham-operated mice. To conclude, the stroke model we developed induces in mice the light-mediated occlusion of one of the main targets of human ischemic stroke, the middle cerebral artery, free from the limitations of commonly used preclinical models.

In Vivo Imaging of the Structural Plasticity of Cortical Neurons After Stroke.

The comprehension of the finest mechanisms underlying experience-dependent plasticity requires the investigation of neurons and synaptic terminals in the intact brain over prolonged periods of time. Longitudinal two-photon imaging together with the expression of fluorescent proteins enables high-resolution imaging of dendritic spines and axonal varicosities of cortical neurons in vivo. Importantly, the study of the mechanisms of structural reorganization is relevant for a deeper understanding of the pathophysiological mechanisms of neurological diseases such as stroke and for the development of new therapeutic approaches. This protocol describes the principal steps for in vivo investigation of neuronal plasticity both in healthy conditions and after an ischemic lesion. First, we give a description of the surgery to perform a stable cranial window that allows optical access to the mouse brain cortex. Then we explain how to perform longitudinal two-photon imaging of dendrites, axonal branches, and synaptic terminals in the mouse brain cortex in vivo, in order to investigate the plasticity of synaptic terminals and orientation of neuronal processes. Finally, we describe how to induce an ischemic lesion in a target region of the mouse brain cortex through a cranial window by applying the photothrombotic stroke model.

Large-scale all-optical dissection of motor cortex connectivity shows a segregated organization of mouse forelimb representations.

In rodent motor cortex, the rostral forelimb area (RFA) and the caudal forelimb area (CFA) are major actors in orchestrating the control of complex forelimb movements. However, their intrinsic connectivity and reciprocal functional organization are still unclear, limiting our understanding of how the brain coordinates and executes voluntary movements. Here, we causally probe cortical connectivity and activation patterns triggered by transcranial optogenetic stimulation of ethologically relevant complex movements exploiting a large-scale all-optical method in awake mice. Results show specific activation features for each movement class, providing evidence for a segregated functional organization of CFA and RFA. Importantly, we identify a second discrete lateral grasping representation area, namely the lateral forelimb area (LFA), with unique connectivity and activation patterns. Therefore, we propose the LFA as a distinct forelimb representation in the mouse somatotopic motor map.

Latency correction in sparse neuronal spike trains.

BACKGROUND: In neurophysiological data, latency refers to a global shift of spikes from one spike train to the next, either caused by response onset fluctuations or by finite propagation speed. Such systematic shifts in spike timing lead to a spurious decrease in synchrony which needs to be corrected. NEW METHOD: We propose a new algorithm of multivariate latency correction suitable for sparse data for which the relevant information is not primarily in the rate but in the timing of each individual spike. The algorithm is designed to correct systematic delays while maintaining all other kinds of noisy disturbances. It consists of two steps, spike matching and distance minimization between the matched spikes using simulated annealing. RESULTS: We show its effectiveness on simulated and real data: cortical propagation patterns recorded via calcium imaging from mice before and after stroke. Using simulations of these data we also establish criteria that can be evaluated beforehand in order to anticipate whether our algorithm is likely to yield a considerable improvement for a given dataset. COMPARISON WITH EXISTING METHOD(S): Existing methods of latency correction rely on adjusting peaks in rate profiles, an approach that is not feasible for spike trains with low firing in which the timing of individual spikes contains essential information. CONCLUSIONS: For any given dataset the criterion for applicability of the algorithm can be evaluated quickly and in case of a positive outcome the latency correction can be applied easily since the source codes of the algorithm are publicly available.

Tracking the Effect of Therapy With Single-Trial Based Classification After Stroke.

Stroke is a debilitating disease that leads, in the 50% of cases, to permanent motor or cognitive impairments. The effectiveness of therapies that promote recovery after stroke depends on indicators of the disease state that can measure the degree of recovery or predict treatment response or both. Here, we propose to use single-trial classification of task dependent neural activity to assess the disease state and track recovery after stroke. We tested this idea on calcium imaging data of the dorsal cortex of healthy, spontaneously recovered and rehabilitated mice while performing a forelimb retraction task. Results show that, at a single-trial level for the three experimental groups, neural activation during the reward pull can be detected with high accuracy with respect to the background activity in all cortical areas of the field of view and this activation is quite stable across trials and subjects of the same group. Moreover, single-trial responses during the reward pull can be used to discriminate between healthy and stroke subjects with areas closer to the injury site displaying higher discrimination capability than areas closer to this site. Finally, a classifier built to discriminate between controls and stroke at the single-trial level can be used to generate an index of the disease state, the therapeutic score, which is validated on the group of rehabilitated mice. In conclusion, task-related neural activity can be used as an indicator of disease state and track recovery without selecting a peculiar feature of the neural responses. This novel method can be used in both the development and assessment of different therapeutic strategies.

Distributed and Localized Dynamics Emerge in the Mouse Neocortex during Reach-to-Grasp Behavior.

A long-standing question in systems neuroscience is to what extent task-relevant features of neocortical processing are localized or distributed. Coordinated activity across the neocortex has been recently shown to drive complex behavior in the mouse, while activity in selected areas is canonically associated with specific functions (e.g., movements in the case of the motor cortex). Reach-to-grasp (RtG) movements are known to be dependent on motor circuits of the neocortex; however, the global activity of the neocortex during these movements has been largely unexplored in the mouse. Here, we characterized, using wide-field calcium imaging, these neocortex-wide dynamics in mice of either sex engaging in an RtG task. We demonstrate that, beyond motor regions, several areas, such as the visual and the retrosplenial cortices, also increase their activity levels during successful RtGs, and homologous regions across the ipsilateral hemisphere are also involved. Functional connectivity among neocortical areas increases transiently around movement onset and decreases during movement. Despite this global phenomenon, neural activity levels correlate with kinematics measures of successful RtGs in sensorimotor areas only. Our findings establish that distributed and localized neocortical dynamics co-orchestrate efficient control of complex movements.SIGNIFICANCE STATEMENT Mammals rely on reaching and grasping movements for fine-scale interactions with the physical world. In the mouse, the motor cortex is critical for the execution of such behavior, yet little is known about the activity patterns across neocortical areas. Using the mesoscale-level networks as a model of cortical processing, we investigated the hypothesis that areas beyond the motor regions could participate in RtG planning and execution, and indeed a large network of areas is involved while performing RtGs. Movement kinematics correlates mostly with neural activity in sensorimotor areas. By demonstrating that distributed and localized neocortical dynamics for the execution of fine movements coexist in the mouse neocortex during RtG, we offer an unprecedented view on the neocortical correlates of mammalian motor control.

Combining Optogenetic Stimulation and Motor Training Improves Functional Recovery and Perilesional Cortical Activity.

Background. An ischemic stroke is followed by the remapping of motor representation and extensive changes in cortical excitability involving both hemispheres. Although stimulation of the ipsilesional motor cortex, especially when paired with motor training, facilitates plasticity and functional restoration, the remapping of motor representation of the single and combined treatments is largely unexplored. Objective. We investigated if spatio-temporal features of motor-related cortical activity and the new motor representations are related to the rehabilitative treatment or if they can be specifically associated to functional recovery. Methods. We designed a novel rehabilitative treatment that combines neuro-plasticizing intervention with motor training. In detail, optogenetic stimulation of peri-infarct excitatory neurons expressing Channelrhodopsin 2 was associated with daily motor training on a robotic device. The effectiveness of the combined therapy was compared with spontaneous recovery and with the single treatments (ie optogenetic stimulation or motor training). Results. We found that the extension and localization of the new motor representations are specific to the treatment, where most treatments promote segregation of the motor representation to the peri-infarct region. Interestingly, only the combined therapy promotes both the recovery of forelimb functionality and the rescue of spatio-temporal features of motor-related activity. Functional recovery results from a new excitatory/inhibitory balance between hemispheres as revealed by the augmented motor response flanked by the increased expression of parvalbumin positive neurons in the peri-infarct area. Conclusions. Our findings highlight that functional recovery and restoration of motor-related neuronal activity are not necessarily coupled during post-stroke recovery. Indeed the reestablishment of cortical activation features of calcium transient is distinctive of the most effective therapeutic approach, the combined therapy.

Translational Stroke Research Review: Using the Mouse to Model Human Futile Recanalization and Reperfusion Injury in Ischemic Brain Tissue.

The approach to reperfusion therapies in stroke patients is rapidly evolving, but there is still no explanation why a substantial proportion of patients have a poor clinical prognosis despite successful flow restoration. This issue of futile recanalization is explained here by three clinical cases, which, despite complete recanalization, have very different outcomes. Preclinical research is particularly suited to characterize the highly dynamic changes in acute ischemic stroke and identify potential treatment targets useful for clinical translation. This review surveys the efforts taken so far to achieve mouse models capable of investigating the neurovascular underpinnings of futile recanalization. We highlight the translational potential of targeting tissue reperfusion in fully recanalized mouse models and of investigating the underlying pathophysiological mechanisms from subcellular to tissue scale. We suggest that stroke preclinical research should increasingly drive forward a continuous and circular dialogue with clinical research. When the preclinical and the clinical stroke research are consistent, translational success will follow.

Cortical propagation tracks functional recovery after stroke.

Stroke is a debilitating condition affecting millions of people worldwide. The development of improved rehabilitation therapies rests on finding biomarkers suitable for tracking functional damage and recovery. To achieve this goal, we perform a spatiotemporal analysis of cortical activity obtained by wide-field calcium images in mice before and after stroke. We compare spontaneous recovery with three different post-stroke rehabilitation paradigms, motor training alone, pharmacological contralesional inactivation and both combined. We identify three novel indicators that are able to track how movement-evoked global activation patterns are impaired by stroke and evolve during rehabilitation: the duration, the smoothness, and the angle of individual propagation events. Results show that, compared to pre-stroke conditions, propagation of cortical activity in the subacute phase right after stroke is slowed down and more irregular. When comparing rehabilitation paradigms, we find that mice treated with both motor training and pharmacological intervention, the only group associated with generalized recovery, manifest new propagation patterns, that are even faster and smoother than before the stroke. In conclusion, our new spatiotemporal propagation indicators could represent promising biomarkers that are able to uncover neural correlates not only of motor deficits caused by stroke but also of functional recovery during rehabilitation. In turn, these insights could pave the way towards more targeted post-stroke therapies.

Inactivation of the Medial Entorhinal Cortex Selectively Disrupts Learning of Interval Timing.

The entorhinal-hippocampal circuit can encode features of elapsed time, but nearly all previous research focused on neural encoding of "implicit time." Recent research has revealed encoding of "explicit time" in the medial entorhinal cortex (MEC) as mice are actively engaged in an interval timing task. However, it is unclear whether the MEC is required for temporal perception and/or learning during such explicit timing tasks. We therefore optogenetically inactivated the MEC as mice learned an interval timing "door stop" task that engaged mice in immobile interval timing behavior and locomotion-dependent navigation behavior. We find that the MEC is critically involved in learning of interval timing but not necessary for estimating temporal duration after learning. Together with our previous research, these results suggest that activity of a subcircuit in the MEC that encodes elapsed time during immobility is necessary for learning interval timing behaviors.

Experimental and Computational Study on Motor Control and Recovery After Stroke: Toward a Constructive Loop Between Experimental and Virtual Embodied Neuroscience.

Being able to replicate real experiments with computational simulations is a unique opportunity to refine and validate models with experimental data and redesign the experiments based on simulations. However, since it is technically demanding to model all components of an experiment, traditional approaches to modeling reduce the experimental setups as much as possible. In this study, our goal is to replicate all the relevant features of an experiment on motor control and motor rehabilitation after stroke. To this aim, we propose an approach that allows continuous integration of new experimental data into a computational modeling framework. First, results show that we could reproduce experimental object displacement with high accuracy via the simulated embodiment in the virtual world by feeding a spinal cord model with experimental registration of the cortical activity. Second, by using computational models of multiple granularities, our preliminary results show the possibility of simulating several features of the brain after stroke, from the local alteration in neuronal activity to long-range connectivity remodeling. Finally, strategies are proposed to merge the two pipelines. We further suggest that additional models could be integrated into the framework thanks to the versatility of the proposed approach, thus allowing many researchers to achieve continuously improved experimental design.

Analysis and Model of Cortical Slow Waves Acquired with Optical Techniques.

Slow waves (SWs) are spatio-temporal patterns of cortical activity that occur both during natural sleep and anesthesia and are preserved across species. Even though electrophysiological recordings have been largely used to characterize brain states, they are limited in the spatial resolution and cannot target specific neuronal population. Recently, large-scale optical imaging techniques coupled with functional indicators overcame these restrictions, and new pipelines of analysis and novel approaches of SWs modelling are needed to extract relevant features of the spatio-temporal dynamics of SWs from these highly spatially resolved data-sets. Here we combined wide-field fluorescence microscopy and a transgenic mouse model expressing a calcium indicator (GCaMP6f) in excitatory neurons to study SW propagation over the meso-scale under ketamine anesthesia. We developed a versatile analysis pipeline to identify and quantify the spatio-temporal propagation of the SWs. Moreover, we designed a computational simulator based on a simple theoretical model, which takes into account the statistics of neuronal activity, the response of fluorescence proteins and the slow waves dynamics. The simulator was capable of synthesizing artificial signals that could reliably reproduce several features of the SWs observed in vivo, thus enabling a calibration tool for the analysis pipeline. Comparison of experimental and simulated data shows the robustness of the analysis tools and its potential to uncover mechanistic insights of the Slow Wave Activity (SWA).

Combined Rehabilitation Promotes the Recovery of Structural and Functional Features of Healthy Neuronal Networks after Stroke.

Rehabilitation is considered the most effective treatment for promoting the recovery of motor deficits after stroke. One of the most challenging experimental goals is to unambiguously link brain rewiring to motor improvement prompted by rehabilitative therapy. Previous work showed that robotic training combined with transient inactivation of the contralesional cortex promotes a generalized recovery in a mouse model of stroke. Here, we use advanced optical imaging and manipulation tools to study cortical remodeling induced by this rehabilitation paradigm. We show that the stabilization of peri-infarct synaptic contacts accompanies increased vascular density induced by angiogenesis. Furthermore, temporal and spatial features of cortical activation recover toward pre-stroke conditions through the progressive formation of a new motor representation in the peri-infarct area. In the same animals, we observe reinforcement of inter-hemispheric connectivity. Our results provide evidence that combined rehabilitation promotes the restoration of structural and functional features distinctive of healthy neuronal networks.

Publisher Correction: Whole-Brain Vasculature Reconstruction at the Single Capillary Level.

A correction to this article has been published and is linked from the HTML and PDF versions of this paper. The error has been fixed in the paper.