Cortical propagation as a biomarker for recovery after stroke
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Abstract
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 compared 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 acute 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 act as biomarkers that are able to uncover neural correlates not only of motor deficits caused by stroke but also of functional recovery during rehabilitation. These insights could pave the way towards more targeted post-stroke therapies.
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###Reviewer #2
General assessment:
This study uses innovative analytical tools to characterise movement-evoked patterns in the cortex and evaluate functional recovery after stroke. They employ a motor task wherein a sliding platform that has to be pulled back by the mouse upon an acoustic cue to obtain a reward. Calcium-imaging cortical events are matched to force events. A propagation map is generated based on SPIKE-order: an asymmetric counter of threshold crossing coincidences between each and all pixels. Three propagation indicators are investigated: duration, angle and smoothness. These indicators show differences between healthy and stroke mice during the first and last three weeks of treatment.
The proposed SPIKE-order algorithm is a promising analytical tool to characterize brain dynamics in a variety of cortical functional …
###Reviewer #2
General assessment:
This study uses innovative analytical tools to characterise movement-evoked patterns in the cortex and evaluate functional recovery after stroke. They employ a motor task wherein a sliding platform that has to be pulled back by the mouse upon an acoustic cue to obtain a reward. Calcium-imaging cortical events are matched to force events. A propagation map is generated based on SPIKE-order: an asymmetric counter of threshold crossing coincidences between each and all pixels. Three propagation indicators are investigated: duration, angle and smoothness. These indicators show differences between healthy and stroke mice during the first and last three weeks of treatment.
The proposed SPIKE-order algorithm is a promising analytical tool to characterize brain dynamics in a variety of cortical functional imaging data. The terms 'spike' or 'synfire' do not correspond to the neuronal processes, but are used analogously referring to threshold crossings, and consistent spatiotemporal patterns of spike coincidence respectively. This analysis is highly versatile, being scale and parameter free, thus this approach must be empirically validated.
Major concerns:
My main concern with the study is in the use of these indicators to track recovery after stroke. There is no control group that received stroke but did not perform the task during the acute phase. An increase in oxygenation in the area over time due to collateral irrigation may account for the reported effects. Without the appropriate control, the recovery in propagation indicators cannot be attributed to motor rehabilitation.
Notably, there is no effect of training on changes to these indicators in healthy mice. Previous work by Makino et al. 2017 reported decreased duration of activity as learning progressed. Looking at spatial gradients of phase, Makino et al also found a secondary activity flow at later stages of training. The authors should provide reasons for the absence of these changes in their indicators of duration and angle.
There is no analysis on the frequency of action types to indicate behavioural recovery. This should be addressed in the discussion, but it may also suggest that these indicators have no relation to a longitudinal effect of the motor task.
The key to the status codes is missing. There are 7 discrete statuses of the robotic slide in total, but only status 3 is described. Also, the schedule for the acoustic cue within status 3 is unclear.
The nature of the reward for pulling is not specified. In the drawing in Figure 1, it looks like it could be water or sucrose. However, it is stated that mice are not water deprived. The difference in cortical activity between R and nR events is due solely to auditory cues and not voluntary action. It is important to know the nature of the reward to assess motivation and intention in the movement.
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###Reviewer #1
I enjoyed reading the paper by Cecchini et al. on using wide-field calcium imaging in mice to assess propagation of motor-related cortical network activity before and after focal photo-thrombotic stroke. The paper is well-written and relatively easy to follow because of the lengthy (perhaps even verbose and at times jargonny) explanations of the methods and results. The authors are clearly experts in the field, having published on the topic of stroke recovery in recent years, and in the methods employed, especially in the analysis approach, which they recently developed (cf. Allegra Mascaro et al., 2019). They also cite many of the relevant papers in the field. After decades of stroke research documenting various aspects of molecular or anatomical changes in circuits after stroke, studies such as this one that focus on …
###Reviewer #1
I enjoyed reading the paper by Cecchini et al. on using wide-field calcium imaging in mice to assess propagation of motor-related cortical network activity before and after focal photo-thrombotic stroke. The paper is well-written and relatively easy to follow because of the lengthy (perhaps even verbose and at times jargonny) explanations of the methods and results. The authors are clearly experts in the field, having published on the topic of stroke recovery in recent years, and in the methods employed, especially in the analysis approach, which they recently developed (cf. Allegra Mascaro et al., 2019). They also cite many of the relevant papers in the field. After decades of stroke research documenting various aspects of molecular or anatomical changes in circuits after stroke, studies such as this one that focus on alterations in network activity, are very important. The main technique used, single-photon calcium imaging through the skull of bulk signals on the cortical surface, is elegant in its simplicity and has clear advantages over similar wide-field imaging techniques using voltage sensors (which includes sub-threshold activity not related to action potentials) or intrinsic signals (which depend on blood flow/volume and are hard to interpret in the context of stroke). The authors then use sophisticated quantitative approaches to analyze three aspects of the propagation of cortical network activity (duration, smoothness, and angle) and how they are affected by stroke and by two rehabilitative strategies. The main findings can be summarized as follows: 1) These three indicators are stable over time (4 weeks) in healthy mice; 2) After stroke, network events last longer and are more chaotic (lower smoothness); 3) A combination of motor training and silencing the healthy hemisphere after stroke drastically alters these three parameters.
The main strengths of the paper, in my opinion, include the novelty of their analysis of wide-field calcium imaging in the context of stroke, especially when coupled with a rehabilitative strategy, and the results showing differences in propagation of activity between stroke and healthy controls. However, I have noted the following issues, some of which I consider serious.
One problem I encountered is that the authors do not provide sufficient data on the impact of stroke, both in terms of size/location and its impact on function (motor pull task), or about the pharmacological silencing approach. Although they refer to their previous paper (Allegra Mascaro 2019), I could not find clear answers there either.
My first recommendation is that the authors present data on the location and size of the infarcts they produced in each of the mice used in the present study. They should show at least a couple of histological examples of infarcts and, more importantly, a graph that plots infarct volume for all the individual mice (this could be in a suppl. figure), and ideally the location of the infarct with respect to the landmarks of M1. PT strokes can be quite variable, and one wonders whether some mice suffered large infarcts whereas in others they are negligible or may have missed M1 altogether.
Second, they should clarify in a lot more detail what the behavioral deficits are after such a stroke, if any, not just as detected by the robot task but also with other behavior assays. In the Allegra Mascaro paper, the plots in Fig. 1D indicate that normal control mice have gradual reductions in peak amplitude and in slope of the force over 5 days of training (whereas stroke mice do not), but it's not clear whether this is statistically significant. Moreover, in the Results section of that paper, they claim the "amplitude and slope of the force task (...) were not significantly different across groups." I believe the authors need to show their behavior data for this new cohort of mice. In fact, if they can't find significant deficits in forelimb function with the pull task after PT stroke, then the authors should clearly state that their robot assay is insensitive (which would seriously undermine the significance of their findings.) The present manuscript states that the combined treatment promotes "a generalized recovery of the forelimb dexterity" (line 358), but this is not supported by any data provided. If the authors are unable to provide behavior data, any statements about the robot task should be modified, if not removed. Solely referring to their 2019 paper is not appropriate, since this is an entirely new group of animals. I'm very much hoping that the authors actually have these data on behavioral performance across time for all mice in the study, because they would be in a position to actually correlate changes in pulling (amplitude, slope) with network activity data and provide a more robust narrative. However, Fig. 6 indicates that the effects of Rehab were the same for all types of events (F vs. nF, Act vs. Pass, or RP vs. nRP), which suggests that there is probably no correlation between training and network activity.
Third, regarding the BoNT/E experiments, neither the Allegra Mascaro 2019 paper, nor this one, provides any evidence that the procedure actually works as intended. The authors should either do in vivo wide-field calcium imaging in a subset of mice in the injected hemisphere to show that spontaneous and motor-related cortical activations are eliminated in toxin-injected mice (or some ephys in slices at the very least), with appropriate controls of course, such as a mice injected with vehicle or with denatured toxin. An important control that is currently missing is a BoNT/E alone group, without stroke (see comment #1 below).
Lastly, I am concerned about the sample size they use for statistics. Although they discuss the numbers of mice in their power analysis, all the plots they show include many more individual points than the number of mice (what are those, FOVs? events?). The preferred sample size would be to use the number of mice. I believe the authors should show the data (and perform statistics) only for individual mice. Otherwise they need to justify why they didn't do stats with n= # mice.
Other comments (not necessarily minor):
I agree that the pattern of activity is different in the Rehab group (presumably an effect of silencing the contralesional, healthy hemisphere). But, since it is also very different from the pattern of propagation in healthy control mice (or pre-stroke baseline), it is also possible that this is also a pathologic pattern, not necessarily reflecting a "new functional efficacy (line 358-9). The authors should comment on this possibility in the Discussion, namely that Rehab did not restore activity to a control pattern, but to a different pattern altogether. This will be easier once they analyze a BoNT/E control group in which mice are injected with BoNT but do not receive a stroke. This is a critical control that will allow the reader to determine whether the effects they see in the Rehab group reflect adaptive plasticity to restore functional connectivity, or simply disconnection from the silenced hemisphere.
Regarding the standardized maps for cortical brain regions in Fig. 1, the authors should explain in more detail how the imaging fields of view (FOV) were superimposed and aligned to the contours; it is briefly described in terms of aligning to Bregman and Lambda, but more information would help if there is concern for animal to animal variability (being off by 3 pixels in any direction is >0.5 mm.) In Fig. 1d it looks like the imaging field of view is actually quite caudal, with very little motor cortex included. Is this a typical representation or was there some variability from animal to animal in the location of the imaging FOV? I recommend that the authors provide the exact location of the imaging FOV rectangle for each animal and an outline of where the PT stroke was located in the same figure. I would also recommend redrawing the contours that demarcate brain regions in Fig. 1c and d so that they do not appear so thick.
I was surprised that spatiotemporal dynamics of the calcium signals did not change with learning the task; the authors suggest this is because mice learn the task so quickly (line 401-8). I wonder if, alternatively, the reason is because they don't learn at all (since they did not report significant differences across days in control mice in their 2019 paper) or because it doesn't require learning. The robot task extends the forelimb into an uncomfortable position and the mice may simply reflexively pull it back into a more comfortable resting position.
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##Preprint Review
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###Summary:
The reviewers were both very enthusiastic about the novelty and potential application of the calcium imaging technique. However, some major issues were raised that dampened the enthusiasm of the paper. Some of the key issues raised were that essential controls are missing, key measurements (behavioral) of post-stroke recovery are not provided, there are some questions about the statistics that were applied to the data, and the sample size used in the experiments was also an area of question.
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