J Physiol 591.10 (2013) pp 2379–2380 2379

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Be still my beating brain –reduction of brain micromotionduring in vivo two-photonimaging

Catharine G. Clark1, Galen J. Marchetti1

and Colin N. Young2

1Department of Biomedical Engineering,College of Engineering, Cornell University,Ithaca, NY, USA2Department of Biomedical Sciences,College of Veterinary Medicine, CornellUniversity, Ithaca, NY, USA

Email: cgc79@cornell.edu

In light of the incredible complexityof the brain, the study of neuralphysiology in health and disease pre-sents many challenges. However, with theadvancement of powerful imaging tools,such as two-photon excitation fluorescencemicroscopy (2PEFM), we now have theopportunity to glimpse into the innerworkings of the brain with high spatialand temporal resolution (Denk et al. 1990).This advanced imaging technique allows forexamination of dynamic interactions andactivity of cellular sub-types (e.g. microglia,astrocytes, neurons) and the surroundingbrain microvasculature (Helmchen & Denk,2005). While the advantages are many, amajor challenge in capturing undistortedhigh-resolution images is the inherent rapidmicromotion caused by respiration andheartbeat. In a recent issue of The Journalof Physiology, Paukert & Bergles (2012)present a novel methodology to overcomethis confounding movement and enhancethe 2PEFM imaging resolution of cellularstructures.

Previous attempts to correct for brainmicromotion, due to vital physiologicalfunctions, have included complex andinvasive techniques such as muscle paralysis,cardiopulmonary bypass, and animalintubation. While these approaches mayreduce micromotion they have profoundeffects on normal physiological function –ultimately confounding the very purposeof functional studies. In addition tophysical attempts to improve specimenstability, post-imaging analysis is frequentlyincorporated, involving complex imagemanipulation. For example, many studiesfit images to a Hidden Markov Model,

a common statistical tool used in avariety of biomedical imaging contextsto extract data from noisy images(Dombeck et al. 2007; Chen et al. 2010).Statistical analyses such as these are highlyuseful, although they frequently requiremathematical assumptions and don’t reachthe authenticity of pure image data.Moreover, not all motion artifacts can becorrected with existing statistical models,as micromotion displacements that occurduring the acquisition of individual frames(such as those caused by heartbeats) aredifficult to correct post hoc. More recently,Laffray et al. (2011) developed an approachto eradicate micromotion by using anoptical stabilization sensor to dynamicallyrefocus the objective onto the plane of inter-est, while monitoring the position of theanimal. Although this may improve imagestability, the device is costly and has yet tobe implemented in commercial systems. Assuch, Paukert & Bergles (2012) sought todesign and develop a cost-effective imagingapproach to reduce in-frame variability,improve overall resolution and increaseimage stability.

Transgenic anaesthetized mice were usedto image the cellular architecture of neuro-nal processes in cortical regions. 2PEFMimaging of dendrites was first performedby rapidly scanning one focal plane, astraditionally done. The authors found thatmotion artifacts were still present evenwhen commonly used post hoc imageregistration was performed. Such artifactsled to movements of entire dendritic spinesup to 1.5 μm, or shifts of ∼10% ofthe entire field of view, which producesprofound limitations when imaging finerdetails of neural dendrites (Chen et al. 2011).Interestingly, comparing images that wereacquired at the same time in the cardiac cyclesignificantly reduced the image distortions.These findings suggest that the beating ofthe heart is the major contributor to imagedistortion.

In order to control for brain micro-motion caused by the beating of theheart, acquisition of individual framescans were synchronized to the cardiaccycle. Specifically, each scan was triggeredwhen an electrocardiogram (ECG) signalexceeded a set voltage, which occurredonly during the R-wave of the cardiaccycle. Using this approach, the authors

demonstrate that the dissimilarity betweenconsecutively taken images was significantlyreduced by R-wave-triggered scanning,compared to traditional non-discriminantscanning. This technique was also beneficialin reducing image distortion whenconsecutive sub-frames (1/10 of a fullframe due to heartbeat triggered scanning)were interlaced and image stacks wereconstructed from multiple focal planes.Removing frames that were acquiredduring respiratory movement did notfurther improve image quality, supportingthe claim that micro-displacements ofdendritic spines are primarily due to thebeating heart. Collectively, the findings ofPaukert & Bergles (2012) demonstrate thatsyncing 2PEFM acquisition with cardiacactivity improves image stability and spatialresolution.

In addition to demonstrating thatthe majority of in-frame neural tissuemovements are due to heartbeat-induceddistortions, this methodological approachmay help facilitate the use of 2PEFMin a number of major areas. First, thenovelty of this approach is that relianceon probabilistic assumptions is reduced,increasing the objectivity of highly sensitivedata. Paukert and Bergles demonstrate thatthe image stability of small neural structures(dendritic spines) can be enhanced throughthe use of cardiac-triggered 2PEFMacquisition. In this regard, 2PEFM offersthe ability to track morphological changesof individual dendritic spines over timeperiods of minutes to months (Hofer et al.2008). Coupling ECG-based scanning andenhanced imaging stability, with studies ofthe synaptic structural plasticity, may greatlyenhance our understanding of the workingsof neuronal processes. Indeed, alterations inthe reorganization and dynamic turnover ofsynapses has been linked to the developmentof the nervous system, to processing ofexperiences (e.g. learning) and neuro-degenerative conditions, such as memoryloss (Pan & Gan, 2008). Furthermore,2PEFM absorption technology allows formicrometre scale disruption of biologicalprocesses, permitting the removal ofsub-micrometre structures. However,ablation and photolysis rely on focusingthe laser beam to a fixed point in spaceand are therefore highly sensitive totissue movements. Cardiac-triggered

C© 2013 The Authors. The Journal of Physiology C© 2013 The Physiological Society DOI: 10.1113/jphysiol.2013.253138

2380 Journal Club J Physiol 591.10

ablation techniques, implementingPaukert and Bergles’ methodology,may facilitate and stabilize a widerange of ablation experiments, therebyenhancing our understanding of physio-logical/pathophysiological structures andprocesses.

Aside from enhancing image stability,the approaches employed by Paukert& Bergles (2012) may also aid studiesfocused on the functional aspects ofsingle neuronal synapses. For example,2PEFM photostimulation and uncaging ofneurotransmitters (e.g. glutamate), permitsthe stimulation of individual synapses.Moreover, studies designed to investigatenetwork activity rely on measuring calciumcurrents as a functional output. Whilethe majority of these studies have beenperformed in vitro due to image stabilityissues, advancements have been made invivo (e.g. Noguchi et al. 2011). Importantly,it is well known that anaesthesia hasa profound effect on neural activityand it is evident that the design ofstudies will have to evolve to includeconscious animals. In this regard, Dombecket al. (2007) demonstrated an awake2PEFM imaging preparation, which allowsfor investigation of neuronal structuresand calcium imaging under resting andrunning conditions. While considered asignificant advancement, a major hurdleregarding this particular animal preparationwill be overcoming mechanical movementartifacts. The authors themselves notedthat this preparation could work wellin conjunction with motion-correctingsoftware. In short, as optical techniques andin vivo preparations continue to advance,consideration of the beating of the hearton functional outcomes will need to beaddressed and as such, Paukert and Bergles’approach may prove to be beneficial.

While this methodology advances thepotential uses of 2PEFM, triggering imagingscans by cardiac activity inherently limitstemporal resolution. Paukert & Bergles(2012) worked with a high frame acquisitionrate of 6.2 Hz on mice with a heartrate around 8.7 Hz. As such, cardiactriggered image acquisition had to beinterrupted mid-scan. As mentioned bythe authors, faster scanning techniquesand interlacing subsequent scans to createan entire image frame may reduce thisissue, but information will still unavoidablybe lost during cardiac activity. While

this is likely not to be an issue formore stable structures (dendrites) or evendynamic cellular movements (microglia),it may be a concern when imaging fast,beat-to-beat physiological changes. Indeed,2PEFM has revealed pulsatile changes incortical blood flow, coinciding with thecardiac cycle (Santisakultarm et al. 2012).Therefore, 2PEFM examinations of cerebralmicrovascular flow and/or neural–vascularcoupling may not warrant the use ofheartbeat-focused image acquisition, ascrucial data may be lost.

Beyond the brain, continual technologicaladvancements of 2PEFM havedemonstrated the utility of this techniquefor in vivo imaging, from the spinal cordto pancreatic β cells (Dunn & Sutton,2008). While each examination presentsunique challenges, image stability remainsa confounding factor for all of them.The brain in fact contends with theleast amount of micromotion due tothe structural confinements of the skull,whereas other areas are mechanically drivenby respiratory and cardiac movements andare susceptible to image shifts of up to tensof micrometres. Indeed, 2PEFM studiesexamining mitochondrial function, physio-logical coupling and calcium currents incardiac myocytes have been performed inLangendorff-perfused heart preparationsto reduce the interference of physiologicalprocesses. Similarly, ex vivo preparationshave been used to study other organs,such as the lung (Dunn & Sutton, 2008).It is therefore clear that the ECG-basedacquisition of image frames, as outlinedby Paukert & Bergles (2012), may proveto be beneficial for future examinationsdeeper within and outside of cortical brainregions.

In summary, Paukert & Bergles (2012)have provided an effective methodologyto still the beating brain. The use ofthis technique, in conjunction with othermovement correction strategies, may havewide ranging applicability and aid in ourunderstanding of the complex physiologyof the brain and beyond in both health anddisease.

References

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Acknowledgements

The authors would like to thank Dr ChrisB. Schaffer (Department of BiomedicalEngineering, Cornell University) for hisinsightful comments.

C© 2013 The Authors. The Journal of Physiology C© 2013 The Physiological Society