Clarity of the rhythmic brainstem (2020)

Controversy, novel animal models/preparations and new techniques can all advance science. This could not be more true for understanding the neural mechanisms generating the respiratory pattern and rhythm. Given the plethora of diseases related to respiratory rhythm/pattern dysfunction (for example, sudden infant death, sleep apnoea, Rett syndrome, congenital central hypoventilation syndrome) this is an important clinical topic. It is also a fascinating area for discovering the intricacies of neural network dynamics and emerging properties required to sustain robust rhythm generation that is critical from the first to the last breath of life. Indeed, much remains undiscovered about how the respiratory central pattern generator transforms itself during different physiological states (e.g. sleep, swallowing), when executing defensive reflexes (e.g. cough, emesis, gag, gasp) and in pathological conditions such as those listed above. Defining the respiratory neural circuit within the brain has been an aim for many. The most intensive research has focused on the brainstem (Del Negro et al. 2018). Developmental studies identifying transcription factors controlling the rhombomeric organisation and function of distinct respiratory cell groups within the brainstem is one example (Thoby-Brisson et al. 2009). Neuroanatomical studies have contributed to defining cell cytoarchictectures, phenotypes and connectivity. Brainstem transection studies using physical cuts, lesions, pharmacological blockade or genetic interventions to silence selective neuronal populations have all helped define the brainstem regions necessary for different respiratory motor patterns as well as some of the synaptic and intrinsic mechanisms that are important for generating distinct respiratory rhythms (e.g. Smith et al. 2007; Marina et al. 2010). Single and paired unit recording studies from specific brainstem regions revealed respiratory neurone types and their connectivity defining them as propriobulbar or spinally projecting, for example. After labelling, respiratory neurones can be classified by neurochemical phenotype. The synaptic interactions between respiratory neurones has been studied using iontophoresis and intracellular recording. Electrode array recordings of multiple respiratory neurones simultaneously throughout the brainstem have been used to identify functional connectivity, and aspects of its dynamics, on a much larger scale (Lindsay et al. 2012). Mathematical models have permitted an integration of this information and have been essential for our understanding of respiratory rhythm neurogenesis as well as driving novel insights and predictions (Molkov et al. 2017). With the advent of in vitro preparations of neonatal rodents (respiratory rhythmic slices) and en bloc brainstem and brainstem–spinal cord preparations, as well as arterially perfused preparations, numerous attempts were made to visualise the activity of the brainstem respiratory network. This has involved calcium (e.g. Onimaru et al. 2018) or voltage-sensitive dyes and allowed a realisation of the temporal and spatial properties of the rhythmically active network under different states. But these studies were compromised as only a part of the network could be visualised at any one time and restricted to superficial regions. Therefore, there has never been a three-dimensional view of the functioning respiratory neural network of the entire brainstem. The study by Dhingra et al. (2020) has addressed this shortfall by demonstrating the dynamics of activity/inactivity of neuronal populations from the complete ponto-medullary respiratory network of single rats in real time. Using the in situ arterially perfused preparation of rat, which generates a three-phase respiratory motor pattern of inspiration, post-inspiration (first stage of expiration) and stage two expiration, the authors used state-of-the-art silicon-based ultrafine multi-electrode array technology to record macroscopic local field potentials from 196–364 sites per rat with known anatomic coordinates in three-dimensional space. The array could be re-positioned along the rostro-caudal axis of the brainstem so that in any animal the location of the contact electrodes covered the brainstem volume containing the respiratory network. With bespoke analysis, the temporal and spatial activity of the network in three dimensions could be visualised as it related to both inspiration (via a phrenic nerve) and post-inspiration (via a vagus nerve). The study is analogous to the Clarity procedure where brain volumes are made transparent to allow visualisation of a defined neuronal network. However, unlike Clarity, Dhingra et al.’s (2020) study also adds the electrical activity to the network and hence provides Clarity of the rhythmic brainstem. Given its fundamental importance to the interpretation of this research, it is worth discussing exactly what has been recorded. The substrate that forms a macroscopic local field potential is most likely a summation of slow synaptic potentials. Synchronous synaptic activity is maximal between respiratory phases, which accounts for the maximal potentials recorded at the respiratory phase transitions. The question then arises as to the catchment volume of these potentials. Although influenced by the characteristics of the recording electrodes, the authors estimate a volume radius of around 400 μm, which for a rat brain is quite a substantial amount of brain tissue. Clearly, future refinement of the recording technology may minimise this thereby giving greater spatial resolution. Notwithstanding this limitation, the types of data generated are discussed below. Respiratory activity was revealed across brain volumes located within the dorsomedial and ventrolateral medulla, and dorsal pontine regions that map on to the nucleus tractus soliatarii (dorsal respiratory column), the pre-Bötzinger and Bötzinger complexes and rostral ventral respiratory group, and the Kölliker Fuse, respectively. Whilst not surprising, these important data ratified the novel approach of functional three-dimensional brain mapping and in that sense formed a crucial component of the study. The authors found that the macroscopic local field potentials were greatest at the transitions between the three respiratory phases: inspiration to post-inspiration, post-inspiration to stage two expiration and stage two expiration to inspiration. This indicates that the greatest energy within the respiratory rhythmic brainstem occurs at the phase transitions, and not during the respiratory phases themselves. Given that the phase transitions are transient in time, this makes the brainstem respiratory central pattern generator relatively energy efficient. Another finding was that only the inspiration–post-inspiration transition occurs across the entire ponto-medullary network. Whether primary activity or an efference copy, this reflects the critical physiological importance of this transition. Examples include: a mechanism for switching off inspiration and initiating the expiration phase; airflow control through the airway giving adequate time for oxygen uptake; production of respiratory sinus arrhythmia via cardiac vagal neurone regulation and modulation of sympathetic bursting for effective arteriolar tone development. It also signals a fundamental importance of post-inspiration as a major component of the machinery generating the respiratory pattern and indeed the prevention of apneusis – a potentially fatal condition locking the system in inspiration. An intriguing question remains: which of the three phases initiates the respiratory cycle? The dynamics portrayed in the online three-dimensional brainstem model (put in weblink) are fascinating and revealing. Indeed, a hitherto unknown aspect of brainstem rhythmic activity was identified. Macroscopic local field potentials within the dorsal respiratory column occurred during the post-inspiration–stage two expiration transition. This information essentially demarks the two periods of expiration but its purpose remains unclear. Together with the inspiratory activity generated in this region, representation of all three phases would be present in this localised network. This may be important for gating incoming sensory information from the periphery such that onward transmission becomes respiratory phase modulated. Finally, given that the dorsal respiratory column contains neurones that convey information to the spinal cord, it has the potential to provide descending respiratory rhythmic drives to distinct populations of respiratory motor neurones. In sum, volumetric electrical mapping of the ponto-medullary respiratory network provides insights into the function of the neuroanatomy of the respiratory pattern generator. The approach will offer fundamental novel insights into the state-dependency of the dynamics of respiratory phase production, duration and phase-switching. It now permits the potential to disentangle how the respiratory network re-configures during physiological challenges such as during heightened chemical drive, sleep states but also disease conditions, and in doing so will help to resolve existing controversies. None declared Health Research Council of New Zealand 19/687 Marsden, Royal Society of New Zealand 18-UOA-219.