The temporal neurovascular coupling response remains intact during sinusoidal hypotensive and hypertensive challenges

Introduction. Neurovascular coupling (NVC) describes the coupling of neuronal metabolic demand to blood supply, which has shown to be impaired with chronic hypertension, as well as with prolonged hypotension. However, it is unknown the extent the NVC response remains intact during transient hypo- and hyper-tensive challenges. Methods. Fifteen healthy participants (9 females/6 males) completed a visual NVC task (‘Where’s Waldo?’) over two testing sessions, consisting of cyclical 30 s eyes closed and opened portions. The Waldo task was completed at rest (8 min) and concurrently during squat-stand maneuvers (SSMs; 5 min) at 0.05 Hz (10 s squat/stand) and 0.10 Hz (5 s squat-stand). SSMs induce 30–50 mmHg blood pressure oscillations, resulting in cyclical hypo- and hyper-tensive swings within the cerebrovasculature, allowing for the quantification of the NVC response during transient hypo- and hyper-tension. Outcome NVC metrics included baseline, peak, relative increase in cerebral blood velocity (CBv), and area-under-the-curve (AUC30) within the posterior and middle cerebral arteries indexed via transcranial Doppler ultrasound. Within-subject, between-task comparisons were conducted using analysis of variance with effect size calculations. Results. Differences were noted between rest and SSM conditions in both vessels for peak CBv (all p < 0.045) and the relative increase in CBv (all p < 0.049) with small-to-large effect sizes. AUC30 metrics were similar between all tasks (all p > 0.090) with negligible-to-small effect sizes. Conclusions. Despite the SSMs eliciting ∼30–50 mmHg blood pressure oscillations, similar levels of activation occurred within the neurovascular unit across all conditions. This demonstrated the signaling of the NVC response remained intact during cyclical blood pressure challenges.

[1]  Jia Liu,et al.  Transfer function analysis of dynamic cerebral autoregulation: A CARNet white paper 2022 update , 2022, Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism.

[2]  J. Smirl,et al.  Time course recovery of cerebral blood velocity metrics post aerobic exercise: A systematic review. , 2022, Journal of applied physiology.

[3]  Ibukunoluwa K. Oni,et al.  Neurovascular coupling on trial: How the number of trials completed impacts the accuracy and precision of temporally derived neurovascular coupling estimates , 2022, Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism.

[4]  C. Iadecola,et al.  Revisiting the neurovascular unit , 2021, Nature Neuroscience.

[5]  P. Ainslie,et al.  Losing the dogmatic view of cerebral autoregulation , 2021, Physiological reports.

[6]  D. Thijssen,et al.  REGULATION OF CEREBRAL BLOOD FLOW IN HUMANS: PHYSIOLOGY AND CLINICAL IMPLICATIONS OF AUTOREGULATION. , 2021, Physiological reviews.

[7]  J. Smirl,et al.  What recording duration is required to provide physiologically valid and reliable dynamic cerebral autoregulation transfer functional analysis estimates? , 2021, Physiological measurement.

[8]  J. Smirl,et al.  Temporal evolution of neurovascular coupling recovery following moderate‐ and high‐intensity exercise , 2021, Physiological reports.

[9]  J. Smirl,et al.  Comparison of diurnal variation, anatomical location, and biological sex within spontaneous and driven dynamic cerebral autoregulation measures , 2020, Physiological reports.

[10]  L. Vianna,et al.  Neurovascular Coupling is Not Influenced by Lower Body Negative Pressure in Humans. , 2020, American journal of physiology. Heart and circulatory physiology.

[11]  J. Smirl,et al.  Dynamic cerebral autoregulation across the cardiac cycle during 8 hr of recovery from acute exercise , 2020, Physiological reports.

[12]  A. Malhotra,et al.  The Neurovascular Unit: Effects of Brain Insults During the Perinatal Period , 2020, Frontiers in Neuroscience.

[13]  L. Halsey The reign of the p-value is over: what alternative analyses could we employ to fill the power vacuum? , 2019, Biology Letters.

[14]  S. Greenland,et al.  Scientists rise up against statistical significance , 2019, Nature.

[15]  J. Claassen,et al.  CrossTalk opposing view: dynamic cerebral autoregulation should be quantified using induced (rather than spontaneous) blood pressure fluctuations , 2017, The Journal of physiology.

[16]  R. Alarcón,et al.  Non‐normal data: Is ANOVA still a valid option? , 2017, Psicothema.

[17]  K. Takakusaki Functional Neuroanatomy for Posture and Gait Control , 2017, Journal of movement disorders.

[18]  J. Smirl,et al.  Where’s Waldo? The utility of a complicated visual search paradigm for transcranial Doppler-based assessments of neurovascular coupling , 2016, Journal of Neuroscience Methods.

[19]  A. Krassioukov,et al.  Neurovascular coupling in humans: Physiology, methodological advances and clinical implications , 2016, Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism.

[20]  Y. Tzeng,et al.  Methodological comparison of active- and passive-driven oscillations in blood pressure; implications for the assessment of cerebral pressure-flow relationships. , 2015, Journal of applied physiology.

[21]  P. Ainslie,et al.  Transcranial Doppler ultrasound: valid, invalid, or both? , 2014, Journal of applied physiology.

[22]  Can Ozan Tan,et al.  Relative Contributions of Sympathetic, Cholinergic, and Myogenic Mechanisms to Cerebral Autoregulation , 2014, Stroke.

[23]  Joseph A Fisher,et al.  Integrative regulation of human brain blood flow , 2014, The Journal of physiology.

[24]  Daniël Lakens,et al.  Calculating and reporting effect sizes to facilitate cumulative science: a practical primer for t-tests and ANOVAs , 2013, Front. Psychol..

[25]  J. Hamner,et al.  The role of myogenic mechanisms in human cerebrovascular regulation , 2013, The Journal of physiology.

[26]  D. Attwell,et al.  Glial and neuronal control of brain blood flow , 2022 .

[27]  Michael A. Cohen,et al.  Sympathetic Control of the Cerebral Vasculature in Humans , 2010, Stroke.

[28]  Gordon H Guyatt,et al.  Design, analysis, and presentation of crossover trials , 2009, Trials.

[29]  N. Samani,et al.  Influence of noninvasive peripheral arterial blood pressure measurements on assessment of dynamic cerebral autoregulation. , 2007, Journal of applied physiology.

[30]  Karen Peebles,et al.  Early morning impairment in cerebral autoregulation and cerebrovascular CO2 reactivity in healthy humans: relation to endothelial function , 2007, Experimental physiology.

[31]  C. Julien The enigma of Mayer waves: Facts and models. , 2006, Cardiovascular research.

[32]  R. Bakeman Recommended effect size statistics for repeated measures designs , 2005, Behavior research methods.

[33]  R. Panerai,et al.  The critical closing pressure of the cerebral circulation. , 2003, Medical engineering & physics.

[34]  G Neil-Dwyer,et al.  Assessment of autoregulation by means of periodic changes in blood pressure. , 1995, Stroke.

[35]  G Parati,et al.  Spectral and sequence analysis of finger blood pressure variability. Comparison with analysis of intra-arterial recordings. , 1993, Hypertension.

[36]  M. Fog THE RELATIONSHIP BETWEEN THE BLOOD PRESSURE AND THE TONIC REGULATION OF THE PIAL ARTERIES , 1938, Journal of neurology and psychiatry.

[37]  R. Mack,et al.  Estimates , 2018, The Bayesian Way.

[38]  Y. Tzeng,et al.  CrossTalk proposal: dynamic cerebral autoregulation should be quantified using spontaneous blood pressure fluctuations , 2018, The Journal of physiology.

[39]  Rong Zhang,et al.  Dynamic cerebral autoregulation during repeated squat-stand maneuvers. , 2009, Journal of applied physiology.

[40]  Transcranial Doppler Ultrasound: Technique and Application , 2022 .