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Evolving Our Understanding of The Neural Control of Breathing Jeff Mendenhall College of William and Mary Department of

Evolving Our Understanding of The Neural Control of Breathing Jeff Mendenhall College of William and Mary Department of Applied Sciences, Room #314. Outline. Why Investigate Breathing Review Standard Model Shortcomings of the Standard Model The Next Step

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Evolving Our Understanding of The Neural Control of Breathing Jeff Mendenhall College of William and Mary Department of

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  1. Evolving Our Understanding ofThe Neural Control of BreathingJeff MendenhallCollege of William and MaryDepartment of Applied Sciences, Room #314

  2. Outline • Why Investigate Breathing • Review • Standard Model • Shortcomings of the Standard Model • The Next Step • Dealing with the Problem of Detailed Models • Where to from here

  3. Our Motivation • Necessity of breathing • Stroke/Disease-induced lesions can impair breathing • CCHS and other disorders of the control of breathing

  4. Outline • Why Investigate Breathing • Review • Standard Model • Shortcomings of the Standard Model • The Next Step • Dealing with the Problem of Detailed Models • Where to from here

  5. System Overview • Neural Control of Inspiration Takes Place in the preBötzinger Complex (preBötC) 1 preBötC XII Nerve Muscles

  6. Terminology Inspiratory burst (raw) Inspiratory burst (smoothed) Inspiratory drive potential amplitude area

  7. Outline • Why Investigate Breathing • Review • Standard Model • Shortcomings of the Standard Model • The Next Step • Dealing with the Problem of Detailed Models • Where to from here

  8. Standard Model • Assumptions: Effectively Isospatial Currents Present: INaP, INaF, IK, IL, Itonic-e, Isyn • Predictions: “Pacemaker” neurons and INaP Essential for Network-Level Bursts

  9. Outline • Why Investigate Breathing • Review • Standard Model • Shortcomings of the Standard Model • The Next Step • Dealing with the Problem of Detailed Models • Where to from here

  10. Problems with the Standard Model I • Assumptions: Effectively Isospatial • Currents Present: INaP, INaF, IK, IL, Itonic-e + ICAN, Ih, IA, INMDA, IGABA

  11. Problems with the Standard Model II • Predictions: “Pacemaker” neurons and INaP are Essential for Network Functioning -Pace, Mackay, Feldman, and Del Negro, J. Physiology, 582: 113-125 2007. 3 -Del Negro, Morgado-Valle. Mackay, and Feldman, J. Neuroscience, 25(2): 446-53.4 -Del Negro, Morgado-Valle, and Feldman, Neuron 34: 821- 30, 2002.5

  12. Outline • Why Investigate Breathing • Review • Standard Model • Shortcomings of the Standard Model • The Next Step • Dealing with the Problem of Detailed Models • Where to from here

  13. Dendritic Compartment Somatic Compartment The Next Step I • Correct Isospatial Assumption • Use Realistic • gNaP Conductance • Add Other Currents

  14. The Next Step II • Add mGluR-IP3-Ca2+-ICAN pathway

  15. The Next Step III: • Add material balance for Ca2+ and Na+ Example: Ca2+ Balance

  16. The Next Step IV • Add calcium microdomains

  17. Outline • Why Investigate Breathing • Review • Standard Model • Shortcomings of the Standard Model • The Next Step • Dealing with the Problem of Detailed Models • Where to from here

  18. The Problem: Dendritic Compartment Somatic Compartment Too Many Poorly Constrained Parameters

  19. Methods: Evolving SolutionsStep 2: Sit back, relax, let the computer do the work

  20. Methods: Evolving SolutionsStep 1: Teach the Fitness Function What is Important Score: 100 Score: -5 (Kill) Score: 40 Score: 50 Fitness Function Score: -30 (Kill)

  21. What Is a Fitness Function Anyway? A weighted sum of fitness measures

  22. Inside the Black Box Trace Statistics Spike/Burst Analyzer Traces Determine Kill Conditions Scores Stable, Bounded Linear Regression Surviving Traces Fitness Parameters

  23. Advantages of Evolutionary Algorithm • Efficiently Handles Large Parameter Spaces • Yields Many Good Regions • Approximates Their Boundaries

  24. Preliminary Results • Problem: Fit the current model to 4 experiment traces • Number of Parameters: 110

  25. Some Evolved Solutions Ideal Curve

  26. V (Dend) Ca2+(Dend) ICAN Ca2+ From Stores

  27. Outline • Why Investigate Breathing • Review • Standard Model • Shortcomings of the Standard Model • The Next Step • Dealing with the Problem of Detailed Models • Where to from here

  28. Future Directions • Add More Experiments • Adjust Parameter Ranges • Make / Test Predictions

  29. Acknowledgements Academic Dr. Christopher Del Negro (C. W&M) Dr. Pete Roper (U. Utah) Financial NSF Grant IOB-0616099 Suzzane Matthews Faculty Research Award

  30. References • Smith, J.C., Ellenberger, H.H., Ballanyi, K., Richter, D.W. & Feldman, J.L. “Pre-Bötzinger complex: a brainstem region that may generate respiratory rhythm in mammals.” Science 254, 726-9 (1991). • Rekling, J.C., Champagnat, J. & Denavit-Saubie, M. (1996) “Electroresponsive properties and membrane potential trajectories of three types of inspiratory neurons in the newborn mouse brain stem in vitro.” J Neurophysiol 75, 795-810. 3. Ryland W. Pace, Devin D. Mackay, Jack L. Feldman, and Christopher A. Del Negro (2007). “Cellular And Synaptic Mechanisms That Generate Inspiratory Drive Potentials In Pre-Bötzinger Neurons In Vitro.” J. Physiology 582: 113-125 2007. 4. Del Negro, C. A., C. Morgado-Valle, et al. (2005). "Sodium and Calcium Current-Mediated Pacemaker Neurons and Respiratory Rhythm Generation." J. Neurosci. 25(2): 446-453. 5. Del Negro, C. A., N. Koshiya, et al. (2002). "Persistent sodium current, membrane properties and bursting behavior of pre-botzinger complex inspiratory neurons in vitro." J Neurophysiol 88(5): 2242-50.

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