Evolving Our Understanding of The Neural Control of Breathing Jeff Mendenhall College of William and Mary Department of Applied Sciences, Room #314
Jan 05, 2016
Evolving Our Understanding ofThe Neural Control of Breathing
Jeff MendenhallCollege 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• Dealing with the Problem of Detailed Models• Where to from here
Our Motivation• Necessity of breathing
• Stroke/Disease-induced lesions can impair breathing
• CCHS and other disorders of the control of breathing
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
System Overview
• Neural Control of Inspiration Takes Place in the preBötzinger Complex (preBötC) 1
QuickTime™ and aTIFF (Uncompressed) decompressor
are needed to see this picture.
preBötC
XII Nerve
Muscles
TerminologyInspiratory
burst (raw)
Inspiratory burst
(smoothed)
Inspiratory drive
potential
amplitude area
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
Standard Model
• Assumptions: Effectively Isospatial
Currents Present:
INaP, INaF, IK, IL, Itonic-e, Isyn
• Predictions: “Pacemaker” neurons and INaP Essential for Network-Level Bursts
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
Problems with the Standard Model I
• Assumptions: Effectively Isospatial
• Currents Present: INaP, INaF, IK, IL, Itonic-e
+ ICAN, Ih, IA, INMDA, IGABA
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
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
The Next Step I
• Correct Isospatial Assumption
• Use Realistic gNaP ConductancegNMDA
gAMPA
INaK
gK
gCa
gL (K,Na,Ca)
ICa-ATP
gA
gtonic
gelec
gCAN
CDendrite
gNaP
INaK
gK
gK(Ca)
gL(K,Na,Ca)
ICa-ATP
gH
gNaF
CSoma
gCa
EK,Na,Ca
ECa ECa
ECAN
ESyn-Ex
ESyn-Ex
EK
EK
EK EK
EH
EAv. Neighbor
ESyn-Ex
ENa
ENa
EK,Na,Ca
gCDendritic Compartment Somatic Compartment
• Add Other Currents
The Next Step II
QuickTime™ and aTIFF (Uncompressed) decompressor
are needed to see this picture.
• Add mGluR-IP3-Ca2+-ICAN pathway
The Next Step III:
• Add material balance for Ca2+ and Na+
Example:
Ca2+ BalanceJIP3
JCaER-Leak
JNa+/Ca2+
Exchanger
JCaER-Leak
JNa+/Ca2+
Exchanger
The Next Step IV• Add calcium microdomains
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
The Problem: Too Many Poorly Constrained Parameters
Dendritic Compartment Somatic Compartment
gNMDA
gAMPA
INaK
gK
gCa
gL (K,Na,Ca)
ICa-ATP
gA
gtonic
gelec
gCAN
CDendrite
gNaP
INaK
gK
gK(Ca)
gL(K,Na,Ca)
ICa-ATP
gH
gNaF
CSoma
gCa
EK,Na,Ca
ECa ECa
ECAN
ESyn-Ex
ESyn-Ex
EK
EK
EK EK
EH
EAv. Neighbor
ESyn-Ex
ENa
ENa
EK,Na,Ca
gC
Methods: Evolving SolutionsStep 2: Sit back, relax, let the computer do the work
Methods: Evolving SolutionsStep 1: Teach the Fitness Function What is Important
Score: 100
Score: -5 (Kill)
Score: 40
Score: 50
Score: -30 (Kill)
Fitness Function
What Is a Fitness Function Anyway?
A weighted sum of fitness measures
Inside the Black Box
Traces
ScoresDetermine Kill Conditions
Spike/Burst Analyzer
TraceStatistics
Surviving Traces Stable, Bounded Linear Regression
Fitness Parameters
Advantages of Evolutionary Algorithm
• Efficiently Handles Large Parameter Spaces
• Yields Many Good Regions
• Approximates Their Boundaries
Preliminary Results
• Problem: Fit the current model to 4 experiment traces
• Number of Parameters: 110
Ideal Curve Some Evolved Solutions
Time
Voltage
Control Control Pulse
Riluzole ApaminPulse
Time
Voltage
Control Control Pulse
Riluzole ApaminPulse
Time
Voltage
Control Control Pulse
Riluzole ApaminPulse
Time
Voltage
Control Control Pulse
Riluzole ApaminPulse
Time
Voltage
Control Control Pulse
Riluzole ApaminPulse
V(Somatic)
Typical Burst
Control Riluzole
V(Somatic)
Typical Burst
Ca2+ From Stores
ICAN
Ca2+(Dend)
V (Dend)
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
Future Directions
• Add More Experiments
• Adjust Parameter Ranges
• Make / Test Predictions
Acknowledgements
AcademicDr. Christopher Del Negro (C. W&M)
Dr. Pete Roper (U. Utah)
FinancialNSF Grant IOB-0616099
Suzzane Matthews Faculty Research Award
References
1. 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).
2. 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.