laboratory 13 : neurophysiology dr. craelius autonomic (involuntary) and somatic (voluntary) nervous...
TRANSCRIPT
Laboratory 13 : NeurophysiologyDr. Craelius
• Autonomic (Involuntary) and Somatic (Voluntary) Nervous Systems)
• Methodologies for measuring and controlling both.
• Relevant to Neuroprostheses. I.e. how can we “decode” what the brain is telling our organs and muscles, so that when the information channels are blocked, we can replace them?
Action Potentialof a Neuron
The output is a pulse train: Its frequency contains the information.In general the higher the frequency, the greater the informationcontent. Neurons in the MI cortex are specialized for such operationsAs kinematics or dynamics.
Neurophysiology Basics
• Muscles and neurons are excitable, and carry information through their pulse rate.
• I = log2(fm*t +1)• Action Potential - a reversal in relative
polarity or change in electrical potential of a cell Neurotransmitters- chemical messengers
• Central neurons are specialized for function.
ANS Background
• Spectral analysis of HRV reveals 2 limbs of the ANS.
• ULF (diurnal) HRV is predictive of cardiac performance.
• HRV signatures using Cepstral Analysis (US patent 6,390,986).
• HRV manipulation can improve asthma (Vaschillo, Lehrer et al, 2004).
• Portable digital recorders of ECG facilitate analysis.
Influences: Autonomic + Mechanical+ Metabolic + Environmental
(HP)
Complexity
Frequency
Time Domain
Heart Rate (HR)
Heart Period (HP)
(HP)
Beat-to-beat (RR)
Pacemaker: Sino-atrial node
HRV Analysis Pyramid
Inverse Problem
Autonomic Nervous System & Heart Rate Variability
• Exerts effects on every organ, but the heart is the most “visible” organ we can examine.
• Para slows it, Sympa speeds it.
Pacemaker
Para
Sympa
Beatmaker
What modulates HR?
• SNS has a periodicity of ~ 20 seconds, and possibly others.
• ANS has a periodicity = breathing rate, and possibly others.
• Thoracic motions alone can modulate, and vagal nerve drive of respiration can contribute.
• Thermoregulation, daily activities can modulate long periodicities.
Can HRV identify disease or specific individuals?
• Age-related normal ranges of overall HRV = SDNN, are known and are predictive of survival after MI.
• A brief record of HR can be a signature of an individual using HR vector cepstral methods *.
*Curcie, D, Craelius W: Recognition of Individual Heart Rate Patterns with Cepstral Vectors, Biological Cybernetics, 77/2:103-109, 1997
Analyzing HRV
• Collect sufficiently long , ‘clean’, epoch, I.e. need at least a few cycles of the rhythm- so for LF , get > 3 X 20 seconds.
• First examine tachogram, edit artifacts.
• Do time domain stats, ie, S.D.
• Do spectral analysis if you have sufficient data, ie. Need several cycles to detect.
Cardiovascular Resonance
• Vaschillo & Lehrer et. Al.
• Get ANS into resonance by biofeedback.
• Deep breathing at resonant rate is key.
• Resonance can influence performance.
Ratios
• LF/HF : estimates sympathetic to parasympathetic activities
• LF-tilt/HF-supine: a more specific estimate
Normal Range Variable Units Normal Values
(mean +- S.D.)SDNN ms 141 39SDANN ms 127 35RMSSD ms 27 12Triangular index ms 37 15Total Power ms2 3466 1018LF ms2 1170 416HF ms2 975 203LF nu 54 4HF nu 29 3LF/HF 1.5- 2.0
HRV Oscillations
Frequency Component
Range
(Hz)
Likely Origin
HF 0.15 - 0.40 Parasympathetic outflow
LF 0.05 - 0.15 Mostly Sympathetic in standing position
VLF 0.003 - 0.05
Possibly thermoregulatory or plasma rennin activity
ULF <0.003 Wide range of determinants like posture, behavioral variables
CollectECG- Lead
II
Detect fiducial R
points
Instantaneous Heart Rate
Stationary?
Free of Artifact?
Time Domain
Measures
Frequency Domain
Power in Bands
Modelling HR Vector
Estimate autonomic activities
Classify individuals
Overall HRV
(Pulse record in our lab)
Processing Pulse Record
Unfiltered Pulses High Pass Filtered @ 0.2 HzBaseline correction: If you filter too much, you differentiate.
Somatic Nervous System:Signals
• Originate in a Motor Neuron– Activated by conscious thought or afferent
input (i.e. reflex)
• Travel through the nervous system to the target muscle(s) via, depolarization (action potential) and neurotransmitters : Signal Degradation
Controller
Proprioception
Vision
+
+_
External Load
Volition
Motion Control Volition + Load -(sensation) = error
Bionic Approaches to Restoring Mobility
• Mobility can be restored by several neuroprosthetic approaches *.
Muscles
Computer
Computer
Muscles
Robot
Brain
BCIAction
Action
Action
Action
BMI
HybridBMI
PMI
Figure 3
1.* Craelius,W.: "The Bionic Man: Restoring Mobility", Science, Vol 295, 1018-1021, 2002.
Brain-Machine/Computer Interfaces
• Monkeys in Brooklyn moving arms in North Carolina, fast learning (Wessberg et al.)
• Completely paralyzed persons moving cursors and robotic arms (Kennedy, PR, et el.)
• Paraplegic with implanted SC chip using switches on walker (Rabischong)
Record Inside the brain ?
• Need > 1000 Implanted electrodes
• Hence need wireless control from external controller
• Electrode biocompatibility and migration
• But decoding volition from motoneurons is surprisingly easy: simple cumulative summation of firing rates (linear)
Volitional Degradation/Restoration
• G = H · V ( G and V are column vectors)
• G is the measured response
• H is the degradation through the system
• V is the volition
• To Retrieve volition:
GHV
1
VolitionBrainTask
Muscular
Output
Motors
Register
ContextEnvironment
Controller
Filter
1/H
State
Degradation
H
State Vector
G
V
V
Linear filter is simplestAnd best decoder
How to measure performance of decoding?
• How accurate is positioning of arm?
• Euclidean distance:
• Speed versus accuracy
SAT test
MT = a + b log2(2A/W) where• MT = average movement time = Time/# of hits • A = amplitude (distance) of movement between
targets• W = width of the target • a = intercept• b = slope• log2(2A/W) == difficulty level
Protocol
1. Pulse recording 5 min --- file
2. SAT test 5 min ---- file
3. Deep Breathing w/pulse recording 5 min--- file.
4. SAT test 5 min ---- file
5. Pulse recording 5 min --- file
6. SAT test 5 min ---- file
Analysis
1. Prepare pulse files, with HP filtering if necessary.
2. Use RR interval program to get intervals- optimize for minimal artifacts.
3. Put RR & SAT data in Excel- analyze & graph.
4. If time, further analyze RR data with Log-a-Rhythm.