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BME 6938 Neurodynamics

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BME 6938 Neurodynamics Instructor: Dr Sachin S Talathi Phase of limit cycle Isochrons-Define phase off limit cycle Phase of a non periodic point is taken to be the ... – PowerPoint PPT presentation

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Title: BME 6938 Neurodynamics


1
BME 6938Neurodynamics
  • Instructor Dr Sachin S Talathi

2
Phase of limit cycle
3
Isochrons-Define phase off limit cycle
Phase of a non periodic point is taken to be the
phase of its periodic proxy
4
Phase Response Curve
5
Weak Coupling- Infinitesimal PRC
Linear Response Function or iPRC
6
Practical Approach to Calculating iPRC
  • Malkins Theorem
  • Let the system have exponentially
    stable limit cycle with period T and receive
    infinitesimal periodic perturbation
  • Then its phase is described by equation
  • Where with
  • (XPPAUTO exploits this theorem to estimate
    iPRC)

7
Brain rhythms (EEG) correlate with behavioral
states
  • Delta (0.5-4 Hz)
  • Dominant rhythm in infants and stage 3 and 4 of
    sleep
  • Theta (4-8 Hz)
  • Normal activity in young children and represents
    drowsiness in adults
  • Alpha (8-12 Hz)
  • It is observed in relaxed state
  • Beta (12-30 Hz)
  • Observed in an anxious state
  • Gamma (gt30 Hz)
  • Observed in attention state and is thought to be
    the learning rhythm

Excited
Relaxed
Drowsy
Deep Sleep
8
Neural synchrony Mechanism for generation of
brain rhythms
Synchronous activity is large-detectable at the
electrodes on the scalp (source of EEG)
9
Neural Synchrony and the Binding Problem
  • No central location in the brain where all
    information related to a task is centralized
  • How are the parallel computations in spatially
    segregated regions in the brain coordinated?
  • How are signals selected and routed from sensory
    structures to executive structures without
    confounding?
  • How information about relatedness of content is
    encoded?
  • Related to the problem of consciousness
  • Potential Answer Neural synchrony

10
How does synchrony arise?
  • Two key mechanisms.
  • Related to the intrinsic properties of neurons in
    terms their preference for input frequencies
    (resonance)
  • Related to the pattern of connectivity between
    neurons and the dynamic properties of intervening
    synapses (network and network interactions)

Note These are not mutually exclusive
explanations
11
Weakly coupled oscillators
Substitute
Note
where
12
Two weakly coupled oscillators
represents deviation from the identical period
for each oscillator
13
Analyze Simple network-Weak Coupled Oscillators
Phase Locked Solution
Stability Criteria
14
Results from Weak Coupling Theory Analysis
15
Spike Time Response Curves
Coupling parameters
perturbation time
Intrinsic period
16
Analysis of the network using STRCs
Phase Locked Solution
Stability Criterion
17
Results from analysis using STRCs
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